Energy Control of HEV Based on Fuzzy Controller Optimized by Particle Swarm Optimization

Abstract

Energy control of HEV plays a very important role in the process of HEV design, which is directly related to the safety and feasibility. Considering the drive system of HEV is nonlinear and complex, a fuzzy control strategy which is combined with particle swarm optimization algorithm is designed to realize the energy control of HEV. Fuzzy control strategy does not need to built accuracy mathematics model and has good robustness, but it mostly depends on engineering experience and has poor ability of self-learning. So particle swarm optimization algorithm has been added to solve these disadvantages of fuzzy control strategy. In conclusion, this method can not only keep the advantage of fuzzy control strategy, but also has ability of self-learning and self-adapt because of particle swarm optimization added. And the simulation proves that this method is feasible and effective.

A Single-Degree-of-Freedom Energy Optimization Strategy for Power-Split Hybrid Electric Vehicles

“…The genetic algorithm (GA) [17,18] is time-consuming due to the fact that it must complete a series of actions including crossover, mutation and elite selection. The particle swarm optimization strategy [19,20] provides a suboptimal solution and it will be not effective when the solution parameters are highly related.…”