Observation problems have been garnering increasing at- tention in recent years. They can be seen as the esti- mation of a periodic output dynamics driven by periodic inputs. At various level of modelling, automotive engine dynamics can be considered as a linear periodic sys- tem mechanically coordinated through the revolution of the crankshaft. In this paper, two practical examples are addressed. The first example is the inversion of sensor dynamics. A classical way of modelling such a sensor is a first order dynamics with periodic excitations which can be, depending on the application, the intake pressure, the intake temperature, the exhaust pressure, the Air Fuel Ra- tio, or the Mass Air Flow. The second example is the es- timation of the engine speed next to the cylinder using as only sensor the easily available instantaneous crankshaft angle speed at the end of the connecting rod. The contribution of this paper is the design of a real-time observer of the periodic excitation of a linear periodic sys- tems by the estimation of the Fourier decomposition of the signal. The estimation of the coefficients of the Fourier basis decomposition of the input periodic excitation is a handy tool for engineering purposes. Indeed, the energy levels of the signal allow another interpretation of the sig- nal and can lead to detect the balance of the engine. This high frequency (6 o crankshaft estimation) information can be used for imbalance diagnosis and torque balance con- trol. Real application observation problems are exposed in their practical context and illustrated by experimental results on a 4 cylinder HCCI engine.
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