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The relationship between ignition, lift-off length and soot formation was investigated for a collection of fuels in an optically-accessible modified 2-stroke engine under a set of typical quasi-steady state Diesel DI conditions. Five fuels including biodiesel blends and Fischer-Tropsch fuels have been selected for their potential to substitute conventional diesel with no major modifications on the engine hardware, and were previously characterized under ambient pressure following ASTM standards. Fuels were injected into a large volume through a single-hole nozzle at three levels of injection pressure, by sweeping ambient temperatures at constant density, and ambient densities at constant temperature. The 8 ms single-shot injections were long enough to reach the stabilization of a free diffusion flame. The OH-chemiluminescence was imaged and lift-off length was measured via image post-processing.

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.