Abstract
In Chinese mainline railway, freight trains need to stop within passenger stations at times because of the delayed passenger trains. Without any decision-support system, it is very difficult for drivers to stop trains within stations with consistency in one braking action. The reasons are that braking performance of train changes with the conditions of braking equipment and the drivers’ subjective evaluations of track profiles and braking distance are vague and imprecise. This paper presents a fuzzy neural network (FNN), which is based on the historical datasets of train stops, to model the latest condition of train braking equipment and to attain the braking distance under a predefined braking rate, track profiles, and initial braking speed. The braking distance is used to find the initial braking position to advise the drivers on commencing braking action. Case studies confirm that it is feasible to stop trains within stations in one braking action by applying the proposed approach. Furthermore, the runtime and energy consumption of train movement are both reduced in comparison to the practical two-step action train stopping (TATS); that is, drivers stop trains before entering stations and remotor at a low speed before slowly stopping within stations.
Highlights
Railway plays a very important role in many countries
The station stopping of freight trains aims to keep the number of changes of braking rate minimal to reduce dynamic longitudinal forces within trains, which may lead to the rupture of coupler yokes in heavy trains [8]
Once the braking distance is attained, the initial braking position is determined and the corresponding ig is known. If it is different from the initial one, the ig forwarded into the fuzzy neural network (FNN) model should be updated to attain the new braking distance until the input ig of FNN equals the weighted average of equivalent track gradient corresponding to the output S of FNN
Summary
Railway plays a very important role in many countries. Its development goes very closely with the stringent requirements on safety, reliability, and environment impacts. Because the train stops twice, the run-time and energy consumption both increase substantially To this end, this paper aims to propose a control approach to assist drivers stop the train within stations in one braking action. The problem discussed in this paper is to find initial braking position according to the target stop point and the braking distance with a constant braking rate. Analytical models have been developed to calculate the braking distance under given control instructions and operation condition [10, 11] These models do not take into account the tear-and-wear of train braking equipment, which directly affects train braking performance. The initial braking rates applied are tuned at real-time at predefined positions according to the estimated train braking performance [15] These methods achieve high accuracy but bring an increase on the operating cost.
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