Citation

Sanjurjo E, Naya MA, Cuadrado J, Schwab AL. Veh. Syst. Dyn. 2019; 57(11): 1705-1719.

Copyright

(Copyright © 2019, Informa - Taylor and Francis Group)

DOI

10.1080/00423114.2018.1551554

PMID

unavailable

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.

Language: en

Keywords

bicycle; inertial sensors; Kalman filter; Roll angle estimator; single-track vehicle