Space-decomposition-based Spectral Modeling for Distributed Battery Thermal Dynamics
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Detail(s)
Original language | English |
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Pages (from-to) | 1634-1641 |
Journal / Publication | IEEE Transactions on Transportation Electrification |
Volume | 8 |
Issue number | 2 |
Online published | 2 Nov 2021 |
Publication status | Published - Jun 2022 |
Link(s)
Abstract
Thermal behavior has sustainable impacts on the safety performance and cycle life of lithium-ion batteries. This paper proposes a physics/data hybrid modeling framework for the thermal process of the pouch cell. Since the thermal effects of the tab area have different dynamic characteristics from other parts of the battery, a space decomposition strategy is designed to generate a more effective multi-physics-based model. To capture the battery thermal dynamics in real time, a reduced-order model is derived using the eigenfunction-based spectral expansion. All the unknown nonlinearities and other disturbances are further compensated through data-based learning. Simulation studies and experiments demonstrate the effectiveness of the proposed modeling methodology.
Research Area(s)
- Batteries, Computational modeling, distributed parameter systems (DPSs), Eigenvalues and eigenfunctions, error compensation, Heating systems, modeling, Temperature sensors, Thermal conductivity, thermal variables measurement
Citation Format(s)
Space-decomposition-based Spectral Modeling for Distributed Battery Thermal Dynamics. / Zhou, Yu; Li, Han-Xiong; Xie, Sheng-Li.
In: IEEE Transactions on Transportation Electrification, Vol. 8, No. 2, 06.2022, p. 1634-1641.
In: IEEE Transactions on Transportation Electrification, Vol. 8, No. 2, 06.2022, p. 1634-1641.
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review