Research Papers: Internal Combustion Engines

An Improved Rate of Heat Release Model for Modern High-Speed Diesel Engines

[+] Author and Article Information
Peter G. Dowell, Sam Akehurst

Department of Mechanical Engineering,
University of Bath,
Bath BA2 7AY, UK

Richard D. Burke

Department of Mechanical Engineering,
University of Bath,
Bath BA2 7AY, UK
e-mail: R.D.Burke@bath.ac.uk

Contributed by the IC Engine Division of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received February 14, 2017; final manuscript received February 15, 2017; published online April 19, 2017. Editor: David Wisler.

J. Eng. Gas Turbines Power 139(9), 092805 (Apr 19, 2017) (14 pages) Paper No: GTP-17-1057; doi: 10.1115/1.4036101 History: Received February 14, 2017; Revised February 15, 2017

To meet the increasingly stringent emissions standards, diesel engines need to include more active technologies with their associated control systems. Hardware-in-the-loop (HiL) approaches are becoming popular where the engine system is represented as a real-time capable model to allow development of the controller hardware and software without the need for the real engine system. This paper focusses on the engine model required in such approaches. A number of semi-physical, zero-dimensional combustion modeling techniques are enhanced and combined into a complete model, these include—ignition delay, premixed and diffusion combustion and wall impingement. In addition, a fuel injection model was used to provide fuel injection rate from solenoid energizing signals. The model was parameterized using a small set of experimental data from an engine dynamometer test facility and validated against a complete data set covering the full engine speed and torque range. The model was shown to characterize the rate of heat release (RoHR) well over the engine speed and load range. Critically, the wall impingement model improved R2 value for maximum RoHR from 0.89 to 0.96. This was reflected in the model's ability to match both pilot and main combustion phasing, and peak heat release rates derived from measured data. The model predicted indicated mean effective pressure and maximum pressure with R2 values of 0.99 across the engine map. The worst prediction was for the angle of maximum pressure which had an R2 of 0.74. The results demonstrate the predictive ability of the model, with only a small set of empirical data for training—this is a key advantage over conventional methods. The fuel injection model yielded good results for predicted injection quantity (R2 = 0.99) and enabled the use of the RoHR model without the need for measured rate of injection.

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Fig. 1

Combustion modeling using Multiple Wiebe approach to capture rate of heat release profile for multiple injection events

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Fig. 2

Simulated rate of heat release showing premixed and diffusion (mixing-controlled) combustion and ignition delay (ID, ignition delay; ROI, rate of injection; and MCC, mixing controlled combustion)

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Fig. 3

Sensitivity of main combustion profile to combustion phasing: (a) correct SOC and (b) early SOC

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Fig. 4

Comparison of ignition delay for Arrhenius, Magnussen, and combined models and experimental data. Curves and measured data represent points obtained from an engine load sweep at 2500 rev/min.

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Fig. 5

Sensitivity of in-cylinder pressure to the phasing of pilot injection for an arbitrary operating point

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Fig. 6

Injector driver current split into three characteristic phases: (a) rise/cracking, (b) hold, and (c) fall

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Fig. 7

Correlation of measured fuel consumption to predicted fuel injected during various injector current phases

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Fig. 8

Normalized fuel-injection map for diesel injector

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Fig. 9

Measured injector currents for pilot and main injections at all engine loads at 2500 rev/min

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Fig. 10

Model parameter optimization routine

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Fig. 11

Measured operating points highlighting subsection of points used in model parameter optimization routines for (a) ignition delay, (b) diffusion combustion, (c) premixed combustion, and (d) wall impingement

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Fig. 12

RoHR evolution during the optimization process for engine operating condition of 2500 rpm and 125 N · m

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Fig. 13

Simulated RoHR using MCC model only at 2500 rev/min for (a) low load, (b) medium load, and (c) full load

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Fig. 14

(a) Predicted versus measured and (b) prediction error for main injection fuel mass

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Fig. 15

Predicted gross heat release (black solid lines) compared to measured gross heat release (gray solid lines) with ROI indicated by the gray dotted lines for a range of engine speeds and loads

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Fig. 16

Measured and predicted pilot injection ignition delay grouped by operating speeds

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Fig. 17

Measured and predicted main injection ignition delay grouped by operating speeds

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Fig. 18

Predicted versus measured gross IMEP for all test points

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Fig. 19

Pmax prediction versus measured across different load points

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Fig. 20

RoHRmax prediction against measured across different load points

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Fig. 21

Predicted and measured point of maximum pressure across different load points




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