Optimal lumped parameters estimation of vehicle passive suspension system using genetic algorithm

H. El-taweel, Mohamed M. Abd elhafiz, H. Metered


In this paper, optimal lumped vehicle passive suspension parameters are estimated using genetic algorithm (GA) to decrease vibration levels of the vehicle body and passenger seat so that better ride comfort and vehicle stability are achieved. The optimal values of suspension parameters for minimizing a combined multi-objective function are tuned using GA due to its simplicity, convergence, and robustness. The equations of motion of five-degrees-of-freedom passive half-vehicle suspension system are derived and simulated using Matlab/Simulink software. Double bumps and random road excitations are used to study the performance of the suspension system including bounce and pitch motion. The performance of the optimized passive suspension system using optimal lumped parameters is compared with the nominal passive to show the efficiency of the proposed optimized suspension system. The simulation results prove that the optimized passive suspension system using GA can offer significant improvements of ride comfort and vehicle stability.

Full Text:



‎[1]‎ H. Metered. Modeling and control of ‎magnetorheological dampers for vehicle suspension ‎systems. PhD Thesis, Department of mechanical, ‎aerospace and civil engineering, Manchester, ‎UK, 2010.‎

‎[2]‎ Gillespie, T. D. Fundamentals of Vehicle Dynamics. ‎Society of Automotive Engineers, Warrendale, PA, ‎USA, 1992.‎

‎[3]‎ L. R. C. Drehmera, W. J. P. Casasa & H. M. Gomesa. ‎Parameters optimization of a vehicle suspension ‎system using a particle swarm optimization algorithm. ‎Vehicle System Dynamics 2015; 53: 449-474.‎

‎[4]‎ Wong, J.Y. Theory of Ground Vehicles. 4th ed., ‎John Wiley & Sons, Inc., Hoboken, NJ, 2008.‎

‎[5]‎ S. Gad, H. Metered, A. Bassuiny & AM Abdel ‎Ghany. Multi-objective genetic algorithm fractional-‎order PID controller for semi-active ‎magnetorheologically damped seat suspension. ‎Jounal of Vibration and Control 2017; 23: 1248-‎‎1266‎

‎[6]‎ G¨undo˘gdu, O¨. Optimal seat and suspension design ‎for a quarter car with driver model using genetic algo-‎rithms. International Journal of Industrial Ergonom-‎ics 2007; 37(4): 327–332.‎

‎[7]‎ T. M. Farid, A. Salah, A. and W. Abbas. Design of ‎optimal linear suspension for quarter car with human ‎model using genetic algorithms. Journal of Applied ‎Sciences Research 2011; 7(11): 1709–1720.‎

‎[8]‎ Likaj, R., Shala, A., Bruqi, M. and Qelaj, M. Optimal ‎design of quarter car vehicle suspension system.14th ‎International Research/Expert Conference, 2010.‎

‎[9]‎ R. K. S Gupta, V. Sonawane, &D. S. S. Sudhakar. ‎Optimization of vehicle suspension system using ‎genetic algorithm, International Journal of ‎Mechanical Engineering and Technology 2015; 6(2): ‎‎47–55.‎

‎[10]‎ Nariman-Zadeh, N., Salehpour, M., Jamali, A., & ‎Haghgoo E. Pareto. Optimization of a five-Degree of ‎Freedom Vehicle Vibration Model Using a Multi-‎Objective Uniform-Diversity Genetic Algorithm ‎‎(MUGA). Engineering Applications of Artificial ‎Intelligence 2010; 23: 543-551.‎

‎[11]‎ H. El-taweel, Mohamed M. Abd elhafiz, & H. ‎Metered. Vibration control of active vehicle ‎suspension system using optimized fuzzy-PID. SAE ‎Technical Paper 2018; 2018-01-1402. ‎

‎[12]‎ H. Metered, A. Elsawaf, T. Vampola, & Z. Sika. ‎Vibration Control of MR-Damped Vehicle ‎Suspension System Using PID Controller Tuned by ‎Particle Swarm Optimization, SAE International ‎Journal of Passenger Cars - Mechanical Systems ‎‎2015; 8(2):426-435‎

‎[13]‎ H. Metered, W. Abbas & AS Emam. Optimized Pro-‎portional Integral Derivative Controller of Vehicle ‎Active Suspension System using Genetic Algorithm. ‎SAE Technical Paper 2018; 2018-01-1399‎

‎[14]‎ Daskupta, D. and McGregor, D.R. Engineering ‎optimization using structured genetic algorithm. John ‎Wiley & Sons, Chichester, Vienna, Austria 1992; ‎‎876p.‎

‎[15]‎ Rajamani, R. Vehicle Dynamics and Control. ‎Springer Science & Business Media, New York, ‎USA, 2006.‎


  • There are currently no refbacks.