A robust Trimmed Body modal model identification method enabling body stiffness characterization Bart Peeters, Theo Geluk, Mahmoud El-Kafafy

Transcription

1 A robust Trimmed Body modal model identification method enabling body stiffness characterization Bart Peeters, Theo Geluk, Mahmoud El-Kafafy Theo Geluk Simcenter Symposium, October 18 th 2017 Realize innovation.

2 Robust Trimmed Body Model Identification and Analysis Content Introduction Trimmed Body Characterization: Challenges Siemens approach Application scenarios Conclusion Page 2

3 Introduction Body Design: typical OEM needs & current trends Light-weight design while keeping performance Demand for weight reduction (CO 2 requirements) Improve handling or NVH performance Body stiffness important for multiple attributes Optimize the body design design the right stiffness in the right place Balance Handling - NVH does body limit optimal suspension performance? Benchmarking Accurate identification of reference data (Static, NVH) Benchmarking Reference data & weak-spot detection Static stiffness Troubleshooting identify improvement potential Identify weak-points for either Static or NVH performances Dynamic stiffness Identify improvement potential key contributors to target response? Page 3

4 Introduction Body Design: Engineering implications Body modal test approach Robust & Accurate Test-based Body Model Identification Body modal analysis approach Body Modal Tests Body Modal Analysis Analysis techniques for Static applications Focus point of this presentation Analysis techniques for NVH applications Body Analysis techniques for Static and NVH Static Static Stiffness Weak-point study CAE-correlation Benchmarking NVH Troubleshooting Mode contribution Hybrid models Benchmarking Page 4 Need for solution that enables Accurate Body Model Identification and Analysis for Static & NVH Providing input for an improved body design

5 Robust Trimmed Body Model Identification and Analysis Content Introduction Trimmed Body Characterization: Challenges Siemens approach Application scenarios Conclusion Page 5

6 Trimmed Body Characterization Typical approaches Typical test-based approach for global body representation (NVH / Static) Test-based approach for local body representation (NVH / Static) Body: suspended free-free Body: suspended free-free Excitation: locally (shaker) Excitation: 2 or more shakers Experimental Modal Analysis: body mode extraction Use driving-point FRF data to either: Identify the hard-point Static stiffness Describe the hard-point dynamic stiffness Page 6

7 Trimmed Body Characterization Test-based related challenges Robust and reliable Body Testing procedure free-free condition Need guidelines Attention for Free-free condition of body structure Input / Output points Choices for input / output locations Interface pieces Usage of interface pieces for FRF inputs Data verifications 0.10 )/N (m/s 2 Log Defined procedure for body testing for Static and NVH applications 0.10e Phase Data checks Hz Page 7

8 Trimmed Body Characterization: Challenges Model identification related challenges Robust and reliable Body Modal Analysis (EMA) procedure Achieving a high quality body modal model can be difficult: Objectivity influence of Engineer s subjective choices Trimmed body has high # of modes which to select / accept Challenges 0.10 What model quality is good? )/N (m/s 2 Log Synthesized FRF BODY:0103:+Z/BODY:0103:+Z 0.10e What mode to select? Synthesized FRF BODY:0103:+Z/BODY:0103:+Z Hz Reciprocal modal models: enable advanced model analysis Modeling detail: should contain both global and local dynamics 0.10 (m/s 2 )/N Log Is the reciprocal model accurate? 0.10e Synthesized FRF BODY:0103:+Z/BODY:0103:+Z Page Synthesized FRF BODY:0103:+Z/BODY:0103:+Z 5.00 Hz

9 Robust Trimmed Body Model Identification and Analysis Content Introduction Trimmed Body Characterization: Challenges Siemens approach Application scenarios Conclusion Page 9

10 Siemens approach Classic Trimmed Body EMA using a limited # of inputs Global excitation Global Body excitation with 2 or more shakers Global mode extraction (e.g. one at front body, one at rear body Local excitation Local hard-point excitation (3DOFs) using hammer/shaker Local mode extraction Total Modal Model Global Flexibility for all response nodes & Local Flexibility for the interface nodes (hard-points) Page 10

11 Siemens approach Classic Trimmed Body EMA using a limited # of inputs Once a modal model is available, any dynamic response (FRF) or static stiffness at a given body node can be estimated With limited # of inputs for EMA on a Trimmed Body: strong risk on estimation of a-symmetric mode shapes A-symmetric modes however, can limit this strongly Application for NVH: estimation of FRFs 2 body nodes Application for Static: stiffness estimation 2 body nodes Page 11 Measured FRF Synthesized FRF Limits model usage for weak-point analysis, modal Mode a-symmetry contribution causes poor study, FRF estimation at 1 node Factor 9 static stiffness difference Same hard-points Left / Right body side Limits model usage for benchmarking, target setting, identification improvements, Mode a-symmetry causes poor Stiffness estimation at 1 node

12 Siemens approach Multiple input EMA far better model identification LMS Engineering approach: EMA with multiple inputs Distributed excitation of global structural behavior Improves estimation of global modes Global + Local excitation EMA residual vectors based on more inputs Improves representation of local flexibility Hard-point excitation in multiple DOFs using hammer/shaker Global + Local mode extraction: Total Modal Model Improved process with multiple inputs Better dynamic and static body characterization FRF synthesis significantly better, symmetric static stiffness result + Measured FRF Synthesized FRF Page 12

13 Siemens approach Multiple input EMA far better model identification Requirements Body Modal Model High number of inputs, outputs in EMA Complex EMA stabilization diagram High FRF synthesis quality required High mode shape quality required Mode set reciprocity required PolyMax + ML-MM handle all these Stabilization High number synthesis mode shapes in of PolyMax quality FRFs quality also also on Trimmed for TB Body but How those to select achieve were requirements Shape Building symmetry, this poles? measured Modal and with Model anyway a reciprocal manually model? is No (ML-MM extra test = maximum effort likelihood modal model) almost impossible Model Parameter estimation for high # inputs Objective, iterative approach and: Optimal synthesis & mode shape quality. manual EMA can introduce unwanted subjectivity as well Real modes: optional ML-MM condition Reciprocity: optional ML-MM condition Note: no extra testing w.r.t. classic procedure required Page 13

14 Robust Trimmed Body Model Identification and Analysis Content Introduction Trimmed Body Characterization: Challenges Siemens approach Application scenarios Conclusion Page 14

15 Application cases Model Identification: FRF Synthesis & Shape quality Results on Trimmed Body using ML-MM High quality FRF synthesis robust representation of body dynamics / flexibility Output is immediately a reciprocal modal model Measurement Synthesis Measurement Synthesis Measurement Synthesis Measurement Synthesis Strongly improved modeshapes more symmetrical, more physical (use multiple input based EMA) ML-MM enables to define a robust, accurate and reciprocal set of modes Page 15

16 Application cases Static: stiffness identification for individual hard points or global body Hard-point static stiffness Global Body static stiffness Excitation: local (shaker) Accurate fit Driving Point FRF (ML-MM) Excitation: global + local Accurate Modal Model (ML-MM) Trimmed Body Body-in-White LMS Engineering toolset: Stiffness Results multiple hard-points Stiffness results & Contribution Analysis Static stiffness extraction from dynamic data Benchmarking, CAE-correlation Static Load Case inputs Page 16

17 Application cases Static: individual suspension connection points Hard-point static stiffness Benchmarking database Identify weak-points Input to body design target setting Advanced further analysis steps Mode contributions, Identify gap with competition Possible on BOTH Body-in-White and Trimmed Body All front suspension to body connection points Page 17

18 Application cases Body Weak-point identification for Vehicle Dynamics Challenge Improving the vehicle dynamic performance through optimized body characteristics Solution Body weak-spot analysis, body modification definition and evaluation Animate Body Deformation together with Mode Contributions, Loads, Handling Parameters Time-domain Loads Body Modes Body Deformation Body Loads Front Lateral Load Rear Lateral Load Step Steer 100Kph Body Model Body weak-point analysis with Siemens toolset Steering Angle Input Understand mechanism between body characteristic & vehicle performance Page 18

19 Robust Trimmed Body Model Identification and Analysis Content Introduction Trimmed Body Characterization: Challenges Siemens approach Application scenarios Conclusion Page 19

20 Robust Trimmed Body Model Identification and Analysis Conclusion Siemens solution for Body Identification & Analysis Testing procedures for Body Model data acquisition Modal Analysis with ML-MM for model identification Multiple input based Accurate real & reciprocal modes Less subjectivity in modal analysis Both on Body-in-White and Trimmed Body Analysis procedures & toolset for Static stiffness distribution & weak-point identification, benchmarking Page 20

21 Thank you Realize innovation.