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

Author(s):  
Çağlar Uyulan ◽  
Metin Gokasan

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.

Author(s):  
Caglar Uyulan ◽  
Metin Gokasan ◽  
Seta Bogosyan

Excessive driving force applied to the trains leads to an inadequate utilization of the adhesion phenomenon occurred at the wheel–rail contact, and an unnecessary power consumption, while inadequate driving force causes the train to run inefficiently. For this reason, the necessity of re-adhesion control in the safe and reliable operation, in the balance of energy consumption, is indisputable. A comparison of the two re-adhesion control strategies, one of which is robust adaptive and the other of which is the modified super-twisting sliding mode, has been presented in this article. These control algorithms developed suppress the wheel slip on time and maintain optimal traction performance after re-adhesion under the nonlinear properties of the traction system and the uncertainties of the adhesion level at the wheel–rail interface. Due to the complex nonlinear relationship between the adhesion force and the slip angular velocity, such a problem becomes a hard problem to overcome as long as the optimal slip ratio is not known. An optimal search strategy has also been developed to estimate and to track the desired slip angular velocity. By means of the proposed strategies, the traction motor control torque is automatically adjusted so as to ensure that the train operates away from the unstable slip zone but adjacent to the optimal adhesion region, and the desired traction capability is attainable once adhesion is regained. Mathematical analyzes are also provided to ensure the ultimate boundedness of the algorithms developed. The effectiveness of the proposed re-adhesion strategies is validated through the theoretical analysis and numerical simulations conducted in MATLAB and Simulink. As a result of consecutive simulations, modified super-twisting algorithm has shown better performance as compared to the robust adaptive one in tracking the optimal slip velocity as wheel–rail contact conditions switch suddenly.


2015 ◽  
Vol 18 (3) ◽  
pp. 174-182 ◽  
Author(s):  
Minh Ngoc Vu ◽  
Minh Cao Ta

This paper presents a slip suppression controller using sliding mode control method for electric vehicles which aims to improve the control performance of Evs in both driving and braking mode. In this method, a sliding mode controller is designed to obtain the maximum driving force by suppressing the slip ratio. The numerical simulations for one wheel model under variations in mass of vehicle and road condition are performed and demonstrated to show the effectiveness of the proposed method.


2015 ◽  
Vol 2015 ◽  
pp. 1-16
Author(s):  
Yin Zhao ◽  
Ying-kai Xia ◽  
Ying Chen ◽  
Guo-Hua Xu

Underwater vehicle speed control methodology method is the focus of research in this study. Driven by a hydraulic flexible traction system, the underwater vehicle advances steadily on underwater guide rails, simulating an underwater environment for the carried device. Considering the influence of steel rope viscoelasticity and the control system traction structure feature, a mathematical model of the underwater vehicle driven by hydraulic flexible traction system is established. A speed control strategy is then proposed based on the sliding mode variable structure of fuzzy reaching law, according to nonlinearity and external variable load of the vehicle speed control system. Sliding mode variable structure control theory for the nonlinear system allows an improved control effect for movements in “sliding mode” when compared with conventional control. The fuzzy control theory is also introduced, weakening output chattering caused by the sliding mode control switchover while producing high output stability. Matlab mathematical simulation and practical test verification indicate the speed control method as effective in obtaining accurate control results, thus inferring strong practical significance for engineering applications.


Energies ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2501 ◽  
Author(s):  
Jinhong Sun ◽  
Xiangdang Xue ◽  
Ka Wai Eric Cheng

With the development of in-wheel technology (IWT), the design of the electric vehicles (EV) is getting much improved. The anti-lock braking system (ABS), which is a safety benchmark for automotive braking, is particularly important. Installing the braking motor at each fixed position of the wheel improves the intelligent control of each wheel. The nonlinear ABS with robustness performance is highly needed during the vehicle’s braking. The anti-lock braking controller (CAB) designed in this paper considered the well-known adhesion force, the resistance force from air and the wheel rolling friction force, which bring the vehicle model closer to the real situation. A sliding mode wheel slip ratio controller (SMWSC) is proposed to yield anti-lock control of wheels with an adaptive sliding surface. The vehicle dynamics model is established and simulated with consideration of different initial braking velocities, different vehicle masses and different road conditions. By comparing the braking effects with various CAB parameters, including stop distance, braking torque and wheel slip ratio, the SMWSC proposed in this paper has superior fast convergence and stability characteristics. Moreover, this SMWSC also has an added road-detection module, which makes the proposed braking controller more intelligent. In addition, the important brain of this proposed ABS controller is the control algorithm, which can be used in all vehicles’ ABS controller design.


2013 ◽  
Vol 347-350 ◽  
pp. 753-757
Author(s):  
Li Zhou ◽  
Lu Xiong ◽  
Zhuo Ping Yu

This paper proposes a wheel slip control strategy for 4WD Electrical Vehicle with In-wheel Motors. In the first part of this paper, a brief introduction of sliding mode control for acceleration slip regulation is given. Consider that its control effect varies with road conditions, another algorithm which can automatically adapt to different roads is designed. This method takes advantage of the peculiarity of the longitudinal static tire force curve and regulates wheel slip ratio to the detected optimal value, aiming to maximize the traction force while preserving sufficient lateral tire force. Simulation results show that the slip rate can be regulated to a value around the optimal slip ratio, and the driving torque is very close to the maximum transmissible torque. The control strategy achieves stronger stability, shorter driving distance and hence better control performance.


Electric vehicle (EV) are being embraced in recent times as they run on clean fuel, zero tail emission and are environment-friendly. Recent advancements in the field of power electronics and control strategies have made it possible to the advent in the vehicle dynamics, efficiency and range. This paper presents a design for traction control system (TCS) for longitudinal stability and Direct Yaw Control (DYC) for lateral stability simultaneous. The TCS and DYC is based on multiple frequency controlled electronic differential with a simple and effective approach. Along with it, some overviews have been presented on some state of the art in traction control system (TCS) and torque vectoring. The developed technique reduces nonlinearity, multisensory interfacing complexity and response time of the system. This torque and yaw correction strategy can be implemented alongside fuzzy control, sliding mode or neural network based controller. The effectiveness of the control method has been validated using a lightweight neighbourhood electric vehicle as a test platform. The acquired results confirm the versatility of proposed design and can be implemented in any DC motor based TCS/DYC.


Electronics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 185 ◽  
Author(s):  
Grzegorz Tarchała ◽  
Teresa Orłowska-Kowalska

Sliding mode control (SMC) of electric drives constitutes a very popular control method for nonlinear multivariable and time-varying systems, e.g., induction motor (IM) drives. Nowadays, IM are the most popular electrical machines (EM) applied in many industrial applications as motion control devices, including electrical and hybrid vehicles. Nowadays, the control systems of EM are mostly realized using digital techniques (microprocessors and microcontrollers). Therefore, all control algorithms should be discretized or the whole control system should be designed in the discrete-time domain. This paper deals with a discrete-time sliding mode control (DSMC) for IM drives. The discrete algorithms for sliding mode control of the motor speed and rotor flux are derived in detail and next tested in simulation research. The simulation tests include the discrete nature of the power converter supplying the IM and present excellent performance of the developed control structure. To obtain the rotor speed regulation invariant to external disturbances, like load torque or inertia, especially during the reaching phase of the switching line, the discrete version of a time-varying switching line was introduced. It is shown that the assumed dynamics of the IM flux and speed is achieved and the proposed control algorithm can be realized using commonly available microcontrollers. The paper is illustrated with comprehensive simulation results for 1.5 kW IM drive, which are verified by experimental tests.


Author(s):  
Hossine Guermit ◽  
Katia Kouzi ◽  
Sid Ahmed Bessedik

Purpose This paper aims to present a contribution to improve the performance of vector control scheme of double star induction motor drive (DSIM) by using an optimized synergetic control approach. The main advantage of synergetic control is that it supports all parametric and nonparametric uncertainties, which is not the case in several control strategies. Design/methodology/approach The suggested controller is developed based on the synergistic control theory and the particle swarm optimization (PSO) algorithm which allow to obtain the optimal parameter of suggested controller to improve the performance of control system. Findings To show the benefits of proposed controller, a comparative simulation results between conventional PI controller, sliding mode controller and suggested controller were carried out. Originality/value The obtained simulation results illustrate clearly that synergetic controller ensures a rapid response, asymptotic stability of the closed-loop system in the all range operating condition and system robustness in presence of parameter variation in all range of operating conditions.


2013 ◽  
Vol 380-384 ◽  
pp. 485-490
Author(s):  
Jian Zhao ◽  
Jin Zhang ◽  
Bing Zhu

In this paper, the concept of intelligent tire and road surface information measurement methods are introduced, and the sliding mode algorithm for traction control system based on intelligent tire is proposed. By applying braking torque onto the driving wheels, the slip rates are adjusted to maintain within the optimal region on different road surface, and the optimal longitudinal traction is achieved. According to the simulation results on the CARSIM and MATLAB co-simulation platform of several working conditions, the TCS based on sliding mode control method improves the traction performance on different road surface effectively.


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