Exploring the potential of artificial intelligence based flywheels as energy-saving devices in industrial settings

A flywheel with a changeable moment of inertia is known as variable Inertia flywheel (VIF) can be proposed to overcome complexity on moment of inertia that causes difficulty during rotating machine start-up. While there is an extensive amount of literature on VIF control strategies, very little ad...

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Bibliographic Details
Main Authors: Syed Munimus, Salam, Rashid, Muhammad Mahbubur, Ali, Mohammad Yeakub, Yvette, Susiapan
Format: Proceeding Paper
Language:English
English
Published: AIP publishing 2024
Subjects:
Online Access:http://irep.iium.edu.my/115368/7/115368_Exploring%20the%20potential.pdf
http://irep.iium.edu.my/115368/8/115368_Exploring%20the%20potential_Scopus.pdf
http://irep.iium.edu.my/115368/
https://pubs.aip.org/aip/acp/article-abstract/3161/1/020125/3310614/Exploring-the-potential-of-artificial-intelligence?redirectedFrom=fulltext
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Institution: Universiti Islam Antarabangsa Malaysia
Language: English
English
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Summary:A flywheel with a changeable moment of inertia is known as variable Inertia flywheel (VIF) can be proposed to overcome complexity on moment of inertia that causes difficulty during rotating machine start-up. While there is an extensive amount of literature on VIF control strategies, very little addresses practical considerations. Depending on the parameters of the application system, a VIF system may be designed and built using a relatively simple control approach. To determine how a semi-active VIF control system and the input parameters of a rotating electrical machine relate to one another in minimizing energy losses, this study collects data from a VIF linked motor system. The last step in developing an intelligent semi active control for the rotating machine linked with VIF is to utilize a machine learning method to predict the parameters of the control application system.