Growing electric mobility makes it difficult for electric vehicles (EVs) to charge adequately
while charging infrastructure capacities are limited. Due to the prolonged charging times …

Electric vehicles (EVs) are the most important components of smart transportation systems.
Limited driving range, prolonged charging times, and inadequate charging infrastructure are …

As the smart city applications are moving from conceptual models to development phase,
smart transportation is one of smart cities applications and it is gaining ground nowadays …

Precise charging time prediction can effectively mitigate the inconvenience to drivers
induced by inevitable charging behavior throughout trips. Although the effectiveness of the …

Large-scale deployment of electric vehicles (EVs) poses a huge challenge to the operation
of the distribution network. As a possible mobile energy carrier, the interaction between EVs …

As a key pillar of smart transportation in smart city applications, electric vehicles (EVs) are
becoming increasingly popular for their contribution in reducing greenhouse gas emissions …

Battery electric vehicles (BEVs) assume a critical role in the promotion of transportation
electrification. Accurate analysis and prediction of BEVs charging behaviors are essential to …

Electric vehicles (EVs) have attracted growing attention in recent years. However, most
existing research has not utilized actual traffic data and has not considered real …

Plug-in Electric Vehicle (PEV) user charging behavior has a significant influence on a
distribution network and its reliability. Generally, monitoring energy consumption has …

In this paper, we developed and compared logit based models of Chinese electric vehicle
(EV) drivers' charging choice behaviors in terms of whether or not to charge at a destination …