Battery pack control method and device, vehicle, medium and program product

Abstract

The invention provides a battery pack control method and device, a vehicle, a medium and a program product, and relates to the technical field of batteries, a battery pack comprises a plurality of battery modules connected in parallel, and the method comprises the following steps: for each battery module in the plurality of battery modules, obtaining life influence parameters corresponding to a plurality of single batteries in the battery module; according to the service life influence parameters corresponding to the plurality of single batteries, predicting first residual service lives of the plurality of single batteries and second residual service lives corresponding to the plurality of battery modules; and controlling the battery pack to charge and discharge according to the first residual life or the second residual life. According to the invention, through predicting the double-layer residual life between the single batteries and the battery modules and correspondingly executing the charging and discharging control strategy, the aging speed of the single batteries or the modules can be effectively delayed, and the aging difference between the modules can be balanced, so that the capacity utilization rate of the battery pack is improved, the use safety of the battery pack is further improved, and the overall service life of the battery pack is further prolonged.

Description

Technical Field

[0001] This disclosure relates to the field of battery technology, and in particular to a battery pack control method, apparatus, vehicle, medium, and program product. Background Technology

[0002] In related technologies, battery packs include multiple battery modules connected in parallel, and each battery module includes multiple individual cells connected in series or parallel. The aging rates and lifespan degradation differ between battery modules and among the individual cells within a battery module, leading to a decrease in the utilization rate of the battery pack's usable capacity and a reduction in safety. Summary of the Invention

[0003] This disclosure provides a battery pack control method, apparatus, vehicle, medium, and program product for improving the capacity utilization, safety, and overall service life of the battery pack.

[0004] According to a first aspect of the present disclosure, a battery pack control method is provided, the battery pack comprising a plurality of battery modules connected in parallel, the method comprising: For each of the plurality of battery modules, obtain the lifespan impact parameters corresponding to the plurality of individual cells in the battery module; Based on the lifespan impact parameters corresponding to the plurality of individual cells, the first remaining lifespan of the plurality of individual cells and the second remaining lifespan of the plurality of battery modules are predicted respectively. The battery pack is controlled to charge and discharge based on the first remaining lifespan or the second remaining lifespan.

[0005] In this way, by predicting the remaining life of individual cells and battery modules at two levels and implementing corresponding charge and discharge control strategies, the aging rate of individual cells or modules can be effectively slowed down, the aging differences between modules can be balanced, thereby improving the capacity utilization of the battery pack and further enhancing the safety and overall service life of the battery pack.

[0006] In some possible implementations, controlling the battery pack to charge and discharge based on the second remaining lifetime includes: Based on the second remaining lifespan corresponding to each of the plurality of battery modules, a first lifespan difference degree between each battery module and other battery modules is determined; In response to a first lifespan difference degree corresponding to the first battery module being greater than a first set threshold, the battery pack is controlled to charge and discharge according to the first lifespan difference degree corresponding to the first battery module.

[0007] In this way, by identifying the first battery module with a difference greater than a first set threshold based on the first lifespan difference of the battery module, the battery module with severe aging in the battery pack can be objectively identified, and the charging and discharging control of the first battery module can be performed to avoid the entire battery pack being scrapped due to the premature failure of a few battery modules, thus effectively extending the total lifespan of the entire battery pack.

[0008] In some possible implementations, the battery pack is controlled to charge and discharge based on a first lifespan difference corresponding to the first battery module, including: In this battery cycle, the target charge and discharge power of the first battery module is determined based on the first lifespan difference corresponding to the first battery module, the total charge and discharge power of the battery pack, and the power distribution model. Determine the target charge / discharge power of the first battery module in the previous battery cycle; For the first battery module, the charging and discharging power of the first battery module is controlled based on the target charging and discharging power of the previous battery cycle, the target charging and discharging power of the current battery cycle, and the first lifespan difference.

[0009] In this way, by using the first lifespan difference of the first battery module and the total charging and discharging power of the battery pack, the target charging and discharging power of the first battery module in each cycle is dynamically calculated. Based on the target charging and discharging power of the first battery module in the current battery cycle and the previous battery cycle, the charging and discharging power of the first battery module is controlled, avoiding the shock and potential danger caused by the step change in power, and improving the safety and smoothness of driving.

[0010] In some possible implementations, the charging and discharging power of the first battery module is controlled based on the target charging and discharging power of the previous battery cycle, the target charging and discharging power of the current battery cycle, and the first lifetime difference, including: Determine the power difference between the target charge / discharge power of the previous battery cycle and the target charge / discharge power of the current battery cycle. Based on the power difference and the first lifespan difference, the charging and discharging power of the first battery module is controlled in a closed loop.

[0011] Thus, by performing closed-loop control on the charging and discharging power of the first battery module based on the power difference and the first lifespan difference, stable power control can be achieved for the first battery module with a large degree of aging. This avoids the first battery module from being subjected to excessive current or power surges when the power demand suddenly increases, thereby effectively slowing down the aging rate of the first battery module and improving system stability and lifespan consistency.

[0012] In some possible implementations, the battery pack is controlled to charge and discharge based on a first lifespan difference corresponding to the first battery module, including: Determine the first lifespan difference of the first battery module in the previous battery cycle; The charging and discharging power of the first battery module is controlled based on the first lifespan difference between the previous battery cycle and the current battery cycle.

[0013] Thus, by dynamically adjusting the control strategy based on the relative change trend of the aging rate of the first battery module in different battery cycles, and responding promptly to the deterioration or improvement of the state of the first battery module, a balance can be achieved between the life retention rate and capacity utilization rate of the first battery module.

[0014] In some possible implementations, the charging and discharging power of the first battery module is controlled based on the first lifespan difference corresponding to the previous battery cycle and the current battery cycle, including: Determine the first difference level corresponding to the first lifespan difference of the first battery module in the previous battery cycle; Determine the second difference level corresponding to the first lifespan difference of the first battery module in the current battery cycle; In response to the difference between the first difference level and the second difference level, closed-loop control is performed on the charging and discharging power corresponding to the first battery module.

[0015] In this way, by adjusting the closed-loop control only when a significant increase in the aging rate of the first battery module is detected, minor fluctuations in the degree of difference can be ignored, avoiding unnecessary or frequent control oscillations caused by small fluctuations in values, and greatly improving the stability of the battery management system control and the smoothness of power output.

[0016] In some possible implementations, controlling the battery pack to charge and discharge based on the first remaining lifetime further includes: Determine that the first lifespan difference degree corresponding to the plurality of battery modules is less than or equal to the first set threshold; For each of the plurality of battery modules, a second lifespan difference between the plurality of individual cells is determined based on the first remaining lifespan corresponding to the plurality of individual cells in the battery module. In response to the second lifespan difference corresponding to the second battery module being greater than a second set threshold, charge and discharge control is performed on the plurality of battery modules.

[0017] Thus, by adjusting the consistency of individual cells within a battery module when there is no significant difference in the second remaining life between battery modules, the dispersion of cell aging can be effectively reduced, preventing faults and safety risks caused by cell failures within the module, and enhancing the safety and reliability of the entire battery pack system.

[0018] In some possible implementations, the method further includes: Determine the actual service life of the battery pack; The first set threshold and / or the second set threshold are adjusted based on the actual service life.

[0019] In this way, by dynamically adjusting the degree of restriction on the lifespan difference between modules and between individual cells within a module based on the actual lifespan of the battery pack, the unnecessary protective restrictions triggered by relatively large but normal lifespan differences between modules or between individual cells within a module are significantly reduced, allowing the battery pack to release more available power and capacity, thus increasing the availability of the battery pack.

[0020] In some possible implementations, based on the lifetime impact parameters corresponding to the plurality of individual cells, a first remaining lifetime for each of the plurality of individual cells and a second remaining lifetime for each of the plurality of battery modules are predicted, including: Based on the lifetime impact parameters corresponding to the multiple individual cells, the initial lifetime decay model corresponding to the individual cells is corrected to obtain the corrected lifetime decay model corresponding to the multiple individual cells. Based on the corrected lifetime degradation model corresponding to each of the multiple individual cells, the first remaining lifetime corresponding to each individual cell is predicted. The second remaining lifespan of the battery module is determined based on the first remaining lifespan corresponding to each individual battery cell.

[0021] In this way, by taking into account the aging differences caused by different parameters on individual cells based on the actual lifespan impact parameters of each cell, the initial lifespan degradation model corresponding to each cell is modified, making the prediction of the first remaining lifespan of each cell more consistent with the actual conditions experienced by that cell. This improves the accuracy of the prediction of the remaining lifespan of individual cells and battery modules, thereby enabling the effective implementation of balancing strategies for the battery pack.

[0022] In some possible implementations, based on the lifetime impact parameters corresponding to the plurality of individual cells, the initial lifetime degradation model corresponding to each individual cell is modified to obtain the modified lifetime degradation model corresponding to the plurality of individual cells, including: Based on the lifespan impact parameters corresponding to the plurality of individual cells in a single cell cycle, the first aging characteristics corresponding to the plurality of individual cells are determined. Based on the lifespan impact parameters corresponding to the plurality of individual cells in the plurality of battery cycles, the second aging characteristics corresponding to the plurality of individual cells are determined, and the second aging characteristics are time-series characteristics. Based on the first aging characteristic and the second aging characteristic, the initial lifetime degradation model is modified to obtain the modified lifetime degradation model corresponding to each of the multiple individual cells.

[0023] Thus, by simultaneously considering the aging effects of a single battery cycle and the cumulative effects during long-term battery use, a more comprehensive description of the battery aging process is provided. For battery packs with complex and variable operating conditions (such as those with non-uniform and non-steady-state aging processes), it can better adapt to and predict their non-uniform and non-steady-state aging processes, improve robustness to complex operating conditions, and significantly enhance the prediction accuracy of the remaining life of individual cells and battery modules.

[0024] In some possible implementations, based on the lifetime impact parameters corresponding to the plurality of individual cells in a single cell cycle, the first aging characteristics corresponding to the plurality of individual cells are determined, including: Determine the set weight parameter combinations corresponding to the plurality of individual cells; Based on the lifespan impact parameters and set weight parameters corresponding to the plurality of individual cells in the cycle of the single cell, the first aging characteristics corresponding to the plurality of individual cells are determined.

[0025] Thus, by determining the set weight parameter combination of individual cells, and based on the life impact parameters and set weight parameter combination corresponding to each cell cycle, the first aging characteristic of individual cells is determined, realizing the cell-level evaluation of the aging degree of different individual cells. This can improve the robustness of the evaluation of the aging degree of different individual cells and significantly improve the prediction accuracy of the remaining life of individual cells and battery modules.

[0026] In some possible implementations, determining the set weight parameter combinations corresponding to the plurality of individual cells includes: Determine the operating parameters corresponding to the plurality of individual cells, wherein the operating parameters include at least one of battery temperature and charge / discharge rate; Based on the operating parameters corresponding to the plurality of individual cells, a set weight parameter combination corresponding to the plurality of individual cells is determined, wherein different operating parameters correspond to different set weight parameter combinations.

[0027] In this way, by determining the corresponding set weight parameter combination through different operating condition parameters of a single battery, the first aging characteristic of the single battery can be calculated. In view of the situation that the fixed weight parameter combination cannot reflect the different lifespan differences caused by the battery under different operating conditions, it can dynamically adapt to the changes in the operating condition parameters of the single battery, which greatly improves the prediction accuracy of the remaining lifespan of the single battery and the battery module.

[0028] In some possible implementations, the method further includes: For each of the plurality of individual cells, determine the degree of variation of the lifespan impact parameters of the individual cell between individual cell cycles; In response to the change in the target parameter among the lifetime impact parameters being greater than a third set threshold, the set weight parameter combination is updated.

[0029] In this way, by identifying the degree of change of the parameters in the lifespan influencing parameters, when a target parameter with a large degree of change is identified, the set weight parameter combination can be updated in a timely manner to ensure that the set weight parameter combination can accurately reflect the actual impact of different lifespan influencing parameters on battery aging under the current actual state of the single battery, and ensure the accuracy and reliability of the prediction of the remaining lifespan of the single battery and battery module.

[0030] In some possible implementations, the parameters affecting the lifespan of the single cell include at least one of the following: state of charge parameter, internal resistance parameter, and temperature parameter; The state of charge parameter is determined based on the change in the state of charge of the individual battery cell within a single battery cycle; the internal resistance parameter includes the ratio of the internal resistance increments of the individual battery cell, which is determined based on the increments of the ohmic internal resistance and polarization internal resistance of the individual battery cell within a single battery cycle; the temperature parameter includes a first temperature parameter and / or a second temperature parameter, the first temperature parameter being determined based on the difference between the surface temperature of the individual battery cell and the surface temperature of other individual batteries in the battery module, and the second temperature parameter being determined based on the difference between the surface temperature of the individual battery cell and the ambient temperature.

[0031] Thus, the lifespan influencing parameters of a single battery cell include one or more of the state of charge parameters, internal resistance parameters, and temperature parameters. By considering the impact of multiple dimensions on battery aging, the one-sidedness of predicting the remaining lifespan based on a single lifespan influencing parameter is avoided, thereby improving the accuracy and reliability of predicting the remaining lifespan of single batteries and battery modules.

[0032] According to a second aspect of the present disclosure, a battery pack control device is provided, the battery pack including a plurality of battery modules connected in parallel, the device comprising: The acquisition module is configured to acquire lifespan impact parameters corresponding to multiple individual cells in each of the plurality of battery modules. The prediction module is configured to predict the first remaining lifespan of the plurality of individual cells and the second remaining lifespan of the plurality of battery modules based on the lifespan impact parameters corresponding to the plurality of individual cells respectively. The control module is configured to control the battery pack to charge and discharge based on the first remaining lifespan or the second remaining lifespan.

[0033] In some possible implementations, the control module is configured to: Based on the second remaining lifespan corresponding to each of the plurality of battery modules, a first lifespan difference degree between each battery module and other battery modules is determined; In response to a first lifespan difference degree corresponding to the first battery module being greater than a first set threshold, the battery pack is controlled to charge and discharge according to the first lifespan difference degree corresponding to the first battery module.

[0034] In some possible implementations, the control module is configured to: In this battery cycle, the target charge and discharge power of the first battery module is determined based on the first lifespan difference corresponding to the first battery module, the total charge and discharge power of the battery pack, and the power distribution model. Determine the target charge / discharge power of the first battery module in the previous battery cycle; For the first battery module, the charging and discharging power of the first battery module is controlled based on the target charging and discharging power of the previous battery cycle, the target charging and discharging power of the current battery cycle, and the first lifespan difference.

[0035] In some possible implementations, the control module is configured to: Determine that the first lifespan difference degree corresponding to the plurality of battery modules is less than or equal to the first set threshold; For each of the plurality of battery modules, a second lifespan difference between the plurality of individual cells is determined based on the first remaining lifespan corresponding to the plurality of individual cells in the battery module. In response to the second lifespan difference corresponding to the second battery module being greater than a second set threshold, charge and discharge control is performed on the plurality of battery modules.

[0036] According to a third aspect of the present disclosure, a vehicle is provided, comprising: processor; Memory used to store processor-executable instructions; The processor is configured to execute the battery pack control method described in the first aspect of the present disclosure.

[0037] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the battery pack control method described in the first aspect of the present disclosure.

[0038] According to a fifth aspect of the present disclosure, a computer program product is provided, including a computer program that, when executed by a processor, implements the battery pack control method described in the first aspect of the present disclosure.

[0039] The technical solutions provided by the embodiments of this disclosure may include the following beneficial effects: This disclosure addresses each battery module in a battery pack by acquiring lifetime impact parameters corresponding to multiple individual cells within the battery module; predicting a first remaining lifetime for each individual cell and a second remaining lifetime for each battery module based on these parameters; and controlling the battery pack to charge and discharge based on either the first or second remaining lifetime. Thus, by predicting the remaining lifetime at both the individual cell and module levels and implementing corresponding charge / discharge control strategies, the aging rate of individual cells or modules can be effectively slowed down, aging differences between modules can be balanced, thereby improving the battery pack's capacity utilization and further enhancing its safety and overall lifespan.

[0040] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0041] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0042] Figure 1 This is a flowchart illustrating a battery pack control method according to an exemplary embodiment.

[0043] Figure 2 This is a schematic diagram of the architecture of a battery pack according to an exemplary embodiment.

[0044] Figure 3 This is a flowchart illustrating a battery pack control method according to an exemplary embodiment.

[0045] Figure 4 This is a schematic diagram illustrating the relationship between the initial lifetime decay baseline and the modified lifetime decay curve according to an exemplary embodiment.

[0046] Figure 5 This is a block diagram illustrating a battery pack control device according to an exemplary embodiment.

[0047] Figure 6 This is a block diagram illustrating a vehicle according to an exemplary embodiment. Detailed Implementation

[0048] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0049] In related technologies, multiple factors contribute to differences in the aging rates between individual cells and battery modules. Even within the same batch of production, different individual cells may exhibit manufacturing errors in parameters such as initial capacity, internal resistance, and self-discharge rate. Furthermore, various factors influence the lifespan of the battery pack during its use.

[0050] For example, there is a temperature gradient inside the battery pack. Modules and cells located at the edge or near heat sources usually operate at higher temperatures. Modules and cells exposed to high temperatures for a long time age faster.

[0051] For example, impedance differences between module connections, impedance differences at individual cell connection points within a module, and battery pack structure design can all lead to uneven current distribution between modules and between individual cells within a module. Some cells may experience higher charge and discharge rates, resulting in inconsistent battery aging rates.

[0052] For example, under the control of the battery management system, different modules or cells of the battery pack may experience different ranges of state of charge (SoC) fluctuations and resting times during use.

[0053] For example, lifespan differences between different modules in a battery pack and between different cells within a module can have serious negative impacts.

[0054] For example, the total usable capacity of a battery pack is limited by the module or cell with the shortest lifespan. When the battery system discharges, the module or cell with the shortest lifespan reaches the discharge cutoff condition first, such as the minimum voltage limit, forcing the entire battery pack to stop discharging, even if other healthy modules and cells still have remaining usable capacity that cannot be released.

[0055] For example, cells or modules with high aging levels are more prone to short circuits, lithium plating, thermal runaway, and other risks, leading to battery pack failure and shutdown, and significantly reducing safety.

[0056] The inventors proposed that for battery systems with multiple modules connected in parallel, the aging dispersion of individual cells can be reduced through two-level compensation, both between and within modules.

[0057] Reference Figure 1 , Figure 1 This is a flowchart illustrating a battery pack control method according to an exemplary embodiment, such as... Figure 1 As shown, the battery pack control method can be used in electronic devices, vehicles, and energy storage devices. The battery pack includes multiple battery modules connected in parallel, and the battery pack control method includes the following steps.

[0058] In step S101, for each of the multiple battery modules, the lifespan impact parameters corresponding to the multiple individual cells in the battery module are obtained.

[0059] In step S102, based on the lifespan impact parameters corresponding to the plurality of individual cells, the first remaining lifespan of the plurality of individual cells and the second remaining lifespan of the plurality of battery modules are predicted respectively.

[0060] In step S103, the battery pack is controlled to charge and discharge according to the first remaining lifespan or the second remaining lifespan.

[0061] For example, a battery pack includes multiple battery modules connected in parallel, which can be used for energy storage and also for providing power to equipment. The battery pack / module can be understood as an intermediate product formed by combining individual batteries in series and parallel, and adding individual battery monitoring and management devices.

[0062] For example, a battery module is a secondary unit of a battery pack, comprising a single cell or multiple cells packaged together in series or parallel. A single cell is the most basic electrochemical unit constituting a battery module and a battery pack.

[0063] like Figure 2 The diagram illustrates the architecture of a battery pack, which comprises n battery modules connected in parallel. Battery module 1 includes *a* individual cells, battery module 2 includes *b* individual cells, and battery module 3 includes *c* individual cells. The number of individual cells in the n battery modules can be the same or different; that is, the values ​​of *a*, *b*, and *c* can be equal or completely unequal, and this is not restricted here.

[0064] For example, a Battery Management System (BMS) or other voltage measurement devices can be used to obtain the voltage and current data of individual cells in each battery module within the battery pack. The BMS is a control system designed to protect the safety of the power battery and can monitor the battery pack's operating status at all times.

[0065] For example, lifespan-affecting parameters refer to parameters that significantly influence the aging rate and remaining lifespan of a battery during its use. Lifespan-affecting parameters may include one or more of the following parameters: temperature, charge / discharge rate, depth of charge / discharge, charge / discharge cutoff voltage, cycle count, state of charge, current / voltage fluctuation, and internal resistance.

[0066] For example, temperature can be the surface temperature of a single battery cell or ambient temperature. Charge / discharge rate is the ratio of current magnitude to the capacity of a single battery cell. Depth of charge / discharge is the percentage of a single battery cell's capacity used during each charge / discharge cycle. Charge / discharge cutoff voltage is the highest voltage a single battery cell reaches when charged or the lowest voltage it reaches when discharged. Cycle count is the number of complete charge / discharge cycles a single battery cell has undergone. State of charge (SOC) is the percentage of a single battery cell's current remaining charge relative to its total capacity, especially after prolonged periods at high or low SOC. Internal resistance is the impedance within a single battery cell, which increases with aging.

[0067] For example, the first remaining lifetime refers to the estimated time a single cell can continue to function normally under specific conditions, such as the remaining number of cycles of a single cell, or the total energy that can be released before its capacity decays to a set threshold. A modified lifetime decay curve can be obtained by fitting a baseline lifetime decay curve based on lifetime impact parameters, and the first remaining lifetime can be predicted based on the modified lifetime decay curve.

[0068] For example, the second remaining lifetime refers to the estimated time that a single battery module can still operate normally under specific conditions. The second remaining lifetime may depend on the first remaining lifetime of the individual cells within the module and the module's connection structure, etc. For instance, the second remaining lifetime of the battery module is the minimum or average of the first remaining lifetimes corresponding to multiple individual cells within the battery module.

[0069] For example, historical data of individual cells, current lifespan-affecting parameters, and battery aging models can be used to estimate the future lifespan of a battery. The aging model can be one or more of empirical models, mathematical models, machine learning models, etc.

[0070] For example, a battery management system can continuously or periodically monitor the lifespan-affecting parameters of each individual cell within a battery pack, such as temperature, internal resistance changes, and capacity changes. Using the collected lifespan-affecting parameters, combined with a battery aging model, the initial remaining lifespan of each individual cell can be independently predicted. Based on the predicted initial remaining lifespan of all individual cells within the module, and considering the consistency parameters of the individual cells within the module, such as lifespan differences, temperature distribution, and other parameters, the second remaining lifespan of the battery module can be determined.

[0071] For example, the predicted first and / or second remaining lifetimes can be analyzed. Based on the first or second remaining lifetime, control strategies can be formulated with the goals of maximizing the overall usable life of the battery pack, ensuring charge and discharge safety, and maintaining usable capacity or power.

[0072] For example, the charging and discharging power of the battery module corresponding to the single cell with the shortest remaining life can be reduced, while the charging and discharging power of other battery modules can be increased accordingly, so as to ensure that the charging and discharging power of all battery modules meets the charging and discharging requirements of the battery pack.

[0073] For example, it can reduce charging current or power, terminate charging earlier, and perform targeted balancing for modules and / or individual units with short lifespans.

[0074] In addition, it can output prompts to remind users to replace modules or units whose lifespan is about to end.

[0075] In this way, by predicting the remaining life of individual cells and battery modules at two levels and implementing corresponding charge and discharge control strategies, the aging rate of individual cells or modules can be effectively slowed down, the aging differences between modules can be balanced, thereby improving the capacity utilization of the battery pack and further enhancing the safety and overall service life of the battery pack.

[0076] In some possible implementations, controlling the battery pack to charge and discharge based on the second remaining lifetime includes: Based on the second remaining lifespan corresponding to each of the plurality of battery modules, a first lifespan difference degree between each battery module and other battery modules is determined; In response to a first lifespan difference degree corresponding to the first battery module being greater than a first set threshold, the battery pack is controlled to charge and discharge according to the first lifespan difference degree corresponding to the first battery module.

[0077] For example, the first lifetime difference is a quantitative metric used to measure the degree of difference between the remaining lifetime of a particular battery module and the remaining lifetime of all other battery modules in the battery pack. For each battery module, the degree of difference between the second remaining lifetime of that battery module and the second remaining lifetime of all other modules in the battery pack can be determined.

[0078] For example, the first lifetime difference can be the difference between the second remaining lifetime of a battery module and the second remaining lifetime of its neighboring battery modules; the first lifetime difference can also be the difference between the second remaining lifetime of a battery module and the median corresponding to the second remaining lifetime of the battery modules.

[0079] For example, the first lifespan difference can also be the battery module whose second remaining lifespan ranking percentile is less than a set value among all battery modules, such as the battery module whose second remaining lifespan ranking is the lowest in the last 10% among multiple battery modules.

[0080] For example, based on the target battery module, the average lifespan of the second remaining lifespan corresponding to other battery modules can be determined, and the first lifespan difference can be determined based on the difference between the second remaining lifespan corresponding to the target battery module and the average lifespan.

[0081] For example, the first set threshold is a pre-set critical value used to determine whether the first lifetime difference has reached the level for charge / discharge control measures to be taken. The first set threshold can be set based on experience, safety margins, and performance optimization goals, etc., and is not limited here.

[0082] For example, the first battery module is a specific battery module whose first lifespan difference is greater than a first set threshold. Specifically, the first battery module is the battery module in the current battery pack that ages the fastest and has the shortest remaining lifespan compared to other modules, and the first battery module limits the charging and discharging performance of the entire battery pack.

[0083] For example, the first lifespan difference of each battery module can be compared with a preset first threshold. If the first lifespan difference of any battery module is greater than the first threshold, it indicates that the battery module ages too quickly compared to other modules, and the battery module can be identified as the first battery module.

[0084] For example, the charging and discharging strategy of the entire battery pack can be determined based on the first lifespan difference of the first battery module to protect the first battery module, slow down its further aging, prevent it from failing prematurely, thereby maximizing the usable lifespan of the entire battery pack and ensuring safety.

[0085] For example, the maximum charging and discharging power or current of the first battery module can be limited based on the first lifespan difference corresponding to the first battery module.

[0086] For example, the charging and discharging power or current allocated to the first battery module can be determined based on the first lifespan difference corresponding to the first battery module and the charging and discharging power or current required by the battery pack.

[0087] In this way, by identifying the first battery module with a difference greater than a first set threshold based on the first lifespan difference of the battery module, the battery module with severe aging in the battery pack can be objectively identified, and the charging and discharging control of the first battery module can be performed to avoid the entire battery pack being scrapped due to the premature failure of a few battery modules, thus effectively extending the total lifespan of the entire battery pack.

[0088] In some possible implementations, the battery pack is controlled to charge and discharge based on a first lifespan difference corresponding to the first battery module, including: In this battery cycle, the target charge and discharge power of the first battery module is determined based on the first lifespan difference corresponding to the first battery module, the total charge and discharge power of the battery pack, and the power distribution model. Determine the target charge / discharge power of the first battery module in the previous battery cycle; For the first battery module, the charging and discharging power of the first battery module is controlled based on the target charging and discharging power of the previous battery cycle, the target charging and discharging power of the current battery cycle, and the first lifespan difference.

[0089] For example, the current battery cycle refers to one or more complete charge-discharge processes that the battery pack is currently undergoing. The previous battery cycle is the complete charge-discharge process corresponding to the one or more battery cycles preceding the current battery cycle.

[0090] For example, the current battery cycle is the cycle corresponding to 50 battery cycles, and the previous battery cycle is the cycle corresponding to 50 battery cycles prior to the current battery cycle. For example, the first 20 battery cycles are the first battery cycle, the 21st to 40th battery cycles are the second battery cycle, and so on.

[0091] For example, the total charging and discharging power of the battery pack refers to the total power demand of the entire battery pack in the current cycle, which can be determined by receiving instructions from the vehicle controller or the upper-level system through the battery management system.

[0092] For example, the power allocation model can be a mathematical model, a machine learning algorithm, or a neural network model, which can be used to allocate the total charge and discharge power demand of the battery pack to the individual battery modules within the pack. The input parameters of the power allocation model can include at least: the total power demand of the battery pack in this battery cycle, and the first lifetime difference of the first battery module, and may also include other possible state parameters, such as temperature and SoC.

[0093] For example, the target charge / discharge power refers to the charge / discharge power allocated to the first battery module in this battery cycle, calculated based on the total power demand of the battery pack in this battery cycle, the first lifespan difference of the first battery module, and the power allocation model.

[0094] For example, the total power requirement for this battery cycle, the first lifetime difference of the first battery module, and other possible parameters can be input into the power allocation model to determine how much power to allocate to the first battery module safely and reliably while meeting the total power requirement. The greater the first lifetime difference of the first battery module, the lower the target charge / discharge power may be allocated to the first battery module.

[0095] For example, the target charge / discharge power of the first battery module in the previous battery cycle can be obtained from the storage unit of the battery management system. Specifically, after determining the target charge / discharge power of the first battery module based on the total power demand of the battery pack in the current battery cycle, the first lifetime difference of the first battery module, and the power allocation model, the battery management system can store the target charge / discharge power in the storage unit for use in the next battery cycle.

[0096] For example, the charging and discharging power of the first battery module can be controlled based on the target charging and discharging power of the previous battery cycle, the target charging and discharging power of the current battery cycle, and the first lifetime difference.

[0097] For example, to avoid excessive impact on the battery module, the rate of change of power may need to be controlled. The difference in charge / discharge power or current between two battery cycles can be determined based on the target charge / discharge power of the previous battery cycle and the target charge / discharge power of the current battery cycle. The charge / discharge power or current of the first battery module can then be controlled based on the difference in charge / discharge power or current and the first lifetime difference of the first battery module.

[0098] In this way, by using the first lifespan difference of the first battery module and the total charging and discharging power of the battery pack, the target charging and discharging power of the first battery module in each cycle is dynamically calculated. Based on the target charging and discharging power of the first battery module in the current battery cycle and the previous battery cycle, the charging and discharging power of the first battery module is controlled, avoiding the shock and potential danger caused by the step change in power, and improving the safety and smoothness of driving.

[0099] In some possible implementations, the charging and discharging power of the first battery module is controlled based on the target charging and discharging power of the previous battery cycle, the target charging and discharging power of the current battery cycle, and the first lifetime difference, including: Determine the power difference between the target charge / discharge power of the previous battery cycle and the target charge / discharge power of the current battery cycle. Based on the power difference and the first lifespan difference, the charging and discharging power of the first battery module is controlled in a closed loop.

[0100] For example, the power difference can be the difference between the target charge / discharge power of the current battery cycle and the target charge / discharge power of the previous battery cycle. The power difference can be used to characterize the direction and magnitude of control over the charge / discharge power of the first battery module.

[0101] For example, closed-loop control is a control relationship in which the controlled output is fed back to the control input in a certain way, and the control effect is applied to the input. This is used to ensure that the power of the first battery module stably reaches the target charge / discharge power corresponding to the current battery cycle. Closed-loop control can employ PID algorithms and / or fuzzy control.

[0102] Here, the input to the PID algorithm can be the first lifetime difference, the target of the PID algorithm can be the power difference, and the coefficients corresponding to the proportional, integral, and derivative in the PID algorithm can be set according to the actual situation.

[0103] Here, fuzzy control can determine the corresponding power value for each adjustment based on the first lifetime difference and power gap, and the specific mapping rules can be set according to the actual situation.

[0104] Here, the input to the PID algorithm can be the first lifetime difference, the target of the PID algorithm can be the power difference, and the coefficients corresponding to the proportional, integral, and derivative in the PID algorithm can be dynamically determined according to the fuzzy control algorithm.

[0105] For example, the first lifetime difference can be used as the input to a PID controller, and the power difference can be used as the control target of the PID controller. The power output of the first battery module is controlled by the adjustment value output by the PID controller until power compensation is completed and the output power of the first battery module reaches the target charge / discharge power corresponding to the current battery cycle.

[0106] Thus, by performing closed-loop control on the charging and discharging power of the first battery module based on the power difference and the first lifespan difference, stable power control can be achieved for the first battery module with a large degree of aging. This avoids the first battery module from being subjected to excessive current or power surges when the power demand suddenly increases, thereby effectively slowing down the aging rate of the first battery module and improving system stability and lifespan consistency.

[0107] In some possible implementations, the battery pack is controlled to charge and discharge based on a first lifespan difference corresponding to the first battery module, including: Determine the first lifespan difference of the first battery module in the previous battery cycle; The charging and discharging power of the first battery module is controlled based on the first lifespan difference between the previous battery cycle and the current battery cycle.

[0108] For example, the battery management system can obtain the first lifetime difference of the first battery module in the previous battery cycle. The charging and discharging power of the first battery module can then be controlled based on the first lifetime difference of the first battery module in the previous and current battery cycles.

[0109] For example, the first lifespan difference corresponding to the current battery cycle is the lifespan difference of the first battery module relative to other modules in the current battery cycle; the first lifespan difference corresponding to the previous battery cycle is the lifespan difference of the first battery module relative to other modules in the previous battery cycle.

[0110] For example, based on the first lifespan difference degree corresponding to the first battery module in the previous battery cycle and the current battery cycle, it can be determined whether the lifespan difference of the first battery module relative to other battery modules changes in two adjacent battery cycles, and if so, the degree of change.

[0111] For example, a certain first battery module has a lifespan difference of 20 cycles compared to other battery modules in the first 50 cycles; and a lifespan difference of 50 cycles compared to other battery modules in the 51st-100th cycles. This indicates that the first battery module ages faster than other battery modules.

[0112] For example, the protection level for the first battery module can be dynamically adjusted based on the relative trend of the aging rate of the first battery module. If the first battery module is deteriorating faster than other battery modules, the power limit on the first battery module can be increased; if the deterioration rate of the first battery module is relatively stable or slowed down compared to other battery modules, the current power limit on the first battery module can be reduced or maintained.

[0113] For example, after the end of this battery cycle, the corresponding first lifetime difference can be used to compare the first lifetime difference in the next battery cycle, continuously adjusting the control strategy to achieve closed-loop control.

[0114] Thus, by dynamically adjusting the control strategy based on the relative change trend of the aging rate of the first battery module in different battery cycles, and responding promptly to the deterioration or improvement of the state of the first battery module, a balance can be achieved between the life retention rate and capacity utilization rate of the first battery module.

[0115] In some possible implementations, the charging and discharging power of the first battery module is controlled based on the first lifespan difference corresponding to the previous battery cycle and the current battery cycle, including: Determine the first difference level corresponding to the first lifespan difference of the first battery module in the previous battery cycle; Determine the second difference level corresponding to the first lifespan difference of the first battery module in the current battery cycle; In response to the difference between the first difference level and the second difference level, closed-loop control is performed on the charging and discharging power corresponding to the first battery module.

[0116] For example, the first difference level is the difference level corresponding to the first lifespan difference of the first battery module in the previous battery cycle, and the second difference level is the difference level corresponding to the first lifespan difference of the first battery module in the current battery cycle.

[0117] For example, the lifespan variation of the battery module can be pre-divided into multiple variation levels. These can be high, medium, and low levels, with each level corresponding to a different variation range. For instance, the ranges for high, medium, and low levels are 20-50%, 15-20%, and 5-15%, respectively.

[0118] For example, the lifespan difference can be divided according to a first preset threshold. The first preset threshold can be determined as the minimum value among the lowest difference levels. For instance, when the first preset threshold is 10%, the difference range corresponding to the lowest difference level could be 10-20%, etc. The maximum value among the highest difference levels can be determined according to the safety difference threshold of a single battery cell. For instance, when the first lifespan difference of the first battery module relative to other battery modules reaches 60%, the first battery module needs to be scrapped or replaced to ensure safety; the difference range corresponding to the highest difference level could be 50-60%, etc.

[0119] It is understood that the numerical examples above are for illustrative purposes only and are not intended to limit the actual implementation.

[0120] For example, the battery management system can determine a first difference level corresponding to the first lifetime difference of the first battery module in the previous battery cycle, and determine a second difference level corresponding to the first lifetime difference of the first battery module in the current battery cycle. The first difference level and the second difference level can be compared.

[0121] For example, if the first difference level and the second difference level are the same, no power control adjustment is triggered, and the previous control strategy can be maintained or baseline control can be executed. If the first difference level and the second difference level are different, it can indicate that the aging degree of the first battery module has changed significantly, that is, the relative aging rate of the first battery module has changed significantly, and the charging and discharging power corresponding to the first battery module can be adjusted through closed-loop control.

[0122] For example, the charging and discharging power limiting strategy for the first battery module can be significantly adjusted according to the direction and magnitude of the level transition. For instance, if the first difference level is medium and the second difference level is high, the maximum allowable charging and discharging power of the first battery module can be reduced by a set value; if the first difference level is medium and the second difference level is medium, the maximum allowable charging and discharging power of the first battery module can be kept unchanged.

[0123] In this way, by adjusting the closed-loop control only when a significant increase in the aging rate of the first battery module is detected, minor fluctuations in the degree of difference can be ignored, avoiding unnecessary or frequent control oscillations caused by small fluctuations in values, and greatly improving the stability of the battery management system control and the smoothness of power output.

[0124] In some possible implementations, controlling the battery pack to charge and discharge based on the first remaining lifespan further includes: determining that the first lifespan difference degree corresponding to the plurality of battery modules is less than or equal to the first set threshold; for each of the plurality of battery modules, determining the second lifespan difference degree between the plurality of individual cells based on the first remaining lifespan corresponding to the plurality of individual cells in the battery module; and controlling the battery pack to charge and discharge based on the second lifespan difference degree corresponding to the second battery module.

[0125] In some possible implementations, controlling the battery pack to charge and discharge based on the first remaining lifetime further includes: Determine that the first lifespan difference degree corresponding to the plurality of battery modules is less than or equal to the first set threshold; For each of the plurality of battery modules, a second lifespan difference between the plurality of individual cells is determined based on the first remaining lifespan corresponding to the plurality of individual cells in the battery module. In response to the second lifespan difference corresponding to the second battery module being greater than a second set threshold, charge and discharge control is performed on the plurality of battery modules.

[0126] For example, the second lifetime variability is a variability index defined within a single battery module, reflecting the inconsistency in the aging rate of individual cells within that module. For a specific battery module, the second lifetime variability can be used to quantify the degree of lifetime difference between the first remaining lifetimes of the individual cells within that module.

[0127] For example, the second lifespan difference can be the standard deviation of the first remaining lifespan of multiple individual cells in the battery module, or the range of the first remaining lifespan of multiple individual cells in the battery module, i.e., the difference between the maximum and minimum values, or the ratio of the shortest lifespan cell to the average lifespan of multiple individual cells in the battery module, etc.

[0128] For example, the second set threshold is a pre-set critical value used to determine whether the second lifetime difference has reached the level for charge / discharge control measures to be taken. The second set threshold can be set based on experience, safety margins, and performance optimization goals, etc., and is not limited here.

[0129] For example, the second battery module is a specific battery module whose second lifespan difference is greater than a second set threshold. Specifically, the second battery module itself has a first lifespan difference less than or equal to the first set threshold among battery modules, but the aging rates of the individual cells within the second battery module are inconsistent, resulting in significant differences in lifespan between individual cells and other individual cells.

[0130] For example, the premise that the first lifespan difference degree corresponding to multiple battery modules is less than or equal to a first set threshold is that the lifespan difference degree among all battery modules in the battery pack is not significant, that is, there is no battery module whose aging rate is much faster than other battery modules. The aging state among the battery modules is relatively uniform.

[0131] For example, when it is determined that the second lifespan difference of the second battery module is greater than the second set threshold, the charging and discharging of the entire battery pack can be controlled according to the set strategy to balance the inconsistency of individual cells within the second battery module.

[0132] For example, the charge and discharge rate of the battery pack can be limited, and reducing the rate can reduce the current stress on all individual cells.

[0133] For example, active balancing of the second battery module can be initiated to reduce the charging and discharging power or current of the second battery module, while increasing the charging and discharging power or current of other battery modules to meet the total charging and discharging requirements of the battery pack, which can alleviate voltage or capacity differences caused by inconsistent lifespan of individual batteries.

[0134] For example, after controlling the charge and discharge of the plurality of battery modules in response to the second lifetime difference corresponding to the second battery module being greater than the second set threshold, the state of the plurality of individual batteries in the second battery module can be continuously monitored to update the prediction of the first remaining lifetime and the calculation of the second lifetime difference.

[0135] Thus, by adjusting the consistency of individual cells within a battery module when there is no significant difference in the second remaining life between battery modules, the dispersion of cell aging can be effectively reduced, preventing faults and safety risks caused by cell failures within the module, and enhancing the safety and reliability of the entire battery pack system.

[0136] In some possible implementations, the method further includes: Determine the actual service life of the battery pack; The first set threshold and / or the second set threshold are adjusted based on the actual service life.

[0137] For example, actual service life refers to the total operating time or historical cycle count of a battery pack from the time it is put into actual use to the current moment. Actual service life can also be calculated as an indicator reflecting the overall aging degree by taking into account factors such as time, cycle count, temperature, and depth of charge and discharge. For example, the equivalent number of cycles or equivalent time corresponding to the capacity retention rate decaying from 100% to the current retention rate value.

[0138] For example, the first set threshold is a preset critical value used to determine whether the first lifespan difference between battery modules is too large, and the second set threshold is a preset critical value used to determine whether the second lifespan difference between multiple individual cells in the battery module is too large.

[0139] For example, as the battery pack ages as a whole, the natural degradation of the performance of individual cells and battery modules is inevitable and common. With a long battery pack lifespan, a certain degree of lifespan difference between battery modules or between individual cells within a battery module is normal and expected. If, in the later stages of battery pack aging, previously set, relatively strict thresholds are still used, protection controls may be triggered too frequently, such as power limiting or premature termination of charging and discharging, resulting in excessive limitation of the battery pack's power or usable capacity, and the remaining value of the battery pack cannot be fully utilized.

[0140] For example, based on the actual service life of the battery pack at present, the first set threshold and / or the second set threshold can be increased according to preset rules, and the adjusted new threshold will be used for subsequent judgment of the first life difference and the second life difference.

[0141] For example, it can be linearly adjusted by summing the adjustment coefficient and the actual service life, along with the initial threshold, to determine the adjusted threshold.

[0142] For example, multiple key threshold adjustment nodes can be defined, such as looping 500 times, 1000 times, and 1500 times, increasing the threshold by a fixed value at each node. The adjustment methods for the first and second set thresholds, and the adjustment values ​​for each time, can be the same or different; there are no restrictions here.

[0143] In this way, by dynamically adjusting the degree of restriction on the lifespan difference between modules and between individual cells within a module based on the actual lifespan of the battery pack, the unnecessary protective restrictions triggered by relatively large but normal lifespan differences between modules or between individual cells within a module are significantly reduced, allowing the battery pack to release more available power and capacity, thus increasing the availability of the battery pack.

[0144] In some possible implementations, based on the lifetime impact parameters corresponding to the plurality of individual cells, a first remaining lifetime for each of the plurality of individual cells and a second remaining lifetime for each of the plurality of battery modules are predicted, including: Based on the lifetime impact parameters corresponding to the multiple individual cells, the initial lifetime decay model corresponding to the individual cells is corrected to obtain the corrected lifetime decay model corresponding to the multiple individual cells. Based on the corrected lifetime degradation model corresponding to each of the multiple individual cells, the first remaining lifetime corresponding to each individual cell is predicted. The second remaining lifespan of the battery module is determined based on the first remaining lifespan corresponding to each individual battery cell.

[0145] For example, an initial life degradation model is a model used to predict the lifespan of a single battery cell. It can be a function model, an empirical model, a relationship curve, etc. However, this initial life degradation model is based on laboratory test data and does not consider the individual performance of single batteries under real-world, complex operating conditions. For example, it does not consider the lifespan changes of single batteries under conditions such as uneven temperature, differences in internal resistance, differences in capacity, and differences in charge / discharge rates.

[0146] For example, a modified lifetime degradation model is a model obtained by adjusting an initial lifetime degradation model, and can be used to predict the lifetime of a specific single cell. Specifically, the modified lifetime degradation model can be obtained by modifying the initial lifetime degradation model based on lifetime impact parameters monitored in actual use of a single cell.

[0147] For example, if the initial lifetime degradation model is a polynomial mathematical model, the coefficients or weight parameters corresponding to different terms in the initial lifetime degradation model can be dynamically adjusted according to the variables in the individual cells of the polynomial mathematical model, such as the surface temperature, internal resistance, and state of charge of the individual cells.

[0148] For example, if the initial lifetime degradation model is a time-series superposition of multiple lifetime-affecting parameters, the time-series characteristics of the individual battery can be obtained based on the actual time-series distribution data of charge-discharge rate, state of charge change, resistance change, temperature change, etc. in multiple battery cycles, and the weight parameters of the initial lifetime degradation model can be adjusted according to the time-series characteristics.

[0149] For example, actual measured capacity decay data or internal resistance growth data can be used to update model parameters in real time through methods such as Kalman filtering and Bayesian inference, so that the predictions can better match the actual aging trajectory of the monomer.

[0150] For example, the first remaining lifespan of a single battery cell can be predicted using a modified lifespan degradation model corresponding to that single cell. The second remaining lifespan of a single battery module can be determined by the first remaining lifespans of multiple single cells within that module. For instance, the minimum of the first remaining lifespans among the multiple single cells in a single battery module can be determined as the second remaining lifespan, or the average or median of the first remaining lifespans among the multiple single cells can be determined as the second remaining lifespan.

[0151] In this way, by taking into account the aging differences caused by different parameters on individual cells based on the actual lifespan impact parameters of each cell, the initial lifespan degradation model corresponding to each cell is modified, making the prediction of the first remaining lifespan of each cell more consistent with the actual conditions experienced by that cell. This improves the accuracy of the prediction of the remaining lifespan of individual cells and battery modules, thereby enabling the effective implementation of balancing strategies for the battery pack.

[0152] In some possible implementations, based on the lifetime impact parameters corresponding to the plurality of individual cells, the initial lifetime degradation model corresponding to each individual cell is modified to obtain the modified lifetime degradation model corresponding to the plurality of individual cells, including: Based on the lifespan impact parameters corresponding to the plurality of individual cells in a single cell cycle, the first aging characteristics corresponding to the plurality of individual cells are determined. Based on the lifespan impact parameters corresponding to the plurality of individual cells in the plurality of battery cycles, the second aging characteristics corresponding to the plurality of individual cells are determined, and the second aging characteristics are time-series characteristics. Based on the first aging characteristic and the second aging characteristic, the initial lifetime degradation model is modified to obtain the modified lifetime degradation model corresponding to each of the multiple individual cells.

[0153] For example, a single battery cycle refers to a set number of complete charge-discharge cycles. Multiple battery cycles are consecutive battery cycles that constitute a time series. For instance, a single battery cycle is 50 complete charge-discharge cycles, and 6 battery cycles are 300 consecutive complete charge-discharge cycles.

[0154] For example, the first aging feature is a feature extracted from lifetime impact parameters monitored within a single battery cycle. The first aging feature can be used to quantify the degree of influence of the lifetime impact parameters on the aging of a single battery cell within a single battery cycle. The second aging feature is a feature extracted from the time series of lifetime impact parameters or the first aging feature monitored over multiple battery cycles. The second aging feature can be used to quantify the long-term aging trend and degree of aging of the lifetime impact parameters on a single battery cell over multiple battery cycles.

[0155] For example, the first aging feature can be obtained by linearly extracting and fusing features from multiple lifetime-affecting parameters. For instance, a linear fusion function can be pre-established to extract features from the corresponding lifetime-affecting parameters, and then the features of multiple lifetime-affecting parameters can be fused by weighted summation to obtain the first aging feature.

[0156] For example, the second aging feature can be obtained by nonlinearly extracting and fusing features from multiple lifetime-affecting parameters corresponding to multiple battery cycles. For instance, an LSTM neural network can be used to extract and fuse the temporal features of multiple lifetime-affecting parameters to obtain the second aging feature corresponding to each individual battery cell. Here, the second aging feature is a temporal feature, including multiple temporal feature sequences.

[0157] For example, the current state of the initial lifetime degradation model can be updated using the first aging feature, and the changing trend of lifetime-influencing parameters in the initial lifetime degradation model can be predicted using the second aging feature. Furthermore, the weight parameters or coefficients in the calculation model corresponding to the first aging feature can be adjusted to correct the initial lifetime degradation model, resulting in a corrected lifetime degradation model. The first remaining lifetime of the individual battery cell can then be predicted using the corrected lifetime degradation model.

[0158] Thus, by simultaneously considering the aging effects of a single battery cycle and the cumulative effects during long-term battery use, a more comprehensive description of the battery aging process is provided. For battery packs with complex and variable operating conditions (such as those with non-uniform and non-steady-state aging processes), it can better adapt to and predict their non-uniform and non-steady-state aging processes, improve robustness to complex operating conditions, and significantly enhance the prediction accuracy of the remaining life of individual cells and battery modules.

[0159] In some possible implementations, based on the lifetime impact parameters corresponding to the plurality of individual cells in a single cell cycle, the first aging characteristics corresponding to the plurality of individual cells are determined, including: Determine the set weight parameter combinations corresponding to the plurality of individual cells; Based on the lifespan impact parameters and set weight parameters corresponding to the plurality of individual cells in the cycle of the single cell, the first aging characteristics corresponding to the plurality of individual cells are determined.

[0160] For example, the weighting parameter combination is a set of predefined weighting coefficients for each individual cell. This weighting parameter combination includes multiple weighting coefficients, each corresponding to a specific lifetime-affecting parameter. For example, the weighting coefficient for temperature is w1, for rate capability it is w2, for SoC it is w3, and for internal resistance it is w4, etc.

[0161] For example, different individual cells can have different combinations of weighting parameters. Different combinations of weighting parameters can be used to characterize factors such as manufacturing differences between individual cells and their different positions within the battery pack, which lead to different degrees of aging of different individual cells in the same cycle.

[0162] For example, each lifespan-affecting parameter of a single battery cell can be processed, such as taking the average value, maximum value, time exceeding the threshold, cumulative stress value, etc., to extract the features corresponding to each lifespan-affecting parameter, and then perform a weighted summation using the set weight parameters corresponding to the single battery cell and the features corresponding to multiple lifespan-affecting parameters respectively, to obtain the first aging feature corresponding to the single battery cell.

[0163] Thus, by determining the set weight parameter combination of individual cells, and based on the life impact parameters and set weight parameter combination corresponding to each cell cycle, the first aging characteristic of individual cells is determined, realizing the cell-level evaluation of the aging degree of different individual cells. This can improve the robustness of the evaluation of the aging degree of different individual cells and significantly improve the prediction accuracy of the remaining life of individual cells and battery modules.

[0164] In some possible implementations, determining the set weight parameter combinations corresponding to the plurality of individual cells includes: Determine the operating parameters corresponding to the plurality of individual cells, wherein the operating parameters include at least one of battery temperature and charge / discharge rate; Based on the operating parameters corresponding to the plurality of individual cells, a set weight parameter combination corresponding to the plurality of individual cells is determined, wherein different operating parameters correspond to different set weight parameter combinations.

[0165] For example, operating condition parameters refer to the state parameters of a single battery cell during its current operation. Operating condition parameters include at least one of battery temperature and charge / discharge rate. Specifically, battery temperature is the current temperature of the single battery cell; for example, it can be the average or maximum surface temperature of the single battery cell. Charge / discharge rate is the current discharge rate of the single battery cell; for example, it can be the average or maximum rate during charging or discharging of the single battery cell.

[0166] For example, a correspondence is established between the set weight parameter combinations and the operating condition parameters, with different operating condition parameters corresponding to different set weight parameter combinations. This correspondence can be established using, for example, a rule base, a function, or a lookup table; there are no restrictions here. Different set weight parameter combinations and their corresponding operating condition parameters can be set based on battery aging test data, empirical values, etc.; there are no restrictions here either.

[0167] For example, when a single battery cell is under a specific combination of operating parameters, such as when the battery temperature is higher than a first set value and the charge / discharge rate is greater than a second set value, a target weighted parameter combination can be used. In the target weighted parameter combination, the weight coefficients corresponding to temperature and internal resistance are larger, while the weight coefficients corresponding to SoC are smaller.

[0168] For example, the battery management system can monitor the operating parameters of each individual battery cell in real time or periodically, including battery temperature and / or charge / discharge rate. Based on a predefined mapping relationship, the system can determine the corresponding set weighted parameter combination for that individual battery cell at that moment, according to the current combination of operating parameters.

[0169] For example, by combining the weighted parameter combination corresponding to the current operating condition of a single battery cell with the lifetime impact parameters collected during this battery cycle, the first aging characteristic of the single battery cell in this battery cycle can be determined. This first aging characteristic can be used to correct the model and predict the lifetime of individual cells and modules.

[0170] In this way, by determining the corresponding set weight parameter combination through different operating condition parameters of a single battery, the first aging characteristic of the single battery can be calculated. In view of the situation that the fixed weight parameter combination cannot reflect the different lifespan differences caused by the battery under different operating conditions, it can dynamically adapt to the changes in the operating condition parameters of the single battery, which greatly improves the prediction accuracy of the remaining lifespan of the single battery and the battery module.

[0171] In some possible implementations, the method further includes: For each of the plurality of individual cells, determine the degree of variation of the lifespan impact parameters of the individual cell between individual cell cycles; In response to the change in the target parameter among the lifetime impact parameters being greater than a third set threshold, the set weight parameter combination is updated.

[0172] For example, a single battery cycle refers to the number of consecutive battery charge-discharge cycles over time, where a single battery cycle includes multiple battery cycles. The degree of variation refers to the amount of numerical change of one or more parameters among the lifespan-affecting parameters between single cycle cycles.

[0173] For example, the third threshold is a preset critical value that can be used to determine whether the degree of change of any parameter in the lifetime impact parameters between single cycles is sufficient to trigger an update event for the weight combination. The target parameters are one or more parameters in the lifetime impact parameters whose degree of change is greater than the third threshold.

[0174] For example, the third threshold setting can filter out normal fluctuations or single abnormal events that affect the lifetime parameters. The weight parameter combination will only be updated when the change is continuous and significant, thus avoiding frequent and ineffective adjustment of the weight parameter combination due to noise.

[0175] For example, if the change in the target parameter exceeds a third preset threshold, it indicates that the target parameter of the single battery cell has undergone a sudden change, and the set weight parameter combination may no longer be applicable. The first aging characteristic can be calculated in the next battery cycle based on the updated set weight parameter combination after updating and storing the set weight parameter combination, or the first aging characteristic can be recalculated in the current battery cycle based on the updated set weight parameter combination.

[0176] For example, if the parameters affecting lifespan include the temperature parameter, internal resistance parameter, and state of charge (SCC) parameter of a single cell, then: For instance, if the temperature parameter of a single cell changes by more than 10% between individual cell cycles, it indicates a sudden change in the surface temperature of that cell, and the weighting parameter corresponding to that temperature parameter can be increased accordingly. If the internal resistance parameter of a single cell changes by more than 5% between individual cell cycles, it indicates a sudden change in the internal resistance of that cell, and the weighting parameter corresponding to that internal resistance parameter can be increased accordingly. If the SCC parameter of a single cell changes by more than 30% between individual cell cycles, it indicates a sudden change in the SCC of that cell, and the weighting parameter corresponding to that SCC parameter can be increased accordingly.

[0177] In this way, by identifying the degree of change of the parameters in the lifespan influencing parameters, when a target parameter with a large degree of change is identified, the set weight parameter combination can be updated in a timely manner to ensure that the set weight parameter combination can accurately reflect the actual impact of different lifespan influencing parameters on battery aging under the current actual state of the single battery, and ensure the accuracy and reliability of the prediction of the remaining lifespan of the single battery and battery module.

[0178] In some possible implementations, the parameters affecting the lifespan of the single cell include at least one of the following: state of charge parameter, internal resistance parameter, and temperature parameter; The state of charge parameter is determined based on the change in the state of charge of the individual battery cell within a single battery cycle; the internal resistance parameter includes the ratio of the internal resistance increments of the individual battery cell, which is determined based on the increments of the ohmic internal resistance and polarization internal resistance of the individual battery cell within a single battery cycle; the temperature parameter includes a first temperature parameter and / or a second temperature parameter, the first temperature parameter being determined based on the difference between the surface temperature of the individual battery cell and the surface temperature of other individual batteries in the battery module, and the second temperature parameter being determined based on the difference between the surface temperature of the individual battery cell and the ambient temperature.

[0179] For example, the state of charge (SOC) parameter can characterize the dynamic change in the SOC of a single battery cell within a single battery cycle. For instance, the SOC parameter can be obtained from the difference between the SOC at the beginning and end of a single battery cycle. Alternatively, the SOC parameter can be obtained from the standard deviation of the SOC within a single battery cycle, i.e., the difference between the maximum and minimum SOC values ​​within a single battery cycle.

[0180] For example, the internal resistance parameter includes the ratio of the internal resistance increments of a single cell, which is the ratio of the increment of ohmic internal resistance to the increment of polarization internal resistance. Ohmic internal resistance is the resistance caused by the resistance to ion conduction within the battery. Polarization internal resistance is the internal resistance caused by polarization during the electrochemical reaction between the positive and negative electrodes of the battery. The increment of ohmic internal resistance is the increase in ohmic internal resistance within a single cell cycle, and the increment of polarization internal resistance is the increase in polarization internal resistance within a single cell cycle.

[0181] For example, the temperature parameters include a first temperature parameter and a second temperature parameter. The first temperature parameter can be determined based on the difference between the surface temperature of the individual battery cell and the surface temperature of other individual batteries in the battery module. The second temperature parameter can be determined based on the difference between the surface temperature of the individual battery cell and the ambient temperature, and can be used to reflect the heat generation intensity of the individual battery cell relative to the ambient temperature.

[0182] For example, the first temperature parameter can be the standard deviation between the surface temperature of a single cell and the surface temperature of other single cells, or it can be the difference between the surface temperature of a single cell and the average surface temperature of other single cells.

[0183] Thus, the lifespan influencing parameters of a single battery cell include one or more of the state of charge parameters, internal resistance parameters, and temperature parameters. By considering the impact of multiple dimensions on battery aging, the one-sidedness of predicting the remaining lifespan based on a single lifespan influencing parameter is avoided, thereby improving the accuracy and reliability of predicting the remaining lifespan of single batteries and battery modules.

[0184] Reference Figure 3-4 An exemplary embodiment of a battery pack control method is proposed, wherein the battery pack control method can be used in a battery management system, which may include a multi-parameter fusion module, a life prediction module, an equalization control module, and a closed-loop equalization control module.

[0185] Here, the multi-parameter fusion module can collect parameters that affect lifespan.

[0186] For example, lifetime-affecting parameters include SoC volatility, internal resistance growth rate, and temperature gradient characteristics. SoC volatility can be determined by the SoC standard deviation (σ_SoC) of a single cell within a single cycle; the internal resistance growth rate ΔR can be determined based on the incremental ratio of the ohmic internal resistance R_O to the polarization internal resistance R_P of a single cell within a single cycle, and can be expressed as ΔR = ΔR_O / ΔR_P; the temperature gradient characteristics include the root mean square deviation (σ_T) of the surface temperature of a single cell within a single cycle and the difference between the surface temperature of the single cell and the ambient temperature (ΔT_amb).

[0187] For example, the multi-parameter fusion module can perform linear fusion of parameters affecting lifespan to obtain a first aging characteristic. For instance, the first aging characteristic λ can be calculated using the following formula. i :λ i =w1×f(σ_SoC)+w2×g(ΔR)+w3×h(σ_T, ΔT_amb); where f() can represent the feature extraction function corresponding to SoC volatility; g() can represent the feature extraction function corresponding to the internal resistance growth rate; h() can represent the feature extraction function corresponding to the temperature gradient feature; w1, w2 and w3 are the weight parameters corresponding to SoC volatility, internal resistance growth rate and temperature gradient feature respectively.

[0188] For example, preset weight combinations can be switched based on operating condition parameters. The preset weight combinations corresponding to different operating condition parameters can be pre-set according to actual conditions. For instance, under operating conditions corresponding to high temperature and high magnification, the values ​​of w2 and w3 are larger, while under other operating conditions, the values ​​of w2 and w3 are smaller.

[0189] For example, the multi-parameter fusion module can process lifetime-influencing parameters to obtain a second aging feature. For instance, an LSTM neural network can be used to extract and fuse features from time-series data of multiple lifetime-influencing parameters.

[0190] Here, the lifetime prediction module can pre-establish an initial lifetime degradation baseline for individual cells based on laboratory data. For example, an 80% capacity retention rate corresponds to 1000 cycles. Figure 4 As shown, the modified lifetime decay curve 402 can be obtained by correcting the initial lifetime decay baseline 401 of the single cell, and the predicted first remaining lifetime of the single cell can be output.

[0191] For example, the initial lifetime degradation baseline of a single-cell battery can be corrected using a Bayesian inference framework. The prior distribution of the Bayesian inference is based on an initial lifetime degradation baseline pre-established using laboratory data. The probability distribution of lifetime-influencing parameters such as SoC volatility, internal resistance growth rate, and temperature gradient characteristics is monitored in real-time using a likelihood function. Then, the posterior distribution is updated using a Bayesian formula based on the prior distribution and the likelihood function, thus correcting the initial lifetime degradation baseline and obtaining the corrected lifetime degradation curve. Bayesian inference can then yield the predicted first remaining lifetime for a single-cell battery.

[0192] For example, a sliding window can be used to detect whether lifetime-influencing parameters have undergone abrupt changes. Specifically, the relationship between the degree of change in lifetime-influencing parameters within two adjacent cycle periods and a set threshold can be used to determine whether abrupt changes have occurred. If abrupt changes occur, weight redistribution logic can be triggered to update the weight parameters corresponding to SoC volatility, internal resistance growth rate, and temperature gradient characteristics, respectively. For instance, if the internal resistance increases by >5% in a single cycle, the weight parameter corresponding to the internal resistance growth rate can be increased.

[0193] Here, the power equalization control module can perform power equalization between battery modules and power equalization between individual cells within a battery module.

[0194] For example, the second remaining lifespan of each battery module can be determined based on the average of the first remaining lifespans of multiple individual cells within the battery module, and the first lifespan difference degree corresponding to the second remaining lifespan of the target battery module relative to the second remaining lifespans of other battery modules can be determined. For example, the first lifespan difference degree ΔRUL_avg can be determined by the following formula: ΔRUL_avg=|RUL_A-RUL_B|; where RUL_A can represent the second remaining lifespan of the target battery module, RUL_B can represent the second remaining lifespans of other battery modules, and when there are multiple other battery modules, RUL_B can represent the average of the second remaining lifespans of the other battery modules.

[0195] For example, when the first lifetime difference ΔRUL_avg is greater than a first set threshold, power balancing is performed between battery modules.

[0196] For example, the target charge / discharge power allocated to the target battery module within the current battery cycle can be determined using an exponential decay function. For instance, the target charge / discharge power P_A corresponding to the target battery module can be determined using the following formula: P_A = P_total × [1 - α·exp(-β·ΔRUL_avg)]; where P_total represents the total charge / discharge power of the battery pack within the current battery cycle, exp(x) represents an exponential function with the natural constant e as its base, and α and β can be obtained by fitting actual data.

[0197] For example, PID control can be used to control the charging and discharging power allocated to the target battery module within the current battery cycle until the target charging and discharging power is reached. Specifically, the target charging and discharging power allocated to the target battery module in the previous battery cycle can be obtained. Based on the target charging and discharging power allocated to the target battery module in the current battery cycle, the power gap ΔP to be compensated is determined. Then, based on the power gap and ΔRUL_avg, PID control is performed using the following formula: ΔP = K_p × ΔRUL_avg + K_i × ∫ΔRUL_avg dt + K_d × dΔRUL_avg / dt; where K_p, K_i, and K_d are the coefficients corresponding to the PID controller and can be set according to actual conditions.

[0198] For example, fuzzy control can be used to determine the activation conditions of PID control. For instance, ΔRUL_avg can be defined as three intervals: low, medium, and high. When the ΔRUL_avg of two adjacent battery cycles does not belong to the same interval, PID control can then be used to control the charging and discharging power allocated to the target battery module in the current battery cycle.

[0199] For example, based on the rule of prioritizing power balancing among battery modules, when it is determined that the first lifetime difference ΔRUL_avg of all battery modules is less than or equal to a first set threshold, the second lifetime difference corresponding to the first remaining lifetime of individual cells in the battery module can be calculated. For example, the standard deviation σ_RUL or the range ΔRUL_local corresponding to the first remaining lifetime of all individual cells in the battery module.

[0200] For example, when σ_RUL is greater than the second set threshold, or ΔRUL_local is greater than the second set threshold, power balancing can be performed on the battery module. For instance, the power or current of the battery module corresponding to the single cell with the highest dispersion can be limited, while the power or current of other battery modules can be increased to meet the total charging and discharging power of the battery pack. Local current limiting (e.g., reducing the current ratio by 10%) can also be used.

[0201] Here, the closed-loop equalization control module has a data feedback mechanism. Specifically, the lifetime prediction module can output RUL distribution to the equalization control module. The equalization control module generates a compensation signal based on ΔRUL_avg or σ_RUL and performs power distribution. After adjustment, the power and / or current data can be returned to the multi-parameter fusion module to form closed-loop control.

[0202] For example, the first and second set thresholds can be dynamically adjusted as the battery ages. For instance, the thresholds are lower in the early stages of battery pack use and higher in the later stages.

[0203] According to actual tests, the internal resistance parameter was measured every 10 minutes using the pulse charge-discharge method. After 2000 cycles, the capacity retention rate of the battery module was still greater than 85%, and the capacity deviation rate of the individual cells after aging was 9%, which is significantly lower than the deviation of existing technologies.

[0204] This disclosure reduces the overload probability of low-lifespan individual cells by controlling multiple parameters such as internal resistance, temperature, and SoC, significantly increasing the lifespan of the battery module. Furthermore, this disclosure requires no additional hardware, relying solely on the battery management system to complete power distribution, making it suitable for battery structures with multiple battery modules connected in parallel.

[0205] Reference Figure 5 , Figure 5 This is a block diagram illustrating a battery pack control device 500 according to an exemplary embodiment. (Refer to...) Figure 5 The battery pack includes multiple battery modules connected in parallel. The battery pack control device 500 includes an acquisition module 501, a determination module 502, and a conversion module 503.

[0206] The acquisition module 501 is configured to acquire lifespan impact parameters corresponding to each of the multiple battery modules in the battery pack for each of the multiple battery modules in the battery module. The prediction module 502 is configured to predict the first remaining lifespan of the plurality of individual cells and the second remaining lifespan of the plurality of battery modules based on the lifespan impact parameters corresponding to the plurality of individual cells respectively. The control module 503 is configured to control the battery pack to charge and discharge based on the first remaining lifespan or the second remaining lifespan.

[0207] In some possible implementations, the control module 503 is configured to: Based on the second remaining lifespan corresponding to each of the plurality of battery modules, a first lifespan difference degree between each battery module and other battery modules is determined; In response to a first lifespan difference degree corresponding to the first battery module being greater than a first set threshold, the battery pack is controlled to charge and discharge according to the first lifespan difference degree corresponding to the first battery module.

[0208] In some possible implementations, the control module 503 is configured to: In this battery cycle, the target charge and discharge power of the first battery module is determined based on the first lifespan difference corresponding to the first battery module, the total charge and discharge power of the battery pack, and the power distribution model. Determine the target charge / discharge power of the first battery module in the previous battery cycle; For the first battery module, the charging and discharging power of the first battery module is controlled based on the target charging and discharging power of the previous battery cycle, the target charging and discharging power of the current battery cycle, and the first lifespan difference.

[0209] In some possible implementations, the control module 503 is configured to: Determine the power difference between the target charge / discharge power of the previous battery cycle and the target charge / discharge power of the current battery cycle. Based on the power difference and the first lifespan difference, the charging and discharging power of the first battery module is controlled in a closed loop.

[0210] In some possible implementations, the control module 503 is configured to: Determine the first lifespan difference of the first battery module in the previous battery cycle; The charging and discharging power of the first battery module is controlled based on the first lifespan difference between the previous battery cycle and the current battery cycle.

[0211] In some possible implementations, the control module 503 is configured to: Determine the first difference level corresponding to the first lifespan difference of the first battery module in the previous battery cycle; Determine the second difference level corresponding to the first lifespan difference of the first battery module in the current battery cycle; In response to the difference between the first difference level and the second difference level, closed-loop control is performed on the charging and discharging power corresponding to the first battery module.

[0212] In some possible implementations, the control module 503 is further configured to: Determine that the first lifespan difference degree corresponding to the plurality of battery modules is less than or equal to the first set threshold; For each of the plurality of battery modules, a second lifespan difference between the plurality of individual cells is determined based on the first remaining lifespan corresponding to the plurality of individual cells in the battery module. In response to the second lifespan difference corresponding to the second battery module being greater than a second set threshold, charge and discharge control is performed on the plurality of battery modules.

[0213] In some possible implementations, the battery pack control device 500 is further configured to: Determine the actual service life of the battery pack; The first set threshold and / or the second set threshold are adjusted based on the actual service life.

[0214] In some possible implementations, the prediction module 502 is configured to: Based on the lifetime impact parameters corresponding to the multiple individual cells, the initial lifetime decay model corresponding to the individual cells is corrected to obtain the corrected lifetime decay model corresponding to the multiple individual cells. Based on the corrected lifetime degradation model corresponding to each of the multiple individual cells, the first remaining lifetime corresponding to each individual cell is predicted. The second remaining lifespan of the battery module is determined based on the first remaining lifespan corresponding to each individual battery cell.

[0215] In some possible implementations, the prediction module 502 is configured to: Based on the lifespan impact parameters corresponding to the plurality of individual cells in a single cell cycle, the first aging characteristics corresponding to the plurality of individual cells are determined. Based on the lifespan impact parameters corresponding to the plurality of individual cells in the plurality of battery cycles, the second aging characteristics corresponding to the plurality of individual cells are determined, and the second aging characteristics are time-series characteristics. Based on the first aging characteristic and the second aging characteristic, the initial lifetime degradation model is modified to obtain the modified lifetime degradation model corresponding to each of the multiple individual cells.

[0216] In some possible implementations, the prediction module 502 is configured to: Determine the set weight parameter combinations corresponding to the plurality of individual cells; Based on the lifespan impact parameters and set weight parameters corresponding to the plurality of individual cells in the cycle of the single cell, the first aging characteristics corresponding to the plurality of individual cells are determined.

[0217] In some possible implementations, the prediction module 502 is configured to: Determine the operating parameters corresponding to the plurality of individual cells, wherein the operating parameters include at least one of battery temperature and charge / discharge rate; Based on the operating parameters corresponding to the plurality of individual cells, a set weight parameter combination corresponding to the plurality of individual cells is determined, wherein different operating parameters correspond to different set weight parameter combinations.

[0218] In some possible implementations, the battery pack control device 500 is further configured to: For each of the plurality of individual cells, determine the degree of variation of the lifespan impact parameters of the individual cell between individual cell cycles; In response to the change in the target parameter among the lifetime impact parameters being greater than a third set threshold, the set weight parameter combination is updated.

[0219] In some possible implementations, the parameters affecting the lifespan of the single cell include at least one of the following: state of charge parameter, internal resistance parameter, and temperature parameter; The state of charge parameter is determined based on the change in the state of charge of the individual battery cell within a single battery cycle; the internal resistance parameter includes the ratio of the internal resistance increments of the individual battery cell, which is determined based on the increments of the ohmic internal resistance and polarization internal resistance of the individual battery cell within a single battery cycle; the temperature parameter includes a first temperature parameter and / or a second temperature parameter, the first temperature parameter being determined based on the difference between the surface temperature of the individual battery cell and the surface temperature of other individual batteries in the battery module, and the second temperature parameter being determined based on the difference between the surface temperature of the individual battery cell and the ambient temperature.

[0220] Regarding the battery pack control device 500 in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the battery pack control method, and will not be elaborated here.

[0221] Based on the same inventive concept, this disclosure also provides a vehicle, comprising: processor; Memory used to store processor-executable instructions; The processor is configured to execute the battery pack control method described in this disclosure.

[0222] Based on the same inventive concept, this disclosure also provides a computer-readable storage medium storing computer program instructions thereon, which, when executed by a processor, implement the battery pack control method provided in this disclosure.

[0223] Based on the same inventive concept, this disclosure also provides a computer program product, including a computer program that, when executed by a processor, implements the battery pack control method described in this disclosure.

[0224] Reference Figure 6 , Figure 6 This is a block diagram illustrating a vehicle 600 according to an exemplary embodiment. For example, vehicle 600 can be a hybrid vehicle, a non-hybrid vehicle, an electric vehicle, a fuel cell vehicle, or other types of vehicle. Vehicle 600 can be an autonomous vehicle, a semi-autonomous vehicle, or a non-autonomous vehicle.

[0225] like Figure 6 As shown, vehicle 600 may include various subsystems, such as infotainment system 610, perception system 620, decision control system 630, drive system 640, and computing platform 660. Vehicle 600 may also include more or fewer subsystems, and each subsystem may include multiple components. Furthermore, each subsystem and each component of vehicle 600 can be interconnected via wired or wireless means.

[0226] In some embodiments, the infotainment system 610 may include a communication system, an entertainment system, and a navigation system, etc.

[0227] The perception system 620 may include several sensors for sensing information about the environment surrounding the vehicle 600. For example, the perception system 620 may include a global positioning system (which may be GPS, BeiDou, or other positioning systems), an inertial measurement unit (IMU), lidar, millimeter-wave radar, ultrasonic radar, and a camera device.

[0228] The decision control system 630 may include a computing system, a vehicle controller, a steering system, a throttle, and a braking system.

[0229] The drive system 640 may include components that provide powered motion to the vehicle 600. In one embodiment, the drive system 640 may include an engine, an energy source, a transmission system, and wheels. The engine may be one or a combination of internal combustion engines, electric motors, and compressed air engines. The engine is capable of converting energy provided by the energy source into mechanical energy.

[0230] Some or all of the functions of vehicle 600 are controlled by computing platform 660. Computing platform 660 may include at least one processor 661 and memory 662, processor 661 may execute instructions 663 stored in memory 662.

[0231] Processor 661 can be any conventional processor, such as a commercially available CPU. Processors may also include graphics processing units (GPUs), field-programmable gate arrays (FPGAs), systems-on-chips (SoCs), application-specific integrated circuits (ASICs), or combinations thereof.

[0232] The memory 662 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0233] In addition to instruction 663, memory 662 can also store data, such as road maps, route information, vehicle position, direction, speed, and other data. The data stored in memory 662 can be used by computing platform 660.

[0234] In this embodiment of the disclosure, processor 661 may execute instruction 663 to complete all or part of the steps of the battery pack control method described above.

[0235] Furthermore, the term “exemplary” is used herein to mean serving as an example, instance, or illustration. Any aspect or design described herein as “exemplary” is not necessarily to be construed as advantageous compared to other aspects or designs. Rather, the use of the term “exemplary” is intended to present the concept in a concrete manner. As used herein, the term “or” is intended to mean an inclusive “or” rather than an exclusive “or.” That is, unless otherwise specified or clear from the context, “X applies A or B” is intended to mean any of the natural inclusive arrangements. That is, “X applies A or B” satisfies any of the foregoing instances if X applies A; X applies B; or both X applies A and B. Additionally, unless otherwise specified or clear from the context to refer to the singular form, the articles “a” and “an” as used in this application and the appended claims are generally understood to mean “one or more.”

[0236] Although terms such as “first,” “second,” and “third” may be used herein to describe various components, parts, regions, layers, or sections, these components, parts, regions, layers, or sections are not limited to these terms. Rather, these terms are used only to distinguish one component, part, region, layer, or section from another. Therefore, without departing from the teachings of the examples described herein, the first component, part, region, layer, or section mentioned in the examples may also be referred to as the second component, part, region, layer, or section. Furthermore, the terms “first” and “second” are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as “first” or “second” may explicitly or implicitly include at least one of that feature. In the description herein, “a plurality” means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0237] Similarly, although this disclosure has been shown and described with respect to one or more implementations, equivalent variations and modifications will occur to those skilled in the art upon reading and understanding this specification and the accompanying drawings. This disclosure includes all such modifications and variations and is limited only by the scope of the claims. In particular, with respect to the various functions performed by the components described above (e.g., elements, resources, etc.), unless otherwise indicated, the terminology used to describe such components is intended to correspond to any component (functionally equivalent) that performs the specific function of the described component, even if structurally not equivalent to the disclosed structure. Furthermore, although specific features of this disclosure may have been disclosed with respect to only one of several implementations, such features may be combined with one or more other features of other implementations, as may be desired and advantageous to any given or particular application. Moreover, with regard to the terms “comprising,” “owning,” “having,” “having,” or variations thereof as used in the detailed description or claims, such terms are intended to be inclusive in a manner similar to the term “including.”

[0238] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the appended claims.

[0239] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A battery pack control method, characterized by, The battery pack includes a plurality of battery modules in parallel, and the method includes: For each battery module of the plurality of battery modules, obtaining a life influence parameter corresponding to each of a plurality of single batteries in the battery module; According to the life influence parameter corresponding to each of the plurality of single batteries, the first residual life of each of the plurality of single batteries and the second residual life corresponding to each of the plurality of battery modules are predicted; According to the first residual life or the second residual life, the battery pack is controlled to charge and discharge.

2. The method of claim 1, wherein, According to the second residual life, the battery pack is controlled to charge and discharge, including: According to the second residual life corresponding to each of the plurality of battery modules, the first life difference degree between each battery module and other battery modules is determined; In response to the first life difference degree corresponding to the first battery module being greater than a first set threshold, the battery pack is controlled to charge and discharge according to the first life difference degree corresponding to the first battery module.

3. The method of claim 2, wherein, According to the first life difference degree corresponding to the first battery module, the battery pack is controlled to charge and discharge, including: In the current battery cycle period, the target charge and discharge power of the first battery module is determined according to the first life difference degree corresponding to the first battery module, the total power of the battery pack and the power distribution model; The target charge and discharge power of the first battery module in the last battery cycle period is determined; For the first battery module, the charge and discharge power of the first battery module is controlled according to the target charge and discharge power of the last battery cycle period, the target charge and discharge power of the current battery cycle period and the first life difference degree.

4. The method of claim 3, wherein, According to the target charge and discharge power of the last battery cycle period, the target charge and discharge power of the current battery cycle period and the first life difference degree, the charge and discharge power of the first battery module is controlled, including: The power gap between the target charge and discharge power of the last battery cycle period and the target charge and discharge power of the current battery cycle period is determined; According to the power gap and the first life difference degree, the charge and discharge power corresponding to the first battery module is closed-loop controlled.

5. The method of claim 2, wherein, According to the first life difference degree corresponding to the first battery module, the battery pack is controlled to charge and discharge, including: The first life difference degree corresponding to the first battery module in the last battery cycle period is determined; According to the first life difference degree corresponding to the first battery module in the last battery cycle period and the current battery cycle period, the charge and discharge power of the first battery module is controlled.

6. The method of claim 5, wherein, According to the first life difference degree corresponding to the first battery module in the last battery cycle period and the current battery cycle period, the charge and discharge power of the first battery module is controlled, including: The first difference level corresponding to the first life difference degree of the first battery module in the last battery cycle period is determined; The second difference level corresponding to the first life difference degree of the first battery module in the current battery cycle period is determined; In response to the first difference level and the second difference level being different, the charging and discharging power corresponding to the first battery module is controlled in a closed loop.

7. The method of claim 2, wherein, According to the first residual life, the battery pack is controlled to charge and discharge, and further comprising: It is determined that the first life difference degree corresponding to the plurality of battery modules is less than or equal to the first set threshold; For each battery module in the plurality of battery modules, according to the first residual life corresponding to each single battery in the battery module, the second life difference degree between the plurality of single batteries is determined; In response to the second life difference degree corresponding to the second battery module being greater than the second set threshold, the plurality of battery modules are controlled to charge and discharge.

8. The method of claim 7, wherein, The method further comprises: determining the actual service life corresponding to the battery pack; According to the actual service life, the first set threshold and / or the second set threshold are adjusted.

9. The method according to any one of claims 1-8, characterized in that, According to the life influence parameters corresponding to the plurality of single batteries, the first residual life of the plurality of single batteries and the second residual life corresponding to the plurality of battery modules are predicted, comprising: According to the life influence parameters corresponding to the plurality of single batteries, the initial life attenuation model corresponding to the single battery is corrected to obtain the corrected life attenuation model corresponding to the plurality of single batteries; According to the corrected life attenuation model corresponding to the plurality of single batteries, the first residual life corresponding to each single battery is predicted; According to the first residual life corresponding to each single battery, the second residual life corresponding to the battery module is determined.

10. The method of claim 9, wherein, According to the life influence parameters corresponding to the plurality of single batteries, the initial life attenuation model corresponding to the single battery is corrected to obtain the corrected life attenuation model corresponding to the plurality of single batteries, comprising: According to the life influence parameters corresponding to the plurality of single batteries in a single battery cycle, the first aging feature corresponding to the plurality of single batteries is determined; According to the life influence parameters corresponding to the plurality of single batteries in a plurality of battery cycles, the second aging feature corresponding to the plurality of single batteries is determined, and the second aging feature is a time sequence feature; According to the first aging feature and the second aging feature, the initial life attenuation model is corrected to obtain the corrected life attenuation model corresponding to the plurality of single batteries.

11. The method of claim 10, wherein, According to the life influence parameters corresponding to the plurality of single batteries in a single battery cycle, the first aging feature corresponding to the plurality of single batteries is determined, comprising: determining a set of weight parameters corresponding to the plurality of single batteries; According to the life influence parameters corresponding to the plurality of single batteries in the single battery cycle and the set of weight parameters, the first aging feature corresponding to the plurality of single batteries is determined.

12. The method of claim 11, wherein, determining a set of weight parameters corresponding to the plurality of single batteries, comprising: determining the working condition parameters corresponding to the plurality of single batteries, the working condition parameters comprising at least one of battery temperature and charging and discharging rate; The method further comprises:

13. The method of claim 11, wherein, The method further comprises: The method further comprises: The life influence parameter of the single battery comprises at least one of a state of charge parameter, an internal resistance parameter, and a temperature parameter.

14. The method of any one of claims 1-8, wherein, The state of charge parameter is determined according to a variation amount of the state of charge of the single battery in a single battery cycle; the internal resistance parameter comprises an internal resistance increment ratio of the single battery, and the internal resistance increment ratio is determined according to increments of ohmic internal resistance and polarization internal resistance of the single battery in a single battery cycle; the temperature parameter comprises a first temperature parameter and / or a second temperature parameter, the first temperature parameter is determined according to a difference degree between a surface temperature of the single battery and surface temperatures of other single batteries in the battery module, and the second temperature parameter is determined according to a difference between the surface temperature of the single battery and an ambient temperature. The battery pack comprises a plurality of battery modules connected in parallel, and the device comprises:

15. A battery pack control device characterized by comprising: The device comprises: The device comprises: The control module is configured to: The control module is configured to:

16. The apparatus of claim 15, wherein, The control module is configured to: The control module is configured to: The control module is configured to:

17. The apparatus of claim 16, wherein, The control module is configured to: The control module is configured to: The control module is configured to: The control module is configured to:

18. 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19. A vehicle characterized by comprising: Comprise: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to perform the battery pack control method of any one of claims 1-14.

20. A computer readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the battery pack control method of any one of claims 1-14.

21. A computer program product, characterised in that, The computer program is executed by the processor to implement the battery pack control method of any one of claims 1-14.

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