Multi-objective Optimization for Hybrid Power System based on the Differential Evolution Algorithm

Considering the disadvantages of energy management multi- objectives optimization for hybrid electric vehicle( HEV) which usually adopts weighted sum method,by using the Pareto optimum algorithm,based on non- dominated sorting method to deal with the fuel economy and emissions( CO,NOxand HC) evaluat...

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Main Authors: Deng Tao, Lin Chunsong, Li Ya’nan, Lu Renzhi
Format: Article
Language:zho
Published: Editorial Office of Journal of Mechanical Transmission 2016-01-01
Series:Jixie chuandong
Subjects:
Online Access:http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2016.10.015
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author Deng Tao
Lin Chunsong
Li Ya’nan
Lu Renzhi
author_facet Deng Tao
Lin Chunsong
Li Ya’nan
Lu Renzhi
author_sort Deng Tao
collection DOAJ
description Considering the disadvantages of energy management multi- objectives optimization for hybrid electric vehicle( HEV) which usually adopts weighted sum method,by using the Pareto optimum algorithm,based on non- dominated sorting method to deal with the fuel economy and emissions( CO,NOxand HC) evaluation indexes,then a new adaptive differential evolution algorithm is proposed and simulated which can be applied to multi- objective optimization of HEV energy management. The simulation results show that,a Pareto optimal solution set can be obtained by the proposed multi- objectives optimization method. And the maximum fuel economy increases by 5. 30%,the largest CO emissions reduces by 3. 65%,in the biggest NOxfalls by 14.40%,the max HC drops down by 3.26%.
format Article
id doaj-art-30f7daa1466744c78d5877afedf6aa6c
institution Kabale University
issn 1004-2539
language zho
publishDate 2016-01-01
publisher Editorial Office of Journal of Mechanical Transmission
record_format Article
series Jixie chuandong
spelling doaj-art-30f7daa1466744c78d5877afedf6aa6c2025-01-10T14:15:19ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392016-01-0140808429926485Multi-objective Optimization for Hybrid Power System based on the Differential Evolution AlgorithmDeng TaoLin ChunsongLi Ya’nanLu RenzhiConsidering the disadvantages of energy management multi- objectives optimization for hybrid electric vehicle( HEV) which usually adopts weighted sum method,by using the Pareto optimum algorithm,based on non- dominated sorting method to deal with the fuel economy and emissions( CO,NOxand HC) evaluation indexes,then a new adaptive differential evolution algorithm is proposed and simulated which can be applied to multi- objective optimization of HEV energy management. The simulation results show that,a Pareto optimal solution set can be obtained by the proposed multi- objectives optimization method. And the maximum fuel economy increases by 5. 30%,the largest CO emissions reduces by 3. 65%,in the biggest NOxfalls by 14.40%,the max HC drops down by 3.26%.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2016.10.015Hybrid powerMulti-objective optimizationNon-dominated sortingAdaptive differential evolution algorithmEnergy management
spellingShingle Deng Tao
Lin Chunsong
Li Ya’nan
Lu Renzhi
Multi-objective Optimization for Hybrid Power System based on the Differential Evolution Algorithm
Jixie chuandong
Hybrid power
Multi-objective optimization
Non-dominated sorting
Adaptive differential evolution algorithm
Energy management
title Multi-objective Optimization for Hybrid Power System based on the Differential Evolution Algorithm
title_full Multi-objective Optimization for Hybrid Power System based on the Differential Evolution Algorithm
title_fullStr Multi-objective Optimization for Hybrid Power System based on the Differential Evolution Algorithm
title_full_unstemmed Multi-objective Optimization for Hybrid Power System based on the Differential Evolution Algorithm
title_short Multi-objective Optimization for Hybrid Power System based on the Differential Evolution Algorithm
title_sort multi objective optimization for hybrid power system based on the differential evolution algorithm
topic Hybrid power
Multi-objective optimization
Non-dominated sorting
Adaptive differential evolution algorithm
Energy management
url http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2016.10.015
work_keys_str_mv AT dengtao multiobjectiveoptimizationforhybridpowersystembasedonthedifferentialevolutionalgorithm
AT linchunsong multiobjectiveoptimizationforhybridpowersystembasedonthedifferentialevolutionalgorithm
AT liyanan multiobjectiveoptimizationforhybridpowersystembasedonthedifferentialevolutionalgorithm
AT lurenzhi multiobjectiveoptimizationforhybridpowersystembasedonthedifferentialevolutionalgorithm