多因素影响下的纯电动汽车电耗算法优化

doi:10.12068/j.issn.1005-3026.2022.02.011

东北大学学报（自然科学版） ›› 2022, Vol. 43 ›› Issue (2): 228-235.DOI: 10.12068/j.issn.1005-3026.2022.02.011

多因素影响下的纯电动汽车电耗算法优化

李琳辉^1,2，张鑫亮¹，连静^1,2，周雅夫¹

(1. 大连理工大学汽车工程学院，辽宁大连116024；2. 大连理工大学工业装备结构分析国家重点实验室，辽宁大连116024)

修回日期:2021-05-12 接受日期:2021-05-12 发布日期:2022-02-28
通讯作者: 李琳辉
作者简介:李琳辉( 1981-)，男，河南辉县人，大连理工大学副教授，博士生导师；周雅夫(1962-)，男，辽宁铁岭人，大连理工大学教授，博士生导师.
基金资助:
国家重点研发计划项目(2018YFE0105500).

Optimization of Power Consumption Algorithm for Pure Electric Vehicle Under the Influence of Multiple Factors

LI Lin-hui^1,2， ZHANG Xin-liang¹， LIAN Jing^1,2， ZHOU Ya-fu¹

1. School of Automotive Engineering， Dalian University of Technology， Dalian 116024， China; 2. State Key Laboratory of Structural Analysis for Industrial Equipment， Dalian University of Technology， Dalian 116024， China.

Revised:2021-05-12 Accepted:2021-05-12 Published:2022-02-28
Contact: LIAN Jing
About author:-
Supported by:
-

摘要/Abstract

摘要： 针对纯电动汽车的电耗预测问题，提出一种考虑环境温度、电池状态和车速等多因素影响的电耗计算模型.首先，基于自主研发的数据采集装置，采集不同城市的纯电动汽车长期行驶数据，作为模型构建的基础；其次，考虑纯电动汽车实际行驶过程中的温度、电池和车速等因素，结合《中国汽车行驶工况》(CATC-LT)道路行驶标准，提出纯电动汽车行驶百公里的电耗模型；最后，对实际复杂环境中的百公里电耗进行优化.结果表明，在多因素影响的行驶环境中，均方根误差在0.83~4.92区间，平均均方根误差为2.00，比传统算法的均方根误差减少了77.1%.

关键词: 纯电动汽车；电耗；中国汽车行驶工况；环境温度；电池状态

Abstract: Aiming at the problem of power consumption prediction of pure electric vehicles， a power consumption calculation model considering the influence of environmental temperature， battery state and vehicle speed was proposed. Firstly， based on the independently developed data acquisition device， the long-term driving data of pure electric vehicles in different cities were collected as the basis of model construction. Secondly， considering the factors such as temperature， battery and speed in the actual driving process of pure electric vehicles， combined with the road driving standard of China automobile driving conditions(CATC-LT)， the power consumption model of pure electric vehicle traveling 100km was proposed. Finally， the power consumption of 100km in the actual complex environment was optimized. The results show that the root-mean-square error (RMSE) is in the range of 0.83-4.92， and the mean RMSE is 2.00， which is 77.1% lower than the RMSE of the traditional method.

Key words: battery electric vehicles; power consumption; driving conditions in China; environment temperature; battery status

中图分类号:

TH270.14

李琳辉，张鑫亮，连静，周雅夫. 多因素影响下的纯电动汽车电耗算法优化[J]. 东北大学学报（自然科学版）, 2022, 43(2): 228-235.

LI Lin-hui， ZHANG Xin-liang， LIAN Jing， ZHOU Ya-fu. Optimization of Power Consumption Algorithm for Pure Electric Vehicle Under the Influence of Multiple Factors[J]. Journal of Northeastern University(Natural Science), 2022, 43(2): 228-235.

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多因素影响下的纯电动汽车电耗算法优化

Optimization of Power Consumption Algorithm for Pure Electric Vehicle Under the Influence of Multiple Factors

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