Optimised Combinatorial Control Strategy for Active Anti-Roll Bar System for Ground Vehicle

  • Abstract
  • Keywords
  • References
  • PDF
  • Abstract

    The objective of this paper is to optimise the proposed control strategy for an active anti-roll bar system using non-dominated sorting genetic algorithm (NSGA-II) tuning method. By using an active anti-roll control strategy, the controller can adapt to current road conditions and manoeuvres unlike a passive anti-roll bar. The optimisation solution offers a rather noticeable improvement results compared to the manually-tuned method. From the application point of view, both tuning process can be used. However, using optimisation method gives a multiple choice of solutions and provides the optimal parameters compared to manual tuning method.



  • Keywords

    anti-roll bar; ride; handling; control strategy; optimisation.

  • References

      [1] Hac, A. ‘Rollover stability index including effects of suspension design’. SAE Technical Paper, 2002.

      [2] Klein, T.M. ‘A statistical analysis of vehicle rollover propensity and vehicle stability’. SAE Technical Paper, 1992.

      [3] Cooperrider, N.K., Thomas, T.M., Hammoud, S.A. ‘Testing and analysis of vehicle rollover behavior’. SAE Technical Paper, 1990.

      [4] Cimba, D., Wagner, J., Baviskar, A.: ‘Investigation of active torsion bar actuator configurations to reduce vehicle body roll’, Vehicle System Dynamics, 2006, 44(9), 719–736.

      [5] Sampson, D.J., Cebon, D.: ‘Active roll control of single unit heavy road vehicles’, Vehicle System Dynamics, 2003, 40(4), 229–270.

      [6] Gergely, B.: ‘Application of active anti roll bar systems for enchancing yaw stability’, Budapest University of Technology and Economy, 2008.

      [7] Sorniotti, A., D’Alfio, N. ‘Vehicle dynamics simulation to develop an active roll control system’. SAE Technical Paper, 2007.

      [8] Darling, J., Hickson, L.: ‘An experimental study of a prototype active anti-roll suspension system’, Vehicle System Dynamics, 1998, 29(5), 309–329.

      [9] Varga, B., Németh, B., Gáspár, P.: ‘Design of anti-roll bar systems based on hierarchical control’, Strojniški vestnik-Journal of Mechanical Engineering, 2015, 61(6), 374–382.

      [10] Yim, S., Jeon, K., Yi, K.: ‘An investigation into vehicle rollover prevention by coordinated control of active antiroll bar and electronic stability program’, International Journal of Control, Automation and Systems, 2012, 10(2), 275–287.

      [11] Krid, M., Benamar, F. ‘Design and ontrol of an active anti-roll system for a fast rover’. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2011. pp. 274–279.

      [12] Zulkarnain, N., Zamzuri, H., Sam, Y., Mazlan, S., Zainal, S. ‘Improving vehicle ride and handling using lqg cnf fusion control strategy for an active antiroll bar system’. Abstract and Applied Analysis, 2014.

      [13] Zulkarnain, N., Zamzuri, H., Mazlan, S.: ‘Ride and handling analysis for an active anti-roll bar: Case study on composite nonlinear control strategy,’ International Journal of Automotive and Mechanical Engineering, 2014, 10.

      [14] Sharifi, M., Shahriari, B.: ‘Pareto optimisation of vehicle suspension vibration for a nonlinear half-car model using a multi-objective genetic algorithm’, Research Journal of Recent Sciences, 2012, 1(8), 17–22

      [15] Zhou, R., Zolotas, A., Goodall, R. ‘Lqg control for the integrated tilt and active lateral secondary suspension in high speed railway vehicles’. Proceedings of the 8th IEEE International Conference on Control and Automation, 2010, pp. 16–21.

      [16] Zulkarnain, N., Imaduddin, F., Zamzuri, H., Mazlan, S.A. ‘Application of an active anti-roll bar system for enhancing vehicle ride and handling’. Proceedings of the IEEE Colloquium on Humanities, Science and Engineering, 2012, pp. 260–265.

      [17] Zamzuri, H., Zolotas, A.C., Goodall, R.M.: ‘Tilt control design for high-speed trains: a study on multi-objective tuning approaches’, Vehicle System Dynamics, 2008, 46(S1), 535–547.

      [18] Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: ‘A fast and elitist multiobjective genetic algorithm: Nsga-ii’, IEEE Transactions on Evolutionary Computation, 2002, 6(2), 182–197.

      [19] Khajavi, M.N., Notghi, B., Paygane, G.: ‘A multi objective optimisation approach to optimize vehicle ride and handling characteristics’, World Academy of Science, Engineering and Technology, 2010, 62, 580–584.

      [20] Ram, A.S.S.S., Sujatha, C.: ‘Multi objective optimisation of vehicle suspension design’, Proceedings of the 13th International Congress on Sound and Vibration, 2006.

      [21] Djukic, D., Bestle, D. ‘Optimisation of damping characteristics for improved vehicle ride and handling’. Proceedings of 19th International Conference on Computer Methods in Mechanics, 2011.

      [22] Sharifi, M., Shahriari, B., Bagheri, A.: ‘Optimisation of sliding mode control for a vehicle suspension system via multi-objective genetic algorithm with uncertainty’, Journal of Basic and Applied Scientific Research, 2012, 2(7), 6724–6729.

      [23] Ahmed, F., Purdy, D. ‘Controller design of active suspension system with terrain preview using evolutionary multi-objective algorithms’. Proceedings of the International Conference on Soft Computing for Problem Solving, 2012. pp. 865–876.

      [24] Herrero, J., Blasco, X., Martínez, M., Ramos, C., Sanchis, J.: ‘Non-linear robust identification of a greenhouse model using multi-objective evolutionary algorithms’, Biosystems Engineering, 2007, 98(3), 335–346.

      [25] Kannan, S., Baskar, S., McCalley, J.D., Murugan, P.: ‘Application of nsga-ii algorithm to generation expansion planning’, IEEE Transactions on Power Systems, 2009, 24(1), 454–461.




Article ID: 20789
DOI: 10.14419/ijet.v7i4.11.20789

Copyright © 2012-2015 Science Publishing Corporation Inc. All rights reserved.