Concept Evaluation and Optimization of a 2-Stage Charging System GT Conference 2014, OCTOBER 20-21 2014 Msc. ETH Pascal Mühlebach, Dr. sc. techn. Christian Lämmle combustion and flow solutions GmbH, Zurich Dipl. Ing. ETH Daniel Gohl, Dipl. Ing. Peter Fledersbacher sa-, Mellingen Dipl. Ing. Peter Obrecht, Prof. Dr. sc. techn. Konstantinos Boulouchos Aerothermochemistry and Combustion Systems Laboratory LAV, Swiss Federal Institute of Technology, ETH Zurich 1
Content Project Overview Investigated 2-Stage Charging Systems Methodology of Optimization Process Results Conclusions & Outlook 2
Project Overview: Objectives Develop and design a 2-stage charging system for 2.0L 4-cylinder diesel engine flight application up to 25 000ft / 7620m (p Amb =0.36bar, T Amb =-35 C /238K) power 100kW @ 3900rpm (target power @ full load from 2500 3900rpm) max cylinder pressure 165bar minimize fuel consumption Estimation of resulting pressure ratio η e = 0.32, λ = 1.3, n = 3900rrr, P = 100kW Ground p AAA = 1.00bar, T AAA = 293K, T III_eee = 350K p III = 2.2bbb π = 2.2 Maaaaaa aaaaaaaa p AAA = 0.36bar, T AAA = 238K, T III_eee = 300K p III = 1.9bbb π = 5.3 3
Project: Structure and Partners Optimize the charging system through simulation Develop an universally applicable optimization tool Compare and optimize different charging concepts with GT-POWER Demonstrator of optimized charging system Support engineering / provide TC maps Build a prototype and demonstrate usability Phenomenological Models Enhance existing models for burn rate, NOx and soot Together with CFS: Implement the models into GT- POWER by means of user coding The project is funded by the Swiss Erdöl-Vereinigung 4
Content Project Overview Investigated 2-Stage Charging Systems Methodology of Optimization Process Results Conclusions & Outlook 5
Investigated 2-Stage Charging Systems System 1: MC + TC System 2: TC + TC IC IC High Pressure mechanically driven compressor IC Low Pressure turbocharger Wastegate High Pressure turbocharger IC Low Pressure turbocharger Wastegate Optimization Parameters Mass Flow Multiplier LP Compressor Mass Flow Multiplier LP Turbine Mass Flow Multiplier HP Compressor Gear Ratio Optimization Parameters Mass Flow Multiplier LP Compressor Mass Flow Multiplier LP Turbine Mass Flow Multiplier HP Compressor Mass Flow Multiplier HP Turbine 6
Content Project Overview Investigated 2-Stage Charging Systems Methodology of Optimization Process Results Conclusions & Outlook 7
Optimization: Methodology Define optimization goal Choose optimization algorithm (PSO, GA) Define parameters Define constraints Write parameter file Start GT-POWER Analyse results Define new parameters Write output file 8
Optimization: Mass Flow Multiplier as a Function of Iteration 9
Content Project Overview Investigated 2-Stage Charging Systems Methodology of Optimization Process Results Conclusions & Outlook 10
Results: Brake Specific Fuel Consumption 11
Results: Compressor Maps MC-TC Low Pressure Compressor (TC) High Pressure Compressor (MC) TC maps provided by sa-charging solutions Considered Engine Speeds [rpm]: 2 250, 2 500, 2 750, 3 000, 3 250, 3 750, 3 900 12
Results: Compressor Maps TC-TC Low Pressure Compressor (TC) High Pressure Compressor (TC) TC maps provided by sa-charging solutions Considered Engine Speeds [rpm]: 2 250, 2 500, 2 750, 3 000, 3 250, 3 750, 3 900 13
Results: Pumping Mean Effective Pressure 14
Results: Maximum Cylinder Pressure 15
Content Project Overview Investigated 2-Stage Charging Systems Methodology of Optimization Process Results Conclusions & Outlook 16
Conclusions & Outlook Both investigated charging versions fulfil the power target under these challenging conditions The engine equipped with two turbochargers shows 3 to 8% lower fuel consumption lower maximum cylinder pressure The engine equipped with one mechanically driven compressor and one turbocharger has advantages in packaging (size of low pressure parts) lower weight The setups will be run again with the phenomenological models (boundaries for turbines) The engine will be tested on a test bench ( ground conditions ) 17
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Results: Temperature Before Turbine 19
Results: Lambda 20
Results: Residual Gases 21
Results: Turbine Maps MC-TC Low Pressure Compressor (TC) Low Pressure Turbine (TC) Considered Engine Speeds [rpm]: 2 250, 2 500, 2 750, 3 000, 3 250, 3 750, 3 900 22
Results: Turbine Maps TC-TC Low Pressure Turbine (TC) High Pressure Turbine (TC) Considered Engine Speeds [rpm]: 2 250, 2 500, 2 750, 3 000, 3 250, 3 750, 3 900 23
GT-POWER Models System 1: MC + TC System 2: TC + TC 24
Particle Swarm Optimization Algorithm Initialize an array of particles with random values Evaluate the desired minimization function Compare evaluation with particle s previous best value If current value < particle s best value: x l,bbbb = x(t) Compare evaluation with group s previous best value If current value < group s best value: x g,bbbb = x(t) Change velocity: v t + 1 = c 1 v(t) + c 2 r 1 x l,bbbb x t + c 3 r 2 x g,bbbb x t Change position: x t + 1 = x t + v(t + 1) Loop to step 2 and repeat until a criterion is met 25