Battery States Monitoring for Electric Vehicles Based on Transferred Multi-Task Learning

Yunhong Che, Yusheng Zheng, Yue Wu, Xianke Lin, Jiacheng Li, Xiaosong Hu, Remus Teodorescu

Research output: Contribution to journalJournal articleResearchpeer-review

1 Citation (Scopus)


State/temperature monitoring is one of the key requirements of battery management systems that facilitates efficient and intelligent management to ensure the safe operation of batteries in electrified transportation. This paper proposes an online end-to-end state monitoring method based on transferred multi-task learning. Measurement data is directly used for sharing information generation with the convolutional neural network. Then, the multiple task-specific layers are added for state/temperature monitoring. The transfer learning strategy is designed to improve accuracy further under various application scenarios. Experiments under different working profiles, temperatures, and aging conditions are conducted to evaluate the method, which covers the wide usage ranges in electric vehicles. Comparisons with several benchmarks illustrate the superiority of the proposed method with better accuracy and computational efficiency. The monitoring results under extremely current working profiles and variable internal and external conditions are evaluated. Results show that the mean absolute error and root mean square error of state of charge and state of energy estimation are less than 2.31% and 3.31%, respectively. The above errors in the prediction of future temperature five steps ahead are less than 0.89 °C and 1.29 °C, respectively. The framework is also suitable for monitoring second-life batteries retired from electric vehicles. This paper illustrates the potential application of data-driven multi-state monitoring throughout the entire battery life.

Original languageEnglish
JournalIEEE Transactions on Vehicular Technology
Issue number8
Pages (from-to)10037-10047
Number of pages11
Publication statusPublished - 1 Aug 2023

Bibliographical note

Publisher Copyright:


  • Aging
  • Batteries
  • Battery charge measurement
  • Battery states monitoring
  • Estimation
  • Monitoring
  • multi-task learning
  • State of charge
  • Temperature measurement
  • temperature prediction
  • transfer learning


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