Determine the Optimiztion Processing for KHST's Suspension Characteristics - Design Parameters(29 ea) : Spring and Damper Characteristics
- Performance Index(46 ea) : Dynamic Behavior (Ride Comfort, Safety, Stability)
Create the Design of Experiments Table (66 Times) considering minimum cost - Orthogonal Array : 33 times, L32 (two Level -> -1, 1)
- D-Optimal Design : 33 times, (Five Level -> 1, 0.5, 0, -0.5, -1)
Simulate the Analysis Model, Iteratively(66 times)
(Using Vampire Program)
Create the Corelation Table between Design parameters and Performance Index : 66 X (29 + 46)
[ Iteration times X (Design Variables + Performance Idex) ]
Create the Function Based Approximation Model
- Response Surface Model : - Neural Network Model :
(2nd Order Polynomial) (considering Non-Linear )
Conform the Accuracy of Models (Screenig : R
2, R
2adj) Modify the Model
Analysis Sensitivity and Define the Optimization Problem - Objective Function :
- Constraints :
Optimization
- Response Surface Model : Variable Matric Method - Neural Network Model : Defferential Evolution Method
Comparison between Optimization and Analysis Results at Optimal Point No
Finish the Design Processing Yes
Accept No Accept
Analysis the
Model Sensitivity
Modify the DOE Table
r2 r4 r6 r8r 1 0 d 2d 4d 6d 8 d 1 0 d 1 2 w 2 w 4 w 6 w 8 w 1 0 w 1 2 s 2s 4 s 6s 8 s 1 0 s 1 2 - 1 . 6
- 1 . 4 - 1 . 2 - 1 . 0 - 0 . 8 - 0 . 6 - 0 . 4 - 0 . 2 0.0 0.2 0.4 0.6 0.8 1.0
Initial V a l u e O p tim i z e d V a l u e
Normalized Value(-1,1)
P e r f o r m a n c e I n d e x
r 3 r 6 r 9 d 2 d 5 d 8 d 1 1w 2 w 5 w 8 w 1 1 s 2 s 5 s 8 s 1 1
- 1 . 0 - 0 . 8 - 0 . 6 - 0 . 4 - 0 . 2 0 .0 0 .2 0 .4 0 .6 0 .8
1 .0 N e tw o r k m o d e l , i n i t i a l N e tw o r k m o d e l , O p t i m i z e d T r u e m o d e l , i n i t i a l T r u e m o d e l , O p t i m i z e d
Noramlized value
P e r f o r m a n c e i n d e x
