A Systematic Review on Lithium-Ion
In certain experiments on automated disassembly, dummy samples have been utilized instead of actual modules or cells to prevent hazardous situations. Kay
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In certain experiments on automated disassembly, dummy samples have been utilized instead of actual modules or cells to prevent hazardous situations. Kay
The paper presents all required tools and processes for battery diagnoses, machine learning-based object recognition, loosening and removing fasteners, opening sealings, gripping components
Lithium-ion batteries are susceptible to thermal runaway during thermal abuse, potentially resulting in safety hazards such as fire and explosion. Therefore, it is crucial to investigate the internal thermal stability and characteristics of thermal runaway in battery pouch cells. This study focuses on dismantling a power lithium-ion battery, identified as Ni-rich
In this work, we demonstrate a cyber-enabled and machine learning enhanced battery disassembly system, in which the computer vision is used to classify different types of
The automatic disassembly of electric vehicle battery has always been a key issue in the field of electric vehicle battery recycling. This paper proposes an opt
Then a close-loop control is implemented to avoid the temperature spike by adjusting the cutting variables timely. Furthermore, quality control is conducted using computer vision model to detect and mitigate cutting defects. System architecture The process flow chart of the battery disassembly system is described in Fig. 1.
A flexible gripper system is presented in detail to show how the disassembly process can be supported by automation and the control architecture and the integrated functionalities, such as voltage or resistance measurement, are
We show that AI could benefit the whole disassembly process, particularly addressing the uncertainty and safety issues. 2019), as well as disassembly system integration and control. The figure in (g1) is adapted from (Poschmann, Brüggemann AI shows strong power in modeling such complex and time-varying battery systems to predict the
battery disassembly systems that can successfully carry out intricate, precise, and dynamic disassembly tasks with strong autonomous decision-making capabilities. Aiming at this difficulty, based on the NeuralSymbolic AI –, this paper designs a battery disassembly au-tonomous mobile manipulator robot system, BEAM-1, with
The battery management system that is located in the battery pack controls, among other things, the charging and discharging process of the battery pack and is supplied with
The only hitch is to find a way to safely and cost-effectively disassemble EV battery packs. Today, the process is almost entirely manual. “Because it''s so labor-intensive,
With the explosion of waste PBs, a brilliant disassembly sequence has a good prospect of solving the low efficiency of PBs disassembly problem .The purpose of disassembly task sequence planning (DTSP) is to plan a systematic disassembly process according to certain information and rules, then remove the parts in sequence under the
One of the first steps of every battery recycling process is the disassembly, which can be a quite time and cost consuming process and hence has to be planned properly. Using
This paper addresses the development of a flexible robotic cell for the fully automated disassembly of battery modules from battery systems. The paper presents all
The process flow chart of the battery disassembly system is described in Fig. 1. The first step of the process is to classify the battery according to its brand and determine its length in order to choose the appropriate machine settings for cutting. During the cutting process, there is a safety concern when temperature spikes.
Disassembly process diagram of a battery pack by technician. The disassembly of individual modules is comprised of the following: (1) the removal of the module BMS and main harness connector, (2
Battery Disassembly Recent research in robotic battery disassembly has unveiled complexities and challenges in automating this process due to inherent uncertainties. Zhang et al. developed an autonomous system for disassembling electric vehicle batteries, achieving high success in laboratory settings and demonstrating efficiency and autonomy in controlled environments .
During the battery disassembly process, the casing and module must be separated. Standard methods include mechanical cutting, laser cutting, hydraulic shearing, and
The purpose of this paper is, therefore, to examine the challenges of the battery disassembly process in relation to the required increase in the degree of automation.
Taking the intelligent disassembly of retired power battery pack as the research object, a virtual robotic disassembly system is constructed. The system consists of a multi
(DOI: 10.3390/en15134856) Manual disassembly of the lithium-ion battery (LIB) modules of electric vehicles (EVs) for recycling is time-consuming, expensive, and dangerous for technicians or workers. Dangers associated with high voltage and thermal runaway make a robotic system suitable for the automated or semi-automated disassembly of EV batteries. In this paper, we
For instance, HRC-based disassembly activities, such as the detection of deformed and defective parts in LIBs, modelling and control of HRC during disassembly processes, HRC disassembly planning and scheduling, and robotic manipulation learning for specific LIB disassembly operations, can be optimised by using state-of-the-art intelligent
In this paper a scenario-based development of disassembly systems is presented with varying possible design aspects as well as different amounts of end of life battery systems.
Fuzzy Logic to Calculate the fuzzy and defuzzified disassembling times applying PHEV battery system: Disassembly completion time: Disassembly graph: EV battery: Xu et al. (2020) Modified Discrete Bees Algorithm based on Pareto to Minimize disassembly cost and time of PC disassembly using task classification: Generational Distance and Hyper
The disassembly of EV batteries commences at the pack level, progresses to the module level, and ends at the cell level. In most cases, EV battery disassembly remains a manual process carried out by technicians due to the low costs and high levels of manipulation and dexterity required. This manual approach presents risks including fire hazards,
These researches involve various methods of optimization including but are not limited to: improved disassembly workstations, 1,5 improved disassembly process, 7 and robotic assistance. 8,10, 16
When considering the battery disassembly process flow, the product and, above all, its design with various subcomponents play an important role for an automated
Some prototypes for robotic disassembly of EV battery systems have been developed in the past 5 years, (LQR) control system was implemented. A system identification method was also implemented
The process of manual disassembly for the pack involved the following steps: (1) removal of the pack cover, (2) disconnection and removal of the main wiring harness and
A data-driven model is built to predict the cutting temperature pattern and the temperature spike can be mitigated by the close-loop control system. Furthermore, quality control is conducted using a neural network model to detect and mitigate the cutting defects. The integrated disassembly platform can realize the real-time diagnosis and closed
Automated Disassembly of Battery Systems to Battery Modules. May 2024; Procedia CIRP 122(2024):25-30 is described using the example of an actual disassembly process. Discover the world''s
The integrated disassembly platform can realize the real-time diagnosis and closed-loop control of the cutting process to optimize the cutting quality and improve the safety.
4.3.1. Disassembly system Based on product properties, the battery system being rather small with only two variants (Audi Q5 and VW Jetta), a small number of parts that need to be disassembled (14) and with rather low complex disassembly processes, the disassembly will be carried out in a single work station.
The research in this field has primarily centered around four key disassembly challenges: evaluating the disassembly process, developing disassembly cells, devising
The second system will represent the removal process of individual EVBS components up to the battery module using robotics and a corresponding line control system. This article is structured as follows.
5. Conclusions Using the example of the Audi Q5 Hybrid battery system, a planning approach for the disassembly of electric vehicle batteries has been demonstrated. Based on a priority matrix, a disassembly sequence for the Q5 battery system has been derived.
The design of the disassembly system must consider the analysis of potentially explosive atmospheres (ATEX) 1 of the area around the battery pack and, if necessary, adopt tools enabled to work in the corresponding ATEX zone.
The disassembly of lithium-ion battery systems from automotive applications is a complex and therefore time and cost consuming process due to a wide variety of the battery designs, flexible components like cables, and potential dangers caused by high voltage and the chemicals contained in the battery cells.
However, the current lack of standardisation in design remains a significant barrier to automating battery disassembly . Additionally, the uncertain conditions of end-of-life or damaged EVBs add to the complexity of executing the disassembly process effectively.
Analysis of emerging concepts focusing on robotised Electric Vehicle Battery (EVB) disassembly. Gaps and challenges of robotised disassembly are reviewed, and future perspectives are presented. Human–robot collaboration in EVB processing is highlighted. The potential of artificial intelligence in improving disassembly automation is discussed.
As identified in various studies, a key obstacle is the significant variation in battery pack designs, which complicates the automation process . Thompson et al. highlighted that the diversity in battery pack designs, along with the use of various fixtures and adhesives, impedes automated disassembly.