Comparison of the re-adhesion control strategies in high-speed train


Uyulan C., Gökaşan M., Bogosyan S.

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING, cilt.232, sa.1, ss.92-105, 2018 (SCI-Expanded) identifier identifier

Özet

Excessive driving force applied to the trains leads to an inadequate utilization of the adhesion phenomenon occurred at the wheel-rail contact, and an unnecessary power consumption, while inadequate driving force causes the train to run inefficiently. For this reason, the necessity of re-adhesion control in the safe and reliable operation, in the balance of energy consumption, is indisputable. A comparison of the two re-adhesion control strategies, one of which is robust adaptive and the other of which is the modified super-twisting sliding mode, has been presented in this article. These control algorithms developed suppress the wheel slip on time and maintain optimal traction performance after re-adhesion under the nonlinear properties of the traction system and the uncertainties of the adhesion level at the wheel-rail interface. Due to the complex nonlinear relationship between the adhesion force and the slip angular velocity, such a problem becomes a hard problem to overcome as long as the optimal slip ratio is not known. An optimal search strategy has also been developed to estimate and to track the desired slip angular velocity. By means of the proposed strategies, the traction motor control torque is automatically adjusted so as to ensure that the train operates away from the unstable slip zone but adjacent to the optimal adhesion region, and the desired traction capability is attainable once adhesion is regained. Mathematical analyzes are also provided to ensure the ultimate boundedness of the algorithms developed. The effectiveness of the proposed re-adhesion strategies is validated through the theoretical analysis and numerical simulations conducted in MATLAB and Simulink. As a result of consecutive simulations, modified super-twisting algorithm has shown better performance as compared to the robust adaptive one in tracking the optimal slip velocity as wheel-rail contact conditions switch suddenly.