The role of artificial intelligence in the mass adoption of electric vehicles

M Ahmed, Y Zheng, A Amine, H Fathiannasab, Z Chen - Joule, 2021 - cell.com
The electrification of mass transportation is hailed as a solution for reducing global
greenhouse-gas emissions and dependence on unsustainable energy sources. The annual …

We got the power: Predicting available capacity for vehicle-to-grid services using a deep recurrent neural network

R Shipman, R Roberts, J Waldron, S Naylor, J Pinchin… - Energy, 2021 - Elsevier
Abstract Vehicle-to-grid (V2G) services utilise a population of electric vehicle batteries to
provide the aggregated capacity required to participate in power and energy markets. Such …

Estimating the aggregated available capacity for vehicle to grid services using deep learning and Nonlinear Autoregressive Neural Network

HS Nogay - Sustainable Energy, Grids and Networks, 2022 - Elsevier
In order for vehicle-to-grid (V2G) services to participate in the power and energy market, they
must provide as much aggregated capacity as the market needs. In order to provide this …

Online machine learning of available capacity for vehicle-to-grid services during the coronavirus pandemic

R Shipman, R Roberts, J Waldron, C Rimmer… - Energies, 2021 - mdpi.com
Vehicle-to-grid services make use of the aggregated capacity available from a fleet of
vehicles to participate in energy markets, help integrate renewable energy in the grid and …

Where will you park? predicting vehicle locations for vehicle-to-grid

R Shipman, J Waldron, S Naylor, J Pinchin… - Energies, 2020 - mdpi.com
Vehicle-to-grid services draw power or curtail demand from electric vehicles when they are
connected to a compatible charging station. In this paper, we investigated automated …

Behavior-Neutral Smart Charging of Plugin Electric Vehicles: Reinforcement Learning Approach

V Dyo - IEEE Access, 2022 - ieeexplore.ieee.org
High-powered electric vehicle (EV) charging can significantly increase charging costs due to
peak-demand charges. This paper proposes a novel charging algorithm which exploits …

A methodology based on floating car data for forecasting the available capacity for vehicle-to-grid services

A Comi, O Hriekova, U Crisalli, G Napoli - Transportation research …, 2024 - Elsevier
The paper investigates the exploitation of the current availability of large amounts of floating
car data (FCD) based on individual mobility for characterising car trips for forecasting the …

Integrating Artificial Intelligence into Electric Vehicle Energy Systems: A Survey

W Hua, D Mullen, A Wahid, K Sitabkhan… - … Workshop on Artificial …, 2023 - Springer
Electric vehicles play an important role in the global transition to “Net Zero” and the
decarbonisation of point source emissions from road transport, as their market share …

[HTML][HTML] Evaluation of electric vehicle response capability in power grid

SY Wong, K Liang, HH Goh - MethodsX, 2024 - Elsevier
In recent years, frequent and substantial area-wide power outages have underscored the
critical need for cities to possess robust backup power sources capable of swift response to …

11 THE ROAD TO ELECTRIC VEHICLES From architecture to portable battery storage via renewable energy research homes Rebecca Roberts

R Roberts - Research Journeys to Net Zero: Current and Future …, 2024 - books.google.com
Early research From a young age I have always been interested in the built environment,
specifically how a building or environment can make someone feel. Combining my love of …