scholarly journals A Study on Misfire Detection Index Not Affected by Post Oscillation of Engine Speed

2020 ◽  
Vol 28 (2) ◽  
pp. 143-150
Author(s):  
Poonggyoo Han
Author(s):  
Fabrizio Ponti

Many methodologies have been developed in the past for misfire detection purposes based on the analysis of the instantaneous engine speed. The missing combustion is usually detected thanks to the sudden engine speed decrease that takes place after a misfire event. Misfire detection and in particular cylinder isolation is anyhow still a challenging issue for engines with a high number of cylinders, for engine operating conditions at low load or high engine speed and for multiple misfire events. When a misfire event takes place in fact a torsional vibration is excited and shows up in the instantaneous engine speed waveform. If a multiple misfire occurs this torsional vibration is excited more than once in a very short time interval. The interaction among these successive vibrations can generate false alarms or misdetection, and an increased complexity when dealing with cylinder isolation. The paper presents the development of a powertrain torsional behavior model in order to identify the effects of a misfire event on the instantaneous engine speed signal. The identified waveform has then been used to filter out the torsional vibration effects in order to enlighten the missing combustions even in the case of multiple misfire events. The model response is also used to quicken the setup process for the detection algorithm employed, evaluating before running specific experimental tests on a test bench facility, the values for the threshold and the optimal setup of the procedure. The proposed algorithm is developed in this paper for an SI L4 engine; Its application to other engine configurations is possible, as it is also discussed in the paper.


Author(s):  
Fabrizio Ponti

Misfire detection is a subject that has been deep studied during the last years and many methodologies have been developed for this purpose. Affordably detecting the misfire event and isolating the cylinder where the missing combustion took place can be considered a solved problem for engines with a limited number of cylinders. Misfire detection and in particular cylinder isolation is still challenging for engine operating conditions at very low load and high engine speed, for engines with a high number of cylinders, or when more than one misfire event is present within the same engine cycle (multiple misfire). In particular this last malfunctioning condition is very challenging, and its detection is enforced by the international regulations without requiring cylinder isolation, but only the number of misfiring cylinders. Many methodologies have been developed in the past based on the analysis of the instantaneous engine speed. The missing combustion effect on this signal is anyway very low when the number of cylinders is high and for engine operating conditions at low engine speed, giving rise to misdetection or false alarms as already mentioned. In addition when a misfire event takes place a torsional vibration is excited and shows up in the instantaneous engine speed waveform. If a multiple misfire occurs this torsional vibration is excited more than once in a very short time interval. The interaction among these successive vibrations can further generate false alarms or misdetection, and an increased complexity when dealing with cylinder isolation is necessary. The approach here presented permits enhancing existing misfire detection methods through optimized algorithm that allows correctly isolating the multiple misfiring cylinders over the entire engine operating range. This has been obtained by proper identifying the effect of the torsional vibration over the instantaneous engine speed. The identified waveform has been then used to filter out the torsional vibration effects in order to enlighten the effects of the missing combustions. In addition a proper instantaneous engine speed windowing has been introduced in order to increase the detection signal to noise ratio over the whole engine operating range. The integration of these two signal processing techniques has proven to be very effective on the engine investigated in this study, and it is easily extendible to other engine architectures. Particular care has been devoted to satisfy on-board implementation requirements in terms of memory allocation and computational power. The tests have been conducted on an L4 1.2 liter spark ignition engine mounted in a test cell. In-cylinder pressure signals have been acquired in order to validate the methodology here developed.


Author(s):  
Fabrizio Ponti

The diagnosis of a misfire event and the isolation of the cylinder in which the misfire took place is enforced by the On Board Diagnostics (OBD) requirements over the whole operating range for all the vehicles whatever the configuration of the engine they mount. This task is particularly challenging for engines with a high number of cylinders and for engine operating conditions that are characterized by high engine speed and low load. This is why much research has been devoted to this topic in recent years, developing different detection methodologies based on signals such as instantaneous engine speed, exhaust pressure, etc., both in time and frequency domains. This paper presents the development and the validation of a methodology for misfire detection based on the time-frequency analysis of the instantaneous engine speed signal. This signal contains information related to the misfire event, since a misfire occurrence is characterized by a sudden engine speed decrease and a subsequent damped torsional vibration. The identification of a specific pattern in the instantaneous engine speed frequency content, characteristic of the system under study, allows performing the desired misfire detection and cylinder isolation. Particular attention has been devoted in designing the methodology in order to avoid the possibility of false alarms caused by the excitation of this frequency pattern independently from a misfire occurrence. Although the time-frequency analysis is usually considered a time consuming operation and is not associated to on-board application, the methodology here proposed has been properly modified and simplified in order to obtain the quickness required for its use directly on-board a vehicle. Experimental tests have been performed on a 5.7 liter V12 spark ignited engine, with the engine mounted on-board a vehicle. The frequency pattern identified is not the same that could be observed when running the engine on a test bench, because of the different stiffness that the connection between the engine and the load presents in the two cases. This makes impossible to set-up the methodology here proposed only on a test bench, without running tests on the vehicle.


Author(s):  
Fabrizio Ponti

The diagnosis of a misfire event and the isolation of the cylinder in which the misfire took place is enforced by the onboard diagnostics (OBD) requirements over the whole operating range for all the vehicles, whatever the configuration of the engine they mount. This task is particularly challenging for engines with a high number of cylinders and for engine operating conditions that are characterized by high engine speed and low load. This is why much research has been devoted to this topic in recent years, developing different detection methodologies based on signals such as instantaneous engine speed, exhaust pressure, etc., both in time and frequency domains. This paper presents the development and the validation of a methodology for misfire detection based on the time-frequency analysis of the instantaneous engine speed signal. This signal contains information related to the misfire event, since a misfire occurrence is characterized by a sudden engine speed decrease and a subsequent damped torsional vibration. The identification of a specific pattern in the instantaneous engine speed frequency content, characteristic of the system under study, allows performing the desired misfire detection and cylinder isolation. Particular attention has been devoted to designing the methodology in order to avoid the possibility of false alarms caused by the excitation of this frequency pattern independently from a misfire occurrence. Although the time-frequency analysis is usually considered a time-consuming operation and not associated to onboard application, the methodology proposed here has been properly modified and simplified in order to obtain the quickness required for its use directly onboard a vehicle. Experimental tests have been performed on a 5.7l V12 spark-ignited engine run onboard a vehicle. The frequency characteristic of the engine-vehicle system is not the same that could be observed when running the engine on a test bench, because of the different inertia and stiffness that the connection between the engine and the load presents in the two cases. This makes it impossible to test and validate the methodology proposed here only on a test bench, without running tests on the vehicle. Nevertheless, the knowledge of the mechanical design of the engine and driveline gives the possibility of determining the resonance frequencies of the system (the lowest one is always the most important for this work) before running tests on the vehicle. This allows saving time and reducing costs in developing the proposed approach.


2002 ◽  
Author(s):  
Nicolò Cavina ◽  
Enrico Corti ◽  
Giorgio Minelli ◽  
Gabriele Serra

2019 ◽  
Vol 87 ◽  
pp. 01011
Author(s):  
Łukasz Grabowski ◽  
Paweł Karpiński ◽  
Konrad Pietrykowski

The misfire phenomenon is particularly unfavourable in aircraft engines because it affects the stability and reliability of work. This paper presents the algorithm for detecting ignition failure in a radial aircraft engine. The Crankshaft Velocity Fluctuation method was applied, which consists in analysing changes in the crankshaft speed signal as a function of time. A zero-dimensional model of the aircraft engine was developed in order to perform the research. The validation of the model was performed using the results from the test bench. The model was subjected to simulation tests in fixed operating conditions. Based on the engine speed signal obtained as a result of the simulation, the normalized second derivative of the signal was determined based on the adopted algorithm. On the basis of this derivative, a criterion was defined to assess the occurrence of the misfire phenomenon. The results of the calculations can be compared in future with the results of the real engine tests.


Author(s):  
M. Boudaghi Kh. N. ◽  
M. Shahbakhti ◽  
S. A. Jazayeri

Control and detection of misfire is an essential part of on-board diagnosis of modern SI engines. This study proposes a novel model-based technique for misfire detection of a multi-cylinder SI engine. The new technique uses a dynamic engine model to determine mean output power, which is then used to calculate a new parameter for misfire detection. The new parameter directly relates to combustion period and is sensitive to the engine speed fluctuations caused by misfire. The new technique only requires measured engine speed data and it is computationally viable for use in a typical ECU. The new technique is evaluated experimentally on a 4-cylinder 1.6-liter SI engine. Three types of misfires are studied including single, continues, and multiple events. The steady-state and transient experiments were done for a wide range of engine speeds and engine loads, using a vehicle chassis dynamometer and on-road vehicle testing. The validation results show the new technique is capable to detect all the three types of misfire with up to 97 percent accuracy during steady-state conditions. The new technique is augmented with a compensation factor to improve the accuracy of the technique for transient operations. The resulting technique is shown to be capable of detecting misfire during both transient and steady-state engine conditions.


Author(s):  
M. Boudaghi ◽  
M. Shahbakhti ◽  
S. A. Jazayeri

Control and detection of misfire are an essential part of on-board diagnosis (OBD) of modern spark ignition (SI) engines. This study proposes a novel model-based technique for misfire detection for a multicylinder SI engine. The new technique uses a dynamic engine model to determine mean output power, which is then used to calculate a new parameter for misfire detection. The new parameter directly relates to combustion period and is sensitive to engine speed fluctuations caused by misfire. The new technique requires only measured engine speed data and is computationally viable for use in a typical engine control unit (ECU). The new technique is evaluated experimentally on a four-cylinder 1.6-l SI engine. Three types of misfire are studied including single, continuous, and multiple-event. The steady-state and transient experiments were done for a wide range of engine speeds and engine loads, using a vehicle chassis dynamometer and on-road vehicle testing. The validation results show that the new technique is able to detect all three types of misfire with up to 94% accuracy during steady-state conditions. The new technique is augmented with a compensation factor to improve the accuracy of the technique for transient operations. The resulting technique is shown to be capable of detecting misfire during both transient and steady-state engine conditions.


Author(s):  
Xiumin Yu ◽  
Le Liu ◽  
Shichun Yang ◽  
Xianglin Zhong ◽  
Derong Liu

Author(s):  
Nicolo` Cavina

The diagnosis of misfire events (or missing combustions) is enforced by On-Board Diagnostics regulations (such as CARB OBD II or European OBD) over the whole engine operating range, for all vehicles equipped with spark ignition engines. Such regulations define both the minimum misfire frequency that is to be detected (related to catalyst damage and/or increased hydrocarbons emissions), and the various misfire patterns that the diagnostic algorithm should be able to detect. In particular, single (no more than one missing combustion per engine cycle) and multiple (more than one misfiring cylinder within the same engine cycle) misfire patterns are to be diagnosed, and the cylinder in which the misfire took place is to be isolated only when single misfires take place (cylinder identification is still not mandatory for multiple misfires). Various single misfire detection methodologies have been successfully developed in recent years (mostly based on the engine speed signal), and this type of misfire diagnosis is still challenging for engines with a high number of cylinders, especially during operating conditions characterized by high engine speed and low load. On the other hand, the detection of multiple misfires is still difficult even for the typical four cylinder engine, since their effects on the engine speed trend have not yet been clarified. In fact, a misfire occurrence is characterized by a sudden engine speed decrease and a subsequent damped torsional vibration. In case of multiple misfires, the engine speed oscillation induced by the first misfiring cylinder may still be present when the second missing combustion takes place, and the resulting engine speed waveform may be erroneously interpreted by the diagnostic algorithm, thus resulting in the improper cylinder being identified or missed detection of a misfiring cylinder. This paper deals with the identification of a specific pattern in the instantaneous engine speed trend, induced by a missing combustion and characteristic of the system under study, that allows performing the desired multiple misfire detection. The methodology has been designed in order to be run on-board, thus requiring low computational power and memory allocation. Its implementation has shown that false alarms can be avoided and correct cylinder isolation is possible, also in presence of multiple misfires. Experimental tests have been performed on a 1.2 liter spark ignition engine mounted in a test cell. Various multiple misfire patterns have been induced by controlling ignition and injection of the various cylinders. In-cylinder pressure signals have been acquired together with the instantaneous engine speed, in order to verify the capability of the methodology.


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