Real-time optimal temperature model free adaptive control of air-cooling PEMFC power generation system based on grey prediction

被引：0
作者：
Yin L. [1 ]
Liu L. [1 ]
Li Q. [1 ]
Chen W. [1 ]
机构：
[1] School of Electrical Engineering, Southwest Jiaotong University, Chengdu
来源：
| 1600年 / Electric Power Automation Equipment Press卷 / 37期
基金：
中国国家自然科学基金;
关键词：
Grey prediction; Model free adaptive control; Optimal temperature characteristics; PEMFC power generation system; Real-time control;
D O I：
10.16081/j.issn.1006-6047.2017.12.023
中图分类号：
学科分类号：
摘要：
The output performance of air-cooling PEMFC(Proton Exchange Membrane Fuel Cell) power generation system is affected by the operating parameters such as operating temperature, gas flow rate, exhaust interval, etc, among which, the operating temperature is the key factor. According to the complex characteristics of temperature control in air-cooling PEMFC power generation system, i.e. nonlinear, time delay, slow time variation, etc, a model free adaptive control method based on grey prediction is proposed for real-time optimal temperature control, which substitutes the results of grey prediction for the current operating temperature measurement of power generation system. Experimental results show that, the proposed method can track the optimal temperature in real-time under different load conditions. Compared with the incremental PID control, the proposed method effectively reduces the overshoot of the system and makes the output power of generation system more stable, which is helpful for long-term stable operation of power generation system and prolongs the service life of electrolysis stack. The proposed method adjusts the controller on line only according to the input and output data of PEMFC, which is insensitive to PEMFC parameters, so the method can be applied to similar air-cooling PEMFC power generation system. © 2017, Electric Power Automation Equipment Press. All right reserved.
引用
收藏
页码：164 / 171
页数：7
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