Model-based predictive control of an Electro-Pneumatic exhaust valve for Internal Combustion engines

Author(s):  
Jia Ma ◽  
Guoming Zhu ◽  
Andrew Hartsig ◽  
Harold Schock
MTZ worldwide ◽  
2015 ◽  
Vol 76 (4) ◽  
pp. 24-29 ◽  
Author(s):  
Stefan Hoffmann ◽  
Michael Schrott ◽  
Thorsten Huber ◽  
Thomas Kruse

2020 ◽  
Vol 5 (2) ◽  
pp. 118-123
Author(s):  
Van Viet Pham

Along with the development of internal combustion engines, camshafts have also been developed to optimize engine performance. In all types of internal combustion engines, the crankshaft is connected to the camshaft via a toothed belt, chain or pinion. When the crankshaft turns, the camshaft spins and opens and closes the intake and exhaust valve respectively. However, in this non-camshaft engine technology, each intake and exhaust valve will be integrated with an electronically controlled hydraulic pump unit. This system provides a unique ability to independently control intake and exhaust valves. For any engine load, load and discharge times can be programmed independently. The decision system is based on driving conditions, used to maximize performance or minimize fuel consumption and emissions. This allows a greater degree of control over the engine which in turn provides significant performance benefits. This article presents reviews of camshaftless technology developed by VALEO. It is a system that uses solenoid valves to open and close the valve. The solenoid valve will be mounted right on top of the valve inside the engine. The author can see that the technology using this electronic control valve will help reduce the fuel consumption of the engine.


MTZ worldwide ◽  
2003 ◽  
Vol 64 (6) ◽  
pp. 30-32 ◽  
Author(s):  
Kosmas Knödler ◽  
Jan Poland ◽  
Thomas Fleischhauer ◽  
Alexander Mitterer ◽  
Stephan Ullmann ◽  
...  

Author(s):  
Yue-Yun Wang ◽  
Ibrahim Haskara

Engine exhaust backpressure is a critical parameter in the calculation of the volumetric efficiency and exhaust gas recirculation flow of an internal combustion engine. The backpressure also needs to be controlled to a presetting limit under high speed and load engine operating conditions to avoid damaging a turbocharger. In this paper, a method is developed to estimate exhaust pressure for internal combustion engines equipped with variable geometry turbochargers. The method uses a model-based approach that applies a coordinate transformation to generate a turbine map for the estimation of exhaust pressure. This estimation can substitute for an expensive pressure sensor, thus saving significant cost for production vehicles. On the other hand, for internal combustion engines that have already installed exhaust pressure sensors, this estimation can be used to generate residual signals for model-based diagnostics. Cumulative sum algorithms are applied to residuals based on multiple sensor fusion, and with the help of signal processing, the algorithms are able to detect and isolate critical failure modes of a turbocharger system.


2018 ◽  
Vol 23 (15) ◽  
pp. 6169-6182
Author(s):  
Tohid Sardarmehni ◽  
Arya Aghili Ashtiani ◽  
Mohammad Bagher Menhaj

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Kai Liang ◽  
Haijun Zhao

To improve the accuracy and efficiency of the objective evaluation of noise quality from internal combustion engines, an automatic noise quality classification model was constructed by introducing an auditory model-based acoustic spectrum analysis method and a convolutional neural network (CNN) model. A band-pass filter was also designed in the model to automatically extract the features of the noise samples, which were later used as input data. The adaptive moment estimation (Adam) algorithm was used to optimize the weights of each layer in the network, and the model was used to evaluate sound quality. To evaluate the predictive performance of the CNN model based on the auditory input, a back propagation (BP) sound quality evaluation model based on psychoacoustic parameters was constructed and used as a control. When processing the label values of the samples, the correlation between the psychoacoustic parameters of the objective evaluation and evaluation scores was analyzed. Four psychoacoustic parameters with the greatest correlation with subjective evaluation results were selected as the input values of the BP model. The results showed that the sound quality evaluation model based on the CNN could predict the sound quality of internal combustion engines more accurately, and the input evaluation score based on the auditory spectrum in the CNN classification model was more accurate than the short-time average energy input evaluation score based on the time domain.


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