Thursday, November 25, 2010

Heavy Haul Braking using Electronically-Controlled Pneumatic (ECP) brakes

GLOBAL demand for Australian coal and iron-ore is driving an expansion of heavy-haul railroading. Some of the heaviest trains in the world operate in extremely challenging conditions with consists of up to 240 wagons hauling iron-ore, magnetite and coal from the interior to ports on the coast. Australia's largest mining companies are equipping their new fleets with electronically-controlled pneumatic (ECP) brakes for increased safety and efficiency. The same is happening in Brazil and South Africa.

ECP braking requires a wire trainline to transmit electronic brake signals along the consist to apply brakes, rather than using air pressure changes in the brake pipe. Wagons receive the signal and brake simultaneously, rather than sequentially over a period of up to 2 minutes, as can be the case with pneumatically-controlled brakes. The result is more precise braking and train handling, reduced in-train forces, and shorter, faster stopping. Moreover, since the brake reservoirs are charged continually, the train can recover and get back to line speed very rapidly after a stop. Five heavy-haul railways - Fortescue Mining Group (FMG), BHP Billiton, Rio Tinto, Pacific National and Queensland Rail have adopted or are currently running ECP brakes in Australia.

 

The benefits of ECP brakes include reduced stopping time, shorter stopping distance, reduced wear on equipment, and quicker re-start after stopping. Results from real-world testing on both moderate and steep gradients, presented by Mr Jim Forrester of Norfolk Southern at the 2010 National Coal Transportation Operations and Maintenance Conference, showed significant improvements in all of these areas.

On moderate gradients, ECP-equipped trains ran at 10% higher speeds than non-ECP trains. Nonetheless, stopping distances were 404.8m on average, 36% less than a train equipped with conventional brakes. Stopping time was similarly shorter: 49 seconds versus 71 seconds. The trains resumed normal speed in 25% less time - a depleted tramline requires handbrakes to be set throughout the train while re-charging, and then released before the train is ready for movement.

 

Results were even better on steep gradients. From the same initial speed, the train stopped in 297.5m, 53% shorter than a conventional train. Stopping time was 46 seconds, versus 88 seconds for the conventionally-braked train. The ECP train resumed normal operating speeds much faster, in 2min 25s versus 1h 23min 33s for the conventional train, because the conventional train had to set its parking brakes while on a gradient.

A key benefit of the networking of the train is simplified diagnostics. The brakes on each wagon now report electronically to the locomotive, enabling in-cab reporting and troubleshooting rather than on-foot, wagon-by-wagon testing. NYAB has developed a Tramline Integrity Locomotive Test (Tilt) device which accesses the Tramline Communications Controller (TCC) diagnostics to make it easier to test trainline functions.

All of these elements are coming into play in Australia as more and more ECP-equipped trains come on line moving ore and coal from the mines to the ports, and out into the world market. South African and Brazilian railways are also taking part in the move to ECP braking. The early results reward the efforts to pioneer electronic braking to bring more and better information to the driver and more efficiency to the heavy-haul railway industry worldwide.

 

Rail Track Maintainance Prediction

In general, rail life is analysed segment-by-segment with each based on the optimum length required for effective analysis and specific track and traffic conditions. The segments are assumed to be homogeneous in that the rail life and certain key parameters will be the same for the entire segment. The rail fatigue life forecasting algorithm uses Weibull analysis techniques to predict defect growth rates and future defect levels. Studies have shown that rail develops fatigue defects as a function of the cumulative traffic that passes over it, in addition to factors such as axleload, wheel-rail contact, and rail metallurgy and cleanliness. The rate of defect formation and accumulation with traffic has been shown to follow a Weibull distribution, which is in the form of a logarithmic relationship. Thus, as the rail ages, the expected rate of defect occurrence increases significantly, corresponding to the logarithmic nature of the Weibull equation. Since complete fatigue and tonnage data is not always available, effective models, such as RailLife, employ a hierarchy of analysis approaches, which are directly related to the actual amount of available data. The output of the algorithms is an annual forecast of defect rate (defects/km/year) and cumulative defects for each segment, together with the forecast life of the rail. Rail life forecasts are based on user defined rail replacement criteria which are usually characterised by the number of defects, particularly fatigue related defects, which occur within a defined period of time, usually a year. This is the point at which it is most appropriate to replace the rail.

 

Rail grinding management software is used to manage the removal or control of rail surface defects and to maintain the rail profile, which in turn affects both rail fatigue and wear rates. Research has shown that rail grinding is extremely effective in reducing the rate of fatigue defect development and extending the rail life. Control of the wheel-rail interface through grinding has also been shown to be effective at reducing the rate of rail wear. Software tools are used to manage, plan, and monitor rail grinding and management of the rail profile. This includes comparison of actual and desired rail profile or template (Figure 3) and the development of a curve-by-curve grinding plan, which defines the number of grinding passes, pattern, and grinding speed.