Roll angle estimator based on angular rate measurements for bicycles

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...

Full description

Saved in:
Bibliographic Details
Published in:Vehicle system dynamics 2019-11, Vol.57 (11), p.1705-1719
Main Authors: Sanjurjo, Emilio, Naya, Miguel A., Cuadrado, Javier, Schwab, Arend L.
Format: Article
Language:English
Subjects:
Algorithms
Angular speed
bicycle
Bicycles
Control stability
inertial sensors
Kalman filter
Kalman filters
Microcontrollers
Motorcycles
Optical measuring instruments
Parameter identification
Roll angle estimator
Sensors
single-track vehicle
Traffic speed
Vehicles
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:0042-3114
1744-5159
DOI:10.1080/00423114.2018.1551554