Review of sensing methodologies for estimation of combustion metrics

For reduction of engine-out emissions and improvement of fuel economy, closed-loop control of the combustion process has been explored and documented by many researchers. In the closed-loop control, the engine control parameters are optimized according to the estimated instantaneous combustion metrics provided by the combustion sensing process. Combustion sensing process is primarily composed of two aspects: combustion response signal acquisition and response signal processing. As a number of different signals have been employed as the response signal and the signal processing techniques can be different, this paper did a review work concerning the two aspects: combustion response signals and signal processing techniques. In-cylinder pressure signal was not investigated as one of the response signals in this paper since it has been studied and documented in many publications and also due to its high cost and inconvenience in the application

Simulation of an aircraft radial engine misfire detection

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

Meta-heuristic algorithms in car engine design: a literature survey

Meta-heuristic algorithms are often inspired by natural phenomena, including the evolution of species in Darwinian natural selection theory, ant behaviors in biology, flock behaviors of some birds, and annealing in metallurgy. Due to their great potential in solving difficult optimization problems, meta-heuristic algorithms have found their way into automobile engine design. There are different optimization problems arising in different areas of car engine management including calibration, control system, fault diagnosis, and modeling. In this paper we review the state-of-the-art applications of different meta-heuristic algorithms in engine management systems. The review covers a wide range of research, including the application of meta-heuristic algorithms in engine calibration, optimizing engine control systems, engine fault diagnosis, and optimizing different parts of engines and modeling. The meta-heuristic algorithms reviewed in this paper include evolutionary algorithms, evolution strategy, evolutionary programming, genetic programming, differential evolution, estimation of distribution algorithm, ant colony optimization, particle swarm optimization, memetic algorithms, and artificial immune system

MODELING OF TRANSFER PATH FOR DETERMINATION OF COMBUSTION AND NOISE METRICS ON DIESEL ENGINES

Determination of combustion metrics for a diesel engine has the potential of providing feedback for closed-loop combustion phasing control to meet current and upcoming emission and fuel consumption regulations. This thesis focused on the estimation of combustion metrics including start of combustion (SOC), crank angle location of 50% cumulative heat release (CA50), peak pressure crank angle location (PPCL), and peak pressure amplitude (PPA), peak apparent heat release rate crank angle location (PACL), mean absolute pressure error (MAPE), and peak apparent heat release rate amplitude (PAA). In-cylinder pressure has been used in the laboratory as the primary mechanism for characterization of combustion rates and more recently in-cylinder pressure has been used in series production vehicles for feedback control. However, the intrusive measurement with the in-cylinder pressure sensor is expensive and requires special mounting process and engine structure modification. As an alternative method, this work investigated block mounted accelerometers to estimate combustion metrics in a 9L I6 diesel engine. So the transfer path between the accelerometer signal and the in-cylinder pressure signal needs to be modeled. Depending on the transfer path, the in-cylinder pressure signal and the combustion metrics can be accurately estimated - recovered from accelerometer signals. The method and applicability for determining the transfer path is critical in utilizing an accelerometer(s) for feedback. Single-input single-output (SISO) frequency response function (FRF) is the most common transfer path model; however, it is shown here to have low robustness for varying engine operating conditions. This thesis examines mechanisms to improve the robustness of FRF for combustion metrics estimation. First, an adaptation process based on the particle swarm optimization algorithm was developed and added to the single-input single-output model. Second, a multiple-input single-output (MISO) FRF model coupled with principal component analysis and an offset compensation process was investigated and applied. Improvement of the FRF robustness was achieved based on these two approaches. Furthermore a neural network as a nonlinear model of the transfer path between the accelerometer signal and the apparent heat release rate was also investigated. Transfer path between the acoustical emissions and the in-cylinder pressure signal was also investigated in this dissertation on a high pressure common rail (HPCR) 1.9L TDI diesel engine. The acoustical emissions are an important factor in the powertrain development process. In this part of the research a transfer path was developed between the two and then used to predict the engine noise level with the measured in-cylinder pressure as the input. Three methods for transfer path modeling were applied and the method based on the cepstral smoothing technique led to the most accurate results with averaged estimation errors of 2 dBA and a root mean square error of 1.5dBA. Finally, a linear model for engine noise level estimation was proposed with the in-cylinder pressure signal and the engine speed as components

Introduction of Abnormal Combustion in Hydrogen Internal Combustion Engines and the Detection Method

As a clean, environmentally friendly and renewable energy source, hydrogen as an alternative engine fuel can greatly reduce atmospheric pollution and alleviate the shortage of oil resources, and is the most promising alternative fuel for vehicles among new fuels. However, due to its fast combustion rate and wide ignition limit, hydrogen often shows abnormal combustion phenomena (such as pre-ignition, backfire and knock), when it is used in the engine, thus affecting the performance and normal use of engines. In this paper, the advantages and disadvantages of hydrogen as an alternative fuel for the engine are summarized according to the characteristics of hydrogen. On this basis, the mechanism, influence factors and harm of abnormal combustion in the hydrogen internal combustion engine are analyzed and summarized, which provides a theoretical basis for solving abnormal combustion problems. Finally, several commonly used abnormal combustion detection methods are summarized.Citation: Liu, J. (2022). Introduction of Abnormal Combustion in Hydrogen Internal Combustion Engines and the Detection Method. Trends in Renewable Energy, 8, 38-48. DOI: 10.17737/tre.2022.8.1.0013

Monitoring of the piston ring-pack and cylinder liner interface in diesel engines through acoustic emission measurements

Investigation of novel condition monitoring systems for diesel engines has received much recent attention due to the increasing demands placed upon engine components and the limitations of conventional techniques. This thesis documents experimental research conducted to assess the monitoring capabilities of Acoustic Emission (AE) analysis. In particular it focuses on the possibility of monitoring the piston ring-pack and cylinder liner interface, a critical engine sub-system for which there are currently few practical monitoring options. A series of experiments were performed on large, two-stroke and small, four-stroke diesel engines. Tests under normal operating conditions developed a detailed understanding of typical AE generation in terms of both the source mechanisms and the characteristics of the resulting activity. This was supplemented by specific tests to investigate possible AE generation at the ring-pack/liner interface. For instance, for the small engines measures were taken to remove known AE sources in order to accentuate any activity originating at the interface whilst for the large engines the interfacial conditions were purposely deteriorated through the removal of the lubricating oil supply to one cylinder. Interpretation of the results was based mainly upon comparisons with published work encompassing both the expected ring-pack behaviour and AE generation from tribological processes. This provided a strong indication that the source of the ring-pack/liner AE activity was the boundary frictional losses. The ability to monitor this process may be of significant benefit to engine operators as it enhances the diagnostic information currently available and may be incorporated into predictive maintenance strategies. A further diagnostic technique considered was the possibility of using AE parameters combined with information of crankshaft speed fluctuations to evaluate engine balance and identify underperforming cylinders.EU Competitive and Sustainable Growth Programme, Project no: GRD2-2001-5001

Diagnostics Methods and Their Application in Automotive Engine

Import 15/01/2013Gasoline engine is a complex power generating machines and used widely in automotive industry, which the failure rate is high. Carrying out the gasoline engine fault diagnostic methods have been studied and still a lasting topic for scientists. Crankshaft instantaneous angular acceleration contains information for fault diagnostic. It can directly reflect the state of applying work and current pressure in each cylinder. By means of analyzing the angular acceleration signal, the instantaneous engine running state and a lot of related faults can be discovered. Under the normal working conditions, the motive force performance of each cylinder is unanimous basically, the gasoline engine operates steadily. Its angular acceleration always fluctuates in a normal range and presents certain regularity. The operation when a certain cylinder is working abnormally, the consistency of motive force is destroyed, the engine becomes bad to the stationary of operation, and the angular acceleration signal will be out of shape. By observing its fluctuation, the working process in each cylinder can be evaluated. In this thesis, the instantaneous angular acceleration is evaluated by phase modulation method using the Hilbert Transform technique. To verify the signal analysis technique, the engine model created originally by Weeks, RW & Moskwa, J.J. is extended by modeling of the non-uniform driving torque in contrast to the original model assuming uniform driving torque to produce fluctuation of the crankshaft angular acceleration. Many subsystems of the engine are also modeled by the simulation program Matlab/Simulink. Torque of engine at some spark advances was simulated to compare and found out the best angle to obtain the maximum brake torque, as well.Zážehový motor je široce používán v dopravních prostředcích. Jako u každého stroje, i u zážehového motoru mohou vznikat poruchy, které je třeba diagnostikovat. Provedení benzínového motoru a metody diagnosticky poruch byly studovány a jsou stále tématem pro výzkum. Okamžité úhlové zrychlení klikového hřídele poskytuje diagnostické informace o poruchách spalovacího procesu. To se může přímo odrážet na výkonu motoru daném aktuálním spalovacím tlakem v každém válci. Prostřednictvím analýzy signálu úhlového zrychlení, ve stavu kdy motor běží, může být objevena spousta chyb. Za normálních pracovních podmínek jsou hnací síly každého válce v podstatě shodné, zážehový motor pracuje v ustáleném režimu. Jeho úhlové zrychlení vždy kolísá v normálním rozsahu a představuje určitou pravidelnost. Když za provozu některý válec pracuje nepravidelně, je narušen časový průběh krouticího momentu, motor se stane nestabilní ve stacionárním provozu a úhlové zrychlení signálu bude vykazovat odchylky. Tím, že sledujeme kolísání okamžitého úhlového zrychlení, může být vyhodnocen spalovací a kompresní proces individuálně v každém válci zvlášť. V této práci, je hodnoceno okamžité úhlové zrychlení klikového hřídele metodou fázové modulace. Nástrojem k demodulaci je analytický signál, jehož imaginární část je vypočtena pomocí Hilbertovy transformace. Chceme-li ověřit metodu zpracování impulsního signálu pro ECU, použijeme simulační model motoru. První dynamický model vytvořili Week, R.W. a Moskwa, J.J.. Tento model průběžně počítal krouticí moment jako konstantu pro všechny fáze práce motoru. K testování výpočtu okamžitého úhlového zrychlení klikového hřídele bylo třeba modelovat vznik nerovnoměrnosti krouticího momentu při hoření paliva ve válci a kompresi směsi, jako příčiny periodického zrychlování a zpomalování při otáčení kliky na požadovaných otáčkách. Model motoru je rozdělen na subsystémy, které jsou modelovány simulačním programem Matlab / Simulink. Krouticí moment motoru při některých zapalovacích postupech byl pro porovnání simulován a byl hledán nejlepší úhel předstihu zapalování pro dosažení maximálního hnacího momentu.Prezenční352 - Katedra automatizační techniky a řízenívyhově

The Characteristics of Instantaneous Angular Speed of Diesel Engines for Fault Diagnosis

Early fault detection and diagnosis of diesel engines are paramount now, especially with countries like the UK and France, in-line with the 2015 Paris agreement on climate change, making plans to ban the use of an automobile with diesel and petrol engines before the year 2040. This ban could affect other sectors where diesel engines are the prime mover and result in more stringent exhaust emission regulations. The instantaneous angular speed (IAS) model based fault diagnosis has shown more prospects of fault detection and location. However, there are serious gaps in available knowledge regarding IAS model based fault diagnosis which takes into account the effect of the system’s modal properties. Hence, this research focuses on the online modal properties identification of a typical engine-load system for an improved performance of IAS based fault diagnosis. Having acknowledged the essentials of IAS based fault diagnosis techniques through a comprehensive literature study, this research firstly investigates the impact of modal properties on the IAS of a four-cylinder engine. This is achieved through a three degree of freedom (DOF) torsional vibration model of the engine-load system, which allows for the modal properties of the system to be calculated and analysed. The calculated modal properties of the system showed one rigid and two flexible modes which had a low (<13Hz) and high (<92Hz) frequencies. The mode shape of the low frequency resonance shows more amplitude on the flywheel-load reference point of the system while that of the high frequency resonance shows more amplitude on the engine-flywheel reference point of the system. It then simulated the IAS which represents the torsional vibration signature with altered modal properties. The simulated result demonstrated that the low frequency resonance is more sensitive to the peak and trough values of the IAS waveform. After identifying the deployment merits of operational modal analysis (OMA) techniques through a comprehensive literature study, this research then explore the prospect of an IAS based output-only modal properties identification of a typical engine-load system. This was done through both experimental and simulation evaluations, which allowed simulated and experimental IAS to be used for implementing covariance-driven reference based stochastic subspace identification (SSI). The simulated result using pseudo-random input shows that the identified resonance frequencies and mode shapes are 80% correlated with the calculated ones. The simulation results also demonstrated that the accuracy of the identified modal properties is dependent on the number of IAS responses used for implementing the covariance-driven reference based SSI technique. The experimental result using estimated IAS during engine shutdown operation showed that both high and low frequency vibration mode can be identified. The identified resonance frequencies with their mode shapes are 80% correlated with the predicted ones. Having identified the modal properties of the engine-load system online through the implementation of an IAS based covariance-driven SSI, this research then investigates the impact of misfire on the system’s modal properties especially the mode shape of the low frequency resonance. This was achieved experimentally by inducing a complete misfire in respective cylinders (1st, 3rd and 4th) and the IAS estimated during engine’s transient shutdown operation was used for implementing a covariance-driven reference based stochastic subspace modal properties identification. While the mode shape of the identified high frequency resonance (<80Hz) showed no characteristics for cylinder misfire detection, that of the low frequency resonance (<13Hz) did. Faults in the engine’s injection system and an abnormal clearance valve train conditions significantly affects its combustion process. The cylinder by cylinder pressure torque obtained from measured IAS through order domain deconvolution technique can be used to detect and diagnose injection faults. In the interim, this research has also recognised that the closer the low-resonance frequency of the model used for the order domain deconvolution gets to its real time value the more accurate the pressure torque becomes. The reconstructed pressure torque which takes into consideration the real time low frequency resonance can be used to detect faulty injection system with different severities and abnormal clearance valve conditions of several severities. Furthermore, the importance of an accurate modal properties utilisation in IAS mode

Modeling and experimental analysis of exhaust gas temperature and misfire in a converted-diesel homogeneous charge compression ignittion engine fuelled with ethanol

Homogeneous charge compression ignition (HCCI) and the exploitation of ethanol as an alternative fuel is one way to explore new frontiers of internal combustion engines with an objective towards maintaining its sustainability. Here, a 0.3 liter singlecylinder direct-injection diesel engine was converted to operate on the alternative mode with the inclusion of ethanol fuelling and intake air preheating systems. The main HCCI engines parameters such as indicated mean effective pressure, maximum in-cylinder pressure, heat release, in-cylinder temperature and combustion parameters, start of combustion, 50% of mass fuel burnt (CA50) and burn duration were acquired for 100 operating conditions. They were used to study the effect of varying input parameters such as equivalence ratio and intake air temperature on exhaust gas emission, temperature and ethanol combustion, experimentally and numerically. The study primarily focused on HCCI exhaust gas temperature and understanding and detecting misfire in an ethanol fuelled HCCI engine, thus highlighting the advantages and drawbacks of using ethanol fuelled HCCI. The analysis of experimental data was used to understand how misfire affects HCCI engine operation. A model-based misfire detection technique was developed for HCCI engines and the validity of the obtained model was then verified with experimental data for a wide range of misfire and normal operating conditions. The misfire detection is computationally efficient and it can be readily used to detect misfire in HCCI engine. The results of the misfire detection model are very promising from the viewpoints of further controlling and improving combustion in HCCI engines

Early Detection and Prevention of Catastrophic Failures of Industrial Engines

Nowadays, there is a tendency to operate some industrial machinery remotely, such as generator sets, gas pumps, and emergency equipment. It is often impossible to directly interfere with the operation of the equipment in the case of unexpected malfunctions. Premature and abrupt failure of the crankshaft bearings in an industrial engine can consequently lead to catastrophic damage. This project designed and tested an inexpensive system that would detect failure of the crankshaft bearings and provide a quick response. Based on the extensive literature review and the author's experience, it was decided that the proposed device comprised oil debris monitoring and vibration acquisition processing systems. The rise in pressure across the filtering element was set to indicate the presence of bearing particles in the engine oil, which would trigger a warning. The parameters of the vibration signal, such as spectrogram, Root Mean Square (RMS), and Crest Factor, were selected to monitor changes to the vibration profile associated with the fault conditions. The Matlab Graphical User Interface (GUI) performed the signal processing and displayed all necessary outputs. It also allowed the data recording and data replay options. The system was tested on a six-cylinder petrol engine with artificially induced failure of one of the crankshaft bearings. The experiments failed to instigate rapid and catastrophic bearing failure due to no load being applied to the engine. Nevertheless, the partial bearing degradation and debris generation were achieved during the test runs. The outcomes showed that the spectrogram and the RMS of the signal provided some response to the progressing failure. The spectrogram revealed the change in magnitudes of the main harmonic orders and the RMS value. For instance, the first harmonic order became dominant and the RMS behaved erratically. Normally, the third harmonic is the most prominent, and the RMS is proportional to the engine revolutions per minute (RPM). Moreover, the debris detection system caught some of the particles generated by the failing bearing. The debris blocked the filtering element, which caused the pressure to rise across the mesh. At this stage, the system is in its conceptual form. The full functionality, such as the ability to stop the engine based on the threshold parameters, has not been programmed. The thresholds are still to be properly determined and confirmed by a series of experiments. Further work is required to check the validity of the first experiments. Additional experiments will need to be performed on the engine whilst mounted to a load cell. Applying the load will allow simulation of the real working condition of the equipment. Future development of the system will require designing a black box solution based on a microcomputer, such Raspberry Pi or similar. The project acknowledges that the system might be unable to prevent subsequent damage to the components. The primary purpose of the system is to save other components and reduce the repair cost