Aging estimation of lithium ion cells under real-world conditions through mechanical stress measurements

Estevez, Manuel Antonio Perez; Conte, Fiorentino Valerio; Tremonti, Claudia; Renzi, Massimiliano

doi:10.1016/j.est.2023.107186

Cited by 4 publications

(1 citation statement)

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“…This enabled a more accurate estimation of the state of charge (SOC) and state of health (SOH) . Therefore, monitoring and evaluating stress levels enabled the prediction of cell SOH and facilitated fault diagnosis, extending cell usage and reducing potential safety risks. , Effective control of the stress distribution minimizes the stress concentration inside the cell, preventing material fracture and failure as a result of excessive stress.…”

Section: Introductionmentioning

confidence: 99%

Stress State Characterization of Li-Ion Batteries Based on a Membrane Sensor

Li,

Zhang,

et al. 2023

Energy Fuels

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Uneven force distribution in the cell may cause material deformation and stress concentration, affecting the performance and life of the cell. The uneven force distribution phenomenon present in the cell is artificially constructed and exacerbated by applying a cross tape to the surface of a Li-ion pouch cell. The flexibility of the membrane sensor allows it to conform better to cells and enables an accurate measurement of the stress distribution. In the early charging stage, the active material in the tape region undergoes preferential Li + insertion, resulting in a rapid increase in stress. In the latter charging stage, the lithiation phenomenon becomes more pronounced in the vicinity of the tape. By disassembling and inspecting the aged electrodes, we observe that the tape-overlapped region experiences the highest and evenly distributed force, resulting in partial electrode structure alteration and crack formation. However, the regions at the outer edge of the tape experience a significant stress gradient, leading to noticeable differences in particle appearance and the formation of Li dendrites. Hence, uneven stress distribution results in uneven utilization of the capacity. This work exemplifies the importance of membrane sensors in cell stress monitoring and explores the effect of inhomogeneous forces on Li + insertion and electrode changes in cells.

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Section: Introductionmentioning

confidence: 99%

Stress State Characterization of Li-Ion Batteries Based on a Membrane Sensor

Li,

Zhang,

et al. 2023

Energy Fuels

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Accurate Model Parameter Identification to Boost Precise Aging Prediction of Lithium‐Ion Batteries: A Review

Ding,

Li,

Dai

et al. 2023

Advanced Energy Materials

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Precise prediction of lithium‐ion cell level aging under various operating conditions is an imperative but challenging part of ensuring the quality performance of emerging applications such as electric vehicles and stationary energy storage systems. Accurate and real‐time battery‐aging prediction models, which require an exact understanding of the degradation mechanisms of battery components and materials, could in turn provide new insights for materials and battery basic research. Furthermore, the primary barrier to meaningful artificial intelligence/machine learning for accelerating the prediction period is the exploitation of accurate aging mechanistic descriptors. This review comprehensively summarizes the evolution of deterioration mechanisms at the material and cell level in different environments and usage scenarios, including the intricate relationships between aging mechanisms, degradation modes, and external influences, which are the cornerstones of modeling simulation and machine learning techniques. Recent advances in electrochemical models coupled with internal battery degradation mechanisms as well as identification and tracking of aging parameters are shown, with particular emphasis on electrode balance and the anticipated trend of machine learning‐assisted reliable remaining useful life prediction. Precise simulation prediction of cell level aging will continue to play an essential role in advanced smart battery research and management, enhancing its performance while shortening experimental sequences.

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