Blended Energy Management Strategy of Plug-in Hybrid Electric Vehicles Based on the Influences of Driving Cycles

Zhenzhen Lei, Pan Zhao, Dongye Sun, Jie Li

Abstract


The adaptability and computational load of blended energy management strategy of plug-in hybrid electric vehicles (PHEV) based on optimization algorithm limit its wide application. In this paper, a blended energy management strategy of PHEV based on the influences of driving cycles is proposed to improve fuel economy. This strategy first uses dynamic programming to analyze the influence of driving cycles and driving distance on optimal control, and formulates real-time control rules based on genetic algorithm optimization. Then different driving cycles is globally optimized, optimal control strategies under different driving distance coefficients is extracted and the strategy in real time according to the acquired information is adjusted. The simulation results show that the proposed strategy can effectively ensure the adaptability and real-time performance of PHEV, and the fuel economy is 11.37%~14.8% higher than the CD-CS strategy under different SOC initial values.

Keywords


plug-in hybrid electric vehicle, real-timeenergy management strategy, global optimization, driving cycle adaptability, fuel economy


DOI
10.12783/dteees/iceee2018/27837

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