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FOR OFFICIAL USE ONLY 1 UNCLASSIFIED: Distribution Statement A. Approved for public release. 1

Mobility of Military Vehicles at TARDEC Amandeep Singh, Ph.D., P.E. May 15, 2012

[email protected]

Presented at SAE Heavy Truck Handling, Dynamics, & Control Symposium, Greenville,

SC, May 15-17

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1. REPORT DATE 15 MAY 2012

2. REPORT TYPE Briefing Charts

3. DATES COVERED 15-04-2012 to 14-05-2012

4. TITLE AND SUBTITLE Mobility of Military Vehicles at TARDEC

5a. CONTRACT NUMBER

5b. GRANT NUMBER

5c. PROGRAM ELEMENT NUMBER

6. AUTHOR(S) Amandeep Sing

5d. PROJECT NUMBER

5e. TASK NUMBER

5f. WORK UNIT NUMBER

7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) U.S. Army TARDEC,6501 East Eleven Mile Rd,Warren,Mi,48397-5000

8. PERFORMING ORGANIZATIONREPORT NUMBER #22912

9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) U.S. Army TARDEC, 6501 East Eleven Mile Rd, Warren, Mi, 48397-5000

10. SPONSOR/MONITOR’S ACRONYM(S) TARDEC

11. SPONSOR/MONITOR’S REPORT NUMBER(S) #22912

12. DISTRIBUTION/AVAILABILITY STATEMENT Approved for public release; distribution unlimited

13. SUPPLEMENTARY NOTES Present at SAE Heavy Truck Handling, Dynamics, & Control Symposium, Greenville, SC May 15-17

14. ABSTRACT -History and Background -Modeling and Simulation at TARDEC -Current Research Efforts -FutureGrowth and Trends

15. SUBJECT TERMS

16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT

Public Release

18. NUMBEROF PAGES

38

19a. NAME OFRESPONSIBLE PERSON

a. REPORT unclassified

b. ABSTRACT unclassified

c. THIS PAGE unclassified

Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18

UNCLASSIFIED 2 2

Disclaimer

“Reference herein to any specific commercial company, product, process, or services by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or the Department of the Army (DoA). The opinions of the author expressed herein do not necessarily state or reflect those of the United States Government or the DoA, and shall not be used for advertising or product endorsement purposes”

UNCLASSIFIED 3 3

Agenda

History and Background

Modeling and Simulation at TARDEC

Current Research Efforts

Future Growth and Trends

UNCLASSIFIED 4

Historical

Dr. Gregory Bekker Considered by many to be the founder of Terra-mechanics as an engineering discipline. Worked at the Army Vehicle Lab (now TARDEC) late 1950’s and early 1960’s.. The Army Mobility Model (NRMM) was co-developed in the 1960’s by TARDEC and Waterways Experiment Station (now ERDEC). Absorbed Power Criteria Developed in the 1960’s at TARDEC by Pradko & Lee. Dynamic Analysis and Design System (DADS) – Developed at U of Iowa for TARDEC in the 1980’s, now commercial.

UNCLASSIFIED 5

Ride and Shock Quality Research

1962-1972

DITIOIT AUINAL NIO. NO. C- ~82 1 • DATE I Feb 6Z Oynunlc Slmull\tlon• l..&boTatory Dnver111 s~ ... ~ Act:.Qn 'l'E!st .

TECHNOLDGY DRNEN. WARRGHTER FOOJSED.

UNCLASSIFIED 6

Analog Computer Used to Compute

Absorbed Power to Quantify Ride Quality


UNCLASSIFIED 7

Astronaut Lunar Rover Training

Date Unknown


UNCLASSIFIED 8 8

Pre-DADS Formulation of Coupled M113s 1977

S23

$13 Sll 520 stl

UNCLASSIFIED 9 9

Pre-DADS Animations of Coupled M113s 1977

t • 0 t • .. t • 8

t • 1 t - 5 t • 9

t - 2 t - 6 t - 10

t •U

t.' . t. 7


UNCLASSIFIED 10

1980

1982

1981

Pre-DADS Simulations


UNCLASSIFIED 11

HEMTT-HEMAT

Ca. 1985


UNCLASSIFIED 12 12 30 May 2012

HPC & Data Management

Concepts C A SS I

Analytics Hardware & Man-In-The-Loop Simulation

Integration & Demonstrators

FTTS

JLTV

Future Force

MRAP

Thermal / CFD

Crew Safety

Structures/Durability

Blast Dynamics

Characterization Durability

Human Dimension

Turret Testing

Virtual Environments

CAVE – Virtual Design Reviews

HPC

CAV

Concepts / Analysis / System Simulation / Integration (CASSI)

Key Partnerships with TARDEC Technology Groups, other Army RDECs/Labs, PM’s,

TRADOC – MCOE, TACOM Sys & Cost Analysis, ATEC

System-centric, M&S-based Services to integrate and assess

the impacts of new concepts/technologies and upgrades to existing systems.

FED

JRaDS

TWVS

12

UNCLASSIFIED 13 13

• Vehicle Dynamics

– Ride and Shock Quality

– Lateral Stability

– Handling (oversteer / understeer)

– Braking

– Rollover

– Soft-soil Mobility

– Suspension/vehicle Loads

• Structural Analysis

– Reliability Modeling and Analysis

– Failure analysis

– Durability degradation

• Technology Insertion

– Semi active/Active suspensions

– Weight growth issues

– Others (suspension upgrades, etc)

• Research and Development

– Operational uncertainties and Reliability

– Accelerated Testing

– Rollover

– Track, Tire and Terrain Modeling etc.

Acquisition and Life Cycle M&S Support (CASSI “A” Analytics-Dynamics and Structures)

UNCLASSIFIED 14 14

CASSI “SS” – System Simulation

Turret Motion Base Simulator

Distributed Simulation

Physical Simulation

Ground Vehicle Simulation Laboratory

• Vehicle Characterization

• System Durability Studies

• Performance Validation

• System “Shakedown” Testing

• Man-In-the-Loop Testing

Ride Motion Simulator

UNCLASSIFIED 15 15

TARDEC’s Suspension Characterization Machine

Suspension vertical stiffness

Toe vs. vertical travel

Camber vs. vertical travel

Roll Center Height

Overall Steering Ratio

Wheel X,Y,Z motion wrt. travel

Machine Specs:

Vehicle Weight Capacity: up to 100,000

lbs

Suspension Travel: Up to 24 in (total)

Maximum Compressive Force: 60,000 lbs

per axle.

Track width: up to 110 in.

Vehicle width up to 150 inches.

Wheel base up to 325 inches.

Vehicle length up to 600 inches.

UNCLASSIFIED 16

HMMWV FoV

Bradley – AoA,

Upgrade

Assessment

Major Programs Supported

XM1124 HE HMMWV - Hybrid

Electric Vehicle Evaluation and

Assessment

FMTV FoV – Armor

Effects on

Performance

JLTV - SSEB, AoA, TD Phase

Performance Assessments

HEMTT – Armor Effects on

Performance M915/NGLH – Armor

Effects on Performance

MRAPs – SSEB, Tech Insertion,

Armor/Power Effects on

Performance

Stryker – Belly

Armor/Power

Effects on

Performance

Abrams – AGT

1500 Testing,

AoA

GCV – Concept Analysis,

Power Pack Sizing, Req’t

Definition, CDD Support

Paladin – PIM

Analysis

UNCLASSIFIED 17

Joint Recovery and Distribution

System (JRaDS) Joint

Capability Technology

Demonstration (JCTD) Program

Major Programs Supported (Cont’d)

Armored Security Vehicle (ASV)

Joint Explosive Ordnance

Disposal Rapid Response

Vehicle (JERRV)

Expanded Capacity Vehicle (ECV)

MRAP All Terrain Vehicle (M-ATV)

Future Tactical Truck System (FTTS)

UNCLASSIFIED 18 18

Mobility Requirements in Military Vehicles

Conventionally, tied to operational performance:

• Ride Quality: 6W Absorbed Power, Half-round Bumps

• NATO Lane Change

• Turning Radius

• Lateral Acceleration Capability in a Steady State Turn

• Soft Soil Mobility, Vehicle Cone Index

• Tilt Table

Open Research Ideas:

• Requirements based on operational uncertainties

• Off-road rollover

• ESC performance under on-road and off-road conditions

• New soft-soil mobility metrics

• Steering feel for fatigue, driving confidence

UNCLASSIFIED 19 19

Current Research Effort Examples

• Investigating state of the art active suspension technologies (such as MR damper) using driving simulators

• Developing active/semi-active suspension for off-road rollover mitigation and ride quality.

• Considering probabilistic approach for operational uncertainties, reliability, and lifecycle cost.

• Developing accelerated testing techniques to improve reliability and mobility.

• Utilizing multi-disciplinary approach to maximize survivability while meeting land mobility requirements (and water mobility for amphibious).

• Terrain, track, and tire modeling, etc.

• …

UNCLASSIFIED 20

Man-in-the-Loop Simulation Example

Examine the effectiveness of MR dampers against passive dampers on

a Stryker Vehicle

Munson Gravel

Belgian Block

Height Field

Vertical Acceleration Belgian Block

Time (100 seconds)

Ve

rtic

al

Ac

ce

lera

tio

n (

g’s

)

_____ Test Data _____ Sim Data

UNCLASSIFIED 21

Model Validation

• Driver in the loop

• Max lateral acceleration on skidpad

– 0.4G max lateral acceleration at 40 mph

• NATO lane change

– Roll Rate

• Ride on simulated Belgian Block course

– Vertical Acceleration

Vertical Acceleration Belgian Block

Time (100 seconds)

Ve

rtic

al

Ac

ce

lera

tio

n (

g’s

)


Time (100 seconds)

Ro

ll R

ate

(d

eg

/s)


UNCLASSIFIED 22

NURBS & Height Field Modeling

• NURBS

– Used the Munson Gravel courses based on RMS values of Munson Gravel.

• Height Field

– Uses texture and RMS of Belgian Block created from photographs of Belgian Block Course

– Driven and reworked to produce representative response based on test data.

Munson Gravel

Visual Texture

Belgian Block

Visual Texture

Munson Gravel

NURBS

Belgian Block

Height Field

Challenges

Suspension performance requires enough resolution to capture suspension

modes

Very dense terrain degrades real-time performance

UNCLASSIFIED 23

Ride Demonstration Results

Sample Vertical Acceleration

Sample Absorbed Power

Demonstrated Benefits:

Lower Vertical Acceleration

Reduced absorbed power

Improved subjective

experience

UNCLASSIFIED 24

Operational Uncertainties

(Ride Example)

0 200 400 600 800 1000-3

-2

-1

0

1

2

3

4

Roa

d H

eigh

t, in

Longitudinal Distance, ft

20 40 60 80 100

-2

-1

0

1

2

3

Time

Ver

tica

l A

ccel

erat

ion

in

G, S

(d,X

,t)

Vertical Accel. (G)

Terrain

Random Variables

Stochastic Input Stochastic Output

Requires Probabilistic Approach

UNCLASSIFIED 25

Quarter-Car Model on Stochastic Terrain

ms

mu

ks bs

bt kt

u(t)

xu

xs

Random Input variables

)1400,7000(~ 2NbsDamping,

Stiffness, ))104(,1040(~ 233 Nks

Random Input Process: Experimental

Stochastic Terrain from Yuma Proving

Grounds.

0 200 400 600 800 1000-3

-2

-1

0

1

2

3

4

Roa

d H

eigh

t, in


Constant design

parameters:

ms =1000 kg

mu =100 kg

Vehicle speed = 20 mph

20 40 60 80 100

-2

-1

0

1

2

3

Time

Ver

tica

l A

ccel

erat

ion

in

G,

S(d

,X,t

)

Random Output Process

(Vertical Acceleration, G’)

Threshold = 2G

UNCLASSIFIED 26

Quarter-Car Model: Road Input Random Process Characterization

AR(3) model was identified based on:

0 10 20 30 40 50-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

Lag

Sam

ple

Au

toco

rrel

atio

n

Sample Autocorrelation Function (ACF)

0 10 20 30 40 50-0.2

0

0.2

0.4

0.6

0.8

LagS

amp

le A

uto

corr

elat

ion

Sample Autocorrelation Function (ACF)

Autocorrelation

Function

Autocorrelation of

Residual process

Statistical tests were performed to verify the model

)5132.0,0(1954.02976.02456.1 2

321 iiiii uuuu

UNCLASSIFIED 27

Observations

0 200 400 600 800 1000-3

-2

-1

0

1

2

3

4

Roa

d H

eigh

t, in


20 40 60 80 100

-2

-1

0

1

2

3

Time

Ver

tica

l A

ccel

erat

ion

in

G, S

(d,X

,t)

Accel. (G)

Terrain

Stationary

input random

process

Linear

system +

Stationary

output random

process

Constant (time-independent) failure

rate

UNCLASSIFIED 28

0 200 400 600 800 1000-3

-2

-1

0

1

2

3

4

Roa

d H

eigh

t, in

Longitudinal Distance, ft 20 40 60 80 100

-2

-1

0

1

2

3

Time

Ver

tica

l A

ccel

erat

ion

in

G, S

(d,X

,t)

Accel. (G)

Terrain

Random Variables

Observations

Time-dependent failure rate

0 20 40 60 80 1000

0.05

0.1

0.15

0.2

Time, sec

Fail

ure

Rate

MCS 500,000 samp

IS 10,000 samp

UNCLASSIFIED 29

Problem Description/Approach

Vehicle speed : 20 mph; Mission distance : 100 miles

Simulation can be practically performed for a short-

duration time

A novel MC-based method to calculate failure rate based on :

Short-duration data and an exponential extrapolation

using MCS or Importance Sampling or Subset

Simulation (Infant Mortality)

Poisson’s assumption (Useful Life)

UNCLASSIFIED 30

btet 0)(ˆ

00

ˆ1

tdt

db

MCS

Exponential

Extrapolation

0

Poisson’s

Assumption tint

Efficient MC Simulation Approach

],[,))(1(1

],0[,1)(

int

)(

int

int

ˆ

int

0

f

ttc

T

dtt

c

T

tttetF

ttetF

m

t

UNCLASSIFIED 31 31

Principle of Importance Sampling: Random Variable Case

Feasible

Region

Increased Performance

x2

x1

f(x1,x2)

contours

g1(x1,x2)=0

g2(x1,x2)=0

Reliable

Optimum fn

UNCLASSIFIED 32

);(

);(),(

i

ii

tf

tft

S x

xx

X

X : Likelihood ratio

at it

1iS tN 1it: Safe sample points

at

if tN 1 ii ttt: Number of failures in

)(

),(

lim)(1

1

0

iS

tN

n

i

ti

tNt

t

t

if

x

Importance Sampling for Random Process

where:

UNCLASSIFIED 33

Quarter-Car Model on Stochastic Terrain

ms

mu

ks bs

bt kt

u(t)

xu

xs

Random Input variables

)1400,7000(~ 2NbsDamping,

Stiffness, ))104(,1040(~ 233 Nks

Random Input Process: Experimental

Stochastic Terrain from Yuma Proving

Grounds.

0 200 400 600 800 1000-3

-2

-1

0

1

2

3

4

Roa

d H

eigh

t, in


Constant design

parameters:

ms =1000 kg

mu =100 kg

Vehicle speed = 20 mph

20 40 60 80 100

-2

-1

0

1

2

3

Time

Ver

tica

l A

ccel

erat

ion

in

G,

S(d

,X,t

)

Random Output Process

(Vertical Acceleration, G’)

Threshold = 2G

UNCLASSIFIED 34

Quarter-Car Example

0 20 40 60 80 100-4

-2

0

2

4

Time, sec

Ver

tica

l A

ccel

erat

ion

,G

0 20 40 60 80 100-4

-2

0

2

4

Time, sec

Ver

tica

l A

ccel

erat

ion

,G

Original PDF 51.0e Sampling

PDF

7.0s

The sampling PDF results in more failures

)5132.0,0(1954.02976.02456.1 2

321 iiiii uuuu

UNCLASSIFIED 35

Threshold = 2 g Threshold = 2.65 g

0 20 40 60 80 1000

0.002

0.004

0.006

0.008

0.01

0.012

0.014

Fai

lure

Rat

e

Time, sec

MCS 500,000 samp

IS 10,000 samp

0 20 40 60 80 1000

0.05

0.1

0.15

0.2

Time, sec

Fail

ure

Rate

MCS 500,000 samp

IS 10,000 samp

Non-Stationary Case

Quarter-Car Example

UNCLASSIFIED 36 36

Accelerated Testing Research

Actuator Capabilities

• Force ration 190 KN • Dynamic stroke 355 mm • Velocity 9.1 m/sec • Force rating of load cell transducer 55 Kip

Analysis Capabilities

• Fatigue Damage Estimate • Statistical Time History Editing • Cycle Counting Analysis

UNCLASSIFIED 37 37

How to Get Involved in Research with TARDEC

• SBIR- Small Business Innovative Research

• Automotive Research Center (ARC)- Alliance between US Army and academia (University of Michigan- Ann Arbor, Clemson University, Oakland University, Virginia Tech, and others). http://arc.engin.umich.edu/.

• Simulation Based Reliability and Safety (SimBRS)

• Cooperative Research and Development Agreement (CRADA).

• Innovation Grants

UNCLASSIFIED 38 38

Thank You!

Q&A

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