WO2021258657A1 - 一种电池健康状态获取方法及装置、存储介质 - Google Patents

一种电池健康状态获取方法及装置、存储介质 Download PDF

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Publication number
WO2021258657A1
WO2021258657A1 PCT/CN2020/135129 CN2020135129W WO2021258657A1 WO 2021258657 A1 WO2021258657 A1 WO 2021258657A1 CN 2020135129 W CN2020135129 W CN 2020135129W WO 2021258657 A1 WO2021258657 A1 WO 2021258657A1
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capacity
battery
calculation condition
capacity change
change
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PCT/CN2020/135129
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English (en)
French (fr)
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尤适运
刘海洋
毛俊
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广州橙行智动汽车科技有限公司
广州小鹏汽车科技有限公司
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Priority to EP20919394.5A priority Critical patent/EP3951408A4/en
Publication of WO2021258657A1 publication Critical patent/WO2021258657A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/392—Determining battery ageing or deterioration, e.g. state of health
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/385—Arrangements for measuring battery or accumulator variables
    • G01R31/387—Determining ampere-hour charge capacity or SoC
    • G01R31/388—Determining ampere-hour charge capacity or SoC involving voltage measurements

Definitions

  • the present invention relates to the technical field of batteries, in particular to a method and device for acquiring battery health status, and a storage medium.
  • SOH State Of Health
  • SOC State of charge
  • allowable power directly affect the driving range and driving experience, so how to accurately estimate the SOH of the battery It is an important issue for pure electric vehicles.
  • the SOH estimation of existing lithium-ion power batteries for new energy vehicles generally uses the number of cycles of the battery to be measured, and the battery health status SOH is obtained by querying the correspondence table between the number of cycles measured in advance and the SOH.
  • the SOH of different batteries is actually different, so this method It cannot truly reflect the actual SOH of the battery, which leads to inaccurate estimation of SOC and driving range, which seriously affects the user's driving experience.
  • the embodiment of the present invention discloses a method and a device for acquiring a battery health state, and a storage medium, which can improve the calculation accuracy of the battery health state.
  • the first aspect of the embodiments of the present invention discloses a method for acquiring a battery health status, the method including:
  • the battery health status is calculated according to the capacity change and the capacity.
  • a device for acquiring a battery health status includes:
  • the capacity change calculation condition judgment module is used to judge whether the capacity change calculation condition is met when the vehicle is powered on;
  • the capacity change calculation module is used to calculate the capacity change
  • the capacity calculation condition judgment module is used to judge whether the capacity calculation condition is met when the vehicle is powered on;
  • Capacity calculation module used to calculate capacity
  • the health state calculation module is used to calculate the health state according to the capacity change and the capacity.
  • a third aspect of the embodiments of the present invention discloses a computer-readable storage medium that stores a computer program, where the computer program causes a computer to execute the method for acquiring a battery health state disclosed in the first aspect of the embodiments of the present invention.
  • the embodiments of the present invention have the following beneficial effects: there is no need to measure the corresponding relationship between the battery life cycle cycle number and the SOH, saving test resources and time; more truly reflecting the actual battery capacity aging degree, and improving the charge State and driving range estimation accuracy provide users with a good driving experience.
  • FIG. 1 is a schematic flowchart of an embodiment of a method for acquiring a battery health state disclosed in an embodiment of the present invention
  • FIG. 2 is a schematic flowchart of another embodiment of a method for acquiring a battery health state disclosed in an embodiment of the present invention
  • FIG. 3 is a schematic diagram of modules of an embodiment of a device for acquiring a battery health state disclosed in an embodiment of the present invention.
  • the embodiment of the present invention provides a method for acquiring the state of health of a battery, which is mainly based on the OCV-SOC (open circuit voltage-state of charge) curve of the battery, and finds two and OCV-SOC curves according to the OCV (open circuit voltage) during the use of the vehicle.
  • the corresponding SOC point accumulates the capacity change between the two points, and the capacity change is divided by the SOC difference between the two points, which is the current battery's actual capacity.
  • the ratio of the actual capacity of the current battery to the nominal capacity when the battery leaves the factory is converted into a percentage, which is SOH.
  • FIG. 1 it is a schematic flowchart of an embodiment of a method for acquiring battery health according to an embodiment of the present invention, including:
  • the capacity change calculation conditions include:
  • the parking time is the time between the last power-off to this power-on
  • S1 is the preset parking time threshold for the calculation condition of the capacity change.
  • S1 may be the time required for the depolarization terminal voltage of the battery to stabilize when the battery is in a static state;
  • Capacity change calculation condition B the current voltage of the battery with the smallest cell voltage corresponds to the SOC value of the OCV-SOC curve of the battery SOC1 ⁇ SOC_judge1;
  • the battery corresponding to the minimum cell voltage is the lowest voltage among all cells in the current battery; the SOC value corresponding to the current voltage can be obtained through the OCV-SOC curve of the battery, and this value is recorded as SOC1;
  • the SOC_judge1 is a preset capacity change calculation conditional state-of-charge threshold. Preferably, it can be set to the lowest SOC point of the plateau area of the OCV-SOC curve, and the plateau area of the OCV-SOC curve refers to the slope of the OCV-SOC curve Areas less than a certain value, such as less than 8mV per 1% SOC;
  • T1 is the time point when it is judged that the calculation condition of the capacity change is satisfied
  • RTC is the time for calculating ⁇ Cap or ⁇ DchaCap, which can be obtained from the internal timing of the BMS or from the outside;
  • I is the current of the battery
  • I d is the current in the battery discharge direction
  • ⁇ Cap is the amount of change in the cumulative capacity from T1 as the starting point in time
  • ⁇ DchaCap is the cumulative change in capacity in the discharge direction starting from T1;
  • the capacity calculation conditions include:
  • Capacity calculation condition A parking time ⁇ S2;
  • the parking time is the time between the last power-off to this power-on
  • S2 is a preset capacity calculation condition time threshold.
  • S2 may be the time required for the depolarization terminal voltage of the battery to stabilize in a static state;
  • Capacity calculation condition B the voltage value of the battery corresponding to the maximum cell voltage corresponds to the SOC value SOC2 ⁇ SOC_judge2 in the OCV-SOC curve;
  • the battery corresponding to the maximum cell voltage is the cell with the highest voltage among all the cells; the SOC value corresponding to the current voltage can be obtained through the OCV-SOC curve of the battery, and this value is recorded as SOC2;
  • the SOC_judge2 is the preset capacity calculation condition state-of-charge threshold. Preferably, it can be set to the highest SOC point of the plateau area of the OCV-SOC curve, and the plateau area of the OCV-SOC curve means that the slope of the OCV-SOC curve is less than a certain value. Value area, such as less than 8mV per 1% SOC;
  • CT is the time when the capacity calculation conditions are judged
  • T1 is the time point when it is judged that the calculation condition of the capacity change is satisfied
  • T_Judge is the preset time difference threshold, which represents the maximum allowable value of the time difference between SOC1 and SOC2. This value is usually not too large, because if it is too large, the battery's long-term self-discharge will not be accumulated in ⁇ Cap, thus making the final result The accuracy is reduced.
  • this threshold may be set to 5 days, for example;
  • ⁇ DchaCap is the cumulative change in capacity in the discharge direction starting from T1;
  • ⁇ DchaCap_Judge is the preset capacity change threshold, which represents the maximum allowable discharge between SOC1 and SOC2, and prevents excessive discharge conditions.
  • the current sampling error is large and the inaccuracy of ⁇ Cap leads to a decrease in the accuracy of the result.
  • This threshold can be set to 0.5*Cap_rate, for example, where Cap_rate is the nominal capacity;
  • Cap_cal is the actual capacity of the battery
  • ⁇ Cap is the amount of change in the cumulative capacity from T1 as the starting point in time
  • SOH_C is the state of health (SOH) of the battery
  • Cap_rate is the nominal capacity of the battery when it leaves the factory.
  • FIG. 2 it is a schematic flowchart of another embodiment of a method for acquiring battery health according to an embodiment of the present invention, including:
  • the capacity change calculation process usually has a certain time limit. For example, in some embodiments of the present invention, it can be limited to not more than 5 days from the time when the capacity change calculation condition is met;
  • the capacity change calculation conditions include:
  • the parking time is the time between the last power-off to this power-on
  • S1 is the preset parking time threshold for the calculation condition of the capacity change.
  • S1 may be the time required for the depolarization terminal voltage of the battery to stabilize in a static state;
  • Capacity change calculation condition B the current voltage of the battery with the smallest cell voltage corresponds to the SOC value of the OCV-SOC curve of the battery SOC1 ⁇ SOC_judge1;
  • the battery corresponding to the minimum cell voltage is the lowest voltage among all cells in the current battery; the SOC value corresponding to the current voltage can be obtained through the OCV-SOC curve of the battery, and this value is recorded as SOC1;
  • the SOC_judge1 is a preset capacity change calculation conditional state-of-charge threshold, preferably, it can be set to the lowest point of the SOC of the plateau area of the OCV-SOC curve, and the plateau area of the OCV-SOC curve refers to the slope of the OCV-SOC curve Areas less than a certain value, such as less than 8mV per 1% SOC;
  • T1 is the time point when it is judged that the calculation condition of the capacity change is satisfied
  • RTC is the time for calculating ⁇ Cap or ⁇ DchaCap, which can be obtained from the internal timing of the BMS or obtained from outside;
  • I is the current of the battery
  • I d is the current in the battery discharge direction
  • ⁇ Cap is the amount of change in the cumulative capacity from T1 as the starting point in time
  • ⁇ DchaCap is the cumulative change in capacity in the discharge direction starting from T1;
  • the capacity calculation conditions include:
  • Capacity calculation condition A parking time ⁇ S2;
  • the parking time is the time between the last power-off to this power-on
  • S2 is a preset capacity calculation condition time threshold.
  • S2 may be the time required for the depolarization terminal voltage of the battery to stabilize in a static state;
  • Capacity calculation condition B the voltage value of the battery corresponding to the maximum cell voltage corresponds to the SOC value SOC2 ⁇ SOC_judge2 in the OCV-SOC curve;
  • the battery corresponding to the maximum cell voltage is the cell with the highest voltage among all cells; the OCV-SOC curve of the battery can obtain the SOC value corresponding to the current voltage, and this value is recorded as SOC2;
  • the SOC_judge2 is the preset capacity calculation condition state-of-charge threshold. Preferably, it can be set to the highest SOC point of the plateau area of the OCV-SOC curve, and the plateau area of the OCV-SOC curve means that the slope of the OCV-SOC curve is less than a certain value. Value area, such as less than 8mV per 1% SOC;
  • CT is the time when the capacity calculation conditions are judged
  • T1 is the time point when it is judged that the calculation condition of the capacity change is satisfied
  • T_Judge is the preset time difference threshold, which represents the maximum allowable value of the time difference between SOC1 and SOC2. This value is usually not too large, because if it is too large, the battery's long-term self-discharge will not be accumulated in ⁇ Cap, thus making the final result The accuracy is reduced.
  • this threshold may be set to 5 days, for example;
  • ⁇ DchaCap is the cumulative change in capacity in the discharge direction starting from T1;
  • ⁇ DchaCap_Judge is the preset capacity change threshold, which represents the maximum allowable discharge between SOC1 and SOC2, and prevents excessive discharge conditions.
  • the current sampling error is large and the inaccuracy of ⁇ Cap leads to a decrease in the accuracy of the result.
  • This threshold can be set to 0.5*Cap_rate, for example, where Cap_rate is the nominal capacity;
  • ⁇ Cap is the amount of change in the cumulative capacity from T1 as the starting point in time
  • SOC2 is the SOC value of the battery voltage value corresponding to the maximum cell voltage obtained when judging whether the capacity calculation condition is met in the OCV-SOC curve;
  • SOC1 is the SOC value of the battery's OCV-SOC curve corresponding to the current voltage of the minimum cell voltage when judging whether the capacity change calculation condition is met;
  • SOH_C is the state of health (SOH) of the battery
  • Cap_rate is the nominal capacity of the battery when it leaves the factory.
  • the embodiment of the present invention also provides a battery health status acquisition device.
  • FIG. 3 it is a schematic diagram of modules of the battery health status acquisition device proposed by the present invention, including:
  • the capacity change calculation condition judgment module 301 is used for judging whether the capacity change calculation condition is met when the vehicle is powered on;
  • the capacity change calculation conditions include:
  • the parking time is the time between the last power-off to this power-on
  • S1 is the preset parking time threshold for the calculation condition of the capacity change.
  • S1 may be the time required for the depolarization terminal voltage of the battery to stabilize when the battery is in a static state;
  • Capacity change calculation condition B the current voltage of the battery with the minimum cell voltage corresponds to the SOC value of the OCV-SOC curve of the battery SOC1 ⁇ SOC_judge1;
  • the battery corresponding to the minimum cell voltage is the lowest voltage among all cells in the current battery; the SOC value corresponding to the current voltage can be obtained through the OCV-SOC curve of the battery, and this value is recorded as SOC1;
  • the SOC_judge1 is a preset capacity change calculation conditional state-of-charge threshold, preferably, it can be set to the lowest point of the SOC of the plateau area of the OCV-SOC curve, and the plateau area of the OCV-SOC curve refers to the slope of the OCV-SOC curve Areas less than a certain value, such as less than 8mV per 1% SOC;
  • the capacity change calculation module 302 is used to calculate the capacity change
  • T1 is the time point when it is judged that the calculation condition of the capacity change is satisfied
  • RTC is the time for calculating ⁇ Cap or ⁇ DchaCap, which can be obtained from the internal timing of the BMS or from the outside;
  • I is the current of the battery
  • I d is the current in the battery discharge direction
  • ⁇ Cap is the amount of change in the cumulative capacity from T1 as the starting point in time
  • ⁇ DchaCap is the cumulative change in capacity in the discharge direction starting from T1;
  • the capacity calculation condition judging module 303 is used for judging whether the capacity calculation condition is met when the vehicle is powered on;
  • the capacity calculation conditions include:
  • Capacity calculation condition A parking time ⁇ S2;
  • the parking time is the time between the last power-off to this power-on
  • S2 is a preset capacity calculation condition time threshold.
  • S2 may be the time required for the depolarization terminal voltage of the battery to stabilize in a static state;
  • Capacity calculation condition B the voltage value of the battery corresponding to the maximum cell voltage corresponds to the SOC value SOC2 ⁇ SOC_judge2 in the OCV-SOC curve;
  • the battery corresponding to the maximum cell voltage is the cell with the highest voltage among all the cells; the SOC value corresponding to the current voltage can be obtained through the OCV-SOC curve of the battery, and this value is recorded as SOC2;
  • the SOC_judge2 is the preset capacity calculation condition state-of-charge threshold. Preferably, it can be set to the highest SOC point of the plateau area of the OCV-SOC curve, and the plateau area of the OCV-SOC curve means that the slope of the OCV-SOC curve is less than a certain value. Value area, such as less than 8mV per 1% SOC;
  • CT is the time when the capacity calculation conditions are judged
  • T1 is the time point when it is judged that the calculation condition of the capacity change is satisfied
  • T_Judge is the preset time difference threshold, which represents the maximum allowable value of the time difference between SOC1 and SOC2. This value is usually not too large, because if it is too large, the battery's long-term self-discharge will not be accumulated in ⁇ Cap, thus making the final result The accuracy is reduced.
  • this threshold may be set to 5 days, for example;
  • ⁇ DchaCap is the cumulative change in capacity in the discharge direction starting from T1;
  • ⁇ DchaCap_Judge is the preset capacity change threshold, which represents the maximum allowable discharge between SOC1 and SOC2, and prevents excessive discharge conditions.
  • the current sampling error is large and the inaccuracy of ⁇ Cap leads to a decrease in the accuracy of the result.
  • This threshold can be set to 0.5*Cap_rate, for example, where Cap_rate is the nominal capacity;
  • the capacity calculation module 304 is used to calculate the capacity
  • Cap_cal is the actual capacity of the battery
  • ⁇ Cap is the amount of change in the cumulative capacity from T1 as the starting point in time
  • the state of health calculation module 305 is configured to calculate the state of health (SOH) according to the capacity change and the capacity
  • SOH_C is the state of health (SOH) of the battery
  • Cap_rate is the nominal capacity of the battery when it leaves the factory.
  • the embodiment of the present invention also discloses a vehicle, which includes the battery health status acquiring device.
  • the embodiment of the present invention also discloses a computer-readable storage medium that stores a computer program, wherein the computer program causes the computer to execute any of the foregoing methods for acquiring the battery health status.
  • the embodiment of the present invention also discloses a computer program product, wherein when the computer program product runs on a computer, the computer is caused to execute part or all of the steps of the method in the above method embodiments.
  • the embodiment of the present invention also discloses an application publishing platform, the application publishing platform is used to publish computer program products, wherein, when the above-mentioned computer program product runs on a computer, the computer is caused to execute parts of the methods in the above method embodiments. Or all steps.
  • the program can be stored in a computer-readable storage medium, and the storage medium includes read-only Memory (Read-Only Memory, ROM), Random Access Memory (RAM), Programmable Read-only Memory (PROM), Erasable Programmable Read Only Memory, EPROM), One-time Programmable Read-Only Memory (OTPROM), Electronically-Erasable Programmable Read-Only Memory (EEPROM), CD-ROM (Compact Disc) Read-Only Memory (CD-ROM) or other optical disk storage, magnetic disk storage, tape storage, or any other computer-readable medium that can be used to carry or store data.
  • Read-Only Memory Read-Only Memory
  • RAM Random Access Memory
  • PROM Programmable Read-only Memory
  • EPROM Erasable Programmable Read Only Memory
  • OTPROM One-time Programmable Read-Only Memory
  • EEPROM Electronically-Erasable Programmable Read-Only Memory
  • CD-ROM Compact Disc Read-Only Memory
  • CD-ROM Compact Disc

Abstract

一种电池健康状态获取方法及装置、存储介质，方法包括：当车辆上电时，判断是否满足容量变化量计算条件（101）；当判断满足容量变化量计算条件时，计算容量变化量（102）；当车辆上电时，判断是否满足容量计算条件（103）；当判断满足容量计算条件时，计算容量（104）；根据容量变化量与容量计算电池健康状态（105）。通过方法及装置、存储介质，可以不需要测量电池全寿命周期循环数与SOH的对应关系，节省测试资源与时间；更真实地反映电池实际容量老化程度，提升荷电状态、续驶里程估算精度，为用户提供良好驾驶体验。

Description

一种电池健康状态获取方法及装置、存储介质
相关申请的交叉引用
本申请要求于2020年06月24日提交中国专利局的申请号为CN202010588936.6、名称为“一种电池健康状态获取方法及装置、存储介质”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本发明涉及电池技术领域，具体涉及一种电池健康状态获取方法及装置、存储介质。
背景技术
对于新能源汽车，尤其是纯电动汽车，锂离子动力电池是主要的动力来源。电池的SOH(State Of Health，健康状态)是动力电池的一个重要参数，表征了电池的老化程度，也就是容量的衰减与内阻的增加。SOH关系到电池的其他重要状态的估算，例如SOC(State of charge，荷电状态)和许用功率的估算，SOC和许用功率直接影响续驶里程和驾驶体验，所以如何准确估算电池的SOH是纯电动汽车的重要课题。
现有新能源汽车锂离子动力电池的SOH估算，一般采用的是计量电池的循环次数，通过查询提前测得的循环数与SOH的对应表得到电池健康状态SOH。实际上由于电池在不同的车辆上所处的温度不同，经历的工况不同以及电池之间的差异等原因，即使是相同的循环次数，实际上不同的电池的SOH也不同，所以这种方法无法真实反映电池的实际SOH，进而导致SOC、续驶里程等估算不准，严重影响用户驾驶体验。
发明内容
本发明实施例公开了一种电池健康状态获取方法及装置、存储介质，能够提高电池健康状态的计算精度。
本发明实施例第一方面公开了一种电池健康状态获取方法，所述方法包括：
当车辆上电时，判断是否满足容量变化量计算条件；
当判断满足所述容量变化量计算条件时，计算容量变化量；
当车辆上电时，判断是否满足容量计算条件；
当判断满足所述容量计算条件时，计算容量；
根据所述容量变化量与容量计算电池健康状态。
本发明实施例第二方面公开了一种电池健康状态获取装置，所述装置包括：
容量变化量计算条件判断模块，用于当车辆上电时，判断是否满足容量变化量计算条件；
容量变化量计算模块，用于计算容量变化量；
容量计算条件判断模块，用于当车辆上电时，判断是否满足容量计算条件；
容量计算模块，用于计算容量；
健康状态计算模块，用于根据所述容量变化量与容量计算健康状态。
本发明实施例第三方面公开一种计算机可读存储介质，其存储计算机程序，其中，所述计算机程序使得计算机执行本发明实施例第一方面公开的电池健康状态获取方法。
与现有技术相比，本发明实施例具有以下有益效果：不需要测量电池全寿命周期循环数与SOH的对应关系，节省测试资源与时间；更真实地反映电池实际容量老化程度，提升荷电状态、续驶里程估算精度，为用户提供良好驾驶体验。
附图说明
为了更清楚地说明本发明实施例中的技术方案，下面将对实施例中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1是本发明实施例公开的一种电池健康状态获取方法的一实施例的流程示意图；
图2是本发明实施例公开的一种电池健康状态获取方法的另一实施例的流程示意图；
图3是本发明实施例公开的一种电池健康状态获取装置的一实施例的模块示意图。
具体实施方式
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。
需要说明的是，本发明的说明书和权利要求书中的术语“第一”、“第二”、“第三”和“第四”等是用于区别不同的对象，而不是用于描述特定顺序。本发明实施例的术语“包括”和“具有”以及他们的任何变形，意图在于覆盖不排他的包含，例如，包含了一系列步骤或单元的过程、方法、系统、产品或设备不必限于清楚地列出的那些步骤或单元，而是可包括没有清楚地列出的或对于这些过程、方法、产品或设 备固有的其它步骤或单元。
本发明实施例提供了一种电池健康状态获取方法，主要根据电池的OCV-SOC(开路电压-荷电状态)曲线，在车辆使用过程中根据OCV(开路电压)找到两个与OCV-SOC曲线对应的SOC点，累计两点之间的容量变化量，容量变化量除以两点之间的SOC差，即为当前电池的实际容量。当前电池的实际容量与电池出厂时的标称容量的比值化为百分数，即为SOH。以下结合具体实施例进行说明。
如图1所示，为本发明实施例的一种电池健康状态获取方法的一实施例的流程示意图，包括：
101、当车辆上电时，判断是否满足容量变化量计算条件；
所述容量变化量计算条件包括：
容量变化量计算条件A、驻车时间≥S1；
驻车时间即为上一次下电到此次上电间隔的时间；
S1为预设的容量变化量计算条件驻车时间阈值，优选地，S1可以是电池静态下去除极化端电压达到稳定所需的时间；
容量变化量计算条件B、最小单体电压的电池的当前电压对应的该电池的OCV-SOC曲线的SOC值SOC1≤SOC_judge1；
所述最小单体电压对应的电池即就是当前电池中所有单体电池中电压最低的；通过该电池的OCV-SOC曲线可以获取当前电压对应的SOC值，将此值记为SOC1；
所述SOC_judge1为预设的容量变化量计算条件荷电状态阈值，优选地，其可以设置为OCV-SOC曲线的平台区的SOC最低点，OCV-SOC曲线的平台区指OCV-SOC曲线的斜率小于一定值的区域，如小于8mV每1％SOC；
以上两个条件都满足时，则认为满足容量变化量计算条件；
102、若满足容量变化量计算条件，则计算容量变化量；
分别计算：
Figure PCTCN2020135129-appb-000001
Figure PCTCN2020135129-appb-000002
其中，
T1为判断满足容量变化量计算条件时的时间点；
RTC为计算ΔCap或ΔDchaCap的时间，可以由BMS内部计时获取或者由外部获取；
I为电池的电流；
I d为电池放电方向的电流；
ΔCap为从T1为时间起点的累计容量的变化量；
ΔDchaCap为从T1为时间起点的累计的放电方向的容量的变化量；
103、当车辆上电时，判断是否满足容量计算条件；
所述容量计算条件包括：
容量计算条件A、驻车时间≥S2；
驻车时间即为上一次下电到此次上电间隔的时间；
S2为预设的容量计算条件时间阈值，优选地，S2可以是电池静态下去除极化端电压达到稳定所需的时间；
容量计算条件B、最大单体电压对应的电池的电压值在OCV-SOC曲线中对应的SOC值SOC2≤SOC_judge2；
所述最大单体电压对应的电池即就是电池中所有单体电池中电压最高的；通过该电池的OCV-SOC曲线可以获取当前电压对应的SOC值，将此值记为SOC2；
所述SOC_judge2为预设的容量计算条件荷电状态阈值，优选地，其可以设置为OCV-SOC曲线的平台区的SOC最高点，OCV-SOC曲线的平台区指OCV-SOC曲线的斜率小于一定值的区域，如小于8mV每1％SOC；
容量计算条件C、CT-T1≤T_Judge
其中：
CT为判断容量计算条件时的时间；
T1为判断满足容量变化量计算条件时的时间点；
T_Judge为预设的时间差阈值，其表示SOC1与SOC2的时间差的最大允许值，此数值通常不会过大，因为太大的话会造成电池长时间的自放电未被累计在ΔCap，从而使得最终结果精度降低，在一些实施例中，此阈值例如可以设置为5天；
容量计算条件D、ΔDchaCap≤ΔDchaCap_Judge
其中：
ΔDchaCap为从T1为时间起点的累计的放电方向的容量的变化量；
ΔDchaCap_Judge为预设的容量变化量阈值，其表示了SOC1与SOC2之间最大容许的放电量，防止过多的放电工况电流采样误差大使得ΔCap不准导致结果精度降低，在一些实施例中，此阈值例如可以设置为0.5*Cap_rate，其中Cap_rate为标称容量；
以上四个条件都满足时，则认为满足容量计算条件；
104、若满足容量计算条件，则计算容量；
具体包括：
Figure PCTCN2020135129-appb-000003
其中，
Cap_cal为电池实际容量；
ΔCap为从T1为时间起点的累计容量的变化量；
105、根据所述容量变化量与容量计算SOH
Figure PCTCN2020135129-appb-000004
其中，
SOH_C为电池的健康状态(SOH)；
Cap_rate为电池出厂的标称容量。
通过以上说明，可以看出本发明实施例至少具有以下有益效果：
采用了较佳的SOC1和SOC2选取方式，从而使得容量的变化量ΔCap和放电方向的容量变化量ΔDchaCap累计精确，所以当前电池实际容量和反映容量的电池健康状态SOH计算精度高；
不需要测量电池全寿命周期循环数与SOH的对应关系，节省测试资源与时间；
更真实地反映电池实际容量老化程度，提升荷电状态、续驶里程估算精度，为用户提供良好驾驶体验。
以上以逻辑正向的方式说明了一个估算SOH的方法实施例，实际上，由于估算SOH通常并不是在一次上电-下电过程中完成的，所以在实际执行中，以时间正向方式实施的实施例看起来与上面的方案并不是完全相同，以下就对时间正向方式实施的实施例进行说明。
如图2所示，为本发明实施例的一种电池健康状态获取方法的另一实施例的流程示意图，包括：
201、当车辆上电时，判断是否有进行中的容量变化量计算过程；
当存在进行中的容量变化量计算过程时，通常电池管理系统中会有相应的记录，通过该记录可以得知是否存在进行中的容量变化量计算过程；
若有，则判断所述容量变化量计算过程是否过期；
由于每个容量变化量计算过程都有一定的期限，超过了期限将会重新判断是否满足容量变化量计算条件；
若无，则判断是否满足容量变化量计算条件；
202、判断所述容量变化量计算过程是否已经过期；
容量变化量计算过程通常有一定的时间限制，例如在本发明的一些实施例中，可以限制为从满足容量变化量计算条件的时间起不超过5天；
若没有过期，则计算容量变化量；
若过期，则判断是否满足容量变化量计算条件；
203、判断是否满足容量变化量计算条件；
所述容量变化量计算条件包括：
容量变化量计算条件A、驻车时间≥S1；
驻车时间即为上一次下电到此次上电间隔的时间；
S1为预设的容量变化量计算条件驻车时间阈值，优选地，S1可以是电池静态下去除极化端电压达到稳定所需的时间；
容量变化量计算条件B、最小单体电压的电池的当前电压对应的该电池的OCV-SOC曲线的SOC值SOC1≤SOC_judge1；
所述最小单体电压对应的电池即就是当前电池中所有单体电池中电压最低的；通过该电池的OCV-SOC曲线可以获取当前电压对应的SOC值，将此值记为SOC1；
所述SOC_judge1为预设的容量变化量计算条件荷电状态阈值，优选地，其可以设置为OCV-SOC曲线的平台区的SOC最低点，OCV-SOC曲线的平台区指OCV-SOC曲线的斜率小于一定值的区域，如小于8mV每1％SOC；
以上两个条件都满足时，则认为满足容量变化量计算条件；
204、计算容量变化量；
分别计算：
Figure PCTCN2020135129-appb-000005
Figure PCTCN2020135129-appb-000006
其中，
T1为判断满足容量变化量计算条件时的时间点；
RTC为计算ΔCap或ΔDchaCap的时间，可以由BMS内部计时获取或者由外部获取；
I为电池的电流；
I d为电池放电方向的电流；
ΔCap为从T1为时间起点的累计容量的变化量；
ΔDchaCap为从T1为时间起点的累计的放电方向的容量的变化量；
205、判断是否满足容量计算条件；
所述容量计算条件包括：
容量计算条件A、驻车时间≥S2；
驻车时间即为上一次下电到此次上电间隔的时间；
S2为预设的容量计算条件时间阈值，优选地，S2可以是电池静态下去除极化端电压达到稳定所需的时间；
容量计算条件B、最大单体电压对应的电池的电压值在OCV-SOC曲线中对应的SOC值SOC2≤SOC_judge2；
所述最大单体电压对应的电池即就是电池中所有单体电池中电压最高的；通过该电池的OCV-SOC曲线可以获取当前电压对应的SOC值，将此值记为SOC2；
所述SOC_judge2为预设的容量计算条件荷电状态阈值，优选地，其可以设置为OCV-SOC曲线的平台区的SOC最高点，OCV-SOC曲线的平台区指OCV-SOC曲线的斜率小于一定值的区域，如小于8mV每1％SOC；
容量计算条件C、CT-T1≤T_Judge
其中：
CT为判断容量计算条件时的时间；
T1为判断满足容量变化量计算条件时的时间点；
T_Judge为预设的时间差阈值，其表示SOC1与SOC2的时间差的最大允许值，此数值通常不会过大，因为太大的话会造成电池长时间的自放电未被累计在ΔCap，从而使得最终结果精度降低，在一些实施 例中，此阈值例如可以设置为5天；
容量计算条件D、ΔDchaCap≤ΔDchaCap_Judge
其中：
ΔDchaCap为从T1为时间起点的累计的放电方向的容量的变化量；
ΔDchaCap_Judge为预设的容量变化量阈值，其表示了SOC1与SOC2之间最大容许的放电量，防止过多的放电工况电流采样误差大使得ΔCap不准导致结果精度降低，在一些实施例中，此阈值例如可以设置为0.5*Cap_rate，其中Cap_rate为标称容量；
以上四个条件都满足时，则认为满足容量计算条件；
206、计算当前电池实际容量；
具体为：
Figure PCTCN2020135129-appb-000007
其中，ΔCap为从T1为时间起点的累计容量的变化量；
SOC2为判断是否满足容量计算条件时获取的最大单体电压对应的电池的电压值在OCV-SOC曲线的SOC值；
SOC1为判断是否满足容量变化量计算条件时最小单体电压的当前电压对应的该电池的OCV-SOC曲线的SOC值；
207、根据容量与容量变化量计算SOH；
Figure PCTCN2020135129-appb-000008
其中，
SOH_C为电池的健康状态(SOH)；
Cap_rate为电池出厂的标称容量。
本发明实施例还提出了一种电池健康状态获取装置，如图3所示，为本发明提出的一种电池健康状态获取装置的模块示意图，包括：
容量变化量计算条件判断模块301，用于当车辆上电时，判断是否满足容量变化量计算条件；
所述容量变化量计算条件包括：
容量变化量计算条件A、驻车时间≥S1；
驻车时间即为上一次下电到此次上电间隔的时间；
S1为预设的容量变化量计算条件驻车时间阈值，优选地，S1可以是电池静态下去除极化端电压达到稳定所需的时间；
容量变化量计算条件B、最小单体电压的电池的当前电压对应的该电池的OCV-SOC曲线的SOC值SOC1≤SOC_judge1；
所述最小单体电压对应的电池即就是当前电池中所有单体电池中电压最低的；通过该电池的OCV-SOC曲线可以获取当前电压对应的SOC值，将此值记为SOC1；
所述SOC_judge1为预设的容量变化量计算条件荷电状态阈值，优选地，其可以设置为OCV-SOC曲线的平台区的SOC最低点，OCV-SOC曲线的平台区指OCV-SOC曲线的斜率小于一定值的区域，如小于8mV每1％SOC；
以上两个条件都满足时，则认为满足容量变化量计算条件；
容量变化量计算模块302，用于计算容量变化量；
具体分别计算：
Figure PCTCN2020135129-appb-000009
Figure PCTCN2020135129-appb-000010
其中，
T1为判断满足容量变化量计算条件时的时间点；
RTC为计算ΔCap或ΔDchaCap的时间，可以由BMS内部计时获取或者由外部获取；
I为电池的电流；
I d为电池放电方向的电流；
ΔCap为从T1为时间起点的累计容量的变化量；
ΔDchaCap为从T1为时间起点的累计的放电方向的容量的变化量；
容量计算条件判断模块303，用于当车辆上电时，判断是否满足容量计算条件；
所述容量计算条件包括：
容量计算条件A、驻车时间≥S2；
驻车时间即为上一次下电到此次上电间隔的时间；
S2为预设的容量计算条件时间阈值，优选地，S2可以是电池静态下去除极化端电压达到稳定所需的时间；
容量计算条件B、最大单体电压对应的电池的电压值在OCV-SOC曲线中对应的SOC值SOC2≤SOC_judge2；
所述最大单体电压对应的电池即就是电池中所有单体电池中电压最高的；通过该电池的OCV-SOC曲线可以获取当前电压对应的SOC值，将此值记为SOC2；
所述SOC_judge2为预设的容量计算条件荷电状态阈值，优选地，其可以设置为OCV-SOC曲线的平台区的SOC最高点，OCV-SOC曲线的平台区指OCV-SOC曲线的斜率小于一定值的区域，如小于8mV每1％SOC；
容量计算条件C、CT-T1≤T_Judge
其中：
CT为判断容量计算条件时的时间；
T1为判断满足容量变化量计算条件时的时间点；
T_Judge为预设的时间差阈值，其表示SOC1与SOC2的时间差的最大允许值，此数值通常不会过大，因为太大的话会造成电池长时间的自放电未被累计在ΔCap，从而使得最终结果精度降低，在一些实施例中，此阈值例如可以设置为5天；
容量计算条件D、ΔDchaCap≤ΔDchaCap_Judge
其中：
ΔDchaCap为从T1为时间起点的累计的放电方向的容量的变化量；
ΔDchaCap_Judge为预设的容量变化量阈值，其表示了SOC1与SOC2之间最大容许的放电量，防止过多的放电工况电流采样误差大使得ΔCap不准导致结果精度降低，在一些实施例中，此阈值例如可以设置为0.5*Cap_rate，其中Cap_rate为标称容量；
以上四个条件都满足时，则认为满足容量计算条件；
容量计算模块304，用于计算容量；
具体用于计算：
Figure PCTCN2020135129-appb-000011
其中，
Cap_cal为电池实际容量；
ΔCap为从T1为时间起点的累计容量的变化量；
健康状态计算模块305、用于根据所述容量变化量与容量计算健康状态(SOH)
Figure PCTCN2020135129-appb-000012
其中，
SOH_C为电池的健康状态(SOH)；
Cap_rate为电池出厂的标称容量。
通过以上说明，可以看出本发明实施例至少具有以下有益效果：
采用了较佳的SOC1和SOC2选取方式，从而使得容量的变化量ΔCap和放电方向的容量变化量ΔDchaCap累计精确，所以当前电池实际容量和反映容量的电池健康状态SOH计算精度高；
不需要测量电池全寿命周期循环数与SOH的对应关系，节省测试资源与时间；
更真实地反映电池实际容量老化程度，提升荷电状态、续驶里程估算精度，为用户提供良好驾驶体验。
本发明实施例还公开一种车辆，该车辆包括所述一种电池健康状态获取装置。
本发明实施例还公开一种计算机可读存储介质，其存储计算机程序，其中，该计算机程序使得计算机执行上述任意一种电池健康状态获取方法。
本发明实施例还公开一种计算机程序产品，其中，当计算机程序产品在计算机上运行时，使得计算机执行如以上各方法实施例中的方法的部分或全部步骤。
本发明实施例还公开一种应用发布平台，该应用发布平台用于发布计算机程序产品，其中，当上述计算机程序产品在计算机上运行时，使得计算机执行如以上各方法实施例中的方法的部分或全部步骤。
本领域普通技术人员可以理解上述实施例的各种方法中的全部或部分步骤是可以通过程序来指令相关的硬件来完成，该程序可以存储于一计算机可读存储介质中，存储介质包括只读存储器(Read-Only Memory，ROM)、随机存储器(Random Access Memory，RAM)、可编程只读存储器(Programmable Read-only Memory，PROM)、可擦除可编程只读存储器(Erasable Programmable Read Only Memory，EPROM)、一次可编程只读存储器(One-time Programmable Read-Only Memory，OTPROM)、电子抹除式可复写只读存储器(Electrically-Erasable Programmable Read-Only Memory，EEPROM)、只读 光盘(Compact Disc Read-Only Memory，CD-ROM)或其他光盘存储器、磁盘存储器、磁带存储器、或者能够用于携带或存储数据的计算机可读的任何其他介质。
以上对本发明实施例公开的一种电池健康状态获取方法及装置、存储介质进行了详细介绍，本文中应用了具体个例对本发明的原理及实施方式进行了阐述，以上实施例的说明只是用于帮助理解本发明的方法及其核心思想；同时，对于本领域的一般技术人员，依据本发明的思想，在具体实施方式及应用范围上均会有改变之处，综上所述，本说明书内容不应理解为对本发明的限制。

Claims (10)

  1. 一种电池健康状态获取方法，其特征在于，包括：
    当车辆上电时，判断是否满足容量变化量计算条件；
    当判断满足所述容量变化量计算条件时，计算容量变化量；
    当车辆上电时，判断是否满足容量计算条件；
    当判断满足所述容量计算条件时，计算容量；
    根据所述容量变化量与容量计算电池健康状态。
  2. 如权利要求1所述的电池健康状态获取方法，其特征在于：
    所述判断是否满足容量变化量计算条件之前还包括：
    当车辆上电时，判断当前是否有进行中的容量变化量计算过程；
    若有则进行所述判断是否满足容量计算条件的步骤；
    若无则进行所述判断是否满足容量变化量计算条件的步骤。
  3. 如权利要求1所述的电池健康状态获取方法，其特征在于：
    所述判断是否满足容量变化量计算条件之前还包括：
    当车辆上电时，判断当前是否有进行中的容量变化量计算过程；
    若判断有进行中的容量变化量计算过程则判断所述进行中的容量变化量计算过程是否过期；
    若判断无进行中的容量变化量计算过程则进行所述判断是否满足容量变化量计算条件的步骤；
    若判断所述进行中的容量变化量计算过程是否过期的结果为过期，则进行所述判断是否满足容量变化量计算条件的步骤；
    若判断所述进行中的容量变化量计算过程是否过期的结果为未过期，则进行所述判断是否满足容量计算条件的步骤。
  4. 如权利要求1至3任一项所述的电池健康状态获取方法，其特征在于：
    所述容量变化量计算条件包括同时满足以下两个条件：
    容量变化量计算条件A：驻车时间≥S1；
    所述S1为预设的容量变化量计算条件驻车时间阈值；
    容量变化量计算条件B：SOC1≤SOC_judge1；
    所述SOC1为最小单体电压的当前电压对应的该电池的OCV-SOC曲线的SOC值；
    所述SOC_judge1为预设的容量变化量计算条件荷电状态阈值。
  5. 如权利要求4所述的电池健康状态获取方法，其特征在于：
    所述计算容量变化量包括：
    计算：
    Figure PCTCN2020135129-appb-100001
    Figure PCTCN2020135129-appb-100002
    其中，
    T1为判断满足容量变化量计算条件时的时间点；
    RTC为计算ΔCap或ΔDchaCap的时间，可以由BMS内部计时获取或者由外部获取；
    I为电池的电流；
    I d为电池放电方向的电流；
    ΔCap为从T1为时间起点的累计容量的变化量；
    ΔDchaCap为从T1为时间起点的累计的放电方向的容量的变化量。
  6. 如权利要求5所述的电池健康状态获取方法，其特征在于：
    所述容量计算条件包括满足以下四个条件：
    容量计算条件A：驻车时间≥S2；
    驻车时间即为上一次下电到此次上电间隔的时间；
    S2为预设的容量计算条件时间阈值；
    容量计算条件B：SOC2≤SOC_judge2；
    所述SOC2为最大单体电压对应的电池的OCV-SOC曲线的SOC值；
    所述SOC_judge2为预设的容量计算条件荷电状态阈值；
    容量计算条件C：CT-T1≤T_Judge
    其中：
    所述CT为判断容量计算条件时的时间；
    所述T1为判断满足容量变化量计算条件时的时间点；
    T_Judge为预设的时间差阈值；
    容量计算条件D：ΔDchaCap≤ΔDchaCap_Judge
    其中：
    所述ΔDchaCap为从T1为时间起点的累计的放电方向的容量的变化量；
    所述ΔDchaCap_Judge为预设的容量变化量阈值上限。
  7. 如权利要求6所述的电池健康状态获取方法，其特征在于：
    所述计算容量包括：
    Figure PCTCN2020135129-appb-100003
    其中，
    所述Cap_cal为电池实际容量；
    所述ΔCap为从T1为时间起点的累计容量的变化量。
  8. 如权利要求7所述的电池健康状态获取方法，其特征在于：
    所述根据所述容量变化量与容量计算电池健康状态包括：
    计算：
    Figure PCTCN2020135129-appb-100004
    其中，
    所述SOH_C为电池健康状态；
    所述Cap_rate为电池出厂的标称容量。
  9. 一种电池健康状态获取装置，其特征在于，包括：
    容量变化量计算条件判断模块，用于当车辆上电时，判断是否满足容量变化量计算条件；
    容量变化量计算模块，用于计算容量变化量；
    容量计算条件判断模块，用于当车辆上电时，判断是否满足容量计算条件；
    容量计算模块，用于计算容量；
    健康状态计算模块，用于根据所述容量变化量与容量计算健康状态。
  10. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质存储计算机程序，其中，所述计算机程序使得计算机执行权利要求1至8任一项所述的电池健康状态获取方法。
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