Computer-implemented method for estimating a battery state based on current characteristics at constant voltage, including vehicle and computer program product

Abstract

The examples described herein provide a method that includes detecting the start of a constant voltage operating phase of a vehicle battery. The method further includes collecting current and voltage information about the battery. The method further includes monitoring a health indicator for the battery based at least in part on the current information. The method further includes determining whether the battery is in a healthy state or in a fault condition by determining whether the health indicator is within an acceptable range. The method further includes, in response to determining that the battery is in a fault condition, performing a corrective action for the battery.

Description

[0001] The present description relates to a computer-implemented method, vehicles, a computer program product and, in particular, to the estimation of battery state based on current characteristics at constant voltage.

[0002] Modern vehicles (e.g., cars, motorcycles, boats, or other motor vehicles) may be equipped with one or more batteries to power various vehicle systems. For example, an electric vehicle may contain one or more batteries to power one or more electric motors that propel the vehicle. This vehicle configuration is referred to as a battery electric vehicle (BEV). Other vehicle types may also be equipped with batteries, such as internal combustion engine vehicles, hybrid electric vehicles, and / or similar vehicles, including combinations and / or multiple combinations thereof.Other examples of vehicle components that may utilize the electrical energy stored in a battery include, but are not limited to, pumps, actuators, sensors, processing systems, displays, climate control systems, infotainment systems, engine control units, and / or the like, including combinations and / or multiples thereof.

[0003] US 2021 / 0 239 766 A1 describes a method and a device for accurately detecting an operating state of a battery in a battery system, the method comprising determining a charging profile of a battery in a battery system, identifying a constant voltage and a corresponding constant current in a charging cycle of the charging profile, estimating at least one decay constant or an internal resistance associated with the battery using at least one of the constant voltage or the constant current, comparing the decay constant with a first threshold or comparing the internal resistance with a second threshold, and detecting an operating status of the battery as faulty or healthy based on the comparison.

[0004] Logarithm. In: Wikipedia, the free encyclopedia. Edited on: February 17, 2024, 11:25 UTC. URL: https: / / de.wikipedia.org / w / index.php?title=Logarithmus&oldid=242278487#Definitio n [accessed on 28.02.2025] describes a definition of the logarithm.

[0005] US 2023 / 0 152 383 A1 describes a processor-implemented method of a battery management system comprising: determining one or more pieces of sample data from a plurality of pieces of battery usage data of a battery, determining a first short-term fatigue metric (SFM) based on the determined one or more pieces of sample data, and storing the first SFM score, wherein the one or more pieces of sample data comprises any one or any combination of two or more of the following: a high charge profile associated with the battery, a high discharge profile associated with the battery, a partial charge profile associated with the battery, and a partial discharge profile associated with the battery.

[0006] WO 2021 / 006860 A1 describes a system, a method, and an article for estimating the state of health of a battery. The current supplied to or drawn from a battery can be measured while maintaining the battery's charge or discharge voltage constant at corresponding charge or discharge voltage limits. A critical baseline state of charge, SOC, of ​​the battery during a first charge or discharge cycle of the battery can be determined, wherein the critical baseline SOC of the battery comprises an estimate of the actual SOC of the battery when a rate of change of the current supplied to or drawn from the battery at constant voltage is approximately equal to a threshold.A subsequent critical SOC estimate of the battery may be determined during a subsequent charge or discharge cycle of the battery, wherein the subsequent critical SOC estimate comprises an estimate of the true SOC of the battery when a rate of change of the current supplied to or drawn from the battery at the constant voltage during the subsequent charge or discharge cycle is approximately equal to the threshold. The battery's state of health may be determined based on a comparison between the baseline critical SOC and the subsequent critical SOC estimate. This process may be repeated until, for example, a target SOC is reached.

[0007] DE 101 64 772 B4 describes a capacity estimation method for a Li-ion cell, comprising the steps of: determining, when the Li-ion cell is charged using a constant current and constant voltage method, a charging current after a predetermined time has elapsed from the time when the charging condition changes from a constant current mode to a constant voltage mode, and calculating an estimated capacity of the Li-ion cell using the charging current.

[0008] According to the invention, a computer-implemented method is provided. The computer-implemented method comprises detecting the start of a constant voltage operating phase of a vehicle battery. The computer-implemented method further comprises collecting current information and voltage information about the vehicle battery. The computer-implemented method further comprises monitoring a health indicator for the vehicle battery based at least in part on the current information. The method further comprises determining whether the vehicle battery is in a healthy state or in a fault condition by determining whether the health indicator is within an acceptable range. The method further comprises, in response to determining that the vehicle battery is in a fault condition, performing a corrective action for the vehicle battery.The condition indicator is based at least in part on a coefficient of determination of a line fit to a natural logarithm of the battery current indicated by the current information.

[0009] According to one embodiment, the condition indicator is based at least in part on a slope of a line fitted to a natural logarithm of the battery current indicated by the current information.

[0010] According to a further embodiment, the collection of current and voltage information about the vehicle battery is carried out while the vehicle battery is in the constant voltage operating phase.

[0011] According to another embodiment, the collecting is terminated in response to determining that the current of the battery indicated by the current information reaches a minimum current level.

[0012] According to another embodiment, the corrective action is at least one of the following: repairing the battery, replacing the battery, correcting an electrolyte leak in the battery, redesigning the battery, and adapting a manufacturing process to manufacture other batteries.

[0013] According to a further embodiment, the error condition is an error due to loss of active material.

[0014] According to a further embodiment, the fault condition is an electrolyte fault.

[0015] According to the invention, a vehicle is also provided. The vehicle includes a vehicle battery and a processing system. The processing system includes a memory with computer-readable instructions. The processing system further includes a processing device for executing the computer-readable instructions, the computer-readable instructions controlling the processing device to perform operations. The operations include detecting the start of a constant voltage operating phase of the vehicle battery of the vehicle. The operations further include collecting current and voltage information about the vehicle battery. The operations further include monitoring a health indicator for the vehicle battery based at least in part on the current information.The operations further include determining whether the battery is in a healthy state or a fault condition by determining whether the health indicator is within an acceptable range. The operations further include, in response to determining that the vehicle battery is in a fault condition, performing a corrective action for the vehicle battery.

[0016] According to one embodiment, the condition indicator is based at least in part on a slope of a line fitted to a natural logarithm of the battery current indicated by the current information.

[0017] According to another embodiment, the condition indicator is based at least in part on a determination coefficient of a line fit to a natural logarithm of the battery current indicated by the current information.

[0018] According to a further embodiment, the acquisition of the current and voltage information about the battery is carried out while the battery is in the constant voltage operating phase.

[0019] According to another embodiment, the collecting is terminated in response to determining that the current of the battery indicated by the current information reaches a minimum current level.

[0020] According to another embodiment, the corrective action is at least one of the following: repairing the battery, replacing the battery, correcting an electrolyte leak in the battery, redesigning the battery, and adapting a manufacturing process to manufacture other batteries.

[0021] According to a further embodiment, the error condition is an error due to loss of active material.

[0022] According to a further embodiment, the fault condition is an electrolyte fault.

[0023] According to the invention, a computer program product is also provided. The computer program product comprises a computer-readable storage medium having program instructions embodied therein, wherein the program instructions are executable by at least one processor to cause the at least one processor to perform operations. The operations include detecting the start of a constant voltage operating phase of a vehicle battery. The operations further include collecting current and voltage information about the vehicle battery. The operations further include monitoring a health indicator for the battery based at least in part on the current information. The operations further include determining whether the vehicle battery is in a healthy state or in a faulty state by determining whether the health indicator is within an acceptable range.The operations further include, in response to determining that the battery is in a fault condition, performing a corrective action for the vehicle battery.

[0024] According to one embodiment, the condition indicator is based at least in part on a slope of a line of fit to a natural logarithm of the battery current indicated by the current information.

[0025] According to another embodiment, the condition indicator is based at least in part on a determination coefficient of a line fit to a natural logarithm of the battery current indicated by the current information.

[0026] According to a further embodiment, the fault condition is a fault due to loss of active material or an electrolyte fault.

[0027] The above features and advantages as well as other features and advantages of the description will be readily apparent from the following detailed description taken in conjunction with the accompanying figures.

[0028] Further features, advantages and details are included only as examples in the following detailed description, which refers to the figures in which they are shown: Fig. 1 is an illustration of a vehicle having a processing system for performing a battery health estimation using current characteristics at a constant voltage; Fig. 2 is a block diagram of the processing system of Fig. 1 to perform a battery state estimation using current characteristics at a constant voltage; Fig. 3A is a flowchart of a method for estimating battery state using current characteristics at a constant voltage; Fig. 3B is a circuit diagram of an equivalent circuit; Fig. 4A shows diagrams of a first failure mode; Fig. Figure 4B shows diagrams of a second failure mode; Fig. 5 is a flowchart of a method for estimating battery state using current characteristics at a constant voltage; and Fig. 6 is a block diagram of a processing system for implementation.

[0029] The following description is merely exemplary. It should be understood that corresponding reference numerals throughout the drawings indicate like or corresponding parts and features. As used herein, the term module refers to processing circuitry, which may include an application-specific integrated circuit (ASIC), an electronic circuit, a processor (collectively, dedicated, or as a group), and memory executing one or more software or firmware programs, combinational logic circuitry, and / or other suitable components that provide the described functionality.

[0030] One or more embodiments described herein relate to estimating the health of a battery (e.g., a vehicle battery) using constant voltage current characteristics. For example, battery current profile characteristics and statistics can be used as battery aging and health indicators. One or more embodiments enable monitoring the health of a battery (e.g., a vehicle battery) using functions that characterize the current profile and rate of change of current during constant voltage (CV) operation of (assembled or individual) battery cells. Such embodiments enable battery fault detection. Battery fault detection improves vehicle operation and function because faulty batteries can be identified and repaired or replaced more efficiently.

[0031] Batteries, for example, automotive batteries, can degrade over time due to natural aging, defects or anomalies in manufacturing, operating conditions, environmental conditions, and / or the like, including combinations thereof. For example, batteries of vehicles operated in very hot or very cold climates may wear out more quickly than batteries of vehicles operated in more temperate climates. Therefore, it is desirable to monitor the condition of vehicle batteries to determine when the batteries need to be serviced and / or replaced. Some approaches to battery health monitoring include a voltage-based approach. A voltage-based approach assesses the battery's condition during constant current operation, where the voltage fluctuates. However, such approaches are ineffective at constant voltage.Furthermore, such approaches are unable to detect specific battery faults because observability is very low during constant-current phases of a charging profile. For example, it is not possible to detect an electrolyte fault at constant current.

[0032] One or more of the embodiments described herein address these and other deficiencies by enabling an estimation of battery health (e.g., a vehicle battery) using constant-voltage current characteristics. The embodiments described herein use derived equations for the expected shape of the current profile during the constant-voltage phase and use a function of the constant-voltage current to estimate the battery health and detect faults, such as electrolyte failure, that are not observable during the constant-current state.

[0033] The operation of a vehicle employing one or more of the embodiments described herein should be improved. For example, as described, one or more embodiments may be used to detect faults, such as an electrolyte fault, that are not observable at constant current conditions. By implementing an estimation of battery health (for example, of a vehicle battery) using constant voltage current characteristics (as described herein), a vehicle is improved because such faults can be detected and corrected, whereas such faults would otherwise go undetected. As a result, corrective actions, such as maintenance, repair, or replacement, can be performed, resulting in an improvement of the vehicle.Furthermore, battery manufacturing may be approved because one or more of the embodiments described herein may be applied during the end-of-the-line cell manufacturing process for the battery to detect failures and / or redesign batteries when premature aging is detected based on data collected from multiple batteries / vehicles.

[0034] Fig. 1 is an illustration of a vehicle 100 having a processing system 102 for performing a battery state estimation using current characteristics at a constant voltage, according to one or more embodiments. The vehicle 100 may be a car, a truck, a van, a bus, a motorcycle, a boat, or any other type of vehicle. According to one embodiment, the vehicle 100 includes an internal combustion engine powered by gasoline, diesel, or the like. According to another embodiment, the vehicle 100 is a hybrid electric vehicle powered partially or entirely by electrical power. According to another embodiment, the vehicle 100 is an electric vehicle powered by electrical power. According to one or more embodiments, the vehicle 100 is an autonomous or semi-autonomous vehicle. An autonomous vehicle is a vehicle that has self-driving capabilities.

[0035] According to one or more embodiments, the vehicle 100 includes the processing system 102 and a battery 104. The battery 104 represents one or more batteries and / or battery systems. A battery system may include one or more batteries and one or more control units for managing the batteries. The battery 104 stores electrical energy that may be used to power systems and / or components of the vehicle 100, such as electric motors, pumps, actuators, sensors, processing systems, displays, climate control systems, infotainment systems, engine control units, and / or the like, including combinations and / or multiples thereof. As the battery 104 is used, it may wear out over time, making it less efficient. For example, the battery 104 may store less electrical power over time than when the battery was new.According to various embodiments, battery 104 may be a single battery cell or a pack / module of cells connected in a mixed parallel and series configuration. It should be appreciated that the embodiments described herein may be applied to any suitable battery chemistry.

[0036] The processing system 102 may use the information collected from the battery 104 to estimate the battery's condition based on constant voltage current characteristics. Further features of the processing system 102 will now be described with reference to Fig. 2 described.

[0037] Fig. 2 is, in particular, a block diagram of the processing system 102 of Fig. 1 for performing a battery state estimation using current characteristics at a constant voltage according to one or more embodiments. The processing system 102 includes a processing device 202, a memory 204, and a battery state estimation engine 210. The processing system 102 may be any device suitable for performing a battery state estimation. For example, the processing system 102 may be a device implemented in or otherwise connected to the vehicle 100. As another example, the processing system 102 may be a smartphone, a tablet computer, a laptop computer, a desktop computer, a wearable device, and / or the like, including combinations and / or multiples thereof.

[0038] Processing device 202 is any suitable processing circuit for processing data and / or instructions. Processing device 202 is an example of one or more of the processing devices 621 of Fig. 6, as described in more detail herein.

[0039] Memory 204 is any suitable device for storing data and / or instructions. Memory 204 is an example of system memory 622, random access memory 623, and / or read-only memory 624 of Fig. 6, as described in more detail herein.

[0040] The battery state estimation module 210 performs a battery state estimation using constant voltage current characteristics, as described in more detail herein.

[0041] Further aspects and features of the battery health assessment machine 210 are described herein with reference to the Fig. 3, Fig. 4A, Fig. 4B and Fig. 5 described.

[0042] The various components, modules, machines and so on that are used in Fig. 2 (e.g., the battery health estimation machine 210) may be implemented as instructions stored on a computer-readable storage medium, as hardware modules, as special-purpose hardware (e.g., application-specific hardware, application-specific integrated circuits (ASICs), special-purpose application-specific processors (ASSPs), field-programmable gate arrays (FPGAs), as embedded controllers, hard-wired circuits, and so on), or as a combination or combinations thereof. According to aspects of the present description, the machine(s) described herein may be a combination of hardware and programming. The programming may be processor-executable instructions stored in tangible memory, and the hardware may include the processing device 202 for executing those instructions.For example, system memory (e.g., memory 204) may store program instructions that, when executed by processing device 202, implement the engines described herein. Other engines may also be used to incorporate other features and functions described in other examples herein.

[0043] Fig. 3A is a flowchart of a method 300 for estimating battery state using constant voltage current characteristics, according to one or more embodiments. The method 300 may be implemented using any suitable system or device. For example, the method 300 may be implemented using the processing system 102 of the Fig. 1 and Fig. 2, of the processing system 600 of the Fig. 6 and / or the like, including combinations and / or multiples thereof. The method 300 will now be described with reference to Fig. 1 and Fig. 2, but is not so limited.

[0044] At block 302, the processing system 102 (e.g., using the battery state estimation engine 210) detects the beginning of a constant voltage operating phase (e.g., constant voltage charging or discharging). The constant voltage operating phase may be detected by monitoring the voltage supplied to the battery 104 during charging (e.g., while the battery 104 is connected to a charging station or other power source, such as the electrical energy generated by a vehicle's electric motor during braking) or during discharging. For example, the voltage may be considered constant if it is within a certain range for a certain period of time (e.g., within + / - 0.5 volts of 240 volts for 5 seconds, within + / - 0.01 volts of 4.2 volts for 7 seconds, and / or the like, including combinations and / or multiples thereof).Other areas and / or other time periods can be realized in various embodiments.

[0045] At block 304, the processing system 102 (e.g., using the battery health estimation engine 210) collects current and voltage information about the battery 104 while the battery 104 is in the constant voltage operating phase. For example, the constant voltage operating phase may be terminated when the current reaches a minimum value. Thus, the processing system 102 collects the current and voltage for the battery 104 until the current reaches the minimum current value.

[0046] In block 306, the processing system 102 (e.g., using the battery health estimation engine 210) monitors one or more health indicators based on the current information acquired in block 304. The health indicators represent the relationship between the voltage of the battery cell / module / pack (e.g., the battery 104) and the current of the battery 104 using physically based model equations, which will now be described in more detail. Various statistical approaches can be applied to the following equations to determine various health indicators, for example, the slope of a line of fit to the natural logarithm of the current (Ln(I)), the coefficient of determination (R 2) of the fit line to the natural logarithm of the current (Ln(I)) and / or the like, including combinations and / or multiples thereof. According to one or more embodiments, the current profile for the battery 104 follows the function of the natural logarithm (Ln) during constant voltage charging / discharging. This behavior enables the use of a health indicator, for example, a linear regression, to monitor the health of the battery during constant voltage charging / discharging.

[0047] In particular, the current during constant-voltage operation can be modeled using the following equations. The single-particle electrochemical battery model is simplified in this section to calculate the expected cell current profile during constant-voltage operation. The cell voltage is the difference between the positive (cathode) and Φs+ and negative (anode) Φs− Solid state potentials: V=Φs+|x=L−Φs−|x=0.

[0048] The potential of each electrode is determined from its overpotential (η), the electrolyte potential (Φ e ) and the open circuit potential of the electrode (U): Φs±(x,t)=η±+Φe±+U±+FReffJ± where J is the molar particle ion flux, F is the Faraday constant and R eff is the effective film resistance. In equation (2), the “+” sign refers to the positive electrode and the “-” sign to the negative electrode. Here, a simplification method is presented to linearize the terms on the right-hand side of equation (2). Assuming I(t) / 2a+L+∗i0+(t)<1, where I(t) is the cell charge per area, the cell overpotential can be related to the cell current as follows: η+−η−=RTαF[sinh−1(I(t)2a+L+∗i0+(t))−sinh−1(−I(t)2a−L−∗i0−(t))]=ε1(t)I(t)

[0049] Where i0 is the exchange current density, L is the thickness of each electrode, and a is the active surface area per unit volume of the electrode. The parameter ε1 is assumed to capture all constant and time-varying terms that linearly correlate the current flow with the cell's overpotential. Similarly, the electrolyte potential is linearized as: Φs+−ϕe−=L++2Lsep+L−2κI(t)=ε2(t)I(t) with κ the ionic conductivity of the electrolyte and L sep the thickness of the separator. The molar flow J can be correlated with the surface flow: FReffJ=FReffI(3Lelectrode∗ε)Rsphere=ε3(t)I(t) with ε the volume fraction of the active material and R sphereis the radius of the sphere representing the electrode in the single-particle model. The open-circuit potential, U, of each electrode is mainly a function of the electrode SOC (ignoring other minor factors such as temperature) and can be linearized as a function of the cell charge capacity, Q: U+−U−=OCP+(SOC)−OCP−(SOC)=ε4(t)Q

[0050] Using equations (1)-(6), the linear cell voltage is calculated as a function of cell current and charge capacity: V=ε1I+ε2I+ε3I+ε4Q

[0051] Equation (7) represents an equivalent circuit battery model 320 as shown in Fig. 3B, with a single resistor for the battery cell. Assuming that the parameters ε1, ε2, ε3, ε4 are constant over time during constant voltage operation, the voltage derivative can be calculated as follows: V˙=(ε1+ε2+ε3)dIdt+εddQdt dQdt=IAeff where A eff is the effective area of ​​the cell. Since the voltage is constant in constant voltage mode, V̇ = 0 and equation (8) simplifies to: dII=−ε4Aeff(ε1+ε2+ε3)dt

[0052] By integrating equation (9), the final correlation between cell current and time during constant voltage operation is as follows: ln(I)=−ε4Aeff(ε1+ε2+ε3)t+ln(I(0))

[0053] As equation (10) suggests, during the constant voltage phase, ln (I) changes linearly with time t with the slope α = -ε4A eff / (ε1 + ε2 + ε3). The change(s) in the model parameters and / or the change in the gradient m of the line are used as a state indicator according to one or more embodiments.

[0054] With continued reference to Fig. 3A, in block 308, In block 308, the processing system 102 determines (e.g., using the battery health estimation engine 210) whether the health indicator is within an acceptable range. For example, the acceptable range may be limited by a minimum health indicator value and a maximum health indicator value. If the health indicator is a slope (m) of a line fitted to a natural logarithm of the battery current (specified by the current information), the acceptable range may be limited by a minimum slope (m min ) and a maximum gradient (m max ). If the status indicator is a determination coefficient (R 2 ) of a line fitted to a natural logarithm of the battery current (given by the current information), the permissible range can be determined by a minimum coefficient of determination (Rmin2) and a maximum coefficient of determination (Rmin2).

[0055] If it is determined that the condition indicator is within an acceptable range (for example, that the gradient (m) is within the range defined by the minimum gradient (m min ) and the maximum gradient (m max )) (block 308 "YES"), the processing system 102 determines that the battery 104 is in a healthy state (block 310). However, if it is determined that the health indicator is not within an acceptable range (for example, that the gradient (m) is outside the range defined by the minimum gradient (m min ) and the maximum gradient (m max)) (block 308 "NO"), the processing system 102 determines that the battery 104 is in a fault condition (block 312). According to one or more embodiments, the method 300 may include, in response to determining that the battery is in a fault condition, performing a corrective action. Examples of corrective actions include repairing a battery, replacing a battery, addressing an electrolyte leak, redesigning a battery, or adapting a manufacturing process (e.g., based on data collected from multiple batteries / vehicles), and / or the like, including combinations and / or multiples thereof.

[0056] Additional processes may also be included, and it should be understood that the Fig. 3A are illustrations and that other processes may be added or existing processes may be removed, modified, or rearranged without departing from the scope of the present description. It should also be understood that the processes shown in Fig. 3A may be implemented as programmatic instructions stored on a non-transitory, computer-readable storage medium that, when executed by a processor (for example, the processing device 202 of Fig. 2, the processor(s) 621 of Fig. 6 and / or the like, including combinations and / or multiples thereof) of a computer system (for example, the processing system 102 of Fig. 1 and Fig. 2, the processing system 600 of Fig. 6 and / or the like, including combinations and / or multiples thereof) cause the processor to perform the processes described herein.

[0057] Fig. 4A shows diagrams 401, 402, 403, 404 of a first failure mode according to one or more embodiments. In this example, the first failure mode is a loss of active material failure. Diagrams 401 and 402 show the voltage (in volts) and the current (in amperes) over time (in minutes) during constant current charging, respectively, and diagrams 403 and 404 show the voltage (in volts) and the current (in amperes) over time (in minutes) during constant voltage charging, respectively. As can be seen from the comparison of diagrams 401 and 404, a loss of active material failure (e.g., failure mode 1 421) can be observed during constant current charging (diagram 401) and during constant voltage charging (diagram 403) compared to a normal state (normal 422).However, in some cases, some faults may not be obvious during constant current charging, which is one reason for assessing the battery condition using constant voltage current characteristics. Fig. For example, Figure 4B shows a fault condition that is not detectable during constant current charging.

[0058] Fig. 4B specifically illustrates plots 411, 412, 413, and 414 of a second failure mode according to one or more embodiments. In this example, the second failure mode is an electrolyte failure. Plots 411 and 412 respectively plot the voltage (in volts) and current (in amperes) over time (in minutes) during constant current charging, and plots 413 and 414 respectively plot the voltage (in volts) and current (in amperes) over time (in minutes) during constant voltage charging. As can be seen from comparing plots 411 and 414, the electrolyte failure (e.g., failure mode 2 431) is not apparent during constant current charging (plot 411), but can be observed during constant voltage charging (plot 413) compared to a normal condition (normal 432).By estimating battery health based on constant voltage current characteristics, battery faults that would otherwise be undetectable can now be detected, improving vehicle functionality.

[0059] Fig. 5 is a flowchart of a method 500 for estimating battery state using current characteristics at a constant voltage, according to one or more embodiments. The method 500 may be implemented using any suitable system or device. For example, the method 500 may be implemented using the processing system 102 of Fig. 1 and Fig. 2, of the processing system 600 of the Fig. 6 and / or the like, including combinations and / or multiples thereof. The method 500 will now be described with reference to the Fig. 1 and Fig. 2, but is not so limited.

[0060] In block 502, the processing system 102 detects (e.g., using the battery state estimation engine 210) the beginning of a constant voltage operating phase.

[0061] In block 504, the processing system 102 (e.g., using the battery health estimation engine 210) collects current and voltage information about the battery 104 while the battery 104 is in the constant voltage phase of operation.

[0062] In block 506, the processing system 102 calculates a voltage deviation (e.g., using the battery state estimation engine 210). The voltage deviation is a measure of how far the actual voltage is from an expected / desired voltage (e.g., a voltage deviation threshold). If the voltage deviation remains below the voltage deviation threshold (block 508 "NO"), then the battery is not in constant voltage mode (block 510). Otherwise (block 508 "YES"), the method 500 proceeds to block 512 and fits a line to the natural logarithm of the current, as described herein. The slope (m) of the line from block 512 is then calculated in block 514 along with the determination coefficient (R 2 ) is calculated for the line.

[0063] If the slope (m) of the line is within an acceptable range and the coefficient of determination (R 2) for the line is greater than a minimum (Block 516 "YES"), no error is present (Block 518). However, if either the gradient (m) of the line is outside an acceptable range and / or the coefficient of determination (R 2 ) for the line is not greater than a minimum (block 516 "NO"), an error may exist and the method 500 continues with block 520.

[0064] In block 520, it is determined whether the coefficient of determination (R 2 ) for the line is smaller than the minimum. If this is the case (block 520 "YES"), an error is likely (block 522). However, if it is determined that the determination coefficient (R 2) for the line is not less than the minimum, a fault is possible (block 524). To determine if a fault exists and what type of fault it is, the method 500 proceeds to block 526, where the capacity drop of the battery 104 is observed. If the capacity of the battery 104 drops (for example, by a certain amount or percentage, below a threshold, and / or the like, including combinations and / or multiples thereof) (block 526 "YES"), it is determined that a loss of active material (LAM) fault has occurred (block 528). If no capacity drop is detected (block 526 "NO"), an electrolyte fault 530 is determined.

[0065] Additional processes may also be included, and it should be understood that the Fig. 5 are illustrations and that other processes may be added or existing processes may be removed, modified, or rearranged without departing from the scope of this description. It should also be understood that the Fig. 5 may be implemented as programmatic instructions stored on a non-transitory, computer-readable storage medium that, when executed by a processor (for example, the processing device 202 of Fig. 2, the processor(s) 621 of Fig. 6 and / or the like, including combinations and / or multiples thereof) of a computer system (for example, the processing system 102 of Fig. 1 and Fig. 2, the processing system 600 of Fig. 6 and / or the like, including combinations and / or multiples thereof) cause the processor to perform the processes described herein.

[0066] According to one or more embodiments, constant voltage phases may be detected during both the charging and discharging portions for each cell group of the battery 104, and the proposed health indicator(s) may be calculated based on the current profile and compared to other cell groups operated under similar operating conditions.

[0067] According to one or more embodiments, the health indicator may be calculated during operation of the cell in a vehicle or when the battery 104 is removed from the vehicle (e.g., at the end of the assembly line of the cell manufacturing process).

[0068] According to one or more embodiments, the current-based health indicators may be used to determine the degree of aging of the battery 104 and to determine whether the battery 104 has aged abnormally during the course of use of the battery 104 in the vehicle or due to misuse of the cell (e.g., operation of the cell at high temperature).

[0069] According to one or more embodiments, the condition indicator(s) can be used together with other condition indicators to isolate a fault. For example, the electrolyte fault can be isolated from the LAM using the capacity drop, since the LAM terminates with a capacity drop, while an electrolyte fault does not cause a capacity drop.

[0070] It should be understood that one or more of the embodiments described herein may be implemented in connection with any other type of computing environment now known or later developed. Fig.For example, Figure 6 shows a block diagram of a processing system 600 for implementing the techniques described herein. In accordance with one or more embodiments described herein, the processing system 600 is an example of a cloud computing node of a cloud computing environment. In examples, the processing system 600 has one or more central processing units (also referred to as "processors" or "processing resources" or "processing devices") 621a, 621b, 621c, and so on (collectively or generally referred to as processor(s) 621 and / or processing device(s) 621). In aspects of the present description, each processor 621 may include a reduced instruction set (RISC) microprocessor. The processors 621 are connected to a system memory 622 and / or various other components via a system bus 633.System memory 622 may include one or more temporary and / or permanent devices, such as random access memory (RAM) 623, read-only memory (ROM) 624, and / or the like, including combinations and / or multiples thereof. System bus 633 may include a basic input / output system (BIOS) that controls certain basic functions of processing system 600.

[0071] Also shown are an input / output adapter 627 and a network adapter 626 connected to the system bus 633. The I / O adapter 627 may be a Small Computer System Interface (SCSI) adapter that communicates with a hard disk 635 and / or a device 636 or other similar component. The I / O adapter 627, the hard disk 635, and the device 636 are collectively referred to herein as mass storage 634. The operating system 640 for execution on the processing system 600 may be stored in the mass storage 634. The network adapter 626 connects the system bus 633 to an external network 638 so that the processing system 600 can communicate with other such systems.

[0072] A display (e.g., a display monitor) 639 is connected to system bus 633 via display adapter 632, which may include a graphics adapter for enhancing the performance of graphics-intensive applications and a controller for video applications. In one aspect of the present description, adapters 626, 627, and / or 632 may be connected to one or more I / O buses connected to system bus 633 via an intermediate bus bridge (not shown). Suitable I / O buses for connecting peripheral devices such as hard drive controllers, network adapters, and graphics adapters typically include common protocols such as Peripheral Component Interconnect (PCI). Additional input / output devices are connected to system bus 633 via user interface adapter 628 and display adapter 632.A keyboard 629, a mouse 630, and a speaker 631 may be connected to the system bus 633 via the user interface adapter 628, which may include, for example, a super I / O chip that integrates multiple devices into a single integrated circuit.

[0073] In some aspects of the present description, processing system 600 includes a graphics processing unit (GPU) 637. Graphics processing unit 637 is a specialized electronic circuit designed to manipulate and alter memory to accelerate the creation of images in a frame buffer intended for output to a display. In general, graphics processing unit 637 is very efficient at handling computer graphics and image processing and has a highly parallel structure, making it more effective than general-purpose CPUs for algorithms that require parallel processing of large blocks of data.

[0074] As configured herein, processing system 600 includes processing capabilities in the form of processors 621, storage capabilities including system memory 622 and mass storage 634, input means such as keyboard 625 and mouse 630, and output capabilities including speakers 631 and display 639. In some aspects of the present description, a portion of system memory 622 and mass storage 634 collectively store operating system 640 to coordinate the functions of the various components represented in processing system 600.

[0075] The terms "a" and "an" do not imply a limitation of quantity, but denote the presence of at least one of the mentioned elements. The term "or" means "and / or" unless the context clearly indicates otherwise. Whenever "an aspect" is mentioned throughout the description, this means that a particular element (for example, a feature, structure, step, or property) described in connection with the aspect is included in at least one of the aspects described therein and may or may not be present in other aspects. Furthermore, the described elements in the different aspects may be combined in any suitable way.

[0076] When an element such as a layer, film, region, or substrate is described as being "on" another element, it may be directly on top of the other element, or there may be intervening elements. Conversely, when an element is described as being "directly on" another element, there are no intervening elements.

[0077] Unless otherwise indicated herein, all examination standards are the most recent standard in force as of the filing date of this application or, if priority is claimed, the filing date of the earliest priority application in which the examination standard appears.

[0078] Unless otherwise defined, technical and scientific terms used herein have the same meaning as commonly understood by a person skilled in the art to which this description belongs.

Claims

[1] Computer-implemented method (300) comprising: Detecting (302) the start of an operating phase with constant voltage of a vehicle battery (104); Acquiring (304) current and voltage information about the vehicle battery (104); monitoring (306) a condition indicator for the vehicle battery (104) based at least in part on the current information; Determining (308) whether the vehicle battery (104) is in a healthy state or in a fault state by determining whether the condition indicator is within an acceptable range; and in response to determining that the vehicle battery (104) is in the fault condition, performing a corrective action for the vehicle battery (104); wherein the condition indicator is based at least in part on a coefficient of determination of a line fit to a natural logarithm of the battery current indicated by the current information. [2] The computer-implemented method (300) of claim 1, wherein the condition indicator is based at least in part on a slope of a line fitted to a natural logarithm of the battery current indicated by the current information. [3] The computer-implemented method (300) of claim 1, wherein collecting the current information and the voltage information about the vehicle battery (104) is performed while the vehicle battery (104) is in the constant voltage operating phase. [4] The computer-implemented method (300) of claim 1, wherein the collecting is terminated in response to determining that the battery current indicated by the current information reaches a minimum current level. [5] The computer-implemented method (300) of claim 1, wherein the corrective action is at least one of the following: repairing the vehicle battery (104), replacing the vehicle battery (104), correcting an electrolyte leak in the battery (104), redesigning the vehicle battery (104), and adapting a manufacturing process to manufacture other vehicle batteries. [6] The computer-implemented method (300) of claim 1, wherein the error condition is a loss of active material error. [7] The computer-implemented method (300) of claim 1, wherein the fault condition is an electrolyte fault. [8] Vehicle (100), comprising: a vehicle battery (104); and a processing system (102), the processing system (102) comprising: a memory (204) having computer-readable instructions; and a processing device (202) for executing the computer-readable instructions, the computer-readable instructions controlling the processing device (202) to perform operations comprising: Detecting (302) the start of an operating phase with constant voltage of the vehicle battery (104); Acquiring (304) current and voltage information about the vehicle battery (104); monitoring (306) a condition indicator for the vehicle battery (104) based at least in part on the current information; Determining (308) whether the vehicle battery (104) is in a healthy state or in a fault state by determining whether the vehicle battery (104) health indicator is within an acceptable range; and in response to determining that the vehicle battery (104) is in the fault condition, performing a corrective action for the vehicle battery (104); wherein the condition indicator is based at least in part on a coefficient of determination of a line fit to a natural logarithm of the battery current indicated by the current information. [9] A computer program product comprising a computer-readable storage medium having program instructions embodied therein, the program instructions being executable by at least one processor (621) to cause the at least one processor (621) to perform operations, comprising: Detecting (302) the start of an operating phase with constant voltage of a vehicle battery (104); Acquiring (304) current and voltage information about the vehicle battery (104); monitoring (306) a condition indicator for the vehicle battery (104) based at least in part on the current information; Determining (308) whether the vehicle battery (104) is in a healthy state or in a fault state by determining whether the condition indicator is within an acceptable range; and in response to determining that the vehicle battery (104) is in the fault state, performing a corrective action for the vehicle battery (104), wherein the condition indicator is based at least in part on a slope of a line fitted to a natural logarithm of the battery current indicated by the current information, wherein the condition indicator is based at least in part on a determination coefficient of a line fit to a natural logarithm of the current of the vehicle battery (104) indicated by the current information, and where the fault condition is a loss of active material fault or an electrolyte fault.

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