Impact of Data Sampling Methods on the Performance of Data-driven Parameter Identification for Lithium ion Batteries

Cho, Gyouho; Kim, Youngki; Kwon, Jaerock; Su, Wencong; Wang, Mengqi

doi:10.1016/j.ifacol.2021.11.227

Cited by 2 publications

(1 citation statement)

References 14 publications

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“…With the recent advances in data-driven methods, highlighted by deep learning, many works in the literature have proposed data-driven methods to solve the technical challenges related to lithium-ion battery technology. In the literature, neural networks have been used in SOC prediction [8]- [13], SOH prediction [14]- [23], model parameter identification [24]- [28], abnormality diagnosis [29], and voltage estimation [30]. For battery temperature prediction, a combined fully connected neural network (FCN) and long short-term memory (LSTM) was implemented to estimate the battery surface temperature [31].…”

Section: Introductionmentioning

confidence: 99%

A Physics-Informed Machine Learning Approach for Estimating Lithium-Ion Battery Temperature

et al. 2022

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The physics-informed neural network (PINN) has drawn much attention as it can reduce training data size and eliminate the need for physics equation identification. This paper presents the implementation of a PINN with adaptive normalization in the loss function to predict lithium-ion battery cell temperature. In particular, the PINN was trained with the actual battery test data, and a lumped capacitance lithium-ion battery thermal relationship was applied to the loss function with the addition of a pre-layer and connection layer to the neural network architecture. The PINN architecture shows the most accurate battery temperature prediction compared with the fully connected neural network (FCN) and its variants evaluated in this study. The proposed PINN architecture has a mean square prediction error of 0.05 ºC with a limited number of training data and without battery thermal model identification.INDEX TERMS Physics-informed neural network, lithium-ion battery, battery temperature

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