Fault detection of Air Intake Systems of SI gasoline engines using mean value and within cycle models

Sengupta, Somnath; De, Soumen; Bhattacharyya, A. K.; Mukhopadhyay, Siddhartha; Deb, Alok Kanti

doi:10.1109/coase.2009.5234095

Cited by 7 publications

(2 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Taking into account the possibilities that a mean-value model can bring to the research, which needs a model of the engine as part of a wider range model, recently more attention has been paid to this type of model; see, for example, Lee [58], Hendricks [59], Sengupta [60], Yacoub [61], Theotokatos [62], Guzzella [63], Yum [64], Scappin [65], Kharroubi [66], Baldi [67], Altosole et al [68].…”

Section: Literature Reviewmentioning

confidence: 99%

Performance and Emission Modelling and Simulation of Marine Diesel Engines using Publicly Available Engine Data

Ghaemi

2021

Polish Maritime Research

View full text Add to dashboard Cite

To analyse the behaviour of marine diesel engines in unsteady states for different purposes, for example to determine the fuel consumption or emissions level, to adjust the control strategy, to manage the maintenance, etc., a goal-based mathematical model that can be easily implemented for simulation is necessary. Such a model usually requires a wide range of operating data, measured on a test stand. This is a time-consuming process with high costs and the relevant data are not available publicly for a selected engine. The present paper delivers a rapid and relatively simple method for preparing a simulation model of a given marine diesel engine, based only on the widely available data in the project guides indicated for steady state conditions. After establishing the framework of the mathematical model, it describes how the parameters of the model can be adjusted for the simulation model and how the results can be verified as well. Conceptually, this is a trial and error method, but the presented case example makes clear how the parameters can be selected to reduce the number of trials and quickly determine the model parameters. The necessary descriptions are given through a case study, which is the MAN-B&W 8S65ME-C8 marine diesel engine. The engine is assumed to be connected to a constant pitch propeller. The presented mathematical model is a mean-value zero-dimensional type with seven state variables. The other variables of the engine are determined based on the state independent variables and the input value, which is the fuel rate. The paper can be used as a guideline to prepare a convenient mathematical model for simulation, with the minimum publicly available data.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Performance and Emission Modelling and Simulation of Marine Diesel Engines using Publicly Available Engine Data

Ghaemi

2021

Polish Maritime Research

View full text Add to dashboard Cite

show abstract

“…In model-based fault diagnosis techniques, several kinds of models have been used for diagnosis. There are logical models, data-driven models and techniques [5], discrete event systems [6], [7], and physics-based models such as mean value engine models (MVEMs) [8], [9], and instantaneous within cycle crank-angle-based models (WCCMs) [9], [10]. MVEMs are "gray-box" models whose complexity is in between those of detailed physics-based instantaneous models and simple behavioral black-box models.…”

Section: Introductionmentioning

confidence: 99%

MVEM-Based Fault Diagnosis of Automotive Engines Using Dempster–Shafer Theory and Multiple Hypotheses Testing

Vasu

Deb

Mukhopadhyay

2015

IEEE Trans. Syst. Man Cybern, Syst.

Self Cite

View full text Add to dashboard Cite

Internal combustion engines exhibit fast pulsating short-time dynamics due to the reciprocating cylinder motion, around mean operating points that change comparatively slow due to inputs such as throttle and load. Comparatively, simple mean value engine models (MVEM) describe the slow changes of the averaged states for automotive control and fault diagnosis. In this paper, a bank of state estimators based on MVEMs is used for fault residual generation. Three faults: 1) throttle mass airflow sensor fault; 2) exhaust gas recirculation valve sensor fault; and 3) exhaust leak fault are considered here. These faults are significant as they affect emission levels. Optimized thresholds for residual classification are derived for minimizing false alarm rates and missed detection rates. The diagnosis logic, based on the principles of structured residuals proposed in literature, is extended here for multiple hypotheses testing. Furthermore, the Dempster-Shafer theory is used to associate a confidence measure with the decision conclusions and this is shown to improve isolation. Performance is demonstrated with automotive engine data obtained from a four-cylinder instantaneous spark-ignition engine (gasoline) system model, developed in the simulation software AMESim.

show abstract

Instantaneous within cycle model based fault estimators for SI engines

Sengupta

Mukhopadhyay

Deb

2011

2011 Annual IEEE India Conference

View full text Add to dashboard Cite

Fault detection of Air Intake Systems of SI gasoline engines using mean value and within cycle models

Cited by 7 publications

References 7 publications

Performance and Emission Modelling and Simulation of Marine Diesel Engines using Publicly Available Engine Data

Performance and Emission Modelling and Simulation of Marine Diesel Engines using Publicly Available Engine Data

MVEM-Based Fault Diagnosis of Automotive Engines Using Dempster–Shafer Theory and Multiple Hypotheses Testing

Instantaneous within cycle model based fault estimators for SI engines

Contact Info

Product

Resources

About