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Evaluation of the State of the health of Li-ion batteries in the context of Circular Economy

Akash Basia 1, 2 
1 G-SCOP_GCSP - Gestion et Conduite des Systèmes de Production
G-SCOP - Laboratoire des sciences pour la conception, l'optimisation et la production
2 G-SCOP_CPP - Conception Produit Process
G-SCOP - Laboratoire des sciences pour la conception, l'optimisation et la production
Abstract : Electric Vehicles (EV) have been one of the most encouraging ways to tackle the adverseenvironmental effect of hydrocarbon-based transport. Most of the EV use Li-ion batteries as theirpower source, owing to their high energy density. These batteries reach its End of Life (EoL)when the capacity degrades by just twenty percent of the original capacity. A reliable circularindustrial system can be developed which should be able to transform post-used EV batteries intonew added-value batteries for less demanding applications, thus prolonging their life and ensuringmore sustainability. Predicting the reliability of a system in its actual life cycle conditions andestimating it’s time to failure(State of the health estimation) is helpful in decision making forthe new value chain. But the technological heterogeneity of the Li-ion batteries, as well as thedynamics of change of operating conditions, accentuates the difficulty to establish PrognosticsHealth Management (PHM) system for the batteries. Also, very few researches talk about State ofhealth with the perspective of re-purposing batteries.The objective of this thesis is to bridge the knowledge gap of diagnostics and prognostics inthe context of circular economy. The results identify a contextual definition of SoH and a novelclassifications for different SoH estimation methods. The thesis also investigates the issues andchallenges posed while estimating SoH for Li-ion battery, with possible solutions. Furthermore, inthis thesis, the ultimate goal is to provide reliable sensor networks as well as information retrievalmodules to develop as accurate as possible a diagnosis and a health prognosis method for lithiumionbatteries in the context of the Circular economy.We proposed an Incremental Capacity (IC) curve based SoH estimation system for Li-ion batteries.The model employs a Kalman filter and a finite differencing method for measurement noiseattenuation. A novel method that combines Support vector regression (SVR) and the AutoregressiveIntegrated Moving Average (ARIMA) model is utilized to model the relationship between ICand the SoH. A use case is created on the NASA AMES open-source battery data. The case studyshows that the proposed model can obtain accurate SoH prediction results without needing theState of Charge information of the battery. Finally, a framework has been proposed for establishinga repurposing based business landscape by exploring the current repurposing trends across theworld.
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Submitted on : Thursday, February 17, 2022 - 9:04:10 AM
Last modification on : Friday, March 25, 2022 - 9:40:32 AM
Long-term archiving on: : Wednesday, May 18, 2022 - 6:24:01 PM


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Akash Basia. Evaluation of the State of the health of Li-ion batteries in the context of Circular Economy. Automatic. Université Grenoble Alpes [2020-..], 2021. English. ⟨NNT : 2021GRALT075⟩. ⟨tel-03578114⟩



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