模型预测控制
控制理论(社会学)
堆栈(抽象数据类型)
控制器(灌溉)
电动汽车
稀释
计算机科学
PID控制器
阴极
汽车工程
控制工程
工程类
控制(管理)
温度控制
功率(物理)
物理
电气工程
热力学
人工智能
农学
程序设计语言
生物
作者
Maximilian K. Eisner,Zheng Zhang,V. Formanski,Ralph Kennel
标识
DOI:10.1016/j.ijhydene.2023.07.113
摘要
This study demonstrates the applicability of an explicit model predictive controller (ExMPC) to the air mass flow control in a fuel cell electric vehicle. The two control tasks comprise the supply of air to the fuel cell stack for the electrochemical reaction as well as the dilution of hydrogen in the outlet gas flow of the cathode subsystem. With the aim of achieving zero control deviation for steady states, the linear model in the state observer is extended with two perturbations. During the experimental validation of the proposed controller, fast dynamics are achieved with the ExMPC, which generally exploits the limits of the control variables. After the calibration of the ExMPC, the final comparison to a set of reference PI controllers reveals a significant improvement in the closed-loop behavior of the cathode subsystem during step changes in the controller setpoints.
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