Model-based estimation and control of wheel slip in locomotives

Abstract

This dissertation investigates wheel slip control of locomotive traction systems in the presence of non-linear wheel surface behaviour and varying adhesion conditions. It is difficult to determine when the maximum point of adhesion has been exceeded since the adhesion coefficient cannot be measured directly during the operation of the locomotive. Therefore, classical slip controllers suppress excessive slip by using predetermined thresholds for the slip velocities and accelerations of the axles. The classical methods are convenient but cannot maximise adhesion utilisation.

Modern methods continuously modulate the torque and are expected to produce superior performance if implemented effectively. Most continuous controllers calculate the reaction torque using a generated slip ratio (slip velocity divided by the locomotive velocity) reference and a slip ratio estimate feedback. Computing the estimate depends on an accurate locomotive velocity estimate, which is difficult to obtain when all the wheelsets of a locomotive are driven. Slip ratio reference generation generally requires estimates of the slip ratio and adhesion coefficient or adhesion force. This dissertation focuses on producing accurate estimates to enable effective slip control.

Adhesion force is the adhesion coefficient multiplied by the normal force. The adhesion coefficient is dependent on the rail conditions. Under constant rail conditions, it varies only with a wheel load and slip ratio change. Therefore, the normal forces, wheel velocities, and locomotive velocity should be modelled accurately to ensure the model produces realistic adhesion coefficients. A linearised railway vehicle model could be well over the 100th order. Such models are helpful for design and validation, but using such complex models in model-based filter or estimator design is impractical.

In this dissertation, a new simulation model is developed that includes the longitudinal, pitch, vertical, and wheelset rotational dynamics. In addition, it includes a unique approach to the coupler force by modelling the wagons using a single-axle wheelset model. This model captured the desired dynamics, including wheelset torsional vibrations and oscillations in the pitch dynamics.

A linear state-observable estimator is developed to produce estimates of slip ratios and adhesion coefficients. The estimation model is an adaptation of the simulation model, but the adhesion forces and coupler force are modelled as unknown disturbances. This estimator requires measurements of the locomotive longitudinal acceleration and velocity, body pitch angle and rate, and the motor angular velocities. The rail angle and motor torque estimates should be provided to the estimator.

The estimates are used in a novel slip ratio reference adaptation method to provide a reference to an adaptive PI controller. The PI controller is used to compute the reaction torque to prevent unstable slip in the rear/reference wheelset, while a speed differential controller is used to prevent slip in the other wheelsets.

The simulation results indicate that the estimator and controller configuration can suppress unstable slip under varying adhesion conditions, thereby preventing damage to the wheels and rail while ensuring maximum adhesion utilisation. Maximum adhesion utilisation allows a locomotive to increase its hauling capacity without increasing its mass.