Energy-optimal control of intelligent track inspection trains: design and experiment

Abstract

A new energy-efficient control strategy for intelligent track inspection trains (ITITs) was developed and its effectiveness evaluated. A sufficiently simple state-space model for a real ITIT is introduced in this paper. This model was used to formulate and solve a constrained optimisation problem to determine the vehicle's optimal speed profile using the pseudo-spectral method to achieve the highest energy savings. A model predictive control (MPC) scheme was then used to create a controller to follow the resulting optimal speed trajectory as closely as possible. The results obtained from co-simulation between a high-fidelity model of the ITIT built within the Amesim software program and the MPC scheme developed in the Matlab/Simulink software environment showed that the optimal speed trajectory was tracked very well when the MPC scheme was applied to the vehicle's high-fidelity model. During the co-simulations, the energy consumption in terms of the battery's state of charge (SOC) changes for the MPC-based optimal speed trajectory following was around 6% less than that for a conventional non-optimal cruise controller. Moreover, in an experiment with a real ITIT, the energy consumption in terms of the SOC changes for the non-optimal cruise controller was 5% more than that for the MPC-based optimal speed trajectory following.