This research paper explores the importance of optimizing the performance of electric
vehicle (EV) batteries to align with the rapid growth in EV usage. It uses predictive machine …

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 …

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 …

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 …

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

For a user-centered deployment of electric vehicle supply equipment (EVSE) infrastructure, it
is vital to understand electric vehicle user charging behavior. This study identifies user …

As the share of battery-electric vehicles (BEVs) in car fleets increases, more and more car
holders will need to charge their electric vehicles at public facilities. Designing public …

The further demand for electric vehicles and smart grids prompts that the comprehensive
function of lithium‐ion batteries (LIBs) has been improved greatly. However, due to sluggish …

Battery electric vehicles (BEVs) have started to play a significant role in the transport sector
and automotive industries. The broader market penetration of BEVs has still not been …

As the number and range of electric vehicles in use increases, and the size of batteries in
those vehicles increases, the demand for fast and ultra-fast charging infrastructure is also …