Energy Management Strategy for Range-Extended Electric Vehicles Based on Improved Particle Swarm Optimization
To improve the overall performance of range-extended electric vehicles(REEV),a multi-point en-ergy management strategy utilizing an enhanced Particle Swarm Optimization(PSO)algorithm is proposed.The vehicle system simulation model and energy management strategy are developed using AVL-Cruise and Matlab/Simulink.An improved PSO algorithm is employed to construct a multi-objective optimization model,targeting fuel economy,emissions,and generator energy conversion loss rate under cycle conditions,with the engine operat-ing point as the optimization variable.Offline optimization provides Pareto optimal solutions for engine operating points across various cycle conditions.The enhanced PSO algorithm shows better population solution precision and optimization capability compared to the traditional PSO algorithm.The proposed multi-point energy management strategy based on this improved PSO algorithm achieves a 16.4％improvement in overall performance compared to conventional strategies.Furthermore,it shows a notable enhancement of 33.3％and 26.5％in performance compared to thermostat and power-following energy management strategies,respectively.
range-extended electric vehiclesrange extenderenergy managementparticle swarm optimizationcomprehensive evaluation index
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