smart charging

Unrestricted charging of electric vehicles (EVs) can result in violations of the grid’s operating limits, and/or equipment damage or failure. To address this, the researchers propose a two-stage smart charging algorithm for EVs in single-family residences.

This paper describes the development and demonstration of a smart charging system for a plug-in electric vehicle (EV) that can help manage grid impacts.

To address the challenges of electric grid stress and fleet operator costs associated with commercial electric vehicle fleets, this report presents a highly flexible smart charging algorithm for managing EV fleets that arrive and depart from a common depot on a schedule.

The report involves a discussion of smart charging for electric vehicles, a comprehensive literature review on the subject, development of models for analyzing EV charging and grid impact, and algorithms for solving the smart charging problem.

This study aims to develop a prediction framework based on a Bidirectional Long Short-Term Memory Network model to suggest when battery electric vehicle drivers should charge their vehicles, in order to to provide a more accurate and precise method of predicting charging events than conventional machine learning models.