차량 현가장치 성능향상을 위한 댐퍼 최적화 설계에 대한 연구

A Study on the Optimization Design of Damper for the Improvement of Vehicle Suspension Performance

Abstract

A damper is a hydraulic device designed to absorb or eliminate shock impulses which is acting on the sprung mass of vehicle. It converting the kinetic energy of the shock into another form of energy, typically heat. In a vehicle, a damper reduce vibration of car, leading to improved ride comfort and running stability. Therefore, a damper is one of the most important components in a vehicle suspension system. Conventionally, the design process of vehicle suspensions has been based on trial and error approaches, where designers iteratively change the values of the design variables and reanalyze the system until acceptable design criteria are achieved. Therefore, the ability to tune a damper properly without trial and error is of great interest in suspension system design to reduce time and effort. For this reason, a many previous researches have been done on modeling and simulation of the damper. In this paper, we have conducted optimal design process to find optimal design parameters of damping force which minimize a acceleration of sprung mass for a given suspension system using genetic algorithm.

Fig. 1 Configuration of suspension system

Fig. 2 Cross section of automotive damper

Fig. 3 Simulation model of the automotive suspension system for the optimization

Fig. 4 Simulation result of vehicle performance with initial design parameters

Fig. 5 Flowchart of genetic algorithm calculation procedure

Fig. 6 Simulation parameters of optimization design

Fig. 7 History plot of objective function and constraint

Fig. 8 Scatter plot of maximum acceleration with P-Q gradient

Fig. 9 Scatter plot of maximum acceleration with minimum deflection of tire

Fig. 10 Simulation log file and best solutions

Fig. 11 Comparison of vehicle performances for the initial and optimized design

Fig. 12 Sinusoidal input signal for the frequency analysis

Fig. 13 Frequency response of sprung mass acceleration

Table 1 Initial design parameters

Table 2 Optimization simulation parameters and conditions for genetic algorithm