湖北汽车工业学院学报2025，Vol.39Issue(1)：28-32,39,6.DOI:10.3969/j.issn.1008-5483.2025.01.006
基于LSTM的电动汽车剩余续驶里程预测
Prediction of Remaining Driving Range of Electric Vehicles Based on LSTM
摘要
Abstract
Based on the LSTM neural network and real vehicle operation data,the research was carried out on the prediction of the remaining driving range of electric vehicles.The raw data were processed by moving average and assignment filling.Through Pearson correlation analysis,three characteristic pa-rameters of total voltage,current remaining power,and its difference from the end-of-discharge capaci-ty were selected.Additionally,four characteristic parameters of power,power change rate,vehicle speed,and acceleration were added.These parameters were respectively put into the model for predict-ing the remaining driving range and comparative analysis,with validation performed on driving seg-ments.The results show that the seven characteristic parameters exhibit an overall small error and rela-tively good performance.关键词
LSTM神经网络/电动汽车/剩余续驶里程Key words
LSTM neural network/electric vehicle/remaining driving range分类
交通运输引用本文复制引用
王焕焕,赵慧勇..基于LSTM的电动汽车剩余续驶里程预测[J].湖北汽车工业学院学报,2025,39(1):28-32,39,6.基金项目
汽车零部件技术湖北省协同创新项目(2015XTZX0403) （2015XTZX0403）
湖北汽车工业学院博士科研启动基金(BK201410) （BK201410）
