workflows zur systemanalyse und optimierung in ansys
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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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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
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
Dynardo is engineering specialist for CAE-based sensitivity analysis, optimization, robustness evaluation and robust design optimization
• Mechanical engineering • Civil engineering &
Geomechanics • Automotive industry • Consumer goods industry • Power generation
CAE-Consulting
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
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
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
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
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
Model Calibrations Identify important model parameter for the best fit between simulation
and measurement
Model Calibrations Identify important model parameter for the best fit between simulation
and measurement
Design Improvement Optimize design performance
Design Quality Ensure design robustness
and reliability
Design Quality Ensure design robustness
and reliability
Design Understanding Investigate parameter sensitivities,
reduce complexity and generate best possible meta models
Design Understanding Investigate parameter sensitivities,
reduce complexity and generate best possible meta models
CAE-Data
Measurement Data
Robust Design
Design Improvement Optimize design performance
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
SPDM
Input 1
Input 2
Input n
Output 1
with Process Integration
and for Automatization
Workflow-Management
ANSYS optiSLang
Postprocessing
Excel Add-In other Solver
Output 2
Output m
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
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
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
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
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
Optimization of an electric motor
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
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
Optimization of an electric motor
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
Commutator motor: working principle What creates the driving torque?
https://commons.wikimedia.org/wiki/File:Kommutator_animiert.gif
B-field from magnets
B-field from coils
motor characteristics • commutator principle • 12 lamellae & coils • one current branch
U0 = 12 V • fixed outer diameter
OD = 78 mm
Optimization of an electric motor
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
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
Optimization of an electric motor
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
Model parametrization
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
Model parametrisation
magnet_coverage: magnet coverage in percent
rotor_borehole: diameter of motor axis
wall_thickness
magnet_voffset: for widening of air gap
HS0
magnet_rounding: as fraction of magnet thickness
airgap gapwidth
magnet_thickness
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
example A: • set rotor diameter • set magnet thickness motor size dependent
example B (used): • set motor size • set magnet thickness rotor size dependent
magnet takes away space available for
rotor and vice versa
the bigger the better (in terms of torque & power)
real-world goal conflict well represented
lost chance to learn about a relevant
tradeoff
Parametrization needs careful decisions
Optimization of an electric motor
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
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
M. Schimmelpfennig - Dynardo GmbH Linz 2016
Calling Maxwell from optiSLang
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
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”
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
represented inside the Workbench node
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”
Optimization of an electric motor
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
Method B: scripting and ASCII files direct coupling Maxwell and oSL
Maxwell • run batch job • run Python script • write transient reports into files
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
text file for transporting input
parameters
Optimization of an electric motor
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
the batch script
Python
Optimization of an electric motor Method B: scripting and ASCII files
direct coupling Maxwell and oSL Maxwell • run batch job • run Python script • write transient reports into files
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
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
reading generated stored data
Optimization of an electric motor Method B: scripting and ASCII files
direct coupling Maxwell and oSL Maxwell • run batch job • run Python script • write transient reports into files
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
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
reading generated stored data
Optimization of an electric motor Method B: scripting and ASCII files
direct coupling Maxwell and oSL Maxwell • run batch job • run Python script • write transient reports into files
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
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
• extract signal data with ETK green area for data analysis • FFT amplitudes of the reference signal picture for postprocessing
Optimization of an electric motor
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
Sensitivity analysis
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
Initial sensitivity analysis (100 DPs)
airgap magnet thickness
magnet edge radius gapwidth
magnet v. offset rotor borehole
magnet coverage wall thickness
hs0 mech. power
losses torque ripple amplitude
restrict some parameters by 20%-30% =
reduction of whole search space by 80%
• Good Meta models for responses but bad for the torque ripples parallel coordinates plot: • select designs of interest • restrict search space
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
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
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
2nd sensitivity analysis (narrowed space) Correlations
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
2nd sensitivity analysis (narrowed space) Correlations
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
2nd sensitivity analysis (narrowed space) Correlations no linear correlation for torque ripples Are there nonlinear dependencies?
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
2nd sensitivity analysis (narrowed space) Getting more information with coloring
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
2nd sensitivity analysis (narrowed space) designs with low torque ripples are scattered
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
Optimization
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
for or the tradeoff is already well captured in the random sampling optimization = picking
eta torque
eta P_mech
Optimization problem definition
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
Optimization problem definition for or the tradeoff is already well captured in the random sampling optimization = picking
but for the nonlinear interactions complicate the situation
eta torque
torque_cv any other goal
eta P_mech
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
Optimization: starting point
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
Objective function minimize:
(1-eta) + 0.4*torque_cv
Constraint:
torque ≥ 0.5
Optimization of an electric motor
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
ARSM (adaptive response surface method) • objective function and constraint
functions treated separately by ARSM • good convergence for the objective
© Dynardo GmbH
Optimization of an electric motor
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
Reference design
© Dynardo GmbH
Optimization of an electric motor
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
parallel coordinates plot • select designs of interest • restrict search space
Best design of the sensitivity
© Dynardo GmbH
Optimization of an electric motor
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
parallel coordinates plot • select designs of interest • restrict search space
Best design of optimization (ARSM)
© Dynardo GmbH
Optimization of an electric motor
43
Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
reference design
© Dynardo GmbH
Optimization of an electric motor
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
sensitivity: best design
© Dynardo GmbH
Optimization of an electric motor
45
Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
optimization: final design
© Dynardo GmbH
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
Optimization of an electric motor
46
Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
Summary
© Dynardo GmbH
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Workflows for analysis and optimization of an electric motor with ANSYS and optiSLang
M. Schimmelpfennig - Dynardo GmbH Linz 2016
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
© Dynardo GmbH