Multi-modal framework for battery state of health evaluation using open-source electric vehicle data

Accurate, practical, and robust evaluation of the battery state of health is crucial to the efficient and reliable operation of electric vehicles. However, the limited availability of large-scale, high-quality field data hinders the development of the battery management system for state of health estimation, lifetime prediction, and fault detection in various applications. In this work, to gain insights into underlying factors limiting battery management system performance in real-world vehicles, we analyze the operational data of 300 diverse electric vehicles over three years to understand the disparities between field data and laboratory battery test data and their effect on state of health estimation.…

• NN
  National Natural Science Foundation of China

  Awards: U23A20327, 52402465, 72361137006
• NK
  National Key Research and Development Program of China

  Award: 2022YFB3305403