Taguchi Based Grey Relational Analysis Methodology for Semi Active Suspension System Using MR Damper

Abstract

Current automotive companies require improvement in ride comfort with an alternative to suspension system of spring and damper. A good suspension system development is a challenging task to enhance ride comfort and road holding which are conflicting with each other. These two characteristics compromise each other as human beings require a soft ride(comfort) as well as hard ride (good handling). As per literature survey it is observed that, in active and passive suspension system, there is always a compromise between ride comfort and road holding hence there is a scope of development in semi active suspension for ride comfort and road holding. This paper elaborates a methodology for semi active suspension system to achieve optimum value of Ride Comfort. The novelty of this work is that, by experimental work it is observed that the current is a significant parameter of semi active suspension by Grey Taguchi Method and it is validated by acheving rank second for current parameter. To implement semi active suspension system MR (Magneto Rheological) Damper is used. The current controller is developed to vary current from 0.1 to 1A. The relationship between the factors affecting a process and output of that process is determined by design of experiment (DOE) method. In this paper Taguchi Method of DOE is implemented for optimization of ride comfort. Using MINITAB software L8 orthogonal array formulated with the total number of 8 runs. The semi active suspension parameters selected for performance are sprung mass, spring stiffness and current with two levels of each parameter. A Quarter Car test rig equipped with NI 9234 data acquisition system is incorporated with provision of levels of each parameter. The experiment is performed and results are utilized to decide relating values in terms of signal-to-noise (S/N) ratio by selecting lower is better characteristics for each run. These results are further investigated to determine the effect of suspension parameter on ride comfort. With both Grey relational analysis and ANOVA, it is found that the current has a significant influence on suspension system. Moreover, the optimal current parameters setting for maximum ride comfort can be obtained.