Work

Optimizing Automated Battery Demanufacturing Through Simulation-Based Analysis and Genetic Algorithm

Year: 2025

Type: article

Abstract: The automation of recycling processes for electric vehicle lithium-ion battery packs is crucial for the advancement of green energy transportation. Testing disassembly strategies on real equipment is time consuming, expensive, and poses significant safety risks. This paper presents a novel simulation-based framework that leverages the integration of a high-fidelity virtual environment with a Robot Operating System (ROS) to visualize and accurately calculate the time required for complex robotic disassembly operations. The calculated operation times are then used as input for genetic algorithm optimization to improve process efficiency. The results demonstrate that automation significantly improves the total speed of the disassembly process compared to manual methods. By utilizing this novel simulation and optimization approach, a 25% improvement in performance was achieved for the pack-to-module disassembly stage. This method provides a safe and cost-effective approach for process design, contributing directly to the development of a circular economy and supporting the transition towards sustainable transportation.

Source: Robotics

DOI: 10.3390/robotics14110156

Authors: Muhammad Talha Bilal, Doris Siyu Tian, Martin Choux, Lei Jiao, Ilya Tyapin

Institution: University of Agder

Language: English

Topic: Extraction and Separation Processes

Subfield: Mechanical Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Responsible consumption and production, Affordable and clean energy

Open Access status: gold

Estimated APC paid: $2,172