【作者】 崔皓勇； 魏中宝； 何洪文；

【Author】 Cui Hao-yong;Wei Zhong-bao;He Hong-wen;National Engineering Laboratory of Electric Vehicles,School of Mechanical Engineering,Beijing Institute of Technology;

【机构】 北京理工大学机械与车辆学院电动车辆国家工程实验室；

【摘要】 单体间固有的容量差异限制了锂离子电池组容量的充分利用,阻碍电动汽车续驶里程的提升及退役电池的梯次利用。基于新兴的智能电池概念,本文提出了利用动态可重构拓扑实现电池容量最大化的方案。首先建立智能电池模型,基于最小方差准则联合扩展卡尔曼滤波提升智能电池荷电状态估计精度。随后利用新型可重构智能电池拓扑,实施包含模组内单体分时介入及模组间拆分-重组的分层均衡策略。实验结果表明所提出的智能电池荷电状态估计方法精度较高,分层均衡策略可使电池组容量利用率提升10.9%,实现电池组内所有单体均衡及智能电池容量最大化利用。更多还原

【Abstract】 The inherent capacity inconsistency among individual cells hinders the efficient utilization of lithium-ion battery packs, limiting the improvement of the driving range of electric vehicles and the second-life battery utilization.Based on the emerging concept of smart battery, this paper proposes a practicable scheme for the battery capacity maximum utilization by a dynamic reconfigurable topology. First, a smart battery model is built and the minimum variance criterion and Extended Kalman Filter(EKF) are employed to improve the estimation accuracy of cell state of charge( SOC). Relying on the accurate SOC information and a novel reconfigurable topology, a hierarchical equalization strategy is proposed incorporating the intra-module time-sharing intervention and inter-module splitting-recombination.Experimental results indicate that the minimum variance-EKF-based SOC estimation method can predict the smart-battery SOC with high accuracy. The hierarchical equalization strategy can improve the pack capacity utilizing rate by 10.9%,promising all-cell equalization and maximum capacity utilization of smart batteries.更多还原