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A Smart Tool for Optimal Energy use of AGVs in the Manufacturing Industry
University West, Department of Engineering Science.
University West, Department of Engineering Science, Division of industrial automation. (KAMPT)ORCID iD: 0000-0002-4091-7732
Volvo group, Goteborg (SWE).
University West, Department of Engineering Science, Division of industrial automation. (KAMPT)
2024 (English)In: IEEE Conference on Emerging Technologies and Factory Automation, ISSN 1946-0740, E-ISSN 1946-0759, p. 1-8Article in journal (Refereed) Published
Abstract [en]

The motivation behind this article stems from potential gains to be made by optimizing the movement profile of Automated Guided Vehicles (AGVs) in an industrial setting. By minimizing the energy consumption of an AGV, increased range, larger recharging intervals, and possibly financial benefits can be achieved. Previous research has shown that high acceleration rates can have a negative impact on the average energy consumption of an AGV, while others suggest that using higher speed may lead to energy savings. In this article a test case is built using the Simplex Motion SH 100B BLDC motor on an AGV in the production line. Using two such identical motors, a test rig is built where one motor acts as the driving motor and the other as the brake. Using an Arduino micro controller and a current sensor, power measurements are taken for the development of a power model for this motor. A simulation model presented for the movement and power consumption of an AGV equipped with two such motors, determine the optimal values for the acceleration rate, cruising speed, and deceleration rate, and estimate the potential energy savings.  

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2024. p. 1-8
Keywords [en]
A gv; Acceleration rates; Automated guided vehicles; Energy savings; Energy use; Energy-consumption; Energy-savings; Optimal energy; Optimisations; Power modeling; Smart manufacturing
National Category
Robotics and automation
Research subject
Production Technology
Identifiers
URN: urn:nbn:se:hv:diva-22711DOI: 10.1109/ETFA61755.2024.10710774Scopus ID: 2-s2.0-85207852328OAI: oai:DiVA.org:hv-22711DiVA, id: diva2:1918909
Conference
IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA), Padova, Italy, 2024
Available from: 2024-12-06 Created: 2024-12-06 Last updated: 2025-02-09Bibliographically approved

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Ramasamy, SudhaZhang, Xiaoxiao

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