MSC Software Confidential MSC Software Confidential

Evaluation and Optimization of

Damper strategies using co-simulations

Presented By: Arun Kumar (A. K.) Chandrasekaran

May 14, 2013

MSC Software Confidential

• Background

• ADAMS and Parameterized Damper model

• Simulation Results

• Optimization

Agenda

2

MSC Software Confidential

• Damper curve optimization for improved ride qualtiy

performance

• Increased damping to improve performance on high RMS

courses causes the performance on lower RMS courses to suffer

– Investigate position dependant damper technology to get

around this challenge

• Also investigate wheel energy to evaluate potential fuel economy

savings from improved ride

Background

3

MSC Software Confidential

• Multi-body Dynamic model in ADAMS/Car

• Accurate model of chassis and suspension

• Basic model of powertrain

• Rigid ground model (no soft-soil considerations)

Approach

4

MSC Software Confidential

ADAMS and Damper models

5

Co-simulation with

MATLAB/Simulink and

ADAMS/Car was used to

optimize dampers

Multibody

Dynamics

Vehicle model in

ADAMS/Car

Parametric

damper model

in MATLAB/

Simulink

Damping Forces

Damper Velocity

and

Displacement

MSC Software Confidential

Co-simulation

6

MATLAB/Simulink Damper model

ADAMS/Car Vehicle Model

MSC Software Confidential

Courses Used

7

Five different courses

with varying terrain

roughness (RMS)

1”

1.5”

2”

2.5”

3”

MSC Software Confidential

• Total Damper force was modeled as a summation of a “pure velocity

dependant component” and a “position dependant component”

• The “pure velocity component” and the “position component” were

optimized separately

Damper Force

8

ntdisplacemedamper on dependant are and

Exponent -

Velocity -

speedmax at Force -

force dampingdependant Position -

*100

eF

e

V

F

F

where

VF

F

FFvF

MAX

MAX

PD

e

e

MAXPD

PDDamper

MSC Software Confidential

• “6W speed” – Speed of the vehicle at which Driver absorbed power is

6W

Criteria

9

Acceleration Absorbed

Power

For example, a 5Hz sin wave with peak amplitude of 0.25g will produce about 6 W

MSC Software Confidential

Fv Curve DoE

10

MSC Software Confidential

Fv Curve DoE - Results

11

Low RMS courses High RMS courses

MSC Software Confidential

FPD DoE

12

Position Dependant Damper Curve DoE

MSC Software Confidential

FPD DoE

13

Typical Damper Curve Candidate

Fo

rce

MSC Software Confidential

FPD DoE – Results

14

Low RMS courses

High RMS courses

MSC Software Confidential

FPD DoE

15

Position Dependant Damper Curve DoE

High

RMS

Low

RMS

Low

RMS

High

RMS

MSC Software Confidential

• Objective function derived from normalized 6W Speeds on

5 RMS courses

• Courses that were traditionally challenging were given a

higher weight

Multi-Objective Optimization

16

i

i

Reqt

6WspdiObj

MSC Software Confidential

Results – Ride

17

Average 40%

improvement

on 6W speeds

across RMS

range

MSC Software Confidential

Roughness Resistance

18

Simulations were ran with

detrended courses (no

grade), zero aerodynamic

drag, and zero (flat road)

rolling resistance tires

),( )( Const Coeff Resistance Rolling vRMSfvf

MSC Software Confidential

Results – Roughness Resistance

19

RR values

show

dependence

on RMS and

frequency

content of

courses

MSC Software Confidential

Results – Roughness Resistance

20

RR values are

passed onto

the fuel

economy

model to

determine mpg

improvement

MSC Software Confidential

Q&A

21

MSC Software Confidential 22