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ORIGINAL RESEARCH article

Front. Robot. AI
Sec. Field Robotics
Volume 11 - 2024 | doi: 10.3389/frobt.2024.1493869
This article is part of the Research Topic Robotic Applications for a Sustainable Future View all 5 articles

Advanced Robotics for Automated EV Battery Testing Using Electrochemical Impedance Spectroscopy

Provisionally accepted
  • 1 University of Birmingham, Birmingham, United Kingdom
  • 2 Newcastle University, Newcastle upon Tyne, North East England, United Kingdom
  • 3 National Research Council (CNR), Roma, Lazio, Italy

The final, formatted version of the article will be published soon.

    This study enhances battery diagnostics by developing a robotic framework for evaluating the state of health (SoH) of lithium-ion batteries (LIBs) from electric vehicles (EVs) using Electrochemical Impedance Spectroscopy (EIS) in an industrial environment. The framework automates the EIS testing process using an industrial robotic setup that includes a KUKA KR20 robot arm mounted on a 5-meter rail track, equipped with a force/torque sensor and a custom-designed End-of-Arm Potentiostat (EOAT) for EIS testing. The system is integrated with a digital twin, enabling operators to visualize the robot's pre-planned actions before real-world execution. The operation mode is shared-control, with some predefined points and operator control when approaching the battery terminal. An admittance controller was designed for precise movement, generating a peak force of 15.1 N and an average force of 5 N, to ensure stable connections between the EOAT and battery terminals. The EOAT's durability was verified through finite element analysis to confirm its testing efficiency. EIS results confirm the framework's capability to identify varying levels of battery degradation, with internal resistance measurements of up to 1.5 milliohms in the most degraded cells, indicating significant capacity loss.

    Keywords: Electrochemical impedance spectroscopy, EV battery, battery testing, Reuse and recycling, Robotic disassembly

    Received: 09 Sep 2024; Accepted: 08 Nov 2024.

    Copyright: © 2024 Rastegarpanah, Contreras, Ahmeid, Asif, Villagrossi and Stolkin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Alireza Rastegarpanah, University of Birmingham, Birmingham, United Kingdom

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.