Our Group

We focus on modeling, estimation, optimization, and control of energy storage systems, including batteries, supercapacitors, and flywheels, for electrified vehicles and renewable energy systems. Using energy storage as a bridge, we are thrilled to connect automotive, transportation, and power system communities through interdisciplinary projects and fill the gap between different energy sectors. Our lab is committed to advancing efficient, reliable, and sustainable power and transportation systems, contributing to a greener future.

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Openings: Our lab is looking for passionate and highly motivated Postdoc Researchers and PhD students. Several positions will be available in energy storage areas, including but not limited to:

• Advanced Battery Management System:
  • Physics-informed machine learning for battery condition monitoring
  • State and parameter estimation at battery string and pack levels
  • Novel power electronics solutions for managing substantial, heterogeneous battery cells
  • Data-driven methods for: 1) detecting cell-level faults in battery packs; 2) estimating battery remaining useful life; and 3) fast evaluating/classifying the used battery cells

Preferred Qualifications: Applicants are expected to have BS/MS/PhD degrees in Electrical Engineering, Control and Automation, Power and Energy, Applied Mathematics, Automotive Engineering, or other related fields.

Prospective candidates, including visiting PhD students in related areas, are welcome to contact Dr. Song at [email protected] with your CV, transcripts, and a 1-page cover letter introducing your research background and interest. Please kindly note that due to the high volume of inquiries, I may not be able to respond to everyone. However, I will carefully review each email and will get back to you ASAP if your qualifications align well with current opportunities.

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