矿用混合动力自卸车粒子群优化模糊控制研究

Research on Particle Swarm Optimization Fuzzy Control for Hybrid Dump Truck

针对某矿用混合动力自卸车,在Matlab中以整车需求转矩与当前车速下发动机最优转矩的差值和动力电池SOC为输入、发动机期望转矩为输出,构建了模糊控制器并建立了整车模糊控制策略。由于模糊控制器的制定主要依靠专家经验,因此一开始控制效果可能并不好。为此利用Cruise和Simulink建立了整车模型和模糊控制策略联合仿真平台,针对模糊控制器的隶属度函数和模糊控制规则,利用粒子群算法以发动机和电机总的等效燃油消耗为优化目标对它们同时进行优化。仿真结果显示,与传统的模糊控制器相比,优化后的模糊控制器能够在有效控制矿用混合动力自卸车动力电池SOC变化的同时提高整车的燃油经济性。

Aiming at a hybrid dump truck, after established the control strategy in Matlab, a fuzzy controller was constructed by using the difference between the requested torque and optimal engine t orque and the battery state-of-charge （SOC） as the inputs, and the engine torque as the output. Because of the fuzzy controller mainly relies on expert＇s experience,so the control effect maybe no good. So using Cruise and Simulink to build the vehicle model and the fuzzy control strategy＇s platform.The membership function and rules of fuzzy controller are optimized simultaneously by using particle swarm optimization based on the optimization object of the engine and motor＇s equivalent fuel eonsuniption. The Simulation results show that ,compared with traditional fuzzy controller, this method maintains battery SOCwithin its operation range more effectively and improve the fuel economy of the hybrid dump truck.