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

作　　者：许傲然 戴菁 谷彩莲 冷雪敏 魏家和 XU Aoran;DAI Jing;GU Cailian;LENG Xuemin;WEI Jiahe(School of Electric Power,Shenyang Institute of Engineering,Shenyang 110136,China;Marketing Service Center,State Grid Liaoning Electric Power Supply Co.,Ltd.,Shenyang 110136,China)

机构地区：[1]沈阳工程学院电力学院,沈阳110136 [2]国网辽宁省电力有限公司营销服务中心,沈阳110136

出　　处：《电源学报》2025年第2期232-239,共8页Journal of Power Supply

基　　金：辽宁省博士启动基金资助项目(2021-BS-198);辽宁省教育厅科技2020资助项目(JJL-2008)。

摘　　要：工业和经济的发展对能源造成了巨大的消耗,同时也带来了严重的能源危机和环境污染,而构建安全、清洁的能源互联网络是解决当今社会发展和环境、能源关系的途径。现在各国都提出新能源电动汽车发展政策,锂离子电池作为电动汽车的核心部件直接关系着它的行驶性能和安全性。电池的荷电状态SOC(state-of-charge)作为锂离子电池应用在各个行业的核心参数,其估算精度直接关系到电池的使用寿命和效率。针对电动汽车应用中电池SOC估算精度存在的问题进行研究,提出基于鲸鱼优化算法WOA(whale optimization algorithm)优化扩展卡尔曼滤波EKF(extended Kalman filter)的SOC估算方法,在构建系统噪声和观测噪声的协方差矩阵的基础上,在动态工况下利用改进优化后的WOA-EKF算法优化噪声协方差矩阵,提高SOC估算精度。并在MATLAB/Simulink中进行了模型参数辨识和对比仿真验证,结果表明:基于WOA优化扩展卡尔曼滤波算法的锂离子电池SOC估算能够在不同的工况下控制SOC估算误差在2%以内,在促进电池在新能源领域中的进一步发展方面具有一定的研究意义。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 development 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 

分 类 号：TM89[电气工程—高电压与绝缘技术]