This article illustrates the use of a virtual vehicle, modelled in MSC Adams/Car, to study and analyse the technique that can be used to extract parameters for handling analysis and subsequently for control purposes. These parameters are usually not available for direct measurement and therefore need to be estimated from other vehicle states. However, presence of process and measurement noise limit the authenticity of these parameters. Kalman filtering algorithm is used as a virtual sensor for noise cancellation and estimation of non-measurable vehicle parameters. This technique uses mathematical model of the plant in conjunction with the system itself to predict the required states. In case of vehicle analysis an experimental vehicle equipped with various sensors is usually used to test and implement the filter; however not all the researchers have direct access to such resources. Therefore this paper describes the possibility of using a virtual vehicle for the purpose.

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