Slip and Adhesion in a Railway Wheelset Simulink Model Proposed for Detection Driving Conditions Via Neural Networks

Abstract

Constantly enlarging operation of locomotives with a very high tractive power in modern railway transport has caused problems with optimal supplying torque from motor to wheelsets. Losses emerging with inadequate torque values lead to wheel slipping connected with excessive wear and limited acceleration. In models simulating dynamics of torque transmission from the drive units to wheels, the most important are the submodel of the drive and the submodel of balance between traction forces and drive resistances. Some issues of this field studied within a PhD program and SGS (CTU Students Grant Competition) has been focused on increasing quality of these submodels. This contribution is aimed at an innovated part in the existing Simulink model utilizing new data sources and modeling techniques. This improvement supports application of operating point detection methods based on machine learning techniques. New control facilities provided with pulse-width modulated frequency control of the asynchronous motor will be used for automatic submission of optimal operating points. The idea of utilization of via simulation obtained data is an on-line training of polynomial neural unit as an approximation of current driving conditions. AbstraktNeustále narůstající provoz lokomotiv s velmi vysokým trakčním výkonem v moderní železniční dopravě způsobuje problémy s přenosem optimálního hnacího momentu z motoru na dvojkolí. Ztráty vyplývající z nevhodných hodnot točivého momentu vedou k prokluzu kol spojeným s nadměrným opotřebením a omezeným zrychlením. V modelech simulujících dynamiku přenosu točivého momentu z pohonné jednotky na dvojkolí jsou nejdůležitější submodely pohonu a rovnováhy mezi trakčními silami a jízdními odpory. Výzkum prováděný v rámci doktorských studijních programů a SGS (Studentská grantová soutěž ČVUT) se zaměřuje na zvyšování kvality těchto submodelů. Tento příspěvek je zaměřen na inovovanou část v existujícím Simulink modelu využívajícím nové zdroje dat a technik modelování. Nové možnosti regulace zajištěné pulzně-šířkovou frekvenční regulací asynchronního motoru budou použity pro automatické poskytnutí optimálních provozních bodů. Představa využití simulací získaných dat je on-line učení polynomické neuronové jednotky jako aproximace současných jízdních podmínek.

Research tools aplicable in designing of high-speed and high-power rail vehicles

“…On the real vehicle the slip is defined based on the difference of the vehicle speed and real rotation speed of a wheel-set. This fact is defined by the equation ( 2) and its deduction in [7] and Figure 8.…”

“…The basic idea for the supposed measurements of the adhesion coefficient comes from the picture of forces, which act in the wheel-rail contact as presented in [7] and Figure 7 and the knowledge, that the adhesion coefficient is a function of a wheel slip. According to the Equation (1) the tangential force T 1 , which is an equivalent of the wheel torque and vertical wheel force Q will be measured and adhesion coefficient µ will be calculated.…”

“…These are the electrical part, the mechanical part and the wheel-rail contact part, as shown in [8] and Figure 9. Fundamentals and function descriptions of the model as a whole were published in [7][8][9] and therefore no attention will be payed to them. The intention of this contribution is to present results of simulations focused on the oscillations.…”

“…The phenomenon of torsion oscillations has been researched via a mathematical model which is equivalent to a fully-sprung mechanical drive of a locomotive, see [7] and Figure 10. For the simulation model the drive has been reduced into a schematic torsion system as presented in Figure 11.…”

“…Particular rotation masses, defined by their mass of inertia J x and torsion springs between them, defined by their torsion stiffness k x are mathematically represented within the simulation model like in [7] and Figure 12.…”