基于pso＿FSVM的车用动力电池温度预测模型研究Research on temperature prediction model of vehicle power battery based on pso＿FSVM
刘荣,童亮,许永红
摘要(Abstract)：
针对混合动力汽车在复杂工况下动力电池温度测量可靠性下降的问题,提出基于pso_FSVM的车用动力电池温度预测模型,该研究分别采集车辆key_on和key_off两种状态下的动力电池温度数据,采用粒子群优化的快速支持向量机算法,构建了稳定的动力电池温度预测模型。实验结果表明,在车辆key_on和key_off两种状态下,数据集的预测数据与实际测量数据的相关系数分别达到0.810 2和0.797 3,温度预测误差小于2℃,pso_FSVM模型提高了动力电池温度预测的精度和可靠性。
关键词(KeyWords)： 混合动力汽车;动力电池温度;粒子群;快速支持向量机;预测模型;热动力学模型
基金项目(Foundation): 国家自然科学基金(51275053);; 电动汽车北京市实验室项目(PXM_2013_014224_000005)~~
作者(Author): 刘荣,童亮,许永红
DOI: 10.16652/j.issn.1004-373x.2018.12.006
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