Study on optimization of parallel hybrid electric assist control strategy

Wang Zhenpo, Luo Hao

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The electric assist control strategy for parallel hybrid electric vehicles has been studied on. A simulation model has been built at the aim of minimizing the fuel consumption. The MLPS (Multi-Level Parameter Scanning algorithm, DIRECT (Dividing Rectangle) algorithm and PSO (Particle Swam Optimization) algorithm has been used to optimize the parameters of control strategy. For the PSO algorithm, a novel method has been used to solve the problem with non-linear constraints. The simulation results show that the new PSO algorithm can solve the problem with non-linear constraints well. The simulation results also show that the three kinds of optimization algorithm can reduce fuel consumption significantly. Meanwhile, DIRECT algorithm is better than MLPS and PSO algorithm in optimization of electric parallel hybrid electric assist control strategy.

Original languageEnglish
Title of host publication28th International Electric Vehicle Symposium and Exhibition 2015, EVS 2015
PublisherKorean Society of Automotive Engineers
ISBN (Electronic)9781510809260
Publication statusPublished - 2015
Event28th International Electric Vehicle Exhibition, EVS 2015 - Goyang, Korea, Republic of
Duration: 3 May 20156 May 2015

Publication series

Name28th International Electric Vehicle Symposium and Exhibition 2015, EVS 2015

Conference

Conference28th International Electric Vehicle Exhibition, EVS 2015
Country/TerritoryKorea, Republic of
CityGoyang
Period3/05/156/05/15

Keywords

  • DIRECT
  • Electric assist control strategy
  • Hybrid electric
  • MLPS
  • PSO

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