A “smarter grid” is expected to be more flexible and more reliable than traditional electric power grids. Among technologies required for the “smarter grid” deployment, this dissertation presents a sustainable microgrid and a spatial and temporal model of plug-in electric vehicle charging demand for the “smarter grid”. First, this dissertation proposes the dynamic modeling technique and operational strategies for a sustainable microgrid primarily powered by wind and solar energy resources. Multiple-input dc-dc converters are used to interface the renewable energy sources to the main dc bus. The intended application for such a microgrid is an area in which there is interest in achieving a sustainable energy solution, such as a telecommunication site or a residential area. Wind energy variations and rapidly changing solar irradiance are considered in order to explore the effect of such environmental variations to the intended microgrid. The proposed microgrid can be operated in an islanded mode in which it can continue to generate power during natural disasters or grid outages, thus improving disaster resiliency of the “smarter grid”. In addition, this dissertation presents the spatial and temporal model of electric vehicle charging demand for a rapid charging station located near a highway exit. Most previous studies have assumed a fixed charging location and fixed charging time during the off-peak hours for anticipating electric vehicle charging demand. Some other studies have based on limited charging scenarios at typical locations instead of a mathematical model. Therefore, from a distribution system perspective, electric vehicle charging demand is still unidentified quantity which may vary by space and time. In this context, this study proposes a mathematical model of electric vehicle charging demand for a rapid charging station. The mathematical model is based on the fluid dynamic traffic model and the M/M/s queueing theory. Firstly, the arrival rate of discharged vehicles at a charging station is predicted by the fluid dynamic model. Then, charging demand is forecasted by the M/M/s queueing theory with the arrival rate of discharged vehicles. The first letter M of M/M/s indicates that discharged vehicles arrive at a charging station with the Poisson distribution. The second letter M denotes that the time to charge each EV is exponentially distributed, and the third letter s means that there are s identical charging pumps at a charging station. This mathematical model of charging demand may allow grid’s distribution planners to anticipate charging demand at a specific charging station. / text

Ultrasonic welding is one of the leading technologies for joining multiple, thin sheets of dissimilar materials, such as copper and aluminum, for automotive lithium-ion batteries. The performance of ultrasonic welds, particularly the fatigue life, however, has not been well studied. In this work, a theoretical fatigue life model for ultrasonically welded joints was developed using continuum damage mechanics. In the model, the damage variable was defined as a function of the increase of the joint electrical resistance, resulting in an electrical resistance-based fatigue life prediction model. The fatigue model contains two constants to be determined with experimental data, depending on different fatigue loads and joint properties. As an application, the fatigue life model was validated for Al-Cu lithium-ion battery tab joints. Mechanical fatigue tests were performed under various stress loading conditions for welds made using different welding parameters. It is shown that the developed model can be used to predict the remaining life of the ultrasonically welded battery tab joints for electric and hybrid electric vehicles by monitoring the electrical resistance change. In addition, thermal and electrical fatigue tests were performed for Al-Cu battery tab welds using simulated operating conditions of electrical vehicles. These included temperature cycling between -40 and 90 °C and current cycling of 0 to 10 A. All the tests were conducted on individual weld joints. The results showed that the thermal and electrical loads imposed insignificant effect on the electrical resistance of the battery tab joints. / text

Energy storage is a crucial condition for both transportation purposes and for the use of electricity. Flywheels can be used as actual energy storage but also as power handling device. Their high power capacity compared to other means of storing electric energy makes them very convenient for smoothing power transients. These occur frequently in vehicles but also in the electric grid. In both these areas there is a lot to gain by reducing the power transients and irregularities. The research conducted at Uppsala university and described in this thesis is focused on an all-electric propulsion system based on an electric flywheel with double stator windings. The flywheel is inserted in between the main energy storage (assumed to be a battery) and the traction motor in an electric vehicle. This system has been evaluated by simulations in a Matlab model, comparing two otherwise identical drivelines, one with and one without a flywheel. The flywheel is shown to have several advantages for an all-electric propulsion system for a vehicle. The maximum power from the battery decreases more than ten times as the flywheel absorbs and supplies all the high power fluxes occuring at acceleration and braking. The battery delivers a low and almost constant power to the flywheel. The amount of batteries needed decreases whereas the battery lifetime and efficiency increases. Another benefit the flywheel configuration brings is a higher energy efficiency and hence less need for cooling. The model has also been used to evaluate the flywheel functionality for an electric grid application. The power from renewable intermittent energy sources such as wave, wind and current power can be smoothened by the flywheel, making these energy sources more efficient and thereby competitive with a remaining high power quality in the electric grid.

Darbo tikslas – ištirti superkondensatorių naudą elektros transporto priemonių dinaminėms savybėms. Darbo uždaviniai: apžvelgti akumuliatorių ir superkondensatorių įkrovimo/iškrovimo charakteristikas bei naujausių superkondensatorių technologijas; išanalizuoti kombinuotos baterijų ir superkondensatorių lygiagretaus darbo įkrovimo/iškrovimo sistemą; Apskaičiuoti elektromobilių dinamines charakteristikas naudojant skirtingus ar kombinuotus elektros energijos šaltinius ir palyginant su vidaus degimo varikliu varomo automobilio dinaminėmis charakteristikomis. Buvo nustatyta, kad superkondensatorių panaudojimas tikslingas tik elektromobilyje, kurio maksimalus greitis yra iki 100 km/h. Jei elektromobilio maksimalus greitis didesnis, baterijų atiduodama galia pakankamai didelė įsibėgėti neviršijant baterijų rekomenduojamo srovės stiprio. Vien šiandieniniais superkondensatoriais varomas elektromobilis negali pakeisti automobilio varomo vidaus degimo varikliu, nes maksimalus atstumas, kurį elektromobilis gali nuvažiuoti yra tik 6,3 km. Vien grafeno superkondensatoriais varomo elektromobilio maksimalus greitis prilygsta benzinu varomo automobilio maksimaliam 233,6 km/h greičiui. Toks elektromobilis būtų penkis kartus galingesnis ir nuvažiuotų tokį patį atstumą, kaip vien baterijomis varomas elektromobilis. / The main objective of the work is to explore the benefits of supercapacitor for electric vehicle dynamic characteristics. The goal of work: to overview the battery and supercapacitor charge / discharge characteristics and the latest technologies of supercapacitors, to analyze the combination of batteries and supercapacitors in “Buck – Boost” converter, Calculate electric dynamic characteristics using different or combined electric energy sources, and compare to an internal combustion engine driven vehicle dynamic characteristics. It was found that the supercapacitor is purposive only electric vehicle, with a maximum speed of 100 km / h. If the top speed of electric car is over 100 km/h then a total power output of batteries is large enough to accelerate and not to exceed the recommended current of the battery. Electric vehicle powered today’s supercapacitors can not replace the internal combustion engine because the maximum distance you can travel is only 6.3 km. graphene supercapacitors driven electric vehicle maximum speed is equivalent gasoline-powered car for a maximum of 233.6 km / h. This electric car is five times more powerful and driven the same distance as the battery-powered electric vehicle.

The effects of climate change along with shifts in social demands have opened up commercial possibilities for new and innovative green technology. At the head of this trend is research into new technologies for Hybrid Electric Vehicles (HEVs) and Battery Electric Vehicles (BEVs). These technologies would provide for more environmentally friendly transportation; however their current performance when compared to Internal Combustion Engine (ICE) Vehicles has led to slow adoption rates. One of the key factors that could help to increase the performance of HEVs and BEVs lies in improvement of the battery systems. Through proper thermal management of the batteries the range and performance of these vehicles can be improved, helping to increase the performance of the vehicles. This study looks at improving the thermal management of the battery system by generating more efficient cooling plates. These cooling plates are set between battery cells and contain channels that coolant is pumped through. Through optimization of these cooling channels, the efficiency of the cooling plates with regards to the average temperature and standard deviation of temperature of the battery cell can both be increased. The power required to run the cooling system can also be reduced by reducing the pressure losses associated with the cooling plate. Numerical optimization on three models of cooling plates was performed. The models were based on multi-inlet and outlet curved channel systems, with one model constructed using arcs and the other two using 90 degree angles. Results showed that improvements of up to 80% could be made depending on the objective functions when compared to an initial design through optimization, with straight channels providing 8% more efficient designs in terms of pressure losses over curved designs, and curved designs providing 6% more efficient designs in terms of average temperature. Analysis on the effects of varying the mass flow rate, heat flux and inlet temperature was also conducted to evaluate their effects on the optimized geometries. This study has practical applications in helping to develop new cooling plates for commercial use through implementation of the generated design features and optimization algorithms. / Thesis (Master, Mechanical and Materials Engineering) -- Queen's University, 2012-09-27 15:09:12.261

This thesis evaluates an electric vehicle with four independently-controlled in-wheel electric motors. The electric vehicle investigated in this work requires a main con- troller that not only coordinates with each individual motor drive controller, but is also needed to distribute torque and power to each in-wheel motor. The controller adjusts the speed of each motor to the driving conditions according to the require- ments and emulates the behavior of a mechanical di erential. Then, in addition to the electronic di erential controller, a simple yet robust control strategy for maximiz- ing traction force between tire and road is developed and presented. Moreover, the controller continuously senses the yaw rate and prevents over- and under-steering by adjusting the torque on the right or left wheels. Simulation and experimental results validate the proposed strategy.

Orientador: José Antenor Pomilio / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação / Made available in DSpace on 2018-08-25T15:20:15Z (GMT). No. of bitstreams: 1 PerezParedes_MarinaGabrielaSadith_M.pdf: 3442654 bytes, checksum: 6edc07da0803fe3dff86c9aa224d8ee3 (MD5) Previous issue date: 2013 / Resumo: Esta dissertação estuda a aplicação de frenagem regenerativa em veículos elétricos, em ação conjunta com freio de atrito. Considera-se o caso de um veículo leve com um motor de indução acionado por inversor. O processo de regeneração ocorre sempre que a velocidade comandada pelo inversor for menor do que a velocidade mecânica. O fluxo reverso de energia é absorvido pela fonte presente no lado CC do inversor. A partir de um único comando de frenagem o sistema é capaz de utilizar os freios elétrico e mecânico de acordo com o melhor procedimento para a recuperação da energia cinética do veículo, respeitando as limitações dos dispositivos eletrônicos e garantindo a frenagem, de acordo com a desaceleração determinada pelo condutor do veículo. Resultados de simulação computacional e em um arranjo experimental permitem analisar e verificar a sistemática proposta / Abstract: This thesis studies the application of regenerative braking in electric vehicles in joint action with friction brake. It is considered the case of a light vehicle with an induction motor driven by an inverter. The regeneration process occurs whenever the commanded speed to the inverter is less than the mechanical speed. The reverse flow of energy was able to be absorbed by the source available on the inverter DC side. From a single braking command, the system was able to use the electrical and mechanical brakes according to the best procedure for recovering the vehicle's kinetic energy, respecting the limitations of electronic devices and ensuring the braking according to the deceleration determined by the vehicle driver. Results of computer simulation and in an experimental setup allows to analyze and validate the methodology / Mestrado / Energia Eletrica / Mestra em Engenharia Elétrica

The development of electric vehicle (EV) greatly promotes building a green and sustainable society. The new technology also brings new challenges. With the penetration of electric vehicles, the charging demands are increasing, and how to efficiently coordinate EVs' charging activities is a major challenge and sparks numerous research efforts. In this dissertation, we investigate the EV charging scheduling problem under the public charging and home charging scenarios from different perspectives. First, we investigate the EV charging scheduling problem under a charging station scenario by jointly considering the revenue of the charging station and the service requirements of charging customers. We first propose an admission control algorithm to guarantee the non-flexible charging requirements of all admitted EVs being satisfied before their departure time. Then, a utility based charging scheduling algorithm is proposed to maximize the profit for the charging station. With the proposed charging scheduling algorithm, a win-win situation is achieved where the charging station enjoys a higher profit and the customer enjoys more cost savings. Second, we investigate the EV charging scheduling problem under a parking garage scenario, aiming to promote the total utility of the charging operator subject to the time-of-use pricing. By applying the analyzed battery charging characteristic, an adaptive utility oriented scheduling algorithm is proposed to achieve a high profit and low task declining probability for the charging operator. We also discuss a reservation mechanism for the charging operator to mitigate the performance degradation caused by charging information mismatching. Third, we investigate the EV charging scheduling problem of a park-and-charge system with the objective to minimize the EV battery degradation cost during the charging process while satisfying the battery charging characteristic. A vacant charging resource allocation algorithm and a dynamic power adjustment algorithm are proposed to achieve the least battery degradation cost and alleviate the peak power load, which is beneficial for both the customers and charging operator. Fourth, we investigate the EV charging scheduling problem under a residential community scenario. By jointly considering the charging energy and battery performance degradation during the charging process, we propose a utility maximization problem to optimize the gain of the community charging network. A utility maximized charging scheme is correspondingly proposed to achieve the utility optimality for the charging network. In summary, the research outcomes of the dissertation can contribute to the effective management of the EV charging activities to meet increasing charging demands. / Graduate

Stricter regulations and evolving environmental concerns have been exerting ever-increasing pressure on the automotive industry to produce low carbon vehicles that reduce emissions. As a result, increasing numbers of alternative powertrain architectures have been released into the marketplace to address this need. However, with a myriad of possible alternative powertrain configurations, which is the most appropriate type for a given vehicle class and duty cycle? To that end, comparative analyses of powertrain configurations have been widely carried out in literature; though such analyses only considered limited types of powertrain architectures at a time. Collating the results from these literature often produced findings that were discontinuous, which made it difficult for drawing conclusions when comparing multiple types of powertrains. The aim of this research is to propose a novel methodology that can be used by practitioners to improve the methods for comparative analyses of different types of powertrain architectures. Contrary to what has been done so far, the proposed methodology combines an optimisation algorithm with a Modular Powertrain Structure that facilitates the simultaneous approach to optimising multiple types of powertrain architectures. The contribution to science is two-folds; presenting a methodology to simultaneously select a powertrain architecture and optimise its component sizes for a given cost function, and demonstrating the use of multi-objective optimisation for identifying trade-offs between cost functions by powertrain architecture selection. Based on the results, the sizing of the powertrain components were influenced by the power and energy requirements of the drivecycle, whereas the powertrain architecture selection was mainly driven by the autonomy range requirements, vehicle mass constraints, CO2 emissions, and powertrain costs. For multi-objective optimisation, the creation of a 3-dimentional Pareto front showed multiple solution points for the different powertrain architectures, which was inherent from the ability of the methodology to concurrently evaluate those architectures. A diverging trend was observed on this front with the increase in the autonomy range, driven primarily by variation in powertrain cost per kilometre. Additionally, there appeared to be a trade-off in terms of electric powertrain sizing between CO2 emissions and lowest mass. This was more evident at lower autonomy ranges, where the battery efficiency was a deciding factor for CO2 emissions. The results have demonstrated the contribution of the proposed methodology in the area of multi-objective powertrain architecture optimisation, thus addressing the aims of this research.

Power demands will increase day-by-day because of widely adopting of Plug-in Electric Vehicles (PEVs) in the world and growing population. Finding and managing additional power resources for upcoming demands is a challenge. Renewable power is one of the alternatives. However, to manage and control renewable resources, we need suitable Energy Storage System (ESS). PEVs have a large battery pack that is used mainly to supply electric motor. Moreover, PEV battery could be used as an ESS to store power at a certain time and use it at another time. Nevertheless, it can play the same role with electric power grids, so it can store power at a time and return it at another time. This role might help the grid to meet the growing demands. In this thesis, we propose a charging and discharging coordination algorithm that effectively addresses the problem of power demand on peak time using the PEV’s batteries as a backup power storage, namely, Flexible Charging and Discharging (FCD) algorithm. The FCD algorithm aims to manage high power demands at peak times using Vehicle to Home (V2H) technologies in Smart Grid and PEV’s batteries. Intensive computer simulation is used to test FCD algorithm. The FCD algorithm shows a significant reduction in power demands and total cost, in proportion to two other algorithms, without affecting the performance of the PEV or the flexibility of PEV owner’s trip schedule.