This study evaluates the total cost of ownership (TCO) of fuel cell electric trucks (FCETs) in France, the United Kingdom, Germany, Italy, Spain, the Netherlands, and Poland, home to more than 75% of HDV registrations in the EU in 2020.

This short topical issues paper supports reconsidering the role of the car in a Mobility as a Service (MaaS) program. In particular, the authors consider the appeal of including electric cars as part of the sharing service, which we call electric car sharing as a service (ECSaaS).

This study aims to determine the optimal location of multi-type electric vehicle (EV) charging stations, e.g., fast and slow charging stations, for maximizing the covered traffic flows under a limited budget while considering EV users' partial charging behavior and elastic demand. A two-phase approach is proposed to efficiently solve this problem.

This paper estimates the maximum capability to reduce CO2 by substituting private car travel for an e-bike. The authors use spatial microsimulation (population-synthesis) to simulate the adult population within every small area in England, taking into account of area type and geodemographic circumstances of the population.

This study presents a mathematical model to describe the problem in detail. For solving the real-world situation, a template-based Adaptive Large Neighborhood Search is developed, complemented with constraint programming for charging management and quadratic programming for delivery and pickup trip schedules.

This study presents an Electric Vehicle Production Routing Problem (EVPRP) to achieve optimal decisions. The authors propose a mixed-integer linear programming model for the EVPRP, which is mathematically validated by solving (via CPLEX) the new instances generated compatible with the EVPRP.

Coordinated charging scheduling can improve the operating economics of charging stations and reduce the required amount of charging facilities. However, existing optimal scheduling schemes either simplify the charging station capacity modeling when considering the traffic uncertainty or ignore the future charging demands when considering charging capacity limitations.

This paper suggests a multi-objective system-level fast charging station recommendation approach to dynamically assign electric vehicles to suitable stations to advance the interests of the coupled system, fast charging stations, and electric vehicle users.

The disordered charging behavior of large-scale electric vehicles will immeasurably impact the distribution grid. How to simultaneously solve the demand for charging and discharging of large-scale electric vehicles and the safe operation of the distribution grid has been a research hotspot in recent years.

The main focus of the battery management system is the estimation of the battery's State of Charge (SOC), which is an indicator to determine the driving range of an electric vehicle. The Extended Kalman Filter (EKF) algorithm is the most promising for SOC estimation when the system is running.