Xin Q. Diesel Engine System Design

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66 Diesel engine system design

shows the time required for the expected fuel savings to offset the device

cost. The payback period is the ratio of the amount of money spent on the

device to the amount of money saved. It is observed that vehicle mileage

has an exponential effect on the payback period. The device cost has a

dominant effect on the payback period. Retail diesel fuel price, vehicle fuel

economy and fuel economy saving percentage all have very strong effects on

the payback period. The general trends that result in a short payback period

can be summarized as follows: lower device cost, increased fuel economy,

increased mileage, and increased diesel fuel price. For heavy-duty long haul

trucks a payback period of less than three years is desirable since many eets

replace trucks after approximately three to four years.

Figure 1.21 is a general purpose illustration to demonstrate the methodology

used in cost analysis. It should be noted that in Fig. 1.21 the additional cost

associated with any secondary uid such as the liquid-based urea used in

SCR (if the device refers to an SCR system) has not been included. When

the operating cost of such a secondary uid is included, the payback period

will be much longer (worse) than that shown in Fig. 1.21.

1.4.7 Review of existing engine cost analysis methods

Fundamental theories of cost analysis and estimating for engineering and

management have been provided by Park and Jackson (1984), Ostwald and

McLaren (2004), and Humphreys (2005).

In the cost–benet analysis for automotive technologies, regulatory agencies

and research institutes have been largely interested in the cost analysis related

to advanced diesel emissions aftertreatment technologies, advanced fuels,

well-to-wheel efciencies of various powertrain technologies, and energy

policies. Generally, the conclusions about a particular technology drawn

from a global viewpoint of the entire society may not be valid at a corporate

level due to the differences in the assumptions of sales volume and other

technical or economical factors. Each company has a unique situation, and

it is important to develop their own cost–benet analysis in order to reach

a wise business decision.

Walsh (1983, 1984) conducted studies on the costs and benets of diesel

particulate control for the North American market. Browning (1997) provided

an overview of the technologies and incremental costs for meeting the US

2004 emissions standards for heavy-duty diesel engines. Burke (2003) used

Excel spreadsheet cost models to show the trade-offs between fuel savings

and economic attractiveness for different hybrid-electric powertrains (mild and

full hybrids) in light-duty vehicles (passenger cars and mid-size SUVs).

State and local agencies use cost-effectiveness as one criterion to decide

whether to implement a particular emissions control program. The cost-

effectiveness is dened as the ratio of the dollar amount to the unit of effect

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67The analytical design process and diesel engine system design

produced by the cost. In a Texas government program, Prozzi et al. (2004)

investigated the cost-effectiveness of an emulsied diesel fuel for highway

construction equipment eets by thoroughly quantifying many sources of cost

impact (e.g., fuel cost penalty, implementation and conversion cost, fuel economy

penalty effects, re-fueling penalty, fuel–emulsion mixing cost, cost of lower

equipment productivity due to the loss of torque, increased maintenance cost,

fuel storage cost, etc.). They concluded that the fuel tested (Lubrizol’s PuriNO

)

is a relatively high cost strategy for NO

reduction, and it will become much

less cost-effective in reducing NO

emissions as the eet replaces the older

engines with new, cleaner electronically-controlled engines. Matthews et al.

(2005) evaluated the effects of an ultra-low-sulfur diesel fuel on emissions, fuel

economy and maintenance cost, and they also calculated the cost-effectiveness

in terms of dollars of cost penalty per ton of NO

removed.

Life cycle assessment is a ‘cradle-to-grave’ approach for assessing a

technology from production and use to nal disposal. Ginn et al. (2004) presented

a comprehensive life cycle economic assessment to compare four alternative

technologies to conventional diesel engine idling for heavy-duty vehicles. The

long haul trucks are idled for a long period of time (e.g., overnight) to heat

or cool the cabin, to keep the engine warm, and to run electrical accessories.

The idling time can be 2400 hours per year. It results in a large amount of

emissions, fuel consumption, and increased engine wear. Ginn et al. (2004)

compared four alternatives (auxiliary power unit, direct-red heater, truck

stop electrication, and advanced truck stop electrication) and assessed

their emissions benets, environmental impact, fuel savings, maintenance/

wear savings, payback period, net present value, and the emissions savings

per dollar cost of technology (i.e., the reciprocal of cost-effectiveness).

Li et al. (2004) introduced a demand–cost–prot economic analysis

method applied to the design decision making about engine manifold surface

nishing. The performance benets on power and BSFC due to improved

manifold surface roughness were simulated with an engine cycle simulation

software package. The microeconomic theory and a demand–cost–prot

model were introduced along with optimization techniques (to maximize the

prot associated with the design) to bridge engine performance simulation,

cost analysis and business decision making. This work provided an attempt

on design for prot.

Diesel engine system cost analysis is a new and challenging inter-disciplinary

eld. It will receive increasing attention from the technical community.

1.5 Competitive benchmarking analysis

1.5.1 The need for competitive benchmarking analysis

Benchmarking is a systematic approach to identifying standards for

comparison. It reveals the gaps in design attributes and provides ideas for

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68 Diesel engine system design

design improvement. Benchmarking should include best-in-class objective

attribute measures and research into how this attribute is achieved.

1.5.2 Methods of competitive benchmarking analysis

Heavy-duty diesel engine design details can be found in numerous books

(for example, the overview by Merrion and Weber, 1999; Heisler, 1995; and

the vehicular engine design textbook by Hoag, 2006). These works cover

empirical design guidelines for engine layout and component details including

engine balance, cylinder head, block, water jacket, bearing, gasket, piston,

crankshaft, camshaft, etc. Advanced design software and nite element analysis

have been widely used in those areas. However, from the point of view of

diesel engine system design, another way to enhance the quality of analysis

in these traditional design areas is to apply a competitive benchmarking

design analysis technique. The technique analyzes one fundamental design

parameter against another by using a large amount of different engine design

data to form empirical trend curves in order to check whether the subject

design falls within or outside the range of the trend. The concept is illustrated

in Fig. 1.22. A simple example is to plot stroke-to-bore ratio versus engine

displacement for multiple engine power ratings. Such a competitive analysis

is very effective for stroke and bore design. In fact, advanced competitive

Design parameter B

Design parameter A (single or combined, dimensional or

dimensionless)

Design subject

to evaluation

Group-2 design

competitive trend

Group-1 design

competitive trend

Contours of constant C

Competitive engine data

1.22 Approach of competitive benchmarking analysis.

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69The analytical design process and diesel engine system design

analysis is much more complex than that, because it requires heuristic

modeling and sometimes similarity theory to extract and group apparent

design parameters in order to reect the fundamental physics. Usually, in

each complex mechanical system, it is possible to extract one or several

fundamental design parameters in a certain combined form that manifests

their physical nature of performance or durability in a rather intuitive and

simple manner. Through such an analysis, major design problems can be

quickly identied for further examination. It is very important to identify

those characteristic design parameters for each component and system.

1.5.3 Basic engine system design parameters

Engine system design features are usually measured by certain basic system

parameters describing the overall engine performance or characteristics, such

as power density, vehicle power-to-weight ratio, high altitude capability

without derating, cold start capability, adequate cooling capacity at hot

ambient temperature, etc. Basic engine system design parameters are very

important for analyzing performance and durability at an overall system

level. Some of the commonly used basic engine system parameters are

presented as follows:

∑ The number of cylinders, which affects the compactness of the engine

and torque balance.

∑ Engine displacement, which affects engine power density.

∑ Cylinder centerline distance, conrod length, and piston compression

height.

∑ Engine cylinder bore diameter, which affects engine weight and wear.

∑ Engine stroke, which affects stroke-to-bore ratio, mean piston speed,

engine speed, and engine friction.

∑ Stroke-to-bore ratio, which affects bore, stroke, engine speed, combustion

chamber clearance, emissions, and heat rejection.

∑ Engine compression ratio, which affects emissions, thermodynamic cycle

efciency, peak cylinder pressure, engine friction, and cold start.

∑ Rated power, which usually determines the most severe thermo-mechanical

condition for structural design.

∑ Rated BMEP, which is the rated torque per engine displacement volume

and is comparable for different engine sizes.

∑ Rated speed, which affects engine rated power and engine–transmission

matching for vehicles.

∑ Rated mean piston speed, which affects the gas-ow velocities in the

intake/exhaust ports and the cylinder, the thermal load and inertia load

in components, engine friction, and wear.

∑ Peak torque, which determines the torque backup and turbine area.

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70 Diesel engine system design

∑ Peak torque speed, which affects the speed reserve and engine–transmission

matching.

∑ Peak BMEP, which is the peak torque per engine displacement volume

and is comparable for different engine sizes.

∑ The coef cient of torque backup, which is equal to the ratio of peak

torque to the torque at rated power, and affects vehicle drivability and

the engine stability to resist a load increase.

∑ The coef cient of speed reserve, which is equal to the ratio of rated

speed to peak-torque speed, and affects vehicle drivability.

∑ The coef cient of adaptability, which is equal to the coef cient of torque

backup multiplied by the coef cient of speed reserve.

∑ The coef cient of rated intensity, which is equal to rated BMEP multiplied

by rated mean piston speed.

∑ Engine weight.

∑ Engine speci c power (also called power density), which is the rated

power per engine displacement volume.

∑ Engine power per piston area, which basically re ects the thermal load

per unit area of the combustion chamber.

∑ Engine weight per displacement volume (also called weight density),

which re ects the effectiveness of structural design and the compactness

of the engine.

∑ Engine speci c weight, which is the ratio of the weight density to the

power density, i.e., the reciprocal of the power-to-weight ratio.

∑ Engine volume per displacement volume, which re ects the compactness

of engine packaging design. (i.e., volume density).

∑ Engine speci c volume, which is the ratio of the volume density to

power density.

∑ A characteristic ratio of engine power or torque to an engine application

parameter, which is a fundamental matching parameter between the

engine as a power or torque source and its application. For example, it

can be the ratio of engine rated power or peak torque to vehicle weight

for on-road trucks.

A brief discussion is provided below to reveal the relationships among

some of the above basic engine system design parameters. According to the

de nitions of BMEP and mean piston speed,

BMEPBM



1.2

= 2S

1.3

engine brake power can be derived as follows, proportional to BMEP, square

of bore diameter and mean piston speed (note that n

= 2 for four-stroke

engines and n

= 1 for two-stroke engines),

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71The analytical design process and diesel engine system design



BMEPBM

ˆˆˆ

BMEPBM

1.4

Engine maximum BMEP re ects the structural capability to sustain peak

cylinder pressure and thermal load. The maximum allowable BMEP has

been constantly increasing over the past several decades in order to meet

the demand for higher torque output produced by a smaller engine. From

equation 1.4 it is observed that increasing cylinder bore diameter can increase

engine power at a given BMEP. Usually, the aerodynamic resistance of intake

and exhaust processes and the component stress caused by inertia loading

are proportional to

. Piston-assembly friction force and thermal  ux

rate are proportional to v

. The wear rate of piston assembly may increase

proportionally or exponentially with v

. Therefore, an increase in v

may

result in an increase in component stress and thermal loading, a reduction in

BMEP

and a decrease in engine life due to an increase in wear. The mean

piston speed is a critical parameter affecting engine performance, durability

and reliability. It needs to be selected with great care.

Usually the values of all the above basic system design parameters are

available in the literature or engine product catalogs. A competitive design

analysis can be readily conducted with this public information.

1.5.4 Competitive benchmarking analysis of engine

performance

Figure 1.23 illustrates the analysis of the relationships among several basic

system design parameters for a large number of heavy-duty diesel engines

in North America, including both on-road and off-road applications. It is

observed that there is a fairly linear correlation between engine rated power

(or peak torque) and engine displacement over a wide range. The majority

of the engines are rated around 1500–3000 rpm, with a rated mean piston

speed around 8–12 m/s. Most engines with a displacement larger than 7

liters are rated around 1500–2400 rpm. The peak torque speeds are usually

around 1100–1700 rpm. Most of the engines have a stroke-to-bore ratio

around 1.1–1.3. There is a clear trend of decreasing engine speci c power

with increasing engine speci c weight. There is also a trend of increasing

engine power per piston area with increasing cylinder bore diameter. Most

of the engines have a coef cient of torque backup around 1–1.45, and a

coef cient of speed reserve around 1.3–1.8. There is a clear correlation

between engine dry weight and engine displacement. There is a large

variation in speci c weight from 2 to 8 kg/kW, mainly caused by small

engines. Most engines with a displacement larger than 7 liters appear to

have a speci c weight around 2.8–3.6 kg/kW.

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I3 I4

I5 I6

V6 V8

V12 V16

I3 I4

I5 I6

V6 V8

V12 V16

I3 I4

I5 I6

V6 V8

V12 V16

I3 I4

I5 I6

V6 V8

V12 V16

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70

Engine displacement (liter)

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70

Engine displacement (liter)

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70

Engine displacement (liter)

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70

Engine displacement (liter)

Engine rated power (kW)

Engine peak torque (N.m)

Engine rated speed (rpm)

Engine peak torque speed (rpm)

2000

1500

1000

500

10000

9000

8000

7000

6000

5000

4000

3000

2000

1000

3500

3000

2500

2000

1500

1000

3500

3000

2500

2000

1500

1000

1.23 Competitive benchmarking performance analysis of 2008 North America HD diesel engines.

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I3 I4

I5 I6

V6 V8

V12 V16

I3 I4

I5 I6

V6 V8

V12 V16

I3 I4

I5 I6

V6 V8

V12 V16

I3 I4

I5 I6

V6 V8

V12 V16

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70

Engine displacement (liter)

Engine stroke (mm)

Engine weight per displacement

volume (kg/liter)

200

190

180

170

160

150

140

130

120

110

100

160

150

140

130

120

110

100

70 80 90 100 110 120 130 140 150 160 170 180 190 200

Engine cylinder bore diameter (mm)

Engine stroke-to-bore ratio

Engine speciﬁc power (kW/liter)

1.4

1.3

1.2

1.1

1.0

0.9

0.8

Good

design

direction

0 10 20 30 40 50 60

Engine speciﬁc power (kW/liter)

0 1 2 3 4 5 6 7 8 9

Engine speciﬁc weight (kg/kW)

1.23 Continued

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1.23 Continued

I3 I4

I5 I6

V6 V8

V12 V16

I3 I4

I5 I6

V6 V8

V12 V16

I3 I4

I5 I6

V6 V8

V12 V16

I3 I4

I5 I6

V6 V8

V12 V16

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70

Engine displacement (liter)

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70

Engine displacement (liter)

70 80 90 100 110 120 130 140 150 160 170 180 190 200

Engine cylinder bore diameter (mm)

Engine speciﬁc power (kW/liter)

Engine power per piston area (kW/cm

)

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

Engine power per piston area (kW/cm

)

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

6 7 8 9 10 11 12 13 14

Rated mean piston speed (m/sec)

Engine speciﬁc power (kW/liter)

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1.23 Continued

I3 I4

I5 I6

V6 V8

V12 V16

I3 I4

I5 I6

V6 V8

V12 V16

I3 I4

I5 I6

V6 V8

V12 V16

I3 I4

I5 I6

V6 V8

V12 V16

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70

Engine displacement (liter)

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70

Engine displacement (liter)

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70

Engine displacement (liter)

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70

Engine displacement (liter)

Coefﬁcient of rated intensity,

BMEP*Vmp (kW/m

)

Coefﬁcient of speed reserve

Coefﬁcient of torque backup

0.35

0.3

0.25

0.2

0.15

0.1

0.05

2.1

1.9

1.8

1.7

1.6

1.5

1.4

1.3

1.2

1.1

0.9

1.7

1.6

1.5

1.4

1.3

1.2

1.1

0.9

0.8

0.7

0.6

Rated mean piston speed (m/sec)

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