Patent ID: 12203994

DETAILED DESCRIPTION

In general the terms and phrases used herein have their art-recognized meaning, which can be found by reference to standard texts, journal references and contexts known to those skilled in the art. The following definitions are provided to clarify their specific use in the context of the invention.

The terms “electrochemical energy device”, “electrochemical energy unit”, and “electrochemical energy systems” refer to a device, unit, or system, respectively, capable of converting chemical energy into electrical energy, or electrical energy into chemical energy. Electrochemical energy devices include, but are not limited to, primary batteries, secondary batteries, electrolysis systems, fuels cells, electrochemical capacitors, ultracapacitors, flow batteries, part solid part fluid electrochemical cells, metal-air batteries such as lithium air batteries and zinc-air batteries, and metal-aqueous batteries such as lithium-water batteries and semi-solid batteries. An electrochemical unit or system is a unit or system that includes at least one electrochemical device, and may include a plurality of electrochemical devices, optionally connected in series, parallel, or a combination thereof. Electrochemical devices, units, and systems may be electrochemical devices, units, and systems for providing electrical energy to a vehicle.

The terms “electrical energy device”, “electrical energy unit”, and “electrical energy systems” refer to a device, unit, or system, respectively, capable of harnessing energy by converting it to electrical energy, and/or storing electrical energy. Electrical energy devices include, but are not limited to, capacitors and photovoltaic devices. An electrical unit or system is a unit or system that includes at least one electrical device, and may include a plurality of electrical devices, optionally connected in series, parallel, or a combination thereof. Electrical devices, units, and systems may be electrical devices, units, and systems for providing electrical energy to a vehicle.

The terms “electrical/electrochemical energy device”, “electrical/electrochemical energy unit”, and “electrical/electrochemical energy systems” refer to a device, unit, or system, respectively, which includes an electrical energy device and/or an electrochemical energy device.

The terms “energy device”, “energy unit”, and “energy system” refers to an electrical/electrochemical energy device, an electrical/electrochemical energy unit, and an electrical/electrochemical energy system, respectively.

The term “change in electromagnetic field” refers to a change in a form of radiant energy that propagates through space via electromagnetic waves and/or photons.

The term “magnetically sensitive” refers to being sensitive to magnetic fields or changes, as a function of time, of magnetic fields. Examples of magnetically sensitive devices include, but are not limited to, an electromagnetic coil, a electromagnetic coil including a ferrite core, a copper coil, a closed loop antenna, a magnetic induction device, a toriodal inductor, a magnetometer, a Hall-effect probe, a solenoid, and a high electrical-conductivity spiral.

The term “electromagnetic coil” refers to a two-terminal electrical component capable of producing an electric current when subjected to a magnetic field which changes as a function of time. Electromagnetic coil may include at least one electrical conductor such as a wire in the shape of a coil, a planar coil, spiral or helix, Electromagnetic coil include an electrically conductive wire shaped to form a loop or a portion of a loop between the two terminals, and an electrically conductive wire shaped to form multiple loops between the two terminals.

The term “signal” refers to a quantity that conveys information about the behavior or attributes of a phenomenon. “Signal” includes a quantity that may provide information about the status of a physical system or convey a message between observers.

The term “system response” refers to the response of system to an applied signal, where the signal may be, for example, electrical, magnetic, or electromagnetic. The term “system response measurement” refers to applying the signal that induces the signal response, and measuring the system response.

The terms “passive detection” and “passively detecting” refer to the performance of measurements that are not system response measurements.

The term “state of health” refers to a figure of merit of the condition of an electrical/electrochemical device or a group of electrical/electrochemical devices for storing energy, compared to its ideal condition. State of health may be determined based on parameter including, but not limited to, resistance, impedance, conductance, capacity, voltage, self-discharge, ability to accept a charge, number of charge-discharge cycles, or a combination thereof.

The term “state of charge” refers to the amount of energy, which may be converted into electrical energy, held by an electrical/electrochemical device or a group of electrical/electrochemical devices for storing energy, compared to its maximum value.

The term “electrical short” refers to a value of electrical resistance that is below a threshold value.

The term “energy device characteristic” refers to a condition associated in an energy device, unit, or system that is indicative of a performance thereof. In an embodiment, the characteristic refers to the state of health of the energy device, unit, or system. In embodiment, the characteristic refers to the state of charge of the energy device, unit, or system. In embodiment, the characteristic refers to an abnormality of the energy device, unit, or system. In embodiment, the characteristic refers to a hard short associated with the energy device, unit, or system, such as between an anode current collector and a cathode current collector, or between an anode active material and a cathode active material, or between an anode current collector and a cathode active material or between an anode active material and a cathode current collector. In embodiment, the characteristic refers to a soft short associated with the energy device, unit, or system, such as between an anode current collector and a cathode current collector, or between an anode active material and a cathode active material, or between an anode current collector and a cathode active material or between an anode active material and a cathode current collector.

The term “abnormality” refers to a condition that develops in an energy device, unit, or system, that is indicative of non-routine, non-optimal, dangerous or otherwise unexpected or unwanted behavior in the energy device, unit, or system. In an embodiment, an abnormality refers to an electrical cutoff in an energy device, unit or system. In an embodiment, an abnormality refers to an electrical short in an energy device, unit or system. In an embodiment, a short circuit can develop between various components of an electrochemical energy device, such as between an anode current collector and a cathode current collector, or between an anode active material and a cathode active material, or between an anode current collector and a cathode active material or between an anode active material and a cathode current collector. In an embodiment, an abnormality refers to a state of health or change in state of health of an energy device, unit, or system indicative a decrease in operational performance, such as an increase in internal resistance, a capacity loss or an inability to undergo charge cycling.

The term “hard short” refers to a short, either external to the energy device, unit, or system, that has a resistance at, or substantially equal to, zero ohms, or otherwise below a predetermined threshold. For example, a hard short may include a solid connection between electrodes within the energy device that causes extremely high current flow and complete discharge resulting in permanent damage to the energy device.

The term “soft short” refers to a short, either external to the energy device, unit, or system that has a resistance non-equal to zero ohms, or otherwise above a predetermined hard-type threshold but below a soft-type threshold (because if above the soft-type threshold, the internal resistance may be substantially the same as the optimal internal resistance). For example, a soft short may include a small localized contact between electrodes within the energy device. Soft shorts may be self-correcting due to melting of the small regions in contact caused by the high current flow which in turn interrupts the current path as in a fuse. The existence of a soft short could possibly be indicated by an increase in the self-discharge of the energy device cell or by a cell with a higher self-discharge than the rest of the population. Soft shorts may be defined by a signal received that is below than a soft short threshold, but above than a hard short threshold.

Estimating internal parameters of an energy device may provide significant information about the state of charge and state of health of the measured battery. This information may then be used to adjust the cycling rate of the energy device, including enabling fast charging of the energy device and setting of voltage limit to avoid overcharge or over-discharge of the energy device, which not only damage the life of the energy device but also can cause serious safety problems.

Internal resistance of an energy device is an important internal parameter that directly affects the performance of the energy device. Further, state of health (and to some extent state of charge) of an energy device depends on the internal resistance of the energy device.

Estimating state of charge and state of health provides many benefits including faster charging and longer battery life. Conventional coulomb counting and OCV methods are very time consuming and very limited. Electrochemcial Impedance Spectroscopy (EIS) measurement, OCV delay over time, and entropy methods are some of the advanced methods to accurately estimate state of charge and state of health. However, these methods require costly hardware and may be difficult to implement in practice.

Embodiments of the systems and methods discussed herein may enable estimation of the internal resistance of the cell overcoming the disadvantages of other state of health and/or state of charge measurement systems. The methods and systems utilize hardware, exterior to the energy device, system, or unit, to measure a receive signal representing change in electromagnetic field produced by the energy device, either passively or actively, and analyze such signal as a function of the internal resistance, standard deviation, mean, variance or other statistical measure of the received signal. As an example, a higher than normal internal resistance reduces the received signal strength and/or its duration. Thus the suggested embodiments herein may be used to estimate the internal resistance of an energy device and thus can be used to estimate the state of health and/or state of charge of the energy device. An example is that an energy device with a potential soft short may show abnormally higher signal strength, due to lower internal resistance, even locally. On the other hand, an aged energy device may show abnormally lower signal strength, due to higher impedance of the energy device.

In addition to the large changes of internal resistance based on the state of health, the internal resistance also changes, although at a smaller scale, with state of charge of the energy device. Thus it is possible to not even estimate state of health based on large changes of internal resistance understood by large deviations from expected received signal, but also based on smaller changes in internal resistance understood by smaller deviations from expected value of received signal.

The “multi-scale” nature of dependence of internal resistance on state of health and state of charge and the relationship between the resistance of the energy device and the received signal analyzed in the systems and methods herein enables estimation of state of health and/or state of charge of the battery.

In addition to the internal resistance, the received signal may also depend directly on the amount of energy in the energy device, which is directly proportional to the state of charge of the energy device. Thus a stronger received signal of a specific energy device may demonstrate higher state of charge of the energy device.

In embodiments, the systems and methods herein may analyze a received signal based on the received signal's instantaneous quantity or parameter, such as maximum power, maximum voltage square, maximum voltage, maximum change in voltage, maximum current, maximum current square, maximum change in current, full-width voltage at half maximum and current at half maximum, or other instantaneous quantity or parameter at a given time. Furthermore, in embodiments, the systems and methods herein may analyze a received signal based on the received signal's integrated quantity or parameter over a period of time, such as “total absolute energy” or “total absolute coulomb” measured accumulatively over a period of time.

Embodiments of the systems and methods discussed herein may estimate the state of charge and state of health of the energy device very rapidly without the need to cycle the battery, thereby overcoming a significant disadvantage of other measurement methods. The systems and methods herein may create at least one arbitrary controlled short external to the energy device cell with a determined resistance, and then measuring the electromagnetic response by a detector, such as an arbitrary coil, measured at least at one known distance. The strength of the induced current in the coil may be a function of the state of charge and state of health of the energy device, in addition to its chemistry and format. The higher the state of charge or state of the health the stronger the measured signal. Thus it is possible, using embodiments of the systems and methods discussed herein, to distinguish between energy devices with different state of charge and state of health for any given energy device chemistry, size and format. The strength of the said induced current in the coil may also be a function of the created short resistance and the distance between the sensor and the energy device. The higher the resistance or further the distance the weaker the measured signal.

In at least one embodiment of an application of the estimation of state of charge and stated of health of energy device, discussed in association with at least some embodiments of the systems and methods discussed herein, fast charging of energy devices is implemented. When recharging a healthy energy device, a stronger received signal may indicate that the energy device can be charged faster than the time that the received signal is weaker. In certain embodiments, this may be due to the dependence of the received signal to the total resistance of the short, which not only includes the known outside resistance between the two poles of the energy device, but also the internal resistance of the energy device. Further, it is known that for some time, typically minutes, after the stop of the charge or discharge of the energy device there are still electrochemical reactions in the energy device and thus it takes time for the voltage to reach the actual the open circuit voltage. Thus, the embodiments discussed herein may measure the received signal at different time periods after the charge or discharge is stopped identifying different received signal values, which can be an indication of the state of health or state of charge of the energy device.

Embodiments of the systems and methods discussed herein provide significant advantages over other energy device management methods, including that, for a group of energy devices, the received signal is mostly governed by the weakest energy device, which is in accordance with the performance of the group, as a group of energy devices is mostly governed by the weakest energy device cell. In a series connection the weakest energy device cell has the highest impedance so the total impedance of the group goes up and thus the received signal gets weak. In a parallel connection the increase in the impedance due to the weak energy device cell is less significant than in the series connection, However, in this case the voltage drop of the weak energy cell due to the resistance of the weak energy cell and also the internal current between the cells is due to tendency of the parallel connection to keep the voltage of all cells the same during the designed external short results in the signal being weaker than normal, again indicating the presence of a cell with not optimal state of health.

Embodiments of the systems and methods herein provide another measurement, namely a change in electromagnetic field caused by the energy device, system, or unit, than a voltage, current, or temperature measurement based energy device management unit. For example, those energy device management units that are thermal based are disadvantaged because they often lack ability to detect internal temperature of the energy device without expensive equipment. Therefore, surface temperature of the energy device may register at 25 degrees Celsius, whereas it is possible that the internal temperature at an internal short is upwards of 800 degrees Celsius. The inability to accurately measure temperature within the energy device may not allow enough time to predict failure long before self-heating begins, or at least for the failing energy device to be physically or electronically removed from use in order to prevent the thermal runaway or its propagation to neighboring energy devices.

Voltage monitoring systems, such as those used in the 787 airplane, which was subject to a failed energy device that caught on fire, cannot monitor potential failures with the speed that embodiments of the present systems and methods are able to. Systems that monitor voltage over a period of time to determine failing energy devices may lack ability to identify a failing energy device in an instance. For example, in the 2013 fire on a 787 Airplane, data collected by the flight data recorder indicated that a potential failure possibly may have been detected almost 10 minutes prior to the start of a thermal runway that led to the failure. However, the voltage monitor was unable to detect the failure signals.

Again, the present systems and methods provide significant advantages because they not only estimates characteristics including, but not limited to, state of charge and state of health, but may also detect any short, small or large, as soon as it happens. Early detection of small shorts is of particular importance especially for a group of batteries, as the voltage drop, resistance drop, temperature rise or current leak may be too small for conventional battery monitoring methods to detect. The present systems and methods detects even these shorts, sometimes called soft shorts, in advance of their development into larger, less resistance shorts. This gives the device management unit the opportunity to predict a large short in advance and prevent thermal runaways. Further, small shorts put additional loads on connected energy devices that can significantly shorten the life of the energy devices. As an example, the said soft shorts can be due to small dendrites reaching the cathode from the anode side.

FIG.1depicts a system100for monitoring characteristics of an energy device102, in embodiments. System100may include a short generator104and a characteristic monitor106.

Energy device102may include a positive terminal108and a negative terminal110, and may have an energy device characteristic112associated therewith. Energy device102may represent an energy device, energy unit, energy system, electrical/electrochemical energy device, electrical energy device, electrical energy unit, electrical energy system, electrochemical energy device, electrochemical energy unit, electrochemical energy system or any other system, device, or unit capable of producing and/or storing energy. Energy device characteristic112may represent state of health, state of charge, a short, a soft short, a hard short, abnormality, or any other characteristic associated with energy device102.

Short generator104may generate an external short105between positive terminal108and negative terminal110across a known resistance107. Known resistance107may be a fixed resistance, or may be a variable resistance without departing from the scope hereof. Short generator104may include a switch114for activating the external short105. In embodiments, switch114may be controlled via a controller116. Short generator104may further include a sensor118for sensing change in electromagnetic field120generated by external short105.

Controller116may include a processor and memory storing transitory and/or non-transitory computer readable instructions (such as software, hardware, firmware, or a combination thereof) that when executed by the processor of controller116implement the following functionality. Controller116may generate a switch control signal122for controlling operation of switch114to cause an instantaneous short within short105. In embodiments, controller116may include a communications interface for receiving a short generation signal124, in which controller116generates switch control signal122in response to receipt of short generation signal124. The communications interface may be based on a wired or wireless communication protocol including Ethernet, lightning cable, coaxial cable, hardwired cable, WiFi, USART, RFID, Bluetooth, Bluetooth Low Energy (BLE), Cellular, 2G, 3G, 4G, 5G, infrared, or any other communication protocol.

Sensor118may include an electromagnetic coil, such as an electrical conductor such as a wire in the shape of a coil, spiral or helix, for sensing change in electromagnetic field120. It should be noted that in sensors118that are planar coils it is important to mention that the strength of the received signal depends on the orientation between the change of the field and the coil, and more than one planar coil may be utilized, for example with coils being at an angle, such as perpendicular to each other. Sensor118may be any of the sensors as discussed in U.S. patent application Ser. No. 14/211,381, entitled “Systems and Methods for Detecting Abnormalities in Electrical and Electrochemical Energy Units,” and which is incorporated herein in its entirety. It should be appreciated that, although sensor118is illustrated as wireless, it may be a wired sensor for sensing electrical short information as opposed to change in electromagnetic field120without departing from the scope hereof. Sensor118may be at a known, predetermined distance126from electrical short105. Although one sensor118is illustrated, it should be appreciated that any number of sensors could be utilized without departing from the scope hereof.

Characteristic monitor106may be in communication with sensor118for receiving a received signal128representing the change in electromagnetic field120. It should be appreciated that the received signal128may be stored within controller116prior to transmission, from either sensor118or controller116, to characteristic monitor106as received signal128. Additional details of characteristic monitor106are discussed in further detail below.

FIGS.2-7depict additional embodiments of systems for monitoring characteristics of an energy device. Specific instances of an item may be referred to by use of a numeral in parentheses (e.g., energy device102(1)) while numerals without parentheses refer to any such item (e.g., energy device102).

FIG.2depicts a system200for monitoring characteristics of an energy device102, in embodiments. System200is similar to system100except that sensor218is located external of the short generator204, for example, within characteristic monitor206; whereas sensor118is located within short generator104.

Energy device102shown in system200is the same as energy device102shown in system100, discussed above.

Short generator204is similar to short generator104and thus may generate an external short105between positive terminal108and negative terminal110across a known resistance107. Short generator204may include switch114for activating the external short105, as discussed above. In embodiments, switch114may be controlled via a controller116as discussed above.

Sensor218may include any of the above discussed features of sensor118. Sensor218may be at a known, predetermined distance226from electrical short105. Although one sensor218is illustrated, it should be appreciated that any number of sensors could be utilized without departing from the scope hereof.

Characteristic monitor206may be in communication with sensor218for receiving a received signal228representing the change in electromagnetic field120. Additional details of characteristic monitor206are discussed in further detail below.

FIG.3depicts a system300for monitoring characteristics of an energy unit302having a plurality of energy devices102(1),102(2), in embodiments. System300is similar to system100except that characteristic monitor306, which is similar to characteristic monitor106, receives signals from a plurality of sensors118associated with each of the plurality of energy devices102(1),102(2) within energy unit302. It should be appreciated that, although shown within energy unit302, characteristic monitor306may be located external to energy unit302. System300provides the advantage that a single characteristic monitor306may monitor a plurality of sensors118associated with each energy device102to provide individual monitoring of each energy device102within an energy unit302.

FIG.4depicts a system400for monitoring characteristics of an energy unit402having a plurality of energy devices102(1),102(2), and short generators204(1),204(2), in embodiments. System400is similar to system200except that characteristic monitors406(1),406(2), which are similar to characteristic monitor206, include each an embedded sensors218. It should be appreciated that, although shown having two separate characteristic monitors406(1),406(2), there may be only a single characteristic monitor406without departing from the scope hereof. System400provides the advantage that each characteristic monitor406may be an independent component such that any make, type, configuration of energy units402(and energy devices102) may be monitored without requiring individual sensor and monitor hardware associated with the energy device/unit itself.

FIG.5depicts a system500for monitoring characteristics of an energy unit502having a plurality of energy devices102(1),102(2), and short generators504(1),504(2), in embodiments. System500is similar to system400except that, instead of two characteristic monitors406(1),406(2), each having an embedded sensors218, there is a single characteristic monitor506with an external sensor518. Moreover, each of short generators504are similar to short generators204, except that a single controller516controls each of short generator504(1),504(2). Characteristic monitor506is similar to characteristic monitor106and includes any of the features discussed above with respect to characteristic monitor106. Sensor518is similar to sensor118and includes any of the features discussed above with respect to sensor118. Sensor518may be at a known, predetermined distance from each of external shorts105(1) and105(2). System500provides the advantage that characteristic monitor506may monitor a plurality of energy devices102within a battery bundle (e.g. energy unit502) without requiring additional hardware and respective sensors518and controllers516for each energy device102.

FIG.6depicts a system600for monitoring characteristics of an energy unit602having a plurality of energy devices102(1),102(2), and short generators504(1),504(2), in embodiments. System600is similar to system500except characteristic monitor606is located external to energy unit602whereas characteristic monitor506was located internal to energy unit502. System600provides the advantage that characteristic monitor606may be a separate device from an energy unit602which may be a bundle of batteries, for example. Therefore, received signal628, which is similar to received signal128discussed above, may be transmitted, via wired or wireless communication, to characteristic monitor606for further processing.

FIG.7depicts a system700for monitoring characteristics of an energy unit702having a plurality of energy devices102(1),102(2), and short generators504(1),504(2), in embodiments. System700is similar to system600except both characteristic monitor706and sensor718are located external to energy unit702whereas only characteristic monitor606was located external to energy unit602in system600. Sensor718is similar to sensor218discussed above. System700provides at least similar advantages as both systems600and400, discussed above.

WithinFIGS.2-7, two energy devices102are depicted coupled in series. However, it should be appreciated that there may be any number of energy units coupled in series, or in parallel, without departing from the scope hereof. Moreover, it should be noted that any one of the energy devices, or units discussed above may include a housing with various mounting structures for mounting the sensor. For example, if the sensor is located internally to an energy unit, the housing may have an internal mounting structure such that the sensor always maintains a known distance to the external short. Alternatively, if the sensor is externally located, such as being internal to a characteristic monitor that is removably attached to the energy unit, then the energy unit may have a mounting structure located on the outside of the housing such that the characteristic monitor may be aligned to maintain the sensor at a given distance from the external short on the energy devices.

FIG.8depicts a characteristic monitor800, in exemplary detail, in embodiments. Characteristic monitor800illustrates additional exemplary detail for any of characteristic monitors106,206,306,406,506,606, and706discussed above with reference toFIGS.1-7. Characteristic monitor800may include a processor802in communication with a communications interface804and memory806.

Processor802operates to execute instructions stored within memory806to implement the functionality discussed herein associated with characteristic monitor800. In embodiments, processor802may include an on- or off-board Analog to Digital Converter (ADC) having sampling speeds in the range of 0.01-100 million samples per second (MSPS). In embodiments, the sampling speed is selected such that approximately 2 samples per peak of the received signal are generated. These sampling speeds may provide increased sensor sampling such that accurate signal parameters830may be obtained.

Communications interface804may be a wired or wireless communications protocol based device. For example, communications interface804may couple characteristic monitor800to a short generator (e.g. any of short generator104,204,504) and any one or more of the components associated therewith (e.g. switch114; controller116,516; and sensor118,218,518,718). Communications interface804may operate based on any one or more of the communications protocols chosen from the group of, but not limited to: Ethernet, lightning cable, coaxial cable, hardwired cable, USART, WiFi, RFID, Bluetooth, Bluetooth Low Energy (BLE), Cellular, 2G, 3G, 4G, 5G, infrared, or any other communication protocol. In embodiments, communications interface804operates to modulate a DC signal on a DC data line. For example, communications interface804may be used to transmit a configuration output824, discussed below, by modulating a DC line, that each energy unit is coupled to in order to transfer the energy therein, with a data signal instead of a separate wireless or wired signal.

In embodiments, communications interface804may operate to transmit or receive data from other configuration monitors or the cloud. For example, the present systems and methods discussed herein may be connected to systems of other energy devices, for example in a cloud setup, providing a benefit of an “Internet of Battery Things”. An online library may thus be created and used in addition to local lookup tables and energy device profiles discussed throughout this disclosure.

Memory806may include any one or more of received signal810, signal analyzer812, lookup table814, state of charge analyzer816, state of health analyzer820, device operation manager822, and configuration output824.

Received signal810may be generated by a sensor, such as sensors118,218,518,718discussed above. In embodiments, characteristic monitor800includes an internal sensor818that includes any of the features discussed above with regards to sensors118,218,518,718. In such embodiments, received signal810may come directly from sensor818located in characteristic monitor800. In other embodiments, characteristic monitor800receives received signal810via communications interface804interacting with an external sensor (e.g. any of sensors118,518, and/or an external controller (e.g. any one of controllers116,516). Received signal810may represent the change in electromagnetic field generated by an external short (e.g. external short105) generated by a short generator (e.g. short generator104,204,504).

Received signal810may be actively or passively generated. In embodiments where received signal810is actively generated, the external short (e.g. external short105) may be generated in response to characteristic monitor800outputting, via communications interface804, short generation output826. Short generation output826is an example of short generation signal124, discussed above with reference toFIGS.1-7, and may indicate when to generate the external short by the short generator. In embodiments where received signal810is passively generated, a short may be detected without any affirmative generation of the detected short. For example, a passive received signal810may be detected when the sensor detects change in an electromagnetic field generated by an internal short within the energy device. It should be appreciated that any received signal discussed herein (e.g. received signals128,628) may be either passive, active, or both.

Signal analyzer812may include transitory and/or non-transitory computer readable instructions (such as software, hardware, firmware, or a combination thereof) that, when executed by processor802, operate to analyze the received signal810. Signal analyzer812may include system configuration information828that is utilized by signal analyzer812to properly calculate signal parameters830of the received signal810. For example, system configuration information828may include knowledge of the sensor (e.g.118,218,518,718,818) used to acquire received signal810, the known, predetermined resistance (e.g. resistance107) of the external short (e.g. external short105), the known distance between the sensor and the short (e.g. distance126,226), etc. In embodiments, signal parameter830may include one or more instantaneous parameters chosen from the group of parameters including: maximum power, maximum voltage square, maximum voltage, maximum change in voltage, maximum current, maximum current square, maximum change in current, full-width voltage at half maximum and current at half maximum. or other instantaneous quantity or parameter at a given time between 1 nanosecond and 10 microseconds from initial short generation, and preferably between 10 nanoseconds and 1 microsecond from initial short generation.

In embodiments, signal parameter830may include one or more integrated parameter chosen from the group of parameters including: total absolute energy and total absolute coulomb measured accumulatively over a period of time. In embodiments, signal parameter830may be based on the following equation 1:
S=f(Q,V,1/r,1/R,1/D·T)  (Eq. 1)
where S is the Strength of the received signal, D is a distance between the battery or the nearest point of the external short and the sensor, R is a known external resistance selected based on the application and battery that can be in series or parallel to the battery and may vary, r is internal resistance of the energy device to the generated short, Q is a stored coulomb in the energy device, and V is a voltage of the energy device. T is temperature.

For a given D=D0, as the external resistance (e.g. resistance105) and internal resistances are in series, by using a high external resistance, R, relative to internal r, (R>>r) the effect of Q will be dominant thus the signal strength can be used to estimate the Q, without any significant disturbance from r; that is based on equation 2:
SR>>r,D=D0=f(Q,V)  (Eq. 2)

On the other hand, a small R compared to r, (R<<r), increases the effect of internal resistance, r, on the Signal, S, thus both Q and r are important, resulting in both SOC and SOH affecting the S.

SR≪r,D=D⁢0=f⁡(Q,V,1r)(Eq.3)

Thus by two experiments, one with using a large R and a small R, on an energy device one can estimate both state of charge and then state of health, because state of charge and then state of health can be decoupled with good precision by choosing the right parameters of R.

The relationship between S and the parameters may depend on some fixed attributes of a given type of energy device. Examples of the fixed attributes for an energy device type are the chemistry and size of active materials, geometry of the electrodes and geometry and size of the battery. This means that by comparing the measured S, from the 2 experiments above, with known values of S for given state of charge and state of health of the type of the energy device, one can estimate the state of charge and state of health of the energy device of the interest. Thus, lookup table814may include predetermined information regarding the energy device, unit, or system (e.g. energy device102, energy unit302,402,502,602,702, etc.) required to identify a characteristic thereof using characteristic monitor800. Lookup table814may include any one or more expected device parameters chosen from the group of expected device parameters including: device brand, device manufacture, device model, device voltage, device C-rate, device material composition, expected device internal resistance, device statistical analysis (such as mean, standard deviation, and variance) and device installation information. Each expected device parameters may be associated with a plurality of exemplary distances between sensor and external short (i.e. external short105).

It should be appreciated that the lookup tables, and signal parameters herein may include information regarding another measurement of the energy device such as voltage, current, and/or temperature.

In embodiments, the signal parameter830may include a statistical analysis of a plurality of received signals810over a given period of time. For example, the statistical analysis may include one or more of a mean, standard deviation thereof, variance thereof, and any other statistical analysis of received signal810. In such an embodiment, signal analyzer812(or one or both of state of charge analyzer816and state of health analyzer820) may receive a plurality of received signals810, and then take the mean, standard deviation, and/or variance thereof. The statistical analysis may then be utilized to predict state of charge, state of health, and energy device lifespan, among other energy device characteristics.

FIG.9depicts an exemplary lookup table900, in an embodiment.FIG.10depicts exemplary lookup table generation data1000, in an embodiment.FIG.11depicts exemplary lookup table generation data1100, in another embodiment.FIGS.9and11are best viewed together with the following description. Lookup table900is an example of lookup table814ofFIG.8. Lookup table shows, for a given energy device type, model, manufacture, etc., peak-to-peak voltages902measured from a plurality of distances904for a plurality of external short resistances906. Distances904are examples of distances126,226, discussed above with reference toFIGS.1-8. External short resistances906are examples of known, predetermined resistance107discussed above with regards toFIGS.1-8. Each value902may be based on an average of the maximum voltage level within the received signal (e.g. received signal810) taken over a plurality of trials. For example, in lookup table generation data, which generated the peak-to-peak voltages902for a 0.35 Ohm short resistance906inFIG.9, four trials were completed and the average maximum was used for the peak-to-peak voltages902inFIG.9.

As shown inFIG.11, lookup table generation data1100may be plotted to generate best fit lines1102-1110. Best fit line1102represents data for a 0.1 Ohm external short. Best fit line1104represents data for a 0.35 Ohm external short. Best fit line1106represents data for a 0.45 Ohm external short. Best fit line1108represents data for a 1 Ohm external short. Best fit line1110represents data for a 1.6 Ohm external short. Within data1100, best fit lines are shown having a format V=mra; where V is the peak-to-peak voltage value, m is a first constant, r is measured value from sensor, and a is an “r-factor” second constant. First and second constants may be required based on the installation configuration. For example if the energy device is located in an enclosure that causes the change in electromagnetic field from the external short to reflect off of the enclosure, the first and second constants may compensate for such reflection to generate an actual voltage value. It should be appreciated that, althoughFIGS.9-11discuss peak-to-peak voltages, similar concepts may be used for instantaneous energy values, current values, or integral values such as total absolute energy and total absolute coulombs without departing from the scope hereof.

Signal analyzer812may further store signal parameter830, captured over a series of measurements on the energy device as an energy device profile832. In embodiments, successive received signals810may be received at a frequency of 2 kHz or less. The number of successive received signals810for a statistical parameter can be, for example, 2 to 10 times to provide enough data points for the statistical analysis. The duration of wait between each of these successive received signals may depend on the battery chemistry and type. As an example, the duration between successive received signals810may be between 1 millisecond and 1 minute.

Energy device profile832may include a history of signal parameters830receive regarding a given energy device, system, or unit. For example, where signal parameters830represent a statistical analysis, as discussed above, energy device profile832may store the history of the statistical parameters for the energy device at a given state of charge per cycle. In other words, energy device profile832may store, for each cycle of the energy device (e.g. for each charge cycle or discharge cycle, or both, of the energy device), what the value of the statistical parameter was at a given state of charge. This may occur at multiple state of charges per cycle. As such, a received signal810may be obtained multiple times throughout a cycle of an energy device, and the signal parameter at those particular times, including signal instantaneous values, integral values, and statistical values, may be stored in association with the particular cycle.

State of charge analyzer816may include transitory and/or non-transitory computer readable instructions (such as software, hardware, firmware, or a combination thereof) that, when executed by processor802, operate to analyze signal parameter830and lookup table814to determine the state of charge of an energy device. State of charge of the energy device may be determined based on an signal parameter830as compared to an expected parameter value for the given short resistance. As an example referring to the values ofFIG.9, if the external short resistance107is 0.35 Ohms, the short distance is 3 cm, and the signal parameter830returns a value that at 1.4245 V, or within a predefined threshold thereof, then it may be determined that the energy device is fully charged. If the signal parameter830indicates a value that is not equal to 1.4245 V, or is outside of a predefined threshold thereof, then a mathematical calculation may be used to determine the charge level of the energy device.

In embodiments, state of charge analyzer816may be based on a signal parameter830that is a statistical parameter. For example, the mean, standard deviation, and/or variance may be determined by signal analyzer812based on a series of received signal810. Particularly, in embodiments the mean may be analyzed to determine state of charge. State of charge analyzer816may then compare the statistical parameter to lookup table814to determine if the measured statistical parameter is within a given threshold from the expected value within the lookup table814. Alternatively, state of charge analyzer816may compare the statistical parameter against a energy device profile832. As such, the energy device profile832may derive an expected value based on one, or a plurality, of previously captured statistical parameters. For example, if the signal parameter830is a statistical parameter based on successive received signals810, on the 100thcycle of the energy device, the expected value within the energy device profile832may be based on a difference in similar statistical parameters (i.e. similar state of charge, etc) derived during the 10thand 50thcycle. As such, the difference between the expected value of the energy device profile832and the statistical parameter-based signal parameter830may indicate state of charge. State of charge analyzer816may take advantage of effect of delay in open circuit voltage stabilization after the current is stopped. It is suggested that the delay in voltage stabilization is due to ions transport from inside the particles to outside the particles within the energy device. This ion transport includes both solid state diffusion and electronic connectivity between the particles and the current collector, and thus can be a measure of health of the energy device. Thus by successive measurements of Signal Strength as discussed herein, and comparing the values of measured “signal strengths” to expected values (e.g within the lookup table814or energy device profile832) the state of charge may be estimated.

State of health analyzer820may include transitory and/or non-transitory computer readable instructions (such as software, hardware, firmware, or a combination thereof) that, when executed by processor802, operate to analyze signal parameter830and lookup table814to determine the state of health of an energy device. State of health of an energy device may indicate a non-optimal internal resistance within the energy device. For example, state of health analyzer820may analyze signal parameter830, at a known state of charge, and compare such signal parameter830to look up table to determine if the internal resistance is optimal. Referring to the values ofFIG.9, for example, assume a fully charged energy device, the external short resistance107is 0.35 Ohms, and the short distance is 3 cm, and the signal parameter830returns a value that at 1.4245 V. This indicates that the internal resistance of the energy device is as expected and thus the energy device has an optimal state of health. However, if the signal parameter830returns a value of 1.524 V, then that means that the internal resistance of the battery is lower than optimal and, for example, caused by an internal short within the energy device. Furthermore, if the signal parameter830returns a value of 1.213 V, then that means that the internal resistance of the battery is higher than optimal and, for example, caused by energy device that has a degraded life-span.

In embodiments, state of health analyzer820may further characterize a type of short. Again taking the assumption, referring toFIG.9values, that the external short resistance107is 0.35 Ohms, and the short distance is 3 cm, and the signal parameter830returns a value that at 1.524 V. This means that there is some level of short internal to the energy device because the total resistance value (i.e. internal resistance of the energy device plus known, predetermined external resistance107) has gone down and thereby the emitted change in electromagnetic field120has a larger value. The difference between the expected total resistance value and the actual total resistance value indicates the type of short. Thus, if the difference is at or below a hard-short type threshold, dependent on the configuration of the energy device (e.g. optimal internal resistance, type, model, manufacture, etc.), then state of health analyzer820may determine a hard short. However, if the difference is above the hard-short type threshold but below the soft-type threshold, then state of health analyzer820may determine a soft short.

In embodiments, state of health analyzer820may be based on a signal parameter830that is a statistical parameter. For example, the mean, standard deviation, and/or variance may be determined by signal analyzer812based on a series of received signal810. Particularly, in embodiments the standard deviation and/or variance may be analyzed to determine state of health. State of health analyzer820may then compare the statistical parameter to lookup table814to determine if the measured statistical parameter is within a given threshold from the expected value within the lookup table814. Alternatively, state of health analyzer820may compare the statistical parameter against an energy device profile832. As such, the energy device profile832may derive an expected value based on one, or a plurality, of previously captured statistical parameters. For example, if the signal parameter830is a statistical parameter based on successive received signals810, on the 100thcycle of the energy device, the expected value within the energy device profile832may be based on a difference in similar statistical parameters (i.e. similar state of charge, etc) derived during the 10thand 50thcycle. As such, the difference between the expected value of the energy device profile832and the statistical parameter-based signal parameter830may indicate state of health. State of health analyzer820may take advantage of effect of delay in open circuit voltage stabilization after the current is stopped. It is suggested that the delay in voltage stabilization is due to ions transport from inside the particles to outside the particles within the energy device. This ion transport includes both solid state diffusion and electronic connectivity between the particles and the current collector, and thus can be a measure of health of the energy device. Thus by successive measurements of Signal Strength as discussed herein, and comparing the values of measured “signal strengths” to expected values (e.g within the lookup table814or energy device profile832) the state of charge may be estimated.

Device operation manager822may include transitory and/or non-transitory computer readable instructions (such as software, hardware, firmware, or a combination thereof) that, when executed by processor802, operate to analyze the findings of one or both of state of charge analyzer816and state of health analyzer820to generate configuration output824.

In embodiments, the charge level identified by state of charge analyzer816may be utilized by device operation manager822to generate configuration output824indicating to enter a fast charging mode for the associated energy device. For example, if the internal resistance, impedance or other characteristic is exceeds expectation, then the configuration output may indicate a fast charge rate. In embodiments, the charge level identified by state of charge analyzer816may be utilized by device operation manager822to generate configuration output824indicating to enter a normal charging mode for the associated energy device, for example when the characteristic is similar to the expected value. In embodiments, the charge level identified by state of charge analyzer816may be utilized by device operation manager822to generate configuration output824indicating to enter a slow charging mode for the associated energy device, for example when the characteristic is not commensurate with the expected value.

In embodiments, the state of health identified by state of health analyzer820may be utilized by device operation manager822to generate configuration output824to alter the connectivity of a given energy device, for example by bypassing, or disconnecting, the given energy device. As an example, if a hard short is identified, configuration output824may be generated controlling a switch that disconnects or bypasses the given energy device such that the given energy device does not impede overall operation of the system using such given energy device. In embodiments, instead of, or additionally to, bypassing and/or disconnecting the given energy device, the configuration output824based on the state of health analyzer820may include a recommended replacement date for the given energy device. For example, if the difference between the expected total resistance value and the actual total resistance value, as discussed above, is not above a critical life-span threshold, then device operation manager822may consult lookup table814to identify when the energy device is expected to fail and thus identify a recommended replacement date.

In embodiments, the state of health and state of charge may be utilized by device operation manager822to generate configuration output824that identifies where a short occurs. For example, if device operation manager822is utilized with a sensor that senses change in electromagnetic field from multiple energy devices, such as shown inFIGS.5-7, device operation manager822may utilize lookup table814to identify the location of the short. Because lookup table814indicates the parameter value at a plurality of distances (for example, distances904inFIG.9), device operation manager822may analyze the signal parameters830using triangulation to identify the specific energy device at which the electrical short occurred. Therefore, this specific energy device may then be bypassed or disconnected to improve the overall efficiency of the energy unit or system.

It should be appreciated that the analysis performed by various aspects fo the characteristic monitor800, including the signal analyzer812, state of charge analyzer816, state of health analyzer820, and device operation manager822may include additional sensed data about the energy device, system, or unit being monitored. For example, one or more of voltage between terminals of the energy device, system, or unit, current between terminals of the energy device, system, or unit, and temperature of the energy device (including internal and/or surface temperature) could be utilized to make a determination about a characteristic. As such, the present embodiments provided another level of safety on top of prior energy device management systems—particularly one that is capable of making a characteristic determination in a much faster manner based on instantaneous, integral, or statistical analysis based signal parameters.

It should be appreciated that one or more of the short generator, sensor, and characteristic monitors discussed above may be implemented in either digital or analog form.

FIG.12depicts a block diagram indicating an analog system1200for monitoring characteristics of an energy device, in embodiments. Analog system1200is an example of system100, discussed above. Analog system1200may include a sensor1218, a signal processing circuitry1212, a logic circuitry1214, and an indicator1226.

Sensor1218is similar to sensor118, discussed above, and may include an electromagnetic coil, such as an electrical conductor such as a wire in the shape of a coil, spiral or helix, capable of sensing change in electromagnetic field from an external short.

Signals generated by sensor1218may be analyzed by signal processing circuitry1212which may include one or more of op-amps, and comparators, and associated circuitry such as resistors, capacitors, inductors, and/or voltage clamp diodes on the positive and negative sides of the sensor for isolating the sensor from signal surges, etc., used to generate a signal for logic circuitry1214. Compared to characterization monitor800ofFIG.8, signal processing circuitry1212may be similar to signal analyzer812in function—namely that signal processing circuitry1212identifies a signal parameter of the signal generated by sensor1218. In embodiments, signal processing circuitry1212may include one or more potentiometers for setting the threshold values utilized within signal processing circuitry1212. These potentiometers may or may not be accessible via a housing of the analog system1200such that the threshold values are changeable during operation of system1200. For example, the threshold values may be desired to be changed based on the specific battery type, make, model, etc. being analyzed. the threshold values may further be changed to reduce false positives detected using system1200. Moreover, the potentiometers may be utilized to set the thresholds at symmetric distances from the half value of the input voltage (Vcc/2). To maintain symmetry between the positive and negative thresholds, they must be set equidistant from the DC bias point using Eq. 2, below:
Vbias−Vlow=Vhigh−Vbias(Eq. 2).

In embodiments, the potentiometer controls only one of the Vhighor Vlowto control the bias point. In embodiments, the system may include an indicator that sets off if the bias is set incorrectly based on the potentiometer settings.

Logic circuitry1214may include one or more of flip-flop logic circuitry, comparators, and associated circuitry such as resistors, capacitors, and/or inductors, etc. Compared to characterization monitor800ofFIG.8, logic circuitry1214may be similar to device operation manager822in function—namely that it analyzes the processed signal from signal processing circuitry1212to identify a configuration output1224(e.g. analogous to configuration output824) for driving indicator1226. Logic circuitry1214may be configured based on the specific energy device being tested. As such, it should be appreciated that logic circuitry1214may implement the functionality as discussed above with respect to one or more of lookup table814, energy device profile832, state of charge analyzer816, and state of health analyzer820.

Indicator1226may be one or more lights, such as an LED, etc, and associated meaning such that the user may understand the output from logic circuitry1214. For example, indicator1226may include three LED lights that respectively emit according to a fully charged, partially charged, low charged, indication from logic circuitry1214. Alternatively, or in addition thereto, indicator1226may indicate a charging speed, such as fast, slow, or normal, without departing from the scope hereof.

FIG.13depicts a block diagram indicating a digital system1300for monitoring characteristics of an energy device, in embodiments. Digital system1300is similar to analog system1200except that one or more of signal processing circuitry1312, logic circuitry1214, and indicators1326(which are respectively similar to signal processing circuitry1212, logic circuitry1214, and indicators1226), are implemented using one or more microprocessors1302.

Sensor1318is similar to sensor118, discussed above, and may include an electromagnetic coil, such as an electrical conductor such as a wire in the shape of a coil, spiral or helix, capable of sensing change in electromagnetic field from an external short.

Signal processing circuitry1312may include an ADC capable of sampling speeds in the range of 0.01-100 MSPS. In embodiments, the sampling speed is selected such that approximately 2 samples per peak of the received signal are generated. These sampling speeds may provide increased sensor sampling such that accurate signal parameters may be obtained. If the sensor1312is located away from a characterization monitor (such as shown inFIGS.1,3,5, and6, discussed above), then the signal processing circuitry1312may be associated with a first microprocessor1302, and the logic circuitry1314and indicators1326may be associated with one or more second microprocessors. Signal processing circuitry1312may implement the functionality of one or more of signal analyzer812and short generation output826, discussed above with reference toFIG.8.

Logic circuitry1314may include any one or more of the signal analyzer812, state of charge analyzer816, state of health analyzer820, and device operation manager822as discussed above. If located separately from signal processing circuitry1312, logic circuitry1314may include communications interface804as discussed above for receiving a received signal, such as received signal810.

Indicators1326may include visual, audio, or tactile indicators such as LED lights, speakers, a display, and a vibrator for indicating any information based on a configuration output such as configuration output824, discussed above.

In either the analog system1200, or digital systems1300discussed above, it should be appreciated that various signal traces in the circuitry may be isolated from the sensor such that data transmission thereon does not interfere with the sensor. For example, signal traces may occur in a different plane of a printed circuit board than the sensor. Moreover, certain embodiments utilize both analog components of system1200and digital components of system1300. In such embodiments, there may be a switching system for selecting the analog or digital components.

FIG.14depicts an exemplary energy unit1400having a plurality of energy devices1402. Each energy device1402is coupled to each other in parallel along a positive voltage line1401and a negative voltage line1403and includes a short generator1404located proximate thereto. Short generator1404may be coupled on a first surface of the energy device1402. Although shown on the end of the energy device1402, any short generator1404may be located on the side or at a distance away from the energy device1402without departing from the scope hereof. In embodiments, the short generator1402is sized and shaped to match the size and shape of a surface of the energy device1402.

Each energy device1402is an example of energy device102discussed above. Each short generator1404is an example of short generator104discussed above. Namely each short generator1404may include a sensor (e.g. sensor118) and a controller (e.g. controller118) for creating external short (e.g. external short105) across a known, predetermined external resistance (e.g. external resistance107).

Each energy device1402further includes a disconnect switch1406. Disconnect switch1406operates to disconnect a given energy device1402if it is determined that the state of charge or state of health is non-optimal for operation of energy unit1400. Each disconnect switch1406may be controlled via a configuration output signal (e.g. configuration output signal824) generated by a characteristic monitor (e.g. characteristic monitor800). In embodiments, each disconnect switch1406is controlled via a control signal transmitted on one or both of positive voltage line1401and negative voltage line1403. For example, in such embodiments the characteristic monitor (e.g. characteristic monitor800) may include a communications interface (e.g. communications interface804) capable of DC data modulation on one or both of positive voltage line1401and negative voltage line1403. In embodiments, each disconnect switch1406is controlled via a wireless or wired transmission including a control signal for controlling the disconnect switch1406.

Detection of shorts in individual ones of energy devices1402provides advantages because in parallel connections the voltage of all the energy devices is identical. Thus, if one of the energy devices1402makes a short circuit, for example by internal dendrite formation and short, then it can't be detected by monitoring the voltage of the energy devices1402and results in either fire and explosion, or at the best case it drains other energy devices1402in the parallel connection. System1400doesn't depend on temperature because once the temperature goes beyond the safe range there is not much that can be done to prevent damage. System1400includes practical and lest costly detectors that may detect internal and/or external shorts even when the detectors are away from the shorted cell. In system1400, any shorted energy device1402in a parallel connection can simply be removed from the circuit and thus the rest of the energy unit1400and circuit can continue performing. The PCB device such as the short detector1404, including the short detector and the switch, can be physically attached to the energy devices1402(though the sort detector does not need not be electronically attached to the energy devices1402).

The short detector1404may have any shape such as the cross section of the energy devices1402, as an example for 18650 cells, the short detector1404may have a diameter of about 18 mm and can be physically placed on bottom of each of the energy devices1402. For large prismatic energy devices1402, the short detector1404may be placed on any sides of a cell. The short detector and the switch may be physically connected or can be disconnected but must be in communication.

System1400may make energy units much safer as it is a solution to detect and react to a short or non-optimal characteristic when the energy devices are in parallel connection.

Further, if the energy devices1402in parallel connections are in close distance, each short detector1404of each energy device1402may be able to also react to the shorts in other energy devices1402. Thus, in embodiments each short detector1404may communicate with one another, or at least those switches1406having an associated energy device1402that the given short detector1404may monitor. For example, each signal from a cell short detector1404may be compared to the one or two neighbor energy devices1402in the parallel connections, the start time and strength of the signal determines the shorted energy device1402.

FIG.15depicts an exemplary energy unit1500having a plurality of energy devices1502. Each energy device1502is coupled to each other in series along a positive voltage line1501and a negative voltage line1503and includes a short generator1504located proximate thereto. Short generator1504is similar to short generator1404and may include any of the above discussed features thereof.

Each energy device1502is an example of energy device102discussed above. Each energy device1502further includes a bypass switch1506. Bypass switch1506operates to bypass a given energy device1502if it is determined that the state of charge or state of health is non-optimal for operation of energy unit1500. Each bypass switch1506may be controlled via a configuration output signal (e.g. configuration output signal824) generated by a characteristic monitor (e.g. characteristic monitor800). In embodiments, each bypass switch1506is controlled via a control signal transmitted on one or both of positive voltage line1501and negative voltage line1503. For example, in such embodiments the characteristic monitor (e.g. characteristic monitor800) may include a communications interface (e.g. communications interface804) capable of DC data modulation on one or both of positive voltage line1501and negative voltage line1503. In embodiments, each bypass switch1506is controlled via a wireless or wired transmission including a control signal for controlling the disconnect switch1506.

In series connections such as system1500, overcharging or under-discharging an energy device may be a major problem. It is desired that all the energy devices1502perform similarly, however a potentially weak energy device in series connection undergoes the same charge and current as all the energy devices1502, so it may reach over-charged or under-discharged condition without any alerts. Embodiments that transmit data and commands over the DC-power wires, such as positive line1501and negative line1503already connect the cells and therefore eliminate additional wiring and/or hardware required for data transmission. In addition, a short detector1504including the communications hardware-software and a switch1506may greatly simplify the management of the energy unit1500. The switch1506may result in bypassing an energy device1502, when its voltage is significantly different from the two neighbor energy devices1502, and connect it back only when the voltages are comparable. Therefore, the characteristic monitor (e.g. characteristic monitor800) used with system1500may measure the voltage of the energy device and compare it with the voltage of the next or previous energy device, or both.

FIG.16depicts a method1600for monitoring characteristics of an energy unit, in embodiments. Method1600may be implemented using any of the systems discussed above inFIGS.1-15.

In step1602, method1600calibrates a characteristic monitor to an energy system being monitored. In one example of step1602, characteristic monitor108is calibrated to energy device102. In another example of step1602, characteristic monitor306is calibrated to energy unit302. In another example of step1602, characteristic monitor406is calibrated to energy unit402. In another example of step1602, characteristic monitor506is calibrated to energy unit502. In another example of step1602, characteristic monitor606is calibrated to energy unit602. In another example of step1602, characteristic monitor706is calibrated to energy unit702. In another example of step1602, characteristic monitor800is calibrated to any of the systems discussed inFIGS.1-7, and12-15. Additional exemplary details of step1602are discussed below.

In step1604, method1600generates a short at the energy device. In one example of step1604, external short105is generated at energy device102as discussed above with regards toFIGS.1-7, and12-15. In another example of step1604, characteristic monitor800generates a short generation output826which is then transmitted via communications interface804to any of controllers116,516as short generation signal124. Controllers116,516then control short generation switch114to generate external short105. Short generation output826may be transmitted via wired or wireless protocols as discussed above with regards toFIG.8.

In step1606, method1600senses change in electromagnetic field emitted from known resistance for the external short generated in step1604. In one example of operation of step1606, any of sensors118,218,518,718,1218and1318monitor change in electromagnetic field120generated from external short105, as discussed above with regards toFIGS.1-7, and12-15and generates received signal810, as discussed with regards toFIG.8.

In step1608, method1600analyzes the received signal based on system configuration to generate signal parameters. In one example of step1600, signal analyzer812analyzes received signal810based on system configuration information828to generate signal parameter830as discussed above with regards toFIG.8. In embodiments, the signal parameter generated in step1608may include one or more instantaneous parameters chosen from the group of parameters including: maximum power, maximum voltage square, maximum voltage, maximum change in voltage, maximum current, maximum current square, maximum change in current, full-width voltage at half maximum and current at half maximum. or other instantaneous quantity or parameter at a given time. In embodiments, the signal parameter generated in step1608may include one or more integrated parameter chosen from the group of: total absolute energy and total absolute coulomb measured accumulatively over a period of time.

In step1610, method1600determines the state of charge based on a comparison of the signal parameter generated in step1608to a lookup table. In one example of step1610, state of charge analyzer816determines the state of charge of energy device102based upon lookup table814and signal parameter830. As an example referring to the values ofFIG.9, if the external short resistance107is 0.35 Ohms, the short distance is 3 cm, and the signal parameter830returns a value that at 1.4245 V, or within a predefined threshold thereof, then it may be determined in step1610that the energy device is fully charged. If the signal parameter830indicates a value that is not equal to 1.4245 V, or is outside of a predefined threshold thereof, then a mathematical calculation may be used, in step1610, to determine the charge level of the energy device.

In step1612, method1600determines the state of health based on a comparison of the signal parameter generated in step1608to a lookup table. For example, state of health analyzer820may analyze signal parameter830, at a known state of charge, and compare such signal parameter830to look up table to determine if the internal resistance is optimal. Referring to the values ofFIG.9, for example, assume a fully charged energy device, the external short resistance107is 0.35 Ohms, and the short distance is 3 cm, and the signal parameter830returns a value that at 1.4245 V. This is determined in step1612that the internal resistance of the energy device is as expected and thus the energy device has an optimal state of health. However, if the signal parameter830returns a value of 1.524 V, then that it is determined in step1612that the internal resistance of the battery is lower than optimal and, for example, caused by an internal short within the energy device. Furthermore, if the signal parameter830returns a value of 1.213 V, then that means that the internal resistance of the battery is higher than optimal and, for example, caused by energy device that has a degraded life-span.

In embodiments of step1612, state of health analyzer820may further characterize a type of short. Again taking the assumption, referring toFIG.9values, that the external short resistance107is 0.35 Ohms, and the short distance is 3 cm, and the signal parameter830returns a value that at 1.524 V. It may be determined in step1612that there is some level of short internal to the energy device because the total resistance value (i.e. internal resistance of the energy device plus known, predetermined external resistance107) has gone down and thereby the change in electromagnetic field120has a larger value. The difference between the expected total resistance value and the actual total resistance value may indicate the type of short. Thus, if the difference is at or below a hard-short type threshold, dependent on the configuration of the energy device (e.g. optimal internal resistance, type, model, manufacture, etc.), then state of health analyzer820may determine in step1612a hard short. However, if the difference is above the hard-short type threshold but below the soft-type threshold, then state of health analyzer820may determine a soft short in step1612.

Steps1610and1612may be sub-steps of a general step1613included in method1600for generating a characterization of the energy device.

In step1614, method1600analyzes the state of charge and/or state of health to determine configuration for the energy device. In one example of step1614, device operation manager822analyzes one or both of state of charge and state of health to determine configuration for the energy device102.

In embodiments of step1614, the charge level identified by state of charge analyzer816may be utilized by device operation manager822to generate configuration output824indicating to enter a fast charging mode for the associated energy device. In embodiments of step1614, the charge level identified by state of charge analyzer816may be utilized by device operation manager822to generate configuration output824indicating to enter a normal charging mode for the associated energy device. In embodiments of step1614, the charge level identified by state of charge analyzer816may be utilized by device operation manager822to generate configuration output824indicating to enter a slow charging mode for the associated energy device.

In embodiments of step1614, the state of health identified by state of health analyzer820may be utilized by device operation manager822to generate configuration output824to alter the connectivity of a given energy device, for example by bypassing, or disconnecting, the given energy device. As an example, if a hard short is identified in step1612, configuration output824may be generated controlling a switch that disconnects or bypasses the given energy device such that the given energy device does not impede overall operation of the system using such given energy device.

In embodiments of step1614, instead of, or additionally to, bypassing and/or disconnecting the given energy device, the configuration output824based on the state of health analyzer820may include a recommended replacement date for the given energy device. For example, if the difference between the expected total resistance value and the actual total resistance value, as discussed above, is not above a critical life-span threshold, then device operation manager822may consult lookup table814to identify when the energy device is expected to fail and thus identify a recommended replacement date.

In embodiments of step1614, the state of health and state of charge may be utilized by device operation manager822to generate configuration output824that identifies where a short occurs. For example, if device operation manager822is utilized with a sensor that senses change in electromagnetic field from multiple energy devices, such as shown inFIGS.5-7and14-15, device operation manager822may utilize lookup table814to identify the location of the short. Because lookup table814indicates the parameter value at a plurality of distances (for example, distances904inFIG.9), device operation manager822may analyze the signal parameters830using triangulation to identify the specific energy device at which the electrical short occurred. Therefore, this specific energy device may then be bypassed or disconnected in step1614to improve the overall efficiency of the energy unit or system.

In step1616, method1600generates a configuration output based on the determination within step1614. In one example of step1616, characterization monitor800outputs configuration output824to one or more of set a charging speed (e.g. fast, normal, slow), bypass or disconnect an energy device, and recommend a replacement time for the energy device.

FIG.17depicts a method1700for calibrating a characteristic monitor to an energy system being monitored, in embodiments. Method1700is for example implemented using any of the characteristic monitors106,306,406,506,606,706,800, etc. as discussed above with regards toFIGS.1-8, and12-15.FIG.1700is an example of step1602of method1600.

In step1702, method1700stores system configuration. In one example of step1702, system configuration information828is stored in memory806, for example including one or more of: knowledge of the sensor (e.g.118,218,518,718,818) used to acquire received signal810, the known, predetermined resistance (e.g. resistance107) of the external short (e.g. external short105), the known distance between the sensor and the short (e.g. distance126,226), etc.

In step1704, method1700sets characteristic monitor thresholds. In one example of step1704, potentiometers are set to configure the threshold values utilized within signal processing circuitry1212. These potentiometers may or may not be accessible via a housing of the analog system1200such that the threshold values are changeable during operation of system1200. In examples, the threshold values may be desired to be changed based on the specific battery type, make, model, etc. being analyzed. The threshold values may further be changed to reduce false positives detected using system1200. Moreover, the potentiometers may be utilized to set the thresholds at symmetric distances from the half value of the input voltage (Vcc/2). To maintain symmetry between the positive and negative thresholds, they must be set equidistant from the DC bias point using Eq. 3, below:
Vbias−Vlow=Vhigh−Vbias(Eq. 3).

In embodiments of step1702, the potentiometer controls only one of the Vhighor Vlowto control the bias point. In embodiments of step1702, an indicator may indicate if the bias is set incorrectly based on the potentiometer settings and thereby the characteristic monitor is set correctly.

In step1706, method1700stores expected energy device parameters as a lookup table. In one example of step1706, lookup table814is generated. Step1706may include sub-steps1708,1710, and1712.

In sub-step1708, method1700fully charges the energy device being stored as lookup table. In one example of sub-step1708, energy device102is fully charged.

In sub-step1710, method1700captures signal parameter of a fully charged energy device of sub-step1708. In one example of step1700, a signal parameter830is generated for a given energy device102. Sub-step1710may repeat for a given number of times and at a plurality of distances between the sensor and the external short. In one example of sub-step1710, four trials are performed on fully charged energy device to generate the values shown inFIG.10.

In sub-step1712, method1700determines an average of the signal parameters captured in sub-step1710. In one example of step1700, lookup table814is generated based on an average of the parameters detected in step1710. For example, values902are generated based on the values ofFIG.10.

FIG.18depicts an exemplary method1800for generating an energy device profile, in embodiments. Method1800may be performed, for example, using characteristic monitor800ofFIG.8to generate energy device profile832therein. Method1800may replace, or be performed in addition to, step1706of method1700. Method1800may be an example of step1602of method1600.

In step1802, method1800analyzes received signal at a first energy cycle. In one example of step1802, signal analyzer812analyzes received signal810at a first energy cycle and stores such received signal810as energy device profile832.

Step1802may include substeps1804-1808, in embodiments. Particularly steps1804-1808are useful for generating a signal parameter830that is a statistical parameter. In sub-step1804, method1800obtains a plurality of received signals. In one example of step1804, a plurality of received signals810are received at a frequency of 2 kHz or less. The number of successive received signals810for a statistical parameter can be, for example, 2 to 10 times to provide enough data points for the statistical analysis. The duration of wait between each of these successive received signals may depend on the battery chemistry and type. As an example, the duration between successive received signals810may be between 1 millisecond and 1 minute.

In sub-step1806, method1800determines statistical analysis of received signals1806. In one example of sub-step1806, method1800analyzes the plurality of received signals810from sub-step1804to determine a signal parameter830as a statistical parameter including one or more of mean, standard deviation, variance, and other statistical parameters.

In sub-step1808, method1800stores the determined statistical analysis from sub-step1806as energy device profile. In one example of sub-step1808, statistical parameter830is stored as energy device profile832within characteristic monitor800.

In step1810, method1800cycles energy device, system, or unit. Step1810may be a full cycle, multiple full cycles, or a partial cycle of the energy device, system, or unit (e.g. energy device102). In one example of step1810, energy device102is cycled for a given period of time, such as one cycle, or half cycle, or other portion of a cycle. As such, it should be appreciated that method1800may include cycling of a temporal or percentage of charge time. The duration of cycling between the two sets of successive measurements can be more than 1 second, more than 1 minute, more than 5 minutes, more 10 minutes or more than 20 minutes.

In step1812, step1802is repeated for a second energy cycle. Step1812may include sub-steps1814,1816, and1818which are similar to sub-steps1804,1806, and1808, respectively. However, in sub-step1808, the energy device profile may be updated instead of stored for the first time.

FIG.19depicts a method1900for balancing an energy unit or system having a plurality of energy devices, in embodiments. Method1900may be performed by characteristic monitor800in an energy unit having a plurality of energy devices (e.g. energy device102) in parallel or in series.

In step1902, method1900determines signal parameters for the plurality of energy devices coupled together. In one example of step1902, characteristic monitor800, or a plurality of characteristic monitors800each coupled to a respective energy device, determines a plurality of signal parameters830for the given energy units. In embodiments, the determined signal parameters830may be an instantaneous, integrated, or statistical based parameter. Particularly, in embodiments, the signal parameters determined may be an instantaneous signal parameter830such as signal strength of the received signal. Particularly, in embodiments, the signal parameters determined may be a statistical-based signal parameter830such as signal strength of the received signal. For example, if the statistical based parameter for a given energy device is based on three received signals810, The “ith” reading of the signal strength of the “jth” energy device may be shown by Si,j. The “mean” value for the energy device “j” is thus
Smean_Cj=(S1_Cj+S2_Cj+S3_Cj)/3

The “variance” for the energy device “j” is thus:
Svarinace_Cj=(S1_Cj−Smean_Cj)2+(S2_Cj−Smean_Cj)2+(S3_Cj−Smean-Cj)2
Similar equations can be used for various statistical analysis such as standard deviation, etc.

In step1904, method1900compares the determined signal parameters for each energy device against each other. In one example of step1904, signal analyzer812analyzes each signal parameter830for each respective energy device against each other. For example, signal analyzer812may determine a mean, a standard deviation, or a variance between the signal parameters830generated for each energy device. For example, assuming four energy devices, each obtaining three received signals830, as discussed above with respect to step1902, the mean for all energy devices may be:
Smean_C=(Smean_C1+Smean_C2+Smean_C3+Smean_C4)/4

The variance for all energy devices may be:
Svariance_C=(Svariance_C1+Svariance_C2+Svariance_C3+Svariance_C4)/4.
Similar equations may be used for other statistical analysis such as standard deviation, etc.

In step1906, method1900generates a configuration output based on the step of comparing (step1904). In one embodiment of step1904, device operation manager822analyzes the mean, standard deviation, or variance between a plurality of received signals from respective energy devices (from steps1902,1904) and generates configuration output824. Particularly, for each of the plurality of energy devices, if the mean, standard deviation, or variance is above a given threshold, then the configuration output may bypass (if the energy devices are in series) or disconnect (if the energy devices are in parallel). For example, using the above discussed equations, an energy device “j” may be faulty when:

(S⁢mean_C-S⁢mean_CjS⁢mean_Cj)2>Th_meanOr⁢if⁢(Svariance-⁢C-Svariance-⁢CjSvariance-⁢Cj)2>Th_variance
where Th_mean, the threshold of mean, and Th_standard deviation, threshold of standard deviation are by the user based on the battery and the application.

FIG.20depicts an exemplary method2000for battery life estimation. Method2000may be performed by characteristic monitor800in an energy unit having a plurality of energy devices (e.g. energy device102) in parallel or in series. Method2000may also be performed via a single energy device as well.

In method2000, steps2002,2004, and2006may be identical to steps1902,1904, and1906, respectively. If method2000is being performed only on a single energy device, then step2004may be skipped.

In step2008, method2000updates an energy device profile for each respective energy device. Step2008may perform method1800. In embodiments, step2008performs only steps1812, including sub-steps1814-1818for each energy device. In embodiments of step2008, energy device profile may generate an expected parameter value for a future energy cycle based on one or more previous energy cycles. For example, if the signal parameter is a statistical parameter based on successive received signals, on the 100thcycle of each respective energy device, the expected value within the energy device profile may be based on a difference in similar statistical parameters (i.e. similar state of charge, etc) derived during the 10thand 50thcycle.

In step2010, method2000performs an energy cycle for each energy device. Step2010may be a full cycle, multiple full cycles, or a partial cycle of the energy device, system, or unit (e.g. energy device102). In one example of step2010, energy device102is cycled for a given period of time, such as one cycle, or half cycle, or other portion of a cycle. As such, it should be appreciated that method2000may include cycling of a temporal or percentage of charge time. The duration of cycling between the two sets of successive measurements can be more than 1 second, more than 1 minute, more than 5 minutes, more 10 minutes or more than 20 minutes.

This series of steps then repeats to monitor energy device lifespan. At any time should step2006determine that the signal parameter is not as expected, based on the energy device profile, then a configuration output may be generated. By monitoring energy device profile, a gradual degradation of the energy device may be monitored and thereby an estimated replacement time may be output as the configuration output.

FIG.21depicts an exemplary method2100for estimating an internal resistance of an energy device. Method2100may be performed using characteristic monitor800discussed above.

In step2102, method2100generates a signal parameter based on a first known resistance. In one example of step2102, characteristic monitor800outputs a short generation output826to control switch114, via controller116, to create an external short105across known resistance107. The change in electromagnetic field120may be sensed by a sensor (e.g. sensor118,218, etc) represented as received signal810. Received signal810may then be analyzed by signal analyzer812to determine signal parameter830.

In step2104, method2100generates a signal parameter based on a second known resistance. In one example of step2104, characteristic monitor800outputs a short generation output826to control switch114, via controller116, to create an external short105across known resistance107. Known resistance107may be a variable resistance such that during step2104, short generation output826indicates a second known resistance value for known resistance107. The change in electromagnetic field120may be sensed by a sensor (e.g. sensor118,218, etc) represented as received signal810. Received signal810may then be analyzed by signal analyzer812to determine signal parameter830.

In step2106, method2100determines an internal resistance based on the received signals810corresponding to each of the first and second known resistnaces discussed above in steps2102,2104. In an embodiment, the energy devices monitored according to first and second known resistances in step2102,2104are in series. In such embodiments, at step2106, signal analyzer may utilize the following equation:

Sseries=f⁡(Q,V,1r+R,1D)

In an embodiment, the energy devices monitored according to first and second known resistances in step2102,2104are in parallel. In such embodiments, at step2106, signal analyzer may utilize the following equation:

Sparallel=f⁡(Q,V,r+Rr·R,1D)

Thus, when R=r then

Sseries,R=r=f⁡(Q,V,12⁢r,1D),orSparallel,R=r=f⁡(Q,V,2r,1D)When⁢R=0Sseries,R=0=f⁡(Q,V,1r,1D)
Alternatively, one can use parallel with R>>r

Sparallel,R≫r=f⁡(Q,V,1r,1D)

By repeating the received signals810using different known resistances in steps2102,2104, that is keeping the Q, V and D constant, then using the first2equations above and any of the 3rdor 4th, the relationship between Signal strength and internal resistance can be estimated. In embodiments, this internal resistance may then be used to estimate state of charge and state of health, for example by state of charge analyzer816and state of health analyzer820, respectively.

FIG.22depicts an exemplary method2200for adaptive charging of an energy device, in embodiments. One reason for not being able to charge energy devices as fast as desired is due to the generated heating
h(heat generated at any time)=I2(current at that time)·r(internal resistance at that time)

Method2200provides a method such that the total heat inside the battery at any given time, H(t), as function of the current, i(t), total charge, Q(t), and resistance of the cell r(t) doesn't exceed a threshold level. The threshold depends on how fast the heat can leave the energy device.
H(t)=∫0ti2(τ)r(τ)dτ<Hthreshold

Method2200may know the internal resistance of the energy device and adjust the charging current such that at any time during the charging the total heat generated in the energy device stays lower than a threshold. The threshold may be defined such that for any location of the energy device, the temperature stays below a safe value.

Within method2200, if internal resistance is high then the applied charging current needs is lowered to limit the generated heat by the energy device. At the same time for high internal resistance the signal strength of the received signals discussed above (e.g. received signal810) is low; that is the strength of signal can be used for adaptive charging of energy devices.

In step2202, method2200generates a first signal parameter for the energy device to be charged. In one example of step2202, characteristic monitor determines signal parameter830in any of the manners discussed above, such as an instantaneous, integral, or statistical parameter.

In step2204, method2200charges the energy device for a given time period at a known charge rate. In one example of step2200, characteristic monitor800generates configuration output824as a charge rate indication to control charging of the energy device102. The given time period may be a length of time, such as 1 minute, 20 minutes, 1 hour, etc. or it may be a percentage of charge such as a full charge cycle, a partial charge cycle, or multiple charge cycles.

In step2206, method2200generates a second signal parameter for the energy device to be charged. In one example of step2202, characteristic monitor determines signal parameter830in any of the manners discussed above, such as an instantaneous, integral, or statistical parameter.

Step2208is a decision, in step2208method2200determines if the second signal parameter is above a high threshold, indicating that the battery is performing better than expected. In one example of step2208, device operation manager822compares the second generated signal parameter against a lookup table814or energy device profile832to determine if the second generated signal parameter is above a high threshold. If in step2208, second signal parameter is above a high threshold, then method2200proceeds to step2212where method2200changes the cycling rate of the energy device to increase the cycling rate. For example, device operation manager822may determine that the cycling rate can increase in step2208, and thus output a configuration output826indicating to increase the cycling rate of the energy device. If in step2208, second signal parameter is below the high threshold, method2200proceeds to decision step2210.

Step2210is a decision, in step2210method2200determines if the second signal parameter is below a low threshold, indicating that the battery is performing worse than expected, and possibly is forming a short within the energy device thus potentially leading to a device failure. In one example of step2210, device operation manager822compares the second generated signal parameter against a lookup table814or energy device profile832to determine if the second generated signal parameter is below a low threshold. If in step2210, second signal parameter is below a low threshold, then method2200proceeds to step2212where method2200changes the cycling rate of the energy device to decrease the cycling rate. For example, device operation manager822may determine that the cycling rate can decrease in step2210, and thus output a configuration output826indicating to decrease the cycling rate of the energy device. If in step2210, second signal parameter is above the low threshold, method2200proceeds to repeat step2204such that method2200is repeated throughout charging of the energy device.

As an example of method2200, for a given energy device the S can be measured every 1 minute during charging and the charging is done such that:a) If S(t)<Slowthen charging current I(t)=m1S1+n1; where n1>0 and m1depends on the application and battery typeb) If Slow<S(t)<Shighthen charging current I(t)=m2S1+n2; where n2>0 and m2depends on the application and battery type and m2>m1c) If Shigh<S(t) then charging current I(t)=m3S1+n3; where n3>0 and m3depends on the application and battery type and m1>m3.

Method2200utilizes the various systems and methods discussed herein, such as shorting a cell (with or without a known external resistance107) to create a very fast discharge of the battery in which the charge transfer resistance plays an important role, thus there is a relationship between the strength of Signal S, and the charge transfer resistance, Ret, which has the double layer effect included. In comparison with a EIS method, the width of the semi-circle represents the charge transfer resistance, Rct. The charge-transfer-resistance accounts for the resistance to charge transfer processes at the surface of the electrode particles. This may be due to the solid electrolyte interphase (SEI) layer inhibiting charge transfer. The size of the semi-circle (width and height) changes as a function of both state of charge and state of health. Comparing a fully charged and a fully discharged battery, the ohmic resistance does not change significantly; however, there is a significant growth in charge transfer resistance as the battery becomes fully discharged. Changes to the impedance spectra are also a result of battery aging. As the SEI layer grows throughout the battery's life, the charge-transfer-resistance increases. Loss of connectivity between electrode particles and degradation of the current collector could also lead to changes in the ohmic resistance. In embodiments, to decouple state of charge estimation and state of health estimation with method2200, method2200may be performed only when the cell is fully charged or discharged so that the state of charge is at a known state. The state of health may then be used as a known constant in estimating the state of charge.

Effect of the Double Layer in the Energy Device:

In embodiments of the above described systems and methods, a received signal may be generated, either passively or actively, based upon electron transfer through a double layer of the energy device. In any electrochemical cell there is a double layer with thickness in the range of, usually, 0.1 nm-20 nm. The electric field in the double layer can often reach 10{circumflex over ( )}9 V/m. The charging (discharging) time of double layer (t) is often in the order of microseconds. By causing an external short (e.g. external short105), the double layer may rapidly charge/discharge such that the external short105emits change in electromagnetic field. Thus one can observe the change in electromagnetic field away from the cell (such as induced current in an electromagnetic coil or any other receiver) as an indication of a short circuit in an energy device. However, it should be appreciated that the present invention is not limited to change in electromagnetic field caused through rapid charge/discharge within a double layer, but also applies to any change in electromagnetic field caused within external short105.

The energy device's double layer, although only 10s of nanometers, is extremely important in electrochemical reactions. The double layer is different for different amount of charges in the battery, and thus state of charge and state of health may be estimated from the behavior of the double layer, namely the rapid charge/discharge therethrough that causes rapid change in electromagnetic field either in the energy device itself or in the external shorts discussed above. Therefore, the shorts either actively generated (e.g. the external shorts105discussed herein) or the internal shorts, need only be generated for a quick period of time (e.g. 1 nanosecond and 10 microseconds, or even between 10 nanoseconds and 1 microseconds).

In embodiments, knowledge of the double layer in the energy device provides an ability to compare ions concentration profile versus voltage profile, without electro-neutrality, to further derive the relationship between the state of charge, which is a function of ions concentration profile, and electric field in the double layer. This may then be combined with relationship between the electric field of the double layer and the received electromagnetic signal by the sensor of the systems and methods described herein.

It should be appreciated that the analysis performed by various aspects of the systems and methods discussed above may include additional sensed data about the energy device, system, or unit being monitored. For example, one or more of voltage between terminals of the energy device, system, or unit, current between terminals of the energy device, system, or unit, and temperature of the energy device (including internal and/or surface temperature) could be utilized to make a determination about a characteristic. As such, at least some embodiments may provide another level of safety on top of prior energy device management systems—particularly one that is capable of making a characteristic determination in a much faster manner based on instantaneous, integral, or statistical analysis based signal parameters. For example, the lookup tables and/or unit profiles may include voltage, current, or temperature sensing data in addition to the received signal data discussed herein.

Detection of Electrical Shorts from Change in Electrical Field Internal to Energy Device

The embodiments discussed herein may analyze any change in electromagnetic field, not just that caused by an external short (i.e. external short105). For example, the sensors discussed herein may be able to detect electromagnetic field changes caused within the energy device themselves. This field change may be compared to a lookup table or energy device profile, similar to those lookup table814and energy device profile832discussed above. This may result in the ability to detect different short types. Moreover, as compared to conventional methods that only monitor current, voltage, and/or temperature, the present embodiments (including those that monitor only change in electromagnetic field from the energy device itself) may detect a short in real-time, enabling the management unit to prevent any thermal runaway. Furthermore, cmbined with the state of charge and state of health estimation, the management unit can detect the type of short (i.e. soft vs hard type) thereby resulting in taking more suitable actions to prevent the damage.

The embodiments discussed herein may be further understood by the following non-limiting examples.

Example 1: Electromagnetic Emission from Battery Cells

Experiment 1. As shown inFIG.23, four alkaline Manganese Dioxide AA battery cells were coupled together in series forming 6.59V battery pack. As shown inFIG.24, a short generator was coupled thereto to create a short across the battery pack. A short detection board including an electromagnetic coil was placed 3 cm and 4 cm away from the short generator. A processing board received the coil signal to analyze the signal. The resistance of the external short was selected at 0.35 Ohms. The short generator portion included a button that, when pressed, generated the external short. Four separate trials illustrated a series of peaks were detected over a duration of less than 10 milliseconds. As shown inFIG.25, at three centimeters between the coil and the external short, the maximum peak-to-peak voltage level was approximately 2.25. As shown inFIG.26, at four centimeters between the coil and the external short, the maximum peak-to-peak voltage level was approximately 1.99.

FIGS.27-29depict the voltage response from the sensor when the AA batteries in series have a total Voltage of 4.532V. It can be seen that the average maximum peak-to-peak voltage level is 1.05V.FIGS.30-32depict the voltage response from the sensor when the AA batteries in series have a total Voltage of 5.441V. It can be seen that the average maximum peak-to-peak voltage level is 1.52V.FIGS.33-35depict the voltage response from the sensor when the AA batteries in series have a total Voltage of 5.5.633V. It can be seen that the average maximum peak-to-peak voltage level is 1.6V. Therefore, it is shown that, when a short is detected with a known resistance and sensed using a sensor at a known distance, then the state of charge and state of health may be determined.

Experiment 2. As shown inFIG.36, three coincells were associated with individual short generators (taped thereto), a respective analog-based short detector was placed a distance away therefrom including logic circuitry and indicator lights for indicating a detected short. As shown inFIG.37, when a short was detected, the indicator lights were turned on.FIG.38depicts two signals on an oscillator. The top signal is the short generation signal, and the bottom signal is the received signal at the coil.FIG.39shows the received signal (lighter gray) and the amplified signal (darker gray). The amplification ratio is fixed and is 15. The coincell shows a received signal having 2 V max peak-to-peak. The signal decays almost as 1/distance.FIG.40depicts the short detected using an oscillator.

Experiment 3: As shown inFIG.41, a short detector box was created. This box included features of the short generator, such as the sensor118and controller116. The box included a housing and was wirelessly communicable to a smart device such as a smartphone, table, computer, etc. for transmitting the received sensor signal for further processing and state of charge/state of health analysis.

Example 2

A battery is being charged in a cellphone. A series of external shorts is generated with known external resistances are generated in the battery every 1 minute during the charging. The duration of each of the series of applied external shorts is 0.1 minute, during this time the said battery cell is in open circuit mode and the charging is stopped. Each series of applied external shorts consists of 5 instantaneous external shorts. The mean and standard value of each of the series is calculated. Using the current profile and voltage profile of the said battery cell, the said mean and standard values of signal strength is compared to previous cycles or a lookup table, and the state of charge, internal resistance and state of health of said battery is thus estimated. Based on the state of charge, internal resistance and state of health estimations the corresponding adaptive charging activity is thus decided and then performed; for example, for a low internal resistance and acceptable state of health and state of charge estimations the applied charging current can be increased until the internal resistance estimation reaches a threshold value.

Example 3

A battery pack is being cycled in an electric vehicle. For each of the battery modules of the said battery pack a series of external shorts with known external resistances are generated in the battery pack every 10 minutes during the cycling. The duration of each of the series of applied external shorts is 1 minute, during this time the said battery module is in open circuit mode and the other battery modules of the pack should compensate for the said module. Each series of applied external shorts consists of 5 instantaneous external shorts. The mean and standard value of each of the series is calculated. Using the current profile and voltage profile of the said battery module, the said mean and standard values of signal strength is compared to the corresponding values of other modules, and the relative internal resistance, state of charge and state of health of each module is thus estimated. Then any required cell balancing activity is thus decided and then performed; for example, after identifying a weaker module, the said weaker module and the rest of the pack will be balanced according to the known methods for balancing a weak module in a pack in state of art.

Example 4

A battery module is being cycled in an electronic device. For each of the battery cells of the said battery pack a series of external shorts with known external resistances are generated in the battery module every 5 minutes during the cycling. The duration of each of the series of applied external shorts is 0.5 minute, during this time the said battery cell is in open circuit mode and the other battery cells of the module should compensate for the said cell. Each series of applied external shorts consists of 5 instantaneous external shorts. The mean and standard value of each of the series is calculated. Using the current profile and voltage profile of the said battery cell, the said mean and standard values of signal strength is compared to the other cells and the relative internal resistance, state of charge and state of health of each said cell is thus estimated. Then any required cell balancing activity is thus decided and then performed; for example, after identifying a weaker cell, the said weaker cell and the rest of the module will be balanced according to the known methods for balancing a weak cell in a module in state of art.

Example 5

A battery pack is being cycled in an electric vehicle. For each of the battery modules of the said battery pack a series of external shorts with known external resistances are generated in the battery pack every 10 minutes during the cycling. The duration of each of the series of applied external shorts is 1 minute, during this time the said battery module is in open circuit mode and the other battery modules of the pack should compensate for the said module. Each series of applied external shorts consists of 5 instantaneous external shorts. The mean and standard value of each of the series is calculated. Using the current profile and voltage profile of the said battery module, the said mean and standard values of signal strength is compared to the corresponding values of earlier cycles or a lookup table, and the internal resistance and state of charge and the state of health of the said module is thus estimated. The values of all modules in the pack are compared and any required cell balancing activity is thus decided and then performed; for example, after identifying a weaker module, the said weaker module and the rest of the pack will be balanced according to the known methods for balancing a weak module in a pack in state of art.

Example 6

A battery module is being cycled in an electronic device. For each of the battery cells of the said battery pack a series of external shorts with known external resistances are generated in the battery module every 5 minutes during the cycling. The duration of each of the series of applied external shorts is 0.5 minute, during this time the said battery cell is in open circuit mode and the other battery cells of the module should compensate for the said cell. Each series of applied external shorts consists of 5 instantaneous external shorts. The mean and standard value of each of the series is calculated. Using the current profile and voltage profile of the said battery cell, the said mean and standard values of signal strength is compared to the corresponding values of earlier cycles or a lookup table, and the internal resistance and state of charge and the state of health of the said cell is thus estimated. The values of all cells in the module are compared and any required cell balancing activity is thus decided and then performed; for example, after identifying a weaker cell, the said weaker cell and the rest of the module will be balanced according to the known methods for balancing a weak cell in a module in state of art.

STATEMENTS REGARDING INCORPORATION BY REFERENCE AND VARIATIONS

All references throughout this application, for example patent documents including issued or granted patents or equivalents; patent application publications; and non-patent literature documents or other source material; are hereby incorporated by reference herein in their entireties, as though individually incorporated by reference, to the extent each reference is at least partially not inconsistent with the disclosure in this application (for example, a reference that is partially inconsistent is incorporated by reference except for the partially inconsistent portion of the reference).

All patents and publications mentioned in the specification are indicative of the levels of skill of those skilled in the art to which the invention pertains. References cited herein are incorporated by reference herein in their entirety to indicate the state of the art, in some cases as of their filing date, and it is intended that this information can be employed herein, if needed, to exclude (for example, to disclaim) specific embodiments that are in the prior art. For example, when a compound is claimed, it should be understood that compounds known in the prior art, including certain compounds disclosed in the references disclosed herein (particularly in referenced patent documents), are not intended to be included in the claim.

When a group of substituents is disclosed herein, it is understood that all individual members of those groups and all subgroups and classes that can be formed using the substituents are disclosed separately. When a Markush group or other grouping is used herein, all individual members of the group and all combinations and subcombinations possible of the group are intended to be individually included in the disclosure. As used herein, “and/or” means that one, all, or any combination of items in a list separated by “and/or” are included in the list; for example “1, 2 and/or 3” is equivalent to “‘1’ or ‘2’ or ‘3’ or ‘1 and 2’ or ‘1 and 3’ or ‘2 and 3’ or ‘1, 2 and 3’”.

Every formulation or combination of components described or exemplified can be used to practice the invention, unless otherwise stated. Specific names of materials are intended to be exemplary, as it is known that one of ordinary skill in the art can name the same material differently. One of ordinary skill in the art will appreciate that methods, device elements, starting materials, and synthetic methods other than those specifically exemplified can be employed in the practice of the invention without resort to undue experimentation. All art-known functional equivalents, of any such methods, device elements, starting materials, and synthetic methods are intended to be included in this invention. Whenever a range is given in the specification, for example, a temperature range, a time range, or a composition range, all intermediate ranges and subranges, as well as all individual values included in the ranges given are intended to be included in the disclosure.

As used herein, “comprising” is synonymous with “including,” “containing,” or “characterized by,” and is inclusive or open-ended and does not exclude additional, unrecited elements or method steps. As used herein, “consisting of” excludes any element, step, or ingredient not specified in the claim element. As used herein, “consisting essentially of” does not exclude materials or steps that do not materially affect the basic and novel characteristics of the claim. Any recitation herein of the term “comprising”, particularly in a description of components of a composition or in a description of elements of a device, is understood to encompass those compositions and methods consisting essentially of and consisting of the recited components or elements. The invention illustratively described herein suitably may be practiced in the absence of any element or elements, limitation or limitations which is not specifically disclosed herein.

The terms and expressions which have been employed are used as terms of description and not of limitation, and there is no intention in the use of such terms and expressions of excluding any equivalents of the features shown and described or portions thereof, but it is recognized that various modifications are possible within the scope of the invention claimed. Thus, it should be understood that although the present invention has been specifically disclosed by preferred embodiments and optional features, modification and variation of the concepts herein disclosed may be resorted to by those skilled in the art, and that such modifications and variations are considered to be within the scope of this invention as defined by the appended claims.