基于滑模观测器的锂离子动力电池荷电状态估计

State-of-charge estimation of lithium-ion power battery using sliding mode observer

基于混合动力脉冲功率特性试验数据辨识得到了锂离子动力电池的等效电路模型参数,提出了基于滑模观测器算法的动力电池荷电状态估计方法。设计了滑模观测器,最后进行了算法验证。结果表明,对FUDS工况,应用滑模观测器算法进行荷电状态估计的最大误差为1.17%,方差为0.000 04,比传统算法获得了更好的估计精度和鲁棒性。

The parameters of equivalent circuit of lithium-ion power battery were obtained from the hybrid pulre power characterization test data model, a state-of charge（SOC） estimation method for the lithium-ion power battery was proposed using a sliding mode observer. The sliding mode observer was designed and descriled in detail. Its algorithm was verified and evaluated by experiments and comparisons with the traditional method. The results show that under the FUDS condition, SOC estimation with the sliding mode observer gives the maximum error of 1. 17% with variance of 0. 000 04, which is more accurate and robust than the traditional algorithm.