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Special Session #8: Battery Diagnosis, Modeling, and Energy Management for Electric Vehicles - VPPC 2022

Special Session #8: Battery Diagnosis, Modeling, and Energy Management for Electric Vehicles

Co-Organizer: Yuanyuan Xie, California State University Fresno, USA
Co-Organizer: Irune Villaluenga, POLYMAT, the Basque Center for Macromolecular Design and Engineering, Spain
Co-Organizer: Kenneth Higa, Lawrence Berkeley National Laboratory, USA

Call For Papers

With the increasing adoption of electric vehicles (EVs), a safe and reliable battery system is one of the most important targets facing engineers. Effective data collection, battery modeling, and diagnosis methods can help engineers monitor battery state-of-health (SOH) and state-of-charge (SOC) more accurately. There is a very broad research area related to battery SOH monitoring and prognosis, such as battery modeling, machine learning, balancing mechanisms, energy management, battery pack topology, battery diagnostic algorithms, etc.

This special session aims at gathering research on battery diagnosis, prognosis, modeling, energy management and their applications in electric vehicles. Through this session, we would like to exchange recent research findings and establish connections and collaboration opportunities between researchers of this field.


Yuanyuan Xie

Bio: Dr. Yuanyuan Xie is an Assistant Professor working in the Department of Mechanical Engineering of the California State University Fresno. He earned his doctorate degree from the University of South Carolina, Columbia in the year of 2013. Prior to joining Fresno State, he worked as a postdoctoral researcher at Chemical Science and Engineering Division of Argonne National Laboratory. His research spans from electrochemical systems, transport phenomena, porous materials and energy storage & conversion. He is also an active member of the Electrochemical Society, the Material Research Society and the American Society of Mechanical Engineering.


Irune Villaluenga

Bio: Dr. Irune Villaluenga is a staff scientist at Polymat: Molecular and Supramolecular Materials Laboratories. She obtained her bachelor’s degree in 2005 and her PhD degree in chemistry in 2010, both from the University of the Basque Country (Spain). This was followed by two postdoctoral appointments at CIC Energigune (Spain) and Lawrence Berkeley National Laboratory/University of California, Berkeley (USA). In 2018, she joined as senior battery materials scientist at Blue Current, Inc. (USA). In 2020, she moved to Spain to join Polymat: Molecular and Supramolecular Materials Laboratories. Her current research interests include smart battery materials, nanostructured block copolymers, hybrid electrolytes, and electrochemistry for energy storage applications


Kenneth Higa

Bio: Dr. Kenneth Higa is a Chemist Research Scientist / Engineer in the Energy Storage and Distributed Resources Division of the Energy Technologies Area at Lawrence Berkeley National Laboratory (Berkeley Lab). His research has ranged from macrohomogeneous modeling of lithium-ion batteries to construction of novel experimental setups to study electrode manufacturing. He has authored a few open-source software packages, including PyGDH, a Python package for solving user-specified discretized equations with the finite volume method on 1D and simple 2D spatial domains. Kenny received a B.S. degree in Chemical Engineering at Caltech, and M.S. and Ph.D. degrees in Chemical Engineering at the University of Illinois at Urbana-Champaign, and was a postdoctoral fellow at Berkeley Lab.


Submission Deadline EXTENDED: 30 May 2022
Acceptance notification: 11 July 2022
Final paper submission deadline: 8 August 2022

To submit a paper to this Special Session, please visit: