Voltage drop cell detection and cell state of health monitoring

Abstract

A method for determining a state of health of an electric battery comprising a plurality of battery cells. The method comprises the step of measuring a battery voltage of each individual battery cell of the plurality of battery cells, and the step of analyzing each measured battery cell voltage to determine a state of health of the corresponding battery cell.

Description

Technical Field

[0001] This disclosure generally relates to rechargeable energy storage systems (RESS), such as battery packs in vehicles. Background Technology

[0002] Motor vehicles that use RESS (such as battery packs) to store large amounts of energy to provide propulsion are available. These vehicles can include, for example, plug-in hybrid electric vehicles, electric vehicles that use an internal combustion engine as a battery charging generator, and battery electric vehicles. Vehicle battery packs typically use multiple battery cells connected in series to achieve a battery pack voltage compatible with the voltage requirements of the traction motor used for vehicle propulsion. To maximize the vehicle's range and battery pack lifespan, it is desirable to monitor the health status of the battery cells within the battery pack.

[0003] As electric vehicle systems achieve their intended purpose, new and improved systems and methods are needed to monitor the health of battery cells in the battery pack and manage the battery system accordingly. Summary of the Invention

[0004] A method for determining the health status of an electric battery pack comprising multiple battery cells is disclosed according to several aspects. The method includes the steps of measuring the battery voltage of each individual battery cell of the plurality of battery cells, and analyzing each measured battery cell voltage to determine the health status of the corresponding battery cell.

[0005] In an additional aspect of this disclosure, the step of analyzing each measured battery cell voltage includes the following steps: determining an average value of the individually measured battery cell voltages in the battery pack; determining a residual voltage value for each of the individual battery cells, wherein the residual voltage value is calculated as the numerical difference between the measured voltage of a particular individual battery cell and the determined average value; and calculating a standard deviation of the determined residual voltage value at each measurement time. The step of analyzing each measured battery cell voltage further includes: identifying abnormal battery cells as those whose residual voltage values ​​exceed a predetermined multiple of the standard deviation within a predetermined time period; and performing a first action when at least one abnormal battery cell is identified.

[0006] In another aspect of this disclosure, the first action includes setting a diagnostic indicator.

[0007] In another aspect of this disclosure, the first action upon identifying at least one abnormal battery cell includes reducing the maximum power delivered by the battery.

[0008] In an additional aspect of this disclosure, the first action includes calculating a reduction in the battery's remaining available energy based on an estimate of the available energy of the abnormal battery cell.

[0009] In another aspect of this disclosure, the first action includes reducing the permissible charging rate of the battery compared to the permissible charging rate of a battery without abnormal battery cells.

[0010] According to various aspects of this disclosure, the first action includes: determining a second average value as the average of voltages measured after excluding voltages associated with all battery cells identified as anomalous battery cells; and determining a second residual voltage value for each of the battery cells not identified as anomalous battery cells, wherein the second residual voltage value is calculated as the numerical difference between the measured voltage of a particular non-nominal individual battery cell and the determined second average value. The first action further includes: calculating a second standard deviation at each measurement time as the standard deviation of the determined second residual voltage value for the non-nominal battery cells; identifying voltage drop battery cells whose second residual voltage value exceeds a predetermined multiple of the second standard deviation; and performing a second action upon identifying at least one voltage drop battery cell.

[0011] In another aspect of this disclosure, the second action includes setting a diagnostic indicator.

[0012] In an additional aspect of this disclosure, the second action includes reducing the maximum power delivered by the battery.

[0013] In another aspect of this disclosure, the second action includes calculating a reduction in the remaining energy available to the battery based on an estimate of the energy available to the voltage drop battery cell.

[0014] In another aspect of this disclosure, the second action includes reducing the permissible charging rate of the battery compared to the permissible charging rate of a battery without a voltage drop battery cell.

[0015] According to various aspects of this disclosure, analyzing each measured battery cell voltage includes: identifying a battery cell corresponding to the lowest measured battery cell voltage among the plurality of battery cells; determining whether the battery cell corresponding to the lowest measured battery cell voltage has an output voltage that remains below a predetermined threshold voltage for a duration greater than a predetermined threshold duration; and performing a third action if the battery cell corresponding to the lowest measured battery cell voltage has an output voltage that remains below the predetermined threshold voltage for a duration greater than the predetermined threshold duration.

[0016] In another aspect of this disclosure, the third action includes analyzing the cell voltages of adjacent cell cells corresponding to the lowest measured cell voltage of the cell, to determine whether the adjacent cell cell is showing an indication of cell voltage drop.

[0017] In an additional aspect of this disclosure, the third action includes comparing the battery pack temperature, the rate of increase of the battery pack temperature, the battery cell temperature, the rate of increase of the battery cell temperature, the battery pack pressure, and / or the rate of increase of the battery pack pressure with a predetermined threshold.

[0018] In another aspect of this disclosure, the third action includes activating a warning signal.

[0019] According to various aspects of this disclosure, analyzing each measured battery cell voltage includes: estimating the battery cell resistance value during constant charge or discharge conditions using a rolling average algorithm, a Kalman filter, or a recursive least squares algorithm; and performing a fourth action if the estimated battery cell resistance value exceeds a predetermined threshold.

[0020] According to another aspect of this disclosure, the fourth action includes setting a diagnostic indicator.

[0021] According to an additional aspect of this disclosure, the fourth action includes maximizing the power delivered from the battery.

[0022] According to another aspect of this disclosure, the fourth action includes calculating a reduction in the remaining energy available to the battery.

[0023] According to another aspect of this disclosure, the fourth action includes reducing the permissible charging rate of the battery compared to the permissible charging rate of a battery that does not have battery cells with estimated cell resistance values ​​exceeding a predetermined threshold.

[0024] Other areas of application will become apparent from the description provided herein. It should be understood that the descriptions and specific examples are intended for illustrative purposes only and are not intended to limit the scope of this disclosure. Attached Figure Description

[0025] The accompanying drawings described herein are for illustrative purposes only and are not intended to limit the scope of the invention in any way.

[0026] Figure 1 This is a schematic diagram of an equivalent circuit model of an electrochemical cell according to an exemplary embodiment;

[0027] Figure 2 This is a schematic diagram of an electrical architecture including a battery pack containing multiple battery cells, according to an exemplary embodiment.

[0028] Figure 3 This is a flowchart of an algorithm for detecting abnormal battery cells in a battery pack, according to an exemplary embodiment.

[0029] Figure 4This is a flowchart of an algorithm for detecting voltage drop battery cells in a battery pack, according to an exemplary embodiment.

[0030] Figure 5 This is a flowchart of an alternative algorithm for detecting voltage drop battery cells in a battery pack, according to an exemplary embodiment.

[0031] Figure 6 This is a flowchart of an algorithm for detecting short-circuited battery cells in a battery pack, according to an exemplary embodiment. Detailed Implementation

[0032] The following description is merely exemplary in nature and is not intended to limit this disclosure, application, or use.

[0033] Motor vehicles that use RESS (e.g., battery packs) to store large amounts of energy to provide propulsion are available. These vehicles can include, for example, plug-in hybrid electric vehicles (EVs), electric vehicles that use an internal combustion engine as a battery charging generator, and battery electric vehicles. Vehicle battery packs typically use multiple battery cells connected in series to achieve a battery pack voltage compatible with the voltage requirements of the traction electric motor used to propel the vehicle. Battery packs used in vehicles are typically configured with battery cells connected in series, and several of these battery packs can be connected in parallel to provide more power to the vehicle. In a non-limiting example, the battery pack can use lithium-ion battery cells with a nominal voltage of 4.2 volts. The battery pack can use 96 of these 4.2-volt cells connected in series to produce a nominal battery pack voltage of 400 volts.

[0034] Battery cells are susceptible to degradation over time due to manufacturing defects, charge-discharge cycles, and their calendar life. Degradation can lead to increased internal resistance and reduced storage capacity. While degradation at certain normal rates is not unexpected, variations in materials, manufacturing tolerances, or environmental stresses during use can cause a particular cell in a multi-cell battery pack to experience a level of degradation exceeding that experienced by other cells in the pack. A higher degree of degradation in a single cell can reduce the energy storage capacity of the battery pack, thus limiting the range of an electric vehicle. More severe degradation can cause thermal damage to the cell, potentially extending to adjacent cells in the pack. The degree of degradation can be expressed as the state of health of the battery pack. As used herein, the term "state of health" refers to the ability of a battery to store and deliver electrical energy compared to a new battery.

[0035] Reference Figure 1 A schematic diagram of an electrochemical cell unit 10 is shown, illustrating the components of an equivalent circuit model of the electrochemical cell unit 10. This model includes components with an open-circuit voltage V. oc The ideal voltage source is 12. Open-circuit voltage V. ocIt is a function of the battery cell's state of charge (SOC) and the battery cell temperature T. As used herein, the term "state of charge" should be understood as representing the level of charge of a battery cell relative to its capacity. (Continue to refer to...) Figure 1 The model of the electrochemical battery cell 10 includes a hysteresis model 14 to illustrate the behavior of chemical processes occurring during battery charging and discharging. The model also includes a first resistor 16, which represents the ohmic resistance Rm in the electrochemical battery cell. The model of the electrochemical battery cell 10 further includes a second resistor 18 connected in parallel with a first capacitor 22 defining a first RC time constant. The second resistor 18 represents a double-layer resistance Rm. dl The first capacitor 22 represents the double-layer capacitor C. dl The model of the electrochemical cell 10 also includes a third resistor 20 connected in parallel with a second capacitor 24 that defines a second RC time constant. The third resistor 20 represents the diffusion resistance R. diff The second capacitor 24 represents the diffusion capacitance C. diff The resistance values ​​of modeled resistors 16, 18, and 20, and the capacitance values ​​of modeled capacitors 22 and 24, were chosen to closely match the observed steady-state and transient behavior of the electrochemical cell 10. The output voltage of the electrochemical cell 10 appears at the first output terminal 26 relative to the second output terminal 28.

[0036] Degradation of electrochemical battery cells can manifest as cell voltage drop. As used in this paper, cell voltage drop refers to the decrease in the cell's output voltage when current is supplied and / or the increase in the cell's voltage when current is supplied for charging. Cell voltage drop is related to internal resistance Rm and R... dl and / or R diff The increase is related to the reduction in the battery cell voltage drop. The battery cell voltage drop can also be related to the decrease in the battery cell's ability to deliver electrical energy.

[0037] Reference Figure 2 A battery pack 40 with n battery cells is shown, including a first battery cell 42, a second battery cell 44, a third battery cell 46, and so on up to an nth battery cell 48. Each of the multiple battery cells can be implemented as follows: Figure 1The electrochemical cell 10 is shown. Optionally, each of the cell units 42, 44, 46...48 can be implemented as a plurality of electrochemical cell units 10 connected in parallel. In a non-limiting example, each of the cell units 42, 44, 46...48 may contain three electrochemical cell units 10 connected in parallel. The cell units in the battery pack 40 are connected in series, such that the nominal battery pack voltage is n times the cell voltage of each individual cell. In a non-limiting example, the battery pack 40 may contain 96 cell units connected in series, each cell having a nominal rated voltage of 4.2 volts, so as to generate a nominal voltage of 400 volts from the battery pack 40. Current can be supplied to the battery pack 40 during charging, or supplied from the battery pack 40 to a load (not shown), as indicated by arrow 50. It should be understood that although the battery pack 40 is described as a single entity comprising all battery cells 42, 44, 46...48, alternatively, the battery cells 42, 44, 46...48 may be divided into multiple battery modules, wherein each module has one or more battery cells connected in series and each module is connected in series with other modules without departing from the scope of this disclosure.

[0038] Continue to refer to Figure 2The controller 60 receives voltage measurements from the first battery cell 42, the second battery cell 44, the third battery cell 46, etc., via the nth battery cell 48. The controller 60 is a non-general-purpose electronic control device having a pre-programmed digital computer or processor 62, and a memory or non-transitory computer-readable medium 64 for storing data such as control logic, software applications, instructions, computer code, data, lookup tables, etc. The controller 60 is also shown having an input port 66 and an output port 68. The computer-readable medium 64 includes any type of media accessible by a computer, such as read-only memory (ROM), random access memory (RAM), hard disk drive, optical disc (CD), digital video disc (DVD), or any other type of memory. The "non-transitory" computer-readable medium 64 does not include wired, wireless, optical, or other communication links that transmit transient electrical signals or other signals. The non-transitory computer-readable medium 64 includes media in which data can be permanently stored and media in which data can be stored and subsequently rewritten, such as rewritable optical discs or erasable memory devices. Computer code includes any type of program code, including source code, object code, and executable code. Processor 62 is configured to execute code or instructions. The code or instructions may be stored within memory 64 or in additional or separate memory. It should be understood that the elements depicted in the block diagram of controller 60 may alternatively be physically implemented in one or a separate module operatively connected to controller 60 without departing from the scope of the invention. Elements executing computer code may be remotely implemented in the vehicle, for example, having a required dataset sent to the cloud, an algorithm executed by a server in the cloud, and results transmitted back to the vehicle from the cloud. As used herein, the term "cloud" refers to a networked computing facility that provides remote data storage and processing services.

[0039] like Figure 2 As conceptually illustrated, input port 66 receives a first signal 70 representing the measured voltage of the first battery cell 42, a second signal 74 representing the measured voltage of the second battery cell 44, a third signal 76 representing the measured voltage of the third battery cell 46, and a fourth signal 80 representing the measured voltage of the nth battery cell 48. Figure 2 It is also shown that input port 66 receives a set of signals 78 representing the measured voltage of the fourth battery cell (not shown) through the (n-1)th battery cell (not shown).

[0040] Reference Figure 3 The flowchart illustrates an algorithm 100 for detecting abnormal battery cells in battery pack 40. In algorithm step 102, the voltage of each battery cell is measured at time t. In algorithm step 104, the average battery cell voltage is calculated. If the measured voltage of the i-th battery cell at time t is denoted as Vcell... i(t), the average cell voltage Vc_m(t) is calculated as

[0041] Then, Algorithm 100 proceeds to step 106, where a residual array is calculated. For each of the n cells, the residual e i (t) is calculated as e i (t) = Vcell i (t) - Vc_m(t); i = 1, 2,... n. In step 108, the standard deviation σ(t) of all the residuals e i (t) calculated in step 106 is calculated as σ(t) = std(e i (t); i = 1, 2,... n).

[0042] In algorithm step 110, each of the individual residual values e i (t) is compared with the multiplier k(I) times the standard deviation of the residuals calculated in step 108 to identify an abnormal cell. The value of the multiplier k(I) is a function of the cell current I and can be, as a non-limiting example, in the range 2 < k(I) < 4. If the battery pack is being charged when the cell voltage measurement is made in step 102, then if e i (t) > k(I)σ(t), then the i-th cell is identified as an abnormal cell. If the battery is discharging when the battery voltage measurement is made in step 102, then if e i (t) < -k(I)σ(t), then the i-th cell is identified as an abnormal cell. For the charging and discharging cases, the multiplier value k(I) can be the same or can be different. After identifying the abnormal cells in step 110, further analysis can be performed, such as will be explained with respect to Figure 3 and Figure 4 as explained. Figure 3 、 Figure 4 and Figure 5 The connector blocks 112 in Figure 3 indicate the link between Algorithm 100 in Figure 4 and Figure 5 the algorithms described in

[0043] Figure 4 illustrates the use of the algorithms linked by the connector block 112 in Figure 3The flowchart illustrates an exemplary algorithm 120 for identifying voltage drop battery cells based on the results determined in algorithm 100. Algorithm 120 performs step 122, where the average battery cell voltage Vc_m(t) is recalculated as in step 104, except that battery cells identified as outliers in step 110 are excluded from the calculation. Algorithm 120 proceeds to step 124, where residuals are calculated as in step 108, except that the average battery cell voltages calculated in step 122 (excluding outliers) are used instead of the original average calculated in step 104. In step 126, the standard deviation of the residuals calculated in step 124 is calculated using only the residual values ​​of battery cells not identified as outliers in step 110.

[0044] In algorithm step 128, the residual values ​​e calculated in step 124 are... i Each of (t) is compared with the multiplier k(I) of the standard deviation of the residual calculated in step 126 to identify weaker or voltage-dropping battery cells. If the battery is charging when the battery cell voltage measurement is performed in step 102, then if e i If (t)>k(I)σ(t), then the i-th battery cell is identified as a weaker or voltage-dropping battery cell. If the battery is discharging when the battery cell voltage is measured in step 102, then if e i If (t) < -k(I)σ(t), then the i-th cell is identified as a weaker or voltage-drop battery cell. The multiplier k can be the same or different for charging and discharging. Furthermore, the multiplier k can be the same or different from the multiplier k used in the calculation in algorithm step 110.

[0045] Figure 5 The steps of an exemplary algorithm 140 are shown, which can be used as... Figure 4 Algorithm 120 shown is executed instead of being used in connections such as those linked by connector block 112. Figure 3 The result determined in algorithm 100 shown is used to identify the voltage drop battery cell. Algorithm 140 includes multiple counters C[1], C[2], ..., C[n], where each counter is associated with one of the n battery cells in the battery pack 40. In decision block 142, the voltage drop battery cell will be determined. Figure 3 The residual value e calculated for the i-th battery cell in step 106. i The absolute value of (t) is compared with the multiplier k(I) of the standard deviation σ(t) of the residual calculated in step 108. If |e is found in step 142 iIf (t)|>k(l)σ(t), then in step 144, the corresponding counter C[i] of the i-th battery cell is incremented, and the algorithm proceeds to step 152. Incrementing the counter C[i] may include adding 1 to the previous counter value. Alternatively, incrementing the counter C[i] may include adding a value, such as |e i (t)| / k(I)σ(t), so that a larger residual value causes the counter value C[i] to advance faster.

[0046] If |e is found in step 142 i If (t)|≤k(I)σ(t), then in step 146, the corresponding counter C[i] of the i-th battery cell is decremented. In step 148, the decremented counter is checked to see if it has a negative value. If not, the algorithm proceeds to step 152. If the decremented counter has a negative value, then in step 150, the decremented counter is reset to zero. Then, the algorithm proceeds to step 152.

[0047] Continue to refer to Figure 5 In decision box 152, the value of counter C[i] is compared with a predetermined diagnostic threshold. If the counter value exceeds the predetermined diagnostic threshold, a flag is set to identify the i-th battery cell as a voltage drop battery cell. The algorithm exits at step 150. Algorithm steps 142 to 150 are executed for each of the n battery cells in the battery pack 40, and the entire process is repeated over a monitoring time window.

[0048] Figure 6 This is a flowchart of algorithm 160, which can be used to identify thermal runaway conditions in a battery cell. In algorithm step 162, the cell voltage is measured for each of the n cell cells in the battery pack. In algorithm step 164, the cell with the lowest measured cell voltage is identified.

[0049] In the discussion related to Algorithm 160, the battery cell with the lowest measured cell voltage will be referred to as the j-th battery cell. In Algorithm step 166, the average cell voltage Vc_m(t) of the (n-1)-th battery cell in the battery pack, excluding the battery cell with the lowest measured cell voltage (the j-th battery cell), is typically calculated as follows:

[0050]

[0051] If the first cell in the battery pack has the lowest measured cell voltage, then the average cell voltage is calculated as follows:

[0052]

[0053] And if the last (nth) cell in the battery pack has the lowest measured cell voltage, the average cell voltage is calculated as: In algorithm step 166, the standard deviation σ(t) of the (n - 1) cells in the battery pack excluding the cell (the jth cell) with the lowest measured cell voltage is also calculated.

[0054] Then, algorithm 160 proceeds to step 168, which calculates the numerical difference e between the lowest measured cell voltage and the average of the measured cell voltages other than the lowest measured cell voltage j (t) = Vcell j (t) - Vc_m(t). Additionally, in step 168, a test is performed to determine the extent to which the cell voltage of the jth cell is lower than the average cell voltage of the remaining cells. If it is determined that e j (t) ≥ -k(I)σ(t), where the predetermined multiplier k(I) is a function of current, then this is an indication that the degree of voltage drop of the jth cell is not significantly greater than the degree of voltage drop of the entire battery pack, and the algorithm proceeds to step 170, where the timer is reset before proceeding to step 172. If it is determined that e j (t) < -k(I)σ(t), where the predetermined multiplier k(I) is a function of current, then this is an indication that the degree of voltage drop of the jth cell is significantly greater than the degree of voltage drop of the entire battery pack, and the algorithm proceeds directly to step 172.

[0055] Continuing to refer to Figure 6 , in step 172, the timer is incremented. In decision step 174, if |Vcell j (t) - 0| ≥ Vmin, the algorithm proceeds to step 176, where Vcell j (t) is resampled, and the algorithm loops back to step 172. If |Vcell j (t) - 0| < Vmin, the algorithm proceeds to step 178. The comparison value Vmin is a calibration value for identifying a shorted cell. As a non - restrictive example, Vmin can be set to 0.2 volts.

[0056] If there is an indication that the jth cell may be shorted, algorithm 160 reaches step 178. In step 178, it is determined whether the timer value is less than the minimum value t min and whether the measured voltage of the cell adjacent to the jth cell is higher than the maximum threshold V max . As used herein, an adjacent cell refers to a cell located near the jth cell, including but not limited to a cell having a boundary that is in direct physical contact with the boundary of the jth cell. As a non - restrictive example, tmin It could be a value of approximately 0.1 seconds. As a non-restrictive example, V max It can be a value of approximately 5 volts. If the timer value is less than the minimum value t... min Furthermore, the measured voltage of the battery cell adjacent to the j-th battery cell is higher than the maximum threshold V. max If the fault is detected, the algorithm proceeds to step 180, where a sensing fault is marked. Otherwise, the algorithm proceeds to step 182.

[0057] Continue to refer to Figure 6 In step 182, it is determined whether the timer value is greater than the maximum value t. max And whether the measured voltage of the battery cell adjacent to the j-th battery cell is less than the average battery voltage Vc_m(t) plus the value ε. In a non-limiting example, the value ε can be set to k(I)σ(t) volts. In a non-limiting example, t max The value can be set to approximately 5 seconds. If the timer value is greater than the maximum value t... max If the measured voltage of a battery cell adjacent to the j-th battery cell is less than the average battery cell voltage Vc_m(t) plus ε, a short circuit in the battery cell is suspected, and the algorithm proceeds to step 186. Otherwise, the algorithm proceeds to step 184. In step 184, the battery cell voltages of the j-th battery cell and its adjacent cells are resampled, and the algorithm loops back to step 172.

[0058] If the algorithm reaches step 186, a short-circuited battery cell that could potentially cause thermal runaway is suspected. In step 186, further steps can be taken to increase the confidence level of the thermal runaway diagnosis. As a non-limiting example, the cell voltage of nearby battery cells can be checked for voltage drops that may be caused by heat propagation from the overheated short-circuited battery cell. Alternatively or additionally, the battery pack temperature, cell temperature, rate of increase of the battery pack temperature, rate of increase of the cell temperature, battery pack pressure, or rate of increase of the battery pack pressure can be compared to predetermined thresholds and used as an indication to confirm a diagnosis of thermal runaway in a battery cell within the battery pack. Appropriate actions can then be taken, such as illuminating a display or activating an audible alarm, to warn vehicle occupants of a possible thermal runaway condition and to evacuate the vehicle.

[0059] Battery cell degradation leads to a reduction in available energy storage, which can decrease driving range or peak power available for vehicle acceleration. Battery cell degradation can also manifest as an increase in internal resistance within the battery cell. (See again...) Figure 1 Under steady-state constant current or quasi-steady-state charging conditions, the battery cell voltage can be expressed as V(t) = V oc +I*R dl +I*R diff +I*Rm+I*R sys , where Rsys This refers to the resistance of the connectors and wiring associated with the battery cell. The term "quasi-steady state" as used here refers to fluctuations of less than 10% over the considered time period. Total battery cell resistance R cell It can be represented as R cell =R dl +R diff +Rm+R sys =(V(t)–V oc Therefore, the cell resistance can be estimated in the rolling window as ) / I. Where n represents the number of time samples in the rolling window, and V(t) i ) and V oc (t i These are the sampled battery cell voltage and the sampled battery cell open-circuit voltage, respectively.

[0060] As an alternative to using rolling window type calculations to estimate the cell resistance during constant current charging or discharging, Figure 1 The equivalent circuit model shown is simplified to

[0061] R(t i+1 )=R(t i )+ε(t i )

[0062] V(t i+1 )=IR(t i )+V oc (t i )+ζ(t i )

[0063] Wherein, R(t) i ) indicates that at sampling time t i Total cell resistance, V(t) i+1 The sampled battery cell terminal voltage (V) represents the voltage at the sampling point. oc (t i ) represents the sampled open-circuit voltage of the battery cell, ε(t) i ) and ζ(t i The noise represents the process and measurement noise. Using this model, the unit resistance R can be estimated using a standard Kalman filter or a recursive least squares estimation algorithm.

[0064] Information about increased resistance in battery cells or battery packs can be used to enhance the operation of electric vehicles. Depending on the severity of the increased resistance, possible responses include, but are not limited to, suppressing rapid charging of the battery to prevent further battery degradation, reducing vehicle power, recalculating the remaining vehicle range value displayed to the vehicle operator, and indicating that the vehicle needs maintenance.

[0065] The method disclosed for determining the health status of a battery offers several advantages. The ability to identify degradation at the cell level using the disclosed method allows for earlier detection of weaker cells. Appropriate measures can then be taken based on the severity of the cell degradation, including, but not limited to, suppressing or reducing rapid charging to prevent further battery degradation, reducing vehicle power, recalculating the remaining vehicle range value displayed to the vehicle operator, and indicating the need for vehicle repair. The ability to identify short-circuited cells using the disclosed method allows for earlier detection of thermal runaway conditions, providing more time to warn vehicle occupants to leave the vehicle. Furthermore, identifying which specific cell in the battery pack is weak enables the replacement of individual modules in a modular battery pack and allows for the remanufacturing of the battery pack by replacing the weaker cells.

[0066] The description in this disclosure is merely exemplary in nature, and variations thereof that do not depart from the essential points of this disclosure are intended to fall within its scope. Such variations should not be considered as deviations from the scheme and scope of this disclosure.

Claims

1. A method for determining the health status of an electric battery pack, the battery pack comprising a plurality of battery cells, the method comprising the following steps: Measure the cell voltage of each individual cell in the plurality of battery cells; as well as Analyze the voltage of each measured battery cell to determine the health status of the corresponding battery cell; The analysis of the voltage of each measured battery cell includes: Determine the average value of the individually measured cell voltages in the battery pack; Determine the remaining voltage value of each battery cell in the individual battery cells, wherein the remaining voltage value is calculated as the numerical difference between the measured voltage of a particular individual battery cell and a determined average value; Calculate the standard deviation of the determined residual voltage value at each measurement time; Abnormal battery cells are identified as those whose remaining voltage value exceeds a predetermined multiple of the standard deviation within a predetermined time period; and The first action is performed when at least one abnormal battery cell is identified; The first action includes: The second average value is determined as the average value of the voltages measured individually after excluding the voltages associated with all battery cells identified as abnormal battery cells; A second residual voltage value is determined for each of the battery cells that are not identified as abnormal battery cells, wherein the second residual voltage value is calculated as the numerical difference between the measured voltage of a particular non-abnormal individual battery cell and a determined second average value. At each measurement time, a second standard deviation is calculated as the standard deviation of the determined second residual voltage value of the non-abnormal individual battery cell; The voltage drop battery cell is identified as a battery cell whose second residual voltage value exceeds a predetermined multiple of the second standard deviation; and The second action is performed when at least one voltage drop battery cell is identified.

2. The method according to claim 1, wherein, The first action includes setting a diagnostic indicator.

3. The method according to claim 1, wherein, The first action includes reducing the maximum power delivered by the battery.

4. The method according to claim 1, wherein, The first action includes calculating a reduction in the remaining available energy of the battery based on an estimate of the available energy of the abnormal battery cell.

5. The method according to claim 1, wherein, The first action includes reducing the permissible charging rate of the battery compared to the permissible charging rate of a battery without abnormal battery cells.

6. The method according to claim 1, wherein, The second action includes setting a diagnostic indicator.

7. The method according to claim 1, wherein, The second action includes reducing the maximum power delivered by the battery.

8. The method according to claim 1, wherein, The second action includes calculating a reduction in the remaining available energy of the battery based on an estimate of the energy available to the voltage drop battery cell.

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