This research investigates the effects of both a Hybrid Energy Storage System and an Electrified Turbocharger in a consumer performance vehicle. This research also attempts to support the development of a prototype vehicle containing a Hybrid Energy Storage System currently being developed at McMaster University. Using a custom simulation tool developed in Matlab Simulink, Simulink models of each of the technologies were developed to predict the behavior of these subsystems across multiple physical domains. Control modeling, optimization and testing was completed for both systems. In addition, controls modeling for the Hybrid Energy Storage System was integrated with the development effort for a prototype vehicle considering the specifics of real world components. To assess the impact of these technologies on a performance vehicle platform, the simulation tool tested each technology using multiple vehicle variations. Three vehicle variants were developed, representing: a conventional performance hybrid design, a hybrid vehicle containing an electrified turbocharger, and a vehicle containing a Hybrid Energy Storage System. Electrical system peak output power was the vehicle specification held constant between each vehicle variant. Each vehicle variant was simulated against a number of traditional drive cycles representing everyday driving scenarios in an attempt to compare fuel economy while identifying each technologies individual impact on the vehicles performance. Finally, each vehicle variant was simulated using a custom performance drive cycle in a virtual race. Both technologies as assessed and in comparison to a larger battery variant, did not result in improved fuel economies during conventional vehicle driving. Both the Hybrid Energy Storage System and electrified turbocharger demonstrated improved vehicle performance in particular scenarios. / Thesis / Master of Applied Science (MASc) / Electrified vehicles have not typically been viewed as performance vehicles. A recent trend has seen a growing number of manufacturers turn to hybrid and electric powertrains to produce high performing vehicles. However, a performance vehicle's electrical power is conventionally limited by the size and power of its battery, adding weight and cost. Two technologies offer the ability to increase the power of these electrified components without the need for a large battery. First, Hybrid Energy Storage System combines ultra-capacitors and batteries to increase the power density of the system. Second, an Electrified Turbocharger improves the turbo lag of a turbocharged engine and also recovers waste heat energy from the exhaust gases which is then used to propel the vehicle. This research identifies and demonstrates the potential impact these two technologies have when included in an American Muscle Car.

This thesis focuses on the concept, design, and simulation of the Reconfigurable Multi-Source Inverter for EV applications and its effectiveness when combined with a HESS. The current trends in the automotive market, including different vehicle types, and the adoption of electrified vehicles by the public are discussed. The benefits and logistics of different vehicle architectures are analyzed and compared. Hybrid vehicles will be essential in helping transition society from conventional internal combustion engine vehicles to purely electric vehicles. The individual components of these electrified vehicles are reviewed, and common topologies are discussed with the benefits of each system compared. The batteries required for these electric vehicles are costly and require many individual cells in order to operate efficiently. Many hybrids vehicles make use of expensive power electronics, such as DC/DC converters to help boost the operating voltage of the battery pack without adding additional cells. A Reconfigurable Multi-Source Inverter in introduced and its switching structure is explained in depth. Its’ ability to make use of multiple DC sources to create four different voltage levels is outlined and possible modulation techniques are presented. This thesis aims to introduce a novel Reconfigurable Multi-Source Inverter using a Space Vector Pulse Width Modulation (SVPWM) scheme and is further investigated through simulations and with plans for experimental validation on an R-L load. / Thesis / Master of Applied Science (MASc) / One of the main factors affecting the cost of electrified vehicles is the expense of building a high voltage battery pack. Motor’s used in electric vehicle applications typically operate at higher voltages and therefore require large battery pack or costly power electronics to step the voltage of the pack up to a suitable operating level. A Reconfigurable Multi-Source Inverter uses a combination of two sources to create different voltage levels. This novel inverter can be used to maximize the voltage of smaller packs to help reduce the overall cost of vehicle electrification.

Numerous countries are trying to reach almost 100\% renewable penetration. Variable renewable energy (VRE), for instance wind and PV, will be the main provider of the future grid. The efforts to decrease the greenhouse gasses are promising on the current remarkable growth of grid connected photovoltaic (PV) capacity. This thesis provides an overview of the presented techniques, standards and grid interface of the PV systems in distribution and transmission level. This thesis reviews the most-adopted grid codes which required by system operators on large-scale grid connected Photovoltaic systems. The adopted topologies of the converters, the control methodologies for active - reactive power, maximum power point tracking (MPPT), as well as their arrangement in solar farms are studied. The unique L(LCL)2 filter is designed, developed and introduced in this thesis. This study will help researchers and industry users to establish their research based on connection requirements and compare between different existing technologies. Another, major aspect of the work is the development of Virtual Inertia Emulator (VIE) in the combination of hybrid energy storage system addressing major challenges with VRE implementations. Operation of a photovoltaic (PV) generating system under intermittent solar radiation is a challenging task. Furthermore, with high-penetration levels of photovoltaic energy sources being integrated into the current electric power grid, the performance of the conventional synchronous generators is being changed and grid inertial response is deteriorating. From an engineering standpoint, additional technical measures by the grid operators will be done to confirm the increasingly strict supply criteria in the new inverter dominated grid conditions. This dissertation proposes a combined virtual inertia emulator (VIE) and a hybrid battery-supercapacitor-based energy storage system . VIE provides a method which is based on power devices (like inverters), which makes a compatible weak grid for integration of renewable generators of electricity. This method makes the power inverters behave more similar to synchronous machines. Consequently, the synchronous machine properties, which have described the attributes of the grid up to now, will remain active, although after integration of renewable energies. Examples of some of these properties are grid and generator interactions in the function of a remote power dispatch, transients reactions, and the electrical outcomes of a rotating bulk mass. The hybrid energy storage system (HESS) is implemented to smooth the short-term power fluctuations and main reserve that allows renewable electricity generators such as PV to be considered very closely like regular rotating power generators. The objective of utilizing the HESS is to add/subtract power to/from the PV output in order to smooth out the high frequency fluctuations of the PV power, which may occur due to shadows of passing cloud on the PV panels. A control system designed and challenged by providing a solution to reduce short-term PV output variability, stabilizing the DC link voltage and avoiding short term shocks to the battery in terms of capacity and ramp rate capability. Not only could the suggested system overcome the slow response of battery system (including dynamics of battery, controller, and converter operation) by redirecting the power surges to the supercapacitor system, but also enhance the inertial response by emulating the kinetic inertia of synchronous generator.

In this thesis, a capacitor semi-active hybrid energy storage system for electric vehicle is proposed. A DC-to-DC bi-directional converter is required to couple the supercapacitor to the system DC bus. Through literature reviews, it was decided that a dual-bridge resonant converter with HF transformer isolation is best suited for the hybrid energy storage application. First, a dual-bridge series resonant converter with capacitive output filter is proposed. Modified gating scheme is applied to the converter instead of the 50% duty cycle gating scheme. Comparing to the 50% duty cycle gating scheme where only four switches work in ZVS, The modified gating scheme allows all eight switches working in ZVS at design point with high load level, and seven switches working in ZVS under other conditions. Next, a dual-bridge LCL-type series resonant converter with capacitive output filter is proposed. Similarly, the modified gating scheme is applied to the converter. This converter shows further improvement in ZVS ability. Operating principles, design examples, simulation results and experimental results of the two newly proposed converters are also presented. In the last part of the thesis, a capacitor semi-active hybrid energy storage system is built to test if the proposed converters are compatible to the system. The dual-bridge LCL-type series resonant converter is placed in parallel to the supercapacitor. The simulation and experimental results of the hybrid energy storage system match closely to the theoretical waveforms. / Graduate

No description available.

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)

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.