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The development of one cycle resolution control strategies and the research at HCCI engines demands an accurate estimation of the trapped mass. In contrast to current methods for determining the mass flow, which are only able to determine averaged values of the flow entering the cylinders, the present paper proposes a methodology based on the in-cylinder pressure resonance. The determination of such frequency allows inferring the cylinder mass with one cycle resolution. In addition, the method permits determining error metrics based on the mass conservation principle. Validation results for a reactivity controlled compression ignition (RCCI) engine equipped with electrohydraulic variable valve timing (VVT) are presented to illustrate the performance of the method.

Observers can be used for combining different information sources, as fast models with slow but accurate sensors. For that, a Kalman filter can be used for identifying the bias and cancelling its variation during time. However, normal calibration procedure is iterative and ad-hoc and this does not get optimal results. Furthermore, the lack of enough accurate references make difficult to estimate the best tuning, and more if the calibration pretends to be an online procedure. For solving this, the paper presents a novel calibration method for Kalman filter based on a Monte Carlo analysis, simulating real conditions by means of statistical distributions. This makes possible to create actual references for estimating error metrics of the observer output. A previous sensitivity study is presented for understanding the performance of the algorithm under different conditions.