567 research outputs found

    Performance improvement in polymer electrolytic membrane fuel cell based on nonlinear control strategies—A comprehensive study

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    A Polymer Electrolytic Membrane Fuel Cell (PEMFC) is an efficient power device for automobiles, but its efficiency and life span depend upon its air delivery system. To ensure improved performance of PEMFC, the air delivery system must ensure proper regulation of Oxygen Excess Ratio (OER). This paper proposes two nonlinear control strategies, namely Integral Sliding Mode Control (ISMC) and Fast Terminal ISMC (FTISMC). Both the controllers are designed to control the OER at a constant level under load disturbances while avoiding oxygen starvation. The derived controllers are implemented in MATLAB/ Simulink. The corresponding simulation results depict that FTISMC has faster tracking performance and lesser fluctuations due to load disturbances in output net power, stack voltage/power, error tracking, OER, and compressor motor voltage. Lesser fluctuations in these parameters ensure increased efficiency and thus extended life of a PEMFC. The results are also compared with super twisting algorithm STA to show the effectiveness of the proposed techniques. ISMC and FTISMC yield 7% and 20% improved performance as compared to STA. The proposed research finds potential applications in hydrogen-powered fuel cell electric vehicles

    Neural network and URED observer based fast terminal integral sliding mode control for energy efficient polymer electrolyte membrane fuel cell used in vehicular technologies

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    In this research work, a Neural Network (NN) and Uniform Robust Exact Differentiator (URED) observer-based Fast Terminal Integral Sliding Mode Control (FTISMC) has been proposed for Oxygen Excess Ratio (OER) regulation of a Polymer Electrolyte Membrane Fuel Cell (PEMFC) power systems for vehicular applications. The controller uses URED as an observer for supply manifold pressure estimation. NN is used to estimate the stack temperature which is unavailable. The suggested control method increased the PEMFC's effectiveness and durability while demonstrating the finite-time convergence of system trajectories. By controlling the air-delivery system in the presence of uncertain current requirements and measurement noise, the approach ensures maximum power efficiency. The Lyapunov stability theorem has been used to confirm the stability of the presented algorithm. In addition, the suggested method eliminated the chattering phenomenon and improved power efficiency. Given these noteworthy characteristics, the research has the potential to decrease sensor dependence and production costs while also improving the transient and steady-state response in vehicular applications

    Control of Proton Exchange Membrane Fuel Cell System

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    265 p.In the era of sustainable development, proton exchange membrane (PEM) fuel cell technology has shown significant potential as a renewable energy source. This thesis focuses on improving the performance of the PEM fuel cell system through the use of appropriate algorithms for controlling the power interface. The main objective is to find an effective and optimal algorithm or control law for keeping the stack operating at an adequate power point. Add to this, it is intended to apply the artificial intelligence approach for studying the effect of temperature and humidity on the stack performance. The main points addressed in this study are : modeling of a PEM fuel cell system, studying the effect of temperature and humidity on the PEM fuel cell stack, studying the most common used power converters in renewable energy systems, studying the most common algorithms applied on fuel cell systems, design and implementation of a new MPPT control method for the PEM fuel cell system

    Clean Energy Systems and Experiences

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    This book reports the latest developments and trends in "clean energy systems and experiences". The contributors to each chapter are energy scientists and engineers with strong expertise in their respective fields. This book offers a forum for exchanging state of the art scientific information and knowledge. As a whole, the studies presented here reveal important new directions toward the realization of a sustainable society

    Advanced Modeling and Research in Hybrid Microgrid Control and Optimization

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    This book presents the latest solutions in fuel cell (FC) and renewable energy implementation in mobile and stationary applications. The implementation of advanced energy management and optimization strategies are detailed for fuel cell and renewable microgrids, and for the multi-FC stack architecture of FC/electric vehicles to enhance the reliability of these systems and to reduce the costs related to energy production and maintenance. Cyber-security methods based on blockchain technology to increase the resilience of FC renewable hybrid microgrids are also presented. Therefore, this book is for all readers interested in these challenging directions of research

    Investigating the stability and degradation of hydrogen PEM fuel cell

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    The hydrogen proton exchange membrane (PEM) fuel cells are promising to utilize fuel cells in electric vehicle (EV) applications. However, hydrogen PEM fuel cells are still encountering challenges regarding their functionality and degradation mechanism. Therefore, this paper aims to study the performance of a 3.2 kW hydrogen PEM fuel cell under accelerated operation conditions, including varying fuel pressure at a level of 0.1–0.5 bar, variable loading, and short-circuit contingencies. We will also present the results on the degradation estimation mechanism of four fuel cells working at different operational conditions, including high-to-low voltage range and high-to-low temperature variations. These experiments examine over 180 days of continuous fuel cell working cycle. We have observed that the drop in the fuel cells' efficiency is at around 7.2% when varying the stack voltage and up to 14.7% when the fuel cell's temperature is not controlled and remained at 95 °C

    Preliminary design of a fuel cell/battery hybrid powertrain for a heavy-duty yard truck for port logistics

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    Abstract The maritime transport and the port-logistic industry are key drivers of economic growth, although, they represent major contributors to climate change. In particular, maritime port facilities are typically located near cities or residential areas, thus having a significant direct environmental impact, in terms of air and water quality, as well as noise. The majority of the pollutant emissions in ports comes from cargo ships, and from all the related ports activities carried out by road vehicles. Therefore, a progressive reduction of the use of fossil fuels as a primary energy source for these vehicles and the promotion of cleaner powertrain alternatives is in order. The present study deals with the design of a new propulsion system for a heavy-duty vehicle for port applications. Specifically, this work aims at laying the foundations for the development of a benchmark industrial cargo–handling hydrogen-fueled vehicle to be used in real port operations. To this purpose, an on-field measurement campaign has been conducted to analyze the duty cycle of a commercial Diesel-engine yard truck currently used for terminal ports operations. The vehicle dynamics has been numerically modeled and validated against the acquired data, and the energy and power requirements for a plug-in fuel cell/battery hybrid powertrain replacing the Diesel powertrain on the same vehicle have been evaluated. Finally, a preliminary design of the new powertrain and a rule-based energy management strategy have been proposed, and the electric energy and hydrogen consumptions required to achieve the target driving range for roll-on and roll-off operations have been estimated. The results are promising, showing that the hybrid electric vehicle is capable of achieving excellent energy performances, by means of an efficient use of the fuel cell. An overall amount of roughly 12 kg of hydrogen is estimated to be required to accomplish the most demanding port operation, and meet the target of 6 h of continuous operation. Also, the vehicle powertrain ensures an adequate all-electric range, which is between approximately 1 and 2 h depending on the specific port operation. Potentially, the hydrogen-fueled yard truck is expected to lead to several benefits, such as local zero emissions, powertrain noise elimination, reduction of the vehicle maintenance costs, improving of the energy management, and increasing of operational efficiency

    Maximum Power Point Tracking Techniques for Photovoltaic Panel: A Review and Experimental Applications

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    This article contains a review of essential control techniques for maximum power point tracking (MPPT) to be applied in photovoltaic (PV) panel systems. These devices are distinguished by their capability to transform solar energy into electricity without emissions. Nevertheless, the efficiency can be enhanced provided that a suitable MPPT algorithm is well designed to obtain the maximum performance. From the analyzed MPPT algorithms, four different types were chosen for an experimental evaluation over a commercial PV system linked to a boost converter. As the reference that corresponds to the maximum power is depended on the irradiation and temperature, an artificial neural network (ANN) was used as a reference generator where a high accuracy was achieved based on real data. This was used as a tool for the implementation of sliding mode controller (SMC), fuzzy logic controller (FLC) and model predictive control (MPC). The outcomes allowed different conclusions where each controller has different advantages and disadvantages depending on the various factors related to hardware and software.This research was funded by the Basque Government through the project EKOHEGAZ (ELKARTEK KK-2021/00092), by the Diputación Foral de Álava (DFA), through the project CONAVANTER, and by the UPV/EHU, through the project GIU20/063

    Modeling and control of fuel cell-battery hybrid energy sources

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    Environmental, political, and availability concerns regarding fossil fuels in recent decades have garnered substantial research and development in the area of alternative energy systems. Among various alternative energy systems, fuel cells and batteries have attracted significant attention both in academia and industry considering their superior performances and numerous advantages. In this dissertation, the modeling and control of these two electrochemical sources as the main constituents of fuel cell-battery hybrid energy sources are studied with ultimate goals of improving their performance, reducing their development and operational costs and consequently, easing their widespread commercialization. More specifically, Paper I provides a comprehensive background and literature review about Li-ion battery and its Battery Management System (BMS). Furthermore, the development of an experimental BMS design testbench is introduced in this paper. Paper II discusses the design of a novel observer for Li-ion battery State of Charge (SOC) estimation, as one of the most important functionalities of BMSs. Paper III addresses the control-oriented modeling and analysis of open-cathode fuel cells in order to provide a comprehensive system-level understanding of their real-time operation and to establish a basis for control design. Finally, in Paper IV a feedback controller, combined with a novel output-injection observer, is designed and implemented for open-cathode fuel cell temperature control. It is shown that temperature control not only ensures the fuel cell temperature reference is properly maintained, but, along with an uncertainty estimator, can also be used to adaptively stabilize the output voltage --Abstract, page iv
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