Management of Electric Vehicles through the Internet of Vehicles

The future vehicles will be connected, automated, shared and electrified (CASE) through the emerging Internet of Vehicles. This PhD project is a fantastic opportunity to work with the expert team in the Birmingham CASE Automotive Research and Education Centre which is a cross-campus research institute in a global top 100 university. The work aims to make a timely contribution to zero-emission transport through advanced modelling and control of large-scale electric vehicle platoons. The research will be conducted based on the state-of-the-art X-in-the-loop testing facility (e.g., AVL Testbed.Connect, AVL PUMA, ETAS LABCAR, IPG-CarMaker) and the research outcome will include an open-source 3D driving environment and onboard control software for real-time multi-objective (energy economy, durability) optimal control. At the core of this research is the development of a multi-agent reinforcement learning algorithm which is capable of environment perception and decision-making from two main dimensions, i.e., a deep inspection of vehicle powertrain systems (e.g., battery system or fuel cell system) and a global interaction with the traffic infrastructure and the vehicles driving around. We will examine the robustness, reliability, and feasibility of the developed models and algorithms with industry partners.