Estimation of the mean value engine torque using an extended kalman filter

Modern ECUs are usually torque orientated. As a consequence, a good estimation of the real mean value output torque of the engine is needed. As torque measurement is mostly too expensive, the ECUs usually include torque estimation algorithms, which, however, are usually quite simple and give a poor estimate of dynamic effects. In this paper we present a simple but effective method to estimate the engine torque based on an extended Kalman filter used in combination with a polynomial engine model and a simple friction model. Using only standard measurements or ECU internal variables, like fuel mass, spark advance for gasoline engines and injection timing for diesel engines, pressure of the intake manifold and speed are enough to get a good estimation value for the mean value torque of the engine. In this paper we also discuss the algorithm of estimating the mean value torque of the engine that is mounted in a vehicle, where usually the load torque is not known. The resulting engine torque is a dynamical torque signal that can be used as base for several control loops that are implemented in the ECU. The method was tested and implemented on a BMW M47D diesel engine mounted on a dynamical test bench.