Parameters optimization for extended-range electric vehicle based on improved chaotic particle swarm optimization

Abstract

Extended-range electric vehicle is considered to be the ideal transition type for electric vehicle. The optimal operation curve control strategy was proposed for a 12 meter-long range extended electric bus. With exponential function inertia weight adjustment and local chaos substitution, an improved chaotic particle swarm optimization algorithm was applied to optimize the key parameters of energy management strategy. Based on MATLAB/Simulink, full vehicle model and corresponding control strategy were built. The simulation results with typical city driving cycles illustrate that, comparing with standard particle swarm optimization, the new algorithm can greatly improve the convergence speed and optimizing precision, and the optimal parameters can be obtained.