Sustainable Transportation with Electric Vehicles

2017 ◽  
Author(s):  
Fanxin Kong ◽  
Xue Liu
Keyword(s):  
Electric Vehicles ◽  
Sustainable Transportation

Comparative environmental life cycle assessment of conventional vehicles with different fuel options, plug-in hybrid and electric vehicles for a sustainable transportation system in Brazil

2018 ◽  
Vol 203 ◽  
pp. 444-468 ◽  
Author(s):  
Lidiane La Picirelli de Souza ◽  
Electo Eduardo Silva Lora ◽  
José Carlos Escobar Palacio ◽  
Mateus Henrique Rocha ◽  
Maria Luiza Grillo Renó ◽  
...  
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Electric Vehicles ◽  
Transportation System ◽  
Sustainable Transportation ◽  
Environmental Life Cycle Assessment

scholarly journals Operating Charging Infrastructure in China to Achieve Sustainable Transportation: The Choice between Company-Owned and Franchised Structures

2019 ◽  
Vol 11 (6) ◽  
pp. 1549 ◽  
Author(s):  
Lin Ma ◽  
Yuefan Zhai ◽  
Tian Wu
Keyword(s):  
Electric Vehicles ◽  
Rapid Development ◽  
Sustainable Transportation ◽  
Sustainable Infrastructure ◽  
Charging Infrastructure ◽  
Initial Stage ◽  
Charging Stations ◽  
Operation Cost ◽  
Optimal Quality

The rapid development of electric vehicles (EVs) is conducive to clean transportation, which is an important aspect of sustainable infrastructure. However, the introduction of EVs is constrained by the lagging development of EV chargers. To optimally promote the development of charging stations, we analyzed the differences in the optimal quality and quantity of EV chargers between company-owned and franchised enterprises by constructing a theoretical model, and the changes in the quality and quantity of EV chargers in different market environments are discussed. We found that the total number of franchised charging stations was larger in general, but that the quality of the franchised charging stations was worse compared with the company-owned stations. The supervision cost, operation cost, and the investment return affect the quality and quantity of EV chargers. Although franchised structures are more conducive in the initial stage to increasing the number of charging stations to meet the needs of EVs, company-owned structures perform better and will be needed to improve the quality of the EV chargers as the market becomes more saturated, necessitating a higher quality of EV chargers.

scholarly journals The influence of electrochemical cycling protocols on capacity loss in nickel-rich lithium-ion batteries

2021 ◽  
Author(s):  
Wesley Dose ◽  
Jędrzej Krzysztof Morzy ◽  
Amoghavarsha Mahadevegowda ◽  
Caterina Ducati ◽  
Clare P. Grey ◽  
...  
Keyword(s):  
Transition Metal ◽  
Metal Oxides ◽  
Lithium Ion Batteries ◽  
Electric Vehicles ◽  
Transition Metal Oxides ◽  
Lithium Ion ◽  
Sustainable Transportation ◽  
Capacity Loss ◽  
Electrochemical Cycling ◽  
Layered Transition Metal

The transition towards electric vehicles and more sustainable transportation is dependent on lithium-ion battery (LIB) performance. Ni-rich layered transition metal oxides, such as NMC811 (LiNi0.8Mn0.1Co0.1O2), are promising cathode candidates for...

scholarly journals frvcpy: An Open-Source Solver for the Fixed Route Vehicle Charging Problem

2021 ◽  
Author(s):  
Nicholas D. Kullman ◽  
Aurelien Froger ◽  
Jorge E. Mendoza ◽  
Justin C. Goodson
Keyword(s):  
Open Source ◽  
Vehicle Routing ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Software Tool ◽  
Sustainable Transportation ◽  
Vehicle Routing Problems ◽  
Routing Problems ◽  
Vehicle Charging ◽  
Community Standard

Electric vehicles offer a pathway to more sustainable transportation, but their adoption entails new challenges not faced by their petroleum-based counterparts. A difficult task in vehicle routing problems addressing these challenges is determining how to make good charging decisions for an electric vehicle traveling a given route. This is known as the fixed route vehicle charging problem. An exact and efficient algorithm for this task exists, but its implementation is sufficiently complex to deter researchers from adopting it. In this work we introduce frvcpy, an open-source Python package implementing this algorithm. Our aim with the package is to make it easier for researchers to solve electric vehicle routing problems, facilitating the development of optimization tools that may ultimately enable the mass adoption of electric vehicles. Summary of Contribution: This work describes a novel software tool for the vehicle routing community. The tool, frvcpy, addresses one of the primary challenges faced by the vehicle routing community when considering problems involving the adoption of electric vehicles (EVs): how to make optimal charging decisions. The state-of-the-art algorithm for solving these problems is sufficiently complex to deter researchers from using it, leading them to adopt less robust methods. frvcpy offers an easy-to-use, lightweight implementation of this algorithm, providing optimal solutions in low (∼5 ms) runtime. It is designed to be easily embedded in larger solution schemes for general EV routing problems, requiring minimal input, offering compatibility with the community standard file types, and offering access both through the command line and a Python API. The tool has thus far proven adaptable, having been used by researchers studying EV routing problems with novel constraints. Our aim with frvcpy is to make it easier for researchers to solve EV routing problems, facilitating the development of optimization tools that may contribute toward the mass adoption of electric vehicles.

scholarly journals Quest for Sustainability: Life-Cycle Emissions Assessment of Electric Vehicles Considering Newer Li-Ion Batteries

2019 ◽  
Vol 11 (8) ◽  
pp. 2366 ◽  
Author(s):  
Arminda Almeida ◽  
Nuno Sousa ◽  
João Coutinho-Rodrigues
Keyword(s):  
Life Cycle ◽  
Electric Vehicles ◽  
Electricity Generation ◽  
Combustion Engine ◽  
Statistical Significance ◽  
Sustainable Transportation ◽  
Assessment Model ◽  
Battery Capacity ◽  
Li Ion ◽  
The Impact

The number of battery electric vehicle models available in the market has been increasing, as well as their battery capacity, and these trends are likely to continue in the future as sustainable transportation goals rise in importance, supported by advances in battery chemistry and technology. Given the rapid pace of these advances, the impact of new chemistries, e.g., lithium-manganese rich cathode materials and silicon/graphite anodes, has not yet been thoroughly considered in the literature. This research estimates life cycle greenhouse gas and other air pollutants emissions of battery electric vehicles with different battery chemistries, including the above advances. The analysis methodology, which uses the greenhouse gases, regulated emissions, and energy use in transportation (GREET) life-cycle assessment model, considers 8 battery types, 13 electricity generation mixes with different predominant primary energy sources, and 4 vehicle segments (small, medium, large, and sport utility vehicles), represented by prototype vehicles, with both battery replacement and non-replacement during the life cycle. Outputs are expressed as emissions ratios to the equivalent petrol internal combustion engine vehicle and two-way analysis of variance is used to test results for statistical significance. Results show that newer Li-ion battery technology can yield significant improvements over older battery chemistries, which can be as high as 60% emissions reduction, depending on pollutant type and electricity generation mix.

scholarly journals Planning of the Charging Station for Electric Vehicles Utilizing Cellular Signaling Data

2019 ◽  
Vol 11 (3) ◽  
pp. 643 ◽  
Author(s):  
Jianmin Jia ◽  
Chenhui Liu ◽  
Tao Wan
Keyword(s):  
Electric Vehicles ◽  
Large Scale ◽  
Travel Demand ◽  
Cellular Signaling ◽  
Sustainable Transportation ◽  
Charging Station ◽  
Step Model ◽  
Pollutants Emission ◽  
Effective Component ◽  
Charging Stations

Electric Vehicles (EVs), by reducing the dependency on fossil fuel and minimizing the traffic-related pollutants emission, are considered as an effective component of a sustainable transportation system. However, the massive penetration of EVs brings a big challenge to the establishment of charging infrastructures. This paper presents the approach to locate charging stations utilizing the reconstructed EVs trajectory derived from the Cellular Signaling Data (CSD). Most previous work focused on the commute trips estimated from the number of jobs and households between traffic analysis zones (TAZs). This paper investigated the large-scale CSD and illustrated the method to generate the 24-hour travel demand for each EV. The complete trip in a day for EV was reconstructed through merging the time sequenced trajectory derived from simulation. This paper proposed a two-step model that grouped the charging demand location into clusters and then identified the charging station site through optimization. The proposed approach was applied to investigate the charging behavior of medium-range EVs with Cellular Signaling Data collected from the China Unicom in Tianjin. The results indicate that over 50% of the charging stations are located within the central urban area. The developed approach could contribute to the planning of future charging stations.

scholarly journals Electric Vehicle Routing, Arc Routing, and Team Orienteering Problems in Sustainable Transportation

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 5131
Author(s):  
Leandro do C. Martins ◽  
Rafael D. Tordecilla ◽  
Juliana Castaneda ◽  
Angel A. Juan ◽  
Javier Faulin
Keyword(s):  
Vehicle Routing ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Combustion Engine ◽  
Optimization Methods ◽  
Sustainable Transportation ◽  
Arc Routing ◽  
Learning Approaches ◽  
Optimization Simulation ◽  
Team Orienteering

The increasing use of electric vehicles in road and air transportation, especially in last-mile delivery and city mobility, raises new operational challenges due to the limited capacity of electric batteries. These limitations impose additional driving range constraints when optimizing the distribution and mobility plans. During the last years, several researchers from the Computer Science, Artificial Intelligence, and Operations Research communities have been developing optimization, simulation, and machine learning approaches that aim at generating efficient and sustainable routing plans for hybrid fleets, including both electric and internal combustion engine vehicles. After contextualizing the relevance of electric vehicles in promoting sustainable transportation practices, this paper reviews the existing work in the field of electric vehicle routing problems. In particular, we focus on articles related to the well-known vehicle routing, arc routing, and team orienteering problems. The review is followed by numerical examples that illustrate the gains that can be obtained by employing optimization methods in the aforementioned field. Finally, several research opportunities are highlighted.

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