The adoption of internet of things in a circular supply chain framework for the recovery of WEEE: the case of lithium-ion electric vehicle battery packs

2020 ◽  
Vol 103 ◽  
pp. 32-44 ◽  
Author(s):  
Celia Garrido-Hidalgo ◽  
F. Javier Ramirez ◽  
Teresa Olivares ◽  
Luis Roda-Sanchez
2019 ◽  
Author(s):  
Ian Kay ◽  
Roja Esmaeeli ◽  
Seyed Reza Hashemi ◽  
Ajay Mahajan ◽  
Siamak Farhad

Abstract This paper presents the application of robotics for the disassembly of electric vehicle lithium-ion battery (LIB) packs for the purpose of recycling. Electric vehicle battery systems can be expensive and dangerous to disassemble, therefore making it cost inefficient to recycle them currently. Dangers associated with high voltage and thermal runaway make a robotic system suitable for this task, as the danger to technicians or workers is significantly reduced, and the cost to operate a robotic system would be potentially less expensive over the robots lifetime. The proposed method allows for the automated or semi-automated disassembly of electric vehicle LIB packs for the purpose of recycling. In order to understand the process, technicians were studied during the disassembly process, and the modes and operations were recorded. Various modes of interacting with the battery module were chosen and broken down into gripping and cutting operations. Operations involving cutting and gripping were chosen for experimentation, and custom end of arm tooling was designed for use in the disassembly process. Path planning was performed offline in both MATLAB/Simulink and ROBOGUIDE, and the simulation results were used to program the robot for experimental validation.


2020 ◽  
Vol 447 ◽  
pp. 227370 ◽  
Author(s):  
Jonas Henschel ◽  
Fabian Horsthemke ◽  
Yannick Philipp Stenzel ◽  
Marco Evertz ◽  
Sabrina Girod ◽  
...  

2011 ◽  
Vol 201-203 ◽  
pp. 2427-2430
Author(s):  
Yuan Liao ◽  
Ju Hua Huang ◽  
Qun Zeng

According to the features of lithium ion battery packs, a distributed battery management system (BMS) for battery electric vehicle (BEV) is designed in this article. The BMS consists of a master module with several sampling modules. The kernel of master module is TMS320C2812 digital signal processor, and the kernel of sampling module is P87C591 singlechip. The main functions of master module include estimation of state of charge (SOC) and security management of lithium ion battery packs, and the main functions of sampling module include battery information collection and CAN bus based communication. SOC estimation method based on Extended Kalman filtering (EKF) theory is adopted in this article to precisely estimate the SOC of lithium ion battery packs.


Sign in / Sign up

Export Citation Format

Share Document