The impact of battery electric vehicles on vehicle purchase and driving behavior in Norway

2018 ◽  
Vol 58 ◽  
pp. 239-258 ◽  
Author(s):  
Gordon Bauer
Keyword(s):  
Electric Vehicles ◽  
Driving Behavior ◽  
Battery Electric Vehicles ◽  
Vehicle Purchase ◽  
The Impact

scholarly journals Joint Optimal Policy for Subsidy on Electric Vehicles and Infrastructure Construction in Highway Network

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2479 ◽  
Author(s):  
Yue Wang ◽  
Zhong Liu ◽  
Jianmai Shi ◽  
Guohua Wu ◽  
Rui Wang
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Optimal Policy ◽  
Practical Case ◽  
Battery Electric Vehicle ◽  
Battery Electric Vehicles ◽  
Endurance Range ◽  
Highway Network ◽  
Charging Stations ◽  
The Impact

The promotion of the battery electric vehicle has become a worldwide problem for governments due to its short endurance range and slow charging rate. Besides an appropriate network of charging facilities, a subsidy has proved to be an effective way to increase the market share of battery electric vehicles. In this paper, we investigate the joint optimal policy for a subsidy on electric vehicles and infrastructure construction in a highway network, where the impact of siting and sizing of fast charging stations and the impact of subsidy on the potential electric vehicle flows is considered. A new specified local search (LS)-based algorithm is developed to maximize the overall number of available battery electric vehicles in the network, which can get provide better solutions in most situations when compared with existed algorithms. Moreover, we firstly combined the existing algorithms to establish a multi-stage optimization method, which can obtain better solutions than all existed algorithms. A practical case from the highway network in Hunan, China, is studied to analyze the factors that impact the choice of subsidy and the deployment of charging stations. The results prove that the joint policy for subsidy and infrastructure construction can be effectively improved with the optimization model and the algorithms we developed. The managerial analysis indicates that the improvement on the capacity of charging facility can increase the proportion of construction fees in the total budget, while the improvement in the endurance range of battery electric vehicles is more efficient in expanding battery electric vehicle adoption in the highway network. A more detailed formulation of the battery electric vehicle flow demand and equilibrium situation will be studied in the future.

Impacts of electricity mix, charging profile, and driving behavior on the emissions performance of battery electric vehicles: A Belgian case study

2015 ◽  
Vol 148 ◽  
pp. 496-505 ◽  
Author(s):  
Surendraprabu Rangaraju ◽  
Laurent De Vroey ◽  
Maarten Messagie ◽  
Jan Mertens ◽  
Joeri Van Mierlo
Keyword(s):  
Electric Vehicles ◽  
Driving Behavior ◽  
Battery Electric Vehicles ◽  
Electricity Mix

scholarly journals Topology analysis of electric vehicles, with a focus on the traction battery

2020 ◽  
Author(s):  
Lorenzo Nicoletti ◽  
Franziska Ostermann ◽  
Maximilian Heinrich ◽  
Alois Stauber ◽  
Xue Lin ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
European Union ◽  
Electric Vehicles ◽  
Initial Result ◽  
Second Step ◽  
The Novel ◽  
Passenger Compartment ◽  
Topology Analysis ◽  
Battery Electric Vehicles ◽  
The Impact

Abstract Over recent years, the number of battery electric vehicles (BEVs) has drastically increased due to new European Union (EU) regulations. These regulations force vehicle manufacturers to adjust their product range in order to fulfill the imposed carbon dioxide limits. Such an adjustment enforces the usage of battery electric vehicles. However, research into the optimal BEV architectures and topologies is still in progress. Therefore, the aim of this paper is an analysis of all the current electric vehicle topologies. From this analysis, the authors identify different basic battery shapes. Subsequently, these shapes are used to describe the impact of the battery on the passenger compartment. As an initial result of this analysis, the authors create a new denomination method, via which it is possible to cluster the battery topologies. In a second step, the collected data is clustered using the novel denomination method. Finally, this paper presents the benchmark topologies for the analyzed segments.

scholarly journals Quantification of the Flexibility Potential through Smart Charging of Battery Electric Vehicles and the Effects on the Future Electricity Supply System in Germany

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2383
Author(s):  
Felix Guthoff ◽  
Nikolai Klempp ◽  
Kai Hufendiek
Keyword(s):  
Electric Vehicles ◽  
Capacity Planning ◽  
Linear Optimization ◽  
Energy System ◽  
Transport Sector ◽  
Additional Energy ◽  
Data Set ◽  
Battery Electric Vehicles ◽  
Smart Charging ◽  
The Impact

Electrification offers an opportunity to decarbonize the transport sector, but it might also increase the need for flexibility options in the energy system, as the uncoordinated charging process of battery electric vehicles (BEV) can lead to a demand with high simultaneity. However, coordinating BEV charging by means of smart charging control can also offer substantial flexibility potential. This potential is limited by restrictions resulting from individual mobility behavior and preferences. It cannot be assumed that storage capacity will be available at times when the impact of additional flexibility potential is highest from a systemic point of view. Hence, it is important to determine the flexibility available per vehicle in high temporal (and spatial) resolution. Therefore, in this paper a Markov-Chain Monte Carlo simulation is carried out based on a vast empirical data set to quantify mobility profiles as accurately as possible and to subsequently derive charging load profiles. An hourly flexibility potential is derived and integrated as load shift potential into a linear optimization model for the simultaneous cost-optimal calculation of the dispatch of technology options and long-term capacity planning to meet a given electricity demand. It is shown that the costs induced by BEV charging are largely determined by the profile costs from the combination of the profiles of charging load and renewable generation, and not only by the additional energy and capacity demand. If the charging process can be flexibly controlled, the storage requirement can be reduced and generation from renewable energies can be better integrated.

scholarly journals Factors Influencing the Diffusion of Battery Electric Vehicles in Urban Areas

2021 ◽  
Author(s):  
Morteza Mashayekhi
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Perceived Risk ◽  
Urban Areas ◽  
Diffusion Of Innovations ◽  
Battery Electric Vehicle ◽  
Battery Electric Vehicles ◽  
Road Map ◽  
Factors Influencing ◽  
The Impact

Purchasing a battery electric vehicle is a type of pro-environmental behavior but the impact of such behavior on the environment becomes significant and beneficial only if a large number of individuals buy it. Therefore, getting battery electric vehicles diffused in a social system is a critical task which needs a special attention from consumers as well as governments and suppliers. This thesis aims to find out all factors influencing the rate of adoption of a battery electric vehicle by using the main constructs and important concepts of theory of diffusion of innovations proposed by Rogers (1962). The results indicate that seven factors influence the rate of adoption of a battery electric vehicle including social pressure, social prestige, usefulness for environment, difficultly of use, price, perceived risk, and knowledge and information about battery electric vehicles. Based on these factors, a road map and a set of policies to accelerate the rate of adoption of battery electric vehicles were proposed.

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