Operation Of Heavy Haul Train Research Articles

Multiobjective Optimization and Weight Selection Method for Heavy Haul Trains Trajectory

Energy-saving, punctuality and smoothness are difficult to achieve in the operation of heavy haul train. This paper proposes a multi-objective method for speed curve optimization. Firstly, a quadratic programming optimization model is established, using train kinetic energy and train force as independent variables and several goals of energy conservation, smoothness, and target speed tracking. Under the supplied weight vector, the model can realize the ideal speed curve under unbounded time. Secondly, in order to address the demand for punctuality, this paper develops a weight selection algorithm to optimal weight vector for any given trip time. Finally, a time-bounded multi-objective speed curve optimization model is proposed, which achieves energy conservation, punctuality and smoothness train operation. The simulation indicates that the proposed algorithm outperforms human driving in multi-objectives. And the designed time bounded weight selection algorithm is more efficient than the conventional linear approaching weight search method.

Analysis of positioning of wayside charging stations for hybrid locomotive consists in heavy haul train operations

Hybrid locomotive concepts have been considered as a step towards converting the railway industry into a green transport mode. One of the challenges in integrating a hybrid locomotive in the train consist is that the battery pack in the locomotive needs to be recharged during a long-haul trip which requires stopping of the train. A typical battery pack requires about 1 h to recharge which is unacceptable. With the improvement in the charging system, it is now possible that the same capacity battery pack could be recharged in 10–12 min which can be a competitive option for the railway companies. This paper proposes a method based on simulation to evaluate the positioning of charging stations on a train network. A typical example of a heavy haul train operation hauled by diesel-electric and hybrid locomotives is used to demonstrate the method by using simulation softwares. The result of the simulation study show that the method developed in this paper can be used to evaluate the state of charge (SoC) status of a hybrid locomotive along the track. It is also shown that the SoC status obtained by the simulation method can be further used to assess the positions of charging stations along the track at the design stage.

Three-dimensional fatigue crack propagation analysis of welded steel beam based on global-local numerical model

The existing fatigue assessment approaches were mainly conducted on the component level. The interaction of local component damage and the global response cannot be well addressed. In this study, three-dimensional (3D) fatigue crack propagation analysis approach based on global-local numerical model was implemented, and examined to be accurate and effective through a series of systematic experimental data obtained by Fisher. Afterwards, the approach was introduced into a typical steel truss bridge for realizing more refined fatigue assessment from the global structural level. The fatigue performance of the longitudinal steel welded beam in the steel truss bridge was investigated based on global-local model and local model respectively. It was found that there is no difference in terms of the fatigue crack growth mechanism between the simulation between global-local model and local model due to that the stress level of the whole structure is relatively low. At last, the effect of heavy haul train operation on the fatigue performance of the steel truss bridge was analyzed. It was observed that the residual life of the longitudinal steel welded beam would have an obvious reduction when the axle load was increasing. The research work in this study presents a technical solution for the fatigue assessment of the global structure and can provide beneficial reference for relevant practical engineering projects.

MODEL-BASED ASSESSMENT OF LONGITUDINAL DYNAMIC PERFORMANCE AND ENERGY CONSUMPTION OF HEAVY HAUL TRAIN ON LONG-STEEP DOWNGRADES

Longitudinal dynamics performance and energy consumption of heavy haul train should be considered in the design of heavy haul railway profile of long-steep downgrades. A quantitative analytical tool is developed to assess the longitudinal dynamic performance and energy consumption of heavy haul trains with large axle loads on grades with different longitudinal profiles, including a longitudinal dynamic model of the train and a method of calculating the energy consumption during the operation of heavy haul train. The model is then preliminarily validated by the data of coupler force collected in two comprehensive tests. Finally, the proposed analytical tool is used to assess the designed longitudinal track profile of a long-deep downgrade segment of the central south heavy haul railway of Shanxi (China).

Intelligent operation of heavy haul train with data imbalance: A machine learning method

Compared with high speed trains and metro subways, heavy haul train operations are more challenging for their complex dynamic characteristics and complicated running environments. When running on a continuous and steep descent, the air brake operation strategy has become the most important issue for the safety and efficiency of heavy haul train transportation. Due to the difficulty in modeling the train’s dynamics and pneumatic brake system precisely, this paper addresses the intelligent driving problem for heavy haul train based on the fusion of expert knowledge and machine learning methodologies. By considering the characteristics of manual driving on steep descent, the pneumatic brake operation problem is formulated as a multi-class classification model. To overcome the negative influences of data imbalances, EasyEnsemble for the multi-class with a KNN based Denoising (EMKD) algorithm is introduced to determine the feasible Air Pressure Reduction (APR) and the exact time for exerting and releasing the air brake. This approach utilizes the EasyEnsemble.M algorithm to moderate the class imbalanced datasets and takes advantage of the AdaBoost.M1 algorithm to ensemble weak classifiers. Specifically, the K-nearest neighbor based Denoising (KD) algorithm is elaborated to remove the possible noise data from the minority dataset. Additionally, expert knowledge is obtained by abstracting the experience of sophisticated drivers and technical specifications, which are employed as operating constraints to regulate the output of the EMKD algorithm. The operational safety in terms of the in-train forces and punctuality of the proposed algorithm are validated by a number of experiments under the real running circumstances of Shuohuang heavy haul railway.

An air brake model for longitudinal train dynamics studies

ABSTRACTExperience of heavy haul train operation shows that heavy haul train fatigue fracture of coupler and its related components, even the accidents are caused by excessive coupler force. The most economical and effective method to study on train longitudinal impulse by reducing the coupler force is simulation method. The characteristics of train air brake system is an important excitation source for the study of longitudinal impulse. It is very difficult to obtain the braking characteristic by the test method, a better way to get the input parameters of the excitation source in the train longitudinal dynamics is modelling the train air brake system. In this paper, the air brake system model of integrated system of air brake and longitudinal dynamics is introduced. This introduce is focus on the locomotive automatic brake valve and vehicle distribution valve model, and the comparative analysis of the simulation and test results of the braking system is given. It is proved that the model can predict the characteristics of train braking system. This method provides a good solution for the excitation source of longitudinal dynamic analysis system.

A New Method for Heavy-Haul Train Operation Monitoring

Based on the vehicle-track coupled dynamic theory, a new method was developed to monitor the state of heavy-haul train, this method can dynamically monitor the wheel/rail dynamic safety performance of heavy-haul train in the dangerous operation condition. The results show that: wheel/rail dynamic action is obvious whether the wheel flat is new or old, and wheel flat could lead to mutational vertical force.