基于QG-SA算法的纯电动公交动力系统参数优化

Power System Parameters Optimization of Electric Transit Bus Based On QG-SA Algorithm

为提高纯电动公交车的爬坡性能、加速性能以及续驶里程,通过AVL_Cruise建立了双轴双电机驱动的纯电动公交车模型,结合量子遗传算法和模拟退火算法的优点,提出了一种QG-SA算法对纯电动公交车的动力系统参数进行了优化。结果表明,与模拟退火算法相比,QG-SA算法不仅缩短了优化时间,且优化效果更好,有效改善了纯电动公交车的动力性和经济性。

To improve gradeability, accelerating ability and driving range of electric transit bus, an electric transit bus model driven by double-shaft dual-motor was built with AVL Cruise, and a QG-SA algorithm was proposed to optimize power system parameters of this bus based on advantages of quantum genetic algorithm and simulated annealing algorithm. The resuhs show that, compared with simulated annealing algorithm, QG-SA algorithm not only shortens optimization time, but also has better optimization effect, moreover, it improves power performance and economy of electric transit bus.