Research and optimization of energy management strategies for range-extended electric vehicles

Aiming at the problem of energy management of range-extended electric vehicles, this paper first analyzes the structural char-acteristics of range-extended electric vehicles, and then comprehensively considers the operating conditions of range-extended electric vehicles, and proposes a multi-parameter energy management control strategy. The effectiveness of the control strategy is verified by simulation. Finally, the control parameters are optimized by the multi-objective genetic optimization algorithm (NSGA-II). The optimization results show that the fuel consumption per 100 kilometers of the vehicle is reduced by 5.2% under the premise of meeting the driving range requirements. NOx emissions remained largely unchanged, but CO-emissions were reduced by 2.5% and HC emissions decreased by 2%. The economy of the whole vehicle has been improved to a certain extent.