Cylinder pressure reconstruction to compensate for crankshaft flexibility based on flexible crank model

Abstract

Amid escalating economic demands and emissions regulations for internal combustion engines, an array of control strategies grounded in in-cylinder state feedback has been introduced and implemented. The exploration of cylinder state feedback has captured the attention of researchers, and one area of intense focus involves reconstructing cylinder pressure based on engine state information due to its cost-effectiveness. In this paper, we introduce a method for compensating crankshaft flexibility. This method encompasses a crankshaft dynamic model, a 17-dimensional input vector, the PCA (Principal Component Analysis) algorithm, and a signal-layer perceptron. This approach efficiently addresses the impact of flexible crankshaft deformation and ensures high accuracy. The results demonstrate that all R2 values for cylinder pressure signals reconstructed via the proposed method exceed 0.9997, with RMSE predominantly ranging between 0.4 and 0.6 bar. Furthermore, the error in Pmax calculation based on cylinder pressure signals is under 0.04 bar, LPP (Location of Peak Pressure) error is below 2°CA, CA50 error remains under 0.5°CA, and IMEPH error is within 0.3 bar. In summation, the presented method facilitates highly precise in-cylinder pressure reconstruction, satisfies the prerequisites for in-cylinder combustion state feedback.