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The combination of electric vehicles (EVs) and intermittent renewable energy sources has received increasing attention over the last few years. Not only does charging electric vehicles with renewable energy realize their true potential as a clean mode of transport, charging electric vehicles at times of peaks in renewable energy production can help large scale integration of renewable energy in the existing energy infrastructure. We present an agent-based model that investigates the potential contribution of this combination. More specifically, we investigate the potential effects of different kinds of policy interventions on aggregate EV charging patterns. The policy interventions include financial incentives, automated smart charging, information campaigns and social charging. We investigate howwell the resulting charging patterns are aligned with renewable energy production and how much they affect user satisfaction of EV drivers. Where possible, we integrate empirical data in our model, to ensure realistic scenarios. We use recent theory from environmental psychology to determine agent behaviour, contrary to earlier simulation models, which have focused only on technical and financial considerations. Based on our simulation results, we articulate some policy recommendations. Furthermore, we point to future research directions for environmental psychology scholars and modelers who want to use theory to inform simulation models of energy systems [ABSTRACT FROM AUTHOR]

This article proposes a method to improve the range of an electric vehicle (EV) by controlling its speed depending on the upcoming traffic signal status. A conventional Adaptive Cruise Control (ACC) controls an EV's speed such that there is a certain distance between the EV and the preceding vehicle. However, if the preceding vehicle drives at a non-optimum speed given the upcoming traffic signal status, as it nears the upcoming traffic signal the preceding vehicle will have to dissipate the unnecessarily gained kinetic energy by braking. If the EV blindly follows such a preceding vehicle using a conventional ACC, the EV will also have to dissipate a part of its kinetic energy by braking. In this work, this problem is addressed by proposing an Efficient Cruise Control (ECC). In the proposed ECC, if the EV is within a certain distance of the upcoming traffic signal, its speed reference is calculated based on the traffic signal status, while maintaining a minimum safe inter-vehicular distance from the preceding vehicle. The ECC is designed using Model Predictive Control theory and it is studied in a simulation environment using a Tesla S vehicle model. The simulation results show that the proposed controller improves the EV's energy efficiency and therefore range, where the latter is an important bottleneck in widespread adoption of EVs. [ABSTRACT FROM AUTHOR]

The purchase of an electric vehicle has become a widely debated topic by the economic community in recent years. However, few personal automobile users, who purchased new cars, have chosen a fully electric vehicle. The novelty of this research came from the assumption that there is a lack of knowledge in this field and fuelled by contradicting information. Potential electric vehicle buyers have developed a real psychosis on the subject, the most consistent motives being among others the charge anxiety. Many researchers consider that the worries of the vehicle users are exaggerated and are not based on reality. Better documentation of the subject would reduce these fears and would increase the process of electrical vehicles absorption. The main objective of this article is to analyse the main anxiety factors by buying an electric vehicle and to reduce the related anxiety. For this purpose, the authors have performed an econometric analysis based on a questionnaire distributed online and face to face in Romania. [ABSTRACT FROM AUTHOR]

Range anxiety describes the drivers’ stress regarding the available battery range while driving an electric vehicle. Considering this issue as a barrier against general acceptance of electric vehicles, several researches has been reviewed. The results show that there is no direct communication among current networks of charging stations which causes isolation in these networks. Thus, the users are not able to use cross-network facilities which leads to range anxiety. To overcome, a protocol is suggested to be used in development of RESTful web services to provide direct communication among the networks of charging stations. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) has been a main component of car sharing market because of their environment friendly attributes. However, imbalance and range anxiety, as frequent problem in traditional one-way EVs sharing system, make a poor operation sometime. For perform a practical one-way car sharing system, considering the special attributes like charging demand, charging modes and range anxiety resulting from limited battery volume about EVs, we propose a mixed integer programming(MIP) model to satisfy the demand generated by customers who change reserved drop-off station. Moreover, we address the location problem with the allocation of two types of charging piles to meet the different types of demand (i.e. the fast charging mode meet the urgent rent demand). Further, we make a numerical study combining practical data collected in Beijing with practical data to decide operation variables above for one-way car sharing system. We find that preference has an influence on the depots location and fleet size of the one-way EVs sharing system. [ABSTRACT FROM AUTHOR]

In electric vehicle, rechargeable battery served as energy source for all its system operation which include electric motor for propulsion system and also other auxiliary components. Therefore, it becomes an important issue to be tackled in EV technology in order to enhance the battery energy capacity for long range operation. In general public view, people tend to be very concern in purchasing the electric car. One of the concerns lies on the question of how far they can travel with only battery for their car propulsion means. Therefore, this study tries to investigate the relation between battery types and the range anxiety faces by electric car makers. The investigations reveals that, Li-ion as the battery with high energy density cover more area or distance travel. [ABSTRACT FROM AUTHOR]

Battery Electric Vehicle (BEV) is a promising candidate in reducing air pollution and fossil fuel dependencies. It is a growing market for the automobile manufacturers. Although there are many advantages of driving a BEV, it is still not widely accepted in the market due to the limited driving range. Other than just improving the technologies that drive the vehicle, an additional range estimation system can calm the ‘range anxiety’ caused by the limited range of BEVs. Merely predicting the range based on the state of charge of the battery, the average driving speed, and the average power consumption is inadequate. This paper proposes a new range estimator, the dynamic range estimator, which also takes into account the driving behavior, in addition to the slopes of the trip for its energy estimation. The driving behavior is obtained based on the response to speed error and the time delay between throttle pedal and brake pedal switching. In this way, the driving behavior is a fixed response for any driving speeds on the same route thus, allowing the energy consumption to be compared for different speeds. [ABSTRACT FROM AUTHOR]