Energy Management of Planetary Gear Hybrid Electric Vehicle Based on Improved Dynamic Programming

被引：1
|
作者：
Tang, Xin [1 ]
Chu, Liang [1 ]
Xu, Nan [1 ]
Zhao, Di [1 ]
Xu, Zhe [2 ]
机构：
[1] Jilin Univ, State Key Lab Automot Simulat & Control, Changchun 130022, Peoples R China
[2] China FAW Grp Corp, R&D Ctr, Changchun 130011, Peoples R China
来源：
NEURAL INFORMATION PROCESSING (ICONIP 2017), PT VI | 2017年 / 10639卷
关键词：
Energy management; Dynamic programming algorithm; Optimal trajectories; HEV; POWER MANAGEMENT; OPTIMIZATION;
D O I：
10.1007/978-3-319-70136-3_14
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Dynamic Programming (DP) is often used in hybrid electric vehicle (HEV) energy management strategies to optimize fuel economy performance. When using the DP algorithm to find the optimal State of Charge (SOC) trajectory, we found that the optimal SOC trajectory is more than one. However, the traditional DP algorithm can just show one optimal path from masses of optimal SOC trajectories. In this paper, we proposed an improved DP algorithm to find a region which is made up of many optimal trajectories. Planetary gear hybrid electric vehicles as a research object in this paper and obtained the better fuel economy by the proposed algorithm with a lower computational complexity. At the same time, this method can offer the possibility for the further optimization of the vehicle ride comfort in the future.
引用
收藏
页码：130 / 138
页数：9
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