The study presents a dynamic optimization framework for assessing the potential of the SAEV fleet in enhancing energy resilience in critical buildings through V2B services.

This paper introduces an innovative modeling approach to address research gaps in urban decarbonization pathways, considering home charging and battery swapping stations' implications.

The study employs a three-dimensional dataset to estimate the impact of domestic EV purchase subsidies on adoption in 316 Chinese cities from January 2016 to December 2019.

The paper addresses a new optimal charging station location problem for intercity highway networks with diverse electric vehicle driving ranges and multiple charging needs during long-haul trips.

The proposed system aims to regulate DC bus voltage and track the battery and supercapacitor with desired references under different load conditions.

The study investigates spatial-temporal factors affecting EV charging station utilization in Cary, North Carolina, using data from 2019-2022 from six charging locations.

The research work aimed to understand battery electric vehicle application with special focus on induction motor due to its magnetless construction and low cost. The work also focused on the selection of suitable power electronic converter and control scheme.

In this study, parameter estimation of the motor is carried out using Gray Wolf Optimization. The unknown parameters are adapted through optimization techniques using a cost function.

This thesis describes the design, control and analysis of both contact based and contactless power transfer system suitable for EV charging system applications. 

This research aims to model, simulate and optimize the components of the Solar Fuel Cell Battery Hybrid Electric Vehicle (SFCHBEV) system. the objective is realized in three steps: design and development of SFCBHEV system, development of an intelligent energy management system, and optimal component sizing of the system using meta-heuristic algorithms.