Roll angle estimator based on angular rate measurements for bicycles. Issue 11 (2nd November 2019)

• Record Type: Journal Article
• Authors: Sanjurjo, Emilio; Naya, Miguel A.; Cuadrado, Javier; Schwab, Arend L.
• Is Part Of: Vehicle system dynamics. Volume 57:Issue 11(2019)
• Page Start: 1705
• Page End: 1719
• Publication Date: 2019-11-02
• Subjects: Roll angle estimator -- bicycle -- single-track vehicle -- Kalman filter -- inertial sensors; Motor vehicles -- Dynamics -- Periodicals; Electronic journals; 629.231
• DOI: 10.1080/00423114.2018.1551554
• Languages: English
• ISSNs: 0042-3114

Abstract

ABSTRACT: Measuring the roll angle of single-track vehicles has always been a challenging task; however, accurate and reliable measurements of this magnitude are paramount for controlling the stability of these vehicles, both for autonomous riding and for safety reasons. A roll angle estimation is also useful in other situations, such as tests to perform the identification of the parameters of the rider control. In this work, a new algorithm is presented for estimating the roll angle of bicycles. This estimator, based on the well-known Kalman filter, employs a wheel speed sensor to approximate the speed of the vehicle, and three angular rate sensors, which are currently small and affordable sensors. The proposed method was implemented in a microcontroller and tested in a bicycle and the results were compared with measurements obtained with optical sensors, showing a good correlation. Although it has not been tested in motorcycles, comparable results are expected.