基于内阻功率消耗的锂电池SOC估计*

doi:10.19562/j.chinasae.qcgc.2020.08.003

汽车工程 ›› 2020, Vol. 42 ›› Issue (8): 1008-1015.doi: 10.19562/j.chinasae.qcgc.2020.08.003

基于内阻功率消耗的锂电池SOC估计^*

靳博文^1,2, 乔慧敏³, 潘天红¹, 陈山²

1.安徽大学电气工程与自动化学院,合肥 230601;
2.江苏大学电气信息工程学院,镇江 212013;
3.湖南大学机械与运载工程学院,长沙 410082

收稿日期:2019-11-19 出版日期:2020-08-25 发布日期:2020-09-24
通讯作者: 潘天红,教授,博士,E-mail:thpan@adu.cn。
基金资助:
*国家自然科学基金(61873113)和江苏省重点研发计划(BE2018370)资助。

Lithium Battery SOC Estimation Based on Internal Resistance Power Consumption

Jin Bowen^1,2, Qiao Huimin³, Pan Tianhong¹, Chen Shan²

1. Electrical Engineering and Automation, Anhui University, Hefei 230601;
2. Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013;
3. Mechanical and Transportation Engineering, Hunan University, Changsha 410082

Received:2019-11-19 Online:2020-08-25 Published:2020-09-24

摘要/Abstract

摘要： 针对锂电池不同使用场合下的剩余电量估算精度的问题,提出了基于内阻功率的放电策略与功率积分的电池剩余电量计算方法。选取电池的1阶Thevenin等效电路模型,通过放电实验确定电池内部参数,建立了电池的可变参数模型。依据电池不同使用需求,通过功率控制电池放电电流,稳定电池的容量,提升了安时积分算法在稳定放电工况下的鲁棒性;将电池的温度、高频率波动电流和健康状况引入积分项,以衡量电池容量消耗速率,并采用功率积分算法估算电池剩余容量。将积分算法与EKF结合,减弱了积分误差对估算精度的影响。搭建实验台架,设计锂电池的放电工况,采用与之对应的放电策略和计算方法。结果表明:本文的方法有效地提升了电池剩余电量的估算精度。

关键词: 锂电池, 可变参数模型, 剩余电量, 功率积分算法, EKF算法, 鲁棒性

Abstract: Aiming at the problem of estimating the remaining capacity of lithium battery under different operation situations, a calculation method of remaining battery capacity based on internal resistance power discharge strategy and power integration is proposed. The first-order Thevenin equivalent circuit model of the battery is selected, the internal parameters of the battery are determined by discharge experiments, and the variable parameter model of the battery is established. According to the different operation requirements of the battery, the battery discharge current is controlled by power, to stabilize battery capacity and improve the robustness of the ampere-hour integral algorithm under stable discharge conditions. The temperature, high frequency fluctuation current and SOH of the battery are introduced into integral item to measure the capacity consumption rate of the battery, and the remaining capacity of the battery is estimated by power integration algorithm. The integration algorithm is combined with EKF to weaken the influence of integral error on estimation accuracy. The experimental bench is set up and the discharge condition of the lithium battery is designed with the corresponding discharge strategy and calculation method adopted. The results show that the method proposed can effectively enhance the estimation accuracy of battery remaining capacity.

Key words: lithium battery, variable parameter model, remaining capacity, power integration algorithm, EKF algorithm, robustness

靳博文, 乔慧敏, 潘天红, 陈山. 基于内阻功率消耗的锂电池SOC估计^*[J]. 汽车工程, 2020, 42(8): 1008-1015.

Jin Bowen, Qiao Huimin, Pan Tianhong, Chen Shan. Lithium Battery SOC Estimation Based on Internal Resistance Power Consumption[J]. Automotive Engineering, 2020, 42(8): 1008-1015.

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基于内阻功率消耗的锂电池SOC估计^*

Lithium Battery SOC Estimation Based on Internal Resistance Power Consumption

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