Performance comparison of lithium polymer battery SOC estimation using GWO-BiLSTM and cutting-edge deep learning methods

Taş, Göksu; Bal, Cafer; Uysal, Ali

doi:10.1007/s00202-023-01934-z

Cited by 2 publications

(1 citation statement)

References 49 publications

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“…State of charge (SOC) is one of the core parameters of lithium power batteries, the accurate estimation of its value not only ensures the safe and reliable operation of the battery, but also improves the battery range and service life [1] . There are four common approaches for estimating the SOC of Li-ion batteries, which are modelbased method [2] , fusion model-based method [3] , experimental-based method [4] and data-driven method [5] . The experiment-based method is simple in principle, easy to implement, and limited in practical application [6] .…”

Section: Introductionmentioning

confidence: 99%

SOC Estimation of Li-ion Battery using on Variational Mode Decomposition and Transformer-Generative Adversarial Network

Wang,

Jiao,

et al. 2023

E3S Web Conf.

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Accurate estimation of the state of charge (SOC) of lithium battery is crucial to improve the dynamic performance and energy utilization of batteries. The method, the existing neural network are used to estimate SOC, has the problems of low accuracy and poor stability under complex working conditions. A new algorithm are proposed to estimate the SOC, which combines Transformer and Generative Adversarial Network (GAN), and the Variational Modal Decomposition (VMD). Firstly, as the excellent prediction ability of Transformer, Transformer is used as the generative network of GAN. Secondly, VMD is used to decompose the SOC historical data into six subsets to increase the input features. Finally, DST work data from the University of Maryland CALCE dataset is used for model training, and the VMD-Transformer-GAN algorithm is compared with LSTM, GRU, and BiLSTM algorithms for experiments. The experimental results show that the VMD-Transformer-GAN algorithm algorithmic estimation model has high stability and accuracy, which verifies the feasibility of the improved scheme.

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