A new real-time optimal energy management strategy for range extended electric vehicles considering battery degradation and engine start-up

Abstract

Range extended electric vehicles (REEVs) offer a solution to the limited range of pure electric vehicles by incorporating an additional energy source. Effectively managing the output power among these energy sources is the key to reduce operating cost. To enhance the economy of REEVs, this paper proposes a multi-objective optimal energy management strategy (MOEMS) that considers battery degradation. The powertrain of the REEV is comprehensively modeled by integrating the efficiency of the range extender, battery, and driving motor. MOEMS is designed to instantaneously minimize the total operating cost of the vehicle, including factors such as fuel consumption, electricity consumption, and battery degradation. To minimize the frequency of engine starts and stops, the cost associated with engine startup is integrated into the objective function. Two control coefficients are introduced into the objective function to regulate the battery state of charge. Additionally, another coefficient is employed to restrict variations of engine output power, thereby avoiding significant fluctuations of engine load. Simulation results show that compared to the adaptive equivalent consumption minimization strategy (AECMS) and rule-based energy management strategy (REMS), the total cost of MOEMS is reduced by 9.1% and 32.3% in WLTC driving cycles, and by 7.9% and 31.7% in CLTC driving cycles.