A Study on Vehicle Suspension Loads Prediction Method Based on Hybrid Road Simulation using Modelica Library and FMI

Abstract

This study presents a method for predicting vehiclesuspension component loads at the early design stage. Ahybrid road simulation combines road load data acquiredfrom a reference vehicle with the Time Waveform Replication(TWR) technique to generate virtual equivalent roadprofiles. The TWR was implemented in Python, and amultibody dynamics vehicle model developed using Modelon'sVehicle Dynamics Library was used to simulate chassisresponse. Integration and iterative simulation between theTWR system and the vehicle model were conducted viaFunctional Mock-up Units using the Python FMI library,FMPy. These virtual inputs were applied to a virtual testrig. In this study, road load data from a reference vehiclewere used to derive the input signals, which were thenapplied to simulate the suspension loads of a targetvehicle. Simulation results were validated againstmeasurement data to confirm the effectiveness of theproposed method.