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LIU Xu-dong, FAN Qing-wu, DUAN Jian-min, ZHOU Da-sen. Optimization of HEV System Parameters Based on Hybrid Adaptive Genetic Algorithm[J]. Journal of Beijing University of Technology, 2009, 35(7): 904-909. DOI: 10.3969/j.issn.0254-0037.2009.07.008
Citation: LIU Xu-dong, FAN Qing-wu, DUAN Jian-min, ZHOU Da-sen. Optimization of HEV System Parameters Based on Hybrid Adaptive Genetic Algorithm[J]. Journal of Beijing University of Technology, 2009, 35(7): 904-909. DOI: 10.3969/j.issn.0254-0037.2009.07.008
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Optimization of HEV System Parameters Based on Hybrid Adaptive Genetic Algorithm

  • 1. The Pilot College of Beijing University of Technology, Beijing 101101, China;

  • 2. College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China

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  • Received Date: February 20, 2008
  • Available Online: December 09, 2022
    Graphical Abstract
    • Abstract
  • Selecting optimization algorithm is an important part in the optimization of HEV system parameters.To overcome the shortcomings of prematurity and slow convergence speed in simple genetic algorithm, a hybrid adaptive genetic algorithm is proposed.Testing results show that the proposed algorithm has both good whole astringency and fast convergence speed.The new hybrid adaptive genetic algorithm is applied to the optimization of HEV system parameters and satisfactory optimization results and convergence effects are obtained.Based on the optimization results, an engine/generator set of a series hybrid electric mini-bus is designed optimally.
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    • References (10)
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