基于灰色预测的空冷型PEMFC发电系统实时最优温度无模型自适应控制

发布时间：2018-04-13 04:16

本文选题：质子交换膜燃料电池发电系统 + 最优温度特性　；参考：《电力自动化设备》2017年12期

【摘要】：空冷型质子交换膜燃料电池(PEMFC)发电系统的输出性能受工作温度、气体流速、尾气排放间隔等操作参数的影响,其中工作温度是影响输出性能的关键因素。针对空冷型PEMFC发电系统温度控制所具有的非线性、时滞、慢时变等复杂特性,提出基于灰色预测的无模型自适应控制方法实现实时最优温度控制。该方法将灰色预测的结果代替发电系统当前工作温度测量值。实验结果表明:所提方法能够在不同负载条件下实现对发电系统最优温度进行实时跟踪。与增量式PID控制相比,所提方法有效减小了系统的超调,使发电系统输出功率更平稳,有利于发电系统的长期稳定运行,延长电堆的使用寿命。且所提方法仅根据PEMFC输入输出数据在线对控制器进行调整,对PEMFC参数不敏感,可应用于类似空冷型PEMFC发电系统。
[Abstract]:The output performance of an air-cooled PEMFC power generation system is affected by operating parameters such as operating temperature, gas flow rate and tail gas emission interval, among which the operating temperature is the key factor affecting the output performance.Aiming at the complex characteristics of temperature control of air-cooled PEMFC power system, such as nonlinear, time-delay and slow time-varying, a model-free adaptive control method based on grey prediction is proposed to realize real-time optimal temperature control.In this method, the grey prediction results are used to replace the current operating temperature measurements of the generation system.The experimental results show that the proposed method can track the optimal temperature of power generation system in real time under different load conditions.Compared with incremental PID control, the proposed method can effectively reduce the overshoot of the system, make the output power of the generation system more stable, facilitate the long-term stable operation of the power generation system and prolong the life of the stack.The proposed method only adjusts the controller online according to PEMFC input and output data and is insensitive to PEMFC parameters. It can be applied to similar air-cooled PEMFC power generation systems.
【作者单位】：西南交通大学电气工程学院;
【基金】：国家科技支撑计划项目(2014BAG08B01) 国家自然科学基金资助项目(61473238,51407146) 四川省杰出青年基金资助项目(2015JQ0016)~~
【分类号】：TM911.4

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