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Analysis of Performance Degradation in Lithium-Ion Batteries Based on a Lumped Particle Diffusion Model
The analysis of performance degradation in lithium-ion batteries plays a crucial role in achieving accurate and efficient fault diagnosis as well as safety management. This paper proposes a method for studying the degradation pattern of lithium-ion batteries and establishing the structure–activity r...
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Published in: | ACS omega 2023-09, Vol.8 (36), p.32884-32891 |
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Main Authors: | , , , , , |
Format: | Article |
Language: | English |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | The analysis of performance degradation in lithium-ion batteries plays a crucial role in achieving accurate and efficient fault diagnosis as well as safety management. This paper proposes a method for studying the degradation pattern of lithium-ion batteries and establishing the structure–activity relationship between internal and external parameters by employing a lumped particle diffusion model. To simulate real-world operating conditions, a cycle life test was conducted with the constant current–constant voltage (CC–CV) charge mode and the discharge mode under New European Driving Cycle (NEDC) working condition. The test aimed to analyze the variations in the external macroscopic characteristic parameters of the battery. Building upon this analysis, a lumped particle diffusion model was constructed, and the model parameters were identified using the Levenberg–Marquardt (L–M) algorithm. Subsequently, the ohmic, activation, and concentration losses of the battery under different aging conditions were determined, revealing the internal state evolution during the degradation process of lithium-ion batteries. The findings indicate that the lumped particle diffusion model provides a comprehensive explanation of the internal mechanisms contributing to the performance degradation of lithium-ion batteries. Moreover, the proposed method offers a novel perspective for the real-time quantitative analysis of lithium-ion battery performance degradation. |
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ISSN: | 2470-1343 2470-1343 |
DOI: | 10.1021/acsomega.3c04222 |