Research on equivalent fuel consumption minimisation strategy design and optimisation for a plug-in hybrid electric vehicle. (24th September 2020)

• Record Type: Journal Article
• Authors: Guo, Huan; Deng, Weishun; Yu, Fan
• Is Part Of: International journal of electric and hybrid vehicles. Volume 12:Number 3(2020)
• Page Start: 185
• Page End: 196
• Publication Date: 2020-09-24
• Subjects: PHEV -- plug-in hybrid electric vehicle -- charge sustaining -- energy management strategy -- IGA -- improved genetic algorithm -- fuel economy -- elite retention strategy -- TGA -- traditional genetic algorithm -- hardware-in-the-loop -- state of charge; Electric vehicles -- Periodicals; 629.229305
• Languages: English
• ISSNs: 1751-4088

Abstract

In this paper, equivalent fuel consumption minimisation strategy (ECMS) based on the optimal fuel economy is proposed and optimised for the Charge Sustaining (CS) period of a plug-in hybrid electric vehicle (PHEV). To overcome the disadvantages of low convergence rate and insufficient population evolution, the crossover probability and mutation probability of the traditional genetic algorithm (TGA) are improved to be varied along with the iteration and fitness value. Meanwhile, elite retention strategy is adopted to avoid the population degradation. Fuel equivalent factor is then optimised by improved genetic algorithm (IGA) to obtain the optimal fuel economy. Corresponding hardware-in-the-loop (HIL) simulations are carried out to verify the effectiveness and rationality of the strategy optimised by IGA. The results indicate that within allowable deviation of the state of charge (SOC), the PHEV can obtain better fuel economy combining the proposed method.