基于IQGA的混合动力车辆传动系参数优化

Parameter Optimization of Hybrid Vehicle Transmission System Based on Improved Quantum Genetic Algorithm

为了协同改善混合动力车辆的动力性、燃油经济性和排放性,以并联式混合动力救援车辆为研究对象,对其传动系参数进行了多目标优化设计。基于ADVISOR分析并搭建了车辆仿真模型;以车辆最高速度、最大爬坡度、规定速度区间内加速时间、等效燃油消耗量和排放量为控制目标,以车辆动力要求、变速器设计原则、蓄电池荷电状态平衡为主要约束条件,采用系数转换法建立了传动系参数优化模型;针对传统优化算法容易早熟收敛的缺点,提出了融合动态量子旋转门和灾变操作的改进量子遗传优化算法;在MATLAB平台通过调用ADVISOR后台函数实现了车辆传动系参数的联合仿真优化。结果表明,所提出的优化方法可明显改善车辆的整体性能,且相比于遗传算法和量子遗传算法,可取得更好的优化效果。

In order to improve the power performance,economy and emission of hybrid vehicles,a parallel hybrid rescue vehicle was taken as the research object,and the multi-objective parameter optimization of the transmission system was carried out.The vehicle simulation model was built based on ADVISOR platform.Taking maximum speed,maximum climbing gradient,acceleration time within specified speed range,equivalent fuel consumption and emission as control targets,and taking vehicle dynamic requirements,transmission design principles,and battery SOC balance as the main constraints,the optimization model for transmission system was established by using weighting coefficient method.Then,for the problem of premature convergence of traditional optimization algorithm,an improved quantum genetic algorithm(IQGA)with dynamic quantum rotation gate and catastrophic operation was proposed.Based on MATLAB,the joint optimization simulation for transmission system was realized by invoking the backstage function of ADVISOR.The simulation results demonstrate that the vehicle overall performance can be significantly improved with the proposed method,and the optimization effect is better than that of genetic algorithm(GA)and quantum genetic algorithm(QGA).