Automotive Innovation ›› 2022, Vol. 5 ›› Issue (3): 333-345.doi: 10.1007/s42154-022-00190-4

• • 上一篇    

Modeling and Decentralized Predictive Control of Ejector Circulation-Based PEM Fuel Cell Anode System for Vehicular Application

Bo Zhang1 · Dong Hao2 · Jinrui Chen3 · Caizhi Zhang1  · Bin Chen4 · Zhongbao Wei5 · Yaxiong Wang6
  

  1. 1. College of Mechanical and Vehicle Engineering, The State Key Laboratory of Mechanical Transmissions, Chongqing
    Automotive Collaborative Innovation Centre, Chongqing University, Chongqing 400044, China
    2. China Automotive Technology &Research Center Co., Ltd., Tianjin 300300, China
    3. Propulsion Research Institute of Chongqing Changan New Energy Vehicle Technology Co., Ltd, Chongqing 400000,
    China  4. China Merchants Testing Certifcation Vehicle Technology Research Institute Co., Ltd., Chongqing 401329, China 5. National Engineering Laboratory for Electric Vehicles, School of Mechanical Engineering, Beijing Institute
    of Technology, Beijing, China
    6. School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, China
  • 出版日期:2022-08-01 发布日期:2022-08-15

Modeling and Decentralized Predictive Control of Ejector Circulation-Based PEM Fuel Cell Anode System for Vehicular Application

Bo Zhang1 · Dong Hao2 · Jinrui Chen3 · Caizhi Zhang1  · Bin Chen4 · Zhongbao Wei5 · Yaxiong Wang6   

  1. 1. College of Mechanical and Vehicle Engineering, The State Key Laboratory of Mechanical Transmissions, Chongqing
    Automotive Collaborative Innovation Centre, Chongqing University, Chongqing 400044, China
    2. China Automotive Technology &Research Center Co., Ltd., Tianjin 300300, China
    3. Propulsion Research Institute of Chongqing Changan New Energy Vehicle Technology Co., Ltd, Chongqing 400000,
    China  4. China Merchants Testing Certifcation Vehicle Technology Research Institute Co., Ltd., Chongqing 401329, China 5. National Engineering Laboratory for Electric Vehicles, School of Mechanical Engineering, Beijing Institute
    of Technology, Beijing, China
    6. School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, China
  • Online:2022-08-01 Published:2022-08-15

摘要:

The dynamic response of fuel cell vehicle is greatly affected by the pressure of reactants. Besides, the pressure difference between anode and cathode will also cause mechanical damage to proton exchange membrane. For maintaining the relative stability of anode pressure, this study proposes a decentralized model predictive controller (DMPC) to control the anodic supply system composed of a feeding and returning ejector assembly. Considering the important influence of load current on the system, the piecewise linearization approach and state space with current-induced disturbance compensation are comparatively analyzed. Then, an innovative switching strategy is proposed to prevent frequent switching of the sub-model-based controllers and to ensure the most appropriate predictive model is applied. Finally, simulation results demonstrate the better stability and robustness of the proposed control schemes compared with the traditional proportion integration differentiation controller under the step load current, variable target and purge disturbance conditions. In particular, in the case of the DC bus load current of a fuel cell hybrid vehicle, the DMPC controller with current-induced disturbance compensation has better stability and target tracking performance with an average error of 0.15 kPa and root mean square error of 1.07 kPa.

Abstract:

The dynamic response of fuel cell vehicle is greatly affected by the pressure of reactants. Besides, the pressure difference between anode and cathode will also cause mechanical damage to proton exchange membrane. For maintaining the relative stability of anode pressure, this study proposes a decentralized model predictive controller (DMPC) to control the anodic supply system composed of a feeding and returning ejector assembly. Considering the important influence of load current on the system, the piecewise linearization approach and state space with current-induced disturbance compensation are comparatively analyzed. Then, an innovative switching strategy is proposed to prevent frequent switching of the sub-model-based controllers and to ensure the most appropriate predictive model is applied. Finally, simulation results demonstrate the better stability and robustness of the proposed control schemes compared with the traditional proportion integration differentiation controller under the step load current, variable target and purge disturbance conditions. In particular, in the case of the DC bus load current of a fuel cell hybrid vehicle, the DMPC controller with current-induced disturbance compensation has better stability and target tracking performance with an average error of 0.15 kPa and root mean square error of 1.07 kPa.