Roll angle estimator based on angular rate measurements for bicycles

Emilio Sanjurjo*, Miguel A. Naya, Javier Cuadrado, Arend L. Schwab

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

9 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)1705-1719
JournalVehicle System Dynamics
Volume57 (2019)
Issue number11
Publication statusPublished - 2018


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


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