Title: Fitness inheritance-based evolutionary algorithm and its application in hybrid electric vehicle design
Authors: Li Zhao; Wan-Ke Cao; Yu-Tao He
National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 10081, China; Shijiazhuang Vocational Technology Institute, Shijiazhuang 050081, China
National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 10081, China
Shijiazhuang University, Shijiazhuang 050000, China
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.
Keywords: fitness inheritance; HEVs; hybrid electric vehicles; driving cycles; fuel consumption; evolutionary algorithms; hybrid vehicles; vehicle design; intelligent optimisation; component size; control strategy; vehicle emissions; simulation; vehicle performance.
Int. J. of Wireless and Mobile Computing, 2014 Vol.7, No.2, pp.180 - 186
Submission date: 04 Jun 2013
Date of acceptance: 25 Jul 2013
Available online: 06 Mar 2014