Enhancing Parametric Analysis Of Transmitted Loads In Mechanical System Using An Intelligent Based Super Capacitor (KEY IJP************398)

• Udeh Ubasinachi Osmond, Attah Godwin O, Chukwuagu M. Ifeanyi

Abstract

The accurate parametric analysis of transmitted loads in mechanical systems is crucial for optimizing performance, ensuring structural integrity, and improving energy efficiency. Traditional methods for evaluating transmitted loads often rely on passive components, such as conventional capacitors, which lack the adaptability required for real-time load variations. This study explores the integration of an intelligent-based supercapacitor system to enhance parametric load analysis in mechanical systems. The proposed approach leverages the high power density and rapid charge-discharge capabilities of supercapacitors, combined with intelligent control mechanisms such as fuzzy logic and artificial intelligence (AI). This integration allows for real-time monitoring, adaptive load balancing, and optimized energy distribution, leading to improved system stability and reduced mechanical wear. The study evaluates the effectiveness of the intelligent-based supercapacitor through simulation and experimental analysis, comparing its performance with conventional energy storage and load management techniques. Results demonstrate that the intelligent-based supercapacitor significantly enhances the accuracy of parametric analysis, reduces transient load fluctuations, and improves overall mechanical system resilience. The findings suggest that this technology is highly beneficial for applications in industries such as aerospace, automotive, and manufacturing, where precise load management is essential. Future research should focus on refining intelligent control algorithms and exploring advanced materials to further enhance the efficiency of supercapacitor-based systems in mechanical load analysis.