Virtual Sensor of Li-Ion Batteries in Electric Vehicles Using Data-Driven Analytic Thermal Solutions

verfasst von

Wei Guo Foo, Rufan Yang, Franz Erich Wolter, Hung Dinh Nguyen

Abstract

Lithium-ion batteries, especially for electric vehicles (EVs), present safety risks, suffer poor performances, and undergo rapid degradation when operating under high temperatures. This, therefore, necessitates thermal monitoring for timely intervention. However, computations for this purpose can be very expensive and difficult to implement in real time. To overcome this problem, we establish a framework based on closed-form solutions to heat equations to estimate important parameters based on measurement data. They will be used for deducing heat generation rates for constructing forward-monitoring models for estimation. Our results show that the root-mean-square error between the estimated and actual temperature is at most 0.23 for sensor input interval between 50 and 60 s over the monitoring time of 1200 s, both with and without varying input currents. In addition, our proposed method achieves computations circa 350 times faster than that of finite element methods.

Organisationseinheit(en)

Fakultät für Elektrotechnik und Informatik

Externe Organisation(en)

Nanyang Technological University (NTU)

Typ

Artikel

Journal

IEEE Transactions on Industrial Electronics

Band

71

Seiten

5844-5852

Anzahl der Seiten

9

ISSN

0278-0046

Publikationsdatum

19.07.2023

Publikationsstatus

Elektronisch veröffentlicht (E-Pub)

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Steuerungs- und Systemtechnik, Elektrotechnik und Elektronik

Ziele für nachhaltige Entwicklung

SDG 7 – Erschwingliche und saubere Energie

Elektronische Version(en)

https://doi.org/10.1109/TIE.2023.3292868 (Zugang: Geschlossen)