Skip to content
DraconiticResearch
Search Sources API
190,860 studies31 sourcesUpdated 36 min ago
Peer-reviewedCC BY 4.0Batteries

A Dynamic Residual Value Assessment and Trade-In Decision Framework for Retired Power Batteries Targeting Multi-Scenario Secondary Utilization

  • Xing He1,2
  • Meng Li1,3
  • Jichao Hong1,3
  • Sijia Yang3,4
  • Jiahao Wei1,3
  • Shangren Xie1,3
  • Lei Zhang1,3
  • Haitao Zhang5
  • Shanshan Guo6,7
7 affiliations
  1. 1School of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083, China
  2. 2Defective Product Recall Technical Center, State Administration for Market Regulation, Beijing 100101, China
  3. 3Shunde Innovation School, University of Science and Technology Beijing, Foshan 528399, China
  4. 4School of Artificial Intelligence, University of Science and Technology Beijing, Beijing 100083, China
  5. 5Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Shenzhen 518110, China
  6. 6College of Mechanical and Automation, Weifang University, Weifang 261061, China
  7. 7Shandong Key Laboratory of Intelligent Manufacturing Technology for Advanced Power Equipment, Jinan 250061, China
Open at sourceDOICite

Abstract

The recycling and secondary utilization of retired power batteries have become increasingly important with the rapid growth of new energy vehicle ownership. Assessing their residual value and guiding trade-in decisions have emerged as key challenges. This study proposes a dynamic residual value assessment and trade-in decision framework for multi-scenario secondary applications. The framework integrates operational data, maintenance records, and market and policy information to characterize battery condition through feature extraction and health indicator construction. A dynamic residual value function combines state of health, remaining useful life, and market adjustment factors to account for nonlinear battery degradation and changing economic conditions. Residual value grading and application scenario matching guide the allocation of retired batteries to suitable utilization pathways. A standardized closed-loop process covering inspection, registration, evaluation, transactions, logistics, and reuse links assessment outcomes to trade-in pricing and implementation. The framework provides a structured basis for residual value assessment, allocation for secondary utilization, and trade-in decision-making for retired power batteries.

Related

  1. Dual-Ligand Engineering of a Stable and High-Utilization Iron Complex Anolyte for Alkaline All-Iron Flow Batteries
    Heng Wang, Zhiyu Wang, Tianyu Yang +3
    ChemRxivPreprintCC BYFull textGeneral chemistryChemRxiv
  2. Electrochemical Properties and Changes of Crystal and Electronic Structures of Spinel-Type Mg1.33– y V1.67– x + y Mn x O4 ( x = 0.15, 0.06 ≤ y ≤ 0.13) for Magnesium Secondary Batteries
    Yasushi Idemoto, Kohei Yamanouchi, Chiaki Ishibashi +3
    ACS OmegaPeer-reviewedCC BY 4.0Full textGeneral chemistryCrossrefEurope PMC
  3. Cross-Dataset Assessment of Electrical Loading, Thermal-Domain Evolution, and Abuse-Domain Separation in UAV-Relevant Lithium-Ion Batteries
    Yuanzhe Li, Ningning Wei, Minghai Li +1
    BatteriesPeer-reviewedCC BY 4.0Electrochemistry & energyCrossref
  4. Cross-Dataset Assessment of Cathode Thermal Descriptors for Whole-Cell Self-Heating Kinetics in Lithium-Ion Batteries: Onset, Reaction Magnitude, and Limits of Transferability
    Yuanzhe Li, Ningning Wei, Minghai Li +1
    BatteriesPeer-reviewedCC BY 4.0Electrochemistry & energyCrossref
  5. State-of-Health Diagnostics in Lithium-Ion Batteries: A Methodological Framework for Scalable Mechanical Ageing Assessments
    Maximilian Graaf, Tim Neugebauer, Niklas Kisseler +2
    BatteriesPeer-reviewedCC BY 4.0Electrochemistry & energyCrossref

Cite

BibTeXRIS
BibTeX
@article{he2026dynamic,
  title = {{A Dynamic Residual Value Assessment and Trade-In Decision Framework for Retired Power Batteries Targeting Multi-Scenario Secondary Utilization}},
  author = {Xing He and Meng Li and Jichao Hong and Sijia Yang and Jiahao Wei and Shangren Xie and Lei Zhang and Haitao Zhang and Shanshan Guo},
  journal = {Batteries},
  year = {2026},
  month = oct,
  doi = {10.3390/batteries12100409},
  url = {https://www.mdpi.com/2313-0105/12/10/409},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - A Dynamic Residual Value Assessment and Trade-In Decision Framework for Retired Power Batteries Targeting Multi-Scenario Secondary Utilization
AU  - Xing He
AU  - Meng Li
AU  - Jichao Hong
AU  - Sijia Yang
AU  - Jiahao Wei
AU  - Shangren Xie
AU  - Lei Zhang
AU  - Haitao Zhang
AU  - Shanshan Guo
PY  - 2026
DA  - 2026/10/08
JO  - Batteries
DO  - 10.3390/batteries12100409
UR  - https://www.mdpi.com/2313-0105/12/10/409
AB  - The recycling and secondary utilization of retired power batteries have become increasingly important with the rapid growth of new energy vehicle ownership. Assessing their residual value and guiding trade-in decisions have emerged as key challenges. This study proposes a dynamic residual value assessment and trade-in decision framework for multi-scenario secondary applications. The framework integrates operational data, maintenance records, and market and policy information to characterize battery condition through feature extraction and health indicator construction. A dynamic residual value function combines state of health, remaining useful life, and market adjustment factors to account for nonlinear battery degradation and changing economic conditions. Residual value grading and application scenario matching guide the allocation of retired batteries to suitable utilization pathways. A standardized closed-loop process covering inspection, registration, evaluation, transactions, logistics, and reuse links assessment outcomes to trade-in pricing and implementation. The framework provides a structured basis for residual value assessment, allocation for secondary utilization, and trade-in decision-making for retired power batteries.
SN  - 2313-0105
ER  -