Optimizing geographic locations for electric vehicle battery recycling preprocessing facilities in California

被引:6
作者
Haynes, Megan W. [1 ]
Gonzalez, Rodrigo Caceres [1 ]
Hatzell, Marta C. [1 ,2 ]
机构
[1] Georgia Inst Technol, George W Woodruff Sch Mech Engn, Atlanta, GA 30332 USA
[2] Georgia Inst Technol, Sch Chem & Biomol Engn, Atlanta, GA 30332 USA
来源
RSC SUSTAINABILITY | 2024年 / 2卷 / 02期
基金
美国国家科学基金会;
关键词
LITHIUM-ION BATTERIES;
D O I
10.1039/d3su00319a
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Spent lithium-ion batteries (LIBs) at end of life pose several safety risks. Specifically, LIBs have the potential to self-ignite during transport, release toxic compounds during incineration, and can leach contaminants into landfills. Spent LIBs, which are classified as hazardous waste, are also subject to numerous policies and require disposal by certified personnel and companies. These requirements result in an increase in transport costs and volume compared to other waste. Efforts to improve LIB recycling focus primarily on reducing costs to make recycling economically profitable. The greatest emphasis is placed on improving recycling technologies; however, transport costs significantly impact the total cost of LIB recycling. Here, we provide a procedure for choosing an unsupervised machine learning clustering heuristic to identify optimal locations for LIB recycling preprocessing facilities in California. The identified decentralized facility locations minimize the transportation distance and the cost of shipping spent electric vehicle batteries between end-use sector facilities and potential second-use locations. Optimizing the location of lithium ion battery preprocessing facilities.
引用
收藏
页码:377 / 389
页数:13
相关论文
共 37 条
[31]   The importance of design in lithium ion battery recycling - a critical review [J].
Thompson, Dana L. ;
Hartley, Jennifer M. ;
Lambert, Simon M. ;
Shiref, Muez ;
Harper, Gavin D. J. ;
Kendrick, Emma ;
Anderson, Paul ;
Ryder, Karl S. ;
Gaines, Linda ;
Abbott, Andrew P. .
GREEN CHEMISTRY, 2020, 22 (22) :7585-7603
[32]   Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges [J].
Usama, Muhammad ;
Qadir, Junaid ;
Raza, Aunn ;
Arif, Hunain ;
Yau, Kok-Lim Alvin ;
Elkhatib, Yehia ;
Hussain, Amir ;
Al-Fuqaha, Ala .
IEEE ACCESS, 2019, 7 :65579-65615
[33]   Optimising the geospatial configuration of a future lithium ion battery recycling industry in the transition to electric vehicles and a circular economy [J].
Viet Nguyen-Tien ;
Dai, Qiang ;
Harper, Gavin D. J. ;
Anderson, Paul A. ;
Elliott, Robert J. R. .
APPLIED ENERGY, 2022, 321
[34]   Optimal design of electric vehicle battery recycling network - From the perspective of electric vehicle manufacturers [J].
Wang, Lei ;
Wang, Xiang ;
Yang, Wenxian .
APPLIED ENERGY, 2020, 275 (275)
[35]   Emergency logistics network design based on space-time resource configuration [J].
Wang, Yong ;
Peng, Shouguo ;
Xu, Min .
KNOWLEDGE-BASED SYSTEMS, 2021, 223
[36]   A fuzzy-based customer clustering approach with hierarchical structure for logistics network optimization [J].
Wang, Yong ;
Ma, Xiaolei ;
Lao, Yunteng ;
Wang, Yinhai .
EXPERT SYSTEMS WITH APPLICATIONS, 2014, 41 (02) :521-534
[37]   A Review on Battery Market Trends, Second-Life Reuse, and Recycling [J].
Zhao, Yanyan ;
Pohl, Oliver ;
Bhatt, Anand I. ;
Collis, Gavin E. ;
Mahon, Peter J. ;
Ruether, Thomas ;
Hollenkamp, Anthony F. .
SUSTAINABLE CHEMISTRY, 2021, 2 (01) :167-205