Computer Aided Ergonomics Case Study: Vehicle Brake System · Computer Aided Ergonomics Case Study:...
Transcript of Computer Aided Ergonomics Case Study: Vehicle Brake System · Computer Aided Ergonomics Case Study:...
Research & Advanced Engineering
Computer Aided Ergonomics
Case Study: Vehicle Brake System
Dipl.-Math. (FH) Jessica Rausch & Dr.-Ing. Karl Siebertz
Ford Forschungszentrum Aachen
Research & Advanced Engineering
Research & Advanced Engineering
Motivation for Biomechanics
• Short development cycles require early ergonomic assessment.
• Better ergonomic performance without expensive features
requires advanced ergonomic analysis tools.
• Many ergonomic issues are related to muscle activation.
• Customer clinics are not suitable for parameter screening and design
optimisation.
Motivation
need for test methods and
Computer Aided Ergonomics using
a biomechanical model of the human body
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Motivation for BiomechanicsRole of the AnyBody Car Driver Model
input tool output benefit
muscle loads objective
+ comfort index data
package data
force-characteristics distribution of comfort index reduced
AnyBody for driver population testing effort
CDM
movement analysis parameter variation system
for baseline design + sensitivity analysis integration
(3-4 test subjects)
generic transfer functions design
for similar cases guidelines
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Motivation for BiomechanicsWorking Areas: Computer Aided Ergonomics
computer model
of car + driver
motion prediction performance criteria
variation of the
human body
Computer Aided Ergonomics
experimental
motion analysis
motion tracking interface
CAD Interface
motion data base
interpolation or simulation
of motion control
data
condensation
fatigue
model
geometric
scaling
strength
scaling
3rd age
force
data base
target values
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Validation Study: Braking
• Ford test vehicle, tunable force
characteristic for brake pedal.
Partially obstructed view.
• Motion analysis:
Qualisys for the upper body and the left leg;
Goniometers at the right leg;
Potentiometer for right heel
• External Loads:
contact switch to identify heel position;
pressure mapping to estimate seat support;
force transducer at the brake pedal
• EMG measurements of right leg muscles
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Validation Study: Braking
-10 0 10 20 30 40 500
50
100
150
pedal travel in mm
ped
al fo
rce in
N
activate
release
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0 1 2 3 4 5 6 70
0.2
0.4
0.6
0.8
1
Tibialis Anterior
time in s
no
rma
lize
d v
alu
e
Test: EMG envelopeCAE: muscle activity
0 1 2 3 4 5 6 70
0.2
0.4
0.6
0.8
1
Soleus
time in s
no
rma
lize
d v
alu
e
Test: EMG envelopeCAE: muscle activity
0 1 2 3 4 5 6 70
0.2
0.4
0.6
0.8
1
Vastus Lateralis
time in s
no
rma
lize
d v
alu
e
Test: EMG envelopeCAE: muscle activity
0 1 2 3 4 5 6 70
0.2
0.4
0.6
0.8
1
Rectus Femoris
time in s
no
rma
lize
d v
alu
e
Test: EMG envelopeCAE: muscle activity
Validation Study: Braking
Research & Advanced Engineering
CAE Parameter Variation: Seating Position
x
y
z
AnyBody Car Driver Model,
Ford Mondeo package,
artificial brake characteristic,
variation of the H-point,
50% female human model,
DoE with full factorial design,
3rd order polynomial model
(without cubic effect of y-pos,
due to array construction)
Factor min max levels
x-pos -0,16 -0,08 5
y-pos -0,01 0,01 3
z-pos -0,025 0,05 4
[m], 50% female pos. , compared to 95% male H-point
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y_pos=0,0
x_posz_pos
max_Act0,40,420,440,460,480,5
-0,16-0,14-0,12-0,1-0,08
-250
2550
(X 0,001)
0,4
0,45
0,5
CAE Parameter Variation: Seating Position
Main Effects Plot for max_Act
ma
x_
Act
x_pos-0.16 -0.08
y_pos-0.01 0.01
z_pos-0.025 0.05
0,4
0,42
0,44
0,46
0,48
0,5
Interaction Plot for max_Act
ma
x_
Act
AB-0.16 -0.08
-
-
+ +
AC-0.16 -0.08
- -
++
BC-0.01 0.01
-
-
++
0,4
0,42
0,44
0,46
0,48
0,5
Factor min max levels
x-pos -0,16 -0,08 5
y-pos -0,01 0,01 3
z-pos -0,025 0,05 4
[m], 50% female pos. , compared to 95% male H-point
R
%96 2
=adjRmodel polynomial order 3rd
Research & Advanced Engineering
y_pos=0,0
x_pos
z_pos
mean_A
ct
-0,16-0,14-0,12
-0,1-0,08
-2502550
(X 0,001)
26
28
30
32
34
36
(X 0,001)
Main Effects Plot for mean_Act
me
an_A
ct
x_pos-0.16 -0.08
y_pos-0.01 0.01
z_pos-0.025 0.05
26
27
28
29
30
31
32(X 0,001) Interaction Plot for mean_Act
me
an
_A
ct
AB-0.16 -0.08
-
-
+
+
AC-0.16 -0.08
-
-
+
+
BC-0.01 0.01
-
-
+ +
26
28
30
32
34
36(X 0,001)
Factor min max levels
x-pos -0,16 -0,08 5
y-pos -0,01 0,01 3
z-pos -0,025 0,05 4
[m], 50% female pos. , compared to 95% male H-point
CAE Parameter Variation: Seating Position
%6,98 2
=adjRmodel polynomial order 3rd
Research & Advanced Engineering
Conclusions
Computer Aided Ergonomics is a valuable tool to improve the vehicle design.
Many working areas need to be addressed simultaneously.
Several of them are related to the human body as such,
others will streamline the workflow and speed up the turn around time.
The validation results of the AnyBody Car Driver Model are promising.
Meta-modelling helps to communicate results to the product development.
DoE seems to work well in this context.
?