| Autor: |
Li, Yang, Karunathilake, Dulmini, Vilathgamuwa, D. Mahinda, Mishra, Yateendra, Farrell, Troy W., Choi, San Shing, Zou, Changfu |
| Zdroj: |
IEEE Industrial Electronics Magazine; Sep2022, Vol. 16 Issue 3, p36-51, 16p |
| Abstrakt: |
To unlock the promise of electrified transportation and smart grids, emerging advanced battery management systems (BMSs) will play an important role in the health-aware monitoring, diagnosis, and control of lithium-ion (Li-ion) batteries (see “Acronyms Used in This Article”). Sophisticated physics-based battery models incorporated into BMSs can offer valuable internal battery information to achieve improved operational safety, reliability, and efficiency and to extend the battery lifetimes. However, because they are developed from fundamental electrochemical and thermodynamic principles, rigorous physics-based models are saddled with exceedingly high cognitive and computational complexity for practical applications. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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