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Engine Optimization Methodologies: Tools and Strategies for Diesel Engine Design

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Engine Optimization Methodologies:

Engine Optimization Methodologies:

Tools and Strategies for

Tools and Strategies for

Diesel Engine Design

Diesel Engine Design

George Delagrammatikas

Dennis Assanis, Zoran Filipi, Panos Papalambros,

Nestor Michelena

The University of Michigan

May 24, 2000

(2)

BACKGROUND: VEHICLE AND ENGINE

FUNDAMENTALS ENGINE TUNING INVERSE DESIGN CVT, INJECTION TIMINGS MAP SHAPING AND MATCHING ENGINE FLEXIBILITY: COMPRESSION RATIO, CVT,HYBRID NOVEL TECHNOLOGIES

(3)

Motivation

Motivation

Federal Regulations

Fuel economy (CAFE)

Emissions (NOx, smog, and other pollutants)

Public Awareness

‘Green’ movement

Global warming scare

Decrease Dependence on Foreign Oil

(4)

Objectives

Objectives

Develop an engine optimization framework

21

st

century conventional and hybrid heavy truck

Implement techniques to conventional vehicle

Define a problem analytically

Apply suitable driving cycle(s)

Investigate location of use on engine map

(5)

Euro III Steady State Test Procedure

(6)

Power Demands on Engine

(7)

HEV System Simulation Framework

HEV System Simulation Framework

ADVISOR Matlab-SIMULINK environment

Parallel HEV

ENGINE FUEL DELIVERY LOOK-UP TABLE

RPM TORQUE

(8)

Baseline Vehicle Parameters

Baseline Vehicle Parameters

Cummins M11-330 (246 kW) Diesel Engine

Wheel/axle assembly for heavy truck

Kenworth T400 Vehicle

Standard heavy vehicle accessory loads

Standard catalyst for CI engine

Eaton Fuller RTLO-12610B 10-Speed Transmission

Generic 10-spd constant efficiency gearbox

(9)

Baseline Cummins Engine Map

(10)

Driving Cycles Investigated

Driving Cycles Investigated

US06 REP05

FHDS FUDS

(11)

Engine Use Points for Various Cycles

Engine Use Points for Various Cycles

US06 REP05

FHDS FUDS

(12)

Power Frequency for Each Cycle

Power Frequency for Each Cycle

US06 REP05

FHDS FUDS

(13)

Output Torque

Output Torque

Engine Speed

Engine Speed

Ideal BSFC Line Generation

(14)

Determine cumulative fuel throughput for

each cycle investigated

Interpolate BSFC from engine map for every

torque/speed combination for that given cycle

Integrate all BSFC’s from above step

Find the total time that engine is producing power

Mean effective BSFC = total BSFC/engine on time

Benefits of Flexible Engine Designs

Benefits of Flexible Engine Designs

Actual Transmission Case

(15)

Ideal BSFC

Ideal BSFC

vs

vs

. Power Level

. Power Level

Power

Power

BSFC (g/kW-hr)

(16)

Benefits of Flexible Engine Designs

Benefits of Flexible Engine Designs

Ideal Transmission Case

Ideal Transmission Case

Find ideal BSFC transmission line on engine

map used for a given cycle

Interpolate BSFC for every visited power level on

the BSFC vs. Power graph

Sum of all BSFC’s is cumulative fuel throughput

Mean effective BSFC = numerical average of total

fuel throughput during time steps when engine is

(17)

Potential Benefits of Ideal CVT Design

Potential Benefits of Ideal CVT Design

0 20 40 60 80 100 120 140

US06 REP05 FUDS FHDS

4*BSFCmin 2*BSFCmin

Incr

eas

e in M

ean BSFC Per

Cyc

le

Incr

eas

e in M

ean BSFC Per

Cyc

le

(18)

Optimum Injection Timing Method

Optimum Injection Timing Method

Using an optimization framework

Vary injection timing for every torque/speed

combination (over 200 map points, ~100 executions

per point)

Computationally prohibitive

Parallel computer framework

Run as many maps as you want at different

injection timings

(19)

Injection Timing Maps

Injection Timing Maps

Engine Speed

Engine Speed

Output Torque

(20)

Optimum Injection Timing Map

Optimum Injection Timing Map

Timing

(21)

Variable Compression Ratio Engine

Variable Compression Ratio Engine

Hypothetical investigation of novel engine

design

Find the ideal fuel consumption benefit

Apply ideal transmission techniques from previous

slides

Determine how BSFC can be optimized at

various power levels

First maximize power density to find engine’s

power upper bound

Allow engine controller to change parameters that

are not normally variable

(22)

Problem Formulation

Problem Formulation

For each power level :

50, 100, 200, 300, 400, 500 kW

Minimize BSFC, subject to:

overall phi < 0.6

20% < percent premixed burn < 40%

peak cylinder pressure < 150 bar

Variables:

(23)
(24)

VCRE - Combined Map

VCRE - Combined Map

TO

RQ

UE

TO

RQ

UE

(25)

Ideal BSFC Line vs. Power Level

170 180 190 200 210 220 230 240 50 100 150 200 250 300 350 400 450 500

Power (kW)

BS

FC (

g

/k

W

-hr)

vcre_bsfc base_bsfc

(26)

Hybrid Powertrain Investigations

(27)

Demands on Engine - CVT vs. 5-Speed

(28)

Demands on Motor - CVT vs. 5-Speed

(29)

Battery SOC - CVT vs. 5-Speed

(30)

Zero Delta SOC - CVT vs. 5-Speed

(31)

Additional Hybrid Clustering Scenarios

Additional Hybrid Clustering Scenarios

Power-Assist Battery Recharge 40 20 60

(32)

Future Directions

Future Directions

How realistic is the variable compression ratio

engine for the driving cycles and vehicles we are

considering?

How can we better quantify the benefits of

increased flexibility in transmission parameters?

What are the effects of injection timing and

variable valve timing on engine map

characteristics?

(33)

Integration with Target Cascading

Integration with Target Cascading

Parameterize engine torque curve

Maximize engine turndown ratio while

meeting mobility constraints

Match maximum torque curve with a real

engine defined by high fidelity model

Use engine visitation points in conjunction

with control strategies to meet BSFC and

emissions targets

Send results back to top level for verification

and subsequent iteration

(34)

Parameterized Max Torque Curve - I

(35)

Parameterized Max Torque Curve - II

(36)

Sample Torque Curves

Sample Torque Curves

(37)

Engine

Engine

Matching

Matching

Subproblem

Subproblem

(38)

Conclusions

Conclusions

High fidelity engine model can be used at

different levels in the design process

Methods have been illustrated on a variety of

different engines

Continue feed-backward work with ADVISOR

and extend methodology to VESIM

References

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