Journal of Jilin University(Engineering and Technology Edition) ›› 2022, Vol. 52 ›› Issue (9): 2085-2095.doi: 10.13229/j.cnki.jdxbgxb20220322

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Design of model⁃free adaptive sliding mode controller for cathode flow of fuel cell

Chong ZHANG1,2(),Yun-feng HU1,2,Xun GONG3,Yao SUN1()   

  1. 1.State Key Laboratory of Automotive Simulation and Control，Jilin University，Changchun 130022，China
    2.College of Communication Engineering，Jilin University，Changchun 130022，China
    3.College of Artificial Intelligence，Jilin University，Changchun 130012，China
  • Received:2022-03-28 Online:2022-09-01 Published:2022-09-13
  • Contact: Yao SUN E-mail:zhangchong196419@163.com;syao@jlu.edu.cn

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Abstract:

Aiming at the cathode flow control problem of proton exchange membrane fuel cells， considering the dependence of existing model-based control schemes on system dynamics and the influence of unmodeled dynamics on system control performance， a new data-driven model-free adaptive control scheme was designed. Firstly， the non-parametric dynamic linearization technology was used to obtain the dynamic linearized data model of cathode flow， which can realize the adaptability and robustness to the internal parameter perturbation and external perturbation of the controlled system. On the basis of this data model, an adaptive second-order sliding mode controller was designed to improve the transient quality and steady-state accuracy of the system. In addition， under the Lyapunov stability framework， it is proved that the cathode flow system finally enters a convergent quasi-sliding mode driven by the proposed control law. Finally， the parameters in the model-free adaptive sliding mode algorithm are determined by quantum particle swarm optimization. The effectiveness of the proposed control system is verified under multiple operating conditions.

Key words: control science and engineering, fuel cell, model-free adaptive control, second-order sliding mode control, quantum particle swarm optimization

CLC Number: 

  • TP13

Fig.1

Structure block diagram of PEMFC system"

Fig.2

Relationship between OER and net power"

Fig.3

Control block diagram of cathode flow control for PEMFC"

Fig.4

Map of air flow rate with respect to compressor speed and pressure ratio"

Fig.5

Optimization tuning curves under nominal parameters"

Fig.6

Simulation under nominal parameters"

Fig.7

Parameter uncertainties"

Fig.8

Simulation under perturbation parameters"

Fig.9

Simulation under perturbation parameters：performance indicators"

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