混合动力汽车控制策略优化研究

Research on Optimum Control Strategy for Hybrid Electric Vehicle

将自适应遗传算法与序列二次规划算法结合构成混合遗传算法,用于求解混合动力汽车控制策略参数优化问题。一方面,分析并建立了控制策略参数优化的有约束非线性模型;另一方面,改进算法中自适应交叉和变异概率调整公式,并提出了序列二次规划算子与遗传算法结合的新方式。仿真结果表明,该算法提高了收敛速度和求解精度,保证了全局收敛性,在混合动力汽车控制策略参数优化中的应用是有效的。

On the basis of Adaptive Genetic Algorithm （AGA） and Sequential Quadratic Programming （SQP） ,a hybrid generic algorithm is presented for parametric optimization of control strategy for Hybrid Electric Vehicle （HEV）. The optimal model of parameters is formulated as a constrained nonlinear programming problem. The hybrid genetic algorithm not only proposes a new calculation formula of crossover and mutation probability,but also proposes a new AGA and SQP combinative mode. The study on case proves the validity of the parameters optimization and the efficiency of this hybrid genetic algorithm.