电源学报2025，Vol.23Issue(2)：232-239,8.DOI:10.13234/j.issn.2095-2805.2025.2.232
基于WOA优化扩展卡尔曼算法的锂离子电池SOC估算研究
Research on SOC Estimation of Lithium-ion Battery Based on WOA Optimized Extended Kalman Algorithm
摘要
Abstract
The development of industry and economy has caused a huge consumption of energy,which brings serious energy crisis and environmental pollution.Therefore,building a safe and clean energy interconnection network is a way to solve the relationship among social development,environment and energy at present.Nowadays,different countries have proposed their policies for the development of new energy electric vehicles(EVs).As the core component of EVs,lithium-ion batteries are directly related to the driving performance and safety of EVs.The state-of-charge(SOC)estimation is a core parameter of lithium-ion batteries used in various industries,and the estimation accuracy is directly related to the service life and efficiency of batteries.In this paper,the problem of battery SOC estimation accuracy in EV applications is studied,and an SOC estimation method based on the extended Kalman filter(EKF)optimized by the whale optimization algorithm(WOA)is proposed.On the basis of constructing the covariance matrix of system noise and observation noise,the improved and optimized WOA-EKF algorithm is used to optimize the noise covariance matrix under dynamic conditions,thus improving the SOC estimation accuracy.The model parameter identification and comparative simulation verification are carried out in MATLAB/Simulink.Results show that the SOC estimation of lithium-ion batteries based on the WOA optimized EKF algorithm can control the SOC estimation error to be within 2%under different working conditions,which is of significance to the promotion of develop-ment of batteries in the new energy field.关键词
锂离子电池/荷电状态估算/观测噪声/鲸鱼优化算法-扩展卡尔曼滤波Key words
Lithium-ion battery/state-of-charge(SOC)estimation/observation noise/whale optimization algorithm-extended Kalman filter(WOA-EKF)分类
动力与电气工程引用本文复制引用
许傲然,戴菁,谷彩莲,冷雪敏,魏家和..基于WOA优化扩展卡尔曼算法的锂离子电池SOC估算研究[J].电源学报,2025,23(2):232-239,8.基金项目
辽宁省博士启动基金资助项目(2021-BS-198) （2021-BS-198）
辽宁省教育厅科技2020资助项目(JJL-2008)This work is supported by the Liaoning Doctoral Startup Fund under the grant 2021-BS-198 （JJL-2008）
Science and Technology 2020 Project of Educational Department of Liaoning Province under the grant JJL-2008 （）
