Accurately and efficiently predicting the fuel consumption of vehicles is the key to improving
their fuel economy. This paper provides a comprehensive review of data-driven fuel …

Electric vehicles are growing in popularity as a form of transportation, but are still underused
for several reasons, such as their relatively low range and the high costs associated with …

Open datasets serve as facilitators for researchers to conduct research with ground truth
data. Generally, datasets contain innovation and knowledge in the domains that could be …

Vehicle Energy Consumption (VEC) estimation aims to predict the total energy required for a
given trip before it starts, which is of great importance to trip planning and transportation …

Recently, the Industrial Internet of Things (IIoT) has shown great application value in
environmental monitoring. However, it suffers from serious bottlenecks in energy and …

Accurately predicting the power demand of large-scale electric vehicles (EVs) is one of the
key tasks of power grid operation optimization. However, this task is difficult to complete due …

Long short-term memory (LSTM) network is extensively researched as an effective tool for
time series prediction, the addition of spatial attention can portray the spatial relationship …

The increasing adoption of electric vehicles has led to new and unpredictable load
conditions for electric vehicle charging stations (EVCSs), making charging demand …

The increasing demand of energy consumption reduction makes evaluating multi-load a
growing and notable challenge. However, if the accuracy of energy evaluation in integrated …

Implementation of advanced intelligent deep learning techniques for Electric Vehicles (EVs)
energy consumption analysis is obstructed by two main subjects. First, the problem of finding …