State of Health Estimation Method for Lithium-Ion Batteries via Generalized Additivity Model and Transfer Component Analysis

Lin, Mingqiang; Yan, Chenhao; Zeng, Xianlin

doi:10.3390/wevj14010014

Cited by 3 publications

(1 citation statement)

References 33 publications

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“…More seriously, battery degeneration can lead to environmental changes, with high temperatures and high humidity changes, and the state of safety (SOS) of the battery will change and cause safety accidents [8,9]. Thus, the parameter of SOH needs to be accurately obtained, it could maintain the stable operation of the battery and prevent safety accidents [10,11].…”

Section: Introductionmentioning

confidence: 99%

State of Health Estimation for Lithium-Ion Batteries Using IAO–SVR

Xing

Liu

Luo

et al. 2023

WEVJ

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The state of health (SOH) of lithium-ion batteries (LIBs) needs to be accurately estimated to ensure the safety and stability of electric vehicles (EVs) while in operation. In this paper, we proposed a SOH estimation method based on Improved Aquila Optimizer (IAO) and Support Vector Regression (SVR) to achieve an accurate estimation of SOH. During the charging and discharging phases of the battery, we analyzed the trends in current, voltage, and energy, then extracted four features. We used the Kendall coefficient and gray relational grade to prove that features and SOH were highly correlated. On the other hand, IAO was used to optimize the penalty factor and kernel function parameters of the SVR to further improve the generalization and mapping ability. The proposed method was verified under different operating conditions using the CACLE battery data set; the results show that high accuracy can be achieved in SOH estimation via IAO–SVR, and the estimation error of mean MAE is remaining within 2%.

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Section: Introductionmentioning

confidence: 99%

State of Health Estimation for Lithium-Ion Batteries Using IAO–SVR

Xing

Liu

Luo

et al. 2023

WEVJ

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Repurposing Second-Life EV Batteries to Advance Sustainable Development: A Comprehensive Review

Akram,

Abdul-Kader

2024

Batteries

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While lithium-ion batteries (LIBs) have pushed the progression of electric vehicles (EVs) as a viable commercial option, they introduce their own set of issues regarding sustainable development. This paper investigates how using end-of-life LIBs in stationary applications can bring us closer to meeting the sustainable development goals (SDGs) highlighted by the United Nations. We focus on how this practice can support three of these goals, namely Goal 7: Affordable and Clean Energy, Goal 12: Responsible Consumption and Production, and Goal 13: Climate Action. We present a literature review that details the aging mechanisms of LIBs, namely battery degradation, state of charge, state of health, depth of discharge, remaining useful life, and battery management systems. Then, we thoroughly examine the environmental and economic benefits of using second-life EV batteries in stationary applications and how they align with the SDGs. Our review of the literature summarizes the most relevant research in battery aging, giving a foundation for further research and allowing effective legislation to be written around EVs. Additionally, our examination of the benefits of using second-life batteries motivates initiatives for sustainable practices, helping both corporations and legislators orient their ideals towards the SDGs.

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Parametric Correlation Analysis between Equivalent Electric Circuit Model and Mechanistic Model Interpretation for Battery Internal Aging

Velasco-Arellano,

Castillo-Magallanes,

Visairo-Cruz

et al. 2024

WEVJ

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In modern electric vehicle applications, understanding the evolution of the internal electrochemical reaction throughout the aging of batteries is as relevant as knowing their state of health. This article demonstrates the feasibility of correlating a mechanistic model of the battery internal electrochemical reactions with an equivalent electrical circuit (EEC) model, providing a practical and understandable interpretation of the internal reactions for electrical specialists. By way of electrochemical impedance spectroscopy analysis and automatic control theory, a methodology for correlating the resistance and capacitance variations of the EEC model and how they reflect the electrochemical reaction changes is proposed. These changes are represented through the time constants of the three RC parallel arrays from an EEC model. PS-260 lead–acid batteries were analyzed throughout the SOC and their useful life to validate this methodology. The result analysis allows us to establish that the first RC array corresponds to the negative electrode reactions in the range of 1.48 Hz to 10 kHz, the second RC array to the positive electrode reactions and generation of sulfates in the range of 0.5 to 1.48 Hz, and the third RC array to the generation of sulfates and their diffusion in the range of 0.01 to 0.5 Hz.

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State of Health Estimation Method for Lithium-Ion Batteries via Generalized Additivity Model and Transfer Component Analysis

Cited by 3 publications

References 33 publications

State of Health Estimation for Lithium-Ion Batteries Using IAO–SVR

State of Health Estimation for Lithium-Ion Batteries Using IAO–SVR

Repurposing Second-Life EV Batteries to Advance Sustainable Development: A Comprehensive Review

Parametric Correlation Analysis between Equivalent Electric Circuit Model and Mechanistic Model Interpretation for Battery Internal Aging

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