Dissertationen zum Thema „Electric vehicle sharing“

Theme of the diploma thesis is design of an urban electric car. The main aim of my diploma thesis is to create a concept of a vehicle which will benefit from advantages of utility vehicles and small urban cars . In my thesis I think about using of ecological materials, effective production technologies and requirements for car in present.

Ce sujet s’inscrit dans la continuité des activités de recherche du laboratoire GREAH sur les problématiques de la gestion optimale d’énergie électrique embarqué à bord des véhicules électriques hybrides. En effet, le couplage de plusieurs sources de natures différentes entraîne des problématiques de dimensionnement, de qualité d’énergie et de la durée de vie des éléments interconnectés. Pour les applications de transport par exemple, les principaux facteurs de ces problématiques reposent sur : - les fluctuations de la puissance demandée par la chaîne de propulsion/ traction, la durée de vie limitée des éléments de stockage d’énergie électrique, l’absence de profil de mission standard réaliste et la nécessité d’optimisation de la consommation énergétique du bord. La méthode adéquate pour l’étude des systèmes multi-sources passe par une approche systémique. Cette approche est nécessaire pour établir des modèles comportementaux des sources et des convertisseurs en vue de l'élaboration des stratégies de gestion optimale des flux énergétiques entre les organes. Le premier objectif de la thèse repose sur le développement des modèles de comportement des batteries et supercondensateurs soumis aux contraintes thermiques et électriques spécifiques aux applications de transport. Le second vise le développement de la stratégie de la gestion d’énergie prenant en compte de l’impact de la température et les fluctuations de puissance demandée par la chaîne de propulsion/ traction (charge)<br>The research work presented in this document is a continuation of the GREAH laboratory research activities on the issues of optimal energy management on board of electric and hybrid electric vehicles. Indeed, the coupling of several electrical energy sources with different characteristics causes several issues like energy sources sizing, energy exchange quality and the lifetime of the interconnected elements. In the case of transport applications, the main factors of these problems are based on the high fluctuations in the power required by the propulsion/traction chain; the limited life expectancy of the electrical energy storage elements; the lack of realistic standard mission profile and the need to optimize the electric vehicles energy consumption. The appropriate method for studying the multi-source systems is by using systemic approach. This approach is necessary to establish behavioral models of energies sources and power converters for the development of optimal energy management strategies. The contribution of this thesis is focused on the investigation and the development of energy management strategies considering the electrical energy sources performances and their state of functioning according to the power fluctuations from the propulsion/traction chain, which presents the load in a touristic vehicle

One of the biggest challenges in the development ofautonomous vehicles is to anticipate the behavior of other roadusers. Autonomous vehicles rely on data obtained by on-boardsensors and make decisions accordingly, but this becomes difficultif the sensors are occluded or have limited range. In this reportwe propose an algorithm for connected vehicles in an intersectionto fuse and share sensor data and gain a better estimationof the surrounding environment. The method used for sensorfusion was a Kalman filter and a tracking algorithm, where timedelay from external sensors was considered. Parameters for theKalman filter were decided through measurement of the sensors’variances as well as tuning. It was concluded that the variancesare dependent on the objects’ movements, which means thatconstant parameters for the Kalman filter would not be enoughto make it efficient. However, the tracking and the sensor sharingmade a significant difference in the vehicle’s detection rate whichcould ultimately increase safety in intersections.<br>En av de största utmaningarna för utvecklingen av autonoma fordon är att förutse andra trafikanters beteenden. Autonoma fordon förlitar sig på data från sensorer ombord och fattar beslut i enlighet med informationen från dessa. Detta blir särskilt svårt om sensorerna skyms eller om sensorerna har begränsad räckvidd. I denna rapport föreslår vi en algoritm för delning och optimering av sensordata för autonoma fordon i en vägkorsning för att ge fordonet en så bra uppfattning av omgivningen som möjligt. Metoden som användes för sensorfusion var ett Kalman-filter tilsammans med en spårningsalgoritm där tidsfördröjning av data från externa sensorer togs i beaktning. Parametrarna för Kalman-filtret valdes genom mätning av sensorns varians samt genom trimning. Slutsatsen drogs att varianserna är beroende av objektens rörelsemönster, vilket innebär att konstanta parametrar för Kalman-filtret inte skulle vara tillräckligt för att göra det funktionellt. Spårningen och delningen av sensordata gjorde emellertid en betydande skillnad i andelen upptäckta objekt vilket skulle kunna nyttjas för att öka säkerheten i korsningar.<br>Kandidatexjobb i elektroteknik 2020, KTH, Stockholm

Purpose: The purpose with this project was to evaluate the environmental, social, and economic aspects regarding two climate positive buildings in Västerås municipality in Sweden. The company responsible for the buildings, ETC Bygg AB, has assigned this task tothe research group Future Energy Center (FEC) at Mälardalen University. Method: The buildings was simulated with the programs IDA ICE and PVGIS to obtain the overall energy consumption and building efficiency as well as the PV system potential. Regarding transportation, vehicle and driver statistics was studied and adapted to the case study to estimate the tenant’s climate impact. Results: The results showed that the electricity obtained from the PV system both covers the building’s, and tenant’s estimated yearly electricity consumption, but also with a surplus available for storage or selling. The simulatedresults were compared to several previous studies with similar outcome, but with slightly different results. The tenants need for climate friendly transportation resulted in a suggestion of an electric mobility station consisting of electric cars, mopeds, and bicycles to lower the tenants carbon mitigation, costs, and energy consumption. Conclusions: Conclusions from the study was that the buildings meet both the BBR, and the FEBY18 Gold requirements with their high energy efficiency, as well as that the solar power system most likely will produce enough energy to cover both building, and tenant power consumption. A conclusion can be made that the transition to electric transportation have a potential to save both a considerable amount of energy and money for the tenants, but also the possibility to lower their collective yearly carbon mitigation. Also, that the life in a climate positive building have mostly, if not only, positive impacts on its residents.

Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 61-64).<br>On-demand ride-sharing systems with autonomous vehicles have the potential to enhance the efficiency and reliability of urban mobility. However, existing ride-sharing algorithms are unable to accommodate high capacity vehicles and do not incorporate future predicted demand. This thesis presents a real-time method for high-capacity ride-sharing that scales to a large number of passengers and trips, dynamically generates optimal routes with respect to online demand and vehicle locations, and incorporates predictions of anticipated requests to improve the performance of a network of taxis. We experimentally assess the trade off between fleet size, capacity, waiting time, travel delay, and amount of predictions for low to medium capacity vehicles. We validated the algorithm with over three million taxi rides from the New York City taxi dataset and demonstrate that our approach can service nearly 99% of Manhattan taxi demand using a fleet of only 3000 vehicles (less than 25% of the active taxis in Manhattan).<br>by Alexander James Wallar.<br>S.M.

Cette thèse traite de la conception d’un convertisseur DC / DC destiné aux véhicules électriques et hybrides (2,5 kW, 400V/14V, 250kHz). Dérivé de la topologie LLC à résonance, ce convertisseur bénéficie des nombreux avantages propres à cette structure particulière. C’est ainsi que le prototype réalisé présente un rendement très élevé, une densité de puissance très forte avec des perturbations EMI très réduites. La première partie de cette thèse est consacrée à l’analyse théorique du circuit LLC afin de dégager un modèle de conversion et une stratégie de contrôle adaptée à l’application visée. Afin de conserver un rendement important sur une large plage de charge, une structure basée sur la mise en parallèle de deux modules LLC est proposée. Une nouvelle stratégie de contrôle à deux boucles est également proposée pour équilibrer le courant entre les deux modules. La seconde partie de la thèse fait appel à la simulation et à l’expérimentation. Il s’agit de minimiser la masse et l’encombrement tout en maximisant le rendement. Un composant magnétique spécial est conçu puis dimensionné pour intégrer le transformateur et diverses inductances de résonance. Ce convertisseur met également en œuvre un système de redressement synchrone robuste avec une compensation de phase, un module de puissance avec une résistance thermique très faible et un système de refroidissement efficace par air. Le rendement maximal mesuré est 95%. Le rendement demeure supérieur à 94% sur une plage de puissance s’étalant de 500 W à 2 kW. La densité de puissance est 1W/cm3. La CEM du convertisseur est développée dans cette thèse<br>In this dissertation, a 2.5kW 400V/14V, 250kHz DC/DC converter prototype is developed targeted for electric vehicle/hybrid vehicle applications. Benefiting from numerous advantages brought by LLC resonant topology, this converter is able to perform high efficiency, high power density and low EMI. A first part of this dissertation is the theoretical analysis of LLC: topology analysis, electrical parameter calculation and control strategy. To arrange high output current, this thesis proposes parallel connected LLC structure with developed novel double loop control to realize an equal current distribution. The second part concerns on the system amelioration and efficiency improvement of developed LLC. A special transformer is dimensioned to integrate all magnetic components, and various types of power losses are quantified based on different realization modes and winding geometries to improve its efficiency. This converter also implements a robust synchronous rectification system with phase compensation, a power semiconductor module, and an air-cooling system. The power conversion performance of this prototype is presented and the developed prototype has a peak efficiency of 95% and efficiency is higher than 94% from 500W to 2kW, with a power density of 1W/cm3. The CEM analysis of this converter is also developed in this thesis

Projekt BeMobility: Carsharing mit e-Fahrzeugen Ziel war die Einbindung von Elektroautos in eine Carsharing- Flotte und ihre Integration in multimodale Angebotskonzepte. Nutzergerechte Mobilitätsangebote für urbane Räume wurden entwickelt und im Realbetrieb beurteilt; hierbei wurde die Attraktivität des Carsharing mit e-Autos untersucht. (Kapitel 1) Forschungsansatz: Feldtest mit multimethodaler Begleitforschung Die angewandte Forschung des InnoZ setzte auf eine Kombination verschiedener Methoden. Sowohl vor als auch während des Feldtests wurden potenzielle Nutzer bzw. Testkunden befragt. Dazu wurden die Methoden Lead-User-Integration, Fokusgruppen sowie breite Befragungen gewählt. (Kapitel 2) Interessenten und Testkunden: Männlich, gebildet und ÖV-affin Potenzielle Nutzer und Testkunden sind den sozialen Leitmilieus zuzuordnen. Sie können als sogenannte Lead User gelten. Die Begleitforschung mit über 500 Befragten in vier Teilstudien lässt wichtige Schlüsse auf Akzeptanz und zukünftige Verbreitung von e-Autos im Carsharing zu. (Kapitel 3) Elektrofahrzeuge: Hoher Fahrspaß, aber Reichweite kritisch Die Erwartungen potenzieller Nutzer aus der Vorfeldphase werden im Praxistest teilweise übertroffen. Dies gilt insbesondere für die Fahreigenschaften der Elektrofahrzeuge. Allerdings werden die Erwartungen an Batterie und Laden sowie speziell an die Reichweite nicht erfüllt. (Kapitel 4) Preisbeurteilung: Geringe Aufpreisbereitschaft für e-Carsharing Für elektrisch betriebene Fahrzeuge gibt es auch im Carsharing- Einsatz kaum eine Aufpreisbereitschaft. Für ausgewählte zusätzliche Services besteht auf Nutzerseite aber eine – wenn auch geringe – ergänzende Zahlungsbereitschaft. (Kapitel 5) Mobilitätskarte: Multimodales Angebot gut bewertet Die befragten Nutzer sehen die Kombination von e-Fahrzeugen mit dem öffentlichen Verkehr als wichtig an. Eine Mobilitätskarte, die eine Nutzung von Flinkster, Call a Bike und ÖPNV ermöglichte, wurde im Feldtest positiv bewertet. (Kapitel 6) Akzeptanz: Hohe Kundenbindung, aber geringe Nutzung Die Testnutzer haben eine hohe emotionale Kundenbindung. Diese wurde aber im Regelfall nicht in eine entsprechend häufige Nutzung der Fahrzeuge umgesetzt. Vielnutzer beurteilten die Dienstleistung e-Carsharing signifikant besser als die große Gruppe der Wenignutzer. (Kapitel 7) Mobilitätstypen: Öko-Überzeugte und ÖV-Affine mit Potenzial Auf Basis des Mobilitätstypenansatzes wurde die Stichprobe der potenziellen e-Carsharing-Kunden in verschiedene Typen aufgeteilt. Die höchsten Potenziale ergaben sich bei den Typen „ökologisch überzeugte Radfahrer und Multimodale“ und „pragmatisch orientierte ÖV-Nutzer“. (Kapitel 8)<br>The BeMobility Project: Car-sharing with Electric Vehicles The aim of the project was the insertion of e-vehicles into a carsharing fleet and its subsequent integration with multi-modal public transport offerings. User-friendly urban mobility services were developed and evaluated under real-world conditions. The attractiveness of integrating e-vehicles into an existing car-sharing service was investigated. (Chapter 1) Methodology: Field Trials and Multi-Method Market Research Potential users and customers were interviewed before and during the field trials. In addition, methods such as “lead-user integration”, focus groups, as well as a general survey of user attitudes were chosen. (Chapter 2) Interested Users and Pilot Customers: Male, Highly-Educated, with an Affinity to Public Transport Potential users and customers generally belong to social groups A/B and can be considered ‘lead-in’ users. The survey of more than 500 users in 4 separate market research studies yielded important insights regarding user acceptance and the future spread of e-vehicles in car-sharing fleets. (Chapter 3) E-Vehicles: Positive Driving Experience but Range is Critical Some expectation of potential users from the pre-trial phase were met or even over-fulfilled. This is true in particular with regards to the driving experience associated with e- vehicles. However, the expectation of users with regard to batteries, charging and, specifically, the range of e-cars were not met. (Chapter 4) Pricing Expectations: Low Acceptance of Surcharges for eCar-Sharing There is very low user acceptance of premium pricing for e-vehicles even when they are deployed as part of a car-sharing service. There was some, but relatively low willingness to pay for additional electric mobility services amongst users. (Chapter 5) Smart Mobility Card: Positive User Response to Multi-Modal Services Offerings The users that were surveyed view the combination of e-vehicles with public transport as important. A smart mobility card, which integrated flat-rate access to the Flinkster e-car-sharing service, the Call-a-Bike service and public transport were positively evaluated in the field trials. (Chapter 6) User Acceptance: Emotional Affinity – Low-Frequency Service Use The test users displayed a strong emotional affinity to the mobility service offerings. Routine, high-frequency users judge the electric car-sharing services significantly more positive than the bigger group of low-frequency users. (Chapter 7) User Characteristics: Green Values and Public Transport Affinity Indicate Potential A sample of car-sharing clients was surveyed. The highest user potential was documented in user types “green-conscious cyclists and multi-modal users” and “pragmatic public transport users”. (Chapter 8)

The transport sector is responsible for large amounts of greenhouse gas (GHG) emissions and dueto the continued growth of both passengers and shopping of goods, these emissions are constantlyincreasing. Globally, 50% of the energy within the transport sector is consumed by passenger carsand commercial vans. Hence, sustainability within mobility is of interest and there are severaldifferent ways to address this issue. One possible solution could be car sharing which is a mobilityproduct-service system (PSS) where the private car is replaced by rental cars. However, diffusionof such PSSs is slow, and they are still limited to small niche markets.In this thesis, a dataset from the research project KTH Mobility Pool (KMP) has been analysed.KMP involved a mobility PSS in which electric vehicles (EVs) were integrated with a digitalbooking system, in a shared use system. The users tried out the PSS during a six-months trialperiod. The aim with this thesis was to identify different factors involved in the adoption of newsustainable mobility PSS. During the thesis work additional research questions emerged regardingthe motivation to participate in trials within new sustainable mobility PSS and what impact thetrial had on the users from an environmental perspective. An exploratory and inductive researchapproach was used, with a data analysis influence by grounded theory. Moreover, the thesis workinvolved a mixed method approach since the analysed dataset derived from interviews, surveysand workshops with the KMP users.Through the comparison of the analysed data and existing literature some conclusions could bedrawn. Common motivators for participating in the KMP trial were the opportunity to try out anew technology, saving money and interest in technology, cars and the environment. Five factorsof importance during the trial could be identified: convenience, car ownership, economy,environment, and safety. The impact of the trial on the users was an increased environmentalconsciousness where the users became more aware of their car usage and felt more environmental.Moreover, the trial also gave the users a more positive attitude towards EVs concerning thedevelopment of the EV market, their range and practicality. In conclusion, more research is neededto unfold and establish a complete and holistic view of the adoption of sustainable mobility PSS.However, the findings in this thesis work have answered some of the questions regarding theadoption of sustainable mobility PSS, which can be useful for future trials.<br>Transportsektorn ansvarar för en stor mängd av växthusgasutsläpp och då både antalet passagerareökar och varuhandeln växer, så ökar även utsläppen konstant. Globalt så går 50% av energin inomtransportsektorn till personbilar och kommersiella fordon. Således är hållbarhet inom mänskligtransport viktig och det finns flera sätt att angripa detta dilemma. En möjlig lösning är samåkning,vilket är ett produkt- och tjänstesystem (PSS) där den privata bilen ersätts med en hyrbil. Dock såär spridningen av sådana PSS långsam och de är fortfarande begränsade till små nischmarknader.I detta examensarbete har en datauppsättning från forskningsprojektet KTH Mobility Pool (KMP)analyserats. KMP involverade ett PSS för mänsklig transport, i vilket elbilar var integrerade medett digitalt bokningssystem, i ett gemensamt användningssystem. Detta PSS användes utavanställda på ett tillverkningsföretag till och från jobbet samt under arbetstid, under en sex månaderlång försöksperiod. Målet med examensarbetet var att identifiera de olika faktorer som ärinvolverade i införandet och användandet av nya hållbara PSS för mänsklig transport. Underarbetets gång så dök ytterligare frågeställningar upp angående vad som motiverade användarna atttesta på PSS för mänsklig transport, och hur testprocessen påverkade dem ur miljösynpunkt. Enundersökande och induktiv forskningsmetod användes, med en dataanalys inspirerad av grundadteori. Examensarbetet involverade dessutom en blandning av både kvalitativa och kvantitativametoder eftersom den analyserade datauppsättningen bestod av intervjuer, undersökningar ochworkshops med KMP-användarna.Genom jämförelse av data som analyserats med befintlig litteratur, kunde vissa slutsatser dras.Vanliga motivationsfaktorer för att delta i KMP-projektet var möjligheten att prova på ny teknik,spara pengar och intressen för teknik, bilar och miljö. Fem faktorer av betydelse under försöketkunde identifieras: bekvämlighet, bilägande, ekonomi, miljö och säkerhet. Effekten av försöket påanvändarna var en ökad miljömedvetenhet där användarna blev mer medvetna om sinbilanvändning och kände att de gjorde något gott för miljön. Dessutom gav testet användarna enmer positiv inställning till elbilar angående marknadens utveckling, elbilars räckvidd och deraspraktiska egenskaper. Sammanfattningsvis behövs mer forskning för att utveckla och upprätta enhelhetsbild över de faktorer som är involverade i införandet och användandet av ett hållbart PSSför mänsklig transport. Dock så har detta examensarbete svarat på frågor angående några av dessafaktorer, vilket kan vara användbart för framtida projekt.

碩士<br>國立交通大學<br>運輸與物流管理學系<br>107<br>This study addresses the optimal allocation of a fleet of plug-in electric vehicles (EVs) to the stations of an EV-sharing system at the beginning of each day. The objective is to maximize the profit of the system operator. A multi-layer time-space network flow is adopted to describe the movement of EVs in the system. An optimal fleet allocation model for EV-sharing systems is then developed based on the multi-layer time-space network. This study applies robust optimization and chance constraint techniques to deal with this fleet allocation problem with uncertain and stochastic demands, respectively. While small-scale instances of the problem can be optimally solve using commercial software such as Gurobi, a network decomposition-based mathheuristic is developed to efficiently solve large-scale instances. A set of computational experiments were conducted based on the data provided by the operator of the EV-sharing system deployed in the Sun-Moon Lake National Park in Nantou, Taiwan. The results show that the proposed model is able to effectively generate optimal fleet allocations under determinstic, uncertain an stochastic demand scenarios. Moreover, the model and the heuristic were tested on a larger problem instance extended from the above-mentioned EV-sharing system. The heuristic is able to obtain good quality solutions in a reasonabe amount of time. Sensitivity analyses of the impact of model parameters on solution performances were also conducted. Two measures of effectiveness, robust price and hedge value, were examined to verify the price-paid and value-gained by applying the robust solution. This study contributes to provide a decision support tool that faciliates operators of EV-sharing systems in effectively determing the deployment of their fleets to stations considering uncertain and stochastic demands.

碩士<br>國立成功大學<br>電機工程學系<br>107<br>This thesis assumes that the existing car-sharing parking lots are used as the e-car-sharing parking lots. In order to maintain a certain service level, the e-car-sharing provider will hire employees to relocate the EVs. In this thesis, for mitigate the tidal phenomenon, the e-car-sharing management system assigns users to the pick-up stations and the return stations for relocation of the EVs, according to the simulated users’ rental information and the incentives provided to users. In the thesis, linear programming (LP) is employed to optimize the charging schedule and satisfy the constraints, such as power contract capacity and the charging power limits to minimize the cost of charging power. In the simulation results, the proposed method can mitigate the EVs tidal phenomenon as expected. Moreover, compared with the previous threshold-charging method, the proposed method can dramatically reduce the cost of charging power. In addition, the thesis explores the relationship between the electricity tariff and users’ preference structures. The results reveal that the proposed e-car-sharing management system may support the owner of charging station in selection of the better electricity pricing model for cost minimization.

碩士<br>國立成功大學<br>工業與資訊管理學系碩博士班<br>101<br>Green transportation has aroused more and more attentions recently, especially by the introduction to the concept of vehicle sharing that promotes shared vehicles to conserve energy, reduce carbon emissions, and improve traffic congestions. The bicycle sharing system has become the most poplar vehicle sharing systems so far. However, for some places with bad weather or topography not so convenient for biking, electric scooters (e-scooters) may serve better than bicycles as shared vehicles, since they are as mobile as bicycles, and can move even faster with ease. This thesis focuses on the initial vehicle deployment at each rental site for a public e-scooter sharing system so that service requirement can be achieved with minimum total cost. In particular, we would like to put optimal number of e-scooters at each rental site in the beginning of each day so that the number of satisfied Origin-Destination demands attains specified service level requirement with minimum number of e-scooters. Two linear mixed integer programming models are proposed based on different ways of recharging batteries: one using the charging stations, and the other using the battery exchange stations. Both models assume uncapacitated rental sites, and available e-scooters are distributed fairly in proportion to their historical OD profile. They differ in how the battery power level changes, where an idle e-scooter recharged in a charging station model gains some battery power within a time period, whereas an idle e-scooter in a battery exchange station model does not gain any battery power, unless the power level is insufficient for one time period in which case the battery will be directly swapped to one with full power level. We first solve these models by the Gurobi optimizer, and learned that models asking for lower service level requirements take longer time. We then design two particle swarm optimization algorithms, named PSOCP and PSOBE, respectively for eeach model. These proposed PSO algorithms can calculate good solutions in much shorter time than Gurobi. Finally, we conduct analyses on the effects in the service level requirements and total costs caused by different battery recharging models, as well as the effects caused by different battery consumption and recharging rates.

碩士<br>國立臺灣科技大學<br>工業管理系<br>104<br>Electric Scooter Sharing Systems (ESSS) are environmental friendly transportation alternatives that offer extra benefits to existing bicycle share customers. This study investigates the optimal initial vehicle deployment for a fully automated ESSS implemented in a city with the highest density of universities in Taiwan. With limited empirical demand and usage information, we simulated the critical demand parameters (trip rates, trip lengths and trip durations) and supply parameters (number of e-scooter and charging dock) and then used the method of optimization by simulation to determine the optimal number of e-scooter under different potential demand situations. Sensitivity analyses were also conducted to identify factors that highly affect the service level or the optimal fleet size. Results obtained from this study not only provide some operational guidelines for the full field deployment of the system, but also offer useful insights to managers who are interested in employing similar electric scooter sharing systems.

碩士<br>國立臺灣科技大學<br>資訊管理系<br>102<br>With the huge increasing with economic development, transportation in cars and motorcycles, so does the serious pollution of carbon dioxide and global warming. Therefore carbon reduction is the main topic worldwide in this century. Due to the concept of environmental protection, economic recession and higher oil price, green transportation has aroused more and more attentions recently, 　especially by the introduction to the concept of vehicle sharing that promotes shared vehicles to conserve energy, reduce carbon emissions, and improve traffic congestions. However, for some places with bad weather or topography not so convenient for biking, electric scooters (e-scooters) may serve better than bicycles as shared vehicles, since they are as mobile as bicycles, and can move even faster with ease. In this thesis, we focuses on hybrid public electric scooter sharing systems, a rental station consist of battery charging stations and battery exchange station, we would like to put optimal number of e-scooters and battery in battery exchange station at each rental site in the beginning of each day so that the number of satisfied Origin-Destination demands attains specified service level requirement with minimum number of e-scooters. Thereby service requirement can be achieved with minimum total cost. Based on demand proportion and rental behavior in real world, we propose a integer model to mimic the actual e-scooter traffic between rental sites. and solve it by Particle Swarm Optimization (PSO) algorithm.

碩士<br>淡江大學<br>運輸管理學系碩士班<br>102<br>Electric vehicle sharing service (EV-Sharing), also called self-service electric vehicle rental service, which business model is similar to YouBike Bicycle rental service of Taipei city. The features of EV-Sharing include an ICT-based pick-up and return process, intensive service locations and automatic self-service. Hence, EV-Sharing is suitable for short-range, regional tourist or commuter transportation. The market potential of EV-Sharing is huge because it can not only save transportation cost, but also relieve traffic congestion, improve transport efficiency and reduce private car parking demand. The development of EV-Sharing in Taiwan, however, is in the initial stage of cognition and can be regarded as an emerging transportation service. This study aims at exploring EV-Sharing market segmentation and their user characteristic by using factor analysis, cluster analysis and ordered probit model. The results show that EV-sharing market segmentation in Taipei Metropolitan can be divided into four groups: "conservative group", "price-sensitive group"," environmentally friendly group" and "brave to try group". It is also found that "brave to try group" and "environmentally friendly group" are both the target user groups whose characteristics are male with an average monthly income of at NTD$20,000-40,000 and own at least one private car. They are willing to accept the longest walking time and charging time comparing with other two groups. The "brave to try group" has the strongest intention to use EV-Sharing service among four groups, for they favor good electric vehicles with on-board equipments and higher speed.The "environmentally friendly group" will emphasize on actual contributions to environmental protection when they use EV-Sharing service in the future. It is recommended that target markets can be focused on tourism and recreation trips. Pricing by rental period or usage time are also valid. Some EV-Sharing service projects should be deployed and promoted by government to encourage people to experience by themselves. In addition, EV-Sharing service locations should be set near to main railway or bus stations to increase its usage.

碩士<br>國立臺北科技大學<br>資訊管理研究所<br>102<br>This study deals with the electric vehicle (EV) allocation problem in an EV-sharing system with uncertain demand. For a given fleet of electric vehicles, the objective is to determine optimal numbers of EVs in the rental stations of the EV-sharing system so as to minimize the total cost of the system operator. We propose a simulation-based genetic algorithm (GA) to solve this complex problem. A simulator is developed and embedded in the proposed algorithm to evaluate the cost of the EV-Sharing system under a given fleet allocation scheme. To examine the performance of the algorithm, this study conducts a set of computational experiments on various sized problem instances generated based on the EV-Sharing system operated in Sun Moon Lake scenic area. We compare the solutions of the GA with those of an enumeration method. The results show that the GA is effective and efficient on solving the problem. Specifically, the GA is able to obtain an optimal solution for more than 70% of the instances and for those that GA fails to obtain optimal solutions, the deviations of GA’s solutions from optimal solutions are all less than 1%. Moreover, while the computational time of the enumeration method increases dramatically with the size of the problem, GA is able to obtain optimal or close-to-optimal solutions in a reasonable amount of time.

<div>In recent years, there has been considerable growth in the adoption and technology development of electric vehicles (EV), autonomous vehicles (AV), and ride sharing (RS). These technologies have the potential to improve transportation sustainability. Many studies have evaluated the environmental impacts of these technologies but the existing literature has three major gaps: (1) the adoption of these three technologies need to be evaluated considering their impact on each other, (2) many existing models do not evaluate systems on a common ground, and (3) the heterogeneous preferences of riders towards these emerging technologies are not fully incorporated. To address these gaps, this work studies and quantifies the environmental and efficiency gains that can be gained through these emerging transportation technologies by developing a Parameterized Preference-based Shared Autonomous Electric Vehicle (PP-SAEV) agent-based model. The model is then applied to a case study of New York City (NYC) taxis to evaluate the system performance with increasing AV, EV, and RS adoption.</div><div><br></div><div>The outputs from the PP-SAEV model show that replacing taxi cabs in NYC with AVs along with RS potentially can reduce CO\textsubscript{2} emissions by 866 metric Tones per day and increase average vehicle occupancy from 1.2 to 3 persons in vehicles with passenger seating capacity of 4. A prediction model based on the PP-SAEV output recommends that 6000 vehicles are needed to maintain the current level of service with 100\% AV and RS adoption using capacity 4 taxis. Taxi fleets with capacity 4 with high RS and low AV adoption are also found to have the least CO\textsubscript{2} emissions. Because the heterogeneous sharing preferences of riders have shown as the major limiting factor to ride sharing, these heterogeneous sharing preferences are further modelled. The results show that high service levels are achieved when all the riders are open to sharing, and the maximum service level is reached when 30\% of riders will only accept shared rides and 70\% of the riders are either indifferent to sharing or prefer to use ride sharing over riding alone. Additionally, the service level and waiting time of riders that are inflexible (will accept only shared or non-shared rides) are greatly impacted by varying mix of riders with different sharing preference. Finally, an optimization model was built to site charging stations in a system with continually increasing EV adoption. Using the best charging station locations, transforming a fleet of autonomous or traditional vehicles to electric vehicles does not significantly change the system service level. The results show that increasing the EV adoption in fleets with 100\% RS and AV adoption reduced the daily CO\textsubscript{2} emissions by about 861 Tones and transforming a fleet of traditional taxi cabs to electric taxi cabs reduced the daily CO\textsubscript{2} emissions by 1100 Tones.</div><div><br></div><div>In summary, this dissertation evaluates the potential growth of autonomous vehicles, ride sharing, and electric vehicles in systems where riders may have heterogeneous sharing preferences, from a system performance`s perspective and assesses the environmental impacts. The developed model and the insights gained from this study can inform policy makers to develop sustainable transportation systems incorporating the emerging transportation technologies.</div>

abstract: As electric powered unmanned aerial vehicles enter a new age of commercial viability, market opportunities in the small UAV sector are expanding. Extending UAV flight time through a combination of fuel cell and battery technologies enhance the scope of potential applications. A brief survey of UAV history provides context and examples of modern day UAVs powered by fuel cells are given. Conventional hybrid power system management employs DC-to-DC converters to control the power split between battery and fuel cell. In this study, a transistor replaces the DC-to-DC converter which lowers weight and cost. Simulation models of a lithium ion battery and a proton exchange membrane fuel cell are developed and integrated into a UAV power system model. Flight simulations demonstrate the operation of the transistor-based power management scheme and quantify the amount of hydrogen consumed by a 5.5 kg fixed wing UAV during a six hour flight. Battery power assists the fuel cell during high throttle periods but may also augment fuel cell power during cruise flight. Simulations demonstrate a 60 liter reduction in hydrogen consumption when battery power assists the fuel cell during cruise flight. Over the full duration of the flight, averaged efficiency of the power system exceeds 98%. For scenarios where inflight battery recharge is desirable, a constant current battery charger is integrated into the UAV power system. Simulation of inflight battery recharge is performed. Design of UAV hybrid power systems must consider power system weight against potential flight time. Data from the flight simulations are used to identify a simple formula that predicts flight time as a function of energy stored onboard the modeled UAV. A small selection of commercially available batteries, fuel cells, and compressed air storage tanks are listed to characterize the weight of possible systems. The formula is then used in conjunction with the weight data to generate a graph of power system weight versus potential flight times. Combinations of the listed batteries, fuel cells, and storage tanks are plotted on the graph to evaluate various hybrid power system configurations.<br>Dissertation/Thesis<br>Masters Thesis Engineering 2016