车用锂离子电池剩余使用寿命预测方法

摘要

剩余使用寿命( RUL)是锂离子电池健康监测与维护的关键参数,反映了电池到寿命终点的剩余工作时间. 本文中提出了反映电池健康状态的电池容量衰退参数,利用这些参数建立RUL预测模型. 将支持向量回归机粒子滤波应用于参数估计与RUL预测,给出了RUL的预测值与概率密度. 结果表明提出的方法准确地预测了电池的RUL.%The remaining useful life ( RUL) is a key parameter for the health monitoring and maintenance of lithium-ion battery, which reflects the remaining service time to the end of life of battery. In this paper, the ca-pacity degradation parameters of battery, reflecting the battery state of health, are proposed to build RUL prediction model. Support vector regression-particle filter ( SVR-PF) is applied to parameter estimation and RUL prediction, with the estimate and probability density of RUL given. The results show that the proposed method can accurately predict the RUL of battery.