A multi‐input and single‐output voltage control for a polymer electrolyte fuel cell system using model predictive control method

Li, Xiufei; Qi, Yiwen; Li, Shian; Tunestål, Per; Andersson, Martin

doi:10.1002/er.6616

Cited by 9 publications

(11 citation statements)

References 36 publications

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“…The reason for undertaking this approach is that an exact model accounting for all the complex subsystems involved in an FCS is impractical for robust stability analysis and control design. 5,7,36 This simplification enables a solution to the aforementioned problems, but using a simple and realizable controller, as we demonstrate.…”

Section: Introductionmentioning

confidence: 89%

“…To facilitate the analysis, we refrain from using intricate models and instead analyze an uncertain system, which portraits the unknown variable nature of the load and fuel cell stack. The reason for undertaking this approach is that an exact model accounting for all the complex subsystems involved in an FCS is impractical for robust stability analysis and control design 5,7,36 . This simplification enables a solution to the aforementioned problems, but using a simple and realizable controller, as we demonstrate.…”

Section: Introductionmentioning

confidence: 98%

“…While FCSs are a promising zero‐emission alternative to fossil‐based power sources, it is well known that the voltage generated by the fuel cell stack fluctuates under load variations 4,5 . Such voltage fluctuations propagate through the system and complicate the task of sustaining a precise output voltage, preventing the widespread use of FCSs as power sources.…”

Section: Introductionmentioning

confidence: 99%

“…3 While FCSs are a promising zero-emission alternative to fossil-based power sources, it is well known that the voltage generated by the fuel cell stack fluctuates under load variations. 4,5 Such voltage fluctuations propagate through the system and complicate the task of sustaining a precise output voltage, preventing the widespread use of FCSs as power sources. Other external disturbances that inevitably degrade the performance of an FCS are electromagnetic interference generated by fast switching transistors and variable frequency transformers.…”

Section: Introductionmentioning

confidence: 99%

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A robust energy processing method for fuel cell systems supplying a time‐varying uncertain load

Ramírez

2022

Intl J of Energy Research

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Summary Robustness and performance are key properties that can contribute to the widespread dissemination of fuel cell systems (FCSs) as power sources, and a precise output voltage can serve as a reliable criterion to evaluate these properties. In this paper, we propose to utilize intentional time delays as part of controllers to achieve proper output voltage regulation in an FCS. In the past few years, there has been a growing interest toward designing controllers with intentional delays to render improved responses and better noise attenuation capabilities in various classes of systems and this investigation extends the use of delay‐based controllers to the application field of FCSs. A natural progression of this research, which to our knowledge has not been addressed, pertains to how such controllers perform in the presence of uncertainties, and whether or not these controllers can accommodate these uncertainties. In this research work, we present a solution to this open problem on a class of proportional integral retarded (PIR) controllers when controlling an FCS supplying a time‐varying uncertain load. Through stability theory, the safe operation of the PIR controlled FCS is systematically guaranteed in spite of uncertain loads and input voltages. Specifically, based on Lyapunov methods and L2‐gain analysis, we derive simple stability conditions to achieve robustness and H∞ performance. We show that utilizing only output voltage measurements the PIR controller can maintain the predictive features of a pure differentiator, but without its inherent noise amplification problems. Hence, low‐pass filtering of signals or reconstruction of the states can be obviated. Compared with published control schemes for FCSs, the PIR controller is structurally simpler and practically realizable, and it is able to maintain robustness against uncertain loads and H∞ performance under exogenous signals without relying on disturbance estimators. Numerical simulations confirm the superiority of the PIR controller over benchmark proportional integral and proportional integral derivative controllers in terms of robustness, performance and noise attenuation capabilities.

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Section: Introductionmentioning

confidence: 89%

Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A robust energy processing method for fuel cell systems supplying a time‐varying uncertain load

Ramírez

2022

Intl J of Energy Research

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“…The feedback and feed‐forward control using the PID controller have been applied to obtain better fuel cell performance [9, 10]. However, it has been found that this method has certain drawbacks, such as a limited control range and insufficient constraint capacity, and the tuning method “trial and error” is adopted to find suitable coefficients [11]. As a result, inconsistent control effects may arise when it is applied under varying operating conditions.…”

Section: Introductionmentioning

confidence: 99%

Optimal oxygen excess ratio tracking of proton exchange membrane fuel cell with uncertainty based on robust model predictive control strategy

Zhang,

Zhang

et al. 2023

Fuel Cells

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To address the challenge of tracking the optimal oxygen excess ratio (OER) in the cell stack cathode of the proton exchange membrane fuel cell (PEMFC), which is subject to norm‐bounded parameter uncertainty and frequent external perturbations, this manuscript provides a novel robust model predictive control strategy with a state feedback control structure and hard constraints. We aim to minimize the tracking error of OER while maximizing the net power under varying operational conditions of the PEMFC. Initially, a control‐oriented model for the air supply system is built and its accuracy is validated by comparing it with experimental results. Next, we construct the discrete state‐space equations for optimal control and employ the linear matrix inequality (LMI) method to transform the problem of difficult min‐max optimization solutions into a convex optimization problem with LMI constraints. Finally, the effectiveness of the proposed control algorithm is validated through simulation. The results demonstrate the strong robustness and superiority of the proposed controller against uncertainties in plant parameters for robust OER trajectory tracking. It improves the transient performance through robust precision tracking applications, which will eventually accelerate PEMFC commercialization.

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A multi‐input and single‐output voltage control for a polymer electrolyte fuel cell system using model predictive control method

Cited by 9 publications

References 36 publications

A robust energy processing method for fuel cell systems supplying a time‐varying uncertain load

A robust energy processing method for fuel cell systems supplying a time‐varying uncertain load

Optimal oxygen excess ratio tracking of proton exchange membrane fuel cell with uncertainty based on robust model predictive control strategy

A study into Proton Exchange Membrane Fuel Cell power and voltage prediction using Artificial Neural Network

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