Experimental study on dynamic response characteristics and performance degradation mechanism of hydrogen-oxygen PEMFC during loading

Chen, Wenshang; Chen, Ben; Meng, Kai; Zhou, Heng; Tu, Zhengkai

doi:10.1016/j.ijhydene.2022.11.036

Cited by 25 publications

(3 citation statements)

References 36 publications

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“…In fixed load scenarios, they can efficiently power residential homes or offices, where stable operation is essential to meet consistent power demand [6]. In reality, achieving perfectly smooth output voltage of OC-PEM fuel cell is unattainable, leading to unavoidable undershoot voltage during loading [7]. Undershoot stress stems from insufficient reactants in the catalyst layer, typically observed under loading conditions [8].…”

Section: Introductionmentioning

confidence: 99%

“…Undershoot stress stems from insufficient reactants in the catalyst layer, typically observed under loading conditions [8]. When gas diffusion into the catalyst layer lags behind gas consumption through reactions, the reactant concentration becomes unstable, resulting in fluctuations in output performance [7]. These fluctuations, in turn, disrupt output stability, posing a threat to the reliability and safety of the fuel cell [9].…”

Section: Introductionmentioning

confidence: 99%

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Enhancing voltage stability through wavelet-fuzzy control of hydrogen flow in OC-PEM fuel cell

Pangaribowo,

Mulyo Utomo,

Budiman

et al. 2024

Bulletin EEI

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Open cathode proton exchange membrane fuel cells (OC-PEM fuel cells) serve as electricity generators, utilizing hydrogen as an input source. While effective for fixed loads like residential applications, challenges arise in dealing with output voltage fluctuations caused by rapid load changes. These fluctuations not only impact fuel cell performance but also introduce instability in the supplied power. To solve this issue, the study proposes an innovative hydrogen flow control system employing a feedforward wavelet- fuzzy method. The primary goal of this control system is to enhance fuzzy control performance using wavelets, mitigating signal fluctuations and achieving optimal stability in fuel cell output voltage under constant load conditions. Wavelet functions act as filters on the fuzzy control input, minimizing fluctuations and refining the entire process. Additionally, a feedforward system is incorporated to maintain hydrogen flow at the set point value. The proposed control system is implemented on a validated model using experimental data. Performance analysis reveals that the proposed method effectively stabilizes voltage by accelerating the recovery time from disturbances.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Enhancing voltage stability through wavelet-fuzzy control of hydrogen flow in OC-PEM fuel cell

Pangaribowo,

Mulyo Utomo,

Budiman

et al. 2024

Bulletin EEI

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“…This is crucial not only from the standpoint of UGV mobility but also for the durability of such a platform. A high current peak required from the power source can lead to the possible destruction of individual polymer electrolyte fuel cells in the PEMFC stack [24,25].…”

Section: Introductionmentioning

confidence: 99%

Applying a 2 kW Polymer Membrane Fuel-Cell Stack to Building Hybrid Power Sources for Unmanned Ground Vehicles

Dudek,

Zarzycki,

Raźniak

et al. 2023

Energies

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The novel constructions of hybrid energy sources using polymer electrolyte fuel cells (PEMFCs), and supercapacitors are developed. Studies on the energy demand and peak electrical power of unmanned ground vehicles (UGVs) weighing up to 100 kg were conducted under various conditions. It was found that the average electrical power required does not exceed ~2 kW under all conditions studied. However, under the dynamic electrical load of the electric drive of mobile robots, the short peak power exceeded 2 kW, and the highest current load was in the range of 80–90 A. The electrical performance of a family of PEMFC stacks built in open-cathode mode was determined. A hydrogen-usage control strategy for power generation, cleaning processes, and humidification was analysed. The integration of a PEMFC stack with a bank of supercapacitors makes it possible to mitigate the voltage dips. These occur periodically at short time intervals as a result of short-circuit operation. In the second construction, the recovery of electrical energy dissipated by a short-circuit unit (SCU) was also demonstrated in the integrated PEMFC stack and supercapacitor bank system. The concept of an energy-efficient, mobile, and environmentally friendly hydrogen charging unit has been proposed. It comprises (i) a hydrogen anion exchange membrane electrolyser, (ii) a photovoltaic installation, (iii) a battery storage, (iv) a hydrogen buffer storage in a buffer tank, (v) a hydrogen compression unit, and (vi) composite tanks.

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Multi‐step performance degradation prediction method for proton‐exchange membrane fuel cell stack using 1D convolution layer and CatBoost

Zhang,

Dong,

et al. 2024

Adaptive Control & Signal

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SummaryThe increasing environmental issues such as climate change and air pollution require energy saving and emission reduction in various fields, such as manufacturing, building, and transportation. To address the above problem, proton‐exchange membrane fuel cells (PEMFC) gradually become promising green energy conversion device due to the advantages of zero pollution, high efficiency, and low operating noise. However, the durability problem has extremely limited the PEMFC large‐scale commercial application. To prolong the service life of PEMFC, performance degradation prediction is an effective method. This paper proposes a multi‐step performance degradation prediction method for proton‐exchange membrane fuel cells based on CatBoost feature selection, convolution computing, and interactive learning mechanism. CatBoost is used to evaluate the importance of the monitor parameters on performance degradation. The evaluation results and PEMFC degradation mechanism analyses are used to select the monitor parameters for construing the prediction model. Based on the 1D convolutional layer and the interactive learning mechanism, the prediction model is proposed to extract the deep features from the monitor data to predict the performance degradation of the fuel cell system. In particular, the multi‐step prediction is performed by the configurable sliding window. The effectiveness of the proposed method is verified on real experiment datasets, and the experiment results show that the proposed method is particularly effective for multi‐step degradation prediction and decreases the computation by feature selection and 1D convolution layer.

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Experimental study on dynamic response characteristics and performance degradation mechanism of hydrogen-oxygen PEMFC during loading

Cited by 25 publications

References 36 publications

Enhancing voltage stability through wavelet-fuzzy control of hydrogen flow in OC-PEM fuel cell

Enhancing voltage stability through wavelet-fuzzy control of hydrogen flow in OC-PEM fuel cell

Applying a 2 kW Polymer Membrane Fuel-Cell Stack to Building Hybrid Power Sources for Unmanned Ground Vehicles

Multi‐step performance degradation prediction method for proton‐exchange membrane fuel cell stack using 1D convolution layer and CatBoost

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