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

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

This research investigates electric vehicle (EV) charging behavior and aims to find the best
method for its prediction in order to optimize the EV charging schedule. This paper …

Electric vehicles (EVs) have emerged as the green energy alternative for conventional
vehicles. While various governments promote EVs, people feel “range anxiety” because of …

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 …

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 …

Short-term prediction of the Electric Vehicle (EV) charging demand is of great importance to
the operation of EV fleets and charging stations. This paper develops a Long Short-Term …

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 …

Electric vehicles may reduce greenhouse gas emissions from individual mobility. Due to the
long charging times, accurate planning is necessary, for which the availability of charging …

With the widespread use of electric vehicles, their charging power demand has increased
and become a significant burden on power grids. The uncoordinated deployment of electric …