Data-Driven Recovery Potential Analysis and Modeling for Batteries Recovery Operations in Electric Bicycle Industry
Joint Authors
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-18, 18 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-11-11
Country of Publication
Egypt
No. of Pages
18
Main Subjects
Abstract EN
To help the government manage waste lead-acid batteries in a more targeted and sustainable way, accurately forecasting the number of waste lead-acid batteries and analyzing their recovery potential play a key role.
In China, electric bicycles are one of the most common means of transportation.
As of the end of 2017, the social holding quantity of electric bicycles in China was over 250 million and that of electric tricycles was over 50 million.
The quantity is equal to the total number of electric bicycles manufactured between 2011 and 2017.
Currently, 90% of electric bicycles adopt lead-acid batteries as their power batteries.
However, there are a few studies on the lead-acid batteries used in electric bicycles as power batteries.
In this paper, we have selected lead-acid batteries used in electric bicycles as the subject of research as such kind of batteries enjoys the widest user base, the most single-battery consumption volume, and the strongest mobility.
Based on the output and sales of electric bicycles, we have obtained the quantity of power lead-acid batteries.
We have then estimated the annual waste quantity of lead-acid batteries used in electric bicycles in 2000-2022 using the “market supply A model” and the “Stanford Model”, respectively, and based on the proportion of raw materials contained in lead-acid batteries and the proportion between reclaimed and discarded lead-acid batteries, we have estimated the recovery potential of discarded lead-acid batteries in 2000-2022.
We estimate that the lead-acid batteries used in electric bicycles only have great recovery potential and there are abundant potential resources for recovery.
The research data and results can help decision-makers make more effective and more accurate management measures and policies.
American Psychological Association (APA)
Zhang, Ping& Liu, Guangfu. 2018. Data-Driven Recovery Potential Analysis and Modeling for Batteries Recovery Operations in Electric Bicycle Industry. Discrete Dynamics in Nature and Society،Vol. 2018, no. 2018, pp.1-18.
https://search.emarefa.net/detail/BIM-1152740
Modern Language Association (MLA)
Zhang, Ping& Liu, Guangfu. Data-Driven Recovery Potential Analysis and Modeling for Batteries Recovery Operations in Electric Bicycle Industry. Discrete Dynamics in Nature and Society No. 2018 (2018), pp.1-18.
https://search.emarefa.net/detail/BIM-1152740
American Medical Association (AMA)
Zhang, Ping& Liu, Guangfu. Data-Driven Recovery Potential Analysis and Modeling for Batteries Recovery Operations in Electric Bicycle Industry. Discrete Dynamics in Nature and Society. 2018. Vol. 2018, no. 2018, pp.1-18.
https://search.emarefa.net/detail/BIM-1152740
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1152740