Train Dynamics Management Project 1999-2005

Project Manager:

Prof Colin Cole

Sponsor Organisations:

• QR

Staff Members:

• Mitchell McClanachan
• Scott Simson
• Trevor Ashman
• Grant Caynes
• Chris Bosomworth

Objectives

The Train Dynamics Management Project has the objective of bringing about an overall improvement of train management from a broad based program of research. The research aims for train management optimisation with focus on reductions in energy consumption and train dynamics while maintaining or improving train schedule running times.

Background

In 1994 the Train Dynamics Group began testing of wagon and train dynamics on the Callemondah-Blackwater coal haulage system. In 1996 comprehensive testing of the whole track section for both empty and loaded trains was completed. This program included coupler force, inter-wagon and brake instrumentation on six hopper type coal wagons and two locomotives. A wealth of field data was obtained and analysed. This data was used to extend knowledge of train dynamics. The Train Dynamics Management Project was implemented in 1999 and has the overall objective of providing practical feedback paths into QR's operating practices that will realise the benefits that continue to accrue from the Train Dynamics research.

Outcomes

(Project Now Closed)

The benefits come from improvements in driver training and hence train handling, as well as reductions in the costs of energy, maintenance and training. Overall, the Train Dynamics Management Project will reduce the cost of running trains.

The project focuses on Unit Coal Trains and Mainline Freight Trains. However, TDMP research addresses the practical engineering and systems that are the essential core business of a railway and as such the research has positive implications for all of QR's operations.

The specific research tasks required to achieve the objective have been identified and are contained in individual projects that are programmed to deliver a system of interactive in-service train management for Mainline Freight operations over several years. The research is intended to then build on this outcome for another few years to develop an intelligent train monitor for unit coal trains.