Patent ID: 12233738

Representative embodiments of this disclosure are shown by way of non-limiting example in the drawings and are described in additional detail below. It should be understood, however, that the novel aspects of this disclosure are not limited to the particular forms illustrated in the above-enumerated drawings. Rather, the disclosure is to cover all modifications, equivalents, combinations, subcombinations, permutations, groupings, and alternatives falling within the scope of this disclosure as encompassed, for instance, by the appended claims.

DETAILED DESCRIPTION

This disclosure is susceptible of embodiment in many different forms. Representative examples of the disclosure are shown in the drawings and herein described in detail with the understanding that these embodiments are provided as an exemplification of the disclosed principles, not limitations of the broad aspects of the disclosure. To that end, elements and limitations that are described, for example, in the Abstract, Introduction, Summary, Description of the Drawings, and Detailed Description sections, but not explicitly set forth in the claims, should not be incorporated into the claims, singly or collectively, by implication, inference, or otherwise. Moreover, the drawings discussed herein may not be to scale and are provided purely for instructional purposes. Thus, the specific and relative dimensions shown in the Figures are not to be construed as limiting.

For purposes of the present detailed description, unless specifically disclaimed: the singular includes the plural and vice versa; the words “and” and “or” shall be both conjunctive and disjunctive; the words “any” and “all” shall both mean “any and all”; and the words “including,” “containing,” “comprising,” “having,” and permutations thereof, shall each mean “including without limitation.” Moreover, words of approximation, such as “about,” “almost,” “substantially,” “generally,” “approximately,” and the like, may each be used herein in the sense of “at, near, or nearly at,” or “within 0-5% of,” or “within acceptable manufacturing tolerances,” or any logical combination thereof, for example. Lastly, directional adjectives and adverbs, such as fore, aft, inboard, outboard, starboard, port, vertical, horizontal, upward, downward, front, back, left, right, etc., may be with respect to a motor vehicle, such as a forward driving direction of a motor vehicle, when the vehicle is operatively oriented on a horizontal driving surface.

Referring now to the drawings, wherein like reference numbers refer to like features throughout the several views, there is shown inFIG.1a representative automobile, which is designated generally at10and portrayed herein for purposes of discussion as a sedan-style, electric-drive passenger vehicle. The illustrated automobile10—also referred to herein as “motor vehicle” or “vehicle” for short—is merely an exemplary application with which novel aspects of this disclosure may be practiced. In the same vein, incorporation of the present concepts into an all-electric vehicle powertrain should also be appreciated as a non-limiting implementation of disclosed features. As such, it will be understood that aspects and features of this disclosure may be applied to other powertrain architectures, may be implemented for any logically relevant type of vehicle, and may be utilized for both DC and AC-based EVCS. Moreover, only select components of the motor vehicles and battery systems are shown and described in additional detail herein. Nevertheless, the vehicles and vehicle systems discussed below may include numerous additional and alternative features, and other available peripheral components, for carrying out the various methods and functions of this disclosure.

The representative vehicle10ofFIG.1is originally equipped with a vehicle telecommunication and information (“telematics”) unit14that wirelessly communicates, e.g., via cell towers, base stations, mobile switching centers, satellite service, etc., with a remotely located or “off-board” cloud computing host service24(e.g., ONSTAR®). Some of the other vehicle hardware components16shown generally inFIG.1include, as non-limiting examples, a touchscreen video display device18, a microphone28, audio speakers30, and assorted input controls32(e.g., buttons, knobs, pedals, switches, touchpads, joysticks, touchscreens, etc.). These hardware components16function, in part, as a human/machine interface (HMI) to enable a user to communicate with the telematics unit14and other system components within and external to the vehicle10. Microphone28provides a vehicle occupant with means to input verbal or other auditory commands; the vehicle10may be equipped with an embedded voice-processing unit utilizing audio filtering, editing, and analysis modules. Conversely, the speaker(s)30provide audible output to a vehicle occupant and may be either a stand-alone speaker dedicated for use with the telematics unit14or may be part of an audio system22. The audio system22is operatively connected to a network connection interface34and an audio bus20to receive analog information, rendering it as sound, via one or more speaker components.

Communicatively coupled to the telematics unit14is a network connection interface34, suitable examples of which include twisted pair/fiber optic Ethernet switch, parallel/serial communications bus, local area network (LAN) interface, controller area network (CAN) interface, media-oriented system transfer (MOST) interface, local interconnection network (LIN) interface, and the like. Other appropriate communication interfaces may include those that conform with ISO, SAE, and/or IEEE standards and specifications. The network connection interface34enables the vehicle hardware16to send and receive signals with one another and with various systems and subsystems both within or “resident” to the vehicle body12and outside or “remote” from the vehicle body12. This allows the vehicle10to perform various vehicle functions, such as modulating powertrain output, governing operation of the vehicle's transmission, selectively engaging the friction and regenerative brake systems, controlling vehicle steering, regulating charge and discharge and conditioning of the vehicle's battery modules, and other automated functions. For instance, telematics unit14may receive and transmit signals and data to/from a Powertrain Control Module (PCM)52, an Advanced Driver Assistance System (ADAS) module54, an Electronic Battery Control Module (EBCM)56, a Steering Control Module (SCM)58, a Brake System Control Module (BSCM)60, and assorted other vehicle modules, such as a transmission control module (TCM), engine control module (ECM), Sensor System Interface Module (SSIM), navigation system control (NSC) module, etc.

With continuing reference toFIG.1, telematics unit14is an onboard computing device that provides a mixture of services, both individually and through its communication with other networked devices. This telematics unit14is generally composed of one or more processors40, each of which may be embodied as a discrete microprocessor, an application specific integrated circuit (ASIC), or a dedicated control module. Vehicle10may offer centralized vehicle control via a central processing unit (CPU)36that is operatively coupled to a real-time clock (RTC)42and one or more electronic memory devices38, each of which may take on the form of a CD-ROM, magnetic disk, IC device, flash memory, semiconductor memory (e.g., various types of RAM or ROM), etc.

Long-range vehicle communication capabilities with remote, off-board networked devices may be provided via one or more or all of a cellular chipset/component, a navigation and location chipset/component (e.g., global positioning system (GPS) transceiver), or a wireless modem, all of which are collectively represented at44. Close-range wireless connectivity may be provided via a short-range wireless communication device46(e.g., a BLUETOOTH® unit or near field communications (NFC) transceiver), a dedicated short-range communications (DSRC) component48, and/or a dual antenna50. It should be understood that the vehicle10may be implemented without one or more of the components depicted inFIG.1or, optionally, may include additional components and functionality as desired for a particular end use. The various communication devices described above may be configured to exchange data as part of a periodic broadcast in a vehicle-to-vehicle (V2V) communication system or a vehicle-to-everything (V2X) communication system, e.g., Vehicle-to-Infrastructure (V2I), Vehicle-to-Pedestrian (V2P), Vehicle-to-Device (V2D), etc.

CPU36receives sensor data from one or more sensing devices that use, for example, photo detection, radar, laser, ultrasonic, optical, infrared, or other suitable technology for executing an automated driving operation, including short range communications technologies such as DSRC or Ultra-Wide Band (UWB). In accord with the illustrated example, the automobile10may be equipped with one or more digital cameras62, one or more range sensors64, one or more vehicle speed sensors66, one or more vehicle dynamics sensors68, and any requisite filtering, classification, fusion and analysis hardware and software for processing raw sensor data. The type, placement, number, and interoperability of the distributed array of in-vehicle sensors may be adapted, singly or collectively, to a given vehicle platform for achieving a desired level of autonomous vehicle operation.

Digital camera62may use a charge coupled device (CCD) sensor or other suitable optical sensor to generate images indicating a field-of-view of the vehicle10, and may be configured for continuous image generation, e.g., at least about 35+ images per second. By way of comparison, range sensor64may emit and detect reflected radio, infrared, light-based or other electromagnetic signals (e.g., short-range radar, long-range radar, EM inductive sensing, Light Detection and Ranging (LIDAR), etc.) to detect, for example, presence, geometric dimensions, and/or proximity of a target object. Vehicle speed sensor66may take on various forms, including wheel speed sensors that measure wheel speeds, which are then used to determine real-time vehicle speed. In addition, the vehicle dynamics sensor68may be in the nature of a single-axis or a triple-axis accelerometer, an angular rate sensor, an inclinometer, etc., for detecting longitudinal and lateral acceleration, yaw, roll, and/or pitch rates, or other dynamics related parameters. Using data from the sensing devices62,64,66,68, the CPU36identifies surrounding driving conditions, determines roadway characteristics and surface conditions, identifies target objects within a detectable range of the vehicle, determines attributes of the target object, such as size, relative position, distance, angle of approach, relative speed, etc., and executes automated control maneuvers based on these executed operations.

To propel the electric-drive vehicle10, an electrified powertrain is operable to generate and deliver tractive torque to one or more of the vehicle's road wheels26. The powertrain is generally represented inFIG.1by a rechargeable energy storage system (RESS), which may be in the nature of a chassis-mounted traction battery pack70, that is operatively connected to an electric traction motor78. The traction battery pack70is generally composed of one or more battery modules72each having a stack of battery cells74, such as lithium ion, lithium polymer, or nickel metal hydride battery cells of the pouch, can, or prismatic type. One or more electric machines, such as traction motor/generator (M) units78, draw electrical power from and, optionally, deliver electrical power to the RESS's battery pack70. A dedicated power inverter module (PIM)80electrically connects the battery pack70to the motor/generator (M) unit(s)78and modulates that transmission of electrical current therebetween.

The battery pack70may be configured such that module management, including cell sensing, thermal management, and module-to-host communications functionality, is integrated directly into each battery module72and performed wirelessly via a wireless-enabled cell monitoring unit (CMU)76. The CMU76may be a microcontroller-based, printed circuit board (PCB)—mounted sensor array. Each CMU76may have a GPS transceiver and RF capabilities and may be packaged on or in a battery module housing. The battery module cells74, CMU76, housing, coolant lines, busbars, etc., collectively define the module assembly.

Presented inFIG.2is an exemplary electrochemical device in the form of a rechargeable lithium-class battery110that powers a desired electrical load, such as automobile10ofFIG.1, and offers fast charging capabilities, such as DCFC. Battery110includes a pair of electrically conductive electrodes, namely a first (negative or anode) working electrode122and a second (positive or cathode) working electrode124, packaged inside a protective outer housing120. In at least some configurations, the battery housing120may be an envelope-like pouch that is formed of aluminum foil or other suitable sheet material. Both sides of a metallic pouch may be coated with a polymeric finish to insulate the metal from the internal cell elements and from adjacent cells, if any. Alternatively, the battery housing (or “cell casing”)120may take on a cylindrical metal can configuration, i.e., for cylindrical battery cell configurations, or a polyhedral metal box configuration, i.e., for prismatic battery cell configurations. Reference to either working electrode122,124as an “anode” or “cathode” or, for that matter, as “positive” or “negative” does not limit the electrodes122,124to a particular polarity as the system polarity may change depending on whether the battery110is being operated in a charge mode or a discharge mode. AlthoughFIG.2illustrates a single battery cell unit inserted within the battery housing120, it should be appreciated that the housing120may stow therein a stack of multiple cell units (e.g., five to five thousand cells or more).

With continuing reference toFIG.2, anode electrode122may be fabricated with an active anode electrode material that is capable of incorporating lithium ions during a battery charging operation and releasing lithium ions during a battery discharging operation. In at least some implementations, the anode electrode122is manufactured, in whole or in part, from a lithium metal, such as lithium-aluminum (LiAl) alloy materials with an Li/Al atomic ratio in a range from 0 at. %≤Li/Al<70 at. %, and/or aluminum alloys with Al atomic ratio >50 at. % (e.g., lithium metal is smelt). Additional examples of suitable active anode electrode materials include carbonaceous materials (e.g., graphite, hard carbon, soft carbon etc.), silicon, silicon-carbon blended materials (silicon-graphite composite), Li4Ti5O12, transition-metals (alloy types, e.g., Sn), metal oxide/sulfides (e.g., SnO2, FeS and the like), etc.

Cathode electrode124may be fabricated with an active cathode electrode material that is capable of supplying lithium ions during a battery charging operation and incorporating lithium ions during a battery discharging operation. The cathode124material may include, for instance, lithium transition metal oxide, phosphate, or silicate, such as LiMO2 (M=Co, Ni, Mn, or combinations thereof); LiM2O4 (M=Mn, Ti, or combinations thereof), LiMPO4 (M=Fe, Mn, Co, or combinations thereof), and LiMxM′2-xO4 (M, M′=Mn or Ni). Additional examples of suitable active cathode electrode materials include lithium nickel cobalt manganese oxide (NCM), lithium nickel cobalt aluminum oxide (NCA), lithium nickel cobalt manganese aluminum oxide (NCMA), and other lithium transition-metal oxides.

Disposed inside the battery housing120between the two electrodes122,124is a porous separator126, which may be in the nature of a microporous or nanoporous polymeric separator. The porous separator126may include a non-aqueous fluid electrolyte composition and/or solid electrolyte composition, collectively designated130, which may also be present in the negative electrode122and the positive electrode124. A negative electrode current collector132may be positioned on or near the negative electrode122, and a positive electrode current collector134may be positioned on or near the positive electrode124. The negative electrode current collector132and positive electrode current collector134respectively collect and move free electrons to and from an external circuit140. An interruptible external circuit140with a load142connects to the negative electrode122, through its respective current collector132and electrode tab136, and to the positive electrode124, through its respective current collector134and electrode tab138. Separator126may be a sheet-like structure that is composed of a porous polyolefin membrane, e.g., with a porosity of about 35% to 65% and a thickness of approximately 25-30 microns. Electrically non-conductive ceramic particles (e.g., silica) may be coated onto the porous membrane surfaces of the separators126.

The porous separator126may operate as both an electrical insulator and a mechanical support structure by being sandwiched between the two electrodes122,124to prevent the electrodes from physically contacting each other and, thus, the occurrence of a short circuit. In addition to providing a physical barrier between the electrodes122,124, the porous separator126may provide a minimal resistance path for internal passage of lithium ions (and related anions) during cycling of the lithium ions to facilitate functioning of the battery110. For some optional configurations, the porous separator126may be a microporous polymeric separator including a polyolefin. The polyolefin may be a homopolymer, which is derived from a single monomer constituent, or a heteropolymer, which is derived from more than one monomer constituent, and may be either linear or branched. In a solid-state battery, the role of the separator may be partially/fully provided by a solid electrolyte layer.

Operating as a rechargeable energy storage system (RESS), battery110generates electric current that is transmitted to one or more loads142operatively connected to the external circuit140. While the load142may be any number of electrically powered devices, a few non-limiting examples of power-consuming load devices include an electric motor for a hybrid or full-electric vehicle, a laptop or tablet computer, a cellular smartphone, cordless power tools and appliances, portable power stations, etc. The battery110may include a variety of other components that, while not depicted herein for simplicity and brevity, are nonetheless readily available. For instance, the battery110may include one or more gaskets, terminal caps, tabs, battery terminals, and other commercially available components or materials that may be situated on or in the battery110. Moreover, the size and shape and operating characteristics of the battery110may vary depending on the particular application for which it is designed.

Discussed below are thermal preconditioning protocols for priming electrochemical devices for a fast-charging event, such as recharging an in-vehicle traction battery pack via DCFC. Dynamic target temperature selection based on historical driving behavior and available charge power at the destination fast charger, for example, allows a battery system to optimally use available system energy to bring the battery's operating temperature to within a predicted “most efficient” charging temperature zone. The preconditioning feature may be automatically triggered and stopped in order to complete the thermal conditioning without wasting vehicle energy. The thermal preconditioning algorithm may perform the following high-level tasks: set a target battery temperature based on a present SOV or SOC and an estimated SOV or SOC of the battery upon arrival at the charger; estimate the time it will take to thermally condition the battery to the target temperature by modelling battery and thermal behavior during the trip to the charger; and decide whether and when to start conditioning based on the distance to charger versus the time to condition.

With reference next to the flow chart ofFIG.3, an improved method or control strategy for preconditioning an electrochemical device, such as vehicle battery pack70ofFIG.1or lithium-class battery110ofFIG.2, using a fast-charging system, such as a Level 3 DC fast charger, is generally described at200in accordance with aspects of the present disclosure. Some or all of the operations illustrated inFIG.3, and described in further detail below, may be representative of an algorithm that corresponds to processor-executable instructions that are stored, for example, in main or auxiliary or remote memory (e.g., memory device38or host service24database ofFIG.1), and executed, for example, by an electronic controller, processing unit, logic circuit, or other module or device or network of modules/devices (e.g., CPU36and/or cloud computing service24ofFIG.1), to perform any or all of the above and below described functions associated with the disclosed concepts. It should be recognized that the order of execution of the illustrated operation blocks may be changed, additional operation blocks may be added, and some of the described operations may be modified, combined, or eliminated.

Method200ofFIG.3begins at START terminal block201with memory-stored, processor-executable instructions for a programmable controller or control module or similarly suitable processor to call up an initialization procedure for scheduling a battery recharge event at a selected battery charging station. System evaluation for provisioning this routine may be executed in real-time, near real-time, continuously, systematically, sporadically, and/or at regular intervals, for example, each 10 or 100 milliseconds during normal and ongoing operation of the motor vehicle10. As yet another option, terminal block201may initialize responsive to a user command prompt, a resident vehicle controller prompt, or a broadcast prompt signal received from an “off-board” centralized vehicle services system (e.g., host cloud computing service24). As a non-limiting example, battery preconditioning and recharge may be enabled from a downloadable mobile software application (“app”), an HMI interface within the vehicle, or by an in-vehicle control module, such as the ADAS or EBCM modules54,56ofFIG.1. Telematics unit14in electric-drive vehicle10ofFIG.1, for example, may display a notification that the traction battery pack70has a low state of charge; the driver may press a soft button to schedule a recharge event and select a desired charging station from a drop-down list or a navigation map. Upon completion of the control operations presented inFIG.3, the method200may advance to END terminal block229and temporarily terminate or, optionally, may loop back to terminal block201and run in a continuous loop.

Upon receipt of a request to schedule a recharge event, method200responsively advances to CHARGER POWER data input block203to ascertain the operating characteristics of the selected battery charging station. These operating characteristics may include a power rating (e.g., in kW), a voltage output (e.g., in VDC), charging cable plug compatibility (for plug-in vehicles), communication network interoperability (e.g., NFC, DSRC, or BLUETOOTH® compatibility), etc. Returning toFIG.1as a non-limiting example, CPU36and EBCM56may collaboratively retrieve this information by wirelessly polling the selected charging station, pulling the data from the cloud24, or assembling the data from open street map sources using resident navigation software. A lack of compatibility between the host vehicle and the selected charging station may result in the driver being prompted to select another available charging station.

In addition to identifying charger power characteristics at data input block203, method200may also automatically respond to a requested recharge event by evaluating select vehicle operating characteristics for running a prediction model at PRECONDITIONING CONDITIONS subroutine block205. CPU36ofFIG.1, for example, may wirelessly poll cell monitoring unit76to retrieve real-time or near real-time diagnostic information for the traction battery pack70. From this data, the CPU36is able to ascertain whether or not a system fault exists within the battery system that is likely to prevent preconditioning of the pack70. One example of such a battery system fault includes a contactor fault within the traction power inverter module80that precludes the transfer of current to/from the pack70. Another example includes a pack sensor fault or an SSIM fault that precludes accurate analysis of pack SOV/SOC. When executing predefined subroutine block205, CPU36may also poll PCM52and EBCM56to retrieve real-time or near real-time propulsion system and battery system information to identify an active vehicle state variable, if any, that is likely to prevent battery preconditioning. Checking vehicle state variables may include confirming that the vehicle10is in a “propulsion system active” mode or confirming that the current SOC of the traction battery pack70is above a predefined minimum value (e.g., to ensure pack conditioning can be implemented without impeding the vehicle's ability to reach the charging station). Upon confirming that there are no existing system faults nor any active vehicle state variables that would impede battery conditioning, method200proceeds to predict battery SOV/SOC, estimate target preconditioning temps, and project battery preconditioning times.

Method200advances from predefined subroutine block205to PREDICTED SOV/SOC subroutine block207to estimate a state of voltage and/or a state of charge for the rechargeable battery upon arrival at the selected charging station. SOV may be used to replace SOC during system evaluation as SOV may be a more accurate indicator of when a battery is likely to shutdown (e.g., under heavy loads, shutdown may occur before SoC reaches 0%). SOV may be considered a naturally adaptive measure for end-of-range prediction as it indirectly describes a battery's power delivery capabilities using terminal voltage behavior under loaded conditions. State of voltage monitoring for a traction battery pack may describe the pack's real-time power capability by measuring the relative stiffness of the battery system; low battery stiffness, which is indicative of a large voltage drops under load, may suggest high internal resistances and poor power capability.

Predicting a battery's SOV/SOC at subroutine block207may involve ascertaining a real-time or near real-time SOV/SOC, forecasting an SOV/SOC battery expenditure associated with an estimated travel time to the charging station location, and calculating the predicted SOV/SOC as the mathematical difference between the present SOV/SOC and the SOV/SOC battery expenditure. Real-time/near real-time SOV/SOC at a subject vehicle's current location is assessed at CURRENT SOV/SOC data input block209. In this instance, determining the present SOV for a battery may include receiving measured voltage data from one or more voltage sensors operatively attached to the battery, and executing an SOV modeling algorithm (e.g., fuzzy logic, zero-phase equivalent, etc.) based, at least in part, on the measured voltage data to determine the present SOV. To estimate an SOV battery expenditure, the CPU36may retrieve a memory-stored lookup table with a time array of data that associates a series of battery use times with corresponding SOV usage, e.g., as calibrated to the make/model of a specific pack. While discussed herein with reference to state of voltage, it is envisioned that alternative system models and attendant control processes may be derived to employ state of charge, state of energy, or other suitable measure of state of health.

With continuing reference toFIG.3, the method200utilizes the charger power characteristics output from data input block203and the predicted SOV/SOC output from subroutine block207to estimate an optimized temperature for preconditioning a battery, as indicated at DCFC TARGET TEMPERATURE database block211. The target preconditioning temperature is devised to enhance the recharge event of the battery. In particular, a target temperature optimizes a scheduled recharging for a battery by minimizing a total charge time for the recharge event while concomitantly minimizing a total system energy expenditure to precondition the battery without damaging the individual battery cells or any of the electrical hardware in the high-voltage electrical system connecting the battery to its various loads. In an example, CPU36accesses a set of memory-stored lookup tables, each of which associates a series of battery temperatures with corresponding SOV values. Each lookup table may be associated with a particular set of charger characteristics (e.g., power rating and/or voltage output). Generally speaking, the method200is attempting to identify what battery temperature or temp range increases charging speed by heating/cooling the battery so that it will accept the full charging capabilities of the selected charge station. For instance, a subject battery may only be able to charge at 50 kW when at 30% SOV and −10° C.; however, the same battery may be able to charge at 300+kW when heated to 20° C. battery temperature. If the predicted SOV is approximately 30% and the selected charging station is a Level 3 DCFC charging station with 350 kW power capacity, the target temp may be set to approximately 20° C. These values will differ for a Level 1 charging station operating at 120 VAC and 1.4-4.2 kW as well as a Level 2 charging station operating at 240 VAC and 6.2-8.2 kW. The target preconditioning temperature is then output at process block213.

Prior to, contemporaneous with, or after deriving an optimal preconditioning temperature, method200carries out process-executable instructions provided by PREDICTION MODEL subroutine block215to estimate the time that will be needed to complete preconditioning of the battery. Estimating a predicted battery preconditioning time to thermally precondition the battery to a target precondition temperature may include modeling the operating behavior of the battery system's internal thermal system and the operating behavior of the traction battery pack for the drive from the vehicle's current location to the charging station's location. In order to model the thermal system behavior and the battery operating behavior, the CPU36may execute an iterative (thermal plant) model and a battery simulation tool as a function of ambient temperature data, past driving behavior data of the motor vehicle, current battery temperature data, the present SOV/SOC, and the predicted SOV/SOC.

The prediction model may perform a Model Loop Determination, which receives as inputs a Loop SOV, a Target SOV, and an Active Cooling/Heating Enabled parameter. This Model Loop Determination then outputs a Loop Counter, Loop SOV, Model Delta Time and Model Total Time. The model then calls a set of functions, including a Battery Electric Model, a Battery Thermal Model, and an Active Cooling/Heating Determination Loop. The Battery Electric Model receives as inputs a Current parameter, the Loop SOV, and a Loop Battery Temp, and then outputs a Loop Battery Electrical Thermal Power. By comparison, the Battery Thermal Model receives as inputs the Loop Battery Electrical Thermal Power, the Active Cooling/Heating Thermal Power, an Ambient Thermal Power, and the Model Delta Time, and outputs a Loop Battery Temp. In the last of the call functions, the Active Cooling/Heating Determination Loop receives as inputs the Loop Battery Temp, the Loop SOV, and a Predicted Charger Power, and then outputs an Active Cooling Enabled value, an Active Cooling Power value, an Active Heating Enabled value, and an Active Heating Power value. After the final loop, a Time to Condition Calculation is performed, which receives as inputs an Estimated Time to DCFC and a Model Time to DCFC and Time to Condition; the final output is the Time to Thermal Condition. In addition to predicting the time needed for preconditioning, the battery/thermal system modeling may also output a predicted battery temperature that may be used to “debug” the model. The model may forecast a final predicted temp for the battery upon arrival at the DCFC after preconditioning is complete, as well as other model parameters (e.g., number of loops in heating, number of loops in cooling, number of total loops, etc.). The final predicted temp may help to “debug” the model and reevaluate the accuracy of the model. The predicted preconditioning time is output at process block217.

After identifying the present SOV (block209), the target preconditioning temperature (block211), and the predicted battery preconditioning time (block215), method200executes TIME TO START PRECONDITIONING decision block219to determine if preconditioning should be started immediately or delayed to a future start time. To complete this decision, DC FAST CHARGER ETA data input/output block221predicts an estimated travel time for the subject vehicle to travel from its current location to the charging station location. Estimated travel times may be derived by resident navigation software from path plan data received, in whole or in part, from a vehicle occupant and/or an ADAS/autonomous control module. By way of non-limiting example, telematics unit14may estimate travel time using GPS-borne geolocation data of the vehicle's current location, a driver-selected destination input via touchscreen display18, and road-level data for a path between origin and destination received from a subscriber-based open street map service.

If the estimated travel time to reach the charging station is greater than the predicted battery preconditioning time, the method200may automatically delay the preconditioning of the battery. On the other hand, if the estimated travel time is less than or equal to the predicted battery preconditioning time, the method200may immediately start battery preconditioning. For example, if the estimated time to precondition the battery is approximately one hour, but the charging station is approximately 2.25 hours away, the battery system may delay initialization of preconditioning for an hour to an hour and 15 minutes. In contrast, if the charging station is only 30 mins away, preconditioning may be initiated immediately based on existing values; however, preconditioning may be amplified to reach the target battery temperature upon arrival at the charging station.

Method200advances from decision block219to DOWNSTREAM CONTROL data output block223to carry out preconditioning of the battery. By way of example, CPU36may transmit one or more control signals to the battery system's internal thermal system to precondition the battery based on the present SOV, target precondition temperature, and predicted battery preconditioning time. EBCM56ofFIG.1, for example, may precondition the traction battery pack70in advance of charging such as by preheating or precooling the pack70while vehicle10is en route to a charging location. When charge preconditioning is not being applied to the traction battery pack70by the EBCM56, the target battery temperature may be set to a nominal temp value within a normal operating temperature range. By increasing or decreasing the temperature of the battery pack70prior to commencement of a charging operation, charging can occur at a faster rate as compared to the charging rate that would be possible if the vehicle10arrived at the charging station after regulating the temperature of the battery pack70using the nominal setting.

During battery preconditioning, the method200monitors a status of the preconditioning of the battery, as indicated at DCFC PRECONDITIONING STATUS process block225. As part of this operation, the EBCM56may confirm that battery conditioning has commenced, track real-time battery temperature during preconditioning, and assess when conditioning has been completed. During preconditioning, the EBCM56may also monitor the battery system for any faults, error events, or requests to disable conditioning; the EBCM56may responsively deactivate preconditioning and output an error report to the driver or a third-party service provider. At HMI display block227, the method outputs battery preconditioning status information to an in-vehicle human-machine interface.

Aspects of this disclosure may be implemented, in some embodiments, through a computer-executable program of instructions, such as program modules, generally referred to as software applications or application programs executed by any of a controller or the controller variations described herein. Software may include, in non-limiting examples, routines, programs, objects, components, and data structures that perform particular tasks or implement particular data types. The software may form an interface to allow a computer to react according to a source of input. The software may also cooperate with other code segments to initiate a variety of tasks in response to data received in conjunction with the source of the received data. The software may be stored on any of a variety of memory media, such as CD-ROM, magnetic disk, and semiconductor memory (e.g., various types of RAM or ROM).

Moreover, aspects of the present disclosure may be practiced with a variety of computer-system and computer-network configurations, including multiprocessor systems, microprocessor-based or programmable-consumer electronics, minicomputers, mainframe computers, and the like. In addition, aspects of the present disclosure may be practiced in distributed-computing environments where tasks are performed by resident and remote-processing devices that are linked through a communications network. In a distributed-computing environment, program modules may be located in both local and remote computer-storage media including memory storage devices. Aspects of the present disclosure may therefore be implemented in connection with various hardware, software, or a combination thereof, in a computer system or other processing system.

Any of the methods described herein may include machine readable instructions for execution by: (a) a processor, (b) a controller, and/or (c) any other suitable processing device. Any algorithm, software, control logic, protocol or method disclosed herein may be embodied as software stored on a tangible medium such as, for example, a flash memory, a solid-state drive (SSD) memory, a hard-disk drive (HDD) memory, a CD-ROM, a digital versatile disk (DVD), or other memory devices. The entire algorithm, control logic, protocol, or method, and/or parts thereof, may alternatively be executed by a device other than a controller and/or embodied in firmware or dedicated hardware in an available manner (e.g., implemented by an application specific integrated circuit (ASIC), a programmable logic device (PLD), a field programmable logic device (FPLD), discrete logic, etc.). Further, although specific algorithms may be described with reference to flowcharts and/or workflow diagrams depicted herein, many other methods for implementing the example machine-readable instructions may alternatively be used.

Aspects of the present disclosure have been described in detail with reference to the illustrated embodiments; those skilled in the art will recognize, however, that many modifications may be made thereto without departing from the scope of the present disclosure. The present disclosure is not limited to the precise construction and compositions disclosed herein; any and all modifications, changes, and variations apparent from the foregoing descriptions are within the scope of the disclosure as defined by the appended claims. Moreover, the present concepts expressly include any and all combinations and subcombinations of the preceding elements and features.