Optimizing layouts of initial AFV refueling stations targeting different drivers, and experiments with agent-based simulations

The number of refuelling stations for AFVs (alternative fuel vehicles) is limited during the early stges of the diffusion of AFVs. Different layouts of these initial stations will result in different degrees of driver concern regardng refueling and will therefore influence dividuals' decisions to adopt AFVs. The question becomes "what is an optimal layout for these initial stations? Should it target all drivers or just a portion of them, and if so, which portion?" Further, how does the number of initial AFV refueling stations influence the adoption of AFVs? This paper explores these questions with agent-based simulations. Using Shanghai as the basis of computational experiments, this paper first generates different optimal layouts using a genetic algorithm to minimize the total concern of different targeted drivers and then conducts agent-based simulations on the diffusion of AFVs with these layout. The main findings of this study are that (1) targeting drivers in the city center can induce the fastest diffusion of AFVs if AV technologies are mature and (2) it is possible that a larger number of initial AFV refueling stations may result in slower diffusion of AFVs because these initial stations may not have sufficient customers to survive. The simulations can provide some insights for cities that are trying to promote the diffusion of AFVs

Big Data for Urban Sustainability: Integrating Personal Mobility Dynamics in Environmental Assessments.

To alleviate fossil fuel use, reduce air emissions, and mitigate climate change, “new mobility” systems start to emerge with technologies such as electric vehicles, multi-modal transportation enabled by information and communications technology, and car/ride sharing. Current literature on the environmental implications of these emerging systems is often limited by using aggregated travel pattern data to characterize personal mobility dynamics, neglecting the individual heterogeneity. Individual travel patterns affect several key factors that determine potential environmental impacts, including charging behaviors, connection needs between different transportation modes, and car/ride sharing potentials. Therefore, to better understand these systems and inform decision making, travel patterns at the individual level need to be considered. Using vehicle trajectory data of over 10,000 taxis in Beijing, this research demonstrates the benefits of integrating individual travel patterns into environmental assessments through three case studies (vehicle electrification, charging station siting, and ride sharing) focusing on two emerging systems: electric vehicles and ride sharing. Results from the vehicle electrification study indicate that individual travel patterns can impact the environmental performance of fleet electrification. When battery cost exceeds $200/kWh, vehicles with greater battery range cannot continuously improve travel electrification and can reduce electrification rate. At the current battery cost of$400/kWh, targeting subsidies to vehicles with battery range around 90 miles can achieve higher electrification rate. The public charging station siting case demonstrates that individual travel patterns can better estimate charging demand and guide charging infrastructure development. Charging stations sited according to individual travel patterns can increase electrification rate by 59% to 88% compared to existing sites. Lastly, the ride sharing case shows that trip details extracted from vehicle trajectory data enable dynamic ride sharing modeling. Shared taxi rides in Beijing can reduce total travel distance and air emissions by 33% with 10-minute travel time deviation tolerance. Only minimal tolerance to travel time change (4 minutes) is needed from the riders to enable significant ride sharing (sharing 60% of the trips and saving 20% of travel distance). In summary, vehicle trajectory data can be integrated into environmental assessments to capture individual travel patterns and improve our understanding of the emerging transportation systems.PhDNatural Resources and Environment and Environmental EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113510/1/caih_1.pd

Prospects for Electric Mobility: Systemic, Economic and Environmental Issues

The transport sector, which is currently almost completely based on fossil fuels, is one of the major contributors to greenhouse gas emissions. Heading towards a more sustainable development of mobility could be possible with more energy efficient automotive technologies such as battery electric vehicles. The number of electric vehicles has been increasing over the last decade, but there are still many challenges that have to be solved in the future. This Special Issue “Prospects for Electric Mobility: Systemic, Economic and Environmental Issues” contributes to the better understanding of the current situation as well as the future prospects and impediments for electro mobility. The published papers range from historical development of electricity use in different transport modes and the recent challenges up to future perspectives

Planning the Charging Infrastructure for Electric Vehicles in Cities and Regions

Planning the charging infrastructure for electric vehicles (EVs) is a new challenging task. This book treats all involved aspects: charging technologies and norms, interactions with the electricity system, electrical installation, demand for charging infrastructure, economics of public infrastructure provision, policies in Germany and the EU, external effects, stakeholder cooperation, spatial planning on the regional and street level, operation and maintenance, and long term spatial planning

Planning the Charging Infrastructure for Electric Vehicles in Cities and Regions

Planning the charging infrastructure for electric vehicles (EVs) is a new challenging task. This book treats all involved aspects: charging technologies and norms, interactions with the electricity system, electrical installation, demand for charging infrastructure, economics of public infrastructure provision, policies in Germany and the EU, external effects, stakeholder cooperation, spatial planning on the regional and street level, operation and maintenance, and long term spatial planning

New Perspectives on Electric Vehicles

Modern transportation systems have adverse effects on the climate, emitting greenhouse gases and polluting the air. As such, new modes of non-polluting transportation, including electric vehicles and plug-in hybrids, are a major focus of current research and development. This book explores the future of transportation. It is divided into four sections: “Electric Vehicles Infrastructures,” “Architectures of the Electric Vehicles,” “Technologies of the Electric Vehicles,” and “Propulsion Systems.” The chapter authors share their research experience regarding the main barriers in electric vehicle implementation, their thoughts on electric vehicle modelling and control, and network communication challenges

iCity. Transformative Research for the Livable, Intelligent, and Sustainable City

This open access book presents the exciting research results of the BMBF funded project iCity carried out at University of Applied Science Stuttgart to help cities to become more liveable, intelligent and sustainable, to become a LIScity. The research has been pursued with industry partners and NGOs from 2017 to 2020. A LIScity is increasingly digitally networked, uses resources efficiently, and implements intelligent mobility concepts. It guarantees the supply of its grid-bound infrastructure with a high proportion of renewable energy. Intelligent cities are increasingly human-centered, integrative, and flexible, thus placing the well-being of the citizens at the center of developments to increase the quality of life. The articles in this book cover research aimed to meet these criteria. The book covers research in the fields of energy (i.e. algorithms for heating and energy storage systems, simulation programs for thermal local heating supply, runtime optimization of combined heat and power (CHP), natural ventilation), mobility (i.e. charging distribution and deep learning, innovative emission-friendly mobility, routing apps, zero-emission urban logistics, augmented reality, artificial intelligence for individual route planning, mobility behavior), information platforms (i.e. 3DCity models in city planning: sunny places visualization, augmented reality for windy cities, internet of things (IoT) monitoring to visualize device performance, storing and visualizing dynamic energy data of smart cities), and buildings and city planning (i.e. sound insulation of sustainable facades and balconies, multi-camera mobile systems for inspection of tunnels, building-integrated photovoltaics (BIPV) as active façade elements, common space, the building envelopes potential in smart sustainable cities)

Sustainable Mobility and Transport

This Special Issue is dedicated to sustainable mobility and transport, with a special focus on technological advancements. Global transport systems are significant sources of air, land, and water emissions. A key motivator for this Special Issue was the diversity and complexity of mitigating transport emissions and industry adaptions towards increasingly stricter regulation. Originally, the Special Issue called for papers devoted to all forms of mobility and transports. The papers published in this Special Issue cover a wide range of topics, aiming to increase understanding of the impacts and effects of mobility and transport in working towards sustainability, where most studies place technological innovations at the heart of the matter. The goal of the Special Issue is to present research that focuses, on the one hand, on the challenges and obstacles on a system-level decision making of clean mobility, and on the other, on indirect effects caused by these changes

Techno-economic optimization and environmental evaluation of electric vehicles in commercial fleets

Die Einführung von batterieelektrischen Fahrzeugen (E-Pkw) gilt als eine wichtige Maßnahme zur Emissionsverringerung im Straßenverkehr. Gewerbliche Flotten in Deutschland bilden hierfür einen vielversprechenden Markt. Um dieses Potential zu realisieren, ist sowohl eine techno-ökonomische Optimierung als auch eine ökologische Bewertung über den Lebenszyklus erforderlich. Das Ziel der Dissertation ist es, hierfür ein methodisches Rahmenwerk zu liefern. Die kumulative Dissertation besteht aus fünf Artikeln, die sich den einzelnen Bestandteilen des Rahmenwerks widmen und großteils auf Technologie- und Nutzungsdaten aus eigenen Messungen aufbauen. Der erste Artikel, Schücking et al. (2016) [Paper I], ist eine technische Analyse. Sie untersucht den realen Energieverbrauch von E-Pkws im Vergleich zu konventionellen Fahrzeugen und identifiziert optimale Betriebspunkte. Die Ergebnisse heben den Einfluss verschiedener Faktoren auf den Energieverbrauch als wichtige Komponente detaillierter techno-ökonomischer und ökologischer Betrachtungen hervor. Der zweite und der dritte Artikel haben einen techno-ökonomischen Fokus. Sie beschäftigen sich mit der Frage, wie E-Pkws einen schnelleren wirtschaftlichen Break-even im Vergleich zu konventionellen Fahrzeugen erreichen können. Der zweite Artikel, Schücking et al. (2017) [Paper II], stellt Ladestrategien vor, welche eine höhere Auslastung der E-Pkw ermöglichen und damit zu geringen Gesamtkosten im Vergleich zu konventionellen Pkw führen können. Unsicherheiten in Fahrprofilen und Energieverbrauch begrenzen die Anwendbarkeit dieser Strategien. Der dritte Artikel, Schücking & Jochem (2020) [Paper III], knüpft hieran an. Er schlägt ein zweistufiges stochastisches Optimierungsmodell zur Minimierung der Investition und Betriebskosten eines E-Pkw unter Berücksichtigung dieser Unsicherheiten vor. Neben der stochastischen Betrachtung ist auch die Abwägung zwischen Batteriekapazität und Ladeleistung in der Investitionsentscheidung ein neuer Beitrag zur Forschung. Im Kontext der stochastischen Optimierung werden ein Hidden Markov Modell zur Generierung komplexer Fahrprofile und eine neue Szenario-Reduktionsheuristik als methodische Weiterentwicklungen angewandt. Artikel vier und fünf liefern eine ökologische Bewertung. Die empirischen Daten sowie der Fokus auf den deutsch-französischen Grenzverkehr zeichnen beide Artikel aus. Der vierte Artikel, Ensslen et al. (2017) [Paper IV], konzentriert sich auf die E-Pkw Nutzungsphase. Er verdeutlicht den Einfluss unterschiedlicher Strommixe und Ladezeitpunkte auf die CO2- Emissionen und Reduktionspotentiale. Der fünfte Artikel, Held & Schücking (2019) [Paper V], betrachtet verschiedene ökologische Wirkungskategorien (wie z.B. Klimawandel, Versauerung Eutrophierung) über den gesamten Lebenszyklus mittels eines modularen Screening-Modells. Die Ergebnisse unterstreichen den Einfluss der Batterie und der Nutzungsphase auf die ökologische Gesamtbilanz. Dem übergreifenden Forschungsziel folgend, zeigen die Ergebnisse der einzelnen Artikel in ihrer Kombination, dass die Optimierung des wirtschaftlichen Nutzens auch die ökologischen Vorteile erhöhen kann. Die ex-ante Ermittlung der optimalen Batteriekapazität sowie ein hoher Betriebsgrad erhöhen nicht nur die Wettbewerbsfähigkeit von E-Pkw, sondern beschleunigen unter bestimmten Voraussetzungen auch den ökologischen Break-even in einem Großteil der betrachteten Wirkungskategorien. Die Eigenschaften, die gewerbliche Anwendungen aus wirtschaftlicher Sicht zu einem vielversprechenden Einführungsmarkt für E-Pkws machen, können damit auch die angestrebten ökologischen Vorteile unterstützen