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Enhancing the efficiency of charging & parking processes for Autonomous Mobile Robot fleets

  • The allocation of tasks to Autonomous Mobile Robots in a production setting in combination with the most efficient parking and charging processes are the focus of this paper. This study presents a simulative evaluation of the theoretical allocation methods developed in Selmair and Maurer (2020) combined with either hard or dynamic availability rules to ascertain the most efficient parameters of an Autonomous Mobile Robot System. In order to quantify this efficiency, the following Key Performance Indicator (KPI) were considered: number of delayed orders, driven fleet metres and the percentage of available Autonomous Mobile Robot as determined by their state of charge. Additionally, as an alternative energy source, a fast-charging battery developed by Battery Streak Inc. was included in this study. The results show that, in comparison to a conventional and commonly used trivial strategy, our developed strategies provide superior results in terms of the relevant KPI.

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Metadaten
Author:Maximilian Selmair, Tobias Maurer, Chun-Han Lai, David Grant
DOI:https://doi.org/10.1016/j.jpowsour.2021.230894
Parent Title (English):Journal of Power Sources
Subtitle (German):A simulative evaluation
Publisher:Elsevier
Document Type:Article
Language:English
Year of first Publication:2022
Release Date:2022/04/03
Tag:AMR; Autonomous Mobile Robot; Battery charging; Battery management systems; Benchmarking; Fleet operations; Mobile robots; NAVIGATION; Secondary batteries; Vehicle Fleet Charging
Volume:521
Issue:3
Article Number:230894
Institutes:Fakultät Maschinenbau
Begutachtungsstatus:peer-reviewed
research focus:Energie und Mobilität
Licence (German):Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG