Modeling, simulation and re-adhesion control of an induction motor–based railway electric traction system

Abstract

Increasing the traction force is a complex problem in the design of railway vehicles; therefore, effective traction systems and algorithms have to be developed. During the traction process, the verification of traction algorithms and control strategies are based on simulations covering all locomotive dynamics. In this article, traction model of a railway vehicle and re-adhesion control method based on simulation approach are investigated to obtain more effective results. The longitudinal dynamic of a railway vehicle having traction system, which comprises two parallel motor groups, each of which has two field-oriented induction motor connected in series, is simulated to examine time-dependent changes in motor stator currents, traction torque, adhesion and resistance forces according to a given speed reference. The interaction between the adhesion force and the slip ratio is established according to the Burckhardt adhesion model, and a modified super-twisting sliding mode slip control is implemented in a computer simulation under various contact conditions so that simulation results approve the presented control method works under the maximum adhesion force. The comparison between the classical and modified version of the proposed control strategy was made to better evaluate the performance of the control system and to better optimize the traction system.

A Critical Review on Traction Control System

“…The motorist can prevent pruning upward, cutting back this blossom valve commanding the accelerator's introduction. Within this instance, the wheel is slightly closer into this center of this flex related for the wheel that's moving speedier and increasingly much by your center of this bend [7,8]. Inside this scenario, the motorist may lose this motorcycle's constraint.…”

Fuzzy control system design for wheel slip prevention and tracking of desired speed profile in electric trains

“…To evaluate the proposed fuzzy control system, a super-twisting sliding mode control (StSMC) [3] has been used. The simulation results for the dry wheel-rail surface have been shown in Figure 9.…”

“…The second step is developing and implementing the appropriate control systems in traction and braking systems to track the desired speed profile in the acceleration, cruising, and braking modes. It is evident that tracking the desired speed profile and obtaining the maximum acceleration without controlling the adhesion force between the wheel and rail is not possible [2], [3]. Automatic train operation (ATO) system generally consists of two main parts, (i) generating the optimal speed profile and (ii) tracking strategy to track the optimal speed profile [4], [5], [6].…”

Freight Train Speed Active Disturbance Rejection Tracking and Wheel Anti-slip Based on T-S Fuzzy Neural Network

“…Velocity tracking research can be divided into two parts: [4] only considering speed tracking control, ignoring other factors; [5][6][7] considering the impact of wheel slipping when performing speed tracking control. [4,[8][9][10][11][12][13] Wheel slipping will cause a deviation in the speed between the train and the wheel. In severe cases, the train will derail.…”

“…An improved ultra-twist sliding mode control was implemented by Uyulan and Gokasan. [10] This control used the Burckhardt adhesion model to achieve maximum adhesion tracking. Its effectiveness was demonstrated in the longitudinal dynamic model of the train.…”