Oct 19, 2017 · This paper presents novel machine-learning-based methods for estimating the state of charge (SoC) of lithium-ion batteries, which use the Gaussian process ...
Oct 19, 2017 · This paper presents novel machine-learning based methods for estimating state of charge. (SoC) of Lithium-ion (Li-ion) batteries which use ...
This paper presents novel machine-learning based methods for estimating state of charge (SoC) of Lithium-ion (Li-ion) batteries which use Gaussian process ...
Jan 16, 2018 · In this paper, we propose novel data-driven methods for es- timating SoC of Li-ion batteries based on Gaussian process regression (GPR) ...
May 1, 2018 · Novel machine-learning-based methods for estimating the state of charge (SoC) of lithium-ion batteries, which use the Gaussian process ...
In this paper, a novel data-driven SOC estimation approach for Lithium-ion (Li-ion) batteries is proposed based on the Gaussian process regression framework.
Oct 1, 2021 · In this article, we propose the deep learning-based transformer model trained with self-supervised learning (SSL) for end-to-end SOC estimation.
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Mar 20, 2021 · A novel non-parametric model for lithium battery based on the Gaussian process regression is proposed.
We developed SoC estimation methods based on recurrent GPR and autoregressive recurrent GPR that model the nonlinear dependence of the SoC on the voltage, ...
Aug 15, 2020 · In this paper, a data-driven method based on Gaussian process regression (GPR) is proposed to provide a feasible solution.