Energy-efficient Medium-speed Maglev Train Control Based on Resistance Fitting

Abstract

Compared with traditional rail transit systems with the same transport capacity, the maglev transport has great advantages in terms of safety, energy conservation and environmental protection. Since the maglev train is driven by the electromagnetic force and does not touch the rail when it is running, the form of basic resistance acting on the maglev train is more complex than that of the traditional train. This imposes extra challenges to obtain the energy-efficient control strategies for maglev trains. In this paper, we consider the energy-efficient control problem for medium-speed maglev trains whose basic resistance is a piecewise-quadratic function of train speed. Firstly, the piecewise-quadratic function is approximated as a single quadratic function by using the least square fitting method. Then, by applying control parameterization and time-scaling transformation technique, the traction and braking forces of the maglev train are approximated as piecewise-constant values at each track segment, and the energy-efficient maglev train control problem is transformed into a finite-dimensional optimization problem which is then solved by using the gradient-based sequential quadratic programming (SQP) algorithm. Finally, the effectiveness and performance of the proposed method are demonstrated by two numerical examples. The simulation results show that the proposed algorithm can fit the original resistance function well, and the obtained control strategy based on the fitted resistance results in lower energy consumption with higher computation efficiency.