A Predictive Real Time NOx Model for Conventional and Partially Premixed Diesel Combustion

Andersson, Magnus; Johansson, Bengt; Hultqvist, Anders; Noehre, Christof

doi:10.4271/2006-01-3329

Cited by 56 publications

(54 citation statements)

References 8 publications

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“…The global mean errors are about 6% and 14%, using experimental or modelled B% respectively. This results are better than other models with similar features found in literature [17,18,30].…”

Section: No X Emission Modelsupporting

confidence: 62%

“…This control strategy uses predictive mathematical models of the processes in order to estimate the future behaviour of the system for given control inputs, thus optimising the selection of the control signals [1,6,10,12,13,14,15,16]. In this scenario, in-cylinder pressure provides direct information on combustion development [6,17,18,19,20,21], as peak pressure, indicated mean effective pressure or heat release. Thus, in-cylinder pressure can be used in different engine control applications such as failure detection [21], air mass flow estimation [22], on-line combustion detection [23], exhaust gas recirculation control [12,24], torque estimation [25], noise control [26] or NO X control [27].…”

Section: Introductionmentioning

confidence: 99%

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Development of a control-oriented model to optimise fuel consumption and NOX emissions in a DI Diesel engine

et al. 2014

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This paper describes a predictive model of NO X and consumption oriented to control and optimisation applications in DI Diesel engines. The model, which is based on the Response Surface Methodology (RSM), is focused on the prediction of NO X emissions and brake specific fuel consumption (output parameters) following a two step process: first, the relationship between engine inputs and combustion parameters is determined and, secondly, engine outputs are predicted from the combustion parameters, taking into account the mechanical losses. The inputs are engine variables related to the intake charge conditions (exhaust gas recirculation rate, intake pressure and temperature), injection settings (start of main and pilot injections, and injection pressure), and some combustion parameters that allow to characterise the in-cylinder gas processes (peak pressure, indicated mean effective pressure and burned angles). Splitting the model into two parts allows using either experimental or modelled combustion parameters, thus enhancing the model flexibility. The proposed model is finally used for multi-objective optimisation of engine operation.

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Section: No X Emission Modelsupporting

confidence: 62%

Section: Introductionmentioning

confidence: 99%

Development of a control-oriented model to optimise fuel consumption and NOX emissions in a DI Diesel engine

et al. 2014

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show abstract

“…Since the oxygen and nitrogen concentrations in Equation (1) are assumed to be in equilibrium at the peak temperature and pressure [26], the oxygen concentration was replaced with the value measured by the exhaust built-in sensor, and the nitrogen concentration was calculated from Equation (14). The re-organized form of the NO formation rate equation yields:…”

Section: Calculation Of the Cycle-averaged No Formation Ratementioning

confidence: 99%

“…However, other NO mechanisms, such as from N 2 O or NO decomposition, cannot be neglected in some particular operating conditions (which occur, e.g., at very high rates of EGR) [14,41]. Taking into account other NO formation and decomposition mechanisms simultaneously, the final NO rate equation can be written as:…”

Section: Fitting Of the Constant In The No Estimation Modelmentioning

confidence: 99%

Development of a Real-Time Virtual Nitric Oxide Sensor for Light-Duty Diesel Engines

Lee

Kim

et al. 2017

Energies

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This study describes the development of a semi-physical, real-time nitric oxide (NO) prediction model that is capable of cycle-by-cycle prediction in a light-duty diesel engine. The model utilizes the measured in-cylinder pressure and information obtained from the engine control unit (ECU). From the inputs, the model takes into account the pilot injection burning and mixing, which affects the in-cylinder mixture formation. The representative in-cylinder temperature for NO formation was determined from the mixture composition calculation. The selected temperature and mixture composition was substituted using a simplified form of the NO formation rate equation for the cycle-by-cycle estimation. The reactive area and the duration of NO formation were assumed to be limited by the fuel quantity. The model predictability was verified not only using various steady-state conditions, including the variation of the EGR rate, the boost pressure, the rail pressure, and the injection timing, but also using transient conditions, which represent the worldwide harmonized light vehicles test procedure (WLTC). The WLTC NO prediction results produced less than 3% error with the measured value. In addition, the proposed model maintained its reliability in terms of hardware aging, the changing and artificial perturbations during steady-state and transient engine operations. The model has been shown to require low computational effort because of the cycle-by-cycle, engine-out NO emission prediction and control were performed simultaneously in an embedded system for the automotive application. We expect that the developed NO prediction model can be helpful in emission calibration during the engine design stage or in the real-time controlling of the exhaust NO emission for improving fuel consumption while satisfying NO emission legislation.

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“…Partially premixed combustion (PPC) is intermediate between compression ignition (CI) and homogeneous charge compression ignition (HCCI) that offers a better control of combustion due to increased stratification [1,2,3,4], compared to HCCI. In conception, increasing the delay time between start of ignition (SOI) and start of combustion (SOC) make the combustion homogenous [5].…”

Section: Introductionmentioning

confidence: 99%

Combustion Stratification for Naphtha from CI Combustion to PPC

Vallinayagam

Vedharaj

et al. 2017

SAE Technical Paper Series

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This study demonstrates the combustion stratification from conventional compression ignition (CI) combustion to partially premixed combustion (PPC). Experiments are performed in an optical CI engine at a speed of 1200 rpm for diesel and naphtha (RON = 46). The motored pressure at TDC is maintained at 35 bar and fuelMEP is kept constant at 5.1 bar to account for the difference in fuel properties between naphtha and diesel. Single injection strategy is employed and the fuel is injected at a pressure of 800 bar. Photron FASTCAM SA4 that captures in-cylinder combustion at the rate of 10000 frames per second is employed. The captured high speed video is processed to study the combustion homogeneity based on an algorithm reported in previous studies.Starting from late fuel injection timings, combustion stratification is investigated by advancing the fuel injection timings. For late start of injection (SOI), a direct link between SOI and combustion phasing is noticed. At early SOI, combustion phasing depends on both intake air temperature and SOI. In order to match the combustion phasing (CA50) of diesel, the intake air temperature is increased to 90°C for naphtha. The combustion stratification from CI to PPC is also investigated for various level of dilution by displacing oxygen with nitrogen in the intake. The start of combustion (SOC) was delayed with the increase in dilution and to compensate for this, the intake air temperature is increased. The mixture homogeneity is enhanced for higher dilution due to longer ignition delay. The results show that high speed image is initially blue and then turned yellow, indicating soot formation and oxidation. The luminosity of combustion images decreases with early SOI and increased dilution. The images are processed to generate the level of stratification based on the image intensity. The level of stratification is same for diesel and naphtha at various SOI. When O 2 concentration in the intake is decreased to 17.7% and 14.7%, stratification level is decreased. NO X emission for both diesel and naphtha show a decreasing trend from CI to PPC.Comparing diesel and naphtha, the soot emission is lower for naphtha. NO X and soot emissions at various SOI are correlated with high speed images of combustion to explain the combustion stratification.

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A Predictive Real Time NOx Model for Conventional and Partially Premixed Diesel Combustion

Cited by 56 publications

References 8 publications

Development of a control-oriented model to optimise fuel consumption and NOX emissions in a DI Diesel engine

Development of a control-oriented model to optimise fuel consumption and NOX emissions in a DI Diesel engine

Development of a Real-Time Virtual Nitric Oxide Sensor for Light-Duty Diesel Engines

Combustion Stratification for Naphtha from CI Combustion to PPC

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