Design, Modeling, and Control of Semi-Active Suspension System for Baja Car

This paper focuses on designing, modeling, and controlling a suspension system for a Baja SAE vehicle with an integrated semi-active suspension damping system. The main goals in order to optimize performance are to maximize vehicle speed through various inputs and minimize stress on critical components. Sensor technology including inertial measurement units (IMU), strain gauges, and hall effects are used to measure vehicle parameters throughout road inputs. This data is then analyzed using machine learning techniques to determine the most influential parameters in maximizing speed and minimizing stress with the fastest reaction time. Once these most influential and implementable parameters are determined to be pitch and roll, they are used to create a simplified on car optimization algorithm to improve vehicle performance, as validated by data collected on the vehicle.