Fitness inheritance-based evolutionary algorithm and its application in hybrid electric vehicle design

Zhao Li, Wan Ke Cao*, Yu Tao He

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

In this paper, we present a Fitness Inheritance-Based Evolutionary Algorithm (FIEA) for optimisation of component size and control parameters in designing a Hybrid Electric Vehicle (HEV). FIEA is an intelligent optimisation tool for adjusting the component size and the control strategy parameters to minimise the weighted sum of fuel consumption (FC) and emissions. In this paper, the simulation tool ADVISOR and the driving cycles FTP, ECE-EUDC, and UDDS were used to evaluate FC, emission and dynamic performance. The experimental results show that the FIEA algorithm is a powerful tool in optimising a parallel HEV. At the same time, FC and the emissions can be improved clearly while the performance of the vehicle is not sacrificed.

Original languageEnglish
Pages (from-to)180-186
Number of pages7
JournalInternational Journal of Wireless and Mobile Computing
Volume7
Issue number2
DOIs
Publication statusPublished - 2014

Keywords

  • Driving cycles
  • Fitness inheritance
  • Fuel consumption
  • HEV
  • Hybrid electric vehicle

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