Modelling and model validation of heavy-haul trains equipped with electronically controlled pneumatic brake systems

Chou, Min-Hung; Xia, Xi; Kayser, Cristine Alessandra

doi:10.1016/j.conengprac.2006.09.006

Cited by 128 publications

(60 citation statements)

References 12 publications

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“…Scown [10] and Simon et al [11] introduced the analysis of train energy consumption into the train dynamics, and the huge differences of energy consumption under the different train control modes were revealed. Aiming at the heavy-haul train with 200 cars, Chou et al [12] integrated the mathematic model of the electronically controlled pneumatic brake system into the train longitudinal dynamic model. Diana et al [13] specially simulated the mechanical couplers equipped in the European freight trains, and calculated the contact forces of each two coupling buffers under the different line conditions.…”

Section: Introductionmentioning

confidence: 99%

Establishment and verification of three-dimensional dynamic model for heavy-haul train–track coupled system

Liu

Zhai

Wang

2016

Vehicle System Dynamics

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For the long heavy-haul train, the basic principles of the intervehicle interaction and train-track dynamic interaction are analysed firstly. Based on the theories of train longitudinal dynamics and vehicle-track coupled dynamics, a three-dimensional (3-D) dynamic model of the heavy-haul train-track coupled system is established through a modularised method. Specifically, this model includes the subsystems such as the train control, the vehicle, the wheel-rail relation and the line geometries. And for the calculation of the wheel-rail interaction force under the driving or braking conditions, the large creep phenomenon that may occur within the wheel-rail contact patch is considered. For the coupler and draft gear system, the coupler forces in three directions and the coupler lateral tilt angles in curves are calculated. Then, according to the characteristics of the long heavy-haul train, an efficient solving method is developed to improve the computational efficiency for such a large system. Some basic principles which should be followed in order to meet the requirement of calculation accuracy are determined. Finally, the 3-D train-track coupled model is verified by comparing the calculated results with the running test results. It is indicated that the proposed dynamic model could simulate the dynamic performance of the heavy-haul train well. ARTICLE HISTORY

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Section: Introductionmentioning

confidence: 99%

Establishment and verification of three-dimensional dynamic model for heavy-haul train–track coupled system

Liu

Zhai

Wang

2016

Vehicle System Dynamics

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“…It is shown by simulations that the approach proposed yields better results in terms of the mean speed tracking error, in-train force, energy consumption and coupler fatigue indicators, when compared to our previous work [24] where no penalties and dynamic weighting methods are employed. In particular, the control proposed in this study reduces |f in | by 21 The results shown in this subsection verify that the the proposed approach is able to achieve better train performance with regard to the performance indicators considered, regardless of the rail track condition.…”

Section: E Performance On a Long Uphill Trackmentioning

confidence: 48%

“…Regarding the penalty factor for coupler damping, the choice of K d is indirectly related to the damping coefficients, d, of couplers in use (refer to [21] for details). A larger d means the coupler can dissipate more energy by damping.…”

Section: Discussionmentioning

confidence: 99%

“…It is concluded in [20] that the single mass model results in large in-train forces when the train is running over the top of a hill where the front part of train is running downhill while the rear part is running uphill. In view of this, the so called cascade mass point model was employed by [21], which models the whole train as individual masses (cars) interconnected by couplers…”

Section: X(t) and V(t) Are The Position And Velocity Of The Train At mentioning

confidence: 99%

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Development of an Optimal Operation Approach in the MPC Framework for Heavy-Haul Trains

Zhang

Zhuan

2015

IEEE Trans. Intell. Transport. Syst.

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Abstract-An operation control approach for heavy haul trains to optimize their performance, including operation safety, service quality and energy consumption, is proposed. Following a model predictive control method, the controller is capable of scheduling a train to operate optimally during a long section of the rail track. In the cost function, two penalty factors are presented, one for the braking forces and one for coupler damping effects. The penalty for braking forces is employed to reduce energy waste incurred by braking. The penalty for coupler damping is introduced to alleviate the cyclic vibration of couplers, which link adjacent cars in the train. The damping penalty is also expected to reduce energy wasted by coupler damping and corresponding maintenance/replacement cost of the dampers. In addition, the weight of the velocity tracking term in the objective function is modified to vary dynamically according to the train's velocity to improve the train's overall performance. Simulations verify the effectiveness of the proposed control approach. Discussions over the impacts of the two penalty factors and dynamic weight method are provided together with some suggestions on their applications.

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“…The discrete linear time-variant high-speed train model that will be linearized at each sampling time is described for model predictive controller design, which is based on a similar multi-points train model first proposed by Xia in [13] for heave-haul trains.…”

Section: Train Dynamicsmentioning

confidence: 99%

Application of the Model Predictive Control with Constraint Tightening for ATO System

Wang¹,

Xu²,

Zou³

et al. 2015

IJCA

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Modelling and model validation of heavy-haul trains equipped with electronically controlled pneumatic brake systems

Cited by 128 publications

References 12 publications

Establishment and verification of three-dimensional dynamic model for heavy-haul train–track coupled system

Establishment and verification of three-dimensional dynamic model for heavy-haul train–track coupled system

Development of an Optimal Operation Approach in the MPC Framework for Heavy-Haul Trains

Application of the Model Predictive Control with Constraint Tightening for ATO System

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