The effects caused by the cylinder wall temperature variations are nontrivial in advanced combustion mode engine control, particularly in cold-start processes and transients when the combustion mode switches from one to another. Being affected by the engine coolant and operating conditions on a cycle-by-cycle basis, cylinder wall temperature is difficult to be directly measured, and it is typically viewed as an unknown disturbance or estimated as a quasi-static parameter. However, such treatments of the cylinder wall temperature may not be sufficient in sophisticated control of combustion processes. This paper aims to estimate the cylinder wall temperature, on a cycle-by-cycle basis, through cylinder pressure signals in diesel engines. In the proposed methods, the cylinder wall temperature is modeled as a disturbance in the in-cylinder pressure dynamics. Thus, the wall temperature in each cylinder can be estimated, on a cycle-by-cycle basis, by the disturbance observer methods in finite crankshaft angles. Furthermore, to reduce the cylinder wall temperature estimation errors caused by the high-frequency noises in the cylinder pressure signals, a robust disturbance observer is proposed and compared with a typical design method. Through GT-Power engine model simulations and engine experimental results, the observer effectiveness, noise attenuation properties, and applications on a multicylinder diesel engine are evaluated.
Engine Cycle-by-Cycle Cylinder Wall Temperature Observer-Based Estimation Through Cylinder Pressure Signals
Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, and CONTROL. Manuscript received April 15, 2011; final manuscript received February 6, 2012; published online September 26, 2012. Assoc. Editor: John R. Wagner.
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Yan, F., and Wang, J. (September 26, 2012). "Engine Cycle-by-Cycle Cylinder Wall Temperature Observer-Based Estimation Through Cylinder Pressure Signals." ASME. J. Dyn. Sys., Meas., Control. November 2012; 134(6): 061014. https://doi.org/10.1115/1.4006222
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