Development of Extended MVEM based UKF estimators

Abstract

Mean Value Engine Models (MVEM) have been used to model the averaged dynamics of an automobile engine system for automotive control and fault diagnosis. For these purposes, it is common to estimate states of interest given noisy measurements using state observers. Since the measurements could be noisy and asynchronous, they should be suitably post-processed before feeding them to a state observer. In this paper, an Unscented Kalman Filter (UKF) was developed for an Extended MVEM and a suitable post-processing algorithm for the measurements has been described.