Patent Description:
This disclosure generally relates to systems and methods for monitoring for a gas analyte, wherein the gas analyte comprises a lithium ion battery electrolyte material released by one or more lithium ion batteries.

In many applications, the potential for unwanted and/or hazardous gases to be emitted into a surrounding environment exists. The ability to react quickly to developing dangers resulting from these gases is of need since it is known that particular gases can have an impact on a surrounding environment and human life. The impact can be devastating and can lead to system failures, mechanical failures, plant failures, devices failures, explosions, fires, and in some instances death.

Batteries are known to contribute to the dangers that hazardous gases can have on the surrounding environment. For example, when a battery begins to degrade, the battery can become susceptible to a condition known as "thermal runaway". If left unchecked, this condition can cause the battery to leak and/or explode. Thermal runaway can be initiated by a short circuit within a battery (e.g., a cell of the battery), improper battery use, physical abuse, manufacturing defects, or exposure of the battery to extreme external temperatures. Thermal runaway occurs when an internal reaction rate of the battery increases to a point that more heat can be generated than can be withdrawn, leading to a further increase in both the internal reaction rate and heat generated.

The effects of a thermal runaway condition can depend on battery type. For example, in flooded electrolyte batteries, such as lead acid batteries, the thermal runaway condition can cause hydrogen to be released, resulting in a hazardous gas escaping into a surrounding environment. In sealed batteries, such as pouched lithium ion batteries, which can be used in devices, such as laptops, cell phones, and the like, the thermal runaway condition can cause an expansion, which can result in the sealed battery exploding and releasing the hazardous electrolyte gas into the surrounding environment.

Non patent literature publication by <NPL>, discloses a system to detect off gas from Li-ion batteries, comprising a gas sensor; a thermal test was conducted with an overcharged battery and the sensor provided a response to the offgas event, there is indication that the sensor provides some degree of early warning prior to a thermal event as much as <NUM> minutes.

The present invention is related to a method comprising monitoring a gas analyte using a monitoring system capable of monitoring lithium ion battery off-gas, wherein the gas analyte comprises a lithium ion battery electrolyte material released by one or more lithium ion batteries, according to claim <NUM>.

Additionally, the present invention is related to a system capable of monitoring lithium ion battery off-gas, according to claim <NUM>.

This disclosure generally relates to systems and methods for monitoring for a gas analyte, wherein the gas source includes a battery and the gas analyte is an off-gas. Thus, the systems and methods described herein can monitor for battery off-gas. The present invention is related to monitoring a battery off-gas condition; in examples which do not form part of the present invention the systems and methods described herein can be implemented in any environment that includes a gas source. For example, the environment can include, but not limited, a safety environment, a test environment, such as a laboratory, a storage environment, such as a data center, an industrial environment, such as a combustion system, a commercial environment, a residential environment, a military environment, a transportation environment, such as a vehicle, a product, such as a commercial and residential device and/or apparatus, or like environments. Accordingly, the scope of this invention is solely defined by the appended claims.

The term "gas analyte" as used herein, includes an electrolyte gas, such as a volatile electrolyte solvent, a volatile component of an electrolyte mixture of the battery, or the like. Volatile electrolyte species can include diethyl carbonate, dimethyl carbonate, methyl ethyl carbonate, ethylene carbonate, propylene carbonate, vinylene carbonate or the like. Additionally, the gas analyte includes a lithium-ion battery off gas; in an example which does not form part of the present invention, the gas analyte can include carbon dioxide, carbon monoxide, methane, ethane, hydrogen, oxygen, nitrogen oxides, volatile organic compounds, hydrogen sulfide, sulfur oxides, ammonia, chlorine, propane, ozone, ethanol, hydrocarbons, hydrogen cyanide, combustible gases, flammable gases, toxic gases, corrosive gases, oxidizing gases, reducing gases, or the like.

The gas source is the battery. The systems and methods described herein can be implemented to monitor the battery for a gas analyte. Over their lifespan, batteries can degrade progressively, which can result in a reduced capacity, cycle life, and safety. A degrading battery can release a gas, which can be referred to herein as the "gas analyte". The gas analyte can be released by the battery during a cycling condition, such as a charge cycle or a discharge cycle. One or more causes of battery degradation can include improper battery use, physical abuse, manufacturing defects, exposure of the battery to extreme external temperatures, overcharge, or the like. The systems and methods described herein can detect the gas analyte during the cycle condition to provide an early warning of a thermal runaway condition. In one example, the early warning can include an audible alarm, a visual alarm, fire suppression, communication with other systems and a user. The gas analyte detected during the cycle condition can be interpreted as a warning that the battery can be at risk of thermal runaway. By providing an early warning, fires, explosions and injuries that can be caused in response to a thermal runaway condition can be substantially mitigated.

Furthermore, by providing an early warning, operational limits of the battery can be substantially extended, and enable monetization of high value, but otherwise "abusive" services, such as occasional high-power discharges or low depths of discharge. Additionally, life extension beyond an industry-standard <NUM>% capacity is possible. The systems and methods described herein can provide substantial benefits, such as improved control and reduction in an overall battery system cost. Moreover, the systems and methods described herein can be configured to monitor any type of battery gas analyte. Thus, the systems and methods described herein can be used to monitor a lithium ion battery, a lead-acid battery, or the like.

The systems and methods described herein can be configured with a plurality of enclosures, such as battery enclosures. Thus, the systems and methods described herein can be used to monitor for a gas analyte released by one or more batteries located within a battery enclosure. The term "battery enclosure" as used herein refers to any housing that can partially encapsulate the one or more batteries. In an example, the enclosure can include a ventilated enclosure or a non-ventilated enclosure. The ventilated enclosure can include a ventilation system that can include an intake and an exhaust. In an even further example, the enclosure can include a battery storage cabinet, a shipping container or a battery rack.

Furthermore, the term "processor" as used herein can refer to any device capable of executing machine readable instructions, such as a computer, controller, an integrated circuit (IC), a microchip, or any other device capable of implementing logic. The term "memory" as used herein can refer to a non-transitory computer storage medium, such as volatile memory (e.g., random access memory), non-volatile memory (e.g., a hard disk drive, a solid-state drive, flash memory or the like) or a combination thereof.

Although examples are described herein relating to a semiconductor gas sensor, it should be appreciated that any type of gas sensor can be used, such as a chemi-resisitive sensor, an electrochemical sensor, a semi conductive metal-oxide sensor, a catalytic sensor, a thermal conductivity sensor, a metal-oxide semiconductor, a potentiometric sensor, an optical sensor, an infrared (IR) sensor, an amperometric sensor, or the like. In a non-limiting example, a hydrogen sensor, such as NTM SenseH<NUM>® or NTM SenseH<NUM>®-R sensor offered by Nexceris, LLC can be used.

In the present invention gas sensors are employed; in some examples which do not form part of the present invention, it should be appreciated that other sensors can be used. Thus, in some examples which do not form part of the present invention, it should be appreciated that the systems and methods described herein are equally applicable to other types of monitoring applications other than gas monitoring. These sensors can include a temperature sensor, a pressure sensor, a proximity sensor, an altitude sensor, a humidity sensor, a radiation sensor, a smoke sensor, a conductivity sensor, a pH sensor, an accelerometer, a speed sensor, a radar, a Doppler radar, a level sensor, a sonar sensor, a lambda sensor, or the like. As an example not forming part of the present invention, the systems and methods described herein can monitor for a change in an environmental condition (e.g., temperature, pressure, proximity, altitude, humidity, radiation, smoke, conductivity, pH, acceleration, speed, distance, velocity, motion, level, such as a liquid, oxygen level, or the like), generate a sensor signal characterizing the change in the environment condition, receive the sensor signal (e.g., at a processor), evaluate the sensor signal relative to a threshold, and generate an alert signal based on a result of the evaluation. Accordingly, in examples not forming part of the present invention, the systems and methods described herein can have a wide range of applicability beyond that of gas monitoring.

<FIG> illustrates an example of a monitoring system <NUM> that can be configured to monitor a gas source <NUM> for a gas analyte. The gas source is a battery. The system <NUM> includes a gas sensor <NUM>. The gas sensor <NUM> can be positioned relative to the gas source <NUM> such that the gas sensor <NUM> is within a gas analyte sensing range of the gas source <NUM>. For example, if the gas source <NUM> is located within an enclosure (or another system) (not depicted in <FIG>), the gas sensor <NUM> can be positioned within the enclosure (or other system) and within the gas analyte sensing range of the gas source <NUM>. In another example, the enclosure can be a sealed battery enclosure such that the battery is sealed off from a surrounding environment. The gas sensor <NUM> is configured to monitor the gas source <NUM> for a gas analyte. The gas analyte within the gas source <NUM> is related to a state of the gas source <NUM> wherein the gas source <NUM> can be releasing the gas analyte.

The gas sensor <NUM> can include a semiconductor gas sensor. In one example, the gas sensor <NUM> can be a semiconductor gas sensor. The semiconductor gas sensor can include a common material. The common material can include tin dioxide, or the like. An electrical resistance of the common material can decrease when a gas, measured in parts-per-million (ppm), comes into contact with the common material. In some examples, the electrical resistance of the common material can increase when the gas comes into contact with the common material. The gas sensor <NUM> can include one or more additional components (not depicted in <FIG>) that can be configured to detect the change in the electrical resistance in the common material and generate a signal representative of a given amount of the gas.

The gas sensor <NUM> is configured to generate a sensor signal characterizing an amount of the gas analyte released by the gas source <NUM>. The sensor signal can be generated based on a given electrical resistance of the common material. According to the present invention, during one or more battery states of the battery, the gas sensor <NUM> is configured to generate one or more sensor signals characterizing amounts of the gas analyte released by the battery. The one or more battery states can include a charging state and a discharging state. A healthy battery can release substantially no gas analyte while charging and/or discharging. As the health of the battery can begin to degrade over time, the battery can release gaseous species corresponding to the gas analyte while charging and/or discharging.

The system <NUM> includes a processor <NUM>. The processor <NUM> can include memory <NUM> for storing data and machine-readable instructions. Alternatively, the memory <NUM> can be external to the processor <NUM>, as shown in <FIG>. The processor <NUM> is configured to access the memory <NUM> and execute the machine-readable instructions stored in the memory <NUM>. In one example, the processor <NUM> is configured to access the memory <NUM> and execute the machine-readable instructions to perform one or more methods, as described herein. For example, the processor <NUM> is configured to receive the one or more sensor signals characterizing amounts of the gas analyte released by the gas source <NUM>. The processor <NUM> is configured to analyze the one or more sensor signals according to one or more threshold levels (bands). The one or more bands can be used to provide a determination of when a sensor signal generated by the gas sensor <NUM> has changed by a meaningful amount over a known baseline for the monitoring system <NUM>. The known baseline can be a function of the one or more sensor signals generated by the gas sensor <NUM>, for example, during a given gas source state of the gas source <NUM>.

The one or more bands include an N-sample moving average (MA), wherein N is an integer greater than one, an upper band at K times an N-sample standard deviation above the moving average (MA+Kα), wherein K is a number greater than one, and a lower band at K times an N-sample standard deviation below the moving average (MA-Kα). The N-sample MA can be calculated by summing the N-samples, and dividing the sum by N. In one example, the K and N parameters can be user definable parameters. The K parameter can correspond to a volatility factor. The parameter "α" is the N-sample standard deviation of the one or more sensor signals.

In one example, the K and N parameters can be set to compensate for noise in a given sensor signal generated by the gas sensor <NUM>. The processor <NUM> can be configured to differentiate noise from an actionable event as described herein. An actionable event can include, an audible alarm, a visual alarm, fire suppression, communication with another system, such as a safety system, or the like. In an even further example, the K and N parameters can be set to compensate for external factors, such as, temperature variations, humidity variations, both, or the like, which can introduce an error in the given sensor signal. Additionally or alternatively, the K and N parameters can be set to compensate for errors in the given sensor signal that can be caused by physical characteristics of the gas sensor <NUM>. For example, the K and N parameters can be set to compensate for gas sensor drift. The K and N parameters can be adjusted during an operating life of the gas sensor <NUM> such that changes in the physical characteristics of the gas sensor <NUM> that can cause drift to be introduced into the given sensor signal can be substantially mitigated. Accordingly, drift errors in the given sensor signal generated by the gas sensor <NUM> can be substantially mitigated by adjusting the K and N parameters.

A gas analyte baseline for the system <NUM> can be defined. The gas analyte baseline can characterize an amount of the gas analyte released by the gas source <NUM> over a period of time. The period of time can be related to one or more gas source states associated with the gas source <NUM>. The one or more gas source states can include an emitting gas state and a non-emitting gas state. Thus, in the emitting gas state, the source <NUM> can be releasing the gas analyte. In the example of the battery, while the battery is in the healthy state, a battery gas analyte baseline for the system <NUM> can be defined to characterize an amount of the gas analyte released by the battery during a cycle condition. A health battery can release substantially no gas analyte.

The gas sensor <NUM> is configured to generate one or more baseline sensor signals. The processor <NUM> is further configured to apply a MA to the one or more baseline sensor signals to determine a MA threshold. The MA of the one or more baseline sensor signals can be calculated by summing the one or more baseline sensor signals and dividing the sum by N, wherein N is a number of the one or more baseline sensor signals. The processor <NUM> can further be configured to determine an upper band threshold at K times a standard deviation of the one or more baseline sensor signals above the MA threshold. The processor <NUM> can further be configured to determine a lower band threshold at K times the standard deviation of the one or more baseline sensor signals below the MA threshold.

Additionally the processor <NUM> is configured to determine a sensitivity threshold to compensate for a false-positive event that can be caused by the N-sample standard deviation having a value substantially equal to zero (e.g., within a given percentage range and/or value range of zero). For example, when the N-sample standard deviation is substantially zero, the monitoring system <NUM> can generate a false response. A false-positive event can include one or more events that can cause the gas sensor <NUM> to generate a non-gas analyte related response (e.g., a response that is not based on the gas analyte released by the gas source <NUM>). Additional, as described herein, a false-positive event can include an event that can cause a gas sensor to generate a signal response based on one or more gases (or analytes) other than those released by a corresponding gas source. The sensitivity threshold is a function of the MA and a difference value between a minimum sensitivity MS and a reference. For example, the sensitivity threshold can be defined by the following equation: MA*(<NUM>-MS). The minimum sensitivity MS can be user definable.

The processor <NUM> is configured to compare the sensitivity threshold relative to one of the upper band threshold and the lower band threshold to identify a threshold that has a greatest value. The threshold with the greatest value is used as an alert threshold as described herein. A given alert threshold can be established that can be sufficiently separated from the MA threshold by comparing the sensitivity threshold relative to a band threshold. When the N-sample standard deviation has a value substantially equal to zero, a corresponding threshold can be substantially near the MA threshold, which can result in the false-positive event. However, by comparing the sensitivity threshold relative to the band threshold, the false-positive event can be substantially mitigated, for example, by providing sufficient separation between the MA threshold and the alert threshold.

The processor <NUM> can further be configured to monitor for the gas analyte during the emitting gas state of the gas source <NUM> and generate a monitored sensor signal characterizing an amount of the gas analyte released by the gas source <NUM> at an instant of time. The gas analyte source is a lithium battery, as the health of the battery can begin to degrade, the battery can release the gas analyte. The gas analyte can be detected during a cycle condition and can be interpreted as a warning that the battery is at risk of thermal runaway. The gas sensor <NUM> can be configured to monitor for the gas analyte during the cycle condition and generate a monitored sensor signal characterizing an amount of the gas analyte released by the battery at an instant of time. The processor <NUM> can further be configured to receive the monitored sensor signal. The processor <NUM> is further configured to compare the monitored sensor signal relative to an alert threshold. The processor <NUM> is further configured to generate an alert signal <NUM> based on a result of the comparison.

For example, the processor <NUM> can be configured to compare the monitored sensor signal relative to one of the sensitivity threshold and the lower band threshold. The processor <NUM> can be configured to generate the alert signal <NUM> in response to the monitored sensor signal being equal to or less than the one of the sensitivity threshold and the lower band threshold. Alternatively, the processor <NUM> can be configured to compare the monitored sensor signal relative to one of the sensitivity threshold and the upper band threshold. The processor <NUM> can be configured to generate the alert signal <NUM> in response to the monitored sensor signal being equal to or greater than one of the sensitivity threshold and the upper band threshold.

In an example which does not form part of the present invention, the processor <NUM> can further be configured to monitor for the gas analyte during the emitting gas state of the gas source <NUM> and generate a plurality of monitored sensor signals characterizing an amount of the gas analyte released by the gas source <NUM> over a corresponding period of time. The processor <NUM> can be configured to evaluate the plurality of monitored sensors signals to determine a number of the plurality of monitored sensor signals that is below a buffer threshold. The buffer threshold can compensate for a false-positive event in the monitoring system <NUM>. The buffer threshold can correspond to a value identifying a number of monitored sensor signals needed for generation of an alert signal. The processor <NUM> can be configured to compare a most recent monitored sensor signal of the plurality of monitored sensor signals relative to the alert threshold and generate the alert signal <NUM> based on a result of the comparison, as described herein.

The processor <NUM> can further be configured to update the alert threshold based on the monitored sensor signals over time. The processor <NUM> can be configured to hold (e.g., latch) a given monitored sensor signal as an alert threshold in response to the given monitored sensor signal crossing a current alert threshold. Thus, the processor <NUM> can stop the MA calculation and update the alert threshold. The processor <NUM> can further be configured to compare the given monitored sensor relative to the updated alert threshold and generate the alert signal <NUM> based on a result of the comparison, as described herein.

The processor <NUM> can further be configured to transmit the alert signal <NUM> to one or more systems to cause the one or more systems to take one or more preemptive measures. The one or more preemptive measures can include automatic shutdown (e.g., a system, a device, a battery, etc.), initiation of fire extinguisher controls, an audible alarm, a maintenance warning, a text message, e-mail, or the like. In the example of the battery, the gas analyte detected during the cycle condition can be interpreted as a warning that the battery can be at risk of thermal runaway. By providing an early warning, fires, explosions and injuries that can be caused in response to a thermal runaway condition can be substantially mitigated. Thus, the monitoring system <NUM> can detect a thermal runaway condition in a development stage. Accordingly, by detecting a thermal runaway scenario at the development stage, preventive measures can be implemented to prevent hazardous conditions and damage to the battery.

<FIG> depicts an example of a graph <NUM> demonstrating gas analyte generated sensor signal <NUM> plotted as a function of time. The sensor signal <NUM> can be generated by a gas sensor (e.g., the gas sensor <NUM>, as depicted in <FIG>) that can be configured to monitor a gas source (e.g., the gas source <NUM>) for a gas analyte condition. The graph <NUM> can include a horizontal axis <NUM> and a vertical axis <NUM>. The horizontal axis <NUM> can correspond to time and can be referred to herein as a time axis <NUM>. The vertical axis <NUM> can correspond to magnitudes of the sensor signal generated by the gas sensor over time, and can be referred to herein as a magnitude axis <NUM>. A first magnitude <NUM> of the magnitude axis <NUM> can correspond to an upper band threshold, a second magnitude <NUM> of the magnitude axis <NUM> can correspond to a MA threshold and a third magnitude <NUM> of the magnitude axis <NUM> can correspond to a lower band threshold. In alternative example, the third magnitude <NUM> can correspond to the sensitivity threshold, the first magnitude <NUM> can correspond to the upper band threshold and second magnitude <NUM> can correspond to the MA threshold.

The graph <NUM> can further include a first range <NUM>. The first range <NUM> can represent a period of time over the time axis <NUM> that the gas source is in a given state, such as a non-emitting gas state. In the example of the battery, the first range <NUM> can represent a period of time over the time axis <NUM> during which the battery can be in a healthy state, and thus can be releasing substantially no gas analyte. As depicted in <FIG>, over the first range <NUM>, the sensor signal <NUM> generated by the gas sensor can be substantially near the second magnitude <NUM> of the magnitude axis <NUM>. The graph <NUM> can further include a transition event <NUM>. The transition event <NUM> corresponds to an instance of time at which the gas source can be transitioning to another state, such as an emitting gas state. Thus at the transition event, the gas source can be releasing the gas analyte. In the example of the battery, the transition event corresponds to an instance of time at which the battery can begin to release the gas analyte. As more gas analyte is released by the gas source over the first range <NUM>, the sensor signal <NUM> generated by the gas sensor based on an amount of the gas analyte released by the gas source can begin to decrease toward the third magnitude <NUM> of the magnitude axis <NUM>, as depicted in <FIG>.

At an alert event <NUM> of the graph <NUM>, the magnitude of the sensor signal <NUM> can be substantially equal to the third magnitude <NUM>. The alert event <NUM> can correspond to a point in time at which the gas source can be emitting a substantial amount of the gas analyte. A substantial amount of the gas analyte can be referred to herein as an undesired amount of the gas analyte and/or hazardous amount of the gas analyte. The gas analyte source is a battery, the alert event <NUM> can correspond to a point in time which the battery can be emitting a substantial amount of the gas analyte. This can be interpreted as a thermal runaway risk. During the alert event <NUM>, an alert (e.g., the alert signal <NUM>, as depicted in <FIG>) can be generated (e.g., by the processor <NUM>, as depicted in <FIG>) to provide an early warning that unwanted and/or hazardous amounts of gas is being released by the gas source. The alert can provide early warning that the battery is at risk for thermal runaway.

The graph <NUM> can further include a second range <NUM>. The second range <NUM> can represent a period of time over the time axis <NUM> that the gas source is in the other state, such as the emitting gas state. In the second range <NUM>, one or more hazardous risks can develop, which if left unchecked can result in damage to a surrounding environment and/or the gas source. By providing an early warning at the alert event <NUM>, preemptive actions can be taken to mitigate the one or more hazardous risks. In the example of the battery, the second range <NUM> can represent a period of time over the time axis <NUM> during which the battery is in a degraded state. If the battery is continued to be operated in the degraded state, the battery can experience thermal runaway, which can lead to damage to the battery or a surrounding external environment. By providing the early warning at the alert event <NUM> thermal runaway preemptive actions as described herein can be taken to avoid the risk for thermal runaway.

<FIG> illustrates an example of a monitoring system <NUM> which does not form part of the present invention, that can be configured to monitor a gas source <NUM> for a gas analyte. In an example, the gas source <NUM> can include a battery. The system <NUM> can include a first gas sensor <NUM>. The first gas sensor <NUM> can be positioned relative to the gas source <NUM>, such that the first gas sensor <NUM> is within gas sensing range of the gas source <NUM>. The first gas sensor <NUM> can be configured to monitor the gas source <NUM> for a gas analyte condition. The gas analyte condition can be related to a state of the gas source <NUM> wherein the gas source <NUM> can be releasing the gas analyte. The system <NUM> can further include a second gas sensor <NUM>. In an example, the first and second gas sensors <NUM> and <NUM> can correspond to semiconductor gas sensors, such as the gas sensor <NUM>, as depicted in <FIG>.

The second gas sensor <NUM> can be configured to monitor for an ambient gas, for example, in an ambient environment <NUM>. The term "ambient environment" as used herein can refer to an area of space that can remain substantially free of the gas analyte released by the gas source <NUM> during one or more gas source states of the gas source <NUM>. The one or more gas source states can include an emitting gas state and a non-emitting gas state. The term "ambient gas" as used herein refers to any gas (or analyte) that can cause sensor signal responses in the first and second gas sensors <NUM> and <NUM>. In an example, the ambient gas can include paint and fuel vapors. The second gas sensor <NUM> can be positioned relative to the gas source <NUM>, such that the second gas sensor <NUM> is not within gas analyte sensing range of the gas source <NUM>. Thus, the second gas sensor <NUM> can be substantially free of susceptibility to the gas analyte released by the gas source <NUM>. Such an arrangement of the first and second gas sensors <NUM> and <NUM> can substantially mitigates false-positive events in the monitoring system <NUM>, as will be described in greater detail herein.

The first gas sensor <NUM> can be configured to generate a first sensor signal characterizing an amount of the gas analyte released by the gas source <NUM>. The first sensor signal can be generated based on a given electrical resistance of the common material of the first gas sensor <NUM>. The first gas sensor <NUM> can be configured to generate a plurality of first sensor signals characterizing amounts of the gas analyte during the one or more gas source states of the gas source <NUM> over a period of time. For example, during a charging cycle and/or discharging cycle, a healthy battery can release substantially no gas analyte. As the health of the battery can begin to degrade, the battery can release gaseous species corresponding to the gas analyte during the charging cycle and/or discharging cycle.

The second gas sensor <NUM> can be configured to generate a second sensor signal characterizing an amount of an ambient gas in the ambient environment <NUM>. The second sensor signal can be generated based on a given electrical resistance of a common material of the second gas sensor <NUM>. The second gas sensor <NUM> can be configured to generate a plurality of second sensor signals characterizing amounts of the ambient gas in the ambient environment during the one or more gas source states of the gas source <NUM> over the period of time.

In one example, the battery can be located within a housing of a ventilated enclosure (e.g., a battery enclosure <NUM>, as depicted in <FIG>, or a battery enclosure <NUM>, as depicted in <FIG>). The first gas sensor <NUM> can be located down-stream in the ventilated enclosure along the gas path relative to the battery (e.g., at an exhaust of the ventilated battery enclosure, such as an exhaust <NUM>, as depicted in <FIG> or an exhaust <NUM>, as depicted in <FIG>). The second gas sensor <NUM> can be located up-stream in the ventilated enclosure along a gas path relative to the battery (e.g., at an intake of the ventilated battery enclosure, such as an intake <NUM>, as depicted in <FIG>, or an intake <NUM>, as depicted in <FIG>).

In the ventilated enclosure, to remove heat generated by the battery, the intake can be configured to draw ambient air in the ambient environment <NUM>, which can include the ambient gas, and stream the ambient air down the gas path to the exhaust, which can be configured to expel the gas. As the ambient air is being streamed down the gas path along which the battery can be located, the heat generated by battery can be substantially removed to reduce an operating temperature of the battery. By positioning the first gas sensor <NUM> down-stream relative to the battery, the first gas sensor <NUM> can detect the gas analyte released by the battery when the gas analyte flows down the gas path, and is within sensing range of the first gas sensor <NUM>. However, since the first gas sensor <NUM> is positioned down-stream, the ambient gas drawn by the intake can cause the first gas sensor <NUM> to generate a sensor response.

The one or more methods described herein can substantially mitigate the monitoring systems <NUM> susceptibility to the ambient gas based on sensor signals generated by both the first and second gas sensors <NUM> and <NUM>. Thus, the one or methods described herein can reduce false-positive events in the monitoring system <NUM>, and thereby false warnings of thermal runaway conditions. A false-positive event can include one or more events that can cause the first gas sensor <NUM> to generate the first sensor signal in response to gases (or analytes) other than those released by the gas source <NUM>. In the example of the battery, false-positive events can cause the first gas sensor <NUM> to generate false responses, which can result in a false alert that the battery is at risk for thermal runaway. A false alert can result in thermal runway preventive measures to be implemented even though the battery could be not at risk of thermal runaway.

The monitoring system <NUM> can further include a processor <NUM>. The processor <NUM> can include memory <NUM> for storing data and machine-readable instructions. Alternatively, the memory <NUM> can be external to the processor <NUM>, as shown in <FIG>. The processor <NUM> can be configured to access the memory <NUM> and execute the machine-readable instructions stored in the memory <NUM>.

In one example, the processor <NUM> can be configured to access the memory <NUM> and execute the machine-readable instructions to perform the one or more methods described herein. The processor <NUM> can be configured to perform one or more methods that can compensate for effects that false-positive events can have on the monitoring system <NUM>. Thus, susceptibility of the monitoring system <NUM> to generating a false alert that the battery is at risk for thermal runaway can be substantially mitigated. Accordingly, the monitoring system <NUM> as described herein can be employed in open-battery environments, such as ventilated enclosures.

To compensate for the effects of false-positive events, the processor <NUM> can be configured to establish a baseline reference for the monitoring system <NUM> to compensate for any part-to-part variability between sensor signals generated by the first gas sensor <NUM> and the second gas sensor <NUM>. For example, the first gas sensor <NUM> and the second gas sensor <NUM> can be exposed to ambient air that is substantially free of both the ambient gas and the gas analyte for a given time period. The given time period can correspond to a minute, an hour, a day, or the like. The processor <NUM> can be configured to receive one or more first baseline sensor signals generated by the first gas sensor <NUM> and one or more second baseline sensor signals generated by the second gas sensor <NUM> during the given time period.

The processor <NUM> can further be configured to evaluate a slope of the one or more first baseline sensors signals. For example, the processor <NUM> can be configured to calculate the slope of each of the one or more first baseline sensors signals and compare the calculated slopes relative to a slope threshold. If the slope of a first baseline sensor signal is equal to or greater than the slope threshold, the first baseline sensor signal can be used for calculating a percent change in resistance in the first gas sensor <NUM> as described herein.

The processor <NUM> can further be configured to calculate the percent change in resistance of the first and second gas sensors <NUM> and <NUM> by applying a time MA to sensor signals. For example, the processor <NUM> can further be configured to apply the MA to the one or more first baseline sensor signals having a slope greater than the slope threshold to generate a first MA baseline. N-samples of the one or more first baseline sensor signals can be summed and divided by N to generate the first MA baseline, wherein N is a number of the one or more first baseline sensor signals. The processor <NUM> can be configured to apply a MA to the one or more second baseline sensors signals to generate a second MA baseline. N-samples of the one or more second baseline sensor signals can be summed and divided by N to generate the second MA baseline, wherein N is a number of the one or more second baseline sensor signals. The first and second MA baselines can be used to compensate for effects that the ambient gas can have on the monitoring system <NUM>.

The first gas sensor <NUM> can be configured to monitor the gas source <NUM> during the one or more gas source states. The first gas sensor <NUM> can be configured to monitor the gas source <NUM> during the emitting gas state for the gas analyte and generate a monitored sensor signal characterizing an amount of the gas analyte released by the gas source <NUM> at a given time. The given time can correspond to an instance of time wherein the gas source <NUM> can be releasing the gas analyte. In the example of the battery, a healthy battery can release substantially no gas analyte, for example, during a charging cycle and/or discharging cycle. As the health of the battery can begin to degrade, the battery can release the gas analyte during the charge cycle and/or discharge cycle. The first gas sensor <NUM> can be configured to monitor the battery during a cycle condition for the gas analyte and generate a monitored sensor signal characterizing an amount of the gas analyte released by the battery at a given time.

The processor <NUM> can further be configured to receive the monitored sensor signal. The processor <NUM> can further be configured to subtract from the first MA baseline the monitored sensor signal to generate a monitored sensor difference. The processor <NUM> can further be configured to divide the monitored sensor difference by the first MA baseline to determine a percentage change response relative to the first MA baseline. The second gas sensor <NUM> can be configured to monitor the ambient environment <NUM> during the emitting gas state for the ambient gas and generate a reference sensor signal characterizing the amount of the ambient gas in the ambient atmosphere <NUM> at the given time. In the example of the battery, the second gas sensor <NUM> can be configured to monitor the ambient environment <NUM> during the charging cycle and/or the discharging cycle. The processor <NUM> can further be configured to subtract from the second MA baseline the reference sensor signal to generate a reference sensor difference. The processor <NUM> can further be configured to divide the reference sensor difference by the second MA baseline to determine a percentage change response relative to the second MA baseline.

Accordingly, the processor <NUM> can be configured to determine a first sensor output (e.g., the monitored sensor difference) based upon a percent change of a first sensor signal (e.g., the monitored sensor signal) relative to a first averaged sensor signal (e.g., the second MA baseline), and a second sensor output (e.g., the reference sensor difference) based upon a percent change of the second sensor signal (e.g., the reference sensor signal) relative to a second averaged sensor signal (the second MA baseline).

The processor <NUM> can further be configured to subtract the percentage change response relative to the first MA baseline from the percentage change response relative to the second MA baseline to generate an overall difference sensor signal. Thus, the reference gas signal can be used to null out changes in gas concentration common to both the first and second sensors <NUM> and <NUM>. Accordingly, the ambient gas detected by both the first and second sensors <NUM> and <NUM> can be identified by the monitoring system <NUM>. The processor <NUM> can further be configured to compare the overall difference sensor signal relative to a threshold. The processor <NUM> can further be configured to generate an alert signal <NUM> based on a result of the comparison.

For example, the processor <NUM> can be configured to compare the overall difference sensor signal relative to the threshold to determine if the overall difference sensor signal is equal to or less than the threshold. Alternatively, the processor <NUM> can be configured to compare the overall difference sensor signal relative to the threshold to determine if the overall difference sensor signal is equal to or greater than the threshold. The processor <NUM> can be configured to generate the alert signal <NUM> in response to the overall difference gas signal being equal to or less (or alternatively greater) than the threshold. In one example, the threshold can include one of the sensitivity threshold, the upper-band threshold and the lower band threshold. These thresholds can be determined by the processor <NUM> according to the methods described herein.

For example, the processor <NUM> can further be configured to determine the upper band threshold at K times a standard deviation of the one or more first baseline sensor signals above the MA baseline. The processor <NUM> can further be configured to determine a lower band threshold at K times the standard deviation of the one or more first baseline sensor signals below the MA baseline. The processor <NUM> can be configured to determine the sensitivity threshold based on the MA of the one or more first baseline sensors signals and a difference value between a minimum sensitivity MS and a reference. The sensitivity threshold can be defined by the following equation: MA*(<NUM>-MS), wherein <NUM> can correspond to the reference.

The processor <NUM> can further be configured to compare the overall difference sensor signal to one of the sensitivity threshold and the lower band threshold. Alternatively, the processor <NUM> can be configured to compare the overall difference sensor signal to one of the sensitivity threshold and the upper band threshold. The processor <NUM> can be configured to generate the alert signal <NUM> in response to the overall difference sensor signal being equal to or less than one of the sensitivity threshold and the lower band threshold (or being equal to or greater than one of the sensitivity threshold and the upper band threshold).

The alert signal <NUM> can be transmitted to one or more systems to cause the one or more systems to take one or more preemptive measures as described herein. In the example of the battery, the gas analyte detected during the cycle condition can be interpreted as a warning that the battery can be at risk of thermal runaway. By providing an early warning, fires, explosions and injuries that can be caused in response to a thermal runaway condition can be substantially mitigated. Thus, the monitoring system <NUM> can detect a thermal runaway condition in a development stage. Accordingly, by detecting a thermal runaway scenario at the development stage, preventive measures can be implemented to prevent hazardous conditions and damage to the battery.

The monitoring system <NUM> can be configured with one or more enclosures. In one example, the enclosure can be a battery enclosure <NUM>, such as depicted in <FIG>. The battery enclosure <NUM> can include a housing <NUM> to house the battery (not depicted in <FIG>), the first gas sensor <NUM> and the second gas sensor <NUM>. In <FIG>, the second gas sensor <NUM> can be positioned relative to the battery, such that second gas sensor <NUM> can be substantially free of susceptibility to the gas analyte released by the battery. In an example, the processor <NUM> can be positioned outside the battery enclosure <NUM>. Alternatively, the processor <NUM> can be positioned within the battery enclosure <NUM>.

In another example, the enclosure can be a battery enclosure <NUM>, such as depicted in <FIG>. The battery enclosure <NUM> can include a housing <NUM> to house the battery (not depicted in <FIG>). The battery enclosure <NUM> can include an intake <NUM>. The intake <NUM> can be configured to draw ambient air into the housing <NUM> to cool the battery. The second gas sensor <NUM> can be positioned within the intake <NUM>. The battery enclosure <NUM> can further include an exhaust <NUM>. The exhaust <NUM> can be configured to expel gas in the housing <NUM> into a surrounding environment. The expelled gas can include the ambient air drawn by the intake <NUM>, the gas analyte emitted by the battery or a mixture thereof. The first gas sensor <NUM> can be positioned within the exhaust <NUM>. In <FIG>, the second gas sensor <NUM> can be positioned relative to the battery such that second gas sensor <NUM> can be substantially free of susceptibility to the gas analyte released by the battery <NUM>. In an example, the processor <NUM> can be positioned outside the battery enclosure <NUM>. Alternatively, the processor <NUM> can be positioned within the battery enclosure <NUM>.

In an even further example, the enclosure can be a lithium-ion battery charging and storage enclosure <NUM>, such as depicted in <FIG>. The lithium-ion battery charging and storage enclosure <NUM> can include a housing <NUM> to house the battery (not depicted in <FIG>). The battery in this example can correspond to a lithium-ion battery. The lithium-ion battery charging and storage enclosure <NUM> can include an intake <NUM>. The intake <NUM> can be configured to draw ambient air into the housing <NUM> to cool the lithium-ion battery. The second gas sensor <NUM> can be positioned within the intake <NUM>. The lithium-ion battery charging and storage enclosure <NUM> can further include an exhaust <NUM>. The exhaust <NUM> can be configured expel gas in the housing <NUM> into a surrounding environment. The expelled gas can include the ambient air drawn by the intake <NUM>, the gas analyte emitted by the lithium-ion battery or a mixture thereof. The first gas sensor <NUM> can be positioned within the exhaust <NUM>. In <FIG>, the second gas sensor <NUM> can be positioned relative to the lithium-ion battery such that second gas sensor <NUM> can be substantially free of susceptibility to the gas analyte released by the lithium-ion battery. In an example, the processor <NUM> can be positioned outside the lithium-ion battery charging and storage enclosure <NUM>. Alternatively, the processor <NUM> can be positioned within the lithium-ion battery charging and storage enclosure <NUM>.

In another example, the battery enclosure can be a shipping container <NUM>, such as depicted in <FIG>. The shipping container <NUM> can house the battery (not depicted in <FIG>), the first gas sensor <NUM> and the second gas sensor <NUM>. In <FIG>, the second gas sensor <NUM> can be positioned relative to the battery such that second gas sensor <NUM> can be substantially free of susceptibility to the gas analyte released by the battery. In an example, the processor <NUM> can be positioned outside the shipping container <NUM>. Alternatively, the processor <NUM> can be positioned within the shipping container <NUM>.

In view of the foregoing structural and functional features described above, methods that can be implemented will be better appreciated with reference to <FIG>. While, for purposes of simplicity of explanation, the methods of <FIG> are depicted and described as executing serially, it is to be understood and appreciated that such methods are not limited by the illustrated order, as some aspects could, in other embodiments, occur in different orders and/or concurrently with other aspects from that shown and described herein. Moreover, not all illustrated features may be required to implement the methods. The methods or portions thereof can be implemented as instructions stored in one or more non-transitory storage media as well as be executed by a processing resource (e.g., the processor <NUM>, as depicted in <FIG> and/or the processor <NUM>, as depicted in <FIG>).

<FIG> depicts an example of a method <NUM> for monitoring a gas source for a gas analyte, useful to understand the present invention. For example, the method <NUM> can be implemented by the monitoring system <NUM>, as depicted in <FIG>. The method begins at <NUM> by monitoring a gas source for a gas analyte. At <NUM>, a sensor signal characterizing an amount of the gas analyte being released by the gas source can be generated. At <NUM>, the sensor signal can be received. At <NUM>, the sensor signal can be evaluated relative to an alert threshold. At <NUM>, an alert signal can be generated based on a result of the evaluation.

<FIG> depicts another example of a method <NUM> for monitoring a gas source for a gas analyte, which is not part of the present invention. For example, the method <NUM> can be implemented by the monitoring system <NUM>, as depicted in <FIG>. The method begins at <NUM> by monitoring a gas source for release of a gas analyte. At <NUM>, an ambient environment can be monitored for a presence of an ambient gas. At <NUM>, a first sensor signal characterizing an amount of the gas analyte being released by the gas source can be generated. At <NUM>, a second sensor signal characterizing an amount of the ambient gas present in the ambient environment can be generated. At <NUM>, a first sensor output can be determined based upon a percent change of the first sensor signal relative to a first averaged sensor signal. At <NUM>, a second sensor output can be determined based upon a percent change of the second sensor signal relative to a second averaged sensor signal. At <NUM>, the first sensor output can be evaluated relative to second sensor output. At <NUM>, an alert signal can be generated based on a result of the evaluation.

<FIG> depicts an even further example of a method <NUM> for monitoring a gas source for a gas analyte, which is not part of the present invention. For example, the method <NUM> can be implemented by the monitoring system <NUM>, as depicted in <FIG>. The method begins at <NUM>, by receiving one or more baseline sensors signals generated by a first gas sensor. At <NUM>, one or more baseline reference sensor signals generated by a second gas sensor can be received. At <NUM>, a slope of each of the one or more baseline sensors signals can be evaluated. At <NUM>, if the slope of a given baseline sensor signal is equal to or greater than the slope threshold, the method can proceed to <NUM>, otherwise the method can proceed to <NUM>. At <NUM>, the given baseline sensor signal can be excluded for further use in the method <NUM>. At <NUM>, a MA can be applied to the one or more monitored baseline sensor signals having a slope greater than the slope threshold to generate a first MA baseline. N-samples of the one or more baseline sensor signals can be summed and divided by N to generate the first MA baseline, wherein N is a number of the one or more baseline sensor signals. At <NUM>, a MA can be applied to the one or more baseline reference sensors signals to generate a second MA baseline. N-samples of the one or more baseline references sensor signals can be summed and divided by N to generate the second MA baseline, wherein N is a number of the one or more baseline reference sensor signals. The first and second MA baselines can be used to compensate for effects that the ambient gas can have on the monitoring system <NUM>.

At <NUM>, the first gas sensor can be configured to monitor the gas source for the gas analyte and generate a monitored sensor signal characterizing the amount of the gas analyte released by the gas source at a given time, for example, during the given state of the gas source. The given time can correspond to an instance of time wherein the gas source can be releasing the gas analyte. Furthermore, at <NUM>, the monitored sensor signal can be subtracted from the first MA baseline to generate a monitored sensor difference. Moreover, at <NUM>, the monitored sensor difference can be divided by the first MA baseline to determine a percentage change response relative to the first MA baseline. At <NUM>, the second gas sensor can be configured to monitor for an ambient gas in an ambient environment and generate a reference sensor signal characterizing the amount of the ambient gas at the given time, for example during a given state of the gas source. Furthermore, at <NUM>, the reference sensor signal can be subtracted from the second MA baseline to generate a reference sensor difference. Moreover, at <NUM>, the reference sensor difference can be divided by the second MA baseline to determine a percentage change response relative to the second MA baseline.

At <NUM>, the percentage change response relative to the first MA baseline can be subtracted from the percentage change response relative to the second MA baseline to generate an overall difference sensor signal. At <NUM>, the overall difference sensor signal can be compared relative to an alert threshold. If the overall difference sensor signal is greater than the alert threshold, the method can proceed to <NUM>, otherwise the method can proceed to <NUM>. At <NUM>, an alert (e.g., the alert signal <NUM>, as depicted in <FIG>) can be generated. At <NUM>, no alert can be generated. The alert can be transmitted to one or more systems to cause the one or more systems to take one or more preemptive measures as described herein.

It is noted that the terms "substantially" and "about" may be utilized herein to represent an inherent degree of uncertainty that can be attributed to any quantitative comparison, value, measurement, or other representation. These terms are also utilized herein to represent a degree by which a quantitative representation may vary from a stated reference without resulting in a change in the basic function of the subject matter at issue.

Claim 1:
A method (<NUM>, <NUM>) comprising:
monitoring (<NUM>) a gas analyte using a monitoring system (<NUM>) capable of monitoring lithium ion battery off-gas, wherein the gas analyte comprises a lithium ion battery electrolyte material released by one or more lithium ion batteries;
generating (<NUM>) a sensor signal (<NUM>) characterizing an amount of the gas analyte;
receiving (<NUM>) the sensor signal;
evaluating (<NUM>) the sensor signal relative to a threshold, wherein the sensor signal is generated during a first state of the one or more lithium ion batteries, the first state corresponding to a state wherein the one or more lithium ion batteries are releasing the gas analyte;
generating one or more baseline sensor signals characterizing an amount of the gas analyte being released during a second state of the one or more lithium ion batteries, the second state corresponding to a state wherein the one or more lithium ion batteries are not releasing the gas analyte;
applying a moving average (MA) to the one or more baseline sensor signals to determine a MA threshold;
determining a given band threshold at K times the standard deviation of the one or more baseline sensor signals one of above and below the MA threshold;
determining a sensitivity threshold based on the MA threshold and a difference value between a minimum sensitivity and a reference;
comparing the sensitivity threshold relative to the given band to identify a threshold having a greatest value;
wherein evaluating the sensor signal relative to the threshold comprises evaluating the sensor signals relative the threshold having the greatest value; and
generating (<NUM>) an alert signal based on a result of the evaluation.