Power battery thermal management control method and device, electronic equipment, medium and product

Abstract

The application discloses a power battery thermal management control method and device, electronic equipment, medium and product. The method comprises the following steps: acquiring the minimum single battery voltage value, real-time dynamic current, power battery minimum temperature, current power estimation value and current polarization voltage of the power battery; calculating the least square estimation battery power value according to the minimum single battery voltage value and the real-time dynamic current; calculating the current power estimation difference value according to the current power estimation value and the least square estimation battery power value; calculating the polarization state change rate according to the current polarization voltage and the pre-stored polarization voltage saturation value; if it is determined that the current power battery has heating demand according to the polarization state change rate, the power battery minimum temperature and the current power estimation difference value, the power battery is controlled to be heated. The method can solve the problems of heavy calibration work, poor adaptability, slow heating response in low-temperature and low-power working conditions and influence on vehicle power performance caused by the dependence on fixed temperature threshold.

Description

Technical Field

[0001] This application relates to the field of battery management technology, specifically to a power battery thermal management control method, device, electronic device, readable storage medium, and computer program product. Background Technology

[0002] To ensure battery safety and prevent thermal runaway, the power batteries of electric vehicles must operate within a certain temperature range during charging and discharging, while avoiding accelerated battery aging due to high temperatures. Therefore, one of the key functions of a battery management system (BMS) is to control battery temperature, promptly initiating cooling to lower the battery temperature when it exceeds a set threshold. Currently, existing technologies typically employ a control strategy based on fixed temperature thresholds. This involves real-time acquisition of the battery's lowest temperature and comparison with preset on and off thresholds to determine whether to activate or deactivate heating, ensuring the battery operates within a suitable temperature range. However, this method relies solely on temperature, failing to accurately reflect the actual heating requirements of the battery under different configurations and operating conditions. This necessitates numerous repeated calibration tests for different battery systems, resulting in low adaptation efficiency. Furthermore, it is prone to heating response lag under low temperature and low charge conditions, impacting overall vehicle performance and user experience. Summary of the Invention

[0003] In view of the above problems, this application provides a power battery thermal management control method, device, electronic device, readable storage medium and computer program product, which can solve the problems of heavy calibration work, poor adaptability and untimely heating response under low temperature and low power conditions, which affect the power performance of the whole vehicle, caused by relying solely on a fixed temperature threshold.

[0004] In a first aspect, this application provides a power battery thermal management control method, including: Obtain the minimum single-cell voltage value, real-time dynamic current, minimum temperature of the power battery, current estimated power capacity, and current polarization voltage of the power battery; Based on the minimum single-cell voltage value and the real-time dynamic current, calculate the least squares estimated battery capacity value; Calculate the difference between the current battery power estimate and the least squares estimated battery power. Calculate the rate of change of polarization state based on the current polarization voltage and the pre-stored polarization voltage saturation value; When it is determined that the power battery has a heating requirement based on the polarization state change rate, the minimum temperature of the power battery, and the difference between the current power capacity estimate, the power battery is heated and controlled.

[0005] In the above technical solution, this method can comprehensively capture core state information such as battery voltage, current, temperature, charge, and polarization voltage, laying a data foundation for accurately judging heating needs; it can also improve the accuracy of charge estimation by combining quantitative analysis of voltage and dynamic current, avoiding judgment errors caused by single parameter estimation deviations; it can also intuitively reflect the deviation between the actual charge state of the battery and the estimated value by comparing the results of dual charge estimations, providing a quantitative basis for judging heating needs; it can also accurately capture the dynamic changes of battery polarization degree based on the ratio analysis of polarization voltage and saturation value, accurately identifying potential heating needs under low temperature and low charge conditions; and it can comprehensively judge polarization state, minimum temperature, and charge difference in multiple dimensions, avoiding the adaptation limitations of fixed thresholds, achieving timely response under low temperature and low charge conditions, and ensuring the vehicle's power performance and user experience.

[0006] In some embodiments, the method further includes: When the rate of change of polarization state is greater than the first polarization state threshold, the lowest temperature of the power battery is less than the preset requested heating temperature threshold, and the current power estimation difference is less than the preset power difference threshold, it is determined that the current power battery has a heating requirement, and the step of heating control of the power battery is executed.

[0007] In the above technical solution, the method can accurately define the triggering scenario of heating demand by clarifying the quantitative judgment conditions of multiple parameters, avoid false triggering or missed triggering, thereby ensuring the timeliness of heating response under critical working conditions such as low temperature and low power, and preventing energy waste caused by unnecessary heating.

[0008] In some embodiments, after the heating control of the power battery, the method further includes: The second polarization state threshold is determined based on the preset polarization state threshold hysteresis parameter and the first polarization state threshold. When the rate of change of polarization state is less than the second polarization state threshold, the lowest temperature of the power battery is greater than the preset exit heating temperature threshold, and the current power estimation difference is less than the preset power difference threshold, the heating control of the power battery is stopped.

[0009] In the above technical solution, the method can avoid frequent start-stop of heating control due to small parameter fluctuations near the threshold by setting polarization state threshold hysteresis and multi-parameter coordinated stop heating judgment conditions, thereby reducing energy consumption and component wear caused by frequent switching.

[0010] In some implementations, calculating the least-squares estimated battery capacity based on the minimum single-cell voltage value and the real-time dynamic current includes: Calculate the estimated value of the first no-load voltage variable based on the minimum single-unit voltage value and the real-time dynamic current; The first no-load voltage variable estimate is subjected to a sliding filter to obtain the second no-load voltage variable estimate; Based on the preset mapping table of static voltage value and battery capacity value and the estimated value of the second no-load voltage variable, the least squares estimated battery capacity value is determined.

[0011] In the above technical solution, the method can suppress data fluctuation interference through sliding filtering, and at the same time improve the stability and accuracy of least squares estimation of power value by combining voltage and current collaborative calculation with preset mapping table matching.

[0012] In some implementations, calculating the rate of change of polarization state based on the current polarization voltage and a pre-stored polarization voltage saturation value includes: Estimate the current polarization voltage value based on the current polarization voltage, the preset polarization time constant, and the previously estimated historical polarization voltage; The rate of change of polarization state is calculated based on the polarization voltage value and the pre-stored polarization voltage saturation value. The polarization voltage saturation value is obtained by conducting cell testing on the power battery in advance.

[0013] In the above technical solution, this method can improve the accuracy and adaptability of polarization state assessment, and provide a quantitative basis that fits the actual characteristics of the battery for judging heating requirements.

[0014] Secondly, this application provides a power battery thermal management control device, comprising: The acquisition unit is used to acquire the minimum single cell voltage value, real-time dynamic current, minimum temperature of the power battery, current estimated power capacity, and current polarization voltage of the power battery. The first calculation unit is used to calculate the least squares estimated battery capacity value based on the minimum single-cell voltage value and the real-time dynamic current. The second calculation unit is used to calculate the current power estimation difference based on the current power estimation value and the least squares estimated battery power value. The third calculation unit is used to calculate the polarization state change rate based on the current polarization voltage and the pre-stored polarization voltage saturation value. The first control unit is used to control the heating of the power battery when it is determined that the power battery has a heating requirement based on the polarization state change rate, the minimum temperature of the power battery and the difference between the current power estimate and the current power level.

[0015] In the above technical solution, the device can comprehensively capture core state information such as battery voltage, current, temperature, charge, and polarization voltage, laying a data foundation for accurately judging heating needs; it can also improve the accuracy of charge estimation by combining quantitative analysis of voltage and dynamic current, avoiding judgment errors caused by the estimation deviation of a single parameter; it can also intuitively reflect the deviation between the actual charge state of the battery and the estimated value by comparing the results of dual charge estimation, providing a quantitative basis for judging heating needs; it can also accurately capture the dynamic changes of battery polarization degree based on the ratio analysis of polarization voltage and saturation value, accurately identifying potential heating needs under low temperature and low charge conditions; and it can comprehensively judge polarization state, minimum temperature, and charge difference in multiple dimensions, avoiding the adaptation limitations of fixed thresholds, achieving timely response under low temperature and low charge conditions, and ensuring the vehicle's power performance and user experience.

[0016] Thirdly, this application provides an electronic device, the electronic device including a memory and a processor, the memory for storing a computer program, the processor running the computer program to cause the electronic device to perform the power battery thermal management control method as described in any one of the first aspects.

[0017] Fourthly, this application provides a readable storage medium storing a computer program, which, when executed by a processor, performs the power battery thermal management control method described in any one of the first aspects.

[0018] Fifthly, this application provides a computer program product, which includes a computer program that, when executed by a processor, performs the power battery thermal management control method described in any one of the first aspects.

[0019] The beneficial effects of this application are: it enables dynamic identification of heating needs during the dynamic driving process of EV vehicles by monitoring the voltage, real-time current, and real-time temperature of individual power battery cells. It also ensures compatibility with different power battery configurations. Furthermore, it avoids problems such as poor power performance and accelerated battery degradation caused by inadequate thermal management control throughout the entire life cycle. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart illustrating the power battery thermal management control method in some embodiments of this application; Figure 2 This is a flowchart illustrating the power battery thermal management control method in some embodiments of this application; Figure 3 This is a logic flowchart of the power battery thermal management control in some embodiments of this application; Figure 4 This is a schematic diagram of the structure of the power battery thermal management control device in some embodiments of this application; Figure 5 This is a schematic diagram of the structure of an electronic device in some embodiments of this application. Detailed Implementation

[0022] The embodiments of the technical solution of this application will now be described in detail with reference to the accompanying drawings. These embodiments are only used to more clearly illustrate the technical solution of this application and are therefore merely examples, and should not be used to limit the scope of protection of this application.

[0023] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0024] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more (including two), similarly, "multiple sets" refers to two or more sets (including two sets), and "multiple pieces" refers to two or more pieces (including two pieces) unless otherwise explicitly defined.

[0025] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0026] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0027] Existing thermal management control methods typically use fixed temperature thresholds for thermal management control. However, this method is usually incompatible with different power battery configurations and requires repeated calibration and matching. At the same time, this method can only judge heating needs based on a single dimension of temperature, making it difficult to fully represent the actual needs of the battery. In addition, it does not consider the thermal management adaptation issues throughout the entire life cycle of the power battery, resulting in poor power performance at low temperatures and low battery levels, accelerated battery degradation rate, and may even affect the driving safety of the entire vehicle.

[0028] To address the aforementioned technical issues, this application provides a power battery thermal management control method. This method estimates the polarization state of the power battery by introducing the least squares method and dynamically determines the heating on / off thresholds by combining the cumulative polarization state change rate, temperature, and SOC from multiple dimensions. This enables the method to be compatible with different power battery configurations, improve calibration efficiency, and make thermal management control more reasonable and accurate, thus making it applicable to thermal management control throughout the entire life cycle of the power battery.

[0029] like Figure 1 As shown, some embodiments of this application provide a power battery thermal management control method, which includes: S101. Obtain the minimum single-cell voltage value, real-time dynamic current, minimum temperature of the power battery, current estimated power capacity, and current polarization voltage of the power battery. S102. Calculate the least squares estimated battery capacity based on the minimum single-cell voltage and real-time dynamic current. S103. Calculate the difference between the current power estimate and the least squares estimated battery power. S104. Calculate the rate of change of polarization state based on the current polarization voltage and the pre-stored polarization voltage saturation value. S105. When it is determined that the power battery has a heating requirement based on the difference between the polarization state change rate, the minimum temperature of the power battery and the current power capacity, the power battery is heated.

[0030] In some embodiments, the minimum single-cell voltage value refers to the voltage measurement value corresponding to the cell with the lowest voltage among all the single-cell cells of the power battery.

[0031] In some embodiments, real-time dynamic current refers to the instantaneous current value collected in real time during the charging and discharging process of the power battery as the operating conditions change.

[0032] In some embodiments, the lowest temperature of the power battery refers to the lowest value among all temperature data collected by the temperature sensor under the current operating conditions of the power battery pack.

[0033] In some embodiments, the current charge estimate refers to the current remaining charge (SOC) value of the power battery estimated in real time using existing algorithms of the battery management system (BMS).

[0034] In some embodiments, the current polarization voltage refers to the instantaneous voltage difference generated by electrochemical polarization, concentration polarization, etc. during the charging and discharging process of the power battery.

[0035] In some embodiments, the least squares estimated battery capacity value refers to the estimated power battery capacity value obtained by fitting the minimum single cell voltage value and the real-time dynamic current based on the least squares method principle.

[0036] In some embodiments, the current battery capacity estimate difference refers to the numerical difference between the current battery capacity estimate and the least squares estimated battery capacity value.

[0037] In some embodiments, the polarization voltage saturation value refers to the maximum limit value that the polarization voltage of this type of power battery can reach, determined by pre-testing the battery cells.

[0038] In some embodiments, the polarization state change rate refers to the ratio of the current polarization voltage to the pre-stored polarization voltage saturation value, which is used as a quantitative indicator to characterize the current polarization degree of the power battery.

[0039] In some embodiments, heating requirement refers to the heating operation requirement of the power battery to maintain a suitable working state, based on a comprehensive judgment of the polarization state change rate, the minimum temperature of the power battery, and the difference between the current power capacity estimate.

[0040] In the above embodiments, this method can comprehensively capture core state information such as battery voltage, current, temperature, charge, and polarization voltage, laying a data foundation for accurately judging heating needs; it can also improve the accuracy of charge estimation by combining quantitative analysis of voltage and dynamic current, avoiding judgment errors caused by single parameter estimation deviations; it can also intuitively reflect the deviation between the actual charge state of the battery and the estimated value by comparing the results of dual charge estimations, providing a quantitative basis for judging heating needs; it can also accurately capture the dynamic changes in the degree of battery polarization based on the ratio analysis of polarization voltage and saturation value, accurately identifying potential heating needs under low temperature and low charge conditions; and it can comprehensively judge polarization state, minimum temperature, and charge difference in multiple dimensions, avoiding the adaptation limitations of fixed thresholds, achieving timely response under low temperature and low charge conditions, and ensuring the vehicle's power performance and user experience.

[0041] In some embodiments, the method further includes: When the rate of change of polarization state is greater than the first polarization state threshold, the lowest temperature of the power battery is less than the preset requested heating temperature threshold, and the current power estimation difference is less than the preset power difference threshold, it is determined that the current power battery has a heating requirement, and the step of heating control of the power battery is executed.

[0042] For example, this method can be used when the rate of change of polarization state β > K and the minimum battery temperature T < T1, |Soc0-SOC Vse When | < δ, it is assumed that the current power battery has a heating requirement, and a heating request is issued. Among these, δ is the SOC difference threshold (preset power difference threshold), used to ensure accurate SOC estimation. Vse The accuracy of the polarization voltage Vpol value can be determined by |Soc0-SOC Vse |<δ is used as a judgment condition for constraint; SOC0 is the current estimated SOC value; SOC Vse Estimate the SOC value using least squares; K is the polarization state threshold (first polarization state threshold). T1 is the threshold temperature for the requested heating.

[0043] In the above embodiments, the method can accurately define the triggering scenarios of heating demand by clarifying the quantitative judgment conditions of multiple parameters, avoid false triggering or missed triggering, thereby ensuring the timeliness of heating response under critical operating conditions such as low temperature and low power, and preventing energy waste caused by unnecessary heating.

[0044] In some embodiments, after heating the power battery, the method further includes: The second polarization state threshold is determined based on the preset polarization state threshold hysteresis parameter and the first polarization state threshold. When the rate of change of polarization state is less than the second polarization state threshold, the lowest temperature of the power battery is greater than the preset exit heating temperature threshold, and the current estimated charge difference is less than the preset charge difference threshold, the heating control of the power battery is stopped.

[0045] For example, when the rate of change of polarization state β < Ky, and the minimum battery temperature T > T2, |Soc0 - SOC Vse When | < δ, it is assumed that the current power battery has no heating requirement, and heating is then discontinued. Among these, δ is the SOC difference threshold; SOC0 is the current estimated SOC value; SOC Vse Estimate the SOC value using least squares; K is the polarization state threshold (first polarization state threshold). y is the polarization state threshold hysteresis parameter; T2 is the threshold temperature for exiting heating; The second polarization state threshold is Ky (determined based on the preset polarization state threshold hysteresis parameter y and the first polarization state threshold K).

[0046] In the above embodiments, the method can avoid frequent start-stop of heating control due to small parameter fluctuations near the threshold by setting polarization state threshold hysteresis and multi-parameter coordinated stop heating judgment conditions, thereby reducing energy consumption and component wear caused by frequent switching.

[0047] In some embodiments, the least-squares estimated battery capacity is calculated based on the minimum single-cell voltage value and the real-time dynamic current, including: Calculate the estimated value of the first no-load voltage variable based on the minimum unit voltage value and the real-time dynamic current; The first no-load voltage variable estimate is subjected to a sliding filter to obtain the second no-load voltage variable estimate; Based on the preset mapping table of static voltage value and battery capacity value and the estimated value of the second no-load voltage variable, the least squares estimated battery capacity value is determined.

[0048] For example, based on the above sampled values ​​(minimum single-cell voltage value U) cell Actual dynamic current I Act Introducing the least squares algorithm to calculate the no-load voltage variable V se (Estimated value of the first no-load voltage variable) The calculation formula is as follows: ; Where I is I Act , i.e., real-time dynamic current; U is U cell That is, the minimum single-unit voltage value; 60 is a fixed coefficient in the formula.

[0049] In some embodiments, the method can be applied to the estimated V se A sliding filter is performed to obtain the second no-load voltage variable estimate; then, the OCV is looked up in reverse. Map (Based on a pre-defined mapping table of static voltage and electrical charge values) the least squares estimate of the state of charge (SOC) is obtained. Vse (Least squares estimation of battery capacity).

[0050] In the above embodiments, the method can suppress data fluctuation interference through sliding filtering, and at the same time improve the stability and accuracy of least squares estimation of power values ​​by combining voltage and current collaborative calculation with preset mapping table matching.

[0051] In some embodiments, the polarization state change rate is calculated based on the current polarization voltage and a pre-stored polarization voltage saturation value, including: Estimate the current polarization voltage value based on the current polarization voltage, the preset polarization time constant, and the previously estimated historical polarization voltage; Calculate the rate of change of polarization state based on the polarization voltage value and the pre-stored polarization voltage saturation value; The polarization voltage saturation value is obtained by conducting pre-testing of the power battery cells.

[0052] For example, the formula for estimating the polarization voltage value is as follows: ; Wherein, Vpol(K) is the latest polarization voltage (the current polarization voltage value). Vpol(K-1) is the polarization voltage calculated last time (the historical polarization voltage estimated last time). RC is the polarization time constant of the battery (the preset polarization time constant).

[0053] For example, this method can calculate the rate of change of polarization state based on the polarization voltage value Vpol and the polarization voltage saturation value Vp, where the polarization voltage saturation value Vp can be obtained from cell test data (the power battery has been tested in advance).

[0054] The formula for calculating the rate of change of polarization state β is: β = d(P) / d(t); Where P=Vpol / Vp represents the polarization saturation, and β is the rate of change of polarization state, representing the current trend of the battery polarization state.

[0055] In the above embodiments, this method can improve the accuracy and adaptability of polarization state assessment, and provide a quantitative basis that fits the actual characteristics of the battery for judging heating requirements.

[0056] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions in this application will be clearly and completely described below. In some embodiments, such as Figure 2 As shown, the power battery thermal management control method includes: S201. Obtain the minimum single-cell voltage value, real-time dynamic current, minimum temperature of the power battery, current estimated power capacity, and current polarization voltage of the power battery. S202. Calculate the estimated value of the first no-load voltage variable based on the minimum unit voltage value and the real-time dynamic current. S203. Perform sliding filtering on the first no-load voltage variable estimate to obtain the second no-load voltage variable estimate. S204. Determine the least squares estimated battery capacity value based on the preset static voltage value to capacity value mapping table and the second no-load voltage variable estimation value. S205. Calculate the difference between the current power estimate and the least squares estimated battery power. S206. Estimate the current polarization voltage value based on the current polarization voltage, the preset polarization time constant, and the previously estimated historical polarization voltage. S207. Calculate the rate of change of polarization state based on the polarization voltage value and the pre-stored polarization voltage saturation value. S208. When the rate of change of polarization state is greater than the first polarization state threshold, the lowest temperature of the power battery is less than the preset requested heating temperature threshold, and the current power estimation difference is less than the preset power difference threshold, it is determined that the current power battery has a heating requirement. S209. Heating control of the power battery; S210. Determine the second polarization state threshold based on the preset polarization state threshold hysteresis parameter and the first polarization state threshold. S211. When the polarization state change rate is detected to be less than the second polarization state threshold, the minimum temperature of the power battery is detected to be greater than the preset exit heating temperature threshold, and the current power estimation difference is detected to be less than the preset power difference threshold, the heating control of the power battery shall be stopped.

[0057] For example, Figure 3 A logic flowchart for thermal management control of a power battery is shown. This logic flowchart can be divided into four logic layers: (1) Input layer It receives core parameters of the power battery, such as the minimum single cell voltage (Ucell), real-time dynamic current (Iact), current power estimate (Soc0), and minimum temperature (T). (2) Data processing layer By calculating voltage / current, combined with no-load voltage variable estimation, moving average filtering, and SOC mapping table (SOCMAP), the least squares estimated energy value (Soc Vse) is obtained. The rate of change of polarization state (β) is calculated by estimating the polarization voltage and the polarization voltage saturation value (Vp). (3) Judgment layer Based on the polarization state change rate (β), temperature (T), and charge difference (Soc0-Soc Vse), the conditional judgments for "request heating" and "exit heating" are executed. (4) Output layer Finally, a heating request signal (THeatReq) is output to realize the thermal management control of the power battery.

[0058] Figure 4 A schematic diagram of a power battery thermal management control device is shown. It should be understood that this device is related to... Figure 1 The method executed in the middle corresponds to the steps involved in the aforementioned method. The specific functions and effects of the device can be found in the description above. To avoid repetition, detailed descriptions are omitted here.

[0059] The power battery thermal management control device includes: The acquisition unit 310 is used to acquire the minimum single cell voltage value, real-time dynamic current, minimum temperature of the power battery, current estimated power capacity, and current polarization voltage of the power battery. The first calculation unit 320 is used to calculate the least squares estimated battery capacity value based on the minimum single cell voltage value and the real-time dynamic current. The second calculation unit 330 is used to calculate the difference between the current power estimate and the least squares estimated battery power. The third calculation unit 340 is used to calculate the rate of change of polarization state based on the current polarization voltage and the pre-stored polarization voltage saturation value. The first control unit 350 is used to control the heating of the power battery when it is determined that the power battery has a heating requirement based on the difference between the polarization state change rate, the minimum temperature of the power battery and the current power estimate.

[0060] In some embodiments, the power battery thermal management control device further includes: The determining unit 360 is used to determine that the current power battery has a heating requirement when the polarization state change rate is greater than the first polarization state threshold, the lowest temperature of the power battery is less than the preset requested heating temperature threshold, and the current power estimation difference is less than the preset power difference threshold, and triggers the first control unit 350 to perform heating control on the power battery.

[0061] In some embodiments, the power battery thermal management control device includes: The determining unit 360 is also used to determine the second polarization state threshold based on the preset polarization state threshold hysteresis parameter and the first polarization state threshold after the first control unit 350 performs heating control on the power battery. The second control unit 370 is used to stop heating control of the power battery when it detects that the rate of change of polarization state is less than the second polarization state threshold, the minimum temperature of the power battery is greater than the preset exit heating temperature threshold, and the current power estimation difference is less than the preset power difference threshold.

[0062] In some embodiments, the first computing unit 320 includes: The first calculation subunit 321 is used to calculate the estimated value of the first no-load voltage variable based on the minimum single-unit voltage value and the real-time dynamic current. The filtering subunit 322 is used to perform sliding filtering on the first no-load voltage variable estimate to obtain the second no-load voltage variable estimate. Subunit 323 is used to determine the least squares estimated battery capacity value based on a preset mapping table of static voltage value and capacity value and the estimated value of the second no-load voltage variable.

[0063] In some embodiments, the third computing unit 340 includes: The estimation subunit 341 is used to estimate the current polarization voltage value based on the current polarization voltage, the preset polarization time constant, and the historical polarization voltage estimated in the last time. The second calculation subunit 342 is used to calculate the rate of change of polarization state based on the polarization voltage value and the pre-stored polarization voltage saturation value. The polarization voltage saturation value is obtained by conducting pre-testing of the power battery cells.

[0064] like Figure 5 As shown, this application provides an electronic device 400, which includes a processor 401 and a memory 402. The processor 401 and the memory 402 are interconnected and communicate with each other through a communication bus 403 and / or other forms of connection mechanism (not shown). The memory 402 stores a computer program that can be executed by the processor 401. When the computing device is running, the processor 401 executes the computer program to perform the method in any of the aforementioned optional implementations.

[0065] This application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the method in any of the aforementioned optional implementations.

[0066] The computer-readable storage medium 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 Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0067] This application provides a computer program product, which includes a computer program that, when run by a processor, executes the method in any of the aforementioned optional implementations.

[0068] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and not to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. These modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application, and they should all be covered within the scope of the claims and specification of this application. In particular, as long as there is no conflict, the various technical features mentioned in the embodiments can be combined in any way. This application is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. A method for thermal management control of a power battery, characterized in that, include: Obtain the minimum single-cell voltage value, real-time dynamic current, minimum temperature of the power battery, current estimated power capacity, and current polarization voltage of the power battery; Based on the minimum single-cell voltage value and the real-time dynamic current, calculate the least squares estimated battery capacity value; Calculate the difference between the current battery power estimate and the least squares estimated battery power. Calculate the rate of change of polarization state based on the current polarization voltage and the pre-stored polarization voltage saturation value; When it is determined that the power battery has a heating requirement based on the polarization state change rate, the minimum temperature of the power battery, and the difference between the current power capacity estimate, the power battery is heated and controlled. The method further includes: When the rate of change of polarization state is greater than the first polarization state threshold, the lowest temperature of the power battery is less than the preset requested heating temperature threshold, and the current power estimation difference is less than the preset power difference threshold, it is determined that the current power battery has a heating requirement, and the step of heating control of the power battery is executed. The method further includes, after controlling the heating of the power battery: The second polarization state threshold is determined based on the preset polarization state threshold hysteresis parameter and the first polarization state threshold. When the rate of change of polarization state is less than the second polarization state threshold, the minimum temperature of the power battery is greater than the preset exit heating temperature threshold, and the current power estimation difference is less than the preset power difference threshold, the heating control of the power battery is stopped. The step of calculating the least-squares estimated battery capacity based on the minimum single-cell voltage value and the real-time dynamic current includes: Calculate the estimated value of the first no-load voltage variable based on the minimum single-unit voltage value and the real-time dynamic current; The first no-load voltage variable estimate is subjected to a sliding filter to obtain the second no-load voltage variable estimate; Based on the preset mapping table of static voltage value and energy value and the second no-load voltage variable estimation value, the least squares estimated battery energy value is determined; The step of calculating the polarization state change rate based on the current polarization voltage and the pre-stored polarization voltage saturation value includes: Estimate the current polarization voltage value based on the current polarization voltage, the preset polarization time constant, and the previously estimated historical polarization voltage; The rate of change of polarization state is calculated based on the polarization voltage value and the pre-stored polarization voltage saturation value. The polarization voltage saturation value is obtained by conducting cell testing on the power battery in advance.

2. A power battery thermal management control device, characterized in that, The power battery thermal management control device includes: The acquisition unit is used to acquire the minimum single cell voltage value, real-time dynamic current, minimum temperature of the power battery, current estimated power capacity, and current polarization voltage of the power battery. The first calculation unit is used to calculate the least squares estimated battery capacity value based on the minimum single-cell voltage value and the real-time dynamic current. The second calculation unit is used to calculate the current power estimation difference based on the current power estimation value and the least squares estimated battery power value. The third calculation unit is used to calculate the polarization state change rate based on the current polarization voltage and the pre-stored polarization voltage saturation value. The first control unit is used to control the heating of the power battery when it is determined that the power battery has a heating requirement based on the polarization state change rate, the minimum temperature of the power battery and the difference between the current power capacity estimate. The power battery thermal management control device further includes: The determining unit is used to determine that the current power battery has a heating requirement when the polarization state change rate is greater than the first polarization state threshold, the lowest temperature of the power battery is less than the preset requested heating temperature threshold, and the current power estimation difference is less than the preset power difference threshold. The determining unit is further configured to determine a second polarization state threshold based on a preset polarization state threshold hysteresis parameter and the first polarization state threshold after the heating control of the power battery is performed. The second control unit is used to stop heating control of the power battery when it detects that the rate of change of polarization state is less than the second polarization state threshold, the minimum temperature of the power battery is greater than the preset exit heating temperature threshold, and the current power estimation difference is less than the preset power difference threshold. The first computing unit includes: The first calculation subunit is used to calculate the first no-load voltage variable estimate based on the minimum single-unit voltage value and the real-time dynamic current. The filtering subunit is used to perform sliding filtering on the first no-load voltage variable estimate to obtain the second no-load voltage variable estimate. The sub-unit is determined to determine the least squares estimated battery capacity value based on a preset static voltage value to capacity value mapping table and the second no-load voltage variable estimation value. The third computing unit includes: The estimation subunit is used to estimate the current polarization voltage value based on the current polarization voltage, the preset polarization time constant, and the previously estimated historical polarization voltage. The second calculation subunit is used to calculate the polarization state change rate based on the polarization voltage value and the pre-stored polarization voltage saturation value; wherein the polarization voltage saturation value is obtained by pre-testing the power battery cells.

3. An electronic device, characterized in that, The electronic device includes a memory and a processor. The memory stores a computer program, and the processor runs the computer program to enable the electronic device to perform the power battery thermal management control method as described in claim 1.

4. A readable storage medium, characterized in that, The readable storage medium stores a computer program, which, when executed by a processor, performs the power battery thermal management control method as described in claim 1.

5. A computer program product, characterized in that, The computer program product includes a computer program, which, when executed by a processor, performs the power battery thermal management control method as described in claim 1.

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