融合经验老化模型和机理模型的电动汽车锂离子电池寿命预测方法研究  

Research on Lithium Ion Battery Life Prediction Method Based on Empirical Aging Model and Mechanism Model for Electric Vehicles

作　　者：梁海强 何洪文[1] 代康伟 庞博 王鹏[1] Liang Haiqiang;He Hongwen;Dai Kangwei;Pang Bo;Wang Peng(School of Mechanical Engineering,Beijing Institute of Technology,Beijing 100081;Beijing New Energy Automobile Company Limited,Beijing 101399;Beijing Automotive Technology Center Company Limited,Beijing 101399)

机构地区：[1]北京理工大学机械与车辆学院,北京100081 [2]北京新能源汽车股份有限公司,北京101399 [3]北京汽车研究总院有限公司,北京101399

出　　处：《汽车工程》2023年第5期825-835,844,共12页Automotive Engineering

摘　　要：为提升实际应用中锂离子动力电池寿命预测精度,本文中提出一种融合经验老化模型和电池机理模型的电池寿命预测方法。该方法以基于经验老化模型SOH预测值作为卡尔曼算法的先验估计,以基于机理模型估计电池未来容量衰减量进而预测得到的SOH作为卡尔曼算法的后验修正,从而实现对锂离子电池寿命的准确预测。基于电芯试验数据的动力电池寿命预测算法验证结果表明,锂离子动力电池剩余寿命预测误差≤5.83%、基于实车数据的锂离子动力电池的剩余寿命预测误差≤8.12%,取得了良好的预测效果,丰富了锂离子动力电池寿命预测的方法。In order to improve the prediction accuracy of remaining useful life of lithium-ion power battery in practical application,a remaining useful life prediction method of lithium-ion power battery combining the empirical aging model and the battery mechanism model is proposed in this paper.The method uses the SOH prediction value based on the empirical aging model as the prior estimate of the Kalman algorithm,and uses the SOH predicted by estimating the future capacity decline of the battery based on the mechanism model as the posterior correction of the Kalman algorithm,so as to achieve accurate prediction of the remaining useful life of the lithium-ion battery.The validation results of power battery remaining useful life prediction algorithm based on the cell test data show that the remaining useful life prediction error of lithium ion power battery is≤5.83%and the maximum error of remaining useful life prediction of lithium-ion power battery based on real vehicle data is 8.12%,which has achieved good prediction results and enriched the life prediction methods of lithium ion power battery.

关 键 词：锂离子电池 融合模型 电池寿命预测 电动汽车 

分 类 号：U469.72[机械工程—车辆工程]