SYSTEM IDENTIFICATION OF THE CRANKSHAFT DYNAMICS IN A 5 CYLINDER INTERNAL COMBUSTION ENGINE

Future emission regulations for internal combustion engines has lead to an increasing interest in control of the combustion process in order to maximize efficiency while keeping the emission levels at a minimum. One possibility to indirectly measure the combustion process quality is by using a crankshaft mounted torque sensor and use model based signal processing techniques to calculate individual cylinder measures of combustion quality. Since the crankshaft is a flexible device the model must be dynamic. In this contribution we present methodology and results of applying system identification techniques for modeling the crankshaft dynamics. Data is collected from an experimental 5 cylinder spark ignited combustion engine and sampled every 1 degree of the crankshaft revolution. For a fixed engine speed the sampling will be almost identical to time based sampling. Data sets from 7 different engine speeds with static operating conditions are used which results in a data set with 7 different sampling frequencies. A frequency domain approach is adopted to estimate a single parametric continuous time model for all engine speeds. The estimated model is evaluated in two soft sensing applications.