Study on Intelligent Control Strategy for Semi-Active Suspension System of Tracked Vehicle

Abstract:

Article Preview

Considering the multiple and complicated driving conditions for tracked vehicles and their structural features, a comprehensive intelligent control method to deal with semi-active suspension was proposed based on the principle of magneto rheological damper. One half of the tracked vehicle suspension system is taken as the research object, where analysis is directed to the vertical amplitude, pitch angle and vertical body acceleration response. And the magneto rheological damper was taken as an actuator, the fuzzy control was taken as feedforward and PID control was taken as feedback. The control system model has been established by using of the complex random road output to simulink due to the condition of MATLAB/Simulink. The simulation results show that it is of good real-time control competence, good robustness and high accuracy, etc. Contrasting to passive suspension, some capability parameters such as the body vertical amplitude, pitch angle and the body vertical acceleration of the semi-active suspension system can had been well controlled by using of the intelligent hybrid control method, for exmple, the root mean square value of vertical amplitude decreased by 37.2%,the root mean square value of pitch angle decreased by 45.2% and root mean square value of the vertical vibration acceleration decreased by 38.6%.

Info:

Periodical:

Edited by:

Zhixiang Hou

Pages:

1162-1171

DOI:

10.4028/www.scientific.net/AMM.48-49.1162

Citation:

Y. H. Zeng et al., "Study on Intelligent Control Strategy for Semi-Active Suspension System of Tracked Vehicle", Applied Mechanics and Materials, Vols. 48-49, pp. 1162-1171, 2011

Online since:

February 2011

Export:

Price:

$35.00

[1] Lauwerys C, Swevers J, Sas P. Model Free Control Design fora Semi-active Suspension of a Passenger Car[C]. Pro-ceedings of ISMA, 2004: 75-86.

DOI: 10.1109/acc.2005.1470296

[2] Margolis D L. The Response of Active and Semi—activeSuspension to Realistic Feedback Signals[J]. Vehicle System Dynamics, 1982(11): 267-282.

[3] Tan Bozheng, Li Yinong, Zheng Ling. Armored vehicle semi-active suspension system research, [J]. Railway Locomotive, 2008. 29 (4) : 66-68.

[4] Chen Bing, Gu Liang, Wang Wenrui, Development of intelligent suspension systems for U.S. military vehicles, [J]. Power Technology, 2004. 96 (4), 57-62.

[5] Wang Qimin, Xu Guoliang, Jin Jianfeng. Rheological properties of magnetorheological fluids and its application, [J]. Chinese Mechanical Engineering . 2002, 13 (3) : 267-270.

[6] Ou Jinping, Guan Xinchun Magnetorheological Damper and Its Performance, [J]. Earthquake Engineering and Engineering Vibration, 1998. 18 (3) : 74-80.

[7] Liao Changrong, Zhang Yulin, Chan Weiming, et al. Damper car design and experimental study, [J]. Functional Materials and Devices, 2001, 7 (4) : 350-354.

[8] LI Lifu, Song Jun. Vehicles based on preview of Magnetorheological Semi-active suspension control, [J]. Functional Materials, 2006, 37 (5) : 796-798.

[9] Marzbanrad J , Ahmadi G. Stochastic optimal preview control of a vehicle suspension [J] . Journal of Sound and Vi2bration, 2004, 275: 973-990.

DOI: 10.1016/s0022-460x(03)00812-5

[10] Yu Fan, Guo Konghui. Active suspension of their vehicle wheelbase preview control combined with Kalman filter, [J] Automotive Engineering, 1999, 21 (2) : 72-79.

[11] Liu Shaojun, Li Yan. Preview Control of Active Suspension Research based on 1 / 2 car model, [J]. Information and Control, 2000, 29 (1). 210-217.

[12] Zhuangde Jun, Fan Yu. More vehicle active suspension with preview control algorithm [J]. China Mechanical Engineering, 2006, 17 (12) : 1316-1319.

[13] Zeng Guangqi, Hu Junan. Fuzzy Control Theory and Application, [M]. Wuhan: Huazhong University Press, 2006, we.

[14] Yonghua, Yi Yixin, Ge Lusheng. New PID Control and Its Application, [M]. Beijing: Mechanical Industry Press since. (1998).

[15] Xiong Chao, Zheng Jian, Zhang Jinqiu, et al. Tracked vehicle suspension system modeling and simulation, [J]. Weapons and equipment automation . 2005, 24 (1) : 9-11.

[16] Zhao Heng, Lu Shifu. Road to face four-wheeled vehicles enter the time-domain model, [J]. Automotive Engineering, 1999. 21 (2) : 112-117.

[17] Tan Runhua, Chen Ying, Lu Yongxiang. Establishment of the time-domain model of vehicle incentives and computer simulation with road surface, [J]. China Journal of Highway 1998, 11 (3) : 96-102.

In order to see related information, you need to Login.