Investigating the Effective Parameters on Vehicle Stability and Multi-objective Optimization of its Dynamic Indices

Document Type : Manufacturing and Production

Authors

1 Assistant Professor, Department of Mechanical Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran

2 Corresponding author: Assistant Professor, Department of Mechanical Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran

Abstract

Rollover which causes a large number of deaths and pecuniary damages is one of the basic challenges in vehicle safety. If we can decrease the possibility of rollover in some conditions, probably other important indices are decreased like vehicle stability. It means that some indices are improved through the change of parameters but some of them are not. For this reason, to improve rollover and stability indices simultaneously, combined Topsis-Taguchi and Shannon Entropy methods were used in this paper. First, a whole vehicle as a dynamic model was chosen and to verify the most important parameters, 13 parameters in 3 levels including geometric and volumetric parameters were verified. 27 series of tests through the Taguchi method in Minitab software were prepared and evaluated in Carsim software for obtaining rolling angles and yaw rate around the Z axle. The six most important parameters in the previous level were distinguished and again 25 tests were conducted through the Taguchi method in 5 stages in Carsim Software and multi-objective optimization was conducted. Results showed the suggested method in 80km/h made rollover index, rolling angle, lateral acceleration, and yaw rate around Z axle be decreased as %28.9, %26.2, %0.3, %0.2, respectively. Again, the tests were conducted at different speeds and it was found that with increasing speed, the improvement percentage of all indicators decreases.

Keywords


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[1]https://www.who.int/violence_injury_prevention/key_facts/VIP_key_fact_3.pdf
[2] Mashadi B, Mostaghimi H. Vehicle lift-off modelling and a new rollover detection criterion. Vehicle system dynamics. 2017;55(5):704-24.##
[3] Jin Z, Li J, Huang Y, Khajepour A. Study on rollover index and stability for a triaxle bus. Chinese Journal of Mechanical Engineering. 2019;32(1):1-15.##
[4] Kazemian AH, Fooladi M, Darijani H. Rollover index for the diagnosis of tripped and untripped rollovers. Latin American Journal of Solids and Structures. 2017;14:1979-99.##
[5] Zhu B, Piao Q, Zhao J, Guo L. Integrated chassis control for vehicle rollover prevention with neural network time-to-rollover warning metrics. Advances in Mechanical Engineering. 2016;8(2):1687814016632679.##
[6] Li H, Zhao Y, Wang H, Lin F. Design of an improved predictive LTR for rollover warning systems. Journal of the Brazilian Society of Mechanical Sciences and Engineering. 2017;39(10):3779-91.##
[7] Badiru IA. The three suspension roll centers and their application to vehicle dynamics. SAE Technical Paper; 2014. Report No.: 0148-7191.##
[8] Parida NC, Raha S, Ramani A. Rollover-preventive force synthesis at active suspensions in a vehicle performing a severe maneuver with wheels lifted off. IEEE Transactions on Intelligent Transportation Systems. 2014;15(6):2583-94.##
[9] Ataei M, Khajepour A, Jeon S. Model predictive rollover prevention for steer-by-wire vehicles with a new rollover index. International Journal of Control. 2020;93(1):140-55.##
[10] Saeedi MA. An active non-linear steering control system to increase vehicle lateral stability. Journal of Aerospace Mechanics. 2019;15(3),47-60 (in Persian).##
[11] Elhami MR, Eldar M. Analyzing and Optimizing the Suspension of a Sandy Vehicle: Responding to Standard Inputs. Journal of Aerospace Mechanics. 2005;1(3) (in Persian).##
[12] Jiang R, Wang D. Optimization of suspension system of self-dumping truck using TOPSIS-based Taguchi method coupled with entropy measurement. SAE Technical Paper; 2016. Report No.: 0148-7191.##
[13] Jiang R, Ci S, Liu D, Cheng X, Pan Z. A hybrid multi-objective optimization method based on NSGA-II algorithm and entropy weighted TOPSIS for lightweight design of dump truck carriage. Machines. 2021;9(8):156.##
[14] Gray RM. Entropy and information theory: Springer Science & Business Media; 2011.##
[15] Rath JJ, Defoort M, Veluvolu KC. Rollover index estimation in the presence of sensor faults, unknown inputs, and uncertainties. IEEE transactions on intelligent transportation systems. 2016;17(10):2949-59.##
[16] Huang W, Wong PK, Wong KI, Vong CM, Zhao J. Adaptive neural control of vehicle yaw stability with active front steering using an improved random projection neural network. Vehicle system dynamics. 2021;59(3):396-414.##
 
Volume 18, Issue 2 - Serial Number 68
Serial No. 68, Summer Quarterly
August 2022
Pages 37-50
  • Receive Date: 24 September 2021
  • Revise Date: 18 November 2021
  • Accept Date: 10 January 2022
  • Publish Date: 23 July 2022