结合遗传算法的群体进化和模拟退火算法可避免迂回搜索的特点,在多目标遗传优化方法的基础上,引入混合优化算法,对HEV能量管理控制参数进行了优化.结果表明,所提出的混合优化算法在解决HEV控制策略多目标优化问题中,避免了传统遗传优化早熟收敛和无方向性等缺点,提高了收敛速度和计算效率.%Combining the features of the colony evolution of genetic algorithm and the merit of simulated annealing in avoiding cycling search, a hybrid optimization algorithm is introduced based on multi-objective genetic algorithm , and an optimization on the control parameters of HEV energy management is conducted. The results show that in multi-objective optimization on HEV control strategy, the hybrid algorithm proposed avoids the defects of premature convergence and random search without direction in traditional genetic algorithm, enhancing the convergence speed and computing efficiency.
展开▼
