An optimal energy consumption calculation method of hybrid electric vehicles with frequency distribution characteristics of driving conditions

被引:0
|
作者
Zeng, Xiaohua [1 ]
Li, Jingjing [1 ,2 ]
Duan, Chaosheng [1 ]
Huang, Yufeng [1 ]
Song, Dafeng [1 ,2 ]
机构
[1] Jilin Univ, Natl Key Lab Automot Chassis Integrat & Bion, 5988 Renmin St, Changchun 130025, Jilin Province, Peoples R China
[2] Jilin Univ, Coll Automot Engn, Changchun 130025, Peoples R China
基金
中国国家自然科学基金;
关键词
Hybrid power system; Driving condition information; Frequency distribution characteristics; Optimal energy consumption; Computational efficiency;
D O I
10.1016/j.seta.2024.104083
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
For a series of problems in the design and optimisation of series hybrid electric vehicles caused by the driving condition input, such as a variety of user conditions, which may hinder the energy-saving ability of such vehicles. Condition construction will inevitably lead to information loss, and traditional design methods require high computational power and encounter a time disaster during the real-world condition data explosion. This study proposes a condition representation method with driving condition frequency distribution characteristics (DCFDCs) and an optimal energy consumption calculation method, that is, instantaneous battery energy balance solution and global battery energy balance correction (IBGB-GBEB) with DCFDCs. The energy consumption calculation results show that the proposed optimal energy consumption method can guarantee the accuracy of the energy consumption calculation and reduce the calculation time cost. The difference in fuel consumption between the optimal energy consumption method and the dynamic planning (DP) algorithm is only 2.50%, but the difference in the calculation time between the two methods is 87.00%. Furthermore, the practical example of hybrid power system (HPS) design parameter optimisation shows that the energy consumption calculation results obtained by the TDCR-DP and DCFDCs-MIGA methods are consistent, and the relative error is only 1.81%. However, the calculation time of the TDCR-DP method is 472 h, whereas that of the DCFDC-MIGA method is only 2.17 h, which is a calculation time reduction of more than 99.54%. The results highlight the effectiveness and time advantage of the optimal energy consumption calculation method with DCFDCs. This study can provide theoretical guidance and technical support for solving system optimisation problems caused by the explosion of driving condition data.
引用
收藏
页数:17
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