Research on Parallel Hybrid Electric Vehicle Control Strategy and GA Optimization

摘要

In this paper, based on the deterministic rule-based control strategy, controller parameters are optimized by genetic algorithms for parallel hybrid electric vehicle. Compared with previous results, this approach can effectively reduce fuel consumption and emissions without sacrificing vehicle performance. Additionally, the contrast experiments between this approach and fuzzy control strategy have also been done. The fuel consumption and emissions of fuzzy control strategy is better than that of optimized deterministic rule-based control strategy. Because the deterministic rule-based control strategy can keep the battery constantly charging or discharging and the motor often work, the fuzzy control strategy often makes the engine work in high efficiency areas or low-emission zones, so it is worse than deterministic rule-based control strategy in terms of vehicle performance.