Data-Driven Modeling and UFIR-Based Outlet NO$_{x}$ Estimation for Diesel-Engine SCR Systems

Jiang, Kai; Yan, Fengjun; Zhang, Hui

doi:10.1109/tie.2019.2924880

Cited by 9 publications

(7 citation statements)

References 37 publications

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“…In order to accurately characterize the combustion process and provide the exit gas enthalpy needed for the exhaust manifold gas exchange sub-model, the total heat loss of the combustion event had to be taken into account. In this work, the combustion heat transfer model, Q comb, loss is based on the Woschni correlation 33 and given by equation (19). Heat loss to the walls by conduction was assumed to be negligible, and the wall temperature (T wall ) was also assumed to be the arithmetic mean of the coolant and measured exhaust gas temperature.…”

Section: Engine Cylinder Modelmentioning

confidence: 99%

“…In the past, data-driven models have been used to capture emissions from diesel engines [16][17][18] and aftertreatment systems. 19 They have also been applied to whole engine systems to predict emissions as well as variables including power, torque, efficiency, and fuel consumption based on characteristics like engine speed, injection timing, and fuel and air properties. [20][21][22][23] From these prior studies, it is clear that neural networks can capture the overall performance of these systems.…”

Section: Introductionmentioning

confidence: 99%

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On the integration of physics-based and data-driven models for the prediction of gas exchange processes on a modern diesel engine

Gonzalez

Ankobea-Ansah

Peng

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part D:

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The need for precise control of complex air handling systems on modern engines has driven research into model-based methods. While model-based control can provide improved performance over prior map-based methods, they require the creation of an accurate model. Physics-based models can be precise, but can also be computationally expensive and require extensive calibration. To address this limitation, this work explores the integration of data-driven models into an overall physics-based framework and applies this approach to the gas exchange processes of a diesel engine with a variable geometry turbocharger and exhaust gas recirculation. One of the most complex parts of this gas exchange loop is the turbocharger. Data-driven methods are used to capture the turbocharger performance and are also applied to the intake manifold, while the simpler features are captured with more traditional physics-based models. This combined modeling approach is able to capture the temperature and pressure dynamics with varying error levels depending on measurement availability and the inter-dependency of the submodels, with the turbocharger neural network model achieving a Normalized Mean Square Error (NMSE) of 5e-5 and the overall engine model achieving a NMSE of 4.5e-3. The work illustrates that the integration of data-driven models can improve overall model accuracy and may be able to reduce the number of sensors needed on the system. The contributions of this work are the development and demonstration of a neural network based turbocharger model and intake air path model, the development of empirical equation-based models for the rest of the engine components along the air path and the demonstration of the integration and interaction of these two types of model to adequately characterize engine operation for control applications.

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Section: Engine Cylinder Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On the integration of physics-based and data-driven models for the prediction of gas exchange processes on a modern diesel engine

Gonzalez

Ankobea-Ansah

Peng

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part D:

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“…According to the conclusion of Figures 12 and 13, the angle between the nozzle jet direction and the target surface (automobile surface) is 30°. Under the same condition of washing the automobile, the following conclusions can be drawn through the comparison before and after the renovation: (1) e water consumption after the renovation is saved by about 46% compared with that before the renovation, thus solving the problem of large water consumption on-site. (2) e distance between nozzles before modification is too small, resulting in serious cross interference of water jets between adjacent nozzles, and the utilization rate of nozzle water jet washing capacity is greatly reduced as shown in Figure 20.…”

Section: Relationship Between Target Distance and Shooting Width Under Different Jet Anglesmentioning

confidence: 96%

“…With the development of society, the number of automobiles is increasing rapidly, and the related research on vehicle maintenance is increasing day by day [1,2]. Among them, the daily washing quantity and frequency are more numerous [3].…”

Section: Introductionmentioning

confidence: 99%

Research on the Influence of External Parameters of Fan-Type Nozzle on Water Jet Performance

Kou

Huo

Hou

2020

Shock and Vibration

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At present, high-pressure water jet technology occupies a very important position in the automobile washing industry. Some automatic washers cannot meet the washing requirements in the washing process due to unreasonable arrangement of nozzles on their spray rods. Based on the theory of computational fluid dynamics (CFD), the internal and external flow field model of the nozzle are established in this paper. Fluent is used to simulate and analyze the flow field, and the external parameters of the nozzle on the side spray bar of the automatic automobile washer are optimized. The simulation results show that after the nozzle and the normal line of the automobile surface are inclined at a certain angle, the target surface is affected not only by normal striking force but also by tangential pushing force, which makes stains easier to remove. The washing effect is the best when the nozzle is inclined 30° to the normal line of the automobile surface. Increasing the nozzle inlet pressure will increase the dynamic pressure on the automobile surface, but the increase of dynamic pressure will decrease after increasing to a certain pressure. The inlet pressure has little effect on the area covered by water jet. The reasonable matching results of jet angle, nozzle spacing, and nozzle distance from the automobile surface (target distance) obtained by numerical simulation can not only make the automobile surface completely covered and cleaned but also ensure less jet interference and no waste of water from adjacent nozzles. The above research conclusions can provide a basic theoretical basis for the optimal design of automatic automobile washing.

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“…p i and r j are regression coefficient vectors in step i and j. Y A is the residual matrix of the A-1 regression equation obtained by iteration. The coefficients of several local linear sub-models can be obtained through the PLS algorithm:½b 1 b 2 :::b n , According to the previous membership degree, the sub-models with different weights are combined to obtain the overall regression model (Jiang et al, 2019):…”

Section: Grey Box Model Of Solenoid Valve Based On Arx Modelmentioning

confidence: 99%

Experimental and numerical validation of a proportional solenoid valve based on the data-driven model

Jiang

Ren

et al. 2021

Transactions of the Institute of Measurement and Control

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Solenoid valves are widely used in mechatronics, robotic systems and industrial occasions. An accurate model is very important for the design and control of a solenoid valve. The dynamical model of the solenoid valve is difficult to obtain due to the complexity of the structure and the interaction of multiple physical fields. This paper proposes two kinds of model of solenoid valve: grey box model and black box model, on the basis of experimental data. ARX model is selected as the basic structure of the grey box model. After clustering the data with the fuzzy c-means algorithm, the overall experimental data is divided into several local linear sub-models, and the model coefficients of the local linear model are obtained by partial least square regression. The overall expression of the model is obtained by combining the local sub-models with membership degree. For the black box model, support vector regression algorithm is used to identify. On the basis of selecting the appropriate parameters, we obtain the black box model of solenoid valve based on data. For the above two models, we carry out experimental verification and error analysis, and compare with the traditional modelling method. According to the results, it can be seen that on the basis of the experimental data, using the data-driven method to construct the model has many advantages, avoiding complex physical analysis, and has high accuracy. The model with high precision will be used in the accurate control and observing estimation of the solenoid valve.

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Data-Driven Modeling and UFIR-Based Outlet NO$_{x}$ Estimation for Diesel-Engine SCR Systems

Cited by 9 publications

References 37 publications

On the integration of physics-based and data-driven models for the prediction of gas exchange processes on a modern diesel engine

On the integration of physics-based and data-driven models for the prediction of gas exchange processes on a modern diesel engine

Research on the Influence of External Parameters of Fan-Type Nozzle on Water Jet Performance

Experimental and numerical validation of a proportional solenoid valve based on the data-driven model

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