International Journal of Automotive Technology

, Volume 20, Issue 1, pp 51–63 | Cite as

Design and Control of an Automotive Variable Hydraulic Damper Using Cuckoo Search Optimized Pid Method

  • Jing Zhao
  • Pak Kin Wong
  • Zhengchao XieEmail author
  • Xinbo Ma
  • Xingqi Hua


The semi-active suspension (SAS) system has been one of the most attractive topics due to its simplicity and effectiveness in the control of vehicle dynamics. This research proposes a cuckoo search optimized proportional-integral-derivative (CS-PID) strategy for the damping force control of the semi-acive suspension system in order to improve vehicle ride quality. Firstly, a quarter-car suspension model with air spring and variable hydraulic damper (VHD) is developed. By constructing the detailed analytical model and describing the working process, the regulating mechanism and external characteristics of the VHD are presented. Subsequently, the CS-PID strategy is designed to generate the desired damping force according to the vehicle states in real-time, followed with the evaluation of the proposed strategy. Finally, the experimental tests are carried out to verify the accuracy of the VHD model and examine the feasibility of the proposed strategy. The numerical simulation reveal that the proposed control strategy is effective in improving the vehicle performance and the experimental results show that the CS-PID strategy can be successfully implemented in the suspension system for practical use.

Key words

Semi-active vehicle suspension Damper control Cuckoo search optimization PID 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Dash, P., Saikia, L. C. and Sinha, N. (2014). Comparison of performances of several Cuckoo search algorithm based 2DOF controllers in AGC of multi-area thermal system. Int. J. Electrical Power & Energy Systems, 55, 429–436.CrossRefGoogle Scholar
  2. Guo, J., Luo, Y. and Li, K. (2017). An adaptive hierarchical trajectory following control approach of autonomous four-wheel independent drive electric vehicles. IEEE Trans. Intelligent Transporation Systems, 99, 1–11.Google Scholar
  3. Guo, J., Luo, Y. and Li, K. (2018a). Robust gainshceduling automatic steering control of unmanned ground vehicles under velocity-varying motion. Vehicle System Dynamics: Int. J. Vehicle Mechanics and Mobility, DOI: Scholar
  4. Guo, J. H., Luo, Y. G., Li, K. Q. and Dai, Y. F. (2018b). Coordinated path-following and direct yaw-moment control of autonomous electric vehicles with sideslip angle estimation. Mechanical Systems and Signal Processing, 105, 183–199.CrossRefGoogle Scholar
  5. Hu, C., Wang, R., Yan, F., Chadli, M., Huang, Y. and Wang, H. (2017a). Robust path-following control for a fully actuated marine surface vessel with composite nonlinear feedback. Trans. Institute of Measurement and Control, 40, 12, 3477–3488.CrossRefGoogle Scholar
  6. Hu, C., Wang, R. R., Yan, F. J., Huang, Y. J., Wang, H. and Wei, C. F. (2018). Differential steering based yaw stabilization using ISMC for independently actuated electric vehicles. IEEE Trans. Intelligent Transportation Systems, 19, 2, 627–638.CrossRefGoogle Scholar
  7. Hu, Y. L., Chen, M. Z. Q. and Sun, Y. H. (2017b). Comfortoriented vehicle suspension design with skyhook inerter configuration. J. Sound and Vibration, 405, 34–47.CrossRefGoogle Scholar
  8. Huang, W., Wong, P. K., Zhao, J. and Ma, X. B. (2018). Output-feedback model-reference adaptive calibration for map-based anti-jerk control of electromechanical automotive clutches. Int. J. Adaptive Control and Signal Processing, 32, 2, 265–285.MathSciNetCrossRefzbMATHGoogle Scholar
  9. Li, P., Lam, J. and Cheung, K. C. (2017a). H∞ control of periodic piecewise vibration systems with actuator saturation. J. Vibration and Control 23, 20, 3377–3391.MathSciNetCrossRefzbMATHGoogle Scholar
  10. Li, P., Lam, J. and Cheung, K. C. (2017b). Motion-based active disturbance rejection control for a non-linear fullcar suspension system. Proc. Institution of Mechanical Engineers, Part D: J. Automobile Engineering 232, 5, 616–631.Google Scholar
  11. Li, P., Lam, J., Kwok, K. W. and Lu, R. (2018). Stability and stabilization of periodic piecewise linear systems: A matrix polynomial approach. Automatica, 94, 1–8.MathSciNetCrossRefzbMATHGoogle Scholar
  12. Ma, X., Wong, P. K. and Zhao, J. (2018a). Adaptive regulating of automotive mono-tube hydraulic adjustable dampers using grey neural network-based compensation system. Proc. Institution of Mechanical Engineers, Part D: J. Automobile Engineering, In Press.Google Scholar
  13. Ma, X., Wong, P. K. and Zhao, J. (2018b). Practical multiobjective control for automotive semi-active suspension system with nonlinear hydraulic adjustable damper. Mechanical System and Signal Processing, DOI: Scholar
  14. Ma, X. B., Wong, P. K. and Zhao, J. (2018c). Cornering stability control for vehicles with active front steering system using T-S fuzzy based sliding mode control strategy. Mechanical System and Signal Processing, DOI: Scholar
  15. Ma, X. B., Wong, P. K., Zhao, J. and Xie, Z. C. (2017). Multi-objective sliding mode control on vehicle cornering stability with variable gear ratio actuator-based active front steering systems. Sensors, 17, 1, 49.Google Scholar
  16. Metered, H. (2012). Application of nonparametric magnetorheological damper model in vehicle semiactive suspension system. SAE Int. J. Passenger Cars-Mechanical Systems, 5, 1, 715–726.CrossRefGoogle Scholar
  17. Qin, Y., He, C., Shao, X., Du, H., Xiang, C. and Dong, M. (2018a). Vibration mitigation for in-wheel switched reluctance motor driven electric vehicle with dynamic vibration absorbing structures. J. Sound and Vibration, 419, 249–267.CrossRefGoogle Scholar
  18. Qin, Y., Xiang, C., Wang, Z. and Dong, M. (2018b). Classification for semi-active suspension system based on system response. J. Vibration and Control, 24, 13, 2732–2748.CrossRefGoogle Scholar
  19. Qin, Y., Zhao, F., Wang, Z., Gu, L. and Dong, M. (2017a). Comprehensive analysis for influence of controllable damper time delay on semi-active suspension control strategies. J. Vibration and Acoustics 139, 3, 031006xxx1–031006xxx12.CrossRefGoogle Scholar
  20. Qin, Y. C., Langari, R., Wang, Z. F., Xiang, C. L. and Dong, M. M. (2017b). Road excitation classification for semi-active suspension system with deep neural networks. J. Intelligent & Fuzzy Systems 33, 3, 1907–1918.CrossRefGoogle Scholar
  21. Sun, S., Deng, H., Du, H., Li, W., Yang, J., Liu, G., Alici, G. and Yan, T. (2015a). A compact variable stiffness and damping shock absorber for vehicle suspension. IEEE/ASME Trans. Mechatronics 20, 5, 2621–2629.CrossRefGoogle Scholar
  22. Sun, S., Ning, D., Yang, J., Du, H., Zhang, S. and Li, W. (2016). A seat suspension with a rotary magnetorheological damper for heavy duty vehicles. Smart Materials and Structures 25, 10, 105032.CrossRefGoogle Scholar
  23. Sun, S., Ning, D., Yang, J., Du, H., Zhang, S., Li, W. and Nakano, M. (2017a). Development of an MR seat suspension with self-powered generation capability. Smart Materials and Structures, 26, 8, 085025.CrossRefGoogle Scholar
  24. Sun, S., Yang, J., Li, W., Deng, H., Du, H. and Alici, G. (2015b). Development of a novel variable stiffness and damping magnetorheological fluid damper. Smart Materials and Structures 24, 8, 085021.CrossRefGoogle Scholar
  25. Sun, X. Q., Yuan, C. C., Cai, Y. F., Wang, S. H. and Chen, L. (2017b). Model predictive control of an air suspension system with damping multi-mode switching damper based on hybrid model. Mechanical Systems and Signal Processing, 94, 94–110.CrossRefGoogle Scholar
  26. Wei, C., Zhang, K., Hu, C., Wang, Y., Taghavifar, H. and Jing, X. (2018). A tunable nonlinear vibrational energy harvesting system with scissor-like structure. Mechanical Systems and Signal Processing, DOI: Scholar
  27. Wong, P. K., Wong, K. I., Vong, C. M. and Cheung, C. S. (2015). Modeling and optimization of biodiesel engine performance using kernel-based extreme learning machine and cuckoo search. Renewable Energy, 74, 640–647.CrossRefGoogle Scholar
  28. Wong, P. K., Xie, Z., Zhao, J., Xu, T. and He, F. (2014). Analysis of automotive rolling lobe air spring under alternative factors with finite element model. J. Mechanical Science and Technology 28, 12, 5069–5081.CrossRefGoogle Scholar
  29. Xie, Z., Wong, P. K., Zhao, J., Xu, T., Wong, K. I. and Wong, H. C. (2013). A noise-insensitive semi-active air suspension for heavy-duty vehicles with an integrated fuzzy-wheelbase preview control. Mathematical Problems in Engineering, 2013, Article ID 121953.Google Scholar
  30. Xie, Z. C., Wong, P. K., Zhao, J. and Xu, T. (2015). Design of a denoising hybrid fuzzy-pid controller for active suspension systems of heavy vehicles based on model adaptive wheelbase preview strategy. J. Vibroengineering 17, 2, 883–904.Google Scholar
  31. Xu, X., Wang, W., Zou, N. N., Chen, L. and Cui, X. L. (2017). A comparative study of sensor fault diagnosis methods based on observer for ECAS system. Mechanical Systems and Signal Processing 87, Part B, 169–183.CrossRefGoogle Scholar
  32. Yang, X.-S. and Deb, S. (2014). Cuckoo search: Recent advances and applications. Neural Computing and Applications 24, 1, 169–174.CrossRefGoogle Scholar
  33. Zhao, J., Wong, P. K., Ma, X. and Xie, Z. (2017a). Chassis integrated control for active suspension, active front steering and direct yaw moment systems using hierarchical strategy. Vehicle System Dynamics: Int. J. Vehicle Mechanics and Mobility 55, 1, 72–103.CrossRefGoogle Scholar
  34. Zhao, J., Wong, P. K., Ma, X. and Xie, Z. (2018a). Design and analysis of an integrated sliding mode control-two-point wheelbase preview strategy for asemi-active air suspension with stepper motor-driven gas-filled adjustable shock absorber. Proc. Institution of Mechanical Engineers, Part I: J. Systems and Control Engineering, DOI: Scholar
  35. Zhao, J., Wong, P. K., Xie, Z. C. and Ma, X. B. (2017b). Cuckoo search-based intelligent control of a novel variable rotary valve system for engines using PID controller. J. Intelligent & Fuzzy Systems 32, 3, 2351–2363.CrossRefGoogle Scholar
  36. Zhao, J., Wong, P. K., Xie, Z. C., Ma, X. B. and Wei, C. Y. (2016a). Design of a road friendly SAS system for heavy-duty vehicles based on a fuzzy-hybrid-ADD and GH-control Strategy. Shock and Vibration, 2016, DOI: Scholar
  37. Zhao, J., Wong, P. K., Xie, Z. C., Wei, C. Y. and Zhao, R. C. (2016b). Design and evaluation of a ride comfort based suspension system using an optimal stiffnessdetermination method. Trans. Canadian Society for Mechanical Engineering 40, 5, 773–785.CrossRefGoogle Scholar
  38. Zhao, R. C., Wong, P. K., Xie, Z. C. and Zhao, J. (2017c). Real-time weighted multi-objective model predictive controller for adaptive cruise control systems. Int. J. Automotive Technology 18, 2, 279–292.CrossRefGoogle Scholar
  39. Zhao, W., Fan, M. and Wang, C. (2019). H∞/extension stability control of automotive active front steering system. Mechanical Systems and Signal Processing, 115, 621–636.CrossRefGoogle Scholar
  40. Zhao, W., Qin, X. and Wang, C. (2018b). Yaw and lateral stability control of automotive four-wheel steer-by-wire system. IEEE/ASME Trans. Mechatronics, Doi: 10.1109/TMECH.2018.2812220.Google Scholar
  41. Zhao, W., Zhang, H. and Li, Y. (2018c). Displacement and force coupling control design for automotive active front steering system. Mechanical Systems and Signal Processing, 106, 76–93.CrossRefGoogle Scholar

Copyright information

© The Korean Society of Automotive Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Jing Zhao
    • 1
    • 2
  • Pak Kin Wong
    • 2
  • Zhengchao Xie
    • 3
    Email author
  • Xinbo Ma
    • 1
    • 2
  • Xingqi Hua
    • 1
  1. 1.School of Electromechanical EngineeringGuangdong University of TechnologyGuangzhouChina
  2. 2.Department of Electromechanical EngineeringUniversity of MacauTaipaMacau
  3. 3.School of Mechanical and Automotive EngineeringSouth China University of TechnologyGuangzhouChina

Personalised recommendations