Experimental Identification of a Car Dynamic Model Using the Numerical Algorithms for Subspace State-Space System Identification

In this paper, a system identification numerical procedure is used to perform an experimental work based on the System Identification Toolbox available in MATLAB. This work aims to show the possibility of identifying a mathematical model of a car using low-cost sensors. The instrumentation used to reach this goal is composed of an Arduino Mega2560, a GPS receiver module, and an inertial measurement unit. The Arduino is used to handle the sensors and to save the measured data. The inertial platform is used to get the linear acceleration and angular rates of the system, while the GPS is used to get the trajectory of the car. By employing the N4SID algorithm, a discrete state-space model of the system can be identified and used to predict the behavior of the car system. It is also possible to obtain a continuous model from the discrete one and to identify the natural frequencies and the system damping factors. The results show the possibility to easily identify a mathematical model of a complex system using a limited set of experimental data.