电动汽车荷电状态估计与能量协同控制研究

2021 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA) Pub Date : 2021-06-28 DOI:10.1109/ICAICA52286.2021.9498217

Fang Bin, Peng Fuming, Lin Qingchao

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引用次数: 0

摘要

将锂离子电池模型划分为三个子系统，采用FFRLS算法在线辨识模型参数。采用SFEKF算法提高了传统EKF算法的滤波精度。提出了基于FFRLS和SFEKF算法的SOC估计算法。它可以准确地估计锂离子电池的SOC，误差在3%左右。此外，锂离子电池和超级电容器形成混合供电系统。提出了一种基于遗传算法优化的模糊逻辑控制的能源协同控制策略。采用Simulink / advisor联合仿真平台对所设计的算法进行了仿真。仿真结果表明，该方法延长了电动汽车动力电池的使用寿命，提高了电动汽车的能源利用率。

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Research on SOC Estimation and Energy Cooperative Control for Electric Vehicles

The lithium-ion battery model is divided into three subsystems, and then the model parameters are identified online by FFRLS algorithm. The SFEKF algorithm is used to improve the filtering accuracy of traditional EKF algorithm. The SOC estimation algorithm is presented, which is based on FFRLS and SFEKF algorithm. It can accurately estimate the SOC of lithium-ion batteries with an error of around 3%. In addition, lithium-ion batteries and super-capacitors form a hybrid power supply system. An energy co-control strategy is presented, which is based on fuzzy logic control that is optimized by genetic algorithms. The designed algorithm is simulated by Simulink / advisor co-simulation platform. The simulation results showed that the service life of the power battery of electric vehicles was prolonged and the energy utilization of electric vehicles was improved.

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来源期刊

2021 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)

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