基于多目标遗传算法的混合电动汽车参数优化

动力系统和控制器参数的同时优化是提高混合电动汽车(HEV)燃油经济性并降低排放的关键。这类优化问题涉及多个相互冲突的优化目标和非线性约束,是典型的多目标优化问题。文中采用多目标遗传算法求解该优化问题的Pareto最优解集,并应用ADVISOR对实际算例的优化结果进行比较分析。结果表明,应用该方法可找到多组可行解,在满足原车动力性要求的前提下能有效提高燃油经济性,降低排放。

Parameters Optimization of Hybrid Electric Vehicle Based on Multi-objective Genetic Algorithms

Concurrent optimization for parameters of powertrain and control system is the key to improving fuel economy and reducing emission of hybrid electric vehicle.It involves several conflicting optimization objectives and nonlinear constraints,and so is a typical multi-objective optimization problem.In this paper,the multi-objective genetic algorithms are used to find the Pareto-optimal solution set,and the ADVISOR is utilized to evaluate the results of optimization for a real vehicle.The results demonstrate that the proposed approach can find many feasible solutions to improve fuel economy and reduce emission without worsening power performance.