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author:

Chen, J. (Chen, J..) [1] | Li, J. (Li, J..) [2] | Xu, Z. (Xu, Z..) [3] | Wang, Y.-X. (Wang, Y.-X..) [4]

Indexed by:

Scopus

Abstract:

The accurate control of automotive fuel cell oxygen excess ratio (OER) is necessary to improve system efficiency and service life. To this end, an anti-disturbance control driven by a feedback linearization model predictive control (MPC)-based cascade scheme is proposed. It considers strong nonlinear coupling and disturbance injection of fuel cell oxygen supply. A six-order nonlinear fuel cell oxygen feeding model is presented. It is further formulated using an extended state observer to rapidly reconstruct the OER, to overcome the slow response and interference errors of sensor measurements. In the proposed cascade control, the outer loop is the anti-disturbance control which is used to realize the optimized OER tracking and the inner loop via the feedback linearization to linearize the oxygen feeding behaviors conducts MPC to regulate the air compressor output mass flow. The feedback linearization demonstrates a robust tracking performance of nonlinear outputs, and the integral absolute error of anti-disturbance control is 0.3021 lower than that of PI control under a custom test condition. Finally, the numerical validation on a hybrid driving cycle indicates that the proposed cascade control can regulate the fuel cell OER with an average absolute error of 0.02313 in the high air compressor operation efficiency zone. © 2020 Hydrogen Energy Publications LLC

Keyword:

Anti-disturbance control; Automotive fuel cell; Cascade control scheme; Feedback linearization; Model predictive control (MPC); Oxygen excess ratio (OER)

Community:

  • [ 1 ] [Chen, J.]Key Laboratory of Industrial Automation Control Technology and Information Processing (Fuzhou University), Fujian Province University, School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, 350116, China
  • [ 2 ] [Li, J.]National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing, 100081, China
  • [ 3 ] [Xu, Z.]Key Laboratory of Industrial Automation Control Technology and Information Processing (Fuzhou University), Fujian Province University, Fuzhou, 350116, China
  • [ 4 ] [Wang, Y.-X.]Key Laboratory of Industrial Automation Control Technology and Information Processing (Fuzhou University), Fujian Province University, School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, 350116, China
  • [ 5 ] [Wang, Y.-X.]National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing, 100081, China

Reprint 's Address:

  • [Wang, Y.-X.]Key Laboratory of Industrial Automation Control Technology and Information Processing (Fuzhou University), Fujian Province University, School of Mechanical Engineering and Automation, Fuzhou UniversityChina

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Source :

International Journal of Hydrogen Energy

ISSN: 0360-3199

Year: 2020

5 . 8 1 6

JCR@2020

8 . 1 0 0

JCR@2023

ESI HC Threshold:132

JCR Journal Grade:2

CAS Journal Grade:3

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 28

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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