基于混合进化算法的汽车传动系优化研究

Optimization of Automobile Powertrain Based on Hybrid Evolutionary Algorithm

针对汽车的动力系优化问题,构建了整车的动力性及经济性目标函数以及约束条件,并结合遗传算法与粒子群优化算法设计了混合进化算法,利用该算法对汽车传动系参数进行了优化。通过加权处理将多目标函数转换为单个目标函数,同时采用惩罚函数将约束条件转化为惩罚项附加于目标函数,实现了利用混合进化算法对汽车传动系参数的优化。最后,通过仿真研究验证了优化算法的正确性和有效性,仿真的分析结果显示优化后的整车的动力性和经济性均得到了一定改善,为汽车传动系的参数优化提供了新的优化算法。

Aiming at optimization of automobile＇s powertrain, the power and economic objective function of automobile and relevant multiple constrains are estlished, and the parameters of powertrain are optimized using Hybrid Evolutionary Algorithm （HEA） which is designed by combining genetic algorithm （GA） with particle swarm optimization （ PSO ）. In order to achieved the optimization of automobile powertrain using Hybrid Evolutionary Algorithm, the objective functions are transformed into a single objective function using weighting method, and the constraint conditions are dealt with as a penalty term attached to the objective function. Finally, the simulation studies are included to verify the effectiveness of designed algorithm, and the results indicate that the power and economic perfornume of the automobile is improved after optimization. New algorithm for the optimization of antomobile＇s powertrain is designed.