Optimal-Sensing-Based Recursive Estimation for Temperature Distribution of Pouch-Type Batteries

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

2 Scopus Citations
View graph of relations



Original languageEnglish
Pages (from-to)912-919
Journal / PublicationIEEE Transactions on Transportation Electrification
Issue number1
Online published2 May 2022
Publication statusPublished - Mar 2023


Real-time monitoring of the battery temperature distribution is essential in developing advanced thermal management systems. This work proposes a recursive temperature field estimation methodology for pouch-type batteries under optimal deployment of limited sensing. First, we utilize the time/space spectral expansion to mathematically derive a physics-based dynamic model considering uncertainty from the complex thermal process. Then we find the optimal sensor placement through the observability degree of the system quantified by the attenuation rate of estimation error. Finally, we perform model-based temperature field estimation, whose performance is boosted by favorable measurements from layout-optimized sensors. Experimental studies indicate the validity of the proposed method.

Research Area(s)

  • adaptive estimation, Batteries, distributed parameter systems, Heating systems, Mathematical models, modeling, Temperature distribution, Temperature measurement, Temperature sensors, thermal variables measurement, distributed parameter systems (DPSs)