Adaptive operation strategy of a polymer electrolyte membrane fuel cell air system based on model predictive control

Hahn, Sergei; Braun, Jochen; Kemmer, Helerson; Reuss, Hans-Christian

doi:10.1016/j.ijhydene.2021.02.135

Cited by 21 publications

(1 citation statement)

References 31 publications

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“…10 Abdullah and Idres 11 proposed a constrained model predictive control (MPC) method to regulate the air flow rate and avoid the oxygen starvation. Nonlinear MPC, 12,13 generalized predictive control, 14 explicit MPC, 15 robust MPC, 16 and other improved MPC algorithms 17,18 were also widely applied in the OER regulation. In addition, the sliding mode control is an outstanding method for fuel cell system control due to its excellent non-linear processing ability, good robustness and fast response.…”

Section: Introductionmentioning

confidence: 99%

A multivariable sliding mode predictive control method for the air management system of automotive fuel cells

Yang,

Fu,

et al. 2023

Measurement and Control

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The proton exchange membrane fuel cell gas control has been one key point in fuel cell management systems. The complexity and coupling of the air management system make it difficult to achieve precise air intake adjustment. In this paper, an accurate joint control method for the air flow and pressure regulation is proposed. The nonlinear mathematical model of the air management system is developed to describe the output characteristic and state change. Based on this, the feedback linearization method is proposed to obtain the direct correspondence between control variables and controlled variables. In addition, to solve the problem that the controlled variables cannot be measured directly, an extended state observer is applied to estimate the stack cathode pressure. The sliding mode predictive control method is proposed to control the oxygen excess ratio and cathode pressure simultaneously. The relative order of the system is used to design the sliding mode surface, and the corresponding predictive model is proposed. The results obtained by simulation experiments show that pressure and mass flow have little effect on each other through decoupling. The proposed algorithm has been verified to have high precision, fast response, and robustness through comparative experiments.

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