Real-Time Implementation of a New MPPT Control Method for a DC-DC Boost Converter Used in a PEM Fuel Cell Power System

settings Open AccessArticle Real-Time Implementation of a New MPPT Control Method for a DC-DC Boost Converter Used in a PEM Fuel Cell Power System by Mohamed Derbeli 1,2,* [OrcID] , Oscar Barambones 1 [OrcID] , Mohammed Yousri Silaa 1 [OrcID] and Cristian Napole 1 [OrcID] 1 Engineering School of Vitoria, University of the Basque Country UPV/EHU, Nieves Cano 12, 1006 Vitoria, Spain 2 National Engineering School of Gabes, University of Gabes, Omar Ibn-Elkhattab, 6029 Gabes, Tunisia * Author to whom correspondence should be addressed. Actuators 2020, 9(4), 105; https://doi.org/10.3390/act9040105 Received: 30 August 2020 / Revised: 25 September 2020 / Accepted: 10 October 2020 / Published: 16 October 2020 (This article belongs to the Section High Torque/Power Density Actuators) Download PDF Browse Figures Abstract Polymer electrolyte membrane (PEM) fuel cells demonstrate potential as a comprehensive and general alternative to fossil fuel. They are also considered to be the energy source of the twenty-first century. However, fuel cell systems have non-linear output characteristics because of their input variations, which causes a significant loss in the overall system output. Thus, aiming to optimize their outputs, fuel cells are usually coupled with a controlled electronic actuator (DC-DC boost converter) that offers highly regulated output voltage. High-order sliding mode (HOSM) control has been effectively used for power electronic converters due to its high tracking accuracy, design simplicity, and robustness. Therefore, this paper proposes a novel maximum power point tracking (MPPT) method based on a combination of reference current estimator (RCE) and high-order prescribed convergence law (HO-PCL) for a PEM fuel cell power system. The proposed MPPT method is implemented practically on a hardware 360W FC-42/HLC evaluation kit. The obtained experimental results demonstrate the success of the proposed method in extracting the maximum power from the fuel cell with high tracking performance.This work was partially supported by Eusko Jaurlaritza/Gobierno Vasco [grant number SMAR3NAK ELKARTEK KK-2019/00051]; the Provincial Council of Alava (DFA) [grant number CONAVAUTIN 2] (Collaboration Agreement)

A Robust Maximum Power Point Tracking Control Method for a PEM Fuel Cell Power System

Taking into account the limited capability of proton exchange membrane fuel cells (PEMFCs) to produce energy, it is mandatory to provide solutions, in which an efficient power produced by PEMFCs can be attained. The maximum power point tracker (MPPT) plays a considerable role in the performance improvement of the PEMFCs. Conventional MPPT algorithms showed good performances due to their simplicity and easy implementation. However, oscillations around the maximum power point and inefficiency in the case of rapid change in operating conditions are their main drawbacks. To this end, a new MPPT scheme based on a current reference estimator is presented. The main goal of this work is to keep the PEMFCs functioning at an efficient power point. This goal is achieved using the backstepping technique, which drives the DC-DC boost converter inserted between the PEMFC and the load. The stability of the proposed algorithm is demonstrated by means of Lyapunov analysis. To verify the ability of the proposed method, an extensive simulation test is executed in a Matlab-Simulink (TM) environment. Compared with the well-known proportional-integral (PI) controller, results indicate that the proposed backstepping technique offers rapid and adequate converging to the operating power point.The authors are very grateful to the UPV/EHU for its support through the projects PPGA18/04 and to the Basque Government for its support through the project ETORTEK KK-2017/00033. The authors would also like to thank the Tunisian Government for its support through the research unit UR11ES82

Design and Implementation of High Order Sliding Mode Control for PEMFC Power System

Fuel cells are considered as one of the most promising methods to produce electrical energy due to its high-efficiency level that reaches up to 50%, as well as high reliability with no polluting effects. However, scientists and researchers are interested more in proton exchange membrane fuel cells (PEMFCs). Thus, it has been considered as an ideal solution to many engineering applications. The main aim of this work is to keep the PEMFC operating at an adequate power point. To this end, conventional first-order sliding mode control (SMC) is used. However, the chattering phenomenon, which is caused by the SMC leads to a low control accuracy and heat loss in the energy circuits. In order to overcome these drawbacks, quasi-continuous high order sliding mode control (QC-HOSM) is proposed so as to improve the power quality and performance. The control stability is proven via the Lyapunov theory. The closed-loop system consists of a PEM fuel cell, a step-up converter, a DSPACE DS1104, SMC and QC-HOSM algorithms and a variable load resistance. In order to demonstrate the effectiveness of the proposed control scheme, experimental results are compared with the conventional SMC. The obtained results show that a chattering reduction of 84% could be achieved using the proposed method.This work was partially supported by Eusko Jaurlaritza/Gobierno Vasco [grant number SMAR3NAK ELKARTEK KK-2019/00051]; the Provincial Council of Alava (DFA) [grant number CONAVAUTIN 2] (Collaboration Agreement)

Control of Proton Exchange Membrane Fuel Cell System

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

A Novel Adaptive PID Controller Design for a PEM Fuel Cell Using Stochastic Gradient Descent with Momentum Enhanced by Whale Optimizer

This paper presents an adaptive PID using stochastic gradient descent with momentum (SGDM) for a proton exchange membrane fuel cell (PEMFC) power system. PEMFC is a nonlinear system that encounters external disturbances such as inlet gas pressures and temperature variations, for which an adaptive control law should be designed. The SGDM algorithm is employed to minimize the cost function and adapt the PID parameters according to the perturbation changes. The whale optimization algorithm (WOA) was chosen to enhance the adaptive rates in the offline mode. The proposed controller is compared with PID stochastic gradient descent (PIDSGD) and PID Ziegler Nichols tuning (PID-ZN). The control strategies’ robustnesses are tested under a variety of temperatures and loads. Unlike the PIDSGD and PID-ZN controllers, the PIDSGDM controller can attain the required control performance, such as fast convergence and high robustness. Simulation results using Matlab/Simulink have been studied and illustrate the effectiveness of the proposed controller.The authors wish to express their gratitude to the Basque Government through the project EKOHEGAZ (ELKARTEK KK-2021/00092), to the Diputación Foral de Álava (DFA) through the project CONAVANTER, and to the UPV/EHU through the project GIU20/063 for supporting this work

Hydrogen at the rooftop: Compact CPV-hydrogen system to convert sunlight to hydrogen

Despite being highest potential energy source, solar intermittency and low power density make it difficult for solar energy to compete with the conventional power plants. Highly efficient concentrated photovoltaic (CPV) system provides best technology to be paired with the electrolytic hydrogen production, as a sustainable energy source with long term energy storage. However, the conventional gigantic design of CPV system limits its market and application to the open desert fields without any rooftop installation scope, unlike conventional PV. This makes CPV less popular among solar energy customers. This paper discusses the development of compact CPV-Hydrogen system for the rooftop application in the urban region. The in-house built compact CPV system works with hybrid solar tracking of 0.1° accuracy, ensured through proposed double lens collimator based solar tracking sensor. With PEM based electrolyser, the compact CPV-hydrogen system showed 28% CPV efficiency and 18% sunlight to hydrogen (STH) efficiency, for rooftop operation in tropical region of Singapore. For plant designers, the solar to hydrogen production rating of 217 kWhe/kgH2 has been presented with 15% STH daily average efficiency, recorded from the long term field operation of the syste

DC Microgrid Modeling and Control in Islanded Mode

Microgrid is new emerging power distribution infrastructures, in smart grid architectures that has the potential to solve major problems arising from distributed generation. Microgrid is defined as the cluster of multiple distributed generators (DGs) that supply electrical energy to consumers with lower power loss. The realization of demand response, efficient energy management, high capability of Distributed Energy Resources (DERs), and high-reliability of electricity delivery leads to a successful Microgrid. In this thesis, DC Microgrid in islanded mode was modelled and controlled and its performance is tested for 24 hours period. The different distributed energy generation systems used are photovoltaic (PV) system, battery energy storage (BESS) system and fuel cell (FC). PV system is modelled by calculating series and shunt resistances of the real life equivalent circuit of the Solar Cell. Four experiments were performed in the Smart Energy lab, RIT Dubai, for the PV systems, to calculate open circuit voltage and short circuit current, to plot the IV characteristics of the PV system, and to track the maximum power point at different irradiances and calculating the daily irradiances. FC modeling was performed in Simulink, the fuel flow was controlled by the output current of the FC to reach the nominal current of 133.3 A and nominal voltage of 45 V. Lithium Ion batteries were used for storing energy generated by the PV system when the supply power exceeds the demand power. Demand power was estimated as the usual daily demand for 24 hours. Controlling these generation systems is performed using converters. Boost Converter used for the PV system was controlled by Maximum Power Point Tracking (MPPT) incremental conductance algorithm to maintain a constant voltage of 300 V at the DC bus despite daily change of the solar power in a day. Boost Buck converter is used to control the charging and discharging processes of the BESS to maintain a constant voltage at the input terminals of the battery to charge it at 130 V and a constant voltage at the DC bus. Boost Converter used for the FC maintained a constant voltage of 100 V

Predictive-TOPSIS-based MPPT for PEMFC Featuring Switching Frequency Reduction

A maximum power point tracking (MPPT) for a proton exchange membrane fuel cell (PEMFC) using a combination of conventional finite control set model predictive control (FCS-MPC) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is proposed in this paper. The key idea is to maximize the power generation from a PEMFC while minimizing the switching frequency of the power converter. The FCS-MPC technique is formulated to track the maximum power of PEMFC highly affected by ever-changing internal parameters. Meanwhile, the TOPSIS algorithm is applied to overcome the potential weaknesses of insulated-gate bipolar transistor (IGBT), which can only withstand a lower switching frequency. In this project, all simulations were run using MATLAB software to display the output power of the PEMFC system. As a result, the proposed predictive-TOPSIS-based MPPT algorithm can track the MPP for various PEMFC parameters within 0.019 s with an excellent accuracy up to 99.11%. The proposed MPPT technique has fast-tracking of the MPP locus, excellent accuracy, and robustness to environmental changes