원문정보
초록
영어
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.
목차
1. Introduction
2. E-REV Energy Management Control Strategy
2.1. Power-Train System Structure
2.2. Optimal Operation Curve Control Strategy
3. Improved Chaotic Particle Swarm Optimization (ICPSO) Algorithm
3.1. Chaotic Mapping
3.2. Exponential Function Inertia Weight Adjustment Strategy
3.3. Local Chaos Substitution
4. Parameters Optimization based on ICPSO Algorithm
4.1. Optimization Objective
4.2. Parameters Optimization
5. Simulation and Result Analysis
6. Conclusions
Acknowledgements
References