Model Analysis of Motorcycle Suspension System Using the Fourth Order of Runge-Kutta Method

Umi Nurofi'atin, Agus Maman Abadi
2018 Eksakta: Jurnal Ilmu-Ilmu MIPA  
The suspension system is part of motorcycle that serves to absorb vibration and shocks of the road surface so as to improve the safety and comfort while driving. Motorcycle typically use double shockbreaker system which analogous to a two-spring system arranged in parallel. The aim of this researh is to analyze the model of the model of double shockbreaker motorcycle suspension system that working without outside force using passive suspension system. The data used are from damper tester
more » ... ent, then model analyzed using analytical method and the fourth order of numerical Runge-Kutta method. This research use shockbreaker observation datas that is the measurment data of spring constant and damping constant by performing damper tester using 4 different loads. The process model analysis using Matlab R2013a. Input variables are spring constant, damping constant, and the mass of the load. Methods of analysis using analytical method and the fourth order of Runge-Kutta method. While the resulting outputs are 2 spring constants, change the length of the spring, damping ratio, the optimal damping of the suspension, and the spring deflection chart against time. This model motorcycle suspension system uses solution of differential equations for the under damped suspension condition, that is the suspension system will be insulated a few moments before reaching the equilibrium position. Therefore, the resulting damping rate of the motorcycle is not optimal yet. This study found the optimal damping for each model of the suspension system. The level of accuracy of the fourth order of runge-kutta method for model analysis of the suspension system is quite high with error <0.1 and the timing of analysis is faster than the analytic method. Future research may use other methods or other input variables for more accurate analysis results.
doi:10.20885/eksakta.vol18.iss2.art3 fatcat:y5nit5b5tbh5bjj6ugyaowotk4