With the increase in the world energy demand and environmental incentives, renewable energy sources (RES) need to determine their place as some of the primary power sources in future power systems. However, due to uncertain energy production, renewable energy sources cause unbalance in the power system due to the unsynchronized supply and electricity demand. The intermittent power production causes undesired power fluctuation, affecting the power quality and reliability of the power source. Energy storage is one solution that is debated to increase the reliability of renewable energy production. This thesis aims to model and simulate hybrid energy storage system (HESS), constructed of hydrogen and ultracapacitor energy storage, to investigate different operation strategies for everyday use and crises. The two different energy storage technologies complement each other, where hydrogen fuel cells can produce power for long periods of time while the ultracapacitor can quickly maintain the balance of production and consumption of electricity for a short instance. The HESS showed promising results for emergency power supply and supported service operation strategies. In case of a power shortage, the HESS could cover for the disconnected production. The ultracapacitor proved to be a suitable component due to its ability to support the shortcomings of a hydrogen energy storage system. Moreover, the HESS could meet the requirements to deliver support services. However, further studies have to be done to investigate how the HESS can deliver multiple support services to increase profit and help maintain the power system's balance and security.

Electrified vehicles (EVs) with a large electric energy storage system (ESS), including Plug-in Hybrid Electric Vehicles (PHEVs) and Pure Electric Vehicles (PEVs), provide a promising solution to utilize clean grid energy that can be generated from renewable sources and to address the increasing environmental concerns. Effectively extending the operation life of the large and costly ESS, thus lowering the lifecycle cost of EVs presents a major technical challenge at present. A hybrid energy storage system (HESS) that combines batteries and ultracapacitors (UCs) presents unique energy storage capability over traditional ESS made of pure batteries or UCs. With optimal energy management system (EMS) techniques, the HESS can considerably reduce the frequent charges and discharges on the batteries, extending their life, and fully utilizing their high energy density advantage. In this work, an intelligent energy allocation (IEA) algorithm that is based on Q-learning has been introduced. The new IEA method dynamically generate sub-optimal energy allocation strategy for the HESS based on each recognized trip of the EV. In each repeated trip, the self-learning IEA algorithm generates the optimal control schemes to distribute required current between the batteries and UCs according to the learned Q values. A RBF neural networks is trained and updated to approximate the Q values during the trip. This new method provides continuously improved energy sharing solutions better suited to each trip made by the EV, outperforming the present passive HESS and fixed-cutoff-frequency method. To efficiently recognize the repeated trips, an extended Support Vector Machine (e-SVM) method has been developed to extract significant features for classification. Comparing with the standard 2-norm SVM and linear 1-norm SVM, the new e-SVM provides a better balance between quality of classification and feature numbers, and measures feature observability. The e-SVM method is thus able to replace features with bad observability with other more observable features. Moreover, a novel pattern classification algorithm, Inertial Matching Pursuit Classification (IMPC), has been introduced for recognizing vehicle driving patterns within a shorter period of time, allowing timely update of energy management strategies, leading to improved Driver Performance Record (DPR) system resolution and accuracy. Simulation results proved that the new IMPC method is able to correctly recognize driving patterns with incomplete and inaccurate vehicle signal sample data. The combination of intelligent energy allocation (IEA) with improved e-SVM feature extraction and IMPC pattern classification techniques allowed the best characteristics of batteries and UCs in the integrated HESS to be fully utilized, while overcoming their inherent drawbacks, leading to optimal EMS for EVs with improved energy efficiency, performance, battery life, and lifecycle cost. / Graduate

Technology advancements enable and encourage higher system electrifications in various applications. More electrified applications need more capable and higher performing sources of energy in terms of power delivery, power regeneration, and energy capacity. For example, in electric, hybrid electric, and plug-in hybrid electric vehicle applications (EVs, HEVs, and PHEVs), the power and energy ratings of the vehicle energy storage system (ESS) have a direct impact on the vehicle performance. Many researchers investigated and studied various aspects of hybrid energy storage systems (HESS) wherein multiple ESSs are combined together to share system loads, increase ESS capabilities, and cycle life. Various configurations and their application specific topologies were also proposed by other researchers; the potential of HESS has been proven to be very promising. In this research, the goal is to present the theory of a HESS configuration that has not been discovered thus far. This HESS configuration is called a series-parallel reconfigurable HESS (SPR-HESS) since it is capable of recombining multiple storage systems into different series, parallel, or series-parallel configurations, via power electronic converters, to accommodate different operation modes and load requirements. Simulations, as well as experimental verifications, are presented in this thesis. / Thesis / Doctor of Philosophy (PhD)

In this thesis, a physics-based single particle modeling is presented to analyze a proposed direct coupled hybrid energy storage modules using lithium-ion battery and ultracapacitor. Firstly, a state of the art for the energy storage system in the electrified vehicles are summarized. Several energy storage elements including lead-acid battery, nickel-metal hydride battery, lithium-ion battery, ultracapacitor, and lithium-ion capacitor are reviewed. Requirements of the energy storage systems in electric, hybrid electric, and plug-in hybrid electric vehicles are generalized. Typical hybrid energy storage system topologies are also reviewed. Moreover, these energy storage elements and hybrid energy storage system topologies are compared to the requirements of the energy storage systems in terms of specific power and specific energy. Secondly, the performance of different battery balancing topologies, including line shunting, ring shunting, synchronous flyback, multi-winding, and dissipative shunting are analyzed based on a linear programming methodology. As a traction battery in an electric or plug-in electric vehicle, high voltage lithium-ion packs are typically configured in a modular fashion, therefore, the analysis considers the balancing topologies at module level and cell level and focuses on minimum balancing time, minimum plug-in charge time, minimum energy loss, and component counts of every balancing topology for the entire battery pack. Thirdly, different modeling techniques for the lithium-ion battery and ultracapacitor are presented. One of the main contributions of this thesis is the development of a physics-based single particle modeling embedded with a solid-electrolyte interface growth model for a lithium-ion battery in battery management system. This development considers the numerical solution of diffusion equation, cell level quantities, parametrization method, effects of number of shells in a spherical particle, SOC-SOH estimation algorithms, and aging effects. The accuracy of the modeling is validated by experimental results of a Panasonic NCR18650A lithium-ion battery cell. Fourthly, the physics-based modeling is applied to analyze the performance of a proposed direct coupled hybrid energy storage module topology based on the Panasonic NCR18650A lithium-ion battery and Maxwell BCAP0350 ultracapacitor. There are many ways to directly connect battery cells and ultracapacitor cells in a module which would influence the performance of the module. The results show that a module has 9 cells in a battery string and 14 cells in an ultracapacitor string can obtain the highest power capability and utilize the most of the energy in an ultracapacitor. More ultracapacitor strings connected in parallel would increase the power density but reduce the energy density. Moreover, the simulation and experimental results indicate that the direct coupled hybrid modules can extend the operating range and slow the capacity fade of lithium-ion battery. An SOC-SOH estimation algorithm for the hybrid module is also developed based on the physics-based modeling. Finally, a pack design methodology is proposed to meet U.S. Advanced Battery Consortium LLC PHEV-40, power-assist, and 48V HEV performance targets for the battery packs or the proposed direct coupled topologies. In order to explore replacement tradeoffs between the battery and ultracapacitor, a case study of the direct coupled topologies is presented. From the case study, ultracapacitors enhance the power capability for short term pulse power and marginally reduce the cost of an entire energy storage system. Moreover, the hybrid module topologies can keep a relatively long all-electric range when the batteries degrade. / Dissertation / Doctor of Philosophy (PhD)

Solving the key issue of sustainability of battery-powered sensors continues to attract significant research attention. The prevailing theme of this research is to address this concern using energy-efficient protocols based on a form of simple cooperative transmission (CT) called the opportunistic large arrays (OLAs), and intelligent exploitation of energy harvesting and hybrid energy storage systems (HESSs). The two key contributions of this research, namely, OLA with transmission threshold (OLA-T) and alternating OLA-T (A-OLA-T), offer an signal-to-noise ratio (SNR) advantage (i.e., benefits of diversity and array (power) gains) in a multi-path fading environment, thereby reducing transmit powers or extending range. Because these protocols do not address nodes individually, the network overhead remains constant for high density networks or nodes with mobility. During broadcasting across energy-constrained networks, while OLA-T saves energy by limiting node participation within a single broadcast, A-OLA-T optimizes over multiple broadcasts and drains the the nodes in an equitable fashion. Another important contribution of this research is the design and analysis of a novel routing metric called communications using HESS (CHESS), which extends the rechargeable battery (RB)-life by relaying exclusively with supercapacitor (SC) energy, and is asymptotically optimal with respect to the number of nodes in the network.

In diesem Beitrag wird eine Betriebsstrategie für einen hybriden Energiespeicher vorgestellt, die sich der Vorhersage zukünftiger Fahrzustände durch ein autonomes Fahrzeug bedient. Dies ermöglicht ein zusätzliches Verringern der Verluste im Vergleich zu herkömmlichen Strategien, die keine Vorhersagen verwenden. Um diese Funktionen umzusetzen, wurden drei Hierarchieebenen definiert. Die oberste enthält die Energiestrategie und bestimmt den langfristigen Ladestandverlauf des Kondensators mit Hilfe der Vorhersagen. Sie gibt der Leistungsstrategie in der mittleren Ebene einen Sollladestand und eine Zielzeit vor, zu der dieser Ladestand erreicht werden soll. Die Leistungsstrategie ist als modellprädiktive Regelung ausgeführt, die den Zielladegrad in einem Toleranzband führt und die Verluste des Energiespeichersystems minimiert. Die unterste Hierarchieebene enthält die Leistungsregelung des verwendeten DC/DC-Wandlers. Diese stellt die Kondensatorleistung nach der Vorgabe durch die Leistungsstrategie ein. Mit Hilfe dieses Ansatzes und einer Vorausschau von maximal 12 s konnten die Verluste im Vergleich zu einer regelbasierten Strategie ohne Vorausschau um 12 % verringert werden. Im Vergleich zu einer global optimierten Lösung, die mittels einer Dynamischen Programmierung erreicht wurde, erzeugt sie 8 % mehr Verluste. / This paper presents an operating strategy for a hybrid energy storage system using the prediction of future driving conditions by an autonomous vehicle. This allows to reduce the losses compared to conventional strategies that do not use predictions. To implement these functions, three hierarchy levels have been defined. The top level is the energy strategy and determines the long-term state of charge of the capacitor using the predictions. It gives the power strategy, the middle level, a target charge level and a target time at which this state of charge should be reached. The power strategy determines the current power distribution using a model predictive approach and stationary loss optimization. The lowest hierarchical level is the power control of the DC/DC converter used. This adjusts the capacitor power according to the specification of the power strategy. With the help of this approach and a forecast of maximum 12 s, the losses could be reduced by12 % compared to a rule-based strategy without a forecast. In comparison to a globally optimized solution achieved by dynamic programming, the new strategy generates 8 % more losses.

Le sujet de thèse aborde la quantification du flux de puissance parcourant les différents systèmes de conversion d'énergie statiques et dynamiques pour aboutir aux éléments de stockage de nature chimique / électrostatique / mécanique lors d'un freinage hybride récupératif brusque issu d’un véhicule électrique à traction avant. Le véhicule électrique est équipé de deux ensembles intégrés moteur-roues indépendants. Le côté commande des convertisseurs et des machines électriques sera aussi traité. La problématique concernera les cas de freinage régénératif brusque imposant des contraintes électriques et mécaniques élevées aux éléments de conversion d'énergie et de stockage. L'outil de simulation adopté est le logiciel Matlab/Simulink®. Un modèle assez fin du véhicule électrique utilisé sera développé afin de pouvoir simuler le comportement du véhicule conformément à la distribution des forces de freinage délivrée par le système de répartition et de quantification des forces de freinage. Une étude de la cinématique et de la dynamique du véhicule selon les différents états de route sera aussi examiné. Cette étude sera utilisée à posteriori dans la formulation des lois de distribution des forces de freinage. Les moteurs utilisés sont de type synchrones à aimants permanents intérieurs. L'objectif est d'assurer un couple électrique de freinage élevé à hautes vitesses de conduite du véhicule. A cette fin, la commande optimale de ces moteurs sera basée sur une nouvelle méthode de génération des courants de références assumant ainsi un couple régénératif élevé et donc une amélioration de l'énergie récupérée. Le système de stockage sera mixte et comportera une batterie Li-Ion et des cellules de supercondensateurs afin de réduire les contraintes sur la batterie et prolonger ainsi sa durée de vie. La structure de puissance de ce système sera analysée ainsi que le système de commande proposé du hacheur à 3 niveaux interfaçant l'ultracapacité avec le bus DC. Une résistance de freinage commandée par un régulateur pseudo-cascade sera aussi intégrée afin de réduire, si nécessaire, les contraintes sur la batterie. L'évaluation et la répartition des forces de freinage sur les quatre roues du véhicule en fonction de l'état de la route sont des éléments clés pour la stabilité du véhicule lors du freinage. La méthode de distribution et de quantification des forces de freinage proposée devra maintenir cette stabilité, répondre aux normes internationales et tirer profit de la présence des moteur-roues à l'avant du véhicule afin de maximiser l'énergie récupérée. Les travaux ont été étendus pour inclure une étude comparative avec un système de stockage contenant un élément de stockage à énergie cinétique comme source d'énergie secondaire pour un véhicule en opération de freinage et de traction. La thèse est le point de départ d'une collaboration de recherche entre l'IFSTTAR /Satie et le département de Génie Electrique du Cnam - Liban, centre associé au Conservatoire National des Arts et Métiers (Paris - France). / The thesis will address the quantification of power flow going through the different energy static and dynamic conversion systems to attain the chemical / electrostatic / mechanical storage elements during a hybrid regenerative brutal braking of a front-wheel driven electric vehicle. The electric vehicle is equipped by two integrated wheel-motors independent sets. The control of the converters and electrical machines is also treated. The problematic concerns the brutal regenerative braking case imposing high electrical and mechanical constraints on energy conversion and storage elements. The simulation tool adopted is Matlab/Simulink®. A detailed model of the used electric vehicle has been developed in order to be able to simulate the vehicle behavior with respect to the braking forces distribution delivered by the repartition and quantification of braking forces system. A study of the kinematics and dynamics of the vehicle according to different road types will be also considered. This study will be used retrospectively in the formulation of the braking forces distribution laws. The motors used are interior permanent magnet synchronous type. The objective is to ensure high electrical braking torque at high driving speeds of the vehicle. To this end, the optimal control of these motors will be based on a new current references generation method assuming then a high regenerative torque and therefore an improvement in the recovered energy. The hybrid storage system includes a Li-Ion battery and supercapacitors cells to reduce stress on the battery and to extend its life. The power structure of the system will be analyzed as well as the 3-level DC/DC converter interfacing the ultracapacitor with the DC bus proposed control system. A braking resistor controlled by a pseudo- cascaded controller will also be integrated to reduce, if necessary, the constraints on the battery. The evaluation and distribution of braking forces on the four wheels depending on road conditions are key elements for the stability of the vehicle during braking. The method of distribution and quantification of braking forces proposed should maintain this stability , meet international standards and take advantage of the presence of wheel motors in the front of the vehicle to maximize the energy recovered. The work has been extended to include a comparative study with a system containing a kinetic energy storage element as a secondary energy source for a braking and traction vehicle operation. The thesis is the starting point of a research collaboration between IFSTTAR / Satie and the Electrical Engineering Department of Cnam- Liban, associated center of the Conservatoire National des Arts et Métiers ( CNAM ), Paris, France.

The popularity of the internal combustion engine (ICE) vehicles has contributed to global warming problem and degradation of air quality around the world. Furthermore, the vehicles??? massive demand on gas has played a role in the depletion of fossil fuel reserves and the considerable rise in the gas price over the past twenty years. Those existing challenges force the auto-industry to move towards the technology development of vehicle electrification. An electrified vehicle is driven by one or more electric motors. And the electricity comes from the onboard energy storage system (ESS). Currently, no single type of green energy source could meet all the requirements to drive a vehicle. A hybrid energy storage system (HESS), as a combination of battery and ultra-capacitor units, is expected to improve the overall performance of vehicles??? ESS. This thesis focuses on the design of HESS and the development of a HESS prototype for electric vehicles (EVs) and hybrid electric vehicles (HEVs). Battery unit (BU), ultra-capacitor unit (UC) and a DC/DC converter interfacing BU and UC are the three main components of HESS. The research work first reviews literatures regarding characteristics of BU, UC and power electronic converters. HESS design is then conducted based on the considerations of power capability, energy efficiency, size and cost optimization. Besides theoretical analysis, a HESS prototype is developed to prove the principles of operation as well. The results from experiment are compared with those from simulation.

No description available.

Ce mémoire porte sur l'étude d'un système de gestion d'énergie électrique dans un système multi-sources soumis à des perturbations exogènes. L'application visée est l'alimentation d'une propulsion hybride diesel/électrique équipée d'un système d'absorption des pulsations de couple. Les perturbations exogènes considérées peuvent être transitoires ou persistantes. Une perturbation transitoire correspond à une variation rapide du couple de charge, due par exemple à une accélération ou une décélération du véhicule. Une perturbation persistante provient du système de compensation des pulsations de couple générées par le moteur thermique. Le premier objectif du contrôle est de maintenir constante la tension du bus continu. Le deuxième objectif est d'absorber dans un système de stockage rapide constitué de super condensateur ces perturbations qui peuvent à terme provoquer une usure prématurée de la batterie. Le troisième objectif est de compenser l'auto-décharge dans le super condensateur en maintenant constante sa tension nominale. Les deux sources (batterie et super condensateur) sont reliées au bus continu par l'intermédiaire de deux convertisseurs boost DC/DC. La commande consiste à piloter les rapports cycliques de chaque convertisseur. C'est un système non linéaire où la commande est multiplicative de l'état. L'approche classique consistant à résoudre les équations Francis-Byrnes-Isidori ne s'applique pas directement dans ce cas où la sortie et la matrice d'interconnection dépendent de la commande. De plus, si cette approche est bien adaptée au rejet de perturbations persistantes, elle montre ces limites pour le rejet de perturbations non persistantes combiné à des objectifs de régulation. Notre approche a consisté à écrire le système sous un formalisme Port-Controlled Hamiltonian et à s'affranchir de la contrainte de la dépendance de la matrice d'interconnection avec la commande en utilisant la théorie des perturbations singulières. La commande du système dégénéré peut ensuite être calculée par une approche passive. Les performances de cette commande ont été testées en simulation et à l'aide d'un banc d'essai expérimental. Les résultats montrent l'efficacité du système d'absorption des différents types de perturbation tout en respectant les deux objectifs de régulation. / This thesis presents the research of energy management in a battery/ultracapacitor hybrid energy storage system with exogenous disturbance in hybrid electric vehicular application. Transient and harmonic persistent disturbances are the two kinds of disturbances considered in this thesis. The former is due to the transient load power demand during acceleration and deceleration, and the latter is introduced from the process of the internal combustion engine torque ripples compensation. Our control objective is to absorb the disturbances causing battery wear via the ultracapacitor, and meanwhile, to maintain a constant DC voltage and to compensate the self-discharge in the ultracapacitor to maintain it operating at the nominal state of charge. The object system is nonlinear due to the multiplicative relation between the input and the state. The traditional approach to solve Francis-Byrnes-Isidori equations cannot be directly applied in this case since the interconnect matrix depends on the control input. Besides, even if this approach is well suited to the rejection of persistent disturbances, it shows the limits for the case of non-persistent disturbances which is also our object. Our contributed control method is realized through a cascade control structure based on the singular perturbation theory. The ultracapacitor current with the fastest motion rate is controlled in the inner fast loop through which we impose the desired dynamic to the system. The reduced system controlled in the outer slow loop is a Hamiltonian system and the controller is designed via interconnection and damping assignment. Simulations and experiments have been carried out to evaluate the control performance. A contrast of the system responses with and without the control algorithm shows that, with the control algorithm, the ultracapacitor effectively absorbs the disturbances; and verifies the effectiveness of the control algorithm.