In-Cycle Real-Time Prediction Technology of NOx Emission of Diesel Engines Based on Cylinder Pressure

2014 ◽  
Vol 7 (2) ◽  
pp. 1084-1092 ◽  
Author(s):  
Jingyi Zhang ◽  
Fuyuan Yang
Author(s):  
Devesh Upadhyay ◽  
Michiel Van Nieuwstadt

Modern Diesel engines are faced with two major emission challenges in their quest to become an environmentally compatible source of motive power, Nitrogen Oxides (NOx) and Particulate Matter (PM). Advanced techniques, such as High Pressure Common Rail (HPCR) fuel injection combined with multiple injections per cycle, are commonly employed to minimize in-cylinder production of NOx and PM. However, to meet the EPA mandated standards it is essential that an aftertreatment system be used. Typical Diesel aftertreatment systems will employ some form of a NOx reducing catalyst and a particulate trap for PM removal. Lean NOx traps and Selective Catalytic Reduction (SCR) are examples of aftertreatment techniques frequently used in Diesel engine applications. Whatever the method of choice, knowledge of the feed-gas NOx concentration is essential for not only assessing the performance of the NOx reduction catalyst but also for defining the control strategy for the aftertreatment system with respect to the management of the reductant quantity to be injected. In the absence of a dynamic NOx emission model the control algorithm has to depend on either a NOx sensor upstream of the catalyst or a static map of the feedgas NOx level as some function of engine influence factors. While NOx sensors add to the overall system cost, creating an accurate and representative NOx map over the entire engine operating range can be a challenging task. A dynamic NOx model would, in theory solve, both of these problems, however it is essential that the model be simple and implementable in real time. A model that uses inputs that are not available from the standard measurement set is of little use for real time control applications as is a model that predicts the temporal and spatial NOx evolution in the engine combustion chamber as such models tend to be computationally expensive. However, it is essential that the model behave like a fast NOx sensor in predicting cycle averaged NOx emission. In this paper we present an approach to developing such a model and present results from model validation against vehicle data. The basic structure of the model relies on well-known mechanisms that describe the NOx creation and decomposition chemical kinetics. Simplifying assumptions are made to allow available measurements to be used as inputs to the model. This leads to a parametric model where the unknown parameters are estimated using Nelder Mead optimization routine available in Matlab®. Model validation against vehicle data is also presented.


2018 ◽  
Vol 21 (3) ◽  
pp. 540-558 ◽  
Author(s):  
Jensen Samuel J ◽  
Ramesh A

Real-time prediction of in-cylinder combustion parameters is very important for robust combustion control in any internal combustion engine. Very little information is available in the literature for modeling the ignition delay period of multiple injections that occur in modern direct-injection diesel engines. Knowledge of the ignition delay period in diesel engines with multiple injections is of primary interest due to its impact on pressure rise during subsequent combustion, combustion noise and pollutant formation. In this work, a physics-based ignition delay prediction methodology has been proposed by suitably simplifying an approach available in the literature. The time taken by the fuel-spray tip to reach the liquid length is considered as the physical delay period of any particular injection pulse. An equation has been developed for predicting the saturation temperature at this location based on the temperature and pressure at the start of injection. Thus, iterative procedures are avoided, which makes the methodology suitable for real-time engine control. The chemical delay was modeled by assuming a global reaction mechanism while using the Arrhenius-type equation. Experiments were conducted on a fully instrumented state-of-the-art common-rail diesel engine test facility for providing inputs to develop the methodology. The thermodynamic condition before the main injection was obtained by modeling the pilot combustion phase using the Wiebe function. Thus, the ignition delays of both pilot and main injections could be predicted based on rail pressure, injection timing, injection duration, manifold pressure and temperature which are normally used as inputs to the engine control unit. When the methodology was applied to predict the ignition delays in three different common-rail diesel engines, the ignition delays of pilot and main combustion phases could be predicted within an error band of ±25, ±50 and ±80 µs, respectively, without further tuning. This method can hence be used in real-time engine controllers and hardware-in-the-loop systems.


2017 ◽  
Vol 19 (3) ◽  
pp. 293-307 ◽  
Author(s):  
Hoon Cho ◽  
Brien Fulton ◽  
Devesh Upadhyay ◽  
Thomas Brewbaker ◽  
Michiel van Nieuwstadt

A real-time implementable, zero-dimensional model for predicting engine-out emissions of nitrogen oxides using in-cylinder pressure measurements is developed. The model is an extension of existing works in open literature that align well with the objectives of real-time implementation. The proposed model uses a simplified Zeldovich NOx mechanism that uses combustion-related parameters derived from simplified thermodynamic and combustion sub-models. The performance of the model is discussed for both a heavy-duty and a light-duty diesel engines. The model behavior is evaluated under input uncertainty so as to provide realistic performance bounds.


2013 ◽  
Vol 34 (2) ◽  
pp. 3075-3082 ◽  
Author(s):  
Wonah Park ◽  
Junyong Lee ◽  
Kyoungdoug Min ◽  
Jun Yu ◽  
Seungil Park ◽  
...  

Author(s):  
Jongsuk Lim ◽  
Seungsuk Oh ◽  
Jeasung Chung ◽  
Myoungho Sunwoo

To develop eco-friendly diesel engines, accurate combustion phase control is important due to its significant effects on harmful emissions and fuel efficiency. In order to accurately control the combustion phase, the detection of the combustion phase should precede control system design. Currently, combustion phase detection is done by the location of 50% mass fraction burned (MFB50), because of its close correlation with emissions and fuel efficiency. However, this method is not easily implemented in real-time applications because the calculation of MFB50 requires a large amount of in-cylinder pressure data and an excessive computational load. For this reason, a combustion phase indicator with a simple algorithm is required for real-time combustion control. In this study, we propose a new combustion phase indicator, called the “Central normalized difference pressures (CNDP).” The CNDP indicates the center of the two crank angles where the normalized difference pressure between firing pressure and motoring pressure (NDP) reaches 90% of the maximum value before peak (NDPbp90), and 70% of the maximum value after peak (NDPap70). The NDPbp90 and NDPap70 are highly correlated with MFB50 and the correlation is enhanced as the center between the two points obtained. The CNDP is represented by a fixed quadratic polynomial with MFB50 that robust to changes in various engine operating conditions such as engine speed, main injection timing, injected fuel quantity, fuel-rail pressure, exhaust gas recirculation (EGR) rate and boost pressure. Furthermore, in performance evaluation, the CNDP requires remarkably fewer in-cylinder pressure data samples, calculation steps and less computation time compared to MFB50. These results show great potential for the CNDP to be a substitute for the MFB50 since the proposed combustion phase detection algorithm can be used effectively for real-time combustion phase detection and control.


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