Decarbonizing road transportation is vital for addressing climate change, given that the sector currently contributes to 16% of global GHG emissions. This paper presents a comparative analysis of ...electric and hydrogen mobility infrastructures in a remote context, i.e., an off-grid island. The assessment includes resource assessment and sizing of renewable energy power plants to facilitate on-site self-production. We introduce a comprehensive methodology for sizing the overall infrastructure and carry out a set of techno-economic simulations to optimize both energy performance and cost-effectiveness. The levelized cost of driving at the hydrogen refueling station is 0.40 €/km, i.e., 20% lower than the electric charging station. However, when considering the total annualized cost, the battery-electric scenario (110 k€/year) is more favorable compared to the hydrogen scenario (170 k€/year). To facilitate informed decision-making, we employ a multi-criteria decision-making analysis to navigate through the techno-economic findings. When considering a combination of economic and environmental criteria, the hydrogen mobility infrastructure emerges as the preferred solution. However, when energy efficiency is taken into account, electric mobility proves to be more advantageous.
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•Decarbonization of public mobility in a remote island context.•Comparative analysis of hydrogen and electric mobility infrastructure.•Techno-economic optimization modeled in PyPSA framework.•Multicriteria Decision Making Analysis to steer policymakers’ decisions.
Mobility as a Service (MaaS) is a concept that aligns with both current and future mobility demands of users, namely intermodal, personalized, on-demand and seamless. Although the number of shared ...mobility, electric mobility and multimodal passenger transport users is rapidly growing, until now, the list of MaaS and electric Mobility as Service (eMaaS) providers is quite short. This could partly be explained by the lack of a common architecture that facilitates the complex integration of all actors involved in the (e)MaaS ecosystem. The goal of this publication is to give an overview of the state of the art regarding (e)MaaS’ ecosystems and architectures. Moreover, it aims to support the further development of eMaaS by proposing a definition and a novel system architecture for eMaaS. Firstly, the state of the art of the MaaS ecosystem is reviewed. Secondly, the eMaaS ecosystem that builds upon our definition of eMaaS is described and the MaaS system- and technical- architectures found in literature are reviewed. Finally, an eMaaS architecture that focuses on the integration of MaaS and electric mobility systems is presented. With the definition, ecosystem and system architecture presented in this work, the aim is to support the further development of the eMaaS concept.
This study is motivated by the prospect of needing to harness significant flows of investment and finance, along with private sector commitment, towards decarbonizing passenger transport in Europe. ...It asks: what types of actors and stakeholder groups, business models, and resulting innovation activity systems might vehicle-to-grid (V2G) technology create or accelerate? Based primarily on qualitative research interviews and focus groups in five countries—Denmark, Finland, Iceland, Norway and Sweden, and a comprehensive literature review, the study assess stakeholder perceptions of primary and secondary business models for V2G. It identifies at least twelve meaningful stakeholder types and corresponding business markets: automotive manufacturers, battery manufacturers, vehicle owners, energy suppliers, transmission and distribution system operators, fleets, aggregators, mobility-as-a-service providers, renewable electricity independent power providers, public transit operators, secondhand markets and secondary markets. These business models fall into the five clusters of equipment, grid services, aggregation, bundling, and secondary markets. We then examine how these business models differ by innovation activity systems—that is, by content, structure, and governance. We lastly translate these findings into policy recommendations of relevance for all types of countries.
•Assesses actors, business models, and innovation activity systems for V2G and electric vehicles in Europe.•Identifies twelve meaningful stakeholder types and corresponding business markets for V2G.•Examines business models across equipment, grid services, aggregation, bundling, and secondary markets.•Concludes with 12 policy implications.
There is a growing need for a broad overview of the state of knowledge on the environmental aspects of Electric Vehicles (EVs), which could help policymakers in the objective of making road ...transportation more sustainable and environmental friendly. This study provides a comprehensive review of the effects of EVs adoption on air quality, greenhouse gas emissions, and human health. Specifically, we (i) synthesized relevant published literature related to environmental implication of EVs, (ii) quantitatively evaluated the effect of EVs on environment and human health, and (iii) identified research gaps and recommend future research areas for the adoption of EVs and their benefits to society. We assessed in total 4734 studies and selected 123 articles of more detailed review, with 65 articles fulfilling the inclusion criteria. The studies reviewed consistently showed reductions in greenhouse gas emissions and emissions of some criteria pollutants. Particularly on PM and SO2, the increases or decreases are very dependent on the context. Overall, the positive benefits of EVs for reducing greenhouse gas emissions and human exposure depends on the following factors: (i) type of EV, (ii) source of energy generation, (iii) driving conditions, (iv) charging patterns, (v) availbailty of charging infrastructure, (vi) govermnat policies, and (vii) climate of a regions. This study provides a comprehansive analysis and review on the benefits of electric mobility.
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•We assessed 4734 studies and selected 123 articles for more detailed review.•Most of the studies were carried out in the United States or China.•EVs may have a role in reducing air pollution and its consequences for health.
The transportation sector accounts for a significant share of greenhouse gas emissions. Hence, the electrification of this sector is a crucial contributor to the mitigation of global warming. Recent ...studies suggest that electric vehicles will be economically paired with internal combustion engine vehicles in the near future. However, relying on private vehicle decarbonization only cannot deliver comprehensive space management efficiency solutions in urban environments. Therefore, it is essential to invest in the technological development and deployment of electric buses for public transportation, directly enhancing the quality of life in large cities. From this perspective, this review examines a wide range of scientific literature on electric bus research using science mapping methods and content analysis to support critical thinking unveiling the main research streams, methods, and gaps of the field. The analysis indicates that future research on electric buses will be mainly devoted to sustainability (encompassing economic, environmental and quality of service dimensions), energy management strategies, and fleet operation.
•Electric bus research is assessed using science mapping and content analysis.•The main electric bus research streams are recognized.•Content analysis of relevant articles is carried out to assess the methods used.•Future research is mainly aimed at energy management strategy and fleet operation.•Recent research gaps are identified.
•Study of electric mobility policy and charging infrastructure effect on PEV uptake.•Panel data on 32 European countries from 2009 to 2019 are used.•Results strongly suggest that charging ...infrastructure increases PEV market share.•Fast charging in particular is a key enabler for higher PEV market shares.•Electric mobility policy packages increase PEV shares more than single policies.
The transportation sector accounts for a significant part of European emissions and is one of the few sectors with rising emissions. Thus one crucial part of the European strategy to reduce overall emissions is a shift, in the transportation sector, to low-emission mobility and electric mobility in particular. As European governments and policymakers consider feasible ways of supporting the transition, one central question is whether the policies and actions they enact should aim for creating incremental or structural change, here operationalized as personal incentives vs. charging infrastructure. Therefore, this analysis investigates the effects of electric mobility policies and charging infrastructure on plug-in electric vehicle (PEV) market shares in Europe from 2009 to 2019. Charging infrastructure, and fast charging infrastructure in particular, demonstrate by far the strongest and most robust results of the analysis, having a significant positive effect on PEV market shares in all models. The analysis also suggests that purchase incentives, ownership tax benefits, and the policy packages for electric mobility tested have a positive and significant effect on PEV adoption. However, these effects are notably weaker and exhibit far less robust findings across the models in the analysis. Thus, while the study cannot conclusively come down on the side of infrastructure over personal incentives, it persuasively points to the crucial importance of charging infrastructures for the electrification of transportation. Theoretically, this makes sense—personal incentives will increase the market shares of PEV, but only incrementally, running the risk of merely supplementing the old fossil fuel-based transportation system rather than replacing it. Charging infrastructure on the other hand creates the potential for structural change, implying that a more active and coordinated build-out of charging infrastructure is needed to ensure a rapid transition to low-emission mobility.
Electric vehicle charging demand models, with charging records as input, will inherently be biased toward the supply of available chargers. These models often fail to account for demand lost from ...occupied charging stations and competitors. The lost demand suggests that the actual demand is likely higher than the charging records reflect, i.e., the true demand is latent (unobserved), and the observations are censored. As a result, machine learning models that rely on these observed records for forecasting charging demand may be limited in their application in future infrastructure expansion and supply management, as they do not estimate the true demand for charging. We propose using censorship-aware models to model charging demand to address this limitation. These models incorporate censorship in their loss functions and learn the true latent demand distribution from observed charging records. We study how occupied charging stations and competing services censor demand using GPS trajectories from cars in Copenhagen, Denmark. We find that censorship occurs up to 61% of the time in some areas of the city. We use the observed charging demand from our study to estimate the true demand and find that censorship-aware models provide better prediction and uncertainty estimation of actual demand than censorship-unaware models. We suggest that future charging models based on charging records should account for censoring to expand the application areas of machine learning models in supply management and infrastructure expansion.
•Observed EV charging demand is limited to the supply of charging stations.•Censored Regression models proposed to model the true demand.•Graph neural networks are extended to model the true latent demand.•Experiments on how demand is censored in Copenhagen, Denmark.•Censorship aware models offer better modelling the latent demand for charging.
Transportation electrification is a promising solution to meet the ever-rising energy demand and realize sustainable development. Lithium-ion batteries, being the most predominant energy storage ...devices, directly affect the safety, comfort, driving range, and reliability of many electric mobilities. Nevertheless, thermal-related issues of batteries such as potential thermal runaway, performance degradation at low temperatures, and accelerated aging still hinder the wider adoption of electric mobilities. To ensure safe, efficient, and reliable operations of lithium-ion batteries, monitoring their thermal states is critical to safety protection, performance optimization, as well as prognostics, and health management. Given insufficient onboard temperature sensors and their inability to measure battery internal temperature, accurate and timely temperature estimation is of particular importance to thermal state monitoring. Toward this end, this paper provides a comprehensive review of temperature estimation techniques in battery systems regarding their mechanism, framework, and representative studies. The potential metrics used to characterize battery thermal states are discussed in detail at first considering the spatiotemporal attributes of battery temperature, and the strengths and weaknesses of applying such metrics in battery management are also analyzed. Afterward, various temperature estimation methods, including impedance/resistance-based, thermal model-based, and data-driven estimations, are elucidated, analyzed, and compared in terms of their strengths, limitations, and potential improvements. Finally, the key challenges to battery thermal state monitoring in real applications are identified, and future opportunities for removing these barriers are presented and discussed.