Home|News|Literature|Journal|Instruction|Forum|Member|Introduction

Chinese  Old version

By    In    Search 

  HomeContents of Chinese Journal of Mechanical Engineering,2012 No.3 Antiskid Control of Railway Train Braking Based on Adhesion Creep Behavior

DOI:, available online at www.cjmenet.com; www.cjmenet.com.cn

Antiskid Control of Railway Train Braking Based on Adhesion Creep Behavior


ZUO Jianyong* and CHEN Zhongkai
Railway and Urban Rail Traffic Academy, Tongji University, Shanghai 200092, China

Received March 3, 2011; revised November 29, 2011; accepted December 12, 2011


Abstract: In modern trains wheelset skidding leads to the deterioration of braking behavior, the degradation of comfort, as well as a boost in system hazards. Because of the nonlinearity and unknown characteristics of wheelset adhesion, simplifications are widely adopted in the modeling process of conventional antiskid controllers. Therefore, conventional antiskid controllers usually cannot perform satisfactorily. In this paper, systematic computer simulation and field tests for railway antiskid control system are introduced. The operating principal of antiskid control system is explained, which is fundamental to the simulation of antiskid brakes, and the simulation model is introduced, which incorporates both the adhesion creep curve and a pneumatic submodel of antiskid control system. In addition, the characteristics of adhesion curves and the simulation target are also provided. Using DHSplus, the pneumatic submodel is created to analyze the performance of the different control strategies of antiskid valves. Then the system simulation is realized by combining the kinematical characteristics of railway trains and the pneumatic submodel. The simulation is performed iteratively to obtain the optimized design of the antiskid control system. The design result is incorporated in the hardware design of the antiskid control system and is evaluated in the field tests in Shanghai Subway Line 1. Judging by the antiskid efficiency, the antiskid braking performance observed in the field tests shows the superiority of the optimized design. Therefore, the proposed simulation method, especially in view of its ease of application, appears to be a useful one for designing railway antiskid control systems.

Key words: antiskid control, adhesion creep, railway train braking, system simulation.

 


* Corresponding author. E-mail: zuojy@tongji.edu.cn
This project is supported by National Natural Science Foundation of China (Grant No. 61004077), National Key Technology R&D Program of the 11th Five Year Plan of China (Grant No. 2009BAG11B02), and Foundation of Traction Power State Key Laboratory of Southwest Jiaotong University, China (Grant No. TPL1107)
© Chinese Mechanical Engineering Society and Springer-Verlag Berlin Heidelberg 2012
 

Open or Download Full Text of this Paper (PDF File)

 

Biographical notes
ZUO Jianyong, born in 1976, is currently a lecturer at Railway and Urban Rail Traffic Academy, Tongii University, China. He received his PhD degree from Shanghai Jiaotong University, China, in 2005. His research interests include simulation and control of trains’ brake system.
Tel: +86-21-69584712; E-mail: zuojy@tongji.edu.cn

CHEN Zhongkai, born in 1987, is currently a MS candidate at Railway and Urban Rail Traffic Academy, Tongji University, China. He received his bachelor degree from Tongji University, China, in 2009. His research interests cover artificial intelligence and control theory.
Tel: +86-21-69584712; E-mail: craigknox@126.com
 

References


[1] LUO Ren, ZENG Jing. Antiskid control simulation of railway vehicle braking[J]. Chinese Journal of Mechanical Engineering, 2008, 44(3): 29–34.

[2] TABO T, OHKA N, KURAOKA H, et al. Automotive antiskid system using modern control theory[J]. Proc. IEEE IECON’85, 1985, 15(3): 390–395.
[3] BRANCO P J C, DENTE J A. An experiment in automatic modeling an electric drive system using fuzzy logic[J]. IEEE Transactions on Systems, Man, and Cybernetics, 1998, 27(2): 254–262.
[4] CHEOK A D, SHIOMI S. Combined heuristic knowledge and limited measurement based fuzzy logic antiskid control for railway applications[J]. IEEE Transactions on Systems, Man, and Cybernetics, 2000, 30(4): 557–567.

[5] REN Lihui, PEI Yuchun, ZUO Jianyong, et al. Modeling and simulation of pneumatic relay valves[C]//The first Sino-Japanese Workshop on Train Braking Press, Tongji University, Shanghai, China, 2008: 75–88.
[6] FLING R, FENTON R. A describing-function approach to antiskid design[J]. IEEE Transactions on Vehicular Technology, 1981, 30(3): 134–144.

[7] HASEGAWA I, NORIMICHI K, YAMAZAKI H. Adhesion force between rail and wheel in wheel skidding on railway rolling stocks and its effective use[C]//Jpn. Mach. Assoc. Trans., Tokyo, Japan, 1994: 245–250.
[8] ZHANG Zhiwei, WU Zhongyou, LIU Fuchun, et al. Study of the hydraulic system simulation and PID auto tuning based on relay feedback of the tantalum-niobium tube straightener[C]// Proceedings of the 2010 5th IEEE Conference on Industrial Electronics and Applications, Taiwan, China, 2010: 1 253–1 257.
[9] GAUCHEL W, SCHELL R. Control of a servo-pneumatic gripper with individually movable jaws[C]//IEEE Conference on Control Applications, Munich, Germany, 2006: 802–806.
[10] GENG Zhixiu, LI Xuefeng, ZHANG Bo. Simulation study of heavy haul train operation on Datong-Qinghuangdao railway[J]. Chinese Railway Science, 2008(2): 88–93.
[11] WICKENS A H. Fundamentals of rail vehicle dynamics: guidance and stability[M]. Amsterdam, Holand: Swets & Zeitlinger Publisher, 2003.
[12] HANMIN L, GILDONG K, SUNGHWAN P. A study on optimal braking control using adhesion coefficient[C]//The 7th International Conference on Power Electronics, Daegu, South Korea, 2007: 343–346.
[13] AHN K, YOKOTA S. Intelligent switching control of pneumatic actuator using on/off solenoid valves[J]. Mechatroincs, 2005, 15(6): 683–702.

[14] WANG Haoxun, XIAO Jun, MO Yimin, Train’s vertical impulse analyzer based on virtual instruments and ARM[J]. Instrument Technique and Sensor, 2007(11): 13–14.
[15] ZHANG J Z, CHEN X, ZHANG P J. Integrated control of braking energy regeneration and pneumatic anti-lock braking[J]. Journal of Mechanical Engineering Science, Part D: J. Automobile Engineering, 2010, 224: 587–610.

[16] KAITWANIDVILAI S, PARNICHKUN M. Force control in a pneumatic system using hybrid adaptive neuro-fuzzy model reference control[J]. Mechatroincs, 2005, 15(1): 23–41.

[17] SHIH M C, MA M A. Position control of a pneumatic cylinder using fuzzy PWM control method[J]. Mechatronics, 1998, 8(3): 241–253.

[18] MESSINA A, GIANNOCCARO N I, GENTILE A. Experimenting and modeling the dynamics of pneumatic actuators controlled by the pulse width modulation (PWM) technique[J]. Mechatroincs, 2005, 15(7): 859–881.




  About us-Contact us-Site map-Advertisement service-Cooperation-Legal statement  

Address: 22 Baiwanzhuang Dajie, Beijing 100037 China    Tel: 8610-88379907    Fax: 8610-68994557

E-mail: cjme@mail.machineinfo.gov.cn  http: //www.cjmenet.com
©2006 Editorial Office of CJME. All Right Reserved