LPV Identification of a Diesel Engine Torque Model

Abstract

Torque estimation has an increasing importance in the field of automotive control, as most engine controllers rely on torque estimation today. In this paper a new approach based on a linear parameter varying (LPV) model is proposed. It relies on a non linear subspace identification method and exploits the natural dependency of many engine processes on the rotational speed, but does not use a physical model, which is very time consuming and difficult to obtain. To this end, first a LPV state space method is introduced and then experimental results are presented which show that the model exhibits high accuracy.