Shape Optimization of Engine Moving Components with Hyper-Study Integration

April 23th, 2013

Sangwoo, Cha

Shape Optimization of Engine Moving Components

with Hyper-Study Integration

Hyundai·Kia Motors R&D Center

Session1: Optimization

Contents

Introduction

- Overview: engine moving components

Shape Optimization of connecting rod

- Analysis Procedure

- Approach for weight reduction

- Optimization results and shape

Shape Optimization of engine piston



- Optimization results and shape

Conclusion

- Summary and conclusions

Overview: engine moving components

Engine moving system

- composed of Piston, Connecting rod, Crankshaft

Role of piston and connecting rod

- transferring force from expanding gas by firing to the crankshaft for making engine power

Increasing needs for Optimization

- CO2 emissions and cost down by weight reduction

- frequently, failure occurrence by the hard condition according to the trend of high power

Connecting rod failure Piston failure

Connecting rod Piston

Crankshaft

Introduction

Contents

Introduction





- Result and Optimized shape





Conclusion


Analysis Procedure Connecting rod

FE model construction

Optimization definition

Structural analysis

Evaluation: postprocessing

Optimization analyze/result

Optimization(Iteration)

Sensitivity through DOE

Re-Optimization

Optimization results and shape

Sensitivity

Optimized shape design

Suggestion of design parameter

Optimization shape design

Fatigue

Safety Factor Deformation Buckling

Safety Factor

Simulation: 4 load case (batch job)

Hypermesh

Design variable: morphing

Hyperstudy

Objective function and

restraint definition

FEMFAT In-house S/W In-house S/W

Assembly Tension/

Compression Buckling

*ABAQUS

Evaluation item for durability Connecting rod

Indirect

evaluation of

bearing wear

Buckling

prediction

Fatigue Safety Factor Big end Stiffness Buckling Safety Factor Item

Problem

/

Analysis

result

Evaluation

What: fatigue safety factor

How: ratio of multi-axial stress

amplitude and fatigue strength

S/W: FEMFAT

Fatigue failure

prediction

What: Big end deformation

How: calculation at tension

loading by least square method

S/W: In-house program

What: Buckling due to high

combustion force

How: Merchant-Rankine formula

(considering eigenvalue, plastic)

S/W: In-house program

Criterion Sorry, it’s confidential

Connecting rod Optimization approach

Optimization objective

- Minimize current connecting rod weight

Response and Constraint

- Fatigue safety factor

- Big end stiffness

- Buckling safety factor

Shape restraint

- No interference with piston and cylinder

block at the dynamic motion

- Limit of the manufacturing tool

(ex. Curvature and angle of cutting tool)

- No big change of the metallic pattern

Criterion

satisfaction

Piston pin

Crankshaft

Connecting

rod

Cap

Rod

Design variables: morphing shape Connecting rod

Small end diameter Small end thickness Shank width(outer)

Shank width(inner) Shank thickness1 Shank thickness2

*Outer *Inner

(section)

HyperMorph

- definition of domain, handle

- based on the design history(PROE)

Design variables

- total 6 shape variables

Upper, lower bound

- using sensitivity analysis(DOE)

Domain, handle

Small end

shank

Big end

Connecting rod Optimization results

Objective Weight 9%,

Constraint

Fatigue Safety Factor

Big end stiffness

Buckling Safety Factor

Response Result

11%,

Same

7%,

Design variable history


But, Criterion satisfaction

Bad

Good

Current Optimization

Optimization shape Connecting rod

Optimization process Measuring dimension(optimization shape)

CAD design(at the design team)

: Current

: Change

: Optimization

Contents

Introduction










Conclusion


Analysis Procedure Piston

Structural analysis

Optimization(Automation and Iteration)

Stress analysis: ABAQUS s/w

Evaluation: postprocessing

Fatigue Safety Factor: FEMFAT s/w

Mass center Extract (from ABAQUS *.dat)

ABAQUS keyword:

Mass center of

element set

Reading safety factor

from FEMFAT result Load and boundary condition

Stress distribution FE model

* temperature * profile: skirt,

pin hole

* Firing pressure,

side force, inertia

Optimization approach Piston

Optimization objective

- Minimize current piston weight

Response and Constraint

- Fatigue safety factor: Criterion satisfaction

- Piston mass center: +/- 5% change bound

(no great difference in the dynamic characteristics)

Shape restraint

- No change of piston crown thickness

(no great difference in the piston temperature)

- Limit of the thickness for casting process

* After optimization for weight reduction, dynamic

analysis is needed for dynamic characteristics Dynamic analysis(using PISDYN)

Crown thickness

Mass center

Piston Design variables: morphing shape

RH thickness

Under-crown area Bottom height

Thrust thickness

LH thickness Oil drain height Oil drain thickness

A-thrust thickness Thrust skirt angle A-thrust skirt angle

Domain, handle

Piston Optimization results

Objective Weight 11%,

Constraint


Piston mass center

Response Result

10%,

Same But, Criterion satisfaction

Objective(weight) history

Optimization weight

Bad

Good


Current

Optimization

Piston Optimization shape

Measuring dimension(optimization shape)

CAD design(at the design team)

: Current : Change : Optimization

Optimization process

Contents

Introduction










Conclusion


Conclusions

Using the shape optimization techniques with Hyper-Study,

1) for the connecting rod, a mass reduction of 9% was achieved.

2) for the piston, a mass reduction of 11% was achieved.

satisfying the restraint and manufacturing restriction

Defining the design variables based on the PRO/E model history,

the optimized shape was easily transferred to the CAD design.

HMC has applied the optimization techniques using Optistruct,

Hyper-study for weight reduction or durability increase of the

other engine components.

Summary and Conclusions

On going study..

Crankshaft optimization

: Current

: Optimization

* Substructuring method for solving

Thank you for your attention !!

Shape Optimization of Engine Moving Components with Hyper-Study Integration

Technology

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