MultiObjective Optimization in Engine Design

Using Genetic Algorithms to Improve Engine Performance

The Test Engine

• 4-stroke 4 cylinder 2.2L • Bore: 93mm; stroke: 81mm; compression ratio: 8.9 • 2 valves per cylinder • Port injection• Combustion: Wiebe function (with spark trimming

simulated by the 50% burn point parameter)• In-cylinder heat transfer modeled by Woschni

model and in-cylinder wall temperatures are fixed at specified values for WOT and 5000 rpm.

GT-Power Model

Optimization of SI Engine

Inputs:

2o30o-10o50% Burn Point(TH50)

10 mm400 mm100 mmIntake Runner Length (INTRUN)

5o151o101oExhaust Cam

Timing(EXHCAM)

5o264o214oIntake Cam Timing(INTCAM)

Step SizeMaximum Value

Minimum ValueVariable

Parameters definition

Allparametersare definedinto [ ]

modeFRONTIER modifies an ASCII input file

Running GT-Power in Batch

Data Parsing from the .out File

NOX

Run Statistics

• Population Size: 20• Number of Generations: 100• Total Number of Simulations: 2000• Algorithm: MOGA / NSGA

(Genetic Algorithms)• Time: Approx 15 hours on

DELL Inspiron 8500, 2.4 GHZ

Optimization of SI EngineCase 1

Objectives:

MinimizeFuel ConsumptionMinimizeNOX

Process Flow in modeFRONTIER

ResultsPareto Frontier (Trade-Off Curve)

Fuel Consumption

NOX

Case 1 – Correlation matrix

• EXHCAM is to be maximised for MinBSFC but minimised for MinNOX (most important)

• TH50 is to be minimised for MinBSFC but maximised for MinNOX

• INTCAM, INTRUNLENGTH are to be maximised for MinBSFC (less important for NOX)

Optimization of SI EngineCase 2

Objectives:

MinimizeNOXMaximizeBrake Power

Process Flow - Case 2

Case 2 – Scatter Chart

Brake Power

NOX

Case 2 – Correlation matrix

• EXHCAM is to be maximised for MaxBKM but minimised for MinNOX

• TH50 is to be maximised for MinNOX (and less important for BKW)

• INTCAM and INTRUNLENGTH are less significant

Optimization of SI EngineCase 3

Objectives:

Constraint: NOX ≤ 350 ppmMinimizeNOXMaximizeBrake Power

Process Flow - Case 3

Case 3: Scatter chart

Brake Power

NOX

constraint

Case 3 – Correlation matrix

• EXHCAM is to be maximised for MaxBKM but minimised for MinNOX

• TH50 is to be maximised for MinNOX (and less important for BKW)

• INTCAM and INTRUNLENGTH are less significant

Conclusion

• An example of integration of GTPower withmodeFRONTIER has been shown

• A 4-cylinder engine has been modelled by GTPower, and modeFRONTIER has been used to optimize itsperformances (Brake Power, BSFC and NOX reduction) finding the best set values of 4 parameters