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Abstract Precise control of hydrogen pressure is crucial for the performance and durability of fuel cell systems. With the widely used common-rail injection system, traditional PID controller still dominates. For a long time, the hydrogen pressure fluctuates acutely when hydrogen purge valve switches or load sharply changes with using PID controller. In recent studies, several new control strategies are presented. However, mostly of them are theoretical and experimental. In this study, an improved common-rail injection system, hydrogen injector/ejector assembly is introduced. Based on a real fuel cell system, a Mamdani fuzzy controller is designed to regulate the hydrogen pressure. The algorithm of fuzzy controller is explained in detail. A comparative study is carried out between fuzzy controller and PID controller. According to the results, the stability of hydrogen pressure with using fuzzy controller is better than using PID controller. This research could be useful for the control of fuel cell system. Highlights • The characters of hydrogen pressure's fluctuation was studied. • A Mamdani-type fuzzy control system was designed to controller the hydrogen pressure in fuel cell system. • The algorithm of the fuzzy controller was introduced in detail. • The controller was proved to be valid and effective for real fuel cell systems. • A comparative study is carried out between fuzzy controller and PID controller. [ABSTRACT FROM AUTHOR]

The oxygen starvation in fuel cells is an important reason for the deterioration of durability. The segmented fuel cell is a method to study the gas distribution inside the fuel cell. In order to study the influence of the grooving method on segmented fuel cell and its application in oxygen starvation diagnosis, a five-serpentine-channel three-dimensional two-phase simulation model is established by FLUENT. Through steady-state simulation, the effect of grooving method on fuel cell performance is studied. The overall performance (polarization curve) of the fuel cell drops slightly, but the current density distribution on the anode graphite plate changes greatly due to the grooves. The "current concentration" phenomenon is proposed based on the current density distribution. Through dynamic simulation, the oxygen starvation under current load mode and voltage load mode is simulated, and the "starvation coefficient" is defined as an oxygen starvation diagnostic index. In the current load mode, the "starvation coefficient" never exceed 15%, because when the oxygen starvation is severe, the simulation cannot converge or even cannot maintain, which corresponds to the voltage reversal in reality. However, in the voltage load mode, the "starvation coefficient" can reach up to 100%. The conclusions have important guiding significance for the judgment of the internal reaction uniformity of the segmented fuel cell by grooving method and provide a theoretical basis for judging whether a fuel cell is out of oxygen by segmented fuel cell. • A two-phase CFD simulation model of segmented fuel cell is established. • "Current concentration" phenomenon is proposed based on the current distribution. • "Starvation coefficient" is defined as an oxygen starvation diagnostic index. • Oxygen starvation under current load mode and voltage load mode is compared. [ABSTRACT FROM AUTHOR]

The contact pressure distribution plays a key role to the proton exchange membrane (PEM) fuel cell performance. The purpose of this study is to propose an equivalent stiffness model combined with an equivalent beam model to predict the contact pressure distribution for a large fuel cell stack. With the established equivalent stiffness model, the equivalent values of contact pressure is revealed. Moreover, these equivalent values are extended by an iterative calculation for contact pressure distribution with an established equivalent beam model. Finally, the presented model is compared to a three-dimensional FEA model. This equivalent stiffness model has high accuracy only with a 4.1% tolerance and the correlation coefficient of FEA and equivalent beam model for the contact pressure distribution at transverse and longitudinal direction is 0.976 and 0.998. This presented equivalent model is effective and can provide a direction for future work on high-performance fuel cell stack design and optimization. • Contact pressure distribution is important to the PEM fuel cell performance. • Equivalent stiffness model can obtain the contact pressure value. • Equivalent beam model can predict the contact pressure distribution. • The effectiveness of the presented model is validated with a FEA model. [ABSTRACT FROM AUTHOR]

Widely acknowledged by experts, the inconsistency between the cells of the proton exchange membrane fuel cell stack during operation is an important cause of the fuel cell life decay. Existing studies mainly focus on qualitative analysis of the effects of operating parameters on fuel cell stack consistency. However, there is currently almost no quantitative research on predicting the voltage consistency through operating parameters with machine learning methods. To solve this problem, a three-dimensional model of proton exchange membrane fuel cell stack with five single cells is established in this paper. The Computational Fluid Dynamic (CFD) method is used to provide the source data for prediction model. After predicting the voltage consistency with several machine learning methods and comparing the accuracy through simulation data, the integrated regression method based on Gradient Boosting Decision Tree (GBDT) gets the highest score (0.896) and is proposed for quickly predicting the consistency of cell voltage through operating parameters. After verifying the GBDT method with the experimental data from the fuel cell stack of SUNRISE POWER, in which the accuracy score is 0.910, the universality and accuracy of the method is confirmed. The influencing sensitivity of each operating parameter is evaluated and the current density has the greatest influence on the predicted value, which accounts for 0.40. The prediction of voltage consistency under different combination of operating parameters can guide the optimization of structural parameters in the process of the fuel cell design and operating parameters in the process of fuel cell control. • Predict voltage consistency through operating parameters with machine learning. • Gradient Boosting Decision Tree (GBDT) method gets the highest score. • The universality and accuracy of GBDT method are verified by experiments. • The influencing sensitivity of each parameter is evaluated. [ABSTRACT FROM AUTHOR]

Abstract As an energy conversion device that converts hydrogen energy into electrical energy, the fuel cell is one of the most promising. Starvation is the main reasons that shortens the lifetime of Proton Exchange Membrane Fuel Cell (PEMFC) for vehicle usage. Therefore, combining the experimental and simulation results, as well as previous studies, based on the external characteristics of PEMFCs, the mechanism of judging the starvation in PEMFCs is explored. It provides a theoretical basis for judging the starvation using external characteristics. In addition, the starvation index is proposed to solve the problem that the starvation in the process of fuel cell loading, which could not be evaluated in the past. This factor can provide guidance for matching and controlling the fuel cell supply system, as well as optimizing the internal structural parameters of the fuel cell. [ABSTRACT FROM AUTHOR]

This paper presents the design and simulation validation of two energy management strategies for dual-stack fuel cell electric vehicles. With growing concerns about environmental issues and the fossil energy crisis, finding alternative methods for vehicle propulsion is necessary. Proton exchange membrane (PEM) fuel cell systems are now considered to be one of the most promising alternative energy sources. In this work, the challenge of further improving the fuel economy and extending the driving range of a fuel cell vehicle is addressed by a dual-stack fuel cell system with specific energy management strategies. An efficiency optimization strategy and an instantaneous optimization strategy are proposed. Simulation validation for each strategy is conducted based on a dual-stack fuel cell electric vehicle model which follows the new European driving cycle (NEDC). Simulation results show that a dual-stack fuel cell system with proposed energy management strategies can significantly improve the fuel economy of a fuel cell vehicle and thus lengthen the driving range while being able to keep the start-stop frequency of the fuel cell stack within a reasonable range. [ABSTRACT FROM AUTHOR]