Sensitivitätsanalyse von passiven Insassenschutzsystemen im Frontalcrash Jürgen Schmidt, Simon Gargallo, Lars Kübler

Transkript

1 Sensitivitätsanalyse von passiven Insassenschutzsystemen im Frontalcrash Jürgen Schmidt, Simon Gargallo, Lars Kübler Weimarer Optimierungs- und Stochastiktage

2 Table of content Introduction: Occupant Safety Systems Safety system components for frontal crash Aim of sensitivity analysis Definition of input and output parameters Results of sensitivity analysis Input Output correlation analysis Output Output correlation analysis Summary

3 Occupant Safety Systems Frontal crash test Legal requirements FMVSS 208 ECE-R94 Quelle: EURO NCAP Consumer ratings Test setups (rigid barrier, ODB, ) US NCAP Dummies (5%ile female, 50%ile male, ) EURO NCAP Crash velocities (40km/h, 56km/h, ) Basis of ratings: Dummy criteria Design of Restraint System Adjustment of belt + airbag systems for best overall performance

4 Safety system components for frontal crash Airbag systems Driver airbag (single / dual stage) Passenger airbag (single / dual stage) Knee airbag Seat belt system Seat belt webbing Retractor Buckle Anchor D-ring Pretensioner (retractor, buckle, anchor) Load Limiter (Constant, Degressive, Switchable)

5 Aim of sensitivity analysis Restraint system parameters Belt: pretensioner D-Ring friction Airbag: generator time to fire airbag Identification Correlations Parameters Dummy criteria Dummy criteria Dummy criteria Sensitive system parameters Dummy criteria a head, max, HIC36, neck tension, Nij, chest deflection, femur forces, Passenger simulation model (Madymo) US-NCAP (Rating) / FMVSS 208 (Law) Hybrid III 5%ile female dummy Adjusted restraint system

6 Definition of input and output parameters Inputs Outputs RS design parameters user defined design parameter intervals Dummy criteria 36 variables 1. Pretensioner [pret min ; pret max ] 1. HIC36 Special Example 2. D-ring friction [μ min ; μ max ] 2. F t,neck Specific inputs + input intervals 12. uniformly distributed 24. Latin Hypercube Sampling (LHS) Aim: 95% Confidence Interval = 0.5 [-0.05; +0.05] Identification of sample size Results meaningful only for this analysis LHS sampled chosen: 350 samples

7 Table of content Introduction: Occupant Safety Systems Safety system components for frontal crash Aim of sensitivity analysis Definition of input and output parameters Results of sensitivity analysis Input Output correlation analysis Output Output correlation analysis Summary

8 Linear correlation matrix Linear correlation matrix C xx Input Output parameters Anthill plot linear correlation Significance filter limit = 95% responses output variable design variables input variable Degree of linear relationship between two characteristic parameters Linear regression model High correlation not necessarily causal relationship Correlation may be affected by other variables relevant linear correlation 0.5 < 0.7 low 0.7 < 0.9 medium 0.9 < 1.0 high

9 Identifying relevant input parameters Linear correlations Linear correlation matrix C xx pretensioner generator load limiter 1 airbag 1 airbag 2 D-ring friction relevant linear correlations ( >0.5) to output parameters

10 Identifying relevant input parameters Quadratic correlations Quadratic correlation matrix C XX Anthill plot linear correlation Quadratic linear correlation coefficients INPUT: airbag 2 vs. OUTPUT: HIC15_05, quadratic r=0.596 airbag 2 Input relevant quadratic correlations ( >0.5) only for airbag 2 INPUT: airbag 2 quadratic correlation 0.5 < 0.7 low 0.7 < 0.9 medium 0.9 < 1.0 high

11 Important Input Output correlations pretensioner 2 load Limiter 3 Neck tension load Limiter 2 airbag 3 pretensioner airbag 1 load limiter 2 airbag 2 load limiter 1 Load limiter 1 D-ring friction Dummy criterion: Neck tension Neck tens. Load limiter % (87%) D-ring friction % (87%) lin. corr. low med high Two important linear correlations Most important: D-ring friction (medium correlation) Load limiter 1 (low correlation)

12 Response surface Linear regression for criterion: Neck Tension Simultaneous increase in D-ring friction Load limiter 1 Increase in belt force Increase in Neck Tension inertia head Load limiter 1 Higher belt force better body restraint

13 Results for Neck criteria NTE NTF Load limiter % (28%) D-Ring friction lin. corr. low med high Neck criteria correlate linear with belt parameters D-Ring friction* Load limiter 1* NCE % (85%) * Basis: interval approach for input parameters NCF % (90%) % (90%) Neck tens % (87%) % (87%) Neck compr % (87%) % (87%) IRF Neck % (45%)

14 Results for Head injury values airbag 2 D-Ring friction airbag 1 generator HIC36 HIC15 IRF head a head,max % (83%) % (88%) % (85%) % (91%) % (73%) % (76%) % (75%) % (80%) t_a head,max 69% (71%) airbag 2 lin. corr. low med high quad. corr. low med high important correlations (quadr.) of airbag 2 with head injury values Head criteria influenced by airbag parameters

15 Response surface Quadratic regression for head deceleration a head,max Contact head - airbag a head,max generator airbag 2 early coupling head - airbag low head deceleration

16 Output Output correlations Linear correlation matrix Quadratic correlation matrix Detection of correlations between dummy criteria of different body regions influencing certain body regions affects other parts of the body Criterion for regression model: magnitude of correlation coefficient + anthill plot

17 Correlations between dummy criteria Correlations between different body regions HIC36 Thorax_a3ms lin quad lin quad NTE 0.56 Head HIC Neck NCE F c,neck NTE NCE F t,neck 0.67 Neck NCF Thorax a 3ms 0.64 F c,neck 0.80 Body regions with correlating dummy criteria HIC36 a 3ms Tibia F t,neck TI low,r TI low,l Correlation Tibia Thorax? Causal relationship?

18 Summary Identification of relevant input parameters reduction of input parameters (e.g. for optimizations) Correlations reveal tendences (only linear and quadratic correlations) Visualisation of correlations helpful for system understanding Important for meaningful results choice of input parameters + definition of input parameter intervals