Algebraic observer design for PEM fuel cell system

© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In this paper, the concept of the algebraic observer is applied to Proton Exchange Membrane Fuel Cell (PEMFC) system. The aim of the proposed observer is to reconstruct the oxygen excess ratio through estimation of their relevant states in real time from the measurement of the supply manifold air pressure. A robust differentiation method is adopted to estimate in finite-time the time derivative of the supply manifold air pressure. Then, the relevant states are reconstructed based on the output-state inversion model. The objective is to minimize the use of extra sensors in order to reduce the costs and enhance the system accuracy. The performance of the proposed observer is analyzed through simulations considering measurement noise and different stack-current variations. The results show that the algebraic observer estimates in finite time and robustly the oxygen-excess ratio.Peer ReviewedPostprint (author's final draft

Design of Energy Management System of a PEMFC–Battery– Supercapacitor Hybrid Tramway

In this chapter, a hybrid power system that consists of multiple proton exchange membrane fuel cell (PEMFC) systems, batteries, and supercapacitors (SCs) is developed for a hybrid tramway. Three energy management strategies that included a fuzzy logic control (FLC), an equivalent consumption minimization strategy (ECMS), and a state machine strategy based on droop control (SMS-DC) are utilized to coordinate multiple power sources, avoid the transients and rapid changes of power demand, and achieve high efficiency without degrading the mechanism performance for an energy management system of hybrid tramway. A hybrid system model of tramway is established with commercially available devices, and then the different energy management strategies are evaluated with a real driving cycle of tramway from Turkey. The results compared with these strategies demonstrate that the higher average efficiencies of the tramway, the lower tramway-equivalent hydrogen consumptions, and more efficient use of the batteries and SCs energy are achieved by the SMS-DC. Therefore, the appropriate energy management system for high-power hybrid tramway will improve the hydrogen consumptions of overall hybrid system and the efficiencies of each power source

Real-time backstepping control for fuel cell vehicle using supercapacitors

A key issue of real-time applications is ensuring the operation by taking into account the stability constraints. For multisource vehicles, stability is impacted by the multisource interactions. Backstepping control ensures stable control for most classes of nonlinear systems. Nevertheless, no backstepping control in real time has been yet proposed for multisource vehicles. The objective of this paper is to apply the backstepping control to a multisource vehicle with fuel cell and supercapacitors for real-time implementation. A distribution criterion is used to allocate energy between sources. Experimental results demonstrate that the developed backstepping control can be implemented in real-time conditions. The supercapacitors can thus help the fuel cell to meet the requirements of the load with a guarantee of system stability. © 1967-2012 IEEE

Nonlinear observer design for PEM fuel-cell systems using first-order sliding mode techniques

This paper presents a nonlinear observer design for Proton Exchange Membrane Fuel-Cell (PEMFC) systems. The aim of the proposed observer is to reconstruct the oxygen excess ratio through the estimation of their relevant states in real time from the measurement of the supply manifold air pressure. A First-Order Sliding Mode (FOSM) differentiation method is adopted to estimate, in finite time, the time derivative of the supply manifold air pressure. By means of the output-state inversion model, the relevant states are reconstructed. The objective of the proposed appproach is to minimize the use of additional sensors in order to reduce the costs and enhance the system accuracy. The performance of the proposed observer is analyzed through simulations considering measurement noise and different stack-current variations. The results show that the nonlinear observer properly estimates in finite time and robustly the oxygen excess ratio.Peer ReviewedPostprint (author's final draft

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

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

Advanced Modeling and Research in Hybrid Microgrid Control and Optimization

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

Stratégies de gestion d’énergie pour véhicules électriques et hybride avec systèmes hybride de stockage d’énergie

Les véhicules électriques et hybrides font partie des éléments clés pour résoudre les problèmes de réchauffement de la planète et d'épuisement des ressources en combustibles fossiles dans le domaine du transporte. En raison des limites des différents systèmes de stockage et de conversion d’énergie en termes de puissance et d'énergie, les hybridations sont intéressantes pour les véhicules électriques (VE). Dans cette thèse, deux hybridations typiques sont étudiées • un sous-système de stockage d'énergie hybride combinant des batteries et des supercondensateurs (SC) ; • et un sous-système de traction hybride parallèle combinant moteur à combustion interne et entraînement électrique. Ces sources d'énergie et ces conversions combinées doivent être gérées dans le cadre de stratégies de gestion de l'énergie (SGE). Parmi celles-ci, les méthodes basées sur l'optimisation présentent un intérêt en raison de leur approche systématique et de leurs performances élevées. Néanmoins, ces méthodes sont souvent compliquées et demandent beaucoup de temps de calcul, ce qui peut être difficile à réaliser dans des applications réelles. L'objectif de cette thèse est de développer des SGE simples mais efficaces basées sur l'optimisation en temps réel pour un VE et un camion à traction hybride parallèle alimentés par des batteries et des SC (système de stockage hybride). Les complexités du système étudié sont réduites en utilisant la représentation macroscopique énergétique (REM). La REM permet de réaliser des modèles réduits pour la gestion de l'énergie au niveau de la supervision. La théorie du contrôle optimal est ensuite appliquée à ces modèles réduits pour réaliser des SGE en temps réel. Ces stratégies sont basées sur des réductions de modèle appropriées, mais elles sont systématiques et performantes. Les performances des SGE proposées sont vérifiées en simulation par comparaison avec l’optimum théorique (programmation dynamique). De plus, les capacités en temps réel des SGE développées sont validées via des expériences en « hardware-in-the-loop » à puissances réduites. Les résultats confirment les avantages des stratégies proposées développées par l'approche unifiée de la thèse.Abstract: Electric and hybrid vehicles are among the keys to solve the problems of global warming and exhausted fossil fuel resources in transportation sector. Due to the limits of energy sources and energy converters in terms of power and energy, hybridizations are of interest for future electrified vehicles. Two typical hybridizations are studied in this thesis: • hybrid energy storage subsystem combining batteries and supercapacitors (SCs); and • hybrid traction subsystem combining internal combustion engine and electric drive. Such combined energy sources and converters must be handled by energy management strategies (EMSs). In which, optimization-based methods are of interest due to their high performance. Nonetheless, these methods are often complicated and computation consuming which can be difficult to be realized in real-world applications. The objective of this thesis is to develop simple but effective real-time optimization-based EMSs for an electric car and a parallel hybrid truck supplied by batteries and SCs. The complexities of the studied system are tackled by using Energetic Macroscopic Representation (EMR) which helps to conduct reduced models for energy management at the supervisory level. Optimal control theory is then applied to these reduced models to accomplish real-time EMSs. These strategies are simple due to the suitable model reductions but systematic and high-performance due to the optimization-based methods. The performances of the proposed strategies are verified via simulations by comparing with off-line optimal benchmark deduced by dynamic programming. Moreover, real-time capabilities of these novel EMSs are validated via experiments by using reduced-scale power hardware-in-the-loop simulation. The results confirm the advantages of the proposed strategies developed by the unified approach in the thesis

Recent Technologies and Control Methods for Electric Power Systems in More Electric Aircrafts: A Review

This paper is aimed at discussing the current trends in the design of Electric Power Systems (EPS) architectures which are intended to be implemented in More Electric Aircrafts (MEAs). Various EPS architectures such as HVAC, HVDC, hybrid HVAC/HVDC etc are studied and compared. Various control techniques which are implemented in order to control the EPS are also reviewed and they are compared on the basis of power quality, ease of installation and maintenance, possibility of future expansion of EPS, need of active power filters and so on. On the basis of the evaluation of various EPS architectures, the need of fuel cell installation in the EPS to be used for MEAs is explained and various ways to incorporate the fuel cell in the said EPS are discussed. Further the need of DC to DC converters in the power grid of a MEA is discussed and various possible choices for the topologies of DC to DC converters are compared on the basis of the parameters such as efficiency, transient response, reliability, electromagnetic emissions, size, weight and so on. Moreover, various controllers such as PI controller, PID controller, Sliding Mode Controller etc which can be used for a closed loop control of DC to DC converters are discussed

Robust control strategies for hybrid solid oxide fuel cell systems

Solid Oxide Fuel Cell (SOFC) systems are electrochemical energy conversion devices characterized by the use of solid oxide as the electrolyte. They operate at high temperatures (between 800± ¡ 1000±C). Mitigating fuel starvation and improving load-following capability of SOFCs are conflicting control objectives. In this thesis, this issue is addressed using a hybrid SOFC ultra-capacitor configuration. The fuel cell is controlled by incorporating a steady-state property of fuel utilization into an input-shaping framework. Two comprehensive control strategies are developed. The first is a Lyapunov-based nonlinear control and the second is a standard H-infinity robust control. Both strategies additionally control the state of charge (SOC) of the ultra-capacitor that provides transient power compensation. A hardware-in-the-loop test-stand is developed where the proposed control strategies are verified. An investigation to improve the hybrid fuel cell system by incorporating a lithium-ion battery as an additional power source is conducted. Combining both battery and ultra-capacitor with a fuel cell is potentially a winning combination especially for high power applications. A novel SOC estimation method for lithium-ion battery is investigated. Based on the combined ultra-capacitor battery hybrid system, a lyapunov-Based nonlinear control strategy is designed

Sizing, dynamic modeling and simulation of a solar-wind-hydrogen power system of the MUN explorer autonomous underwater vehicle

In this doctoral research dissertation, sizing, dynamic modeling, and simulation of a solar, wind and hydrogen power system of the MUN Explorer Autonomous Underwater Vehicle (AUV) have been explored, integrating a Polymer Electrolyte Membrane (PEM) fuel cell into an existing power system which uses a lithium ion battery as the main source of its energy. Along with the batteries the integrated fuel cell was designed to power the MUN Explorer AUV to increase its hours of operation and reduce the number of batteries. The installation of hydrogen and oxygen gas tanks next to the batteries augmented the buoyancy force underwater. An electrolyzer powered by solar and wind energy, was used to produce hydrogen. The produced hydrogen was then stored in gas cylinders. A PEM fuel cell was used to consume the hydrogen gas inside the MUN Explorer AUV. The fuel cell was connected to a DC / DC Boost Converter to increase the output voltage from 24 to 48 V, as required by the battery and DC motor. It was proposed that the renewable excess energy be stored and used for recharging a battery. The system design is based on MUN Explorer data sheets and system dynamic simulation results. The system sizing was performed using Hybrid Optimization Model for Electrical Renewable (HOMER) software. The dynamic model was then built in MATLAB / Simulink environment to give a better understanding of the system’s behaviour. A PI controller was applied in the dynamic model to maintain the operating conditions such as motor speed, DC bus voltage and the load torque. The simulation of dynamic models and experiment results in hydrogen production and consumption were compared and found to have an acceptable error. The results from hydrogen production systems (solar and wind) were measured to be 7.0 ml/min. The PI controller provided satisfactory results in terms of maintaining the same operating conditions of the MUN Explorer AUV with a fuel cell