Research on Automatic Matching Model of Power Battery
In order to realize the intelligent matching of power battery,an automatic battery sorting and matching system were designed.The intelligent matching algorithm based on the optimized fuzzy clustering algorithm and support vector machine was studied,and an automatic matching prediction model of power battery was proposed.Firstly,the model introduces the Xie-Beni validity index to find the best number of classifications,then uses the genetic adaptive algorithm and the optimized fuzzy clustering algorithm to classify the power battery data.Finally,the classification results were taken as input samples to establish a prediction model of SVM.In order to ensure the accuracy of the model and improve the generalization degree of the model,the cross-validation method is used to optimize the parameters of the training model.The experimental results show that the average prediction accuracy of the proposed model is more than 95%,which meets the actual needs of enterprises.
Battery matching Support vector machines Fuzzy clustering algorithm Adaptive genetic algorithm
Chuanfu Xin Fengxia Zhao Yujin Wu Jianshe Gao
School of Mechanical Engineering,Zhengzhou University,Zhengzhou 450001,China
国际会议
浙江湖州
英文
749-759
2019-08-12（万方平台首次上网日期，不代表论文的发表时间）