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The trend to reduced development times represents a strong motivation for an extended use of dynamical engine test benches, which are used to reproduce driving conditions typically measured in the vehicle. To reproduce the engine load conditions a complex control system is used, which has an inherently different nature in comparison with the vehicle driving conditions and consequently also limitations. As a consequence, the set of possible transients is limited by the actuator limitations and the bandwidth of the control loops. Outside the admissible transients it is necessary to do a trade-off between goals, mainly between the precision of the reproduction of the engine speed and the precision of the load torque tracking. In this paper we discuss how to calculate the admissible set and how to do a trade off. Based on these cognitions we present a feedforward control algorithm which allows best performance transients simulation along the performance limits.

Torque control is a basic element of engine control systems, in particular since it has become a standard interface for different functionalities. Torque control is also a critical requirement emission test cycle simulation on test benches. This torque control is usually reached by extensive, physical based modeling of the vehicle. This paper presents an approach to avoid this effort and to obtain a dramatic reduction of the parametrization work, by first determining an approximated model and then updating it online during operation. This model is than used for a stable inverse control. To handle model uncertainties and perturbation a correction feedback, with robustifying effect, is added to the control structure. This approach is detailed using data and measurements on a BMW M47D production diesel engine on a dynamic test bench.

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.