Estimation of Default Probabilities - Part 1: The Mean Value Model

2003 ◽  
Author(s):  
Uwe Wehrspohn
Keyword(s):  
Mean Value ◽  
Mean Value Model ◽  
The Mean ◽  
Value Model

Physics-Based Control Oriented Mean Value Model for Diesel Combustion Process With EGR Sensitivity

2011 ◽  
Author(s):  
Byungchan Lee ◽  
Dohoy Jung ◽  
Yong-Wha Kim
Keyword(s):  
Heat Transfer ◽  
Combustion Process ◽  
Mean Value ◽  
Diesel Combustion ◽  
Design Development ◽  
Combustion Heat ◽  
Mean Value Model ◽  
Pressure Cycle ◽  
The Mean ◽  
Value Model

A Physics-based mean value model that predicts engine combustion, heat transfer, gas exchange, and friction loss has been developed. The model is developed starting from the thermodynamic principles of an ideal gas standard limited pressure cycle concept. The idealized assumptions that are typically used in a limited pressure cycle concept are relieved to enhance the fidelity of the model by introducing variables that account for the in-cylinder heat transfer and the combustion characteristics that change under varying EGR rate as well as the engine speed and load while minimal number of empirical correlations are used to ensure the compactness and flexibility of the physics-based mean value model. The model is calibrated and validated with the simulation results from a detailed GT-Power® engine model previously calibrated with experimental results from a Ford 6.7 liter Diesel engine. The comparison shows good agreement between the results from the mean value model and the GT-Power® model. The mean value model developed in this study is a flexible simulation tool that provides excellent computational efficiency without sacrificing critical physical details of the Diesel combustion process required by the control design development.

scholarly journals Diesel Mean Value Engine Modeling Based on Thermodynamic Cycle Simulation Using Artificial Neural Network

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2823 ◽  
Author(s):  
Eunhee Ko ◽  
Jungsoo Park
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Mean Value ◽  
Volumetric Efficiency ◽  
Exhaust Gas ◽  
Control Logic ◽  
Mean Value Model ◽  
The Mean ◽  
Artificial Neural ◽  
Value Model

This study aims to construct a reduced thermodynamic cycle model with high accuracy and high model execution speed based on artificial neural network training for real-time numerical analysis. This paper proposes a method of constructing a fast average-value model by combining a 1D plant model and exhaust gas recirculation (EGR) control logic. The combustion model of the detailed model uses a direct-injection diesel multi-pulse (DI-pulse) method similar to diesel combustion characteristics. The DI-pulse combustion method divides the volume of the cylinder into three zones, predicting combustion- and emission-related variables, and each combustion step comprises different correction variables. This detailed model is estimated to be within 5% of the reference engine test results. To reduce the analysis time while maintaining the accuracy of engine performance prediction, the cylinder volumetric efficiency and the exhaust gas temperature were predicted using an artificial neural network. Owing to the lack of input variables in the training of artificial neural networks, it was not possible to predict the 0.6–0.7 range for volumetric efficiency and the 1000–1200 K range for exhaust gas temperature. This is because the mean value model changes the fuel injection method from the common rail fuel injection mode to the single injection mode in the model reduction process and changes the in-cylinder combustion according to the injection timing of the fuel amount injected. In addition, the mean value model combined with EGR logic, i.e., the single-input single-output (SISO) coupled mean value model, verifies the accuracy and responsiveness of the EGR control logic model through a step-transient process. By comparing the engine performance results of the SISO coupled mean value model with those of the mean value model, it is observed that the SISO coupled mean value model achieves the desired target EGR rate within 10 s. The EGR rate is predicted to be similar to the response of volumetric efficiency. This process intuitively predicted the main performance parameters of the engine model through artificial neural networks.

A Mean-Value Model of a Turbocharged HCCI Diesel Engine with External Mixture Formation

2005 ◽  
Author(s):  
M. Canova ◽  
L. Garzarella ◽  
M. Ghisolfi ◽  
S. Midlam-Mohler ◽  
Y. Guezennec ◽  
...  
Keyword(s):  
Diesel Engine ◽  
Mean Value ◽  
Mixture Formation ◽  
Mean Value Model ◽  
Value Model

The Use of a Mean Value Model to Achieve the Best Efficiency of a Variable Speed Generator Coupled to a Diesel Engine

2012 ◽  
Author(s):  
Augusto F. Pacheco ◽  
Jonas R. Tibola ◽  
Mario E. S. Martins ◽  
Paulo R. M. Machado ◽  
Humberto Pinheiro ◽  
...  
Keyword(s):  
Diesel Engine ◽  
Mean Value ◽  
Variable Speed ◽  
Mean Value Model ◽  
Value Model

scholarly journals A Mean-Value Model for Control of Homogeneous Charge Compression Ignition (HCCI) Engines

2004 ◽  
Vol 127 (3) ◽  
pp. 355-362 ◽  
Author(s):  
D. J. Rausen ◽  
A. G. Stefanopoulou ◽  
J.-M. Kang ◽  
J. A. Eng ◽  
T.-W. Kuo
Keyword(s):  
Mass Flow ◽  
Homogeneous Charge Compression Ignition ◽  
Mean Value ◽  
The State ◽  
State Of Charge ◽  
Inert Gas ◽  
Compression Ignition ◽  
Hcci Engines ◽  
Mean Value Model ◽  
Value Model

A Mean Value Model (MVM) for a Homogeneous Charge Compression Ignition (HCCI) engine is presented. Using a phenomenological zero-dimensional approach with five continuous and three discrete states we first model the effects of the Exhaust Gas Recirculation (EGR) valve, the exhaust Rebreathing Lift (RBL), and the fueling rate on the state of charge in the cylinder at intake valve closing. An Arrhenius integral is then used to model the start of combustion, θsoc. A series of simple algebraic relations that captures the combustion duration and heat release is finally used to model the state of charge after the HCCI combustion and the Location of Peak Pressure (LPP). The model is parametrized and validated using steady-state test data from an experimental gasoline engine at the General Motors Corporation. The simple model captures the temperature, pressure, air-to-fuel ratio, and inert gas fraction of the exhausted mass flow. This characterization is important for the overall HCCI dynamics because the thermodynamic state (pressure, temperature) and concentration (oxygen and inert gas) of the exhausted mass flow affect the next combustion event. The high dilution level in HCCI engines increases the significance of this internal feedback that generally exists to a smaller extent in conventional spark-ignition and compression-ignition internal combustion engines.

Model and Calibration of a Diesel Engine Air Path With an Asymmetric Twin Scroll Turbine

2013 ◽  
Author(s):  
Mike J. Hand ◽  
Erik Hellström ◽  
Doohyun Kim ◽  
Anna Stefanopoulou ◽  
Justin Kollien ◽  
...  
Keyword(s):  
Diesel Engine ◽  
System Analysis ◽  
Flow Characteristics ◽  
Load Condition ◽  
Mean Value ◽  
Complex Flow ◽  
Transient Control ◽  
Mean Value Model ◽  
Value Model ◽  
And Control

A control-oriented model and its associated tuning methodology is presented for the air path of a six cylinder 13 L diesel engine equipped with an asymmetric twin-scroll turbine, wastegate (WG), and exhaust gas recirculation (EGR). This model is validated against experimental engine data and shows good agreement. The small scroll of the asymmetric twin scroll turbine is fed by the exhaust of three cylinders via a split manifold that operates at higher pressure than the exhaust manifold feeding the larger turbine scroll. The asymmetric design with the high exhaust back pressure on three of the six cylinders gives the necessary EGR capability, with reduced pumping work, but leads to complex flow characteristics. The mean-value model describes the flows through the engine, the flow through the two turbine scrolls, the EGR flow, and the WG flow as they are defined, and defines the pressure of the manifolds they connect to. Using seven states that capture the dynamics of the pressure and composition in the manifolds and the speed of the turbo shaft, the model can be used for transient control, along with set point optimization for the EGR and WG flows for each speed and load condition. The relatively low order of the model makes it amenable to fast simulations, system analysis, and control design.

scholarly journals Calibration and Validation of a Mean Value Model for Turbocharged Diesel Engine

2013 ◽  
Vol 5 ◽  
pp. 579503 ◽  
Author(s):  
Ruixue Li ◽  
Ying Huang ◽  
Gang Li ◽  
Kai Han ◽  
He Song
Keyword(s):  
Diesel Engine ◽  
Mean Value ◽  
Turbocharged Diesel Engine ◽  
Calibration And Validation ◽  
Mean Value Model ◽  
Value Model
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