Probabilistic Engine Performance Scatter and Deterioration Modeling

2007 ◽  
Author(s):  
Stefan Spieler ◽  
Stephan Staudacher ◽  
Roland Fiola ◽  
Peter Sahm ◽  
Matthias Weißschuh
Keyword(s):  
Test Data ◽  
Probabilistic Approach ◽  
Engine Performance ◽  
Aircraft Engine ◽  
Operating Conditions ◽  
Performance Data ◽  
Maintenance Cost ◽  
Performance Parameters ◽  
Engine Operation ◽  
The Impact

The change of performance parameters over time due to engine deterioration and production scatter plays an important role to ensure safe and economical engine operation. A tool has been developed which is able to model production scatter and engine deterioration on the basis of elementary changes of numerous construction features. In order to consider the characteristics of an engine fleet as well as random environmental influences, a probabilistic approach using Monte Carlo Simulation (MCS) was chosen. To quantify the impact of feature deviations on performance relevant metrics, non-linear sensitivity functions are used to obtain scalars and offsets on turbomachinery maps which reflect module behavior during operation. Probability density functions (PDFs) of user-defined performance parameters of an engine fleet are then calculated by performing an MCS in a performance synthesis program. For the validation of the developed methodology pass-off test data, endurance engine test data, as well as data from engine maintenance incoming tests have been used. For this purpose, measured engine fleet performance data have been corrected by statistically eliminating the influence of measuring errors. The validation process showed the model’s ability to predict more than 90% of the measured performance variance. Furthermore, predicted performance trends correspond well to performance data from engines in operation. Two model enhancements are presented, the first of which is intended for maintenance cost prediction. It is able to generate PDFs of failure times for different features. The second enhancement correlates feature change and operating conditions and thus connects airline operation and maintenance costs. Subsequently, it is shown that the model developed is a powerful tool to assist in aircraft engine design and production processes thanks to its ability to identify and quantitatively assess main drivers for performance variance and trends.

Probabilistic Engine Performance Scatter and Deterioration Modeling

2008 ◽  
Vol 130 (4) ◽  
Author(s):  
Stefan Spieler ◽  
Stephan Staudacher ◽  
Roland Fiola ◽  
Peter Sahm ◽  
Matthias Weißschuh
Keyword(s):  
Test Data ◽  
Probabilistic Approach ◽  
Engine Performance ◽  
Aircraft Engine ◽  
Operating Conditions ◽  
Performance Data ◽  
Maintenance Cost ◽  
Performance Parameters ◽  
Engine Operation ◽  
The Impact

The change of performance parameters over time due to engine deterioration and production scatter plays an important role to ensure safe and economical engine operation. A tool has been developed which is able to model production scatter and engine deterioration on the basis of elementary changes of numerous construction features. In order to consider the characteristics of an engine fleet as well as random environmental influences, a probabilistic approach using Monte Carlo simulation (MCS) was chosen. To quantify the impact of feature deviations on performance relevant metrics, nonlinear sensitivity functions are used to obtain scalars and offsets on turbomachinery maps, which reflect module behavior during operation. Probability density functions (PDFs) of user-defined performance parameters of an engine fleet are then calculated by performing a MCS in a performance synthesis program. For the validation of the developed methodology pass-off test data, endurance engine test data, as well as data from engine maintenance, incoming tests have been used. For this purpose, measured engine fleet performance data have been corrected by statistically eliminating the influence of measuring errors. The validation process showed the model’s ability to predict more than 90% of the measured performance variance. Furthermore, predicted performance trends correspond well to performance data from engines in operation. Two model enhancements are presented, the first of which is intended for maintenance cost prediction. It is able to generate PDFs of failure times for different features. The second enhancement correlates feature change and operating conditions and thus connects airline operation and maintenance costs. Subsequently, it is shown that the model developed is a powerful tool to assist in aircraft engine design and production processes, thanks to its ability to identify and quantitatively assess main drivers for performance variance and trends.

Impact of Compressor Surge on Performance and Emissions of a Marine Diesel Engine

2016 ◽  
Vol 138 (10) ◽  
Author(s):  
Nikolaos-Alexandros Vrettakos
Keyword(s):  
Steady State ◽  
Diesel Engine ◽  
Engine Performance ◽  
Marine Diesel Engine ◽  
Performance Parameters ◽  
Test Bed ◽  
Engine Operation ◽  
Compressor Surge ◽  
Marine Diesel ◽  
The Impact

The operation during compressor surge of a medium speed marine diesel engine was examined on a test bed. The compressor of the engine's turbocharger was forced to operate beyond the surge line, by injecting compressed air at the engine intake manifold, downstream of the compressor during steady-state engine operation. While the compressor was surging, detailed measurements of turbocharger and engine performance parameters were conducted. The measurements included the use of constant temperature anemometry for the accurate measurement of air velocity fluctuations at the compressor inlet during the surge cycles. Measurements also covered engine performance parameters such as in-cylinder pressure and the impact of compressor surge on the composition of the exhaust gas emitted from the engine. The measurements describe in detail the response of a marine diesel engine to variations caused by compressor surge. The results show that both turbocharger and engine performance are affected by compressor surge and fast Fourier transform (FFT) analysis proved that they oscillate at the same main frequency. Also, prolonged steady-state operation of the engine with this form of compressor surge led to a non-negligible increase of NOx emissions.

scholarly journals Application of a Constant Gain Extended Kalman Filter for In-Flight Estimation of Aircraft Engine Performance Parameters

2005 ◽  
Author(s):  
Takahisa Kobayashi ◽  
Donald L. Simon ◽  
Jonathan S. Litt
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Aircraft Engine ◽  
Operating Conditions ◽  
Accurate Estimation ◽  
Aircraft Engines ◽  
Performance Parameters ◽  
Efficient Manner ◽  
Engine Operation ◽  
Engine Model

An approach based on the Constant Gain Extended Kalman Filter (CGEKF) technique is investigated for the in-flight estimation of non-measurable performance parameters of aircraft engines. Performance parameters, such as thrust and stall margins, provide crucial information for operating an aircraft engine in a safe and efficient manner, but they can not be directly measured during flight. A technique to accurately estimate these parameters is, therefore, essential for further enhancement of engine operation. In this paper, a CGEKF is developed by combining an on-board engine model and a single Kalman gain matrix. In order to make the on-board engine model adaptive to the real engine’s performance variations due to degradation or anomalies, the CGEKF is designed with the ability to adjust its performance through the adjustment of artificial parameters called “tuning parameters.” With this design approach, the CGEKF can maintain accurate estimation performance when it is applied to aircraft engines at off-nominal conditions. The performance of the CGEKF is evaluated in a simulation environment using numerous component degradation and fault scenarios at multiple operating conditions.

Probabilistic Engine Maintenance Modeling for Varying Environmental and Operating Conditions

2010 ◽  
Author(s):  
Matthias Mu¨ller ◽  
Stephan Staudacher ◽  
Winfried-Hagen Friedl ◽  
Rene´ Ko¨hler ◽  
Matthias Weißschuh
Keyword(s):  
Engine Performance ◽  
Distribution Functions ◽  
Performance Model ◽  
Operating Conditions ◽  
Maintenance Cost ◽  
Engine Operation ◽  
Performance Deterioration ◽  
And Performance ◽  
The Individual ◽  
Engine Maintenance

The maintenance and reliability of aircraft engines is strongly influenced by the environmental and operating conditions they are subjected to in service. A probabilistic tool has been developed to predict shop visit arisings and respective maintenance workscope that depends on these factors. The tool contains a performance model of the engine and a number of physics-based damage mechanisms (at piece part level). The performance model includes variation of performance relevant parameters due to production scatter and delivers the conditions to determine the deterioration of the individual parts. Shop visit maintenance is modeled as a result of limitations to engine operation, e.g. reaching TGT limit, or mechanical deterioration. The influence of maintenance actions on engine performance is determined on component basis. The maintenance strategy can consist of proactive and reactive maintenance elements. The decision of repair or replacement of any single part is implemented through a sum of different logic rules in the model. The loading capacity scatter depends on the engine type and is operator independent. It is represented via data-driven distribution functions, in which the probabilities of failure, repair and replacement for each part are specified depending on the number of reference flight cycles. The loading variation is considered through a physics-based cycle weighting. The developed tool runs a Monte Carlo simulation in which a fleet of engines is modeled through their respective lifetime of maintenance and performance deterioration. Using an example it is shown that the model can describe the effects of varying environmental and operating conditions on part damage, and therefore engine maintenance cost and reliability.

The impact of piston thermal barrier coating roughness on high-load diesel operation

2019 ◽  
pp. 146808741989348 ◽  
Author(s):  
Eric Gingrich ◽  
Michael Tess ◽  
Vamshi Korivi ◽  
Peter Schihl ◽  
John Saputo ◽  
...  
Keyword(s):  
Heat Transfer ◽  
Surface Roughness ◽  
Thermal Barrier Coating ◽  
Engine Performance ◽  
Operating Conditions ◽  
Thermal Barrier ◽  
Engine Operation ◽  
Barrier Coating ◽  
The Impact ◽  
High Output

Thermal barrier coatings of various thickness and surface roughness were applied to the piston crown of a single-cylinder research engine and tested over a range of high-output diesel operating conditions, some near 30 bar gross indicated mean effective pressure. Three yttria-stabilized zirconia coated pistons were compared to a baseline metal piston. At each operating condition, a start-of-injection sweep was conducted to generate efficiency trends and find the optimal combustion phasing. Three variations of pistons coated with a graded-layer thermal barrier coating were tested: (1) 0.185 mm coating thickness with a surface roughness of approximately Ra = 11.8 µm, (2) 0.325 mm thickness with Ra = 11.8 µm, and (3) 0.325 mm thickness with Ra = 6.0 µm. Both coated pistons with Ra = 11.8 µm did not show any statistically significant improvement to engine performance when compared to the metal baseline piston, but did produce higher filter smoke numbers. The coated piston with Ra = 6.0 µm and 0.325 mm showed an increase of gross indicated thermal efficiency of up to 3.5% (relative) compared to the metal baseline piston for operating conditions comparable to standard engine operation and a reduction of filter smoke number back to the metal baseline. The increase in efficiency was found to correlate with additional late-cycle apparent heat release and a reduction in in-cylinder heat transfer. The very high-output conditions showed statistically insignificant changes in performance or heat transfer, which may have been related to the long injection duration used for these cases targeting outside of the piston bowl.

Artificial neural network–based performance modeling of a diesel engine within the whole operating region considering dynamic conditions

2018 ◽  
Vol 233 (11) ◽  
pp. 2970-2984 ◽  
Author(s):  
Liang Sun ◽  
Wei Wei ◽  
Qingdong Yan ◽  
Hongchao Jian
Keyword(s):  
Neural Network ◽  
Test Data ◽  
Interpolation Method ◽  
Engine Performance ◽  
Operating Conditions ◽  
Bench Test ◽  
Parameter Distribution ◽  
Performance Parameters ◽  
Dynamic Conditions ◽  
Engine Model

Engine performance under full working conditions, especially dynamic ones, is indispensable in many vehicle-level research fields. To acquire the engine performance parameters, a novel whole-region engine model, considering both steady and dynamic conditions, was developed based on limited test data in this work. This model used throttle position, engine speed, and its acceleration as the input variables to predict torque and brake-specific fuel consumption under all practical conditions within its operating envelope. The engine bench test was first conducted under typical operating conditions to collect test data for model development and validation. Then, the backpropagation neural network with designed structure was employed to perform data fitting for test conditions. After the analysis of parameter distribution tendency, the two-step interpolation method was used to generalize performance parameters under conditions apart from those test ones. The cross-condition prediction accuracy of developed engine model was validated by test data under various operating conditions. Also, the parameter prediction error of proposed modeling method was lower compared to that of existing neural network methods, which further proved its applicability to dynamic engine modeling issues.

scholarly journals Optimal Tuner Selection for Kalman Filter-Based Aircraft Engine Performance Estimation

2009 ◽  
Vol 132 (3) ◽  
Author(s):  
Donald L. Simon ◽  
Sanjay Garg
Keyword(s):  
Kalman Filter ◽  
Estimation Error ◽  
Engine Performance ◽  
Aircraft Engine ◽  
Operating Conditions ◽  
Performance Estimation ◽  
Experimental Simulation ◽  
Tuning Parameter ◽  
Estimation Accuracy ◽  
On Line

A linear point design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multivariable iterative search routine that seeks to minimize the theoretical mean-squared estimation error. This paper derives theoretical Kalman filter estimation error bias and variance values at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared with the conventional approach of tuner selection. Experimental simulation results are found to be in agreement with theoretical predictions. The new methodology is shown to yield a significant improvement in on-line engine performance estimation accuracy.

scholarly journals A New Method to Determine the Impact of Individual Field Quantities on Cycle-to-Cycle Variations in a Spark-Ignited Gas Engine

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4136
Author(s):  
Clemens Gößnitzer ◽  
Shawn Givler
Keyword(s):  
Kinetic Energy ◽  
Flow Field ◽  
Turbulent Kinetic Energy ◽  
Negative Impact ◽  
Operating Conditions ◽  
Engine Operation ◽  
Gas Engine ◽  
Cycle Simulation ◽  
Simulation Results ◽  
The Impact

Cycle-to-cycle variations (CCV) in spark-ignited (SI) engines impose performance limitations and in the extreme limit can lead to very strong, potentially damaging cycles. Thus, CCV force sub-optimal engine operating conditions. A deeper understanding of CCV is key to enabling control strategies, improving engine design and reducing the negative impact of CCV on engine operation. This paper presents a new simulation strategy which allows investigation of the impact of individual physical quantities (e.g., flow field or turbulence quantities) on CCV separately. As a first step, multi-cycle unsteady Reynolds-averaged Navier–Stokes (uRANS) computational fluid dynamics (CFD) simulations of a spark-ignited natural gas engine are performed. For each cycle, simulation results just prior to each spark timing are taken. Next, simulation results from different cycles are combined: one quantity, e.g., the flow field, is extracted from a snapshot of one given cycle, and all other quantities are taken from a snapshot from a different cycle. Such a combination yields a new snapshot. With the combined snapshot, the simulation is continued until the end of combustion. The results obtained with combined snapshots show that the velocity field seems to have the highest impact on CCV. Turbulence intensity, quantified by the turbulent kinetic energy and turbulent kinetic energy dissipation rate, has a similar value for all snapshots. Thus, their impact on CCV is small compared to the flow field. This novel methodology is very flexible and allows investigation of the sources of CCV which have been difficult to investigate in the past.

scholarly journals Simulation Research of Aircraft Piston Engine Rotax 912

2019 ◽  
Vol 252 ◽  
pp. 05007 ◽  
Author(s):  
Łukasz Grabowski ◽  
Ksenia Siadkowska ◽  
Krzysztof Skiba
Keyword(s):  
Combustion Process ◽  
Engine Performance ◽  
Aircraft Engine ◽  
Basic Unit ◽  
Piston Engine ◽  
Engine Operation ◽  
Simulation Research ◽  
One Dimensional ◽  
Operation Process ◽  
Model Aircraft

This paper reports the results of simulation works of Rotax 912 aircraft piston engine, which is a basic unit in most ultra-light aircrafts. The method for preparing the model aircraft engine operation process was presented. Simulation tests were carried out in the AVL Boost programme. The programme allows a full use of zero-dimensional and one-dimensional modelling. It also allows a comparison of other engine models. The developed model has enabled us to simulate the flow of air through the inlet pipes, carburettors, valves and combustion process. The preparation of the model required us to enter parameters that are not available in the manufacturer's catalogue, therefore, necessary measurements and analysis of the engine parts were carried out on a laboratory bench. The calculations in the AVL Boost programme were carried out in the conditions determined for the selected BMEP values with the objective of characterising the engine performance by determining its power, torque and fuel consumption.

Assessing Double Injection and Intake Air Temperature Effects on Gasoline HCCI Engine Performance and Emissions Using Fully-Automated Experiments and Micro-Genetic Algorithms

2002 ◽  
Author(s):  
Mustafa Canakci ◽  
Eric Hruby ◽  
Rolf D. Reitz
Keyword(s):  
Air Temperature ◽  
Gasoline Engine ◽  
Engine Performance ◽  
Operating Conditions ◽  
Spray Angle ◽  
Injection Timing ◽  
Engine Operation ◽  
Double Injection ◽  
Performance And Emissions ◽  
Engine Performance And Emissions

Homogeneous charge compression ignition (HCCI) is receiving attention as a new low emission engine concept. Little is known about the optimal operating conditions for this engine operation mode. Combustion at homogeneous, low equivalence ratio conditions results in modest temperature combustion products, containing very low concentrations of NOx and PM as well as providing high thermal efficiency. However, this combustion mode can produce higher HC and CO emissions than those of conventional engines. An electronically controlled Caterpillar single-cylinder oil test engine (SCOTE), originally designed for heavy-duty diesel applications, was converted to a HCCI direct-injection gasoline engine. The engine features an electronically controlled low-pressure common rail injector with a 60°-spray angle that is capable of multiple injections. The use of double injection was explored for emission control, and the engine was optimized using fully-automated experiments and a micro-genetic algorithm (μGA) optimization code. The variables changed during the optimization include the intake air temperature, start of injection timing, and split injection parameters (percent mass of the fuel in each injection, dwell between the pulses). The engine performance and emissions were determined at 700 rev/min with a constant fuel flow rate at 10 MPa fuel injection pressure. The results show that significant emissions reductions are possible with the use of optimal injection strategies.

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