化工进展

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固体氧化物燃料电池温度系统的改进型广义预测控制方法

刘 欣,郝晓弘,杨新华,安爱民   

  1. 兰州理工大学电气工程与信息工程学院,甘肃 兰州 730050
  • 出版日期:2013-10-05 发布日期:2013-10-14

A new method of improved generalized predictive control for solid oxide fuel cell’s temperature system

LIU Xin,HAO Xiaohong,YANG Xinhua,AN Aimin   

  1. College of Electrical and Information Engineering,Lanzhou University of Technology,Lanzhou 730050,Gansu,China
  • Online:2013-10-05 Published:2013-10-14

摘要: 固体氧化物燃料电池的工作状态是一个高温、高速率变化的化学反应过程,其入口气体温度的稳定性直接影响到燃料利用率和电池效率。本文提出一种改进的带有外部输入的非线性自回归积分滑动平均模型,结合两极燃料和空气的流量比、负载电流变化值来实现入口气体温度的非线性广义预测控制方法,采用了基于非线性最小二乘法的Levenberg-Marquardt算法确定该模型的参数。仿真结果表明,该模型与温度控制系统的传递函数模型相结合后能有效并迅速的获得燃料、氧化剂流量这两种操作量的预测值并使系统在较高的温度工作点当负载电流发生波动时能克服变化引起的参数偏差,保持运行时输出电压的稳定性。

关键词: 板式固体氧化物燃料电池, 广义预测控制, NARIMAX模型, Levenberg-Marquardt算法

Abstract: The working condition of solid oxide fuel cell is a chemical reaction process of high-temperature,high-rate change. The stability of gas inlet temperature directly affects fuel utilization and cell efficiency. This paper presents an improved external input of nonlinear autoregressive integrated moving average model which combines the ratio of fuel and air flow rates and the load current change to realize nonlinear generalized predictive control for the temperature of gas inlets,and uses the Levenberg-Marquardt algorithm based on nonlinear least squares to determine the parameters. The prediction values of real-time flow rates of fuel and air could be obtained accurately and quickly based on the combination of the model and transfer function model for the temperature control system,so that at higher temperature operation,the system could overcome parameter deviations due to changes caused by load current and retain the stability of output voltage.

Key words: plate solid oxide fuel cell, generalized predictive control(GPC), NARIMAX model, Levenberg-Marquardt algorithm