Railway wheels have to be reprofiled or replaced if they do not fulfil certain demands and the costs for these actions can be considerable for the vehicle owner. The purpose of this work is to study wheel profiles at reprofiling through wheel wear simulations and reprofiling statistics.

The application at hand is the Rc4 locomotive used by the railway freight company Green Cargo. The locomotives travel the whole electrified Swedish railway network but a large part of the traffic is on the lines Malmö-Hallsberg and Luleå-Ockelbo. For these two lines the distributions of curve radius, track quality and lubrication have been analysed.

The simulation method is based on a load collective concept where the load collective is a discretization of actual conditions such as track design geometry, rail profiles, track irregularities, lubrication, vehicle speed and traction. The discretization results in a number of dynamic time-domain simulations to be performed in each wear step. The time-domain simulations are done with the MBS (Multi-Body-Simulation) tool Gensys. From these simulations the wear is calculated with a program developed in MATLAB, the wheel profile is updated and the next wear step is entered. In the vehicle-track simulations the wheel-rail contact is modelled with the Hertzian theory for the normal contact and Kalker’s simplified theory for the tangential forces. Archard’s wear equation together with wear coefficients have been used to calculate the material worn off from the wheel. The wear coefficients have been determined from dry conditions and to compensate for both natural and manmade lubrication two scaling factors are used.Reprofiling of wheels on the Rc4 locomotive is done in two workshops and wheel profiles and wheel lathe differs between these two workshops. At assembling of new wheels the wheels have the UIC/ORE S1002 profile with flange thickness 32.5 mm but in order to save wheel diameter at reprofiling two different profiles with smaller flange thickness are used. From a wheelset database used by Green Cargo for maintenance planning statistics such as distribution of reprofiling causes, seasonal variations of wheel wear and damages, running distances, life length of wheels and wear rates for different profiles have been extracted.

For evaluation purposes wheel profiles of three locomotives were measured before and after the first reprofiling. When comparing measured and simulated wheel profiles it can be concluded that the simulation overestimates flange wear somewhat but the shape of the flange is close to measurements. Wheel tread wear is generally well predicted but the shape differs more. The simulation results are also compared, with good agreement, to simple measurements of wheel wear scalars from the wheelset database. For some wheel profiles problems in the simulations with unrealistic cavities at the wheel tread remain to be solved.Through simulations it has been seen that with a slight change of one of the profiles used at reprofiling running distance before reprofiling due to thin flanges can be increased with 95 kkm.