Virtual torque sensor for electrical bicycles

IFAC-PapersOnLine, vol. 53, pp. 8903–8908

Abstract

We present a novel approach to the reconstruction of the physical pedalling torque in an electrically powered bicycle. The external force due to the road slope that is acting on the bicycle is estimated employing the reconstruction of the inclination angle with an orthogonal filter. This orthogonal filter uses an adaptive weighting between gyroscope and accelerometer sensor data. The applied weighting function is based on the bicycle’s acceleration, estimated from a bicycle velocity sensor. By employing a nonlinear physical model of the bicycle, the cyclist’s pedalling torque is reconstructed with an Unscented Kalman Filter. Experimental results from the inclination angle estimator and virtual torque sensor for different road slopes underline the performance of the proposed approach.

Authors 5

1. Berno J.E. Misgeld corresponding Aachen Philips Chair for Medical Information Technology

   RWTH Aachen University

   Affiliation as printed

   Amprio GmbH, Neuss, Germany

   Philips Chair for Medical Information Technology, RWTH Aachen University, Aachen, Germany

2. Lukas Bergmann Aachen Philips Chair for Medical Information Technology

   RWTH Aachen University

   Affiliation as printed

   Philips Chair for Medical Information Technology, RWTH Aachen University, Aachen, Germany

3. Bence Szilasi
   Affiliation as printed

   Amprio GmbH, Neuss, Germany

4. Steffen K. Leonhardt Aachen Philips Chair for Medical Information Technology

   RWTH Aachen University

   Affiliation as printed

   Philips Chair for Medical Information Technology, RWTH Aachen University, Aachen, Germany

5. Dietmar Greven
   Affiliation as printed

   Amprio GmbH, Neuss, Germany