Optimal Energy Management for Series-Parallel Hybrid Electric City Bus Based on Improved Genetic Algorithm

  • Bingzhan ZHANG Hefei University of Technology, School of Automotive and Traffic Engineering, Hefei
  • Guodong ZHAO Hefei University of Technology, School of Automotive and Traffic Engineering
  • Yong HUANG Hefei University of Technology, AnHui Key Laboratory of Digit Design and Manufacture, Hefei
  • Yaoyao NI Hefei University of Technology, School of Automotive and Traffic Engineering, Hefei
  • Mingming QIU Hefei University of Technology, School of Mechanical Engineering, Hefei

Abstract

This paper aims at proposing an efficient energy management strategy of the series-parallel hybrid electric bus (SPHEB) by using improved genetic algorithm. Firstly, the energy management strategy based on the logical threshold value is developed. The simulation model considering the vehicle dynamic performance is established by the combination of Matlab and Cruise software. Then, an improved genetic algorithm based on adaptive crossover probability and mutation probability is proposed to solve local convergence and premature convergence. Eventually, Chinese typical city bus driving cycle and the composite driving cycle are considered to show the effectiveness of the proposed energy management strategy in terms of the fuel economy. The results indicate that the fuel consumption are improved by 5.85% and 5.01% respectively, and the parameters obtained by optimizing for the composite driving cycle are more adaptable to the driving conditions and have better economic performance in all driving scenarios.

Published
2020-06-18
Section
MECHANICAL TECHNOLOGIES