Periodic Reporting for period 1 - HOEMEV (Hierarchical Optimal Energy Management of Electric Vehicles)
Reporting period: 2019-08-01 to 2021-07-31
The overarching objective of this project was to develop a novel computationally efficient hierarchical adaptive optimal control framework incorporating transportation information and drivers’ habits suitable for energy management of multi-source electric vehicles. This project aimed to sufficiently merge the critical information of human, road and vehicle with a hierarchical control framework to facilitate the energy management of electric vehicles. The proposed cutting-edge research will contribute to the fundamental research of electric vehicle energy management by developing the next generation electric vehicle control strategy. The proposed research not only benefits EU vehicle and battery industries, but also contributes to the research excellence of the EU in wider disciplines.
Upon finishing the project, the fellow has successfully advanced a hierarchical and predictive control theory for energy management of electric vehicles and applied them to design a distribution strategy adaptively according to driving range, transportation information and battery performance variation. The fellow conducted a variety of research on hierarchical optimal energy management of electric vehicles. The project has fully achieved its objectives and milestones according to the well-designed research plan.
After the high-quality research at QMUL, the fellow published 44 papers in top journals. These papers are open access. Based on the project support, the fellow not only finished all the designated research tasks, but also extended the research to intelligent connected vehicles and advanced lithium-ion battery control. In addition, the fellow attended a few international conferences (even with the huge challenges as a result of COVID-19 pandemic), including the 34th World Electric Vehicle Symposium & Exhibition, the 4th CAA International Conference on Vehicular Control and Intelligence, and MSCA European Green Deal cluster, to disseminate research output. The fellow won the Excellent Paper Award in EVS34. The fellow was elected to the Fellow of Institution of Engineering and Technology, due to his outstanding contributions to optimal control of electric vehicles. The fellow was also elected to an editor of two journals: IEEE Access and Vehicles.
The project’s research output can dramatically improve the controlling performance of widely-accepted lithium-ion batteries. As the key energy storage components of electric vehicles, lithium-ion batteries need to be properly managed to ensure safe, efficient, and reliable operation. To promote on-board management for batteries, the fellow has provided a game-changing software based on the developed hierarchical high-performance management algorithms using the advantage of cloud computation and wireless communication. The project can reduce the occurrence probability of hazard in batteries by 90%, and has improved the operation performance of batteries dramatically. The fellow’s research output has shown potential market opportunities as well as having wider impact in terms of aligning with the green deal and a decarbonized transport system and sustainable circular economy through improving electric vehicle and battery technology. The fellow’s research output could be a valuable reference that would be of interest to the government and could be shared with instructive suggestions to policymakers to potentially influence the vehicular technology development and electric vehicle future trends. Some general perspectives were summarized by the fellow and shared through the MSCA Green Deal Cluster Event.