Research on Intelligent Adaptive Energy Management Strategy for Range-Extended Electric Vehicles Based on Vehicle Driving Conditions

This paper takes a certain range-extended hybrid vehicle as the research object and proposes an intelligent adaptive energy management strategy based on vehicle driving conditions. Firstly, the vehicle driving conditions are processed, principal component analysis and cluster analysis are carried out to establish an LVQ operating condition recognition neural network model. Based on the operating condition recognition results, an intelligent adaptive strategy is established to dynamically adjust the equivalent factor and engine start-stop conditions based on the ECMS strategy. characteristics of the operating conditions are integrated to further optimize the equivalent factor; a vehicle and strategy model is built in Simulink for simulation verification. The simulation results show that compared with the power-following strategy, the equivalent fuel consumption of the established adaptive energy management strategy is reduced by 5.08% under the selected comprehensive urban operating conditions.