Optimal recovery model in a used batteries closed-loop supply chain considering uncertain residual capacity. (December 2021)
- Record Type:
- Journal Article
- Title:
- Optimal recovery model in a used batteries closed-loop supply chain considering uncertain residual capacity. (December 2021)
- Main Title:
- Optimal recovery model in a used batteries closed-loop supply chain considering uncertain residual capacity
- Authors:
- Liu, Chang-Yi
Wang, Hui
Tang, Juan
Chang, Ching-Ter
Liu, Zhi - Abstract:
- Graphical abstract: Highlights: We examine the impact of uncertain residual capacity of used batteries on the CLSC. We investigate the collection and remanufacturing strategies of used batteries. The two base recovery models of used batteries are formulated. We extend the models to a manufacturer-dominated CLSC and a competitive CLSC. Abstract: The collection and echelon utilization of used batteries (UBs) retired from energy vehicles (EVs) has received great attention in theory and practice. However, there has been no clear formulation of the optimal recovery model or assessment of how the uncertain residual capacity of UBs affects collection and remanufacturing strategies. This study characterizes the uncertain residual capacity based on the battery capacity level required for remanufacturing, and first formulates two base models of supplier recovery and manufacturer recovery in a supplier-dominated closed-loop supply chain (CLSC). Our results show that the impact of uncertain residual capacity on the operational decisions and economic performance of the CLSC is related to the recovery model, remanufacturing strategy, maximal unit remanufacturing cost of UBs, and the substitution degree of low-speed EVs for regular EVs. Compared with the supplier-recovery model, the manufacturer-recovery model brings a higher profit to the EV manufacturer and CLSC when no or partial UBs are remanufactured, but a lower profit for the battery supplier, and places a greater burden on theGraphical abstract: Highlights: We examine the impact of uncertain residual capacity of used batteries on the CLSC. We investigate the collection and remanufacturing strategies of used batteries. The two base recovery models of used batteries are formulated. We extend the models to a manufacturer-dominated CLSC and a competitive CLSC. Abstract: The collection and echelon utilization of used batteries (UBs) retired from energy vehicles (EVs) has received great attention in theory and practice. However, there has been no clear formulation of the optimal recovery model or assessment of how the uncertain residual capacity of UBs affects collection and remanufacturing strategies. This study characterizes the uncertain residual capacity based on the battery capacity level required for remanufacturing, and first formulates two base models of supplier recovery and manufacturer recovery in a supplier-dominated closed-loop supply chain (CLSC). Our results show that the impact of uncertain residual capacity on the operational decisions and economic performance of the CLSC is related to the recovery model, remanufacturing strategy, maximal unit remanufacturing cost of UBs, and the substitution degree of low-speed EVs for regular EVs. Compared with the supplier-recovery model, the manufacturer-recovery model brings a higher profit to the EV manufacturer and CLSC when no or partial UBs are remanufactured, but a lower profit for the battery supplier, and places a greater burden on the environment. Furthermore, we extend the base models to the manufacturer-dominated CLSC and a CLSC with two competing suppliers to investigate the rationality of the above results. … (more)
- Is Part Of:
- Transportation research. Volume 156(2021)
- Journal:
- Transportation research
- Issue:
- Volume 156(2021)
- Issue Display:
- Volume 156, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 156
- Issue:
- 2021
- Issue Sort Value:
- 2021-0156-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-12
- Subjects:
- Closed-loop supply chain -- EVs battery collection -- Recovery model -- Remanufacturing strategy
Logistics -- Periodicals
Transportation -- Periodicals
388.011 - Journal URLs:
- http://www.sciencedirect.com/science/journal/13665545 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.tre.2021.102516 ↗
- Languages:
- English
- ISSNs:
- 1366-5545
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9026.274640
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British Library HMNTS - ELD Digital store - Ingest File:
- 20075.xml