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13 Dynardo AT.Pdf Workflows zur Systemanalyse und Optimierung in ANSYS anhand der Auslegung eines Elektromotors ----------------------------------------------------------------- Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang M. Schimmelpfennig, Dynardo GmbH ACUM 2016 Linz 2 © Dynardo GmbH Dynardo • Founded: 2001 • More than 60 employees, offices at Weimar and Vienna • Leading technology companies Daimler, Bosch, E.ON, Nokia, Siemens, BMW are supported Software Development CAE-Consulting • Mechanical engineering • Civil engineering & Geomechanics Dynardo is engineering specialist for • Automotive industry CAE-based sensitivity analysis, • Consumer goods industry optimization, robustness evaluation • Power generation and robust design optimization Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 3 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH Master of Design Robust Design Optimization (RDO) in virtual product development Our customized FE-consulting and software products enable you to: • Quantify risks • Identify optimization potentials • Perform variant studies • Secure resource efficiency • Ensure product quality • Improve product performance • Save time to market Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 4 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH optiSLang • is an general purpose tool for variation analysis using CAE-based design sets (and/or data sets) for the purpose of • sensitivity analysis • design/data exploration • calibration of virtual models to tests • optimization of product performance • quantification of product robustness and product reliability • Robust Design Optimization (RDO) and Design for Six Sigma (DFSS) serves arbitrary CAX tools with support of process integration, process automation and workflow generation Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 5 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH Design Understanding Investigate parameter sensitivities, Design Improvement reduce complexity and Optimize design performance generate best possible meta models CAE-Data Robust Design Measurement Data Model Calibrations Design Quality Identify important model parameter Ensure design robustness for the best fit between simulation and reliability and measurement Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 6 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH SPDM Input Workflow-Management Output 1 1 with Process Integration Input and for Output 2 Automatization 2 Input Output n m Excel Add-In ANSYS optiSLang other Solver Postprocessing Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 7 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH optiSLang as an ANSYS Workbench plugin • optiSLang modules Sensitivity + MOP, Optimization and Robustness are directly available in ANSYS Workbench Signal Processing module to work with curves inside ANSYS Workbench Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 8 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH CAX-Interfaces – the ANSYS Workbench Node • optiSLang Integrations provides the flexibility to extend the process chain • ANSYS Workbench can be coupled with different other solvers like MATLAB, SimulationX or Abaqus • External geometry or mesh generators can work together with the ANSYS Workbench node Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 9 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH Optimization of an electric motor Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 10 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH Optimization of an electric motor The motor simulation • ANSYS Maxwell 2D model • commutator principle Sensitivity analysis with optiSLang • problem understanding • identification of influential parameters • identification of tradeoffs Optimization with optiSLang • minimization of torque ripples • maximization of the efficiency “eta” η = Pout/Pin • suitable in this case: ARSM – adaptive response surface method Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 11 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH Optimization of an electric motor Commutator motor: working principle motor characteristics What creates the driving torque? • commutator principle • 12 lamellae & coils B-field from • one current branch magnets U0 = 12 V B-field from • fixed outer diameter coils OD = 78 mm https://commons.wikimedia.org/w iki/File:Kommutator_animiert.gif Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 12 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH Optimization of an electric motor The model: 2D commutator motor FE-simulation simulation details • time: 16.67 ms in 180 steps Δt = 92.6 μs • time integration: Backward Euler • ensure that stationary state is reached (not all designs will become stationary at the same time) data extraction: • key properties extracted by analyzing only the last cycle • access to output variables via Ansys Workbench ParameterSet • access to signals via Ansys Workbench or ASCII files Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 13 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH Model parametrization Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 14 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH Model parametrisation magnet_coverage: magnet coverage in percent magnet_thickness airgap gapwidth magnet_rounding: as fraction of magnet thickness rotor_borehole: diameter of motor axis HS0 wall_thickness magnet_voffset: for widening of air gap Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 15 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH Optimization of an electric motor Parametrization needs careful decisions example A: example B (used): • set rotor diameter • set motor size • set magnet thickness • set magnet thickness motor size dependent rotor size dependent the bigger the better magnet takes away (in terms of torque & power) space available for rotor and vice versa lost chance to learn real-world goal about a relevant conflict well tradeoff represented Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 16 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 17 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH Calling Maxwell from optiSLang Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 18 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH Optimization of an electric motor Method A: using Ansys Workbench in Maxwell • export scalar output variables to Optimetrics • parallel design computation with Optimetrics Parametric in the Workbench • optiSLang and Maxwell communicate through the ParameterSet parallel/distributed computation: • RSM, PBS, LSF, HPC pack • use “optiSLang inside Ansys” alternative: • optiSLang full version and a “Workbench node” Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 19 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH Optimization of an electric motor Method A: using Ansys Workbench in Maxwell • export scalar output variables to Optimetrics • parallel design computation with Optimetrics Parametric in the Workbench • optiSLang and Maxwell communicate represented inside through the ParameterSet the Workbench node parallel/distributed computation: • RSM, PBS, LSF, HPC pack • use “optiSLang inside Ansys” alternative: • optiSLang full version and a “Workbench node” Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 20 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH Optimization of an electric motor Method B: scripting and ASCII files direct coupling Maxwell and oSL Maxwell • run batch job • run Python script text file for • write transient reports into files transporting input signal data accessible parameters optiSLang • text-based batch job node • extract signal data with ETK • signal data free mathematical computations inside optiSLang parallel/distributed computation: • optiSLang spawns Maxwell batch jobs Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 21 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH Optimization of an electric motor Method B: scripting and ASCII files direct coupling Maxwell and oSL Maxwell • run batch job • run Python script the batch script • write transient reports into files signal data accessible optiSLang • text-based batch job node • extract signal data with ETK • signal data free mathematical Python computations inside optiSLang parallel/distributed computation: • optiSLang spawns Maxwell batch jobs Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 22 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH Optimization of an electric motor Method B: scripting and ASCII files direct coupling Maxwell and oSL Maxwell • run batch job • run Python script reading generated • write transient reports into files stored data signal data accessible
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