Retired Power Battery Cascading Utilization: Scenario Adaptation and Optimal Configuration
Abstract
performance inconsistencies among retired batteries and the complexity of application scenarios lead to low sorting efficiency and severe
resource misallocation. This study proposes an optimized utilization method tailored to multi-scenario requirements. A multi-dimensional
performance evaluation system and a dynamic classification model are developed to precisely match retired batteries with differentiated ap
plication scenarios, including energy storage, power, and consumer electronics. Validation using multi-source datasets and physical samples
demonstrates that the proposed method achieves a classification accuracy exceeding 92%, improves the consistency of reorganized battery
packs by 35%, and increases full lifecycle economic benefits by 18%24%. This research provides a feasible technical pathway for the large
scale cascading utilization of retired power batteries.
Keywords
Full Text:
PDFReferences
[1] Yu Q, Liu C, Li R, et al. Research on a hybrid model for flood probability prediction based on time convolutional network and particle
swarm optimization algorithm[J]. Scientific Reports[2026-03-07]. DOI:10.1038/s41598-024-80100-2 .
[2] Chen C L P, Wen G X, Liu Y J, et al. Observer-Based Adaptive Backstepping Consensus Tracking Control for High-Order Non
linear Semi-Strict-Feedback Multiagent Systems[J]. IEEE Transactions on Cybernetics, 2017, 46(7):1591-1601 . DOI:10.1109/
TCYB.2015.2452217.
[3] Chandra R, Simmons J. Bayesian Neural Networks via MCMC: A Python-Based Tutorial[J]. IEEE Access, 2024, 12(000):31 .
DOI:10 .1109/ACCESS.2024.3401234.
[4] Nylund K L, Asparouhov T, Muthn, Bengt O. Deciding on the Number of Classes in Latent Class Analysis and Growth Mixture
Modeling: A Monte Carlo Simulation Study[J]. Structural Equation Modeling A Multidisciplinary Journal, 2007, 14(4):535-569 .
DOI:10 .1080/10705510701575396 .
[5] Carrion M,Arroyo J M.A computationally efficient mixed-integer linear formulation for the thermal unit commitment problem[J]. IEEE
Transactions on Power Systems, 2006, 21(3):1371-1378 . DOI:10.1109/TPWRS.2006.876672 .
[6] Lluc, Canals, Casals, et al. Second life batteries lifespan: Rest of useful life and environmental analysis[J]. Journal of Environmental
Management, 2018. DOI:10.1016/j.jenvman.2018.11.046 .
[7] Li Zhen, Dong Huichao. Feasibility Study on the Secondary Utilization of Retired Lithium-ion Power Batteries [J]. Power Supply Tech
nology, 2016, 40(8):3. DOI:10.3969/j.issn.1002-087X.2016.08.012
[8] Zhang K, Wu C, Ye J, et al. A Pre-Test and Decoupled ChargeDischarge Two-Tier Protocol for Rapid Assessing Aqueous Battery
Designs[J].ACS APPLIED ENERGY MATERIALS, 2025, 8(13):9815-9819 . DOI:10.1021/acsaem.5c01315 .
[9] Tian J, Zhou Y, Zhang X, et al. Echelon Utilization of Retired Batteries: Solutions, Challenges, and Prospects[J]. IEEE Journal of
Emerging and Selected Topics in Industrial Electronics, PP[2026-03-07]. DOI:10.1109/JESTIE.2025.3650048 .
[10] Yu H,Wang S. Blockchain-Enabled Closed-Loop Supply Chain Optimization for Power Battery Recycling and Cascading Utilization[J].
Sustainability (2071-1050), 2025, 17(9). DOI:10.3390/su17094192 .
[11] Xu Y. Capacity Estimation and Cascade Utilization Method of Retired Lithium Ion Batteries[J]. Journal of Nanoelectronics and Opto
electronics, 2017, 12(8):803-807 . DOI:info:doi/10.1166/jno.2017.2166 .
DOI: http://dx.doi.org/10.70711/itr.v3i3.9236
Refbacks
- There are currently no refbacks.
