Adaptive Suspension Systems in Motorcycles: AI-Assisted Control and Structural Optimization

Abstract

The evolution of motorcycle suspension design has expanded from conventional telescopic forks to advanced smart systems integrating sensors and adaptive dampers. This research proposes an adaptive suspension system that leverages artificial intelligence (AI) for real-time decision-making, structural optimization through finite element analysis (FEA), and the integration of digital twin technology for predictive maintenance. Simulation and computational analysis reveal superior load distribution, improved vibration damping, and reduced brake dive compared to traditional designs. AI-assisted adaptability enables the system to dynamically respond to diverse terrain conditions, ensuring enhanced rider comfort, stability, and safety. The findings contribute to the next generation of intelligent motorcycle dynamics.