针对质子交换膜燃料电池空气供给子系统氧气过量比的控制问题,首先,建立面向控制的质子交换膜燃料电池系统的四阶非线性动态模型,构建电堆负载电流与最佳氧气过量比之间的拟合曲线方程;随后,设计一种采用新型复合趋近律的滑模控制器,并利用沙丘猫群优化算法对滑模控制中的参数进行寻优和整定;最后,对改进后的滑模控制器进行仿真验证,并与PID和其余3种滑模控制进行对比分析。仿真结果表明：当电堆负载电流变化时,改进后的滑模控制器可根据阴极流量偏差参数调节空压机的驱动电压,此时系统实时氧气过量比会迅速向最佳氧气过量比靠近,可将其两者之间的偏差控制0.1%之内,其所需的平均调节时间和误差性能指标均优于对比组。
Abstract
Aiming at the problem of controlling the excess ratio of oxygen in the air supply subsystem of proton exchange membrane fuel cells. Firstly, a control-oriented fourth-order nonlinear dynamic model of the proton exchange membrane fuel cells system is established, and a fitting curve equation between the stack load current and the optimal oxygen excess ratio is constructed. Subsequently, a sliding mode controller using a new compound reaching law is designed, and the parameters in the sliding mode control are optimized and tuned using the sand cat swarm optimization algorithm. Finally, the improved sliding mode controller is simulated and verified, and compared with PID and other three sliding mode controllers. The simulation results show that when the load current of the stack changes, the improved sliding mode controller can adjust the driving voltage of the air compressor according to the cathode flow deviation parameter. At this time, the real-time oxygen excess ratio of the system will quickly approach the optimal oxygen excess ratio. The deviation between the two can be controlled within 0.1%, and the required average adjustment time and error performance indicators are better than those of the comparison group.
关键词
质子交换膜燃料电池 /
空气供给子系统 /
滑模控制 /
沙丘猫群优化算法 /
氧气过量比
Key words
proton exchange membrane fuel cells /
air supply subsystem /
sliding mode control /
sand cat swarm optimization algorithm /
oxygen excess ratio
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基金
先进能源科学与技术广东省实验室佛山分中心（佛山仙湖实验室）开放基金（XHD2020-003）
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