采用NSGA-II算法的车载复合电源参数匹配

doi:10.13229/j.cnki.jdxbgxb201705002

吉林大学学报(工学版) ›› 2017, Vol. 47 ›› Issue (5): 1336-1343.doi: 10.13229/j.cnki.jdxbgxb201705002

采用NSGA-II算法的车载复合电源参数匹配

周放¹, 宋传学¹, 梁天唯², 肖峰¹

1.吉林大学汽车仿真与控制国家重点实验室,长春 130022;
2.吉林大学机械科学与工程学院,长春 130022

收稿日期:2016-08-24 出版日期:2017-09-20 发布日期:2017-09-20
通讯作者: 肖峰(1986-),男,助理研究员,博士.研究方向:汽车系统动力学.E-mail:xiaofeng4206@126.com
作者简介:周放(1988-),男,博士研究生.研究方向:车载复合电源关键技术.E-mail:zhoufang13@mails.jlu.edu.cn
基金资助:
吉林省科技重点攻关项目(20150204017GX)

Parameter matching of on-board hybrid energy storage system using NSGA-II algorithm

ZHOU Fang¹, SONG Chuan-xue¹, LIANG Tian-wei², XIAO Feng¹

1.State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China;
2.College of Mechanical Science and Engineering, Jilin University, Changchun 130022, China

Received:2016-08-24 Online:2017-09-20 Published:2017-09-20

摘要/Abstract

摘要： 提出了一种主动并联式车载复合电源的参数匹配/能量管理联合优化方法。首先,根据整车性能指标确定电池组和超级电容组的容量范围,并针对部件性能制定能量管理策略,然后,以复合电源替换成本和日均电耗最小为目标建立多目标优化函数,采用受控精英多目标遗传算法(Controlled elitist NSGA-II)在不同的日均里程下对复合电源参数和能量管理策略同时进行优化,得到对应的Pareto解集,作为备选。综合考虑备选集的初始成本、百公里总成本和电池组寿命里程,优选电池组和超级电容组参数。优化结果表明:日均里程在48 km以内时,匹配22 kW·h电池组,超过48 km后,里程越大,匹配电池组容量越大;在不同的日均里程下,不同容量的电池组匹配一个60 W·h左右的超级电容组可以达到综合性能最优。与电池单独优化相比,电源替换成本平均降低11.5 %,寿命里程平均提高19.8 %,日均总成本平均降低13.2 %。

关键词: 车辆工程, 复合电源, 受控精英多目标遗传算法, 替换成本, 多目标优化

Abstract: An integrated parameter matching/energy management optimization method is proposed for active on-board Hybrid Energy Storage System (HESS). The optimization model with two indicators, HESS replacement costs and energy consumption, was set up and solved using controlled elitist NSGA-Ⅱalgorithm to obtain Pareto sets as alternatives. After comparing the initial cost, daily total cost and battery pack mileage of lifetime of the alternatives, HESS parameters and corresponding energy management were selected. When the daily range is within 48 km, the optimal battery pack capacity is 22 kW·h, when the daily range exceeds 48 km, the optimal battery pack capacity increases with the daily range. An ultracapacitor pack around 60 W·h is adequate for various daily range. Compared with the optimization results of battery only, using the proposed optimization method, the replacement cost is reduced by 11.5% in average, the battery pack mileage of lifetime is raised by 19.8% in average, the daily total cost is reduced by 13.2%. The proposed optimization method ensures that the main indicators are optimal and the secondary indicators are satisfactory.

Key words: vehicle engineering, hybrid energy storage system(HESS), controlled elitist NSGA-II, replacement cost, multi-objective optimization

中图分类号:

U461.8

周放, 宋传学, 梁天唯, 肖峰. 采用NSGA-II算法的车载复合电源参数匹配[J]. 吉林大学学报(工学版), 2017, 47(5): 1336-1343.

ZHOU Fang, SONG Chuan-xue, LIANG Tian-wei, XIAO Feng. Parameter matching of on-board hybrid energy storage system using NSGA-II algorithm[J]. 吉林大学学报(工学版), 2017, 47(5): 1336-1343.

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采用NSGA-II算法的车载复合电源参数匹配

Parameter matching of on-board hybrid energy storage system using NSGA-II algorithm

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