储能科学与技术 ›› 2023, Vol. 12 ›› Issue (3): 857-869.doi: 10.19799/j.cnki.2095-4239.2022.0703

• 储能系统与工程 • 上一篇    下一篇

基于Simscape的质子交换膜燃料电池冷却系统建模与温度控制策略

王星(), 孙俊(), 陈宁芳, 闫立   

  1. 武汉理工大学船海与能源动力工程学院,湖北 武汉 430063
  • 收稿日期:2022-11-25 修回日期:2022-12-09 出版日期:2023-03-05 发布日期:2023-04-14
  • 通讯作者: 孙俊 E-mail:287748240@qq.com;sunjun@whut.edu.cn
  • 作者简介:王星(1998—),男,硕士研究生,研究方向为燃料电池系统仿真与控制,E-mail:287748240@qq.com
  • 基金资助:
    国家自然科学基金重点项目(U1709215)

Modeling of a proton exchange membrane fuel cell cooling system based on the Simscape temperature control strategy

Xing WANG(), Jun SUN(), Ningfang CHEN, Li YAN   

  1. School of Ship-Ocean and Energy and Power Engineering, Wuhan University of Technology, Wuhan 430063, Hubei, China
  • Received:2022-11-25 Revised:2022-12-09 Online:2023-03-05 Published:2023-04-14
  • Contact: Jun SUN E-mail:287748240@qq.com;sunjun@whut.edu.cn

摘要:

为了提高质子交换膜燃料电池(PEMFC)冷却系统模型精度且能够方便有效地对其实现控制,提出基于 Simulink/Simscape构建膨胀水箱、冷却液循环泵、散热器等关键冷却系统模块,对燃料电池冷却系统进行物理建模仿真;水冷型燃料电池电堆的温度与冷却液出入堆温差主要受散热器的空气流量与循环水的流量影响, 针对空气流量与循环水流量存在强耦合关系,提出了冷却液流量跟随电流控制,线性自抗扰控制空气流量的联合控制策略,实现了散热风扇和循环水泵控制的解耦;为保证控制策略的有效性,减少整定参数的工作量,提出了精英遗传算法优化ADRC(自抗扰控制)参数的方法,优化后的控制策略应对输入有扰动时,系统的最大超调量仅有1.23%且能在30 s内再次达到稳定,因此能够对燃料电池电堆温度实现有效控制。仿真结果表明通过优化后的控制策略在无干扰或有白噪声干扰的阶跃负载电流影响下,都能够对电堆温度与冷却液温差实现有效控制,具有很强的鲁棒性与抗干扰能力。

关键词: 质子交换膜燃料电池(PEMFC), 冷却系统模型, 流量跟随, 自抗扰控制, 遗传算法优化

Abstract:

To improve the accuracy of the cooling system model of a Proton Exchange Membrane Fuel Cell (PEMFC) and control it conveniently and effectively, key cooling system modules, such as an expansion tank, coolant circulating pump, and radiator are constructed based on Simulink/Simscape, and the physical modeling and simulation of the fuel cell cooling system are performed. The temperature of the water-cooled fuel cell stack and the temperature difference between the coolant in and out of the stack are mainly affected by the radiator's airflow and the circulating water flow. Given the strong coupling relationship between the airflow and the circulating water flow, a combined control strategy of the coolant flow following the current control and the linear active disturbance rejection control airflow is proposed, which realizes the decoupling of the cooling fan and the circulating water pump control. Therefore, an elite genetic algorithm is proposed to optimize the parameters of Active Disturbance Rejection Control to ensure the effectiveness of the control strategy and reduce the workload of setting parameters. When the optimized control strategy is disturbed by the input, the maximum overshoot of the system becomes 1.23% and can be stabilized again within 30 s. Therefore, the temperature of the fuel cell stack can be effectively controlled. Simulation results show that the optimized control approach has excellent resilience and anti-interference ability and can efficiently regulate the stack and coolant temperature difference under the influence of step load current without interference or white noise interference.

Key words: proton exchange membrane fuel cell, cooling system model, traffic following, active disturbance rejection control, genetic algorithm optimization

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