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Data-Driven State o...
Data-Driven State of Health Estimation Method of Lithium-ion Batteries for Partial Charging Curves
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Tang, Jinrui (författare)
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- Li, Yang, 1984 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Wang, Shaojin (författare)
- Wuhan University of Technology
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Xiong, Binyu (författare)
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Li, Xiangjun (författare)
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Pan, Jinxuan (författare)
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- Chen, Qihong (författare)
- Wuhan University of Technology
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Wang, Peng (författare)
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(creator_code:org_t)
- 2024
- 2024
- Engelska.
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Ingår i: IEEE Transactions on Energy Conversion. - 1558-0059 .- 0885-8969. ; In Press
- Relaterad länk:
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https://doi.org/10.1...
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https://research.cha...
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Abstract
Ämnesord
Stäng
- State of health (SOH) is one of the most important performance indicators of lithium-ion batteries (LIBs). Accurate estimation of SOH is a prerequisite for the safe and reliable operation of LIBs. Traditional SOH estimation methods predominantly rely on complete charging cycle data acquired through laboratory testing. However, in practical application, the charging behaviors of electric vehicle users are random and unpredictable, making the partial charging curves difficult to utilize the traditional methods. This work introduces a novel data-driven approach to estimating a battery's SOH for partial charging cases. Firstly, a curve fitting method is proposed to extract health indicators (HIs) from partial charging voltage data, where novel HIs based on the energy-voltage curve are extracted. A composite Gaussian process regression-based data-driven method is proposed to achieve highly accurate SOH estimation. The method's adaptability to real-world partial charging habits is evaluated through three representative scenarios derived from extensive charging behavior reports of EV users. The impact of partial charging on HI extraction is analyzed based on the three identified scenarios. The proposed method is verified using a combination of our laboratory testing data and the Oxford open dataset. The results show that the proposed framework demonstrates the ability to estimate SOH accurately and strong robustness to various partial charging behaviors.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Maskinteknik -- Energiteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Mechanical Engineering -- Energy Engineering (hsv//eng)
- NATURVETENSKAP -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Probability Theory and Statistics (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Annan elektroteknik och elektronik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Other Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)
Nyckelord
- partial charging
- Fading channels
- Aging
- Lithium-ion battery
- Batteries
- Estimation
- Testing
- Discharges (electric)
- Integrated circuit modeling
- state of health estimation
- health indicator
- data-driven method
Publikations- och innehållstyp
- art (ämneskategori)
- ref (ämneskategori)
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