TY - JOUR
T1 - Roll angle estimator based on angular rate measurements for bicycles
AU - Sanjurjo, Emilio
AU - Naya, Miguel A.
AU - Cuadrado, Javier
AU - Schwab, Arend L.
PY - 2018
Y1 - 2018
N2 - 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.
AB - 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.
KW - bicycle
KW - inertial sensors
KW - Kalman filter
KW - Roll angle estimator
KW - single-track vehicle
UR - http://www.scopus.com/inward/record.url?scp=85058071843&partnerID=8YFLogxK
U2 - 10.1080/00423114.2018.1551554
DO - 10.1080/00423114.2018.1551554
M3 - Article
AN - SCOPUS:85058071843
SN - 0042-3114
VL - 57 (2019)
SP - 1705
EP - 1719
JO - Vehicle System Dynamics
JF - Vehicle System Dynamics
IS - 11
ER -