Instantaneous within cycle model based fault estimators for SI engines

Sengupta, Somnath; Mukhopadhyay, Siddhartha; Deb, Alok Kanti

doi:10.1109/indcon.2011.6139610

Cited by 3 publications

(4 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some detections were obtained at low loads. Since there exist no work in literature on EGR valve sensor faults (except for some detection results using an instantaneous model in [26]), comparisons cannot be ventured. Note that the leak detection model described in (15) uses differentiation that causes unwanted noise amplification.…”

Section: Discussionmentioning

confidence: 99%

“…However, it appears that no work on the detection of EGR valve sensor faults has been proposed in literature, with the exception of [26] that uses WCCMs. Also, most of the diagnosis work on engine system leaks relate to leaks in the intake manifold [1], [5].…”

Section: Fault Residual Generatorsmentioning

confidence: 99%

“…In both these fault cases, the EGR flow and leak flow can be estimated by analytical redundancy [26]. Equation (4) can be generically written asṁ where A eff is the effective area = C d A, X, Y, and Z are functions of states.…”

Section: Fault Estimationmentioning

confidence: 99%

“…This makes the model used specific to the experimental engine. However, in this paper, a general analytical leak model is made use of, which was first derived in [26] to detect leaks using WCCMs. This has been used in the context of MVEMs for the first time in [21] and in this paper for EGR valve sensor fault and exhaust leak fault detection.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

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.

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

Section: Discussionmentioning

confidence: 99%

Section: Fault Residual Generatorsmentioning

confidence: 99%

Section: Fault Estimationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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.

View full text Add to dashboard Cite

show abstract

Model based Online Fault Diagnosis of Automotive Engines using Joint State and Parameter Estimation

2015

Self Cite

View full text Add to dashboard Cite

In this work, an Extended Kalman Filter (EKF) based tunable diagnoser, which uses a minimal hybrid nonlinear state space model of a spark ignition (SI) four stroke engine, is used for the detection and isolation of a variety of engine system faults including intake manifold leak, injector fault and exhaust manifold leak. The state estimates and innovation sequences from the EKF based estimator are shown to be adequate for the detection and isolation of the faults under consideration. Once a fault is detected and isolated, the diagnoser could be tuned online to perform fault identification by redefining a model/fault parameter as an additional state to be estimated and then performing a joint state and parameter estimation. The engine model and diagnoser are implemented in SimulinkTM and are validated against an AMESimTM model of the engine. For the nominal engine model, the performance of the EKF estimator is compared with two other computationally more expensive nonlinear estimators, namely the Unscented Kalman Filter (UKF) and Rao-Blackwell Particle Filter (RBPF).

show abstract

Development of SI-Engine based Extended MVEMs for use in Estimators for Engine Health Management

Vasu

Deb

Mukhopadhyay

et al. 2012

SAE Technical Paper Series

View full text Add to dashboard Cite

Instantaneous within cycle model based fault estimators for SI engines

Cited by 3 publications

References 13 publications

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

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

Model based Online Fault Diagnosis of Automotive Engines using Joint State and Parameter Estimation

Development of SI-Engine based Extended MVEMs for use in Estimators for Engine Health Management

Contact Info

Product

Resources

About