Online Identification of Running Resistance and Available Adhesion of Trains
Two important physical aspects that determine the performance of a
running train are the total running resistance that acts on the whole
train moving forward, and the available adhesion (utilizable
wheel-rail-friction) for propulsion and breaking. Using the measured
and available signals, online identification of the current running
resistance and available adhesion and also prediction of future values
for a distance ahead of the train, is desired. With the aim to enhance
the precision of those calculations, this thesis investigates the
potential of online identification and prediction utilizing the
Extended Kalman Filter.
The conclusions are that problems with observability and sensitivity
arise, which result in a need for sophisticated methods to numerically
derive the acceleration from the velocity signal. The smoothing spline
approximation is shown to provide the best results for this numerical
differentiation. Sensitivity and its need for high accuracy,
especially in the acceleration signal, results in a demand of higher
sample frequency. A desire for other profound ways of collecting
further information, or to enhance the models, arises with
possibilities of future work in the field.
Jesper Ahlberg and Esbjörn Blomquist
2011
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Last updated: 2021-11-10
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