In this paper, the genetic algorithm is used to optimize the weights and thresholds of the neural network, and a neural network cold-start emission prediction model for hybrid electric vehicles is built.

The utilization of public transportation has been encouraged at the societal level as a solution. An all-electric vehicle is evaluated in this research paper.

This study reviews the studies that apply machine learning models to improve EV charging service operations and provides future research directions.

This article presents a comprehensive review of existing literature on the life cycle assessment of "lightweighting" electric vehicles.

In this article, the problem of planning the flexibility of electric vehicle charging and discharging to coordinate with wind and solar production and to compensate for the uncertainty of these resources has been solved using the CPLEX solver.

The research study emphasizes the impact of braking concepts considering regenerative braking system and energy consumption aspects in electric vehicles in a perspective different from earlier approaches.

In this work, the authors investigated the problem of scheduling the charging of electric vehicles to reduce the maximum peak power while satisfying all charging demands.

The study analyzes ZE-HDV specifications, including battery suppliers, capacity, range, and energy density at the OEM level, and tracks advancements in battery-swapping and FCEV technologies.

The study provides detailed cost breakdowns for the ZEV powertrain battery and other components across various Canadian passenger vehicle classes and predicts changes in these costs over the next two decades.

Using two approaches to model regional carbon taxes on airfares—accounting by country of departure and accounting by operator registration country—this paper examines the market effects of various regulatory approaches.