Multi Cylinder TPA and DI Pulse Model Development using GT-SUITE
Lakshmidhar Reddy Isuzu Technical Center America
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OverviewSteps to Develop Combustion Model1. Data collection and validation2. TPA model setup and validation3. Combustion model calibration (DI
Pulse)
V2017 and Earlier TPA Model V2018 TPA Model
Instrumentation:• Crank angle averaged Cylinder pressure for all cylinders for 200 cycles• Crank angle averaged Intake manifold high pressure signal for 200 cycles• Crank angle averaged Exhaust manifold high pressure signal for 200 cycles• Intake and Exhaust manifold temperature using shielded thermocouples• Intake manifold species concentration to calculate EGR % from CO2 concentrations • Engine out emissions concentrations• Injector current signal • Temperature and Pressure sensors before and after subsystems
Data collected:• Engine operating range Without EGR• Engine operating range with EGR• Rail Pressure variation• EGR variation
Each point is stabilized for 5 minutes before data collection for engine operation stability
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Data used for Multi Cylinder TPA
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Test Points
Three Pressure analysis: • Intake, Cylinder and Exhaust pressure profiles are used to calculate the burn rate and in-
cylinder trapped conditions• Calculated burn rate profile imposed and cylinder pressure calculations are performed based on
model setup conditions• The above process continues till the pressures, temperatures and mass flow converge
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Three Pressure Analysis ( TPA)
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TPA Model Setup Developed from 3D CAD data
Key model parameters (calibratables):• Air flow• Exhaust temperature (Manifold heat transfer
multiplier) • Log P-Log V curve or Gas exchange process
(Valve timings, valve lash, blowby flow)• IMEP (In-cylinder heat transfer multiplier)
Exhaust pressure profile
Intake pressure profile
Injector Rate Map is used to replicate actual injection pulses
Log P-Log V Analysis
Log P-Log V curves for two operating conditions were shown above Pumping loop trend from initial TPA results were not matching
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Pumping Loop Analysis
Exhaust gas recompression was observed in measured data With the baseline valve timings this is not observed Adjusted valve timings keeping lift constant to match exhaust recompression
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Pumping Loop Analysis
Same kind of behavior was seen at different engine operating condition
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Intake and Exhaust Valve Timings
Intake and Exhaust valve timings were adjusted to decrease valve overlap. Decrease in valve overlap increases recompression of exhaust gases in-cylinder
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Log P-Log V After Valve timings Adjusted
Same operating conditions after valve timing adjustment were matching with measured data
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Blowby Model
Leak path diameter was calibrated to match blowby flow assuming constant crank case pressure and temperature
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Model Validation – Air Flow
Air flow error was less than 4% at all points
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Model Validation – Exhaust Temperature
Exhaust temperature error was very high at low speeds This was due to engine operated at high load for longer time before actual test conducted. This leads to heating of
gas by pipe wall temperatures Stabilization time needs to be function of temperature delta to overcome this effect.
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Model Validation - IMEP
At less than 10% of load values of IMEP are vey low Small deviation in absolute values leads to higher relative errors
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Log P-Log V curve – Six Example Points
DI Pulse Model: DI Pulse is Direct Injection Diesel Multi Pulse model to predict heat release as calculated in the Cylinder pressure analysis
DI Pulse model calibrated using:
1. Entrainment rate multiplier
2. Ignition Delay Multiplier
3. Premixed Combustion rate Multiplier
4. Diffusion Combustion rate Multiplier
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DI Pulse Calibration
Model setup same as TPA model
60 Points selected with varying speed and load
Multi Objective Genetic Algorithm available in GT-POWER was used for optimization
Burn rate RMS error and Absolute peak cylinder pressure error were defined as objectives for optimization
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DI Pulse Model Calibration V2017 and Earlier DI Pulse Model V2018 DI Pulse Model
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DI Pulse Results – 16 Example Points
Crank Angle
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DI Pulse Results – 16 Example Points
Crank Angle
Pr
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Significant Improvement in Air flow accuracy from Single cylinder to Multi cylinder TPA because of capturing manifold dynamics
Both models were unable to capture variation in Peak Cylinder pressure. This is due to unequal distribution of Air and EGR for different cylinders
Combustion model was sensitive to changes in model setup once completed
Sub-system models were developed very carefully to predict same flow, pressure and temperature boundary conditions for combustion model
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Conclusions and Future Work
Future Work Development of NOx, HC and CO emission models Integrate sub-system models with combustion model and validate detailed Engine model Using model to support Engine calibration and hardware selection for future Engine family
Krishna Natti and Nick keeler for helping in Engine Dyno setup and data collection.
Kevin Roggendorf, Navin Fogla and Syed Wahiduzzaman from Gamma Technologies Inc for providing constant support and Beta version of V2018 GT-SUITE.
Bruce Vernham, Yasuo Fukai, Yifan Wei and ISUZU Global CAE team for their constant support.
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Acknowledgements
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Discussions and QuestionsContact details:Lakshmidhar Reddy Model Based Development EngineerIsuzu Technical Center [email protected]
Back Up Slides
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Cylinder Pressure Variation
Since Optimization is setup to match Peak Cylinder pressure of average of 4 Cylinders it is very tough to see C to C variation.
EGR distribution also plays key role in this variations between cylinders which is very tough to correlate in 1D flow dynamic model.
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Intake and Exhaust Valve Timings Sweep
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Intake and Exhaust Valve Lash Sweep