Optimal Control Strategy for a Pressure-Wave Supercharged SI Engine

2003 ◽  
Author(s):  
Peter Spring ◽  
Lino Guzzella ◽  
Christopher H. Onder
Keyword(s):  
Pressure Wave ◽  
Mean Value ◽  
Spark Ignition Engine ◽  
Exhaust Gas ◽  
Optimal Control Strategy ◽  
Engine Torque ◽  
Torque Response ◽  
Steady Rate ◽  
Mean Value Model ◽  
Value Model

On the basis of a control-oriented mean-value model of a spark-ignition engine supercharged with a pressure-wave supercharger, this paper introduces an operation strategy which minimizes the torque response time to driver commands. Since in pressure-wave superchargers fresh air and exhaust gas are in direct contact in the cell wheel, unwanted and excessive exhaust gas recirculation over the pressure-wave supercharger has to be limited by appropriate control actions. The most critical situation arises when large amounts of exhaust gas are recirculated during a hard acceleration, which causes the engine torque to drop sharply and thus to severely affect driveability. In order to prevent such situations, a set of actuators (throttles, valves, etc.) has to be controlled in a coordinated way. Conventional strategies cause the actuators to be closed at a fairly slow, steady rate. Our investigations show that driveability can be improved with a somewhat more complex strategy.

A Mean-Value Model of Internal Combustion Engine Based on Variable Valve Phase Timing

2012 ◽  
Author(s):  
S. M. Navid Khatami ◽  
Olusegun J. Ilegbusi
Keyword(s):  
Gas Exchange ◽  
Phase Angle ◽  
Combustion Engine ◽  
Mean Value ◽  
Operating Conditions ◽  
Spark Ignition Engine ◽  
Wide Range ◽  
Mean Value Model ◽  
Variable Valve ◽  
Value Model

A simplified Mean-Value Model (MVM) is developed to represent spark ignition engine functions. The model is based on variable valve phase angle over a wide range of operating conditions. Gas exchange dynamics is simulated to determine the mass air flow into the cylinder. This flow is altered by variable valve phase mechanism. In this paper, phasing the exhaust and intake valves is considered equally (dual equal) and is equipped with hydraulics Continuous Variable Valve Timing (CVVT) mechanism. The model developed reflects these modifications and uses gas exchange dynamics to capture valve phase, manifold pressure, and engine rotating speed. The values of flow rates from this simplified mathematical model is compared and validated with engine-dynamometer experimental data. The results show strong agreement in a wide range of operating points while the variation of phase angle is limited to nominal values.

scholarly journals A MEAN VALUE MODEL FOR ESTIMATION OF LAMINAR AND TURBULENT FLAME SPEED IN SPARK-IGNITION ENGINE

2015 ◽  
Vol 11 ◽  
pp. 2224-2234 ◽  
Author(s):  
Ali Ghanaati ◽  
◽  
Intan Z. Mat Darus ◽  
Mohd Farid Muhamad Said ◽  
Amin Mahmoudzadeh Andwari ◽  
...  
Keyword(s):  
Turbulent Flame ◽  
Spark Ignition ◽  
Mean Value ◽  
Flame Speed ◽  
Spark Ignition Engine ◽  
Turbulent Flame Speed ◽  
Mean Value Model ◽  
Value Model

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.

Control-Oriented Mean-Value Model of a Fuel-Flexible Turbocharged Spark Ignition Engine

2010 ◽  
Author(s):  
Thomas Coppin ◽  
Olivier Grondin ◽  
Guenael Le Solliec ◽  
Laurent Rambault ◽  
Nezha Maamri
Keyword(s):  
Spark Ignition ◽  
Mean Value ◽  
Spark Ignition Engine ◽  
Mean Value Model ◽  
Value Model

Analysis on Mean Value Model of Gasoline Engine in HEV Applications

2011 ◽  
Vol 464 ◽  
pp. 299-302
Author(s):  
Jian Hao Zhou ◽  
Yin Nan Yuan ◽  
Gong Ping Mao ◽  
Jia Yi Du
Keyword(s):  
Engine Speed ◽  
Gasoline Engine ◽  
Mean Value ◽  
Fuel Film ◽  
Engine Torque ◽  
Film Model ◽  
Mean Value Model ◽  
Value Model ◽  
Operating Points ◽  
Speed Engine

A mean value model of the 1.5L gasoline engine was established. It mainly consists of fuel film model, transient fuel film compensation model and dynamic output model. After the validation of steady state, the power and economic performances were analyzed with NEDC drive cycle. Together with engine operating points, special attention was such key parameters as paid to engine speed, engine torque and fuel consumption. The dynamic model is validated. The air-fuel ratio fluctuation was studied to validate the fuel film model.

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
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