Acceleration Velocity Trajectory Optimization of Intelligent EVs Using Battery Life Model

被引：1
|
作者：
Chu, Hong [1 ]
Zheng, Qing [1 ]
Guo, Lulu [1 ,2 ]
Gao, Bingzhao [1 ]
机构：
[1] Jilin Univ, State Key Lab Automot Simulat & Control, Changchun, Jilin, Peoples R China
[2] Jilin Univ, Dept Control Sci & Engn, Changchun, Jilin, Peoples R China
来源：
IFAC PAPERSONLINE | 2018年 / 51卷 / 31期
基金：
国家重点研发计划;
关键词：
Intelligent EVs; lithium-ion battery; control-oriented life model; velocity trajectory optimization;
D O I：
10.1016/j.ifacol.2018.10.051
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, taking an intelligent electric vehicle as the research object, mathematical models are firstly built for calculating the percentage of lithium-ion battery capacity loss and the internal resistance increase. Based on the model established, a control-oriented battery life model is derived using to calculate the battery capacity loss during an acceleration process. Then, a velocity trajectory optimization framework is presented to minimize the battery aging life for intelligent EVs during an acceleration process and the problem is solved by SQP algorithm. Finally, according to the simulation results, it can be concluded that the energy consumption per meter is 5.50kJ/m from 0 to 100km/h within 10s. The effect on battery capacity is much greater than that on battery internal resistance during the acceleration process. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
引用
收藏
页码：285 / 289
页数：5
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