HOEMEV · Hierarchical Optimal Energy Management of Electric Vehicles

Hierarchical Optimal Energy Management of Electric Vehicles

The transportation sector is a key contributor to greenhouse gas (GHG), air pollution and noise. Road transport accounts for around one fifth of the GHG emissions of the European Union (EU). It has been widely recognized that vehicle electrification provides a potential way for the EU to move towards a more decarbonized transport system and sustainable circular economy. Although sales of electric vehicles have been growing steadily in recent years, they only represent 1.4% of all new cars sold in the EU in 2017. Developing electric vehicle technologies is essentially important to increase the market share, and control technology plays an indispensable role in improving the overall efficiency of electric vehicles; however, their control problem is very challenging because electric vehicles exhibit complex dynamics with uncertainties and nonlinearities, and strong physical couplings among different subsystems. Moreover, considering the significant advancement of other technologies in contributing to the development of smart transportation systems, it is highly promising to develop advanced control strategies for electric vehicles which can be combined with these latest enabling technologies to dramatically improve the overall efficiency of the energy management of electric vehicles. This was the main motivation for the fellow to pursue this project on electric vehicle control by developing an advanced electric vehicle control framework enhanced by the advantages of the latest enabling technologies in other disciplines. 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.

Data: CORDIS, © European Union