The authors analyzed at the fuel consumption of internal combustion HDVs manufactured between 2012 and 2017 and certified under Stage 1 and Stage 2 fuel consumption requirements. This research does not include battery or fuel cell electric vehicles.

Electrification of vehicle fleets has gained considerable momentum as many companies involving urban mobility in their operations are committed to reducing their carbon footprint.

Private electric vehicles and electric taxis are two of the most common electric vehicles (EVs) in the cities. It is important to regulate the charging load file of PREVs and ETs, which has a significant impact on the power grid.

This article utilizes consortium blockchain to design a decentralized, secure, and privacy-preserving scheme for bidirectional power trading between electric vehicles (EVs) and the power grid.

This paper discusses the Inspiria charging station facility in Norway, which enables various charging point operators to offer different charging systems for different purposes and needs.

A new means of transport for the German market is personal light electric vehicles (PLEVs). The most common form of PLEV at present is the e-scooter (e-kick-scooter). This new type of mobility, and its use, are part of the public discourse and discussed in the media.

This paper defines and discusses different charging strategies of EVs. The literature covering Plug-in Electric Vehicles (EVs) contains many charging/discharging strategies.

The launch of both battery electric vehicles (BEVs) and autonomous vehicles (AVs) on the global market has triggered ongoing radical changes in the automotive sector. The aim of this paper is to provide an overview of the cost structure of BEVs and AVs, as well as to define the technical parameters that are important.

Autonomous electric buses (AEB) have widely been envisioned in future public transportation systems due to their large potential to improve service quality while reducing operational costs.

This paper presents the state of charge estimation of lithium-ion battery systems using six machine learning algorithms for electric vehicles application.