Estimation and optimization of key lithium-ion battery physical characteristics in hybrid plug-in electric vehicles.
To develop the next-generation EV energy management technology, it is imperative to investigate novel algorithm designs and methods so that we can accurately and effectively incorporate the internal battery states associated with the key physical characteristics to construct an optimal vehicle energy management controller. The critical battery states for EV energy management include state of charge (SOC), state of health (SOH), and state of power (SOP). Despite the importance of accurately combining battery SOC, SOH, and SOP in energy management, little work has been done to investigate the synergetic effects of all these states, particularly in a predictive energy control framework of EVs. With the identified research gaps, this project will make full use of the comprehensive research resources of Chalmers, Chongqing University, and industry partners from both Sweden and China, and take a bold lead to develop hierarchical estimation and optimization methodologies for lithium-ion batteries in EVs. In addition to high-quality fundamental research, this joint mobility project will also contribute to the education/training of doctoral students and postdoc researchers, as well as to the internationalization of both universities.
Torsten Wik (contact)
Full Professor at Chalmers, Electrical Engineering, Systems and control, Automatic Control
Researcher at Chalmers, Electrical Engineering, Systems and control, Automatic Control
The Swedish Foundation for International Cooperation in Research and Higher Education (STINT)
Project ID: CH2020-8779
Funding Chalmers participation during 2021–2024
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