Cycle-by-cycle estimation of cylinder pressure and indicated torque waveform using crankshaft speed fluctuations

Abstract

In this work, frequency response functions (FRFs) are used for estimation of cycle-by-cycle cylinder pressure and indicated torque waveform, using crankshaft speed fluctuations. The FRFs are mapped as a function of the discrete Fourier transform of engine speed, mean speed and manifold pressure using a multilayer neural network. The accuracy of the model is analysed using some of the parameters derived from the cylinder pressure. These include the indicated mean effective pressure and peak pressure. The load torque on the engine is also estimated using a closed-loop observer. The model is tested on a test rig consisting of single-cylinder engine coupled with an eddy current dynamometer. The results show that the model is suitable for the estimation of cylinder pressure and other variables related to it at the operating points where the cyclic variations are within a driveability limit.

A comparison of sliding mode and FRF-based observers for cylinder pressure estimation of spark ignition engine

“…where p ( θ ) , p man , A p and ds ( θ ) d θ are cylinder pressure, manifold pressure, piston head surface area and the piston stroke derivative, respectively. Furthermore, frictional torque is estimated by using the regression fit on experimental data (Ali and Saraswati, 2015).…”

“…In contrast to this, many methods are proposed in the literature where cylinder pressure is estimated indirectly by using crankshaft speed measurements (Bizon et al, 2014; Liu et al, 2012; Taglealatela et al, 2013). Of these methods, frequency analysis (Ali and Saraswati, 2015; Azzoni et al, 1999; Jia et al, 2014; Lee et al, 2001) and sliding mode observer (SMO) (Chen and Moskwa, 1997; Haskara and Mianzo, 2001; Kao and Moskwa, 1995; Shiao and Moskwa, 1995) are widely used.…”

“…The frequency analysis method (Ali and Saraswati, 2015; Azzoni et al, 1999; Jia et al, 2014; Lee et al, 2001) is based on the principle that the first few harmonics of engine speed carry enough information to determine the cylinder pressure. The inverse of frequency response function (FRF) between the crankshaft speed and cylinder pressure is precomputed.…”

“…Furthermore, it requires pre-computation and mapping of FRFs in the complete operating domain of the engine. As FRFs are calculated using the averaged cycle data, the results are significantly affected by an increase in cycle-by-cycle variations (Ali and Saraswati, 2015).…”

“…The accuracy of estimation is tested using the two combustion indicators, namely the peak pressure (PP) and the indicated mean effective pressure (IMEP). The results of the observer are compared with the results of the FRF model (Ali and Saraswati, 2015) at three operating conditions. It is shown that the averaged relative error, using SMO, for PP and IMEP is reduced for all the test conditions in comparison with the cylinder pressure estimation using FRF.…”