Train Braking Distance Estimation Under Different Operating Conditions
01 Jan 2011-pp 39-45
TL;DR: In this paper, the authors developed a dynamic model of a train consist that includes three railcars for performing a parametric study to evaluate how various elements will affect the train stopping distance, from an initial speed.
Abstract: One of the critical factors in Positive Train Control (PTC) is accurately estimating the train braking distance under different conditions. Accurate estimation of the braking distance will allow the trains to be spaced closer together, with reasonable confidence that they will stop without causing a collision. This study will develop a dynamic model of a train consist that includes three railcars for performing a parametric study to evaluate how various elements will affect the train stopping distance, from an initial speed. Parameters that can be varied in the model include, initial train speed, railcar weight, wheel-rail interface condition, and dynamic braking force. Other parameters are included in the model such as aerodynamic drag forces and air brake forces. The model is based on a multibody formulation of the railcars, trucks (bogies), and suspensions. The paper will include the derivation of the mathematical model and the results of a numerical study in Matlab. The results indicate that the railcars’ weight and initial speed play a significant role in the stopping distance and the time required to stop the train. Our future work will include using this model for closed-loop control of the dynamic braking forces, such that the train braking distance and time to stop can be minimized, under various wheel-rail dynamic conditions.Copyright © 2011 by ASME
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TL;DR: Evaluations have been made on brake disc-pad mechanisms which are the most important components in all brake systems in terms of safe operation especially for freight and high-speed trains.
33 citations
Dissertation•
28 Mar 2013
TL;DR: In this paper, a model reference adaptive control (MRAC) for train dynamic braking is investigated in order to control dynamic braking forces while remaining within the allowable adhesion and coupler forces.
Abstract: The application of Model Reference Adaptive Control (MRAC) for train dynamic braking is investigated in order to control dynamic braking forces while remaining within the allowable adhesion and coupler forces. This control method can accurately determine the train braking distance. One of the critical factors in Positive Train Control (PTC) is accurately estimating train braking distance under different operating conditions. Accurate estimation of the braking distance will allow trains to be spaced closer together, with reasonable confidence that they will stop without causing a collision. This study develops a dynamic model of a train consist based on a multibody formulation of railcars, trucks (bogies), and suspensions. The study includes the derivation of the mathematical model and the results of a numerical study in Matlab. A threerailcar model is used for performing a parametric study to evaluate how various elements will affect the train stopping distance from an initial speed. Parameters that can be varied in the model include initial train speed, railcar weight, wheel-rail interface condition, and dynamic braking force. Other parameters included in the model are aerodynamic drag forces and air brake forces. An MRAC system is developed to control the amount of current through traction motors under various wheel/rail adhesion conditions while braking. Minimizing the braking distance of a train requires the dynamic braking forces to be maximized within the available wheel/rail adhesion. Excessively large dynamic braking can cause wheel lockup that can damage the wheels and rail. Excessive braking forces can also cause large buff loads at the couplers. For DC traction motors, an MRAC system is used to control the current supplied to the traction motors. This motor current is directly proportional to the dynamic braking force. In addition, the MRAC system is also used to control the train speed by controlling the synchronous speed of the AC traction motors. The goal of both control systems for DC and AC traction motors is to apply maximum available dynamic braking while avoiding wheel lockup and high coupler forces. The results of the study indicate that the MRAC system significantly improves braking distance while maintaining better wheel/rail adhesion and coupler dynamics during braking. Furthermore, according to this study, the braking distance can be accurately estimated when MRAC is used. The robustness of the MRAC system with respect to different parameters is investigated, and the results show an acceptable robust response behavior.
10 citations
TL;DR: In this article, the proper dynamics of wheelset for velocities acting in three dimensions of wheelsets and rail track along with creep forces on each wheel in longitudinal, lateral and spin directions has been enumerated and computed for suitable modeling.
Abstract: Adhesion level control is very necessary to avoid slippage of rail wheelset and track from derailment for smoothing running of rail vehicle. In this paper the proper dynamics of wheelset for velocities acting in three dimensions of wheelset and rail track has been discussed along with creep forces on each wheel in longitudinal, lateral and spin directions has been enumerated and computed for suitable modeling. The concerned results have been simulated by Matlab code to observe the correlation of this phenomenon to compare creepage and creep forces for detecting adhesion level. This adhesion identification is recognized by applying coulomb’s law for sliding friction by comparing tangential and normal forces through co-efficient of friction
4 citations
01 Jan 2013
TL;DR: In this paper, the authors present an experimental investigation of critical stopping distances and time to stop for passenger vehicles travelling along various road surfaces and environmental conditions, including evasive manuvers and braking functions initiated by the driver as objects suddenly appear in the path of the vehicle.
Abstract: This research work presents an experimental investigation of critical stopping distances, and time to stop for passenger vehicles travelling along various road surfaces and environmental conditions. Although this is a complex problem with numerous variables, we investigate different weight classes of vehicles, vary specific vehicle parameters and script the environment to emulate realistic driving scenarios. A quarter-car physical hardware platform is utilized along with realistic driver inputs to the Vehicle Modeling and Simulation Laboratory (VMSL) platform. The VMSL platform utilizes CarSim©, a commercial software package, and Matlab/Simulink© to implement the vehicle brake actuator and brake control system. The research investigation proceeds by modeling evasive manuvers and braking functions that are initiated by the driver as objects suddenly appear in the path of the vehicle. We constrain the problem by assuming minimum advance warning (i.e., time) from the sensor set (i.e., RADAR, LIDAR, Vision). Key performance parameters (decel, stopping distance, surface friction coefficient -µ) are recorded and analysed for data statistics to avoid crashes. Research results are derived and presented as mathematical models of stopping distances and times to stop as a function of set parameters (µ friction coefficient, vehicle speed, and input pressure at the master cylinder). It is critical for braking system engineers to achieve shorter stopping distances and thus keep the drivers and passengers safe as well as reduce or avoid crashes all together.
2 citations
Cites background or result from "Train Braking Distance Estimation U..."
...Both the, work presented here and the work presented in [13] reach the same conclusion....
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...The work presented in [13] focuses on development of railcar train model and its respective equations of motion for the estimation of braking distance as a function of various parameters....
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...The research work presented here can be strongly tied and compared with [13, 14] where the research is focused on estimating the safe braking distance for train....
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..., multicar model, steel tracks), simulation results in this investigation are similar for train braking distance estimation [13, 14]....
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...The figures presented in section C in [13] are similar to Fig....
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01 Jan 2014
TL;DR: In this paper, the authors analyzed the adhesion of rail wheelset under the assumption of constant creep coefficient and derived equations of creepage and creep forces in longitudinal, lateral and angular directions.
Abstract: Adhesion level control plays significant role in order to keep smooth running of a train. To design a proper adhesion controller, adhesion dynamics needs to be analyzed. In this paper adhesion is analyzed by modeling rail wheelset dynamics under the assumption of constant creep coefficient. Equations of creepage and creep forces were derived in longitudinal, lateral and angular directions. Numerical simulation was conducted under assumption of constant creep coefficient. The creep coefficient was obtained by applying Coulomb's law of friction. From the simulation results it can be concluded that adhesion level for suitable dynamic model determination depends on assumption of creep analysis to avoid slip or derailment of rail wheelset.
1 citations