NICELY NONLINEAR ENGINE TORQUE ESTIMATOR

Abstract

In automotive powertrain control strategy, engine torque estimators are preferred to expensive sensors for obvious economic reasons. In the literature several works have been presented proposing both instantaneous engine torque and mean engine torque estimators. The first ones are based on complex models and tipically are suitable for diagnosis purposes, while the latter estimate the torque by means of static maps. In this work, a nonlinear torque estimator for a spark ignition engine has been developed. The total torque acting at the engine shaft has been obtained solving a tracking problem by means of an LQ control strategy. The novel idea is to reduce the nonlinear engine model to a second order Taylor approximation, named a nicely nonlinear model. It is then linearized via feedback and an LQ controller is designed. This approach has been tested on Mid-Size real time dSPACE simulator showing excellent results both for performance and for computational load.