The monitoring of temperature distribution is critical to the safety performance and cycle life of lithium-ion batteries (LIBs). This article introduces a systematic solution for real-time modeling of the battery thermal process under nonhomogeneous boundary conditions. The proposed method integrates the nonhomogeneity separation and the time-space (T/S) separation. First, the nonhomogeneity separation is designed to homogenize the boundary conditions. Then, the spatiotemporal dynamics can be decomposed by the T/S separation. With the T/S separation, a set of spatial basis functions (SBFs) are designed to deal with the spatial complexity, and then, a corresponding temporal model is constructed to capture the temporal nonlinearity. According to the Rademacher complexity, the generalization bound of the developed model is deduced, thereby ensuring the modeling performance. Experimental studies demonstrate the validity of the proposed modeling method.
Dual Separation-Based Spatiotemporal Modeling Methodology for Battery Thermal Process Under Nonhomogeneous Boundary Conditions
IEEE Transactions on Transportation Electrification ; 7 , 4 ; 2260-2268
01.12.2021
2259159 byte
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Extreme learning machine based spatiotemporal modeling of lithium-ion battery thermal dynamics
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AIAA | 1963
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