Railways play one of the most important roles in today’s transport systems throughout the world due to their safety, relatively high traction capacity and low operation and maintenance cost [1]. With the development of electric drive and power electronics technology, the capacity and efficiency of railway transport has been improved dramatically, giving birth to higher speed passenger trains and higher capacity heavy haul trains. In Australia, the development of the mineral resources industry drives further improvement of railway operational efficiency without bringing excessive burden to infrastructural maintenance. The purpose of this thesis is to provide the required modelling and simulation to determine appropriate tractional system conditions and controllers to achieve this. The first part of this thesis is focused on building a locomotive mathematical model including all the essential dynamic components and interactions to provide prediction of locomotive dynamic response. The overall model consists of locomotive dynamics, wheel/rail contact dynamics and electrical drive and control dynamics. The locomotive dynamics include longitudinal, vertical and pitch motions of the locomotive body, front and rear bogies and six axles. For the wheel/rail contact dynamics, the Polach model is used to obtain the amount of tractive force generated due to wheel/rail interaction on the contact patch. The simplified electric drive dynamics are designed according to the traction effort curves provided by industry using constant torque and constant power regions. Modes of oscillations have been identified by eigenmode analysis and show that all the vertical and pitch modes of the locomotive dynamics are stable. The modes that are most likely to contribute to dynamic behaviour are identified and it is shown that the locomotive body pitch mode is most excited by traction perturbations. The locomotive dynamic behaviour under changes in contact conditions is also examined. The second part of this thesis is focused on achieving higher tractive force under different operating speed and wheel/rail contact conditions. The dynamic impact of a new control strategy is compared with that of a traditional fixed threshold creep/adhesion control strategy. A fuzzy logic based control strategy is employed to adjust the torque output of the motors according to the operating condition of the locomotive to achieve higher tractive force than that with the traditional constant creep control strategy. Simulation results show that by controlling the torque generated by the electric drives, tractive force can be maximized. However, the benefit in the tractive force increase is marginal under low speed operation at the cost of higher creep values. Under high speed operation, due to the impact of the electric drive traction effort characteristics, the dynamic responses with both control strategies are mostly identical. The last part of this thesis is focused on specialized real-time traction control that regulates the wear to low levels, which is motivated by the increased amount of rail wear damage observed in the rail industry in recent years. In this thesis, a novel real-time approach of controlling wear damage on rail tracks is proposed based on a recent wear growth model. Simulation results show that under high speed operation the dynamic responses are mostly identical with two investigated control strategies due to the impact of the electric drive traction effort characteristics. However, the new control strategy can effectively reduce wear damage dramatically under other operation conditions, with a relatively small amount of tractive force decrease. The work in this thesis explores various aspects of locomotive traction research. The most important contributions are the development of a mathematical/simulation model for predicting the dynamic response of a locomotive under change of operating conditions and its impact on wear damage on rail tracks. The impact of maximizing tractive effort on rail track wear damage is quantified, providing practical guidance on locomotive operation. In addition to this, the development and testing of a specialized real-time traction control strategy that regulates the wear to low levels based on a recent wear growth model is provided.