Abstract
Large-scale adoption of electric vehicles can reap significant energy and environmental benefits while also reducing reliance on fossil fuels. Nonetheless, accompanying the benefits of electric vehicles, several economic and ecological challenges arise from the production of Lithium-ion batteries, which are currently the most popular type of batteries used in electric vehicles. Remanufacturing is a promising end-of-life strategy and can lead to more sustainable Lithium-ion battery supply chains to support large-scale adoption of electric vehicles. Several factors will dictate the feasibility and effectiveness of remanufacturing, including economic viability, production capability, and battery demand and supply. Unfortunately, while there exists significant research efforts on remanufacturing at the laboratory scale, there lacks research that investigates Lithium-ion battery remanufacturing at the enterprise scale. Motivated by this, in this paper, a state-of-the-art closed loop supply chain network model for Lithium-ion battery remanufacturing considering different quality levels of spent battery returns is proposed. An optimization model is developed to maximize the network profit and a sensitivity analysis is performed to determine the impact of several important model parameters on the profitability of the proposed supply chain network. A numerical case study is implemented which shows that 9.81–30.93% increase in profit can be achieved if remanufacturing is integrated in Lithium-ion battery supply chain networks. Moreover, the sensitivity analysis shows that careful implementation of the proposed algorithm coupled with understanding of battery parameters are the keys to implementing cost-effective electric vehicle Lithium-ion battery supply chains. In all, this research will help stimulate the implementation of remanufacturing, promote economically and environmentally sustainable supply chain management in the electric vehicle battery industry, and support the transportation sector in reducing environmental burdens.
Original language | English (US) |
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Pages (from-to) | 277-286 |
Number of pages | 10 |
Journal | Applied Energy |
Volume | 226 |
DOIs | |
State | Published - Sep 15 2018 |
All Science Journal Classification (ASJC) codes
- Mechanical Engineering
- General Energy
- Management, Monitoring, Policy and Law
- Building and Construction
- Renewable Energy, Sustainability and the Environment