Development of misfire detection algorithm using quantitative FDI performance analysis |
| |
| Affiliation: | 1. IRTES-SET (Laboratoire Systèmes et Transports), University of Technology of Belfort-Montbéliard, Belfort 90010, France;2. FCLab FR CNRS 3539, FEMTO-ST UMR CNRS 6174, University of Technology of Belfort-Montbéliard, Belfort 90010, France;1. Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Via Ponzio 34/5, Milano, Italy;2. RSE, Via Rubattino 54, Milano, Italy |
| |
| Abstract: | A model-based misfire detection algorithm is proposed. The algorithm is able to detect misfires and identify the failing cylinder during different conditions, such as cylinder-to-cylinder variations, cold starts, and different engine behavior in different operating points. Also, a method is proposed for automatic tuning of the algorithm based on training data. The misfire detection algorithm is evaluated using data from several vehicles on the road and the results show that a low misclassification rate is achieved even during difficult conditions. |
| |
| Keywords: | Misfire detection Fault diagnosis Fault detection and isolation Kullback–Leibler divergence Pattern recognition |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
