采用NSGA-II算法的混合动力能量管理控制多目标优化方法

邓涛; 林椿松; 李亚南; 卢任之

doi:10.7652/xjtuxb201510023

您当前的位置：

首页 >

文章列表页 >

采用NSGA-II算法的混合动力能量管理控制多目标优化方法

更新时间：2025-07-09

- 采用NSGA-II算法的混合动力能量管理控制多目标优化方法
- A Multi-Objective Optimization Method for Energy Management Control of Hybrid Electric Vehicles Using NSGA-II Algorithm
- 西安交通大学学报 2015年49卷第10期页码：143-150
- 作者机构：
  
  重庆交通大学机电与车辆工程学院,重庆,400074
- 作者简介：
- 基金信息：
  
  : 2015-01-28。作者简介: 邓涛(1982—),男,博士,副教授,硕士生导师。基金项目: 国家自然科学基金资助项目(51305473);中国博士后科学基金资助项目(2014M552317);重庆市基础与前沿研究计划项目(cstc2013jcyjA0794);重庆市教委科学技术研究资助项目(KJ120421);重庆市博士后研究人员特别资助项目(xm2014032)
- DOI：10.7652/xjtuxb201510023
  中图分类号： TP18;U469.7
- 网络首发：2015-10-10，
  
  纸质出版：2015
- 稿件说明：
移动端阅览
邓涛, 林椿松, 李亚南, 等. 采用NSGA-II算法的混合动力能量管理控制多目标优化方法[J]. 西安交通大学学报, 2015,49(10):143-150.

A Multi-Objective Optimization Method for Energy Management Control of Hybrid Electric Vehicles Using NSGA-II Algorithm[J]. 2015, 49(10): 143-150.
邓涛, 林椿松, 李亚南, 等. 采用NSGA-II算法的混合动力能量管理控制多目标优化方法[J]. 西安交通大学学报, 2015,49(10):143-150. DOI： 10.7652/xjtuxb201510023.

A Multi-Objective Optimization Method for Energy Management Control of Hybrid Electric Vehicles Using NSGA-II Algorithm[J]. 2015, 49(10): 143-150. DOI： 10.7652/xjtuxb201510023.

摘要

综合考虑燃油经济性、排放性与驾驶性对混合动力能量管理控制优化的优点

以某款并联混合动力汽车为研究对象

选取能量管理控制参数与传动系参数作为待优化参数

以动力性作为约束条件

建立混合动力能量管理控制多目标优化评价方法

提出基于NSGA-II算法的混合动力系统多目标优化方法

并与优化前控制策略进行仿真对比分析。结果表明:在满足基本约束的前提下

优化后燃油经济性最多提高了7.8%

平均提高了6.38%; 驾驶性性能指标最多提高了27.12%

平均提高了21.74%; 排放性综合指标平均提高了41.51%。提出的多目标优化算法具有良好的收敛性与分布性

得到的Pareto最优解集能够给混合动力能量管理控制策略提供更多的权衡选择方案

体现了多目标优化的优势。

Abstract

A multi-objective optimization evaluation method for hybrid electric vehicle(HEV)is proposed by comprehensively considering the influences of fuel economy

emission and drivability on the energy management control for HEV. The multi-objective optimization algorithm based on NSGA-II(non-dominated sorting genetic algorithm-II)is established by setting the parameters of the energy management control and the driveline system as the optimal parameters for the parallel hybrid electric vehicles

and the dynamic performance as the constraint condition. Then the proposed method is comparatively analyzed with the traditional control strategy that only considers the fuel economy. Simulation results show that the maximum fuel economy performance increases by 7.8% and the average value increases by 6.38%; the maximum drivability performance increases by 42.28% and the average value increases by 21.74%; the average synthetic emission performance increases by 41.51%. The proposed multi-objective optimization algorithm has good convergence and distribution. The obtained Pareto optimum solutions may provide more trade-off options for HEV energy management control strategy

which reflect the advantages of multi-objective optimization.

关键词

Keywords

references

张冰战. 插电式混合动力电池汽车能量管理策略研究 [D]. 合肥: 合肥工业大学, 2011.

李翔晟, 陈斗, 周永军. 基于最小瞬时等效燃油消耗的液压混合动力车辆能量管理策略 [J]. 公路交通科技, 2012, 29(12): 148-152.

LI Xiangsheng, CHEN Dou, ZHOU Yongjun. Energy management strategy of hydraulic hybrid vehicle based on instantaneous equivalent fuel consumption minimization [J]. Journal of Highway and Transportation Research and Development, 2012, 29(12): 148-152.

秦大同, 曾育平, 苏岭, 等. 基于近似极小值原理的插电式混合动力汽车实时控制策略 [J]. 机械工程学报, 2015, 51(2): 134-140.

QIN Datong, ZENG Yuping, SU Ling, et al. Plug-in hybrid vehicle's real-time control strategy based on approximate Pontryagin's minimum principle [J]. Journal of Mechanical Engineering, 2015, 51(2): 134-140.

杨亚联, 蒲斌, 胡晓松, 等. ISG型速度耦合混合动力系统全局最优控制方法 [J]. 重庆大学学报, 2013, 36(9): 71-77.

YANG Yalian, PU Bin, HU Xiaosong, et al. Study on global optimization control strategy of ISG velocity coupling hybrid electric vehicle [J]. Journal of Chongqing University, 2013, 36(9): 71-77.

肖仁鑫, 李涛, 邹敢, 等. 基于随机动态规划的混联式混合动力汽车能量管理策略 [J]. 汽车工程, 2013, 35(4): 317-321.

XIAO Renxin, LI Tao, ZOU Gan, et al. Energy management strategy for series-parallel hybrid electric vehicle based on stochastic dynamic programming [J]. Automotive Engineering, 2013, 35(4): 317-321.

PATRICK M W. Plug-in hybrid electric vehicle supervisory control strategy considerations for engine exhaust emissions and fuel use [D]. Blacksbury, VA, USA: Virginia Polytechnic Institute and State University, 2011.

秦大同, 隗寒冰, 段志辉, 等. 重度混合动力汽车油耗和排放多目标实时最优控制 [J]. 机械工程学报, 2012, 48(6): 83-89.

QIN Datong, WEI Hanbing, DUAN Zhihui, et al. Multiple-objective real-time optimum control strategy for fuel consumption and emission of full hybrid electric vehicle [J]. Journal of Mechanical Engineering, 2012, 48(6): 83-89.

PIERRE M, ALAIN C, GUILLAUME C, et al. Energy management of HEV to optimize fuel consumption and pollutant emissions [C]∥Proceedings of 11th International Symposium on Advanced Vehicle Control. Yokohama, Japan: JSAE, 2012: 81-87.

WANG Q, FRANK A A. Plug-in HEV with CVT: configuration, control, and its concurrent multi-objective optimization by evolutionary algorithm [J]. International Journal of Automotive Technology, 2014, 15(1): 103-115.

SHASHI K A, WANG G, AN L Q, et al. Using the Pareto set pursuing multi-objective optimization approach for hybridization of a plug-in hybrid electric vehicle [J]. Journal of Mechanical Design, 2012, 134(9): 503-509.

GALVAGNO E, MORINA D, SORNIOTTI A, et al. Drivability analysis of through-the-road-parallel hybrid vehicles [J]. Mechanical, 2013, 48(2): 351-366.

岳明玥, 周一丹, 马改. 深度混合动力汽车NVH问题的研究进展 [J]. 机械设计与制造, 2015(2): 268-271.

YUE Mingyue, ZHOU Yidan, MA Gai. Research progress on deep hybrid vehicle NVH problem [J]. Machinery Design Manufacture, 2015(2): 268-271.

郑宏宇, 王琳琳, 赵伟强, 等. 基于电控制动系统的客车制动力分配控制策略 [J]. 吉林大学学报: 工学版, 2015, 45(2): 347-351.ZHENG Hongyu, WANG Linlin, ZHAO Weiqiang, et al. Braking force distribution control strategy of bus based on electronically controlled braking system [J]. Journal of Jilin University: Engineering and Technology Edition, 2015, 45(2): 347-351.

DANIEL F O, WANG X Y, RYAN M, et al. An energy management controller to optimally trade off fuel economy and drivability for hybrid vehicles [J]. IEEE Transactions on Control Systems Technology, 2012, 20(6): 1490-1505.

宋康, 陈潇凯, 林逸. 汽车行驶动力学性能的多目标优化 [J]. 吉林大学学报: 工学版, 2015, 45(2): 352-357.

SONG Kang, CHEN Xiaokai, LIN Yi. Multi objective optimization of vehicle dynamic behaviors [J]. Journal of Jilin University: Engineering and Technology Edition, 2015, 45(2): 352-357.

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

采用改进多目标粒子群算法的海岛综合能源系统优化调度

面向边缘端工业微服务部署的多目标白鲨优化算法

带锥形孔的矩阵冷却通道流动换热多目标优化

大型可展开网状天线展开过程仿真建模与竖向索预拉力优化调控

采用改进多目标粒子群算法的海岛综合能源系统优化调度