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001024565 0247_ $$2doi$$a10.1016/j.etran.2023.100255
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001024565 1001_ $$0P:(DE-HGF)0$$aYang, Sijia$$b0$$eCorresponding author
001024565 245__ $$aFast screening of lithium-ion batteries for second use with pack-level testing and machine learning
001024565 260__ $$aAmsterdam [u.a.]$$bElsevier$$c2023
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001024565 520__ $$aFast and accurate screening of retired lithium-ion batteries is critical to an efficient and reliable second use with improved performance consistency, contributing to the sustainability of renewable energy sources. However, time-consuming testing, representative criteria extraction, and large module-to-module inconsistencies at the end of first life all pose great challenges for fast screening. This paper proposes a fast screening approach with pack-level testing and machine learning to evaluate and classify module-level aging, where disassembly of the battery pack and individual testing of modules are not required. Dynamic characteristic-based criteria are designed to extract the comprehensive performance of the retired modules, making the approach applicable for battery packs with module state-of-charge inconsistencies up to 30%. Adaptive affinity propagation clustering is utilized to classify the modules and further accelerate the screening progress. The proposed approach is implemented and validated by conducting pack-level and module-level experiments with a retired battery pack consisting of 95 modules connected in series. The screening time is reduced by at least 50% compared with approaches that require module-level testing. Reasonable static performance consistency and better dynamic performance consistency, as well as higher screening stability, are achieved, with average overall performance improvements of 18.94%, 4.83% and 34.41% compared with the three benchmarks, respectively. Its adaptability to a larger current rate shows promise for large-scale applications in second-use screening.
001024565 536__ $$0G:(DE-HGF)POF4-1223$$a1223 - Batteries in Application (POF4-122)$$cPOF4-122$$fPOF IV$$x0
001024565 536__ $$0G:(BMBF)03XP0334$$aBMBF 03XP0334 - Model2Life- Modellbasierte Systemauslegung für 2nd-Life-Nutzungsszenarien von mobilen Batteriesystemen (03XP0334)$$c03XP0334$$x1
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001024565 7001_ $$0P:(DE-HGF)0$$aZhang, Caiping$$b1$$eCorresponding author
001024565 7001_ $$0P:(DE-HGF)0$$aJiang, Jiuchun$$b2
001024565 7001_ $$0P:(DE-HGF)0$$aZhang, Weige$$b3
001024565 7001_ $$0P:(DE-HGF)0$$aChen, Haoze$$b4
001024565 7001_ $$0P:(DE-HGF)0$$aJiang, Yan$$b5
001024565 7001_ $$0P:(DE-Juel1)172625$$aSauer, Dirk Uwe$$b6
001024565 7001_ $$00000-0002-2916-3968$$aLi, Weihan$$b7$$eCorresponding author
001024565 773__ $$0PERI:(DE-600)2981331-1$$a10.1016/j.etran.2023.100255$$gVol. 17, p. 100255 -$$p100255 -$$teTransportation$$v17$$x2590-1168$$y2023
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