Application of FRF with SISO and MISO model for accelerometer-based in-cylinder pressure reconstruction on a 9-L diesel engine

Abstract

Engine control with feedback from engine combustion process diagnostics can help improve fuel efficiency and assist in meeting stricter emission regulations. The standard is to use in-cylinder pressure measurements with analysis including rate of heat release. The measurement is usually obtained with intrusive sensors that require a special mounting process and engine structure modification. The potential of the low-cost non-intrusive accelerometer as an alternative means to reconstruct the in-cylinder pressure has been demonstrated by previous investigations. In this work, start of injection (SOI) sweep test conditions at varied speed spanning both low load and high load were conducted on an inline 6-cylinder, 9 L diesel engine. The relationship between the in-cylinder pressure and the accelerometer signal was quantified with frequency response function (FRF). The robustness of the obtained FRF was evaluated by applying the single-test-based FRF to reconstruct the in-cylinder pressures for other test conditions. Two models, single-input single-output (SISO) and multiple-input single-output (MISO), were investigated and compared where the accelerometer signal was taken as the input and in-cylinder pressure as the output. The optimal channel used to acquire the input signal in the SISO model was selected on the basis of coherence analysis. Results show that the MISO model assisted by principal component analysis (PCA) and offset-compensation processes can result in better in-cylinder pressure estimation than the SISO model for conditions with 2200 rpm engine speed. With the purpose of minimizing the cost for accelerometer employment, the minimum number of inputs used to reconstruct the in-cylinder pressure in the MISO model was pursued. Thresholds were set based on three estimated in-cylinder pressure parameters to select the qualified input channels and two input channels were finally determined. Results showed that the two-input single-output FRF model coupled with the PCA and offset-compensation processes improves the FRF’s robustness for the in-cylinder pressure estimation in comparison to the SISO FRF model based on all the tests conducted in this paper.