BATTERY CELL CONDITION ASSESSMENT BASED ON STATE OF CHARGE DEVIATION

Abstract

A system for evaluating a battery assembly includes a sensing device configured to sense parameters related to a group of cells of the battery assembly and a diagnostic module.The diagnostic module is configured to perform estimating a state-of-charge (SOC) value for the group of cells based on measurements taken during a selected time window, calculating a statistical value related to the estimated SOC value for the group of cells, assigning the estimated SOC value to a selected one of a plurality of SOC bins based on the statistical value, wherein each SOC bin of the plurality of SOC bins comprises a subset of a range of SOC values, calculating a deviation of each SOC value in the selected bin relative to a plurality of SOC values ​​in the selected bin, and determining whether the group of cells is in good condition based on the deviation.

Description

INITIATIONThe subject disclosure relates to batteries and, more particularly, to estimates of battery parameters including state of charge.Vehicles, including gasoline and diesel powered vehicles, as well as electric and hybrid electric vehicles, have battery storages for powering electric motors, electronics, and other vehicle subsystems. Monitoring battery system state is an important aspect of battery operation. In some monitoring methods, state-of-charge (SOC) behavior within the cells of a battery array is determined.EP 3 929 606 B1 discloses a battery management system for estimating a state of charge of a plurality of battery cells. A current measurement unit measures a cell current of a plurality of cells connected in series, a voltage measurement unit measures a cell voltage of each battery cell, and a control unit coupled to the current measurement unit and the voltage measurement unit classifies the plurality of battery cells based on a state of charge of each battery cell estimated in a previous cycle.In document US 2019 / 0 293 720 A1 a device is disclosed which contains two estimation devices and one computing device and evaluates the current safety of a battery. When an external temperature of the battery changes, a calorie value of the battery used for calculating a safety index is estimated.Document DE 10 2022 126 352 A1 discloses a current measurement circuit that measures a charging current of a battery comprising a plurality of cell groups while the battery is being charged. Voltages of the cell groups are measured by a voltage measurement circuit. Internal resistances of the cell groups are calculated and used to determine whether cell groups are faulty.SUMMARYIn an exemplary embodiment, a system for evaluating a battery array includes a sensing device configured to sense parameters related to a group of cells of the battery array, and a diagnostic module. The diagnostic module is configured to perform state-of-charge (SOC) value estimation for the group of cells based on measurements performed during a selected time window, calculate a statistical value related to the estimated SOC value for the group of cells, map the estimated SOC value to a selected one of a plurality of SOC containers based on the statistical value, each SOC container of the plurality of SOC containers including a subset of a range of SOC values, calculate a deviation of each SOC value in the selected container relative to a plurality of SOC values in the selected container, and determine whether the group of cells is in good state based on the deviation.In addition to one or more of the features described herein, the statistical value is an average group SOC calculated based on the measurements, and the deviation includes a group SOC deviation and a canister deviation, wherein the group SOC deviation corresponds to a difference between the estimated SOC value and the average group SOC, and the canister deviation corresponds to a difference between an SOC value in the selected canister and an average of the plurality of SOC values in the selected canister.In addition to one or more of the features described herein, determining whether the group of cells is in good condition comprises calculating a change in the deviation.In addition to one or more of the features described herein, the change in the deviation is based on the difference between the group SOC deviation and the canister deviation.In addition to one or more of the features described herein, the group of cells is determined to be in good condition based on when the change in the deviation is below a change threshold.In addition to one or more of the features described herein, each SOC value is obtained by calculating a voltage of the group of cells based on voltage samples taken during the selected time window and estimating each SOC value based on an open circuit voltage (OCV) SOC curve.In addition to one or more of the features described herein, the diagnostic module is configured to accumulate cell compensation commands from a cell compensation process.In addition to one or more of the features described herein, calculating the deviation includes compensating for the change in the deviation based on the cell compensation commands.In addition to one or more of the features described herein, the battery assembly is at least one of a battery module and a battery pack of a vehicle.In another exemplary embodiment, a method of evaluating a battery array includes monitoring a group of cells of the battery array, estimating a state-of-charge (SOC) value for the group of cells based on measurements taken during a selected time window, calculating a statistical value related to the estimated SOC value for the group of cells, assigning the estimated SOC value to a selected one of a plurality of SOC containers based on the statistical value, wherein each SOC container of the plurality of SOC containers includes a subset of a range of SOC values, calculating a deviation of each SOC value in the selected container relative to a plurality of SOC values in the selected container, and determining whether the group of cells is in good condition based on the deviation.In addition to one or more of the features described herein, the statistical value is an average group SOC calculated based on the measurements, and the deviation includes a group SOC deviation and a canister deviation, wherein the group SOC deviation corresponds to a difference between the estimated SOC value and the average group SOC, and the canister deviation corresponds to a difference between an SOC value in the selected canister and an average of the plurality of SOC values in the selected canister.In addition to one or more of the features described herein, determining whether the group of cells is in good condition comprises calculating a change in the deviation.In addition to one or more of the features described herein, the change in the deviation is based on the difference between the group SOC deviation and the canister deviation.In addition to one or more of the features described herein, the group of cells is determined to be in good condition based on when the change in the deviation is below a change threshold.In addition to one or more of the features described herein, calculating the deviation includes compensating the deviation based on cell compensation commands accumulated in a cell compensation process.In addition to one or more of the features described herein, the battery assembly is at least one of a battery module and a battery pack of a vehicle.In another exemplary embodiment, a vehicle system includes memory comprising computer readable instructions and a processing device for executing the computer readable instructions, the computer readable instructions controlling the processing device to perform a method. The method includes monitoring a group of cells of a battery array, estimating a state-of-charge (SOC) value for the group of cells based on measurements taken during a selected time window, calculating a statistical value related to the estimated SOC value for the group of cells, associating the estimated SOC value with a selected one of a plurality of SOC containers based on the statistical value, each SOC container of the plurality of SOC containers including a subset of a range of SOC values, calculating a deviation of each SOC value in the selected container relative to a plurality of SOC values in the selected container, and determining, whether the group of cells is in good condition based on the deviation.In addition to one or more of the features described herein, the statistical value is an average group SOC calculated based on the measurements, and the deviation includes a group SOC deviation and a canister deviation, wherein the group SOC deviation corresponds to a difference between the estimated SOC value and the average group SOC, and the canister deviation corresponds to a difference between an SOC value in the selected canister and an average of the plurality of SOC values in the selected canister.In addition to one or more of the features described herein, determining whether the group of cells is in good condition includes calculating a change in the deviation based on a difference between the group SOC deviation and the canister deviation.In addition to one or more of the features described herein, calculating the deviation includes compensating the deviation based on cell compensation commands accumulated in a cell compensation process.The above features and advantages, as well as other features and advantages of the disclosure, will be readily apparent from the following detailed description when taken in conjunction with the accompanying drawings.BRIEF DESCRIPTION OF THE DRAWINGSOther features, advantages, and details are set forth, by way of example only, in the following detailed description, wherein: FIG. 1 is a top view of a motor vehicle including a battery assembly, according to an example embodiment; FIG. 2 shows an example of a range of state-of-charge (SOC) and a set of SOC containers selected according to an example embodiment of a method for evaluating a battery cell group and / or battery array; FIG. 3 is a flow diagram illustrating aspects of a method for evaluating the state of a battery cell group and / or battery array, according to an example embodiment; and FIG. 4 illustrates a computer system according to an example embodiment.DETAILED DESCRIPTIONApparatuses, systems, and methods are provided for evaluating the state of a battery cell group and / or a battery array. An embodiment of a battery state evaluation system is configured to determine the state of the battery based on the state-of-charge (SOC) information collected over time. The system divides a selected SOC range into a plurality of subsets or bins and accumulates SOC estimates of battery cell groups over a selected time window.For each cell group in a battery module (or each cell group in another battery assembly or battery system), an SOC value is estimated and an average SOC value is calculated based on measurements (e.g., voltage samples) for each cell group and / or battery module. For each cell group, the estimated SOC value is assigned to a corresponding bin based on the average SOC value. If SOC values in the canister have been previously acquired for this module, an average of the SOC values in the canister (a "canister average") is calculated.A difference between the estimated SOC value and the average SOC value is calculated (referred to as "first deviation" or "group SOC deviation"). A difference between each of the SOC values in the canister and the canister average is determined (referred to as "second deviation" or "canister deviation"). For example, a battery cell group is determined to be faulty if a change in the first deviation over time exceeds a threshold value. In one embodiment, a battery cell group is determined to be faulty when the difference between the first deviation and the second deviation is above a difference threshold.The embodiments described herein provide numerous advantages and technical effects. The embodiments enable effective diagnosis of battery state by monitoring changes in SOC, thereby providing improved robustness of a battery assembly during the lifetime of the assembly. The embodiments also reduce the effects of capacity variations by grouping SOC values into bins as described herein, enabling accurate diagnostic processes over a wide SOC range.The embodiments are not limited to use with a particular vehicle and may be applicable in various contexts. For example, the embodiments may be used in automobiles, trucks, aircraft, construction machinery, agricultural equipment, automated factory installations, and / or any other device or system that uses rechargeable energy storage systems.FIG. 1 illustrates an embodiment of a motor vehicle 10 that includes a vehicle body 12 that at least partially defines an occupant compartment 14. The vehicle body 12 also supports various subsystems of the vehicle, including a propulsion system 16, and other subsystems for assisting functions of the propulsion system 16, and other vehicle components, such as a brake subsystem, a suspension system, a steering subsystem, a fuel injection subsystem, an exhaust subsystem, etc.The vehicle 10 may be an internal combustion engine vehicle, an electrically driven vehicle (EV), or a hybrid vehicle. In one embodiment, the vehicle 10 is a hybrid vehicle that includes an engine system 18 and at least one electric motor assembly. In one embodiment, the propulsion system 16 includes an electric motor 20 and may include one or more additional motors mounted at various locations. The vehicle 10 may be a fully electric vehicle having one or more electric motors.The vehicle 10 includes a battery system 22 that may be electrically connected to the engine 20 and / or other components such as the vehicle electronics. The battery system 22 may be configured as a rechargeable energy storage system (RESS). In one embodiment, the battery system 22 includes a battery assembly, such as the high voltage battery pack 24, having a plurality of battery modules 26. The battery system 22 may also include a monitoring unit 28 that includes components such as a processor, memory, an interface, a bus, and / or other suitable components.A "battery array" in one embodiment refers to a group of battery cells (i.e., two or more cells). For example, the battery assembly may be, for example, the battery pack 24, a battery module 26, or a group of cells (not shown) in a module 26.Each battery module includes a plurality of cells (not shown) having a selected chemistry. In one embodiment, each cell is a lithium ion battery, such as a lithium ferrophosphate (LFP) battery or a lithium nickel manganese cobalt oxide (NCM) battery. The battery pack 24 is not so limited and may have any suitable chemistry. Other examples include nickel-metal hydride and lead acid chemicals.The battery array includes one or more groups of cells ("cell groups"). A cell group is, in one embodiment, a battery module 26 or a group of cells within the battery module 26.The battery system 22 is electrically connected to components of the propulsion system 16. The propulsion system also includes an inverter module 30 and a direct current (DC)-DC converter module 32. the inverter module 30 (e.g., a traction inverter or TPIM) converts direct current from the battery system 22 into polyphase alternating current (AC) (e.g., three-phase, six-phase, etc.) for powering the motor 20.The vehicle 10 may include various control modules (electronic control modules or ECUs). For example, an auxiliary power module (APM) 34 is included for providing power to accessories (e.g., 12V loads). An onboard charger module (OBCM) 36 may be included that connects the battery system 22 to a charging port 38 and controls aspects of charging the battery system 22 (e.g., from a charging station, a power grid, or other vehicle) and / or providing charge to an external system.The vehicle 10 also includes a computer system 40 that includes one or more processing devices 42 and a user interface 44. The various processing devices and units may communicate with each other via a communication device or system, such as a controller area network (CAN) or transmission control protocol (TCP) bus.One or more processing devices are configured to monitor and evaluate the state of the battery, and identify one or more fault states. An embodiment of an evaluation system includes a processing device, such as an in-vehicle processing device (e.g., the OBCM 36, the monitoring unit 28, and / or a RESS controller), that detects or estimates state of charge (SOC) values over time. An SOC range is selected that is divided into a plurality of subsets or bins.An SOC value for a cell group (e.g., a module 26) may be estimated by collecting voltage measurements or samples over time, estimating a group voltage, and determining an SOC value for the cell group. After estimating the SOC of a cell group for a selected time window, an average group SOC (or other statistical value) is calculated using the measurements. The estimated SOC value is assigned to a canister based on the average group SOC.FIG. 2 shows an example of an SOC range and the division of the SOC range into SOC bins. In this example, the SOC values are based on associated open circuit voltage (OCV) values. Correlations between SOC and OCV may be determined by modeling and / or experimentally.FIG. 2 illustrates a plot 60 of OCV (in volts (V)) as a function of SOC, expressed as a percentage of cell capacity. An OCV-SOC curve 62 represents OCV as a function of SOC for a group of battery cells. In this example, an SOC range 64 is selected as a range between 30% and 100% of the capacity, and the SOC range 64 is divided into a plurality of subsets, referred to as bins 66.Embodiments are discussed herein with reference to the diagram 60 and the containers 66 of FIG. 2 for illustrative purposes. The embodiments are not limited to a particular OCV-SOC curve, voltage range, or canister selection.The state of a cell group is evaluated in one embodiment based on comparing each SOC value in a bin 66 to other SOC values in the bin 66. Each SOC value in the bin 66 (or only the estimated SOC value) is compared to a statistical value related to the data in the bin 66. In one embodiment, the statistical value is an average value of the in-canister SOC values ("canister average"). The state of a group of battery cells may be determined using a deviation of an SOC value in the canister 66 from the canister average (or other statistical value). This deviation is referred to as "bin deviation".In one embodiment, the state of the group of battery cells is determined by comparing the bin variation with previous variations (e.g., bin variations calculated in previous iterations). A change or trend in the bin deviation relative to previous bin deviations is calculated and used to determine the condition. For example, the group of cells is determined to be in good condition if the change in the bin deviation is below a selected change threshold.In one embodiment, the state of the group of battery cells is determined by comparing the canister deviation with a deviation related to SOC values estimated from measurements ("group SOC deviation"). The group SOC deviation is determined by estimating a group voltage and corresponding SOC value based on a set of measurements (e.g., voltage samples) and calculating an average SOC value from the set of measurements. The group SOC deviation is the difference between the estimated SOC value and the average group SOC value. The group of cells is determined to be in good condition if the difference between the canister deviation and the group SOC deviation is below a selected threshold.In one embodiment, the one or more processing devices acquire cell balancing information related to the cell balancing operations performed during a time window. For example, cell balancing commands that dictate the charging or discharging of cells within a battery array (to balance the SOC between cells) are used to determine any charging or discharging that has occurred due to the cell balancing. The cell compensation commands may be used to compensate for deviation calculations.Cell balancing processes are used to balance the SOC between cells in a battery array, such as the battery module 26 or the battery pack 24. Cell balancing can minimize cell-to-cell power fluctuations and mitigate the effects of cell degradation in individual cells. In some embodiments, cell balancing includes redistributing energy and / or charge between cells in a battery pack to achieve a more uniform SOC.A balancing process includes estimating or measuring the state-of-charge (SOC) of each cell group in a battery array. A cell group may be a module 26 or a group of connected cells within a module. The cell group having the lowest state of charge is determined, and the determined SOC is compared with the SOC of each other current cell group. When a cell group exceeds (i.e., is not at equilibrium) the identified SOC value by a certain threshold, energy is discharged from the unbalanced cell group until the unbalanced cell(s) re-reach the threshold.FIG. 3 illustrates embodiments of a method 80 for evaluating a battery arrangement (e.g., the battery pack 24). Aspects of the method 80 may be performed by one or more processors located in the vehicle 10 (e.g., the monitoring unit 28, the computer system 40, etc.). It should be appreciated that the method 80 is not so limited and may be performed by any suitable processing device or system or combination of processing devices. Moreover, the method 80 is not limited to use with the vehicle 10, as the method 80 may be performed in connection with any suitable battery or battery system.The method 80 includes a series of steps or steps represented by blocks 81- 102. The method 80 is not limited to the number or order of steps therein, as some of the steps represented by blocks 81- 102 may be performed in an order other than that described below, or fewer than all of the steps may be performed.At block 81, a processing device monitors the battery system 22. An SOC range is selected and the SOC range is divided into a plurality of consecutive bins. The containers may be of the same length as the containers in Fig. 2, but are not so limited.In block 82, a time window for collecting measurements is selected, referred to as filter length. In addition, a voltage range is selected (filter voltages) and an OCV-SOC curve is acquired for each cell group to be evaluated (e.g., each module 26). The measurement data is collected over time by collecting voltage samples during the time window. It should be noted that sampling continues at the end of the time window such that measurement data is collected and a group voltage, an SOC value, and an average SOC value may be determined for each successive time window.The time window may be any period of operation of the vehicle 10. For example, the time window may include one or more periods of time during which the battery pack 24 discharges (e.g., when the vehicle 10 is powered). Additionally or alternatively, the time window may also include periods of time during which the battery pack is charged via the charging port 38.In block 83, cell balancing information is acquired. In one embodiment, cell balancing commands generated by a cell balancing process are collected and accumulated during battery operation and / or charging. Cell balancing information is acquired by accessing accumulated cell balancing commands. For each cell balance command, the ampere hours (Ah) derived from each cell group are calculated. The dissipated amp hours determined from the compensation commands are accumulated over a period between the last canister update (see block 92) and the current cell compensation calculation.In one example, the impact of the cell balance command is determined by accumulating the cell balance commands (e.g., summing the dissipated amp-hours associated with each command). The cell compensation commands may be accumulated before method 80 begins (or after determining that a cell group is in a good state or a bad state) and are accumulated until the conditions of blocks 85 and 87 are met.In block 84, the polarization voltage is estimated and the processing device determines whether various conditions are met.In block 85, the processing device determines whether a filter condition is met. The filter condition is used to determine if there is enough data for evaluation. The processing device determines, for example, a plurality of stress samples collected over the filter length. If the number of samples collected is below a threshold, the data is insufficient for estimating the group voltage (i.e., the filter condition is not met), and the processing device continues to accumulate data at block 82.In block 86, the polarization voltage is compared to a selected threshold. If the polarization voltage is above the threshold, the method returns to block 82.At block 87, for each measured cell group (e.g., module 26), an SOC value is calculated based on the collected voltage samples. In one embodiment, the SOC value for a cell group is calculated based on an OCV-SOC curve associated with the cell group.For example, if there are sufficient voltage samples and the polarization condition is met, the cell group voltage is determined from the collected voltage samples and is used to determine a filtered SOC value. The cell group voltage is input to the OCV-SOC curve to produce a filtered SOC value. For example, the group voltage may be filtered and then applied to the OCV curve to obtain the filtered SOC value, or the raw group voltage may be applied to the OCV SOC curve and then filtered to obtain the filtered SOC value.In block 88, an average of the SOC values in the box is calculated (container average). The method 80 may be modified to take other statistical features of the data in a container into account as well. Thus, the filtered SOC value in a container may be compared to any statistical characteristic.In block 89, a canister deviation is calculated for the filtered SOC and corresponding canister data. In one embodiment, the canister deviation corresponds to the difference between the filtered in-canister SOC value and the canister average. Moreover, an average SOC value is calculated based on the measurements acquired during the current time window, and the SOC group deviation is calculated as the difference between the calculated SOC value for the cell group and the average SOC value.In block 90, the canister is evaluated based on the filtered average SOC. For example, in block 91, each bin is examined and it is determined whether there is data in the bin, for example from previous SOC estimates. If not, the method continues to block 92 where the container is updated and a filter used to collect voltage samples is reset.In block 93, for each container having data, the cell balancing information is used to calculate the amount of discharge that occurred in the cell group due to the cell balancing. For example, the average amp hours compensated for the cell group relative to the average SOC are calculated based on a cell compensation command (e.g., based on the commanded amounts of energy dissipation). The average amp hours for each of a plurality of cell compensation commands are accumulated, for example, over a period of time from the time the memory was last updated and the group voltage was calculated in a current iteration of method 80.The amp hours accumulated between the current filtered SOC and a previous filtered SOC may be determined by open loop calculation using estimates of the cell group voltage and the equilibrium resistance.In block 94, a deviation is compensated using cell compensation information. For example, cell balancing commands are used to identify cells that have been discharged for balancing purposes. When a cell group was balanced, the amount of charge discharged is subtracted from the observed tendency of the deviation associated with that cell group. Cell compensation may be used to compensate for the canister deviation and / or the group SOC deviation.In block 95, a change in the deviation is calculated. The change in the deviation may be a difference between a current and a previous container deviation. The change in the deviation may be a difference between the location deviation and the group SOC deviation.In block 96, a threshold is selected or calculated. The threshold value is an amount for the change in the deviation.In one embodiment, the threshold is a dynamic threshold calculated using the current average SOC.The dynamic threshold is a function of the total time between the filtered SOC estimates (i.e., the time elapsed between the calculation of a previous filtered SOC in a previous iteration of method 80 and the estimate of the current filtered SOC). The dynamic threshold is also a function of a static offset and the difference in average SOC between the filtered SOC estimates.In one embodiment, the threshold is equal to the maximum of the elapsed time, a first growth factor, and "noise-blocking.". Noise rejection grows with the error sources and is module specific. The noise trap can be calculated as follows:Noise Trap = Static Offset + (absolute value of the difference of the average group SOC between the current and a previous iteration)*GF2 + (time between the current and the previous iteration)*GF3,wherein GF2 is a second growth factor and GF3 is a third growth factor.In block 97, the change in the deviation is compared to the threshold (e.g., a dynamic or static threshold). If the change in the deviation exceeds the threshold for one of the SOC values in the selected canister, the canister is updated at block 101 and an indication of failure is output at block 102. The indication may be forwarded to another processing device or system or displayed to a user. The failure indication may be in any format and provide information in a manner suitable for conveying that the deviation is too great and a high discharge condition is present.At block 98, if none of the variance changes exceed the threshold, the processing device determines that the cells for the container are in good condition (or at least that diagnostic method exists). In block 99, the container is updated and indicates that the cells for the selected container are in good condition (block 100).FIG. 4 illustrates aspects of an embodiment of a computer system 140 that may perform various aspects of the embodiments described herein. The computer system 140 includes at least one processing device 142 that generally includes one or more processors for performing aspects of the image acquisition and analysis methods described herein.Components of computer system 140 include processing device 142 (such as one or more processors or processing units), memory 144, and bus 146 that connects various system components including system memory 144 to processing device 142. System memory 144 may be a non-transitory computer readable medium and may include a plurality of computer readable media. These media may be any available media that can be accessed by the processing device 142, both volatile and nonvolatile media, and removable and non-removable media.System memory 144 includes, for example, non-volatile memory 148, such as a hard disk, and may also include volatile memory 150, such as random access memory (RAM) and / or cache memory. Computer system 140 may also include other removable / non-removable, volatile / non-volatile storage media of the computer system.System memory 144 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments described herein. For example, system memory 144 stores various program modules that generally perform the functions and / or methods of the embodiments described herein. One or more modules 152 may be included for performing functions related to detecting OCV, SOC, and other measurements of the battery arrangement, as well as battery state assessment, as discussed herein. The system 140 is not so limited as other modules may be included. As used herein, the term "module" refers to processing circuitry that may include an application specific integrated circuit (ASIC), an electronic circuit, a processor (shared, dedicated, or group), and memory that executes one or more software or firmware programs, combinatorial logic circuitry, and / or other suitable components that provide the described functionality.The processing device 142 may also communicate with one or more external devices 156, such as a keyboard, a pointing device, and / or other devices (e.g., a network card, a modem, etc.) that enable the processing device 142 to communicate with one or more other computing devices. Communication with various devices may be via input / output (I / O) interfaces 164 and 165.The processing device 142 may also communicate with one or more networks 166, such as a local area network (LAN), a general wide area network (WAN), a bus network, and / or a public network (e.g., the Internet), via a network adapter 168. It should be appreciated that other hardware and / or software components may also be used in conjunction with computer system 140, although not shown. Examples include, but are not limited to: microcode, device drivers, redundant processing units, external hard disk arrays, RAID systems, data archive systems, etc.The terms "a / e / r / s" do not mean a quantity limitation, but rather denote the presence of at least one of the stated objects. The term "or" means "and / or" unless the context clearly indicates otherwise. Throughout the specification, when "an aspect" is mentioned, it means that a particular element (e.g., feature, structure, step, or characteristic) described in connection with the aspect is included in at least one of the aspects described herein, and may or may not be present in other aspects. In addition, it is to be understood that the described elements may be combined in any suitable manner in the various aspects.When an element such as a layer, film, region or substrate is referred to as being "on" another element, it may be directly on the other element or intervening elements may also be present. In contrast, there are no intervening elements when an element is referred to as being "directly on" another element.Unless otherwise specified herein, all testing standards are the latest standard in effect on the filing date of this application or, if a priority is claimed, the filing date of the earliest priority application in which the testing standard appears.Unless otherwise defined, the technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains.Although the above disclosure has been described with reference to exemplary embodiments, it is known by those skilled in the art that various changes may be made and equivalent elements may be replaced without departing from the scope of the invention. In addition, many changes may be made to adapt a particular situation or material to the teachings of the disclosure without departing from its essential scope. Therefore, the present disclosure is not intended to be limited to the particular embodiments disclosed, but to include all embodiments falling within its scope.LegendIn the drawing figures, N represents No and Y represents Yes

Claims

A system for evaluating a battery array, comprising: a sensing device configured to sense parameters relating to a group of cells of the battery array; and a diagnostic module configured to perform: estimating a state-of-charge (SOC) value for the group of cells based on measurements performed during a selected time window; calculating a statistical value relating to the estimated SOC value for the group of cells; assigning the estimated SOC value to a selected one (66) of a plurality of SOC containers (66) based on the statistical value, wherein each SOC container (66) of the plurality of SOC containers (66) comprises a subset of a range of SOC values; calculating a deviation of each SOC value in the selected container (66) relative to a plurality of SOC values in the selected container (66); and determining whether the group of cells is in good condition based on the deviation.The system of claim 1, wherein the statistical value is an average group SOC calculated based on the measurements, and the deviation comprises a group SOC deviation and a canister deviation, wherein the group SOC deviation corresponds to a difference between the estimated SOC value and the average group SOC, and the canister deviation corresponds to a difference between an SOC value in the selected canister (66) and an average of the plurality of SOC values in the selected canister (66).The system of claim 2, wherein determining whether the group of cells is in good condition comprises calculating a change in the deviation.The system of claim 3, wherein the change in the deviation is based on a difference between the group SOC deviation and the canister deviation, and the group of cells is determined to be in good condition based on the change in the deviation being less than a change threshold.The system of claim 1, wherein each SOC value is acquired by calculating a voltage of the group of cells based on voltage samples taken during the selected time window and estimating each SOC value based on an open circuit voltage (OCV) SOC curve.The system of claim 3, wherein the diagnostic module is configured to accumulate cell compensation commands from a cell compensation process, and calculate the deviation comprises compensating for the change in the deviation based on the cell compensation commands.The system of claim 1, wherein the battery assembly is at least one of a battery module and a battery pack (24) of a vehicle (10).A method of evaluating a battery array, comprising: monitoring a group of cells of the battery array; estimating a state-of-charge (SOC) value for the group of cells based on measurements taken during a selected time window; calculating a statistical value related to the estimated SOC value for the group of cells; assigning the estimated SOC value to a selected one (66) of a plurality of SOC containers (66) based on the statistical value, wherein each SOC container (66) of the plurality of SOC containers (66) comprises a subset of a range of SOC values; calculating a deviation of each SOC value in the selected container (66) relative to a plurality of SOC values in the selected container (66); and determining whether the group of cells is in good condition based on the deviation.The method of claim 8, wherein the statistical value is an average group SOC calculated based on the measurements, and the deviation comprises a group SOC deviation and a canister deviation, wherein the group SOC deviation corresponds to a difference between the estimated SOC value and the average group SOC, and the canister deviation corresponds to a difference between an SOC value in the selected canister (66) and an average of the plurality of SOC values in the selected canister (66).The method of claim 9, wherein the determining whether the group of cells is in good condition is based on calculating a deviation based on a difference between the group SOC deviation and the canister deviation, and the group of cells is determined to be in good condition based on the change in the deviation being less than a change threshold.

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