Automated Battery Management Systems for Electric Vehicles

Details

• Creators:
  Na, Woonki ; Xie, Yuanyuan
• Corporate Creators:
  San Jose State University. College of Business. Mineta Transportation Institute
• Corporate Contributors:
  California State University, Fresno. Fresno State Transportation Institute (FSTI) ; State of California SB1 2017/2018, Trustees of the California State University Sponsored Programs Administration ; Fresno County Transportation Authority ; United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
• Subject/TRT Terms:
  Active Artificial Intelligence Battery Management System Cell Balancing Cost Effectiveness Electric Vehicles Fuel Cell Vehicles Infrastructure Literature Reviews Performance Reliability Storage Batteries

  More +
• Publication/ Report Number:
  26-20
• DOI:
  https://doi.org/10.31979/mti.2026.2534
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Corporate Publisher:
  San Jose State University. College of Business. Mineta Transportation Institute
• Abstract:
  Electric vehicle (EV) safety, efficiency, and lifetime are strongly influenced by how well battery cells are managed, and as EV adoption accelerates, improving battery performance has become critical to vehicle reliability, cost, and public trust. This report conducts a field study on the core technologies and challenges in Battery Management Systems (BMS), focusing on the classification of BMS circuit topologies (design/structures) and systematically reviewing different topologies of active cell balancing circuits (systems that move energy from stronger battery cells to weaker ones). The study provides a detailed analysis of the working principles, advantages, and disadvantages of various active balancing circuit topologies. Additionally, it elaborates on the key algorithms underpinning battery balancing. The report also examines the main challenges in designing these systems, including balancing efficiency, cost, reliability, and the ability to scale. It also highlights the difficulty of accurately understanding battery conditions and making real-time decisions as operating conditions change. The study also summarizes and reviews major breakthroughs in balancing algorithms within the field. By conducting comprehensive research on circuit topologies and core algorithms, this report informs the design and performance optimization of BMS, particularly active balancing systems. Addressing these challenges is essential to improving EV safety, reducing costs, and supporting the broader adoption of electric vehicles.
• Format:
  PDF
• Funding:
  SB1-SJAUX_2023-26
• Collection(s):
  University Transportation Centers
• Main Document Checksum:
  urn:sha-512:4b20a69caaf683f4bfa079b5f98286f605ab0e237b04e2b7475773a317059caef0cdf39b5f62927776f575194071bd9128ed547985816684f248110488e37f17
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/92983/dot_92983_DS1.pdf
• File Type:
  [PDF - 6.61 MB ]