Energy-efficient operation of heavy haul trains in an MPC framework

Abstract

An operation control approach for heavy haul trains to reduce the train's operating cost with operational safety and service quality considered is proposed. The main purpose of this study is to alleviate the cyclic vibration of couplers connecting neighboring cars in the train and to improve the train's overall performance. This is done by presenting a penalty factor for the coupler damping and a dynamically varying weight on the velocity tracking term in the objective function of the formulated problem. Reduction of coupler maintenance/replacement cost and energy consumption of the train are expected by the introduced penalty factor for the coupler damping in the optimization problem. The dynamically varying weight for velocity tracking term is expected to give room for improving the train's other performance indicators when the train's velocity tracking is sufficiently good. The problem is solved following a model predictive control approach. Taking advantage of the model predictive control approach, the controller designed is capable of scheduling the train to operate optimally during a long section of the rail track. Simulations verify that the proposed control approach is effective in improving the train's performance.