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

• Main Authors: Syed Munimus, Salam, Rashid, Muhammad Mahbubur, Ali, Mohammad Yeakub, Yvette, Susiapan
• Format: Proceeding Paper
• Language: English; English
• Published: AIP publishing 2024
• Subjects: TN331 Mine transportation, haulage and hoisting. Mining machinery
• 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
• Institution: Universiti Islam Antarabangsa Malaysia

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.