A Model for the Estimation of Inducted Air Mass and the Residual Gas Fraction using Cylinder Pressure Measurements

2000 ◽  
Author(s):  
Michael Mladek ◽  
Christopher H. Onder
Keyword(s):  
Pressure Measurements ◽  
Cylinder Pressure ◽  
Air Mass ◽  
Residual Gas Fraction ◽  
Residual Gas

scholarly journals Prediction Modeling and Analysis of Knocking Combustion using an Improved 0D RGF Model and Supervised Deep Learning

Energies ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 844 ◽  
Author(s):  
Seokwon Cho ◽  
Jihwan Park ◽  
Chiheon Song ◽  
Sechul Oh ◽  
Sangyul Lee ◽  
...  
Keyword(s):  
Deep Learning ◽  
System Analysis ◽  
Combustion Engine ◽  
Cylinder Pressure ◽  
Estimation Model ◽  
Experimental Conditions ◽  
Modeling And Analysis ◽  
Residual Gas Fraction ◽  
Residual Gas ◽  
The Individual

The knock phenomenon is one of the major hindrances for enhancing the thermal efficiency in spark-ignited engines. Due to the stochastic behavior of knocking combustion, analytical cycle studies are required. However, there are many problems to be addressed with regard to the individual cycle analysis of in-cylinder pressure data. This study thus proposes novel, comprehensive and efficient methodologies for evaluating the knocking combustion in the internal combustion engine. The proposed methodologies include a filtering method for the in-cylinder pressure, the determination of the knock onset, and the calculation of the residual gas fraction. Consequently, a smart knock onset model with high accuracy could be developed using a supervised deep learning that was not available in the past. Moreover, an improved zero-dimensional (0D) estimation model for the residual gas fraction was developed to obtain better accuracy for closed system analysis. Finally, based on a cyclic analysis, a knock prediction model is suggested; the model uses 0D ignition delay correlation under various experimental conditions including aggressive cam phase shifting by a dual variable valve timing (VVT) system. Using the proposed analysis method, insight into stochastic knocking combustion can be obtained, and a faster combustion speed can lead to a higher knock intensity in a steady-state operation.

Air Charge and Residual Gas Fraction Estimation for a Spark-Ignition Engine Using In-Cylinder Pressure

2017 ◽  
Author(s):  
Arya Yazdani ◽  
Jeffrey Naber ◽  
Mahdi Shahbakhti ◽  
Paul Dice ◽  
Chris Glugla ◽  
...  
Keyword(s):  
Spark Ignition ◽  
Spark Ignition Engine ◽  
Cylinder Pressure ◽  
Residual Gas Fraction ◽  
Residual Gas

An On-Line Model for Predicting Residual Gas Fraction by Measuring Intake/Exhaust and Cylinder Pressure in CAI Engine

2008 ◽  
Author(s):  
Seungmok Choi ◽  
Minyoung Ki ◽  
Kyoungdoug Min ◽  
Jinkook Kong ◽  
Kyoungjoon Chang ◽  
...  
Keyword(s):  
Cylinder Pressure ◽  
Line Model ◽  
On Line ◽  
Residual Gas Fraction ◽  
Residual Gas

Two-Stroke Marine Diesel Engine Variable Injection Timing System Performance Evaluation and Optimum Setting for Minimum Fuel Consumption at Acceptable NOx Levels

2014 ◽  
Author(s):  
Dimitrios T. Hountalas ◽  
Spiridon Raptotasios ◽  
Antonis Antonopoulos ◽  
Stavros Daniolos ◽  
Iosif Dolaptzis ◽  
...  
Keyword(s):  
Diesel Engine ◽  
Fuel Consumption ◽  
Engine Performance ◽  
Operating Conditions ◽  
Specific Fuel Consumption ◽  
Injection Timing ◽  
Nox Emissions ◽  
Pressure Measurements ◽  
Cylinder Pressure ◽  
Start Of Injection

Currently the most promising solution for marine propulsion is the two-stroke low-speed diesel engine. Start of Injection (SOI) is of significant importance for these engines due to its effect on firing pressure and specific fuel consumption. Therefore these engines are usually equipped with Variable Injection Timing (VIT) systems for variation of SOI with load. Proper operation of these systems is essential for both safe engine operation and performance since they are also used to control peak firing pressure. However, it is rather difficult to evaluate the operation of VIT system and determine the required rack settings for a specific SOI angle without using experimental techniques, which are extremely expensive and time consuming. For this reason in the present work it is examined the use of on-board monitoring and diagnosis techniques to overcome this difficulty. The application is conducted on a commercial vessel equipped with a two-stroke engine from which cylinder pressure measurements were acquired. From the processing of measurements acquired at various operating conditions it is determined the relation between VIT rack position and start of injection angle. This is used to evaluate the VIT system condition and determine the required settings to achieve the desired SOI angle. After VIT system tuning, new measurements were acquired from the processing of which results were derived for various operating parameters, i.e. brake power, specific fuel consumption, heat release rate, start of combustion etc. From the comparative evaluation of results before and after VIT adjustment it is revealed an improvement of specific fuel consumption while firing pressure remains within limits. It is thus revealed that the proposed method has the potential to overcome the disadvantages of purely experimental trial and error methods and that its use can result to fuel saving with minimum effort and time. To evaluate the corresponding effect on NOx emissions, as required by Marpol Annex-VI regulation a theoretical investigation is conducted using a multi-zone combustion model. Shop-test and NOx-file data are used to evaluate its ability to predict engine performance and NOx emissions before conducting the investigation. Moreover, the results derived from the on-board cylinder pressure measurements, after VIT system tuning, are used to evaluate the model’s ability to predict the effect of SOI variation on engine performance. Then the simulation model is applied to estimate the impact of SOI advance on NOx emissions. As revealed NOx emissions remain within limits despite the SOI variation (increase).

Machine Learning Integration with Combustion Physics to Develop a Composite Predictive Model for Reactivity Controlled Compression Ignition Engine

2021 ◽  
pp. 1-27
Author(s):  
Chinmaya Mishra ◽  
P.M.V. Subbarao
Keyword(s):  
Machine Learning ◽  
Predictive Model ◽  
Alternative Methods ◽  
Compression Ignition ◽  
Combustion Control ◽  
Reactivity Controlled Compression Ignition ◽  
Operating Condition ◽  
Residual Gas Fraction ◽  
Residual Gas ◽  
Engine Operating Condition

Abstract Phasing of combustion metrics close to the optimum values across operation range is necessary to avail benefits of reactivity controlled compression ignition (RCCI) engines. Parameters like start of combustion occurrence crank angle (θsoc), occurrence of burn rate fraction reaching 50% (θ50), mean effective pressure from indicator diagram (IMEP) etc. are described as combustion metrics. These metrics act as markers for macroscopic state of combustion. Control of these metrics in RCCI engine is relatively complex due to the nature of ignition. As direct combustion control is challenging, alternative methods like combustion physics derived models are a subject of research interest. In this work, a composite predictive model was proposed by integrating trained random forest (RF) machine learning and artificial neural networks (ANN) to combustion physics derived modified Livengood-Wu integral, parametrized double-Wiebe function, autoignition front propagation speed based correlations and residual gas fraction model. The RF machine learning established a correlative relationship between physics based model coefficients and engine operating condition. The ANN developed a similar correlation between residual gas fraction parameters and engine operating condition. The composite model was deployed for the predictions of θsoc, θ50 and IMEP as RCCI engine combustion metrics. Experimental validation showed an error standard deviation (θ68.3,err) of 0.67 °CA, 1.19°CA, 0.223 bar and symmetric mean absolute percentage error of 6.92%, 7.87% and 4.01% for the predictions of θsoc, θ50 and IMEP respectively on cycle to cycle basis. Wide range applicability, lesser experiments for model calibration, low computational costs and utility for control applications were the benefits of the proposed predictive model.

TWO OBSERVERS FOR IN-CYLINDER MASS ESTIMATION USING CYLINDER PRESSURE MEASUREMENTS

2007 ◽  
Vol 40 (10) ◽  
pp. 219-226 ◽  
Author(s):  
P. Giansetti ◽  
G. Colin ◽  
Y. Chamaillard ◽  
P. Higelin
Keyword(s):  
Pressure Measurements ◽  
Cylinder Pressure ◽  
Mass Estimation

scholarly journals Comparative Study of the Effective Release Energy, Residual Gas Fraction, and Emission Characteristics with Various Valve Port Diameter-Bore Ratios (VPD/B) of a Four-Stroke Spark Ignition Engine

Energies ◽  
2020 ◽  
Vol 13 (6) ◽  
pp. 1330 ◽  
Author(s):  
Nguyen Xuan Khoa ◽  
Ocktaeck Lim
Keyword(s):  
Load Condition ◽  
Experimental System ◽  
Optimization Method ◽  
Spark Ignition ◽  
Spark Ignition Engine ◽  
Pressure Increase ◽  
Intake Port ◽  
Exhaust Port ◽  
Residual Gas Fraction ◽  
Residual Gas

In this research, the residual gas, peak firing pressure increase, and effective release energy were completely investigated. To obtain this target, the experimental system is installed with a dynamo system and a simulation model was setup. Through combined experimental and simulation methods, the drawbacks of the hardware optimization method were eliminated. The results of the research show that the valve port diameter-bore ratio (VPD/B) has a significant effect on the residual gas, peak firing pressure increase, and effective release energy of a four-stroke spark ignition engine. In this research, the engine was performed at 3000 rpm and full load condition. Following increased IPD/B ratio of 0.3–0.5. The intake port and exhaust port diameter has a contrary effect on engine volumetric efficiency, the residual gas ratio increase 27.3% with larger intake port and decrease 18.6% with larger exhaust port. The engine will perform optimal thermal efficiency when the trapped residual gas fraction ratio is from 13% to 14%. The maximum effective release energy was 0.45 kJ at 0.4 intake port-bore ratio, and 0.451 kJ at 0.35 exhaust port-bore ratio. The NOx emission increases until achieved a maximum value after that decrease even VPD/B was still increasing. With a VPD/B ratio of 0.35 to 0.4, the engine works without the misfiring.

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