A new application of the Extended Kalman Filter to the estimation of roll angles of a motorcycle with Inertial Measurement Unit

• Main Authors: Romualdi Lorenzo, Mancinelli Nicolò, de Felice Alessandro, Sorrentino Silvio
• Format: Article
• Language: English
• Published: University of Belgrade - Faculty of Mechanical Engineering, Belgrade 2020-01-01
• Series: FME Transactions
• Subjects: motorcycle kinematics; motorcycle dynamics; roll angle estimation; real time estimation; extended kalman filter
• Online Access: https://scindeks-clanci.ceon.rs/data/pdf/1451-2092/2020/1451-20922002255R.pdf

The capability of providing a real-time reliable measure of the actual roll angle is of great importance for the racing motorcycle dynamics. This study presents a method based on an Extended Kalman Filter (EKF) for the estimation of the actual roll angle of a motorcycle equipped with an Inertial Measurement Unit (IMU), with the advantage of not needing the development and implementation of a complete motorcycle model. Measured data which, depending on the additional instrumentation available on the motorcycle, do not form a complete set of input data for the estimation algorithm, induce the introduction of approximations affecting the accuracy of the results. A thorough error analysis is carried out by means of numerical simulations along with experimental validations. As a result, a novel approximate form for the kinematical model of the IMU is developed, yielding an overall good accuracy in the roll angle estimates.