Workflows zur Systemanalyse und Optimierung in ANSYS anhand der Auslegung eines Elektromotors
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig, Dynardo GmbH ACUM 2016 Linz
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© Dynardo GmbH
Dynardo
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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
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 23 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
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 24 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH
Optimization of an electric motor • extract signal data with ETK green area for data analysis • FFT amplitudes of the reference signal picture for postprocessing
Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 25 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH
Sensitivity analysis
Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 26 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH
Initial sensitivity analysis (100 DPs)
• Good Meta models for responses but bad for the torque ripples parallel coordinates plot: restrict some parameters by 20%-30% • select designs of interest = • restrict search space reduction of whole search space by 80%
airgap magnet edge radius magnet v. offset magnet coverage hs0 losses torque ripple magnet thickness gapwidth rotor borehole wall thickness mech. power amplitude
Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 27 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH
2nd sensitivity analysis (limited space – 200 DPs) • Very good metamodels for responses • Medium metamodels for the torque ripples • Analyze of the optimization potential • Multi-objective approach • Correlation analysis
Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 28 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH
2nd sensitivity analysis (narrowed space)
Correlations
Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 29 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH
2nd sensitivity analysis (narrowed space)
Correlations
Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 30 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH
2nd sensitivity analysis (narrowed space)
Correlations no linear correlation for torque ripples Are there nonlinear dependencies?
Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 31 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH
2nd sensitivity analysis (narrowed space)
Getting more information with coloring
Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 32 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH
2nd sensitivity analysis (narrowed space)
designs with low torque ripples are scattered
Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 33 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH
Optimization
Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 34 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH
Optimization problem definition
for eta torque
or eta P_mech
the tradeoff is already well captured in the random sampling
optimization = picking
Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 35 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH
Optimization problem definition
for eta torque
or eta P_mech
the tradeoff is already well captured in the random sampling
optimization = picking
but for torque_cv any other goal
the nonlinear interactions complicate the situation
Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 36 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH
Optimization: starting point
Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 37 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH
Optimization of an electric motor
Objective function minimize:
(1-eta) + 0.4*torque_cv
Constraint:
torque ≥ 0.5
Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 38 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH
Optimization of an electric motor
ARSM (adaptive response surface method) • objective function and constraint functions treated separately by ARSM • good convergence for the objective
Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 39 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH
Optimization of an electric motor
Reference design
Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 40 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH
Optimization of an electric motor
parallel coordinates plot • select designs of interest • restrict search space
Best design of the sensitivity
Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 41 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH
Optimization of an electric motor
parallel coordinates plot • select designs of interest • restrict search space
Best design of optimization (ARSM)
Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 42 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH
Optimization of an electric motor
reference design
Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 43 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH
Optimization of an electric motor
sensitivity: best design
Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 44 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH
Optimization of an electric motor
optimization: final design
Next steps: • Take final design as start for Maxwell 3D analysis • Ad some new parameters • Pre-analysis in 2D saves a lot of time because the design space in 3D is now smaller Last step: • Make a robustness analysis to check the influence of tolerances
Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 45 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH
Summary
Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 46 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH
Summary - Optimization of an electric motor
Coupling Maxwell with optiSLang • via Workbench (node) easy use but only scalar parameters • via ASCII files powerful signal processing (incl. Large Scale-DSO) Sensitivity analysis • identification of important parameters and correlations • exploring tradeoffs and optimization potentials • meta models (MOPs): can be used for optimization visualization gain knowledge about nonlinear interactions
Optimization • ARSM: efficient & robust algorithm for optimization directly on simulation • torque ripples reduced by 73%, efficiency increased by 36% • play with parametrization and goals fast gain of engineering intuition
Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 47 M. Schimmelpfennig - Dynardo GmbH Linz 2016 © Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang 48 M. Schimmelpfennig - Dynardo GmbH Linz 2016