基于SOC的锂动力电池组双向主动均衡控制

SOC-Based Bi-Directional Active Equalization Control for Lithium-Ion Power Battery

电动汽车锂动力电池组中单体电池的不一致性会导致电池组的容量和使用寿命的衰减,严重影响了电动汽车的性能。为此设计了一种以双向Buck-Boost拓扑为主电路的主动均衡控制系统,采用极限学习机(Extreme Learning Machine,ELM)预测电池的荷电状态(State of Charge,SOC),并以SOC作为主要的均衡判据,提出了一种新型的主动均衡控制策略,实现了锂电池组在充电过程和静置状态下的主动均衡。实验结果表明:所提出的双向主动均衡控制方法可以准确高效地实现均衡目标,且能量损耗较少。

The inconsistency of cell in the electric vehicles＇ lithium-ion power battery pack leads to decrease the battery pack＇s capacity and lifetime, and even seriously affect the electric vehicles＇ performance. An active equalization system was designed based on the hi-directional Buck-Boost topology. A novel active equalization control strategy was proposed to balance the lithium-ion battery pack in the process of charging and static state, which extreme learning machine （ELM） was used to predict the state of charge（SOC）, and SOC was employed as the main balance criterion. The simulation results show that the proposed bi-directional active equalization method can realize the equalization target accurately and efficiently with less ener- loss.