Big-Data-Based Power Battery Recycling for New Energy Vehicles: Information Sharing Platform and Intelligent Transportation Optimization

• Main Authors: Haijun Yu, Hongliang Dai, Guangdong Tian, Yinghao Xie, Benben Wu, Ying Zhu, Hongliang Li, Han Wu
• Format: Article
• Language: English
• Published: IEEE 2020-01-01
• Series: IEEE Access
• Subjects: Big data; traceability; traction battery; path optimization; new energy vehicle
• Online Access: https://ieeexplore.ieee.org/document/9104991/

This paper focuses on the principal problems in the actual transaction of decommissioned power batteries such as the asymmetry of information, huge risk and difficult is sues such as recovery and trace. And constructed a new energy vehicle decommissioned power battery recycling platform based on the big data technology. Integrated characteristics of big data information, this paper analyzes the operating mechanism of the Big-Data-Based power battery recovery platform. The functional module on this platform is designed and investigated for the functional requirements of users and shared in formation based on big data. Based on the analysis of traffic big data, a traction battery dangerous goods transportation optimization system is established by using Baidu map application program interface (API). The improved ant algorithm was used to obtain the shortest path model and decrease the transportation costs and risks, besides, it boosts the value of information resources maximum and gives impetus to the power battery recycling industrial transformation and upgrading.