2022
DOI: 10.1002/ente.202200151
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State‐of‐Health Estimation of Lithium‐Ion Batteries Based on Thermal Characteristics Mining and Multi‐Gaussian Process Regression Strategy

Abstract: Accurate prediction of the state of health (SOH) is essential to ensure the safety and reliability of battery operation. The thermal factor is an important indicator of SOH and many methods based on temperature are sensitive to measurement noise. To improve SOH estimation precision, a new health indicator (HI) directly extracted from the temperature curve is developed and an integrated multi-Gaussian process regression (MGPR) model is proposed. First, based on the trend analysis of the charging temperature cur… Show more

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Cited by 7 publications
(3 citation statements)
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“…In the recent years, artificial intelligence (AI) and specially machine learning (ML) techniques have progressed as powerful tools to support the state estimation and performance analysis of batteries [29,30] and control their manufacturing processes. [31,32] Considering each individual process of Li-ion production chain, ML models are developed to relate the manufacturing variables and the physical characteristics of the cathode in studies.…”
Section: Doi: 101002/ente202200893mentioning
confidence: 99%
“…In the recent years, artificial intelligence (AI) and specially machine learning (ML) techniques have progressed as powerful tools to support the state estimation and performance analysis of batteries [29,30] and control their manufacturing processes. [31,32] Considering each individual process of Li-ion production chain, ML models are developed to relate the manufacturing variables and the physical characteristics of the cathode in studies.…”
Section: Doi: 101002/ente202200893mentioning
confidence: 99%
“…[ 16 ] At present, there is no research on estimating the self‐discharge voltage drop by GPR. However, GPR method has been widely used in the field of SOC [ 17 ] and state of health (SOH) [ 18 ] of lithium batteries. Deng et al [ 17 ] and Guo et al [ 18 ] show that the GPR model has good performance in the estimation of SOC and SOH.…”
Section: Introductionmentioning
confidence: 99%
“…However, GPR method has been widely used in the field of SOC [ 17 ] and state of health (SOH) [ 18 ] of lithium batteries. Deng et al [ 17 ] and Guo et al [ 18 ] show that the GPR model has good performance in the estimation of SOC and SOH. As the self‐discharge process of a lithium‐ion battery is a complex, dynamic, and nonlinear electrochemical process, it is often difficult to accurately estimate the self‐discharge voltage drop.…”
Section: Introductionmentioning
confidence: 99%