|本期目录/Table of Contents|

[1]周美兰,张宇,杨子发,等.带压缩因子粒子群优化的混合动力汽车模糊能量管理策略[J].电机与控制学报,2011,(11):67-72.
 ZHOU Mei-lan,ZHANG Yu,YANG Zi-fa,et al.Fuzzy energy management strategy for HEV based on particle swarm optimization with compressibility factor[J].,2011,(11):67-72.
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带压缩因子粒子群优化的混合动力汽车模糊能量管理策略(PDF)
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《电机与控制学报》[ISSN:1007-449X/CN:23-1 408/TM]

卷:
期数:
2011年11
页码:
67-72
栏目:
出版日期:
2011-11-20

文章信息/Info

Title:
Fuzzy energy management strategy for HEV based on particle swarm optimization with compressibility factor
作者:
周美兰; 张宇; 杨子发; 康娣;
哈尔滨理工大学电气与电子工程学院; 哈尔滨哈飞汽车工业集团有限公司研发中心;
Author(s):
ZHOU Mei-lan1ZHANG Yu1YANG Zi-fa2KANG Di1
1.School of Electrical and Electronic Engineering,Harbin University of Science and Technology,Harbin 150080,China; 2.R & D Center,Harbin Hafei Automobile Industry Group Co.,Ltd.,Harbin 150060,China
关键词:
混合动力汽车 能量管理 模糊控制 压缩因子 粒子群优化
Keywords:
hybrid electric vehicle energy management fuzzy control compressibility factor particle swarm optimization
分类号:
U469.7
DOI:
-
文献标志码:
A
摘要:
针对改装后的哈飞赛豹混合动力汽车,以混合驱动系统需求转矩和电池组荷电状态(SOC)为输入,以发动机转矩为输出,应用带压缩因子粒子群算法优化量化因子的方法构建了能量管理模糊控制器,克服了传统的模糊控制存在精确度不高、自适应能力有限等问题,使模糊控制器的鲁棒性和控制精确度都得到提高。基于混合动力汽车专用仿真软件的研究表明,经过优化的模糊能量管理策略与未优化的策略相比燃油经济性提高了14.19%;优化前蓄电池的回收效率分别为18.95%、23.95%和14.47%,而优化后的分别提高至29.37%、26.20%、和20.12%;尾气中NOX、CO、HC由优化前0.202 g/km1、.1 g/km和0.282 g/km分别降至0.104 g/km0、.46 g/km和0.279 g/km。
Abstract:
Aiming at the refit HAFEI hybrid electric vehicle(HEV),a fuzzy controller of energy management is constructed based on particle swarm optimization(PSO) with compressibility factor,which using the system torque request and the battery state of charge(SOC) as inputs,and the engine torque as the output.In this way,the problems of the low precision and limited adaptive capability in conventional fuzzy control are overcome,and the robustness and control accuracy of fuzzy controller are improved.The s...

参考文献/References:

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备注/Memo

备注/Memo:
黑龙江省教育厅科学技术研究项目(11551072)
更新日期/Last Update: 2012-04-11