Computer aided engineering applied to engine design

Transcription

1 Computer aided engineering applied to engine design GT-Power UGM - Saclay Clément Dumand - clement.dumand@mpsa.com Team Manager in Scientific & Future Technologies Department RESEARCH & DEVELOPMENT May 17 th 2017

2 Full Digital Ambition Digital Validation Boost Present

3 Nowadays status in Groupe PSA Physical Testing validation cost for which CAE is NOT used (%) Physical Testing validation cost for which CAE is used (%) Confidence / fidelity index Level 4 : No Physical Test needed Level 3 : Good maturity of Simulation / No Physical adjustment needed 2025 target is to have CEA everywhere with a confidence index higher or equal to 3 Level 2 : Physical adjustments are needed to reach performance target 3

4 11 MAIN CAE FIELDS Legend : Functional Simulation Multi Body Finite / Volume Element 4

5 Part design challenges Nowadays methods Most of designs are iterative and manual design using a single simulation tool Challenges : To improve models accuracy To improve simulation cost / complexity To define new criterions for numerical design Constraints / Objectives First steps of the full digital design project User Best tradeoffs High fidelity Tool 5

6 Part design challenges Nowadays methods Simulation domain tends to grow : multi-physics simulation or co-simulation Challenges : To avoid to many interface between codes all in one code To manage complexity (high number of parameters, objectives, constraints, etc.) Constraints / Objectives Users Best tradeoffs High fidelity Tool A High fidelity Tool B 6

7 Torque Combustion systems design strategies Simulation complexity tends to grow : tools managed by automatic optimization methods Supervisor Combustion system optimization for several operating conditions Engine acoustics Combustion process 1D / 3D coupling for each operating points Speed 7

8 Automatic optimization of combustion system For a single operating condition Constraints / Objectives Supervisor Best tradeoffs Parametrized piston shape 8

9 Automatic optimization of combustion system For a single operating condition Optimization result 9

10 2020 objectives Combustion system design Automatically design combustion systems for gasoline and Diesel engines Objectives : To maximize the whole efficiency and max torque curve To maximize the exhaust temperature for aftertreatment systems lightoff (Diesel part loads, gasoline starting) To fulfill constraints (noise, emissions targets, stability criterion, mechanical limits) Final outputs : Overall gains / maps IFSC Torque 10

11 2020 objectives Remaining challenges to achieve full digital design (gasoline engines) To use CFD to calibrate 1D combustion model To determine intake and exhaust pressure drops (steady state simulations) To find a way to calibrate combustion speed and knock limits in 1D from 3D results Constraints / Objectives Supervisor To improve models accuracy Knock Soot (PN / PM) To enrich optimization with new criterions Combustion stability Low speed pre-ignition 11

12 2020 objectives Complex system validation Complex system approach, with a global overview of the whole system : Engine example Engine BSFC cycle fuel consumption Raw emission and after treatment behavior (transient) Engine cooling and part thermo-mechanical stress (transient) Engine friction Engine control We need global simulation tools in order to simulate the whole complex system Challenges : Simulation accuracy Interface with specific codes Simulation time (up to real time) Global optimization 12

13 2020 objectives Complex system validation A global and collaborative simulation for complex systems Supervisor High fidelity High fidelity High fidelity Tool A Tool A Tool A All in one or co-simulation tool High fidelity High fidelity Tool High B fidelity Tool B Tool B 13

14 2025+ objectives Continue to improve the conception efficiency More and more complex systems Artificial Intelligence to manage the design process Constraints / Objectives Data base AI Best tradeoffs Management strategies High fidelity tools Low fidelity tools 14

15 Full digital design 4 topics have to be improved Labs Supervisor AI for design Industries & codes suppliers Complex systems simulations 2025 target Global optimization New criterions for Industries robust & Labs design Simulations accuracy & speed-up Codes suppliers & Labs 15

16 Thanks for your attention