EVOLVE: Electric Vehicles Point Location Optimisation via Vehicular Communications
Lead Research Organisation:
University of Huddersfield
Department Name: Sch of Computing and Engineering
Abstract
Recent developments in the Electric Vehicles (EV) technologies have made great strides to offer new modes of smart green urban mobility, where EVs are used as the main transportation mode replacing the conventional diesel and petrol powered vehicles. EVs are expected to play a key role in achieving ambitious targets of lowering greenhouse emission in the transportation sector. Given the EV penetration rates and future forecasts, it is essential to develop technologies that tackle charging management of EVs considering a holistic view of charging supply/delivery management for EVs, communication of EVs to the smart grid infrastructure system using 5G and beyond systems, smart grids and big data analytics for EVs optimise smart mobility and enhance the quality of experience for EV users. EVOLVE aims to exploit the scientific excellence and expertise of key academic and industrial players into a joint collaborative effort to design, develop and test various technologies that consider the holistic view of EV charging taking into account the view of technical and business stakeholders. EVOLVE will pursue innovation for advancing the technologies in EV charging ecosystem by orchestrating and managing the underlying networking and computational resources, design innovative algorithms using Artificial Intelligence (AI) and Machine Learning ML), developing communication protocols, prediction and optimising load in smart grids, developing software systems and user interfaces (UIs). EVOLVE aims to transcend analytical models and simulation-based validation and aims to deliver five proof-of-concept (PoC) demonstrations. EVOLVE project will provide a platform to foster a close collaboration between academia and industry partners providing each with a unique experience to create new knowledge, share know-how and skills development.
Organisations
Publications
Abbas W
(2024)
Heuristic Antenna Selection and Precoding for a Massive MIMO System
in IEEE Open Journal of the Communications Society
Che F
(2023)
Novel Fine-Tuned Attribute Weighted Naïve Bayes NLoS Classifier for UWB Positioning
in IEEE Communications Letters