Nov 15, 2023 · In this paper we have presented a hybrid approach for the critical task of estimating battery SOC from EIS data. Our method combines data-driven ML with equivalent-circuit models, and was validated experimentally on …

May 15, 2021 · To this end, this paper employs informative measurements of electrochemical impedance spectroscopy (EIS) in machine learning models (ML), i.e., linear regression model and Gaussian process regression (GPR), to accurately predict the SOC of li-ion batteries.

Dec 1, 2024 · Electrochemical Impedance Spectroscopy (EIS) is a powerful technique for characterizing batteries, providing valuable insights into charge transfer kinetics like ion diffusion and interfacial reactions.

The paper proposes a new experimental measurement method for State of Charge (SoC) estimation able to optimize between measurement time and target Accuracy adoptable in Battery Management System (BMS) design where both these parameters are key parameters for the overall management performance.

Apr 6, 2020 · In this paper, we show that gaussian process regression (GPR) can accurately estimate the capacity and predict RUL using the EIS spectrum, which are key indicators of the SoH of a battery.

In this paper, a battery state of charge (SoC) estimation strategy with deep neural networks (DNN) and Electrochemical Impedance Spectroscopy (EIS) is proposed. EIS data was obtained for a range of conditions and was used as inputs to a DNN.

Dec 12, 2024 · To tackle this challenge, we propose a novel partial-range SOC-insensitive model for precise battery capacity estimation using transformer neural networks complemented by an EIS change pattern model based on the k-nearest neighbors (KNN) algorithm.

Apr 25, 2011 · EIS measurements were performed on 3-electrode coffee bag Li-ion cells during cycling with the aim of identifying the ageing mechanisms in these applications and determining impedance parameters related to the State-of-Charge (SoC) and State-of …

Mar 4, 2025 · EIS measurement: Electrochemical Impedance Spectroscopy (EIS) was measured at every 25% SOC during charging and discharging at 0.1 C. 3. Cycling for degradation: The cell was cycled at 0.5 C for 50 cycles using 80% of the voltage range.

Buchicchio et al. [33] demonstrated that using EIS's ECM parameters for SOC estimation could enhance accuracy compared to using raw EIS data on the same dataset. Random forest (RF) is an ensemble learning method containing multiple decision trees and an effective method for processing one-dimensional data [34].