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research-article

Hybrid State Space Modelling of an SI Engine for Online Fault Diagnosis

[+] Author and Article Information
Nadeer E.P

Advanced Technology Development Centre (ATDC), Indian Institute of Technology, Kharagpur, West Bengal, 721302, India
epnadeer@iitkgp.ac.in

Amit Patra

Department of Electrical Engineering, Indian Institute of Technology, Kharagpur, West Bengal, 721302, India
amit@ee.iitkgp.ernet.in

Siddhartha Mukhopadhyay

Department of Electrical Engineering, Indian Institute of Technology, Kharagpur, West Bengal, 721302, India
smukh@ee.iitkgp.ernet.in

1Corresponding author.

ASME doi:10.1115/1.4038164 History: Received March 21, 2016; Revised September 30, 2017

Abstract

In this work, a nonlinear hybrid state space model of a complete spark ignition (SI) gasoline engine system from throttle to muffler is developed using the mass and energy balance equations. It provides within-cycle dynamics of all the engine variables such as temperature, pressure and mass of individual gas species in the intake manifold, cylinder and exhaust manifold. The inputs to the model are same as that are commonly exercised by the Engine Control Unit (ECU) and its outputs correspond to available engine sensors. It uses generally known engine parameters, does not require extensive engine maps found in mean value models and requires minimal experimentation for tuning. It is demonstrated that the model is able to capture a variety of engine faults by suitable parameterization. The state space modelling is parsimonious in having the minimum number of integrators in the model by appropriate choice of state. It leads to great computational efficiency due to the possibility of deriving the Jacobian expressions analytically in applications such as on-board state estimation. The model was validated both with data from an industry standard engine simulator and those from an actual engine after relevant modifications. For the test engine, the engine speed and crank-angle were extracted from the crank position sensor signal. The model was seen to match the true values of engine variables both in simulation and experiments.

Copyright (c) 2017 by ASME
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