Optimal Control Strategy Based on PSO for Powertrain of Parallel Hybrid Electric Vehicle
暂无分享,去创建一个
This paper presents a control strategy based on the multilevel hierarchical control for the powertrain of the parallel hybrid electric vehicle (HEV). The simulation model of this control strategy is constructed by using Matlab/Simulink/Stateflow and is optimized by applying the improved particle swarm optimization (PSO) algorithm. Under the satisfaction with the vehicle dynamic property and the balance of the state of charge of the battery, this control strategy properly determines the direction and quantity of the energy flow in the powertrain of the parallel HEV and makes the engine, the motor and the battery operate efficiently in optimal state in order to minimize the fuel consumption and emissions.
[1] Gregory N. Washington,et al. Development of Fuzzy Logic and Neural Network Control and Advanced Emissions Modeling for Parallel Hybrid Vehicles , 2003 .
[2] Liu Hua-ying. A Modified Particle Swarm Optimization for Solving Constrained Optimization Problems , 2005 .
[3] Riccardo Poli,et al. Particle swarm optimization , 1995, Swarm Intelligence.