Real Time Estimation of Engine Torque for the Detection of Engine Misfires

Author:

Connolly Francis T.1,Rizzoni Giorgio2

Affiliation:

1. Ford Motor Company, 1115 GTL, P.O. Box 2053, Dearborn, MI 48121-2053

2. Department of Mechanical Engineering, The Ohio State University, 206 West 18th Avenue, Columbus, OH 43210-1107

Abstract

The need for improvements in the on-line estimation of engine performance variables is greater nowadays as a result of more stringent emission control legislation. There is also a concurrent requirement for improved on-board diagnostics to detect different types of malfunctions. For example, recent California Air Resources Board (CARB) regulations mandate continuous monitoring of misfires, a problem which, short of an expensive measurement of combustion pressure in each cylinder, is most directly approached by estimating individual cylinder torque. This paper describes the theory and experimental results of a method for the estimation of individual cylinder torque in automative engines, with the intent of satisfying the CARB misfire detection requirements. Estimation, control, and diagnostic functions associated with automotive engines involve near periodic processes, due to the nature of multi-cylinder engines. The model of the engine dynamics used in this study fully exploits the inherent periodicity of the combustion process in the crank angle domain in order to obtain a simple deconvolution method for the estimation of the mean torque produced by each cylinder during each stroke from a measurement of crankshaft angular velocity. The deconvolution is actually performed in the spatial frequency domain, recognizing that the combustion energy is concentrated at discrete spatial frequencies, which are harmonics of the frequency of rotation of the crankshaft. Thus, the resulting deconvolution algorithm is independent of engine speed, and reduces to an algebraic operation in the frequency domain. It is necessary to perform a Discrete Fourier Transform (DFT) on the measured angular velocity signal, sampled at fixed uniform crank angle intervals. The paper discusses the model used in the study, and the experimental validation of the algorithm, which has been implemented in real time using a portable computer and has been tested extensively on different production vehicles on a chassis dynamometer and on the road.

Publisher

ASME International

Subject

Computer Science Applications,Mechanical Engineering,Instrumentation,Information Systems,Control and Systems Engineering

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1. In-Cylinder Pressure Estimation from Rotational Speed Measurements via Extended Kalman Filter;Sensors;2023-04-27

2. Combustion parameter evaluation of diesel engine via vibration acceleration signal;International Journal of Engine Research;2021-07-18

3. Misfire detection of diesel engine based on convolutional neural networks;Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering;2021-01-11

4. Air–Fuel Ratio Imbalance Diagnostic of Spark-Ignited Engines With Modulated Sliding Discrete Fourier Transform;Journal of Dynamic Systems, Measurement, and Control;2020-03-18

5. Detection of engine misfire using characteristic harmonics of angular acceleration;Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering;2019-03-13

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