Performance testing and system characterization. DOE Hybrid Test Vehicle phase III: final report.

Energy Department, Washington, D.C.

Energy Management of a Battery-Ultracapacitor Hybrid Energy Storage System in Electric Vehicles

Electric vehicle (EV) batteries tend to have accelerated degradation due to high peak power and harsh charging/discharging cycles during acceleration and deceleration periods, particularly in urban driving conditions. An oversized energy storage system (ESS) can meet the high power demands; however, it suffers from increased size, volume and cost. In order to reduce the overall ESS size and extend battery cycle life, a battery-ultracapacitor (UC) hybrid energy storage system (HESS) has been considered as an alternative solution. In this work, we investigate the optimized configuration, design, and energy management of a battery-UC HESS. One of the major challenges in a HESS is to design an energy management controller for real-time implementation that can yield good power split performance. We present the methodologies and solutions to this problem in a battery-UC HESS with a DC-DC converter interfacing with the UC and the battery. In particular, a multi-objective optimization problem is formulated to optimize the power split in order to prolong the battery lifetime and to reduce the HESS power losses. This optimization problem is numerically solved for standard drive cycle datasets using Dynamic Programming (DP). Trained using the DP optimal results, an effective real-time implementation of the optimal power split is realized based on Neural Network (NN). This proposed online energy management controller is applied to a midsize EV model with a 360V/34kWh battery pack and a 270V/203Wh UC pack. The proposed online energy management controller effectively splits the load demand with high power efficiency and also effectively reduces the battery peak current. More importantly, a 38V-385Wh battery and a 16V-2.06Wh UC HESS hardware prototype and a real-time experiment platform has been developed. The real-time experiment results have successfully validated the real-time implementation feasibility and effectiveness of the real-time controller design for the battery-UC HESS. A battery State-of-Health (SoH) estimation model is developed as a performance metric to evaluate the battery cycle life extension effect. It is estimated that the proposed online energy management controller can extend the battery cycle life by over 60%.

Modeling of Electric Hybrid Vehicles based on Innovative Energy Storage Technologies for Super Sports Cars Applications

Today, the contribution of the transportation sector on greenhouse gases is evident. The fast consumption of fossil fuels and its impact on the environment has given a strong impetus to the development of vehicles with better fuel economy. Hybrid electric vehicles fit into this context with different targets, starting from the reduction of emissions and fuel consumption, but also for performance and comfort enhancement. Vehicles exist with various missions; super sport cars usually aim to reach peak performance and to guarantee a great driving experience to the driver, but great attention must also be paid to fuel consumption. According to the vehicle mission, hybrid vehicles can differ in the powertrain configuration and the choice of the energy storage system. Lamborghini has recently invested in the development of hybrid super sport cars, due to performance and comfort reasons, with the possibility to reduce fuel consumption. This research activity has been conducted as a joint collaboration between the University of Bologna and the sportscar manufacturer, to analyze the impact of innovative energy storage solutions on the hybrid vehicle performance. Capacitors have been studied and modeled to analyze the pros and cons of such solution with respect to batteries. To this aim, a full simulation environment has been developed and validated to provide a concept design tool capable of precise results and able to foresee the longitudinal performance on regulated emission cycles and real driving conditions, with a focus on fuel consumption. In addition, the target of the research activity is to deepen the study of hybrid electric super sports cars in the concept development phase, focusing on defining the control strategies and the energy storage system’s technology that best suits the needs of the vehicles. This dissertation covers the key steps that have been carried out in the research project.

Development of predictive energy management strategies for hybrid electric vehicles supported by connectivity

Nowadays, the spreading of the air pollution crisis enhanced by greenhouse gases emission is leading to the worsening of the global warming. In this context, the transportation sector plays a vital role, since it is responsible for a large part of carbon dioxide production. In order to address these issues, the present thesis deals with the development of advanced control strategies for the energy efficiency optimization of plug-in hybrid electric vehicles (PHEVs), supported by the prediction of future working conditions of the powertrain. In particular, a Dynamic Programming algorithm has been developed for the combined optimization of vehicle energy and battery thermal management. At this aim, the battery temperature and the battery cooling circuit control signal have been considered as an additional state and control variables, respectively. Moreover, an adaptive equivalent consumption minimization strategy (A-ECMS) has been modified to handle zero-emission zones, where engine propulsion is not allowed. Navigation data represent an essential element in the achievement of these tasks. With this aim, a novel simulation and testing environment has been developed during the PhD research activity, as an effective tool to retrieve routing information from map service providers via vehicle-to-everything connectivity. Comparisons between the developed and the reference strategies are made, as well, in order to assess their impact on the vehicle energy consumption. All the activities presented in this doctoral dissertation have been carried out at the Green Mobility Research Lab} (GMRL), a research center resulting from the partnership between the University of Bologna and FEV Italia s.r.l., which represents the industrial partner of the research project.

Simulated Annealing Approach Applied to the Energy Resource Management Considering Demand Response for Electric Vehicle

The aggregation and management of Distributed Energy Resources (DERs) by an Virtual Power Players (VPP) is an important task in a smart grid context. The Energy Resource Management (ERM) of theses DERs can become a hard and complex optimization problem. The large integration of several DERs, including Electric Vehicles (EVs), may lead to a scenario in which the VPP needs several hours to have a solution for the ERM problem. This is the reason why it is necessary to use metaheuristic methodologies to come up with a good solution with a reasonable amount of time. The presented paper proposes a Simulated Annealing (SA) approach to determine the ERM considering an intensive use of DERs, mainly EVs. In this paper, the possibility to apply Demand Response (DR) programs to the EVs is considered. Moreover, a trip reduce DR program is implemented. The SA methodology is tested on a 32-bus distribution network with 2000 EVs, and the SA results are compared with a deterministic technique and particle swarm optimization results.

System Investigation for Hybrid Electric Vehicle

A hybrid electric vehicle is a fast-growing concept in the field of vehicle industry. Nowadays two global problems make manufactures to develop such systems. These problems are: the growing cost of a fuel and environmental pollution. Also development of controlled electric drive with high control accuracy and reliability allows improving of vehicle drive characteristics. The objective of this Diploma Thesis is to investigate the possibilities of electrical drive application for new principle of parallel hybrid vehicle system. Electric motor calculations, selection of most suitable control system and other calculations are needed. This work is not final work for such topic. Further investigation with more precise calculations, modeling, measurements and cost calculations are needed to answer the question if such system is efficient.

Comparative Analysis of Alternative Hybrid Systems for Automotive Applications

The main objective of this work was to investigate the impact of different hybridization concepts and levels of hybridization on fuel economy of a standard road vehicle where both conventional and non-conventional hybrid architectures are treated exactly in the same way from the point of view of overall energy flow optimization. Hybrid component models were developed and presented in detail as well as the simulations results mainly for NEDC cycle. The analysis was performed on four different parallel hybrid powertrain concepts: Hybrid Electric Vehicle (HEV), High Speed Flywheel Hybrid Vehicle (HSF-HV), Hydraulic Hybrid Vehicle (HHV) and Pneumatic Hybrid Vehicle (PHV). In order to perform equitable analysis of different hybrid systems, comparison was performed also on the basis of the same usable system energy storage capacity (i.e. 625kJ for HEV, HSF and the HHV) but in the case of pneumatic hybrid systems maximal storage capacity was limited by the size of the systems in order to comply with the packaging requirements of the vehicle. The simulations were performed within the IAV Gmbh - VeLoDyn software simulator based on Matlab / Simulink software package. Advanced cycle independent control strategy (ECMS) was implemented into the hybrid supervisory control unit in order to solve power management problem for all hybrid powertrain solutions. In order to maintain State of Charge within desired boundaries during different cycles and to facilitate easy implementation and recalibration of the control strategy for very different hybrid systems, Charge Sustaining Algorithm was added into the ECMS framework. Also, a Variable Shift Pattern VSP-ECMS algorithm was proposed as an extension of ECMS capabilities so as to include gear selection into the determination of minimal (energy) cost function of the hybrid system. Further, cycle-based energetic analysis was performed in all the simulated cases, and the results have been reported in the corresponding chapters.

Optimal Supervisory Control of Hybrid Vehicles

Hybrid vehicles (HV), comprising a conventional ICE-based powertrain and a secondary energy source, to be converted into mechanical power as well, represent a well-established alternative to substantially reduce both fuel consumption and tailpipe emissions of passenger cars. Several HV architectures are either being studied or already available on market, e.g. Mechanical, Electric, Hydraulic and Pneumatic Hybrid Vehicles. Among the others, Electric (HEV) and Mechanical (HSF-HV) parallel Hybrid configurations are examined throughout this Thesis. To fully exploit the HVs potential, an optimal choice of the hybrid components to be installed must be properly designed, while an effective Supervisory Control must be adopted to coordinate the way the different power sources are managed and how they interact. Real-time controllers can be derived starting from the obtained optimal benchmark results. However, the application of these powerful instruments require a simplified and yet reliable and accurate model of the hybrid vehicle system. This can be a complex task, especially when the complexity of the system grows, i.e. a HSF-HV system assessed in this Thesis. The first task of the following dissertation is to establish the optimal modeling approach for an innovative and promising mechanical hybrid vehicle architecture. It will be shown how the chosen modeling paradigm can affect the goodness and the amount of computational effort of the solution, using an optimization technique based on Dynamic Programming. The second goal concerns the control of pollutant emissions in a parallel Diesel-HEV. The emissions level obtained under real world driving conditions is substantially higher than the usual result obtained in a homologation cycle. For this reason, an on-line control strategy capable of guaranteeing the respect of the desired emissions level, while minimizing fuel consumption and avoiding excessive battery depletion is the target of the corresponding section of the Thesis.

Controllable assembly of graphene hybrid materials and their application in energy storage and conversion

Hybrid Elektrodenmaterialien (HEM) sind der Schlüssel zu grundlegenden Fortschritten in der Energiespeicherung und Systemen zur Energieumwandlung, einschließlich Lithium-Ionen-Batterien (LiBs), Superkondensatoren (SCs) und Brennstoffzellen (FCs). Die faszinierenden Eigenschaften von Graphen machen es zu einem guten Ausgangsmaterial für die Darstellung von HEM. Jedoch scheitern traditionelle Verfahren zur Herstellung von Graphen-HEM (GHEM) scheitern häufig an der fehlenden Kontrolle über die Morphologie und deren Einheitlichkeit, was zu unzureichenden Grenzflächenwechselwirkungen und einer mangelhaften Leistung des Materials führt. Diese Arbeit konzentriert sich auf die Herstellung von GHEM über kontrollierte Darstellungsmethoden und befasst sich mit der Nutzung von definierten GHEM für die Energiespeicherung und -umwandlung. Die große Volumenausdehnung bildet den Hauptnachteil der künftigen Lithium-Speicher-Materialien. Als erstes wird ein dreidimensionaler Graphen Schaumhybrid zur Stärkung der Grundstruktur und zur Verbesserung der elektrochemischen Leistung des Fe3O4 Anodenmaterials dargestellt. Der Einsatz von Graphenschalen und Graphennetzen realisiert dabei einen doppelten Schutz gegen die Volumenschwankung des Fe3O4 bei dem elektrochemischen Prozess. Die Leistung der SCs und der FCs hängt von der Porenstruktur und der zugänglichen Oberfläche, beziehungsweise den katalytischen Stellen der Elektrodenmaterialien ab. Wir zeigen, dass die Steuerung der Porosität über Graphen-basierte Kohlenstoffnanoschichten (HPCN) die zugängliche Oberfläche und den Ionentransport/Ladungsspeicher für SCs-Anwendungen erhöht. Desweiteren wurden Stickstoff dotierte Kohlenstoffnanoschichten (NDCN) für die kathodische Sauerstoffreduktion (ORR) hergestellt. Eine maßgeschnittene Mesoporosität verbunden mit Heteroatom Doping (Stickstoff) fördert die Exposition der aktiven Zentren und die ORR-Leistung der metallfreien Katalysatoren. Hochwertiges elektrochemisch exfoliiertes Graphen (EEG) ist ein vielversprechender Kandidat für die Darstellung von GHEM. Allerdings ist die kontrollierte Darstellung von EEG-Hybriden weiterhin eine große Herausforderung. Zu guter Letzt wird eine Bottom-up-Strategie für die Darstellung von EEG Schichten mit einer Reihe von funktionellen Nanopartikeln (Si, Fe3O4 und Pt NPs) vorgestellt. Diese Arbeit zeigt einen vielversprechenden Weg für die wirtschaftliche Synthese von EEG und EEG-basierten Materialien.

Practical design considerations of cascaded hybrid battery storage systems

The high cost of batteries has led to investigations in using second-life ex-transportation batteries for grid support applications. Vehicle manufacturers currently all have different specifications for battery chemistry, arrangement of cells, capacity and voltage. With anticipated new developments in battery chemistry which could also affect these parameters, there are, as yet, no standards defining parameters in second life applications. To overcome issues relating to sizing and to prevent future obsolescence for the rest of the energy storage system, a cascaded topology with an operating envelope design approach has been used to connect together modules. This topology offers advantages in terms of system reliability. The design methodology is validated through a set of experimental results resulting in the creation of surface maps looking at the operation of the converter (efficiency and inductor ripple current). The use of a pre-defined module operating envelope also offers advantages for developing new operational strategies for systems with both hybrid battery energy systems and also hybrid systems including other energy sources such as solar power.

MILITARY VEHICLE OPTIMIZATION AND CONTROL

It is remarkable that there are no deployed military hybrid vehicles since battlefield fuel is approximately 100 times the cost of civilian fuel. In the commercial marketplace, where fuel prices are much lower, electric hybrid vehicles have become increasingly common due to their increased fuel efficiency and the associated operating cost benefit. An absence of military hybrid vehicles is not due to a lack of investment in research and development, but rather because applying hybrid vehicle architectures to a military application has unique challenges. These challenges include inconsistent duty cycles for propulsion requirements and the absence of methods to look at vehicle energy in a holistic sense. This dissertation provides a remedy to these challenges by presenting a method to quantify the benefits of a military hybrid vehicle by regarding that vehicle as a microgrid. This innovative concept allowed for the creation of an expandable multiple input numerical optimization method that was implemented for both real-time control and system design optimization. An example of each of these implementations was presented. Optimization in the loop using this new method was compared to a traditional closed loop control system and proved to be more fuel efficient. System design optimization using this method successfully illustrated battery size optimization by iterating through various electric duty cycles. By utilizing this new multiple input numerical optimization method, a holistic view of duty cycle synthesis, vehicle energy use, and vehicle design optimization can be achieved.

Particle swarm optimization based approaches to vehicle-to-grid scheduling

This paper addresses the problem of energy resources management using modern metaheuristics approaches, namely Particle Swarm Optimization (PSO), New Particle Swarm Optimization (NPSO) and Evolutionary Particle Swarm Optimization (EPSO). The addressed problem in this research paper is intended for aggregators’ use operating in a smart grid context, dealing with Distributed Generation (DG), and gridable vehicles intelligently managed on a multi-period basis according to its users’ profiles and requirements. The aggregator can also purchase additional energy from external suppliers. The paper includes a case study considering a 30 kV distribution network with one substation, 180 buses and 90 load points. The distribution network in the case study considers intense penetration of DG, including 116 units from several technologies, and one external supplier. A scenario of 6000 EVs for the given network is simulated during 24 periods, corresponding to one day. The results of the application of the PSO approaches to this case study are discussed deep in the paper.

An optimal scheduling problem in distribution networks considering V2G

This paper addresses the problem of energy resource scheduling. An aggregator will manage all distributed resources connected to its distribution network, including distributed generation based on renewable energy resources, demand response, storage systems, and electrical gridable vehicles. The use of gridable vehicles will have a significant impact on power systems management, especially in distribution networks. Therefore, the inclusion of vehicles in the optimal scheduling problem will be very important in future network management. The proposed particle swarm optimization approach is compared with a reference methodology based on mixed integer non-linear programming, implemented in GAMS, to evaluate the effectiveness of the proposed methodology. The paper includes a case study that consider a 32 bus distribution network with 66 distributed generators, 32 loads and 50 electric vehicles.

Eines interactives per l'aprenentatge de la dinà mica i el control dels convertidors de potència

El projecte s'ha centrat en el disseny i desenvolupament de laboratoris virtuals per a la docència del dispositius i mètodes de gestió d’energia. Això s’ha realitzat a dos nivells clarament diferenciats, el primer grup de laboratoris correspon als convertidors electrònics de potencia i el segon grup de laboratoris correspon a un conjunt de casos d’aplicacions concretes. En el primer grup es descriu el detall del funcionament dels diferents elements mentre que en el segon els descriuen les idees i conceptes bàsics de funcionament. Els laboratoris virtuals de convertidors electrònics de potència inclouen el convertidor elevador (boost), el convertidor reductor (buck), i convertidors acobladors magnèticament. Aquestes permeten estudiar el comportament dinàmica des d’un punt de vista commutat o bé promitjat, les aplicacions incorporen també la possibilitat de sintonitzar els controladors. Aquestes aplicacions han estat desenvolupades per ser un complement per les sessions de pràctiques presencials. Els laboratoris virtuals d’aplicacions, inclouen els sistema de transport metropolità, el vehicle híbrid i els sistemes de gestió de talls transitoris en el subministrament d’energia principalment. Aquestes laboratoris permeten introduir els estudiants de forma qualitativa en els diferents conceptes i tècniques emprades en els sistemes de generació, transport i transformació d’energia. Totes les aplicacions han estat desenvolupades emprant Easy JAVA Simulations, aquesta eina permet desenvolupar laboratoris multiplataforma fàcilment distribuïbles a través d’internet.

Dieselmoottorisen kaupunkilinja-auton muuttaminen sarjahybridiajoneuvoksi

Tutkimus on pohjustusta Lappeenrannan teknillisen yliopiston Green Campus–hankkeessa tulevaisuudessa mahdollisesti rakennettavalle Cambus–hybridibussille ja siihen liittyvälle muutostyölle. Tässä tutkimuksessa käsitellään asioita, joita kohdataan kun tavallinen dieselkäyttöinen linja–auto muutetaan hybridiajoneuvoksi. Työ sisältää teoriaosuuden, jossa esitellään peruskomponentteja esimerkiksi moottoreiden ja energianvarastointitekniikoiden osalta sekä uusimpia kehityskohteita polttomoottoreiden osalta. Tutkimuksessa on myös vertailtu erilaisia hybridivaihtoehtoja sekä käsitelty mm. tasauspyörästön välityssuhteen ja vaihteiston vaikutusta bussin teoreettiseen suorituskykyyn. Tehdyn tutkimustyön perusteella on hahmoteltu eräs mahdollinen sarjahybridibussin voimansiirtolinja esimerkkikomponentteineen. Tutkimuksessa esitetään myös laskelmia järjestelmän teoreettisesta polttoaineenkulutuksesta jarrutusenergian talteenotto huomioiden perinteiseen kaupunkilinja-autoon verrattuna.