Energy management strategy of connected hybrid electric vehicles considering electricity and oil price fluctuations: A case study of ten typical cities in China

Abstract

Energy management strategy (EMS) plays an important role in improving energy economy of plug-in hybrid electric vehicles (PHEVs). The frequently fluctuations of electricity and oil prices have significant impacts on EMS optimization. In this study, the influence law of the varying prices on the optimal control policy is revealed. The statistical analysis of electricity and fuel prices for typical cities in China is proposed as a case study, and then a varying prices-conscious EMS for PHEVs is developed. The presented control strategy is optimized based on the simulated annealing particle swarm optimization (SA-PSO) algorithm. Taking into account the above efforts, the price influence surfaces (PIS) are proposed and a PIS-based adaptive EMS is finally established. The presented control strategy can achieve better energy economy under real-world driving condition than traditional EMS that doesn't concern the impacts of price variations. The results indicate that the energy cost of PHEV can be further reduced by up to 9.88% under certain driving situations.