【摘要】 为提升纯电动汽车动力总成冷却系统温度控制效果并降低能量消耗，提出一种遗传算法（GA）优化模糊PID参数的控制方法。搭建纯电动汽车分布式冷却系统模型，将模糊控制理论与PID相结合，实时调整PID控制参数，并采用遗传算法优化模糊PID的量化因子和比例系数，建立GA-模糊PID控制器，在所制定的控制策略下调节冷却系统中电子水泵转速和风扇风速，控制冷却液进口温度，进而控制动力总成温度。通过AMESim和Simulink联合仿真，结果表明，相比阈值控制和PID控制，GA-模糊PID控制具有良好的温度控制能力和节能效果。更多还原

【Abstract】 In order to improve the temperature control effect of pure electric vehicle powertrain cooling system and reduce energy consumption, a genetic algorithm(GA) control method for optimizing fuzzy PID parameters was proposed. Build a model of a distributed cooling system for pure electric vehicles, combine fuzzy control theory with PID, adjust PID control parameters in real time, and use genetic algorithm to optimize the quantization factor and proportional coefficient of fuzzy PID, and establish a GA-fuzzy PID controller.Under the control strategy, the speed of the electronic water pump and the fan speed in the cooling system are adjusted, the temperature of the coolant inlet is controlled, and the temperature of the powertrain is controlled. Through AMESim and Simulink co-simulation,the results show that, compared with threshold control and PID control, GA-fuzzy PID control has better temperature control ability and energy saving effect.更多还原