基于模糊逻辑与遗传算法的燃料电池热管理方法研究

Research on Thermal Management Method of Fuel Cell Based on Fuzzy Logic and Genetic Algorithm

有效的质子交换膜燃料电池(Proton Exchange Membrane Fuel Cell,PEMFC)热管理是提升氢燃料电池汽车安全性、耐久性以及运行效率的关键因素之一。该文提出一种PEMFC电堆热管理控制方法,使电堆出入口温度保持在设定值。该方法以PEMFC热管理系统模型中电堆出入口温度的变化为依据,设计一种二维模糊控制器,并应用遗传算法优化模糊控制器的隶属度函数,从而使模糊控制器的控制精度更高。为验证所提出方法的有效性,该文选用Autonomie软件中的一款氢燃料电池汽车,在两种标准工况上进行PEMFC热管理方法验证。仿真结果显示,经过遗传算法优化后的模糊控制器相对于未优化的模糊控制器具有更高的控制精度,电堆出入口温度与设定值的偏差更低。

The thermal management of proton exchange membrane fuel cells(PEMFCs)influences the safety,durability,and operating efficiency of hydrogen fuel cell vehicles.A thermal management control method is proposed for PEMFCs in this research to maintain the temperature at the inlet and outlet of the stack at the set values.A two-dimensional fuzzy controller is designed based on the temperature changes at the inlet and outlet of the stack in the thermal management system model of PEMFCs,where the membership function of the fuzzy controller is optimized by using the genetic algorithm,so that the control precision of the fuzzy controller is higher.A hydrogen fuel cell vehicle from the Autonomie software is used to validate the proposed thermal management method of the PEMFC on two standard vehicle driving conditions.Simulation results show that the fuzzy controller optimized by the genetic algorithm presents the higher control accuracy than the one without the optimization.