中国电机工程学报2024，Vol.44Issue(6)：2330-2339,后插21,11.DOI:10.13334/j.0258-8013.pcsee.221789
一种基于GRU的氢燃料重卡汽车工况下锂离子电池温度预测模型
A GRU Based Temperature Prediction Model of Lithium-ion Battery for Hydrogen Fuel Heavy Truck Under Operating Conditions
摘要
Abstract
Addressing the complexities of power battery conditions,unpredictable surface temperature changes,and significant time lags encountered during the operation of heavy hydrogen fuel cards,this study focuses on the outside surface temperature of lithium-ion power batteries as the primary research target.To this end,an enhanced gate recurrent unit(GRU)neural network is proposed,optimized through the integration of a cross-entropy loss function and adaptive moment estimation(Adam).This approach establishes a surface temperature prediction model for lithium-ion power batteries,aiming to improve the accuracy and reliability of temperature predictions.The model uses the special gate mechanism and global processing ability of GRU neural network to obtain the nonlinear relationship between the surface temperature of lithium-ion battery and battery charging and discharging current,voltage,charging and discharging time,historical temperature,current temperature and ambient temperature.In this paper,four accuracy evaluation functions are used to evaluate the prediction model.The accuracy of the model is verified by simulation experiments under five ambient temperatures.The results show that the error of battery temperature prediction model based on GRU is relatively small compared with back propagation(BP)neural network model and recurrent neural network(RNN)neural network model,which indicates that the temperature prediction model of lithium-ion battery based on GRU has higher accuracy.This paper presents a new method for accurately predicting the surface temperature of lithium-ion phosphate battery.关键词
氢燃料重卡/锂离子电池/温度预测模型/门控循环单元神经网络/深度学习Key words
hydrogen fuel heavy truck/lithium-ion batteries/temperature prediction model/gated recurrent neural network/deep learning分类
交通工程引用本文复制引用
闫志远,孙桓五,刘世闯,赵立禹..一种基于GRU的氢燃料重卡汽车工况下锂离子电池温度预测模型[J].中国电机工程学报,2024,44(6):2330-2339,后插21,11.基金项目
山西省科技重大专项项目(20181102009).Major Special Project of Science and Technology in Shanxi Province(20181102009). （20181102009）
