5-i

CHAPTER 5. ENGINEERING ANALYSIS

TABLE OF CONTENTS

5.1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-1

5.2 EQUIPMENT CLASSES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-2

5.3 IDENTIFICATION OF BASELINE UNITS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-3

5.3.1 Efficiency Levels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-3

5.3.2 Capacities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-5

5.4 METHODOLOGY OVERVIEW . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-5

5.5 TEARDOWN ANALYSIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-6

5.5.1 Selection of Units . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-6

5.5.2 Generation of Bills of Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-8

5.6 COST MODEL AND DEFINITIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-8

5.6.1 Cost Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-9

5.6.2 Cost Model Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-10

5.6.3 Cost Model Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-11

5.6.4 Outsourcing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-12

5.6.5 Factory Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-13

5.7 INDUSTRY COST-EFFICIENCY CURVES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-14

5.7.1 Plotting Absolute Cost Versus Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-15

5.7.2 Translating Absolute Cost to Incremental Cost . . . . . . . . . . . . . . . . . . . . . . . . 5-15

5.7.3 Fitting the Cost-Efficiency Curve and Confidence Interval . . . . . . . . . . . . . . 5-16

5.8 DESIGN OPTION ANALYSIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-19

5.8.1 Accuracy of Industry Cost-Efficiency Curves above 11.5 EER . . . . . . . . . . . 5-20

5.9 ALTERNATIVE REFRIGERANT ANALYSIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-22

5.9.1 Alternative Refrigerant Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-22

5.9.2 Alternative Refrigerant Product Availability . . . . . . . . . . . . . . . . . . . . . . . . . . 5-22

5.9.3 Differences Between R-22 and R-410a . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-23

5.9.4 Cost-Efficiency Curve for R-410a Equipment . . . . . . . . . . . . . . . . . . . . . . . . 5-23

LIST OF TABLES

Table 5.2.1 Census Data for Equipment Sub-Categories . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-2

Table 5.5.1 Numbers of Products Considered and Selected from the 7.5-ton Equipment 

Class . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-7

Table 5.5.2 Numbers of Products Considered and Selected from the 15-ton Equipment 

Class . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-7

Table 5.6.1 Cost Model Outsourcing Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-12

Table 5.6.2 Purchased Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-13

Table 5.7.1 The 7.5-ton Equipment Class Cost-Efficiency Relationship and Confidence 

Interval . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-17
5-ii

Table 5.7.2 The 15-ton Equipment Class Cost-Efficiency Relationship and Confidence 

Interval . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-18

Table 5.8.1 Comparison Table for the Model Calibration Versus Test Data . . . . . . . . . . . 5-20

LIST OF FIGURES

Figure 5.3.1 Range of Efficiency Levels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-4

Figure 5.4.1 Illustration of the Engineering Analysis Methodology . . . . . . . . . . . . . . . . . . . 5-6

Figure 5.5.1 Efficiency Levels for the 30 Products Considered During the Teardown 

Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-7

Figure 5.7.1 Illustration of the Cost Translation Process . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-16

Figure 5.7.2 The 7.5-ton Equipment Class Cost-Efficiency Curve and Confidence 

Interval . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-17

Figure 5.7.3 The 15-ton Equipment Class Cost-Efficiency Curve and Confidence 

Interval . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-18

Figure 5.8.1 7.5-ton Cost-Efficiency Curve with Simulated Design Option Points . . . . . . 5-21

Figure 5.8.2 15-ton Cost-Efficiency Curve with Simulated Design Option Points . . . . . . . 5-21

Figure 5.9.1 7.5-ton R-22 Cost-Efficiency Curve with R-410a Design Option Points 

Overlaid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-24

Figure 5.9.2 15-ton R-22 Cost-Efficiency Curve with R-410a Design Option Points 

Overlaid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-24
5-1

CHAPTER 5. ENGINEERING ANALYSIS

5.1 INTRODUCTION

The engineering analysis establishes the relationship between the cost and efficiency of

commercial unitary air conditioners and heat pumps. This relationship serves as the basis for

cost-benefit calculations in terms of individual consumers, manufacturers, and the nation.

In this chapter, the Department discusses the identification of baseline products, the

methodology used to generate bills of materials (BOMs) and costs, the process for constructing

industry cost-efficiency curves, and the impact of using an alternative refrigerant on the costefficiency relationship of certain commercial unitary air conditioners and heat pumps.

To establish the industry cost-efficiency curves, the Department used: (1) reverse

engineering methodologies, (2) product information from manufacturer catalogs, and (3)

computer simulations and other analytical methods to investigate the efficiency improvements

resulting from one or more design options. The Department developed BOMs, which are

detailed descriptions of each unit that the Department considered. After that, the Department

developed a cost model that converted the BOMs into factory costs. By applying manufacturer

markups to the computed factory costs, the Department constructed industry cost-efficiency

curves, with statistical confidence intervals, from the factory costs. Finally, the Department used

computer simulations of existing equipment with various design options to verify the predicted

cost-efficiency curves.

In a subsequent life-cycle cost analysis, described in the following chapter, the

Department used the industry cost-efficiency curves to determine consumer prices for

commercial unitary air-conditioning equipment, by applying distribution markups and sales tax

or builder markups.

In conducting the engineering analysis, the Department only considered equipment that

include technologies and techniques that improve the energy-efficiency ratio (EER) of

commercial unitary air-conditioning equipment. As mentioned in the screening analysis, the

Department understands that there are potential energy savings associated with technologies and

techniques that can improve the net annual energy performance of a system, but which generally

reduce or have no effect on EER. (More information on these technologies is available in

Appendix A.) However, EPCA requires the Department to consider only those which improve

EER. The EPCA establishes energy-efficiency standards for commercial unitary airconditioning equipment under 42 U.S.C. 6313(a)(1)(C) and (2)(A), and which are measured and

expressed in terms of EER under 42 U.S.C. 6314(a)(4)(A). Therefore, the Department is not

considering technologies that reduce or have no effect on EER at this time.
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5.2 EQUIPMENT CLASSES

As discussed in the market assessment, the Department defined four equipment subcategories for its analysis:

C single-package and split-system unitary air conditioners from $65,000 to <135,000

Btu/hr in capacity;

C single-package and split-system heat pumps from $65,000 to <135,000 Btu/hr in

capacity;

C single-package and split-system unitary air conditioners from $135,000 to <240,000

Btu/hr in capacity; and 

C single-package and split-system heat pumps from $135,000 to <240,000 Btu/hr in

capacity.

The engineering analysis considered only single-package equipment in the estimate of

the cost-efficiency relationship for the equipment sub-categories listed above. The Department

focused on the single-package equipment because this represents the highest sales volume within

the commercial unitary market segment, as shown in Table 5.2.1.

Table 5.2.1 Census Data for Equipment Sub-Categories

Equipment Class $65,000 to

<135,000

Btu/hr

$135,000 to

<240,000

Btu/hr*

Total Unit

Sales

% of Total

Sales

Single-Package Unitary AC 135,563 60,544 197,107 68

Split-System Unitary AC 41,950 14,038 55,988 19

Single-Package and 

Split-System Heat Pumps

21,620 21,620 13

Total 288,705 100

Source: 2001 Census Data for Refrigeration, Air Conditioning, and Warm Air Heating Equipment *

 Census data include units with capacities up to 249,999 Btu/hr.

Although DOE did not explicitly analyze split systems in the engineering analysis, the

Department estimates that the results of the single-package analysis apply to the split systems

and that the systems have equivalent cost-efficiency relationships. While the size constraints

(i.e., cabinet requirements) may be different for the two types of systems, the technologies and

design choices required to increase the efficiency are similar. Both systems will realize

essentially equivalent benefits from such improvements as higher-efficiency compressors, larger

coil surface area, and other applied technologies.

The Department does not consider the single-package and split heat pump systems to be

equivalent to the single-package air-conditioning equipment analyzed in the engineering
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analysis. However, the Department intends to adjust the minimum efficiency of the heat pump

equipment in a manner consistent with the American Society of Heating, Refrigerating and AirConditioning Engineers, Inc. (ASHRAE) methodology used to set the ASHRAE 90.1-1999

levels for unitary systems with heat pump heating.

Niche equipment includes vertical package units and specialized equipment dedicated to

controlling temperatures and humidity levels not associated with human comfort, i.e., in

laboratories, sensitive storage areas, and computer rooms. The Department did not consider

these niche units in the establishment of the cost-efficiency relationship. At this point, the

Department has not decided how to establish efficiency levels for these units.

5.3 IDENTIFICATION OF BASELINE UNITS

The identification of the baseline unit requires establishing both the baseline efficiency

level (minimum EER rating) and the baseline capacity used to represent the different capacities

of the equipment classes ($65,000 to <135,000 Btu/hr and $135,000 to <240,000 Btu/hr).

5.3.1 Efficiency Levels

The Department is required to increase the efficiency standards for the four equipment

classes to at least meet the minimum efficiency level specified in the latest edition of the

ASHRAE 90.1 standard. The most recent version of the standard, ASHRAE 90.1-1999, became

effective as of October 29, 2001. The Department must either accept these minimum levels or

demonstrate that higher levels are technologically feasible and economically justified, and would

save a significant amount of energy. Because the Department is not able to consider levels lower

than that of ASHRAE 90.1-1999, it set the baseline efficiency levels at the minimum levels

specified in ASHRAE 90.1-1999.

The Department understands that there are certain manufacturing costs associated with

any increase in the efficiency of air-conditioning equipment from current EPCA levels to the

ASHRAE 90.1-1999 levels. For this reason, DOE included in the engineering analysis

equipment with efficiency levels greater than or equal to the EPCA efficiency levels but lower

than the baseline ASHRAE 90.1 levels, along with equipment with efficiency levels greater than

or equal to the baseline ASHRAE 90.1 levels. The Department determined the manufactured

costs of the lower-efficiency equipment using the same methodology as it did for the higherefficiency equipment, and considered these costs when constructing the industry cost-efficiency

curves. Since it set the baseline at the ASHRAE 90.1 levels, however, the Department used

“incremental cost” (the cost of raising equipment efficiency from the ASHRAE level to some

incrementally-higher efficiency level) to describe the industry cost-efficiency curves (see Figure

5.3.1). As such, the portion of the industry cost-efficiency curve below the ASHRAE Standard

90.1 efficiency level is only relevant for establishing the trend of the curve near the baseline

efficiency level. Any decrease in efficiency below the baseline level is illustrated by a negative

incremental cost.
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ASHRAE

(Baseline)

Decreasing Cost Increasing Cost

EPCA

Efficiency Level

Incremental Cost $0

Figure 5.3.1 Range of Efficiency Levels

At the time the engineering analysis was conducted, the highest efficiency level for

commercial unitary air conditioners in the $65,000 Btu/h to <240,000 Btu/h range available on

the market was 11.5 EER. The engineering analysis used reverse engineering on this existing

equipment to develop a cost-efficiency curve up to 11.5 EER. Extending the curve beyond 11.5

EER required extrapolation and then verification using design-option analysis modeling. The

Department’s modeling indicated that, with some additional conventional-type design

modifications, such as increases to the size of heat exchangers and modification of the airflow

paths (both of which may need new and larger cabinets), the highest practical efficiency level

was about 12.0 EER. To limit uncertainty associated with the extrapolated curve beyond 11.5

EER, the maximum efficiency level that DOE evaluated was 12.0 EER. The Department

verified the extrapolated cost-efficiency curve using design-option modeling between 11.5 and

12.0 EER. Beyond the 12.0 EER level, the Department will need to consider technologies that

are not currently available or non-conventional technologies that are not typically in use by the

industry.

Since the time the engineering analysis was conducted, several new commercial unitary

air conditioners, with rated efficiency levels up to 12.2 EER, have become available on the

market. In addition, the Department recently became aware of one manufacturer that claims an

EER level of 13.5 for its commercial unitary air-conditioning equipment. The Department is

unaware of any other equipment with a similar EER rating.
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5.3.2 Capacities

The four equipment classes that the Department defined cover two capacity ranges: from

$65,000 Btu/hr to <135,000 Btu/hr and from $135,000 Btu/hr to <240,000 Btu/hr. In terms of

nominal tons, the capacity ranges are 5.5 to 11 tons and 11.5 to 20 tons, respectively. After

reviewing available products in each equipment class and interviewing several of the

manufacturers, the Department set the representative capacity (i.e., the equipment capacity to be

analyzed in detail for this segment) for the $65,000 to <135,000 Btu/hr equipment at 7.5 tons

and the baseline capacity of the $135,000 to <240,000 Btu/hr equipment at 15 tons. For some

manufacturers, these sizes represent their “sweet spots,” i.e., where they have maximized the

ratio of cooling capacity to manufacturing cost. Increasing the efficiency of these models would

generally be very difficult and expensive because manufacturers have packed as much

equipment as they are able into the smallest possible cabinet size. On the other hand, for some

manufacturers, the baseline capacities represent the least cost-optimized product. Increasing the

efficiency of these products would be less expensive because there is room in the cabinet to

increase coil size and add other types of energy-saving devices without moving to a larger

cabinet. A majority of the manufacturers that commented about this issue to the Department

agree that the 7.5-ton and 15-ton capacities adequately represent the equipment classes and the

wide array of design constraints. A few manufacturers, however, suggested that 10-ton and 20-

ton units would provide a better representation of the baseline.

5.4 METHODOLOGY OVERVIEW

The methodology for the engineering analysis is a logical, concise, and reproducible

process, as illustrated in Figure 5.5.1. At the start of the process, the Department created BOMs

for a sample of existing equipment that use R-22 refrigerant by reverse engineering, through

either physical teardowns or catalog teardowns (see section 5.5). The Department then estimated

the costs of each unit by feeding the BOMs into the cost model (see section 5.6). The next step

was to fit curves to the combined cost-efficiency points to represent the cost-efficiency behavior

of the industry, and derive confidence intervals that describe the accuracy of the curve (see

section 5.7). Using a design-option analysis, DOE then validated the accuracy of the curve

between 11.5 EER and 12.0 EER, where there were no existing equipment data points, by using

the cost model and performance models to simulate units at higher efficiency levels (see section

5.8). In the last step of the process—the alternative refrigerant analysis—the Department

compared the cost-efficiency behavior of R-410a equipment to the R-22 cost-efficiency curve by

using the cost model and performance models to simulate R-410a equipment (see section 5.9).
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Create bill

of materials

(BOM)

[section 5.5]

Estimate

factory costs 

[section 5.6]

Create R-22

cost-efficiency

curves that

represent

the industry

[section 5.7]

Verify the

curve’s 

behavior at

higher EER

levels

[section 5.8]

Compare the

behavior of

R-410a

equipment

to the R-22

curves

[section 5.9]

Physical

teardowns

Catalog

teardowns

Complete

BOMs

Cost model

CostEfficiency

Points

Performance model

Preliminary

Cost-Efficiency

Curve

Final

Cost-Efficiency

Curve

Figure 5.4.1 Illustration of the Engineering Analysis Methodology

5.5 TEARDOWN ANALYSIS 

Other than obtaining detailed manufacturing costs directly from a manufacturer, the most

accurate method for determining the production cost of a piece of equipment is to disassemble

the equipment piece-by-piece and estimate the material and labor cost of each piece, commonly

called a physical teardown. A supplementary method, called a catalog teardown, uses published

manufacturer catalogs and supplementary component data to estimate the major physical

differences between a piece of equipment that has been physically disassembled and another

piece of similar equipment. The teardown analysis performed for this engineering analysis

includes four physical teardowns and 14 catalog teardowns, for a total of 18 teardowns.

5.5.1 Selection of Units

The Department based its selection of 18 products for teardown, from a pool of 30

products considered in the analysis (see Figure 5.5.1), on clear and consistent guidelines to

closely represent the market. The selected equipment exhibit four common characteristics that

are key to an accurate and consistent teardown analysis:

1. The selected products, taken together, evenly cover the full range of efficiency levels

considered in the analysis (see Tables 5.5.1 and 5.5.2).

2. From any given manufacturer, the Department selected at least one lower-efficiency

product and one higher-efficiency product, preferably sharing similar characteristics

(e.g., both would be from the same product line).
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8 9 10 11 12 13

8 9 10 11 12 13

ASHRAE

90.1-1999 Level

EPCA 1992

Level

7.5-ton Products

15-ton Products

EER

EER

Figure 5.5.1 Efficiency Levels for the 30 Products Considered During the

Teardown Analysis

3. The selected products tend to be from manufacturers that have relatively large market

shares in the commercial unitary air-conditioning market, and thus are representative of

typical design approaches.

4. The selected products are base products with few, if any, product features or options that

add cost without affecting equipment efficiency.

Table 5.5.1 Numbers of Products Considered and Selected from the 7.5-ton Equipment Class

EER range 8.6–9.0 9.1–9.5 9.6–10.0 10.1–10.5 10.6–11.0 11.1–11.5

Products considered 312513

Products selected for physical

teardown 000110

Products selected for catalog

teardown 200203

Table 5.5.2 Numbers of Products Considered and Selected from the 15-ton Equipment Class

EER range 8.6–9.0 9.1–9.5 9.6–10.0 10.1–10.5 10.6–11.0 11.1–11.5

Products considered 333303

Products selected for physical

teardown 001001

Products selected for catalog

teardown 130102
5-8

The Department does not explicitly identify the efficiency levels of the units it tore down,

because doing so could expose sensitive information about individual manufacturers’ products.

The physical teardowns were meticulous and provided comprehensive knowledge about

the products; the Department characterized each equipment part according to its weight,

dimensions, material, quantity, and the manufacturing processes used to fabricate and assemble

it. The catalog teardowns were less meticulous because they were limited to public information

published by manufacturers, such as coil dimensions, weight, compressor type, and box

dimensions. The Department obtained information that was unavailable from the catalog data,

such as fan details, number of sensors, or assembly details, from the physical teardowns of a

similar product or by estimations based on industry knowledge and discussions with

manufacturers. 

5.5.2 Generation of Bills of Materials

The end result of each teardown was a structured BOM. Structured BOMs describe each

equipment part and its relationship to the other parts, in the estimated order in which

manufacturers assembled them. The BOMs describe each fabrication and assembly operation in

detail, including the type of equipment needed (e.g., presses, drills) and the process cycle times. 

The result is a thorough and explicit model of the production process.

The BOMs incorporate all materials, components, and fasteners classified as either raw

materials or purchased parts and assemblies. The classification into raw materials or purchased

parts is based on the Department’s previous industry experience, recent information in trade

publications, and discussions with high- and low-volume original equipment manufacturers

(OEMs). The Department also visited several manufacturing plants to reinforce its

understanding of the industry’s current manufacturing practices.

For purchased parts, the purchase price is an estimate based on volume-variable price

quotations and detailed discussions with suppliers. For fabricated parts, the price of intermediate

materials (e.g., tube, sheet metal) and the cost of transforming them into finished parts is an

estimate based on current industry pricing. For a continued discussion of the cost details and

assumptions, refer to section 5.6.

5.6 COST MODEL AND DEFINITIONS

Once the Department disassembled selected units and gathered information from

manufacturer catalogs on additional products, the next step was to implement an adequate cost

model that could translate physical information into costs.

The cost model is based on production activities and divides factory costs into the

following categories:

• Material: direct and indirect materials;
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• Labor: fabrication, assembly, and indirect and overhead (burdened) labor; and 

• Overhead: equipment depreciation, tooling depreciation, building depreciation, utilities,

equipment maintenance, and rework.

5.6.1 Cost Definitions

Because there are many different accounting systems and methods in use to monitor

costs, and different definitions might generate confusion, the Department defines the above

terms as follows:

• Direct material: Purchased parts (out-sourced) plus manufactured parts (made inhouse).

• Indirect material: Material used during manufacturing (e.g., welding rods, adhesive).

• Fabrication labor: Labor associated with in-house piece manufacturing.

• Assembly labor: Labor associated with final assembly and sub-assemblies.

• Equipment and plant depreciation: Money allocated to pay for initial equipment

installation and replacement as the production equipment wears out.

• Tooling depreciation: Cost for initial tooling (including non-recurring engineering and

debugging of the tools) and tooling replacement as it wears out.

• Building depreciation: Money allocated to pay for the building space.

• Utilities: Electricity, gas, telephones, etc.

• Equipment maintenance: Money spent on yearly maintenance, both materials and

labor.

• Indirect labor: Plant labor that scales directly, based on the number of direct workers

(assembly + fabrication). This includes supervisors, technicians, and manufacturing

engineering support.

• Overhead Labor: Fixed plant labor that is spread over a number of product lines. This

includes accounting, quality control, shipping, receiving, floor supervisors, plant

managers, office administration, and environmental health and safety. Not included are

research and development, corporate management, general administration, and

maintenance labor.
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• Rework: Labor and materials associated with correction of in-plant manufacturing

defects.

The Department fed the cost data in all the BOMs—whether they were obtained through

physical teardowns, catalog teardowns, or, as discussed in other sections, through numerical

simulations—into the cost model. The cost model makes use of specific assumptions to provide

cost estimates. The following sections describe these assumptions.

5.6.2 Cost Model Overview

This section provides a general overview of the process the Department used to convert

physical information about commercial unitary air conditioners into cost information. The

explanation provided here is a simplification, because an exhaustive explanation of the cost

modeling techniques is beyond the scope of this document. More information is available in

Appendix B.

The first step of the process was to collect physical data on the dimensions, weight, and

other information that plays a role in determining the cost of a part. After gathering this

information through physical and catalog teardowns, the Department stored the raw information

in a spreadsheet organized by major equipment subassemblies. The comprehensive list of all

subassemblies and their physical information constitutes the BOM. 

To determine the costs, the Department could follow two different paths, depending on

whether a subassembly was purchased (out-sourced) or produced in-house. Section 5.6.4, where

the major assumptions are described, provides a list of all the purchased subassemblies.

For purchased parts, DOE gathered price quotations from major suppliers at different

production volumes. Using this information, the Department was able to build cost-versus-size

correlations, such as cost-versus-motor horsepower, cost-versus-condenser fan diameter, and

cost-versus-circulating blower wheel diameter. These correlations were very useful during the

design option analysis (see section 5.8), when DOE scaled up specific parts and estimated the

performance of such “hypothetical” units.

For parts produced in-house, DOE reconstructed manufacturing processes for each part

using internal expertise and additional modeling software. For example, for an access panel, the

Department estimated the time required for setup, handling, changeover, and punching holes, as

well as the number of holes and hits. By repeating this process over and over, the Department

was able to assign labor time, equipment utilization, and other important factors to each

subassembly in each of the units considered for this analysis. The last step was the conversion of

all this information into dollar values. To perform this task, it was necessary to collect

information on such factors as labor rates, tooling depreciation, and costs of purchased raw

materials. The Department assumed values for these parameters using internal expertise and

confidential information available to its contractors. Although most of the assumptions are
5-11

manufacturer-specific and cannot be revealed, section 5.6.5 provides a discussion of the ranges

used for each specific assumption.

The Department used a slightly different approach to estimate the cost of the condenser

and evaporator coils. In this case, the Department used a separate coil model. The coil model

converts each coil’s physical descriptors into coil costs by calculating the number of fins, hairpin

bends, U-bends, take-offs, and coil ends. The model accounts for physical characteristics that

affect coil cost. It relies on a process-based cost model that accounts for every fabrication and

assembly step. The Department obtained fabrication equipment costs and processing times from

equipment vendors, and obtained raw material prices from vendors based on their pricing at the

time. More information is available in Appendix B.

In sum, DOE assigned costs of labor, materials, and overhead to each part, including

coils, whether purchased or produced in-house. The Department then aggregated single-part

costs into major assemblies (e.g., cabinet assembly, condensing unit, evaporator unit, controls,

packaging, condenser coil assembly, evaporator coil assembly, furnace, compressors, and

shipping) and summarized these costs in a worksheet.

The Department repeated this same process for each unit, representing a specific

efficiency level at a given capacity, and mapped the resulting cost-efficiency points to use as

building blocks of the cost-efficiency curves.

5.6.3 Cost Model Assumptions

As discussed in the previous section, assumptions about manufacturer practices and cost

structure play an important role in estimating the final cost of equipment. During this analysis,

some assumptions were different for each specific manufacturer, depending on their strategic

position, their manufacturing practices, and their size. The Department aggregated the final cost

values to prevent disclosure of confidential information.

In previous rulemakings, the Department used average numbers for all the units

considered in order to decrease uncertainty in the first step of the analysis; it later added

uncertainty to the average specifications during a separate uncertainty analysis. The Department

considers that both the previously-used approach and the current approach are valid to estimate

the manufacturing costs. Furthermore, in the current rulemaking, the Department went through

the exercise of changing the assumptions to market share-weighted industry averages and

compared the results obtained with the two different methods. The Department found no

substantial differences, except that the latter approach inherently gives less weight to high-cost

producers (which typically have lower market shares), and therefore results in slightly lower

costs. 

The next sections provide discussions of specific assumptions relating to outsourcing

decisions, factory parameters, and production volumes. When the assumptions are

manufacturer-specific, they are presented as ranges to prevent disclosure of confidential
5-12

information.

5.6.4 Outsourcing

The Department characterized parts based on whether manufacturers purchase them from

outside suppliers or fabricate them in-house. For purchased parts, DOE estimated the purchase

price. For fabricated parts, DOE estimated the price of intermediate materials (e.g., tube, sheet

metal) and the cost of transforming them into finished parts. Whenever possible, the Department

obtained price quotes directly from suppliers of the manufacturers of the units being analyzed. 

For higher-efficiency equipment, DOE assumed the component purchase volume as the baseline;

this assumption may have resulted in lower component prices than manufacturers currently pay. 

Most of the manufacturing operations are carried out in-house, as summarized in Table 5.6.1.

Table 5.6.1 Cost Model Outsourcing Assumptions

Process Sub–Process In–House Outsourced

Tube Forming Tube Cut U

Tube Bend U

Collar U

Tube Coil U

Sheet Metal Stamping U

Press Brake U

Blanking U

Turret Punch U

Plasma Cut U

Welding Seam Welding U

Spot Welding U

Machining Machining Center U

Cutting Insulation Cut U

Finishing Paint U

Assembly Adhesive Bonding U

Brazing U

Press Fit U

Fixture U

Miscellaneous Assembly Operation U

Final Assembly Packaging U

Quality Assurance (Leak Check) U

Charging Refrigerant Charging U

Molding Injection Mold U

Casting Sand Cast U
5-13

Condensing Unit

Assembly

Compressor

Purchased Sub-Assemblies

Condenser Fan Blade

Condenser Fan Motor

Evaporating Unit Evaporator Fan Motor

Evaporator Blower

Controls Control Boards

Capacitors, transformers, contactors, etc.

Line pressure sensors

Heating Section Gas valve

Blower motor

TXV/Orifice

Filter/Dryer

Table 5.6.2 Purchased Components

Similarly, the Department assumed that the components shown in Table 5.6.2 (on the

following page) are purchased from external suppliers.

5.6.5 Factory Parameters

Factory parameters are manufacturer-specific. For example, low-cost manufacturers are

likely to be at the lower end of the ranges presented in the following tables. In the Notice of

Proposed Rulemaking (NOPR), a manufacturer impact analysis will examine variability of costs

among manufacturers.

The Department based its assumptions for the factory parameters on manufacturer

interviews and analysis of common industry practices. Table 5.6.3 lists these assumptions. 
5-14

Table 5.6.3 Factory Parameter Assumptions

Total Manufacturer Compressor Purchases 400,000–500,000

Annual Production Volume (units/year) 12,000–73,000

Press Lot Size (in days) 0.25–1

Ratio of Designed vs. Actual Production Capacity 1.15–1.3

Direct labor Wages ($/hr) $15.2–18.3

Equipment Uptime 85–95%

Assembly Factor (ratio of actual to ideal) 1.25–2

Tooling Depreciation (in years) 4–5

Fringe Benefit Ratio 35–65%

Pre-painted Steel Cost ($/lb) $0.30–0.41

Building Cost ($/sq.ft.) 80–120

Refrigerant 22 Cost ($/lb) 0.85–1.2

Worker Downtime 10–20%

Building Life (in years) 25–40

Property Taxes (as % of building cost) 0.6–2.1%

Rework Rate 0–8%

5.7 INDUSTRY COST-EFFICIENCY CURVES

Creating the industry cost-efficiency curves was a three-step process that consisted of

plotting the raw data points as cost versus efficiency, translating the cost data from absolute costs

to incremental costs, and fitting a least-squares curve and 95 percent confidence interval to the

incremental cost-versus-efficiency data.

According to discussions with manufacturers and observations of the cost-efficiency

data, DOE learned that cost behaves exponentially as EER increases. In other words, as air

conditioners become more efficient, it becomes increasingly difficult and costly to increase

efficiency to the next higher level. This is partly because traditional lower-cost design changes,

such as increasing coil area or upgrading compressor efficiency, may not suffice. For example,

the design may already use the highest-efficiency compressor, and increasing the coil area any

more may degrade its performance by changing its refrigerant temperatures to be above or below

acceptable limits. Therefore, DOE derived the cost-efficiency curves using an exponential

curve-fit.
5-15

5.7.1 Plotting Absolute Cost Versus Efficiency

The cost model analysis created cost estimates for each of the 18 teardown products, as

detailed in section 5.6. The cost output from the model includes all manufacturing costs and a

manufacturer’s markup, which covers corporate overhead expenses. This combined cost, called

“absolute cost” for purposes of discussion, is the price at which the manufacturer sells the

product to distributors, resellers, and similar parties—it is not the final cost to the end-user,

because it does not include the distribution markups.

The absolute cost from the model is plotted as a function of each product’s efficiency in

terms of its EER. Manufacturers publish EER values for each of their products, according to

ARI specifications. Each of the resulting two plots of absolute cost versus efficiency—one for

the 7.5-ton equipment class and one for the 15-ton equipment class—has nine data points.

The Department does not present any absolute costs in this document, because doing so

could expose sensitive information about individual manufacturers’ products.

5.7.2 Translating Absolute Cost to Incremental Cost

For the next step in the process of creating the industry cost-efficiency curves, the

Department translated the absolute costs into incremental costs. Incremental cost, as discussed

in Section 5.3, is the cost of raising equipment efficiency from the baseline efficiency level

(ASHRAE 90.1 efficiency level) to some incrementally higher efficiency level.

As illustrated in Figure 5.7.1, the cost translation process shifts the absolute costs of each

manufacturer’s products so that the incremental cost of their products equals zero at the baseline

ASHRAE 90.1 efficiency level described in section 5.3.1. The Department shifts costs for

products made by the same manufacturer equally, but shifts costs for products made by different

manufacturers independently. To do this, DOE first fits an exponential curve to each

manufacturer’s product data points separately. Then, DOE shifts each curve down until it

intersects the y axis (incremental cost equal to zero) at the baseline efficiency. The Department

shifts all data points for a given manufacturer down by the same amount as the curve, so that the

resulting data points represent incremental cost versus EER. The Department then discards the 

individual manufacturer curve-fits, and the analysis continues with the translated cost data

points.
a

 Mendenhall and Sincich, Statistics for Engineering and the Sciences, 4th Edition, 1995.

5-16

EER

Absolute Cost

EER

Incremental Cost

Figure 5.7.1 Illustration of the Cost Translation Process

5.7.3 Fitting the Cost-Efficiency Curve and Confidence Interval

For the final step in the process of creating the industry cost-efficiency curves, DOE fit

an exponential curve to the translated cost-EER data points, using a least-squares regression

analysis. The result is an industry cost-efficiency curve for each of the two equipment classes

(7.5-ton and 15-ton), which represents the costs for the industry to incrementally increase

equipment efficiency above the ASHRAE 90.1 baseline levels. The curves do not represent any

single manufacturer, nor do they describe any variance between manufacturers; they represent

the industry as a whole. The regression analysis also produced confidence intervals for the costefficiency curves.

The Department used the regression analysis tool included in the Microsoft Excel 97

software program to perform the least-squares regression analysis for creating the exponential

curve-fits and confidence intervals. A least-squares regression analysis establishes a curve of a

given type (exponential in this case) that “best fits” the data. A confidence interval describes the

accuracy of the curve, based on the scatter of the data. In this case, DOE used a 95 percent

confidence interval, which means that if the costs of a sample of products are at the same

efficiency level, 95 times out of 100 their “best fit” cost will be within the confidence interval.a

Figures 5.7.2 and 5.7.3 present the industry cost-efficiency curves and confidence

intervals, while Tables 5.7.1 and 5.7.2 show the results in tabular form. Because DOE did not

consider data points with efficiency levels above 11.5 EER, DOE extrapolated the portion of the

curves between 11.5 EER and 12.0 EER. The accuracy of this portion of the curves was

uncertain at this point in the analysis. The design option analysis described in section 5.8 further

discusses the level of accuracy in this portion of the curves. 
5-17

-$250

$0

$250

$500

$750

$1,000

8.5 9.0 9.5 10.0 10.5 11.0 11.5 12.0 12.5

EER

Product Cost Delta ($)

ASHRAE 90.1-1999

Standard

Industry Cost-Efficiency Curve

95% Confidence Interval

Figure 5.7.2 The 7.5-ton Equipment Class Cost-Efficiency Curve and Confidence Interval

Table 5.7.1 The 7.5-ton Equipment Class Cost-Efficiency Relationship and Confidence

Interval

10.1-EER 10.5-EER 11.0-EER 11.5-EER 12.0-EER

Incremental

Cost $0 $47 +/-$14 $139 +/-$41 $292 +/- $85 $543 +/- $159
5-18

-$500

$0

$500

$1,000

$1,500

$2,000

8.5 9.0 9.5 10.0 10.5 11.0 11.5 12.0 12.5

EER

Product Cost Delta ($)

ASHRAE 90.1-1999

Standard

Industry Cost-Efficiency Curve

95% Confidence Interval

Figure 5.7.3 The 15-ton Equipment Class Cost-Efficiency Curve and Confidence Interval

Table 5.7.2 The 15-ton Equipment Class Cost-Efficiency Relationship and Confidence

Interval

9.5-EER 10.0-EER 10.5-EER 11.0-EER 11.5-EER 12.0-EER

Incremental

Cost $0 $62 +/-$35 $165 +/-$94

$334 +/-

$191

$613 +/-

$351

$1072 +/-

$615

The industry cost-efficiency curve for the 15-ton equipment class is steeper than the one

for the 7.5-ton equipment class, in part because the larger equipment is bigger and has more

material. For example, a manufacturer may increase efficiency in both 7.5-ton and 15-ton

equipment by increasing condenser coil area. To get the same EER increase, the condenser area

must be increased more for the 15-ton equipment than for the 7.5-ton equipment. This leads to

higher direct material costs as well as higher labor costs and other indirect costs for the 15-ton

equipment.

The confidence interval is wider for the 15-ton equipment than for the 7.5-ton equipment,

in part because there was more scatter in the incremental cost data among the manufacturers for

the larger-capacity equipment.
5-19

5.8 DESIGN OPTION ANALYSIS

The purpose of the design option analysis is to validate the accuracy of the costefficiency curves at efficiency levels between 11.5 EER and 12.0 EER. As mentioned in section

5.3.1 and illustrated in Figure 5.5.2, there were no products in that efficiency range evaluated

during the teardown analysis, so there were no data points available for the curve-fit. 

Consequently, the accuracy of the curve in this range is not known. However, the design option

analysis simulates equipment with efficiency levels above 11.5 EER and compares its costs with

the costs predicted by extending the existing curve.

The simulated design option data points do not influence the industry cost-efficiency

curves. The Department did not consider these data points in the curve-fitting procedures

discussed in section 5.7.3; they served primarily as a check on the accuracy of the existing

curves between 11.5 EER and 12.0 EER.

To simulate equipment, the Department used a combination of modeling tools and

techniques, as detailed in Appendix C. The Department performed the refrigerant-side heat

transfer and balance calculations using the Oak Ridge National Laboratory’s (ORNL) heat pump

model, using compressor performance data for commercially available compressors. The

Department used a custom heat exchanger software program to perform the air-side heat transfer

and pressure drop calculations. The Department used a combination of manufacturer data, test

data, published fan performance curves, and published motor performance curves to determine

fan power and airflow.

The first step in the analysis simulated the performance of the four existing products that

DOE physically tore down, as described in section 5.5. Additionally, DOE had one of the

products tested (according to Air-Conditioning and Refrigeration Institute (ARI) testing

standards) at a third-party testing laboratory to measure its specific performance parameters,

including refrigerant pressures and temperatures, mass flows, capacity, and EER. The

Department used the test data to construct and calibrate the model (see Table 5.8.1), and then

performed various design option combinations to simulate equipment with increased efficiencies. 

Through discussions with manufacturers and using engineering judgement, the Department

established several design guidelines to limit the design option simulations (see Table C.3.1 in

Appendix C).

The Department estimated the costs of the simulated equipment using the cost model

discussed in section 5.6.
b

 Mendenhall and Sincich, Statistics for Engineering and the Sciences, 4th Edition, 1995.

5-20

Capacity (Btu/hr) 91,037 92,741**

EER 10.334 10.45**

Compressor Power (W) 7,325 7,430 +/- 2.0%

Evaporator Blower Power (W) 910 880 +/- 2.0%

Condenser Fan Power (W) 575 562 +/- 2.0%

Evaporator Pressure (PSIA) 96.8 98.7 +/- 2.0%

48.8 Average: 50** 

(48.7 - 51.2)†

Predicted by

Model

Measured by 

ITS Testing

Evaporator Temperature (oF)

-1.8%

-1.1%

-1.4%

+3.4%

+2.3%

-1.9%

1.2 oF

Difference

Condenser Pressure (PSIA) 279.2 282.2 +/- 2.0%

121.3 Average: 122.1**

(120.6 - 123.7) Condenser Temperature ( † oF)

-1.1%

0.8 oF

* Using ARI Test “A” methods

** Calculated from measured data † Range calculated from pressure error band 

Table 5.8.1 Comparison Table for the Model Calibration Versus Test Data

5.8.1 Accuracy of Industry Cost-Efficiency Curves above 11.5 EER

Based on the design option analysis, the general trend of the curve between 11.5 EER

and 12.0 EER is generally accurate, because none of the design option points lies outside of the

95 percent prediction interval.

Similar to the confidence interval described in section 5.7.3, a prediction interval

describes the accuracy of the curve-fit in predicting the cost of any single unit. In this case, the

Department used a 95 percent prediction interval, which means that, for any single unit at a

certain efficiency level, 95 times out of 100 its cost will be within the prediction interval.b

Figure 5.8.1 shows the simulated design option points and prediction interval for the 7.5-ton

equipment class, and Figure 5.8.2 shows the simulated design option points and prediction

interval for the 15-ton equipment class.
5-21

-$250

$0

$250

$500

$750

$1,000

8.5 9.0 9.5 10.0 10.5 11.0 11.5 12.0 12.5

EER

Product Cost Delta ($)

ASHRAE 90.1-1999

Standard

Manufacturer “A” Design Options

Manufacturer “B” Design Options

Industry Cost-Efficiency Curve

95% Confidence Interval

95% Prediction Interval

Figure 5.8.1 7.5-ton Cost-Efficiency Curve with Simulated Design Option Points

-$500

$0

$500

$1,000

$1,500

$2,000

8.5 9.0 9.5 10.0 10.5 11.0 11.5 12.0 12.5

EER

Product Cost Delta ($)

ASHRAE 90.1-1999

Standard

Manufacturer “A” Design Options

Manufacturer “B” Design Options

Industry Cost-Efficiency Curve

95% Confidence Interval

95% Prediction Interval

Figure 5.8.2 15-ton Cost-Efficiency Curve with Simulated Design Option Points
5-22

5.9 ALTERNATIVE REFRIGERANT ANALYSIS

The purpose of the alternative refrigerant analysis is to identify any substantive

differences between the cost-efficiency behavior of R-410a and R-22 equipment. For this

analysis, the Department simulated R-410a equipment using the same performance models

described in section 5.8, calculated their costs using the same cost model described in section

5.6, and compared those simulated data points to the existing R-22 cost-efficiency curve. The

Department only considered simulations because, at the time the analysis was conducted, there

were no commercially available R-410a products in the 7.5-ton or 15-ton equipment classes.

The Department constructed baseline R-410a equipment models, starting with existing R22 models (see section 5.8), swapping out compressor maps, and using design options to bring

the R-410a equipment to the same efficiency level as the R-22 equipment. The Department then

performed various design option combinations to simulate equipment with increased efficiencies.

5.9.1 Alternative Refrigerant Selection

Two refrigerants, R-410a and R-407c, are currently under consideration as substitutes for

R-22, which will be phased out of new equipment in 2010. While R-407c has similar pressuretemperature characteristics as R-22 and thus is more easily adapted to existing R-22 designs, it is

less efficient. By contrast, R-410a operates at higher pressures than R-22, thus requiring

substantial redesign of R-22 equipment. However, R-410a offers efficiency benefits relative to

R-407c. Consequently, the consensus of manufacturers contacted by the Department during the

rulemaking process was that R-410a is the most likely replacement for R-22 in new commercial

unitary equipment as the phaseout of R-22 approaches.

5.9.2 Alternative Refrigerant Product Availability

Although some unitary air-conditioning products using R-410a are commercially

available, none was available when the engineering analysis was conducted in the capacity range

that the analysis covers. However, since the analysis was conducted, the Department has learned

that there is one R-410a commercial unitary air conditioner now available on the market in the

15-ton representative capacity. The majority of the R-410a products are currently being sold

primarily for residential applications. Consequently, the Department’s analysis compared the

design differences between R-22 and R-410a products in smaller packaged units (i.e., 5-ton

units) to gain general engineering insight.

As components, there are R-410a compressors that are commercially available in sizes

that can be used in commercial unitary air conditioners rated $65,000 through <240,000 Btu/h. 

The Department used performance characteristics from those compressors for input to its

engineering analysis.
5-23

5.9.3 Differences Between R-22 and R-410a 

Because R-410a equipment was not available in the equipment classes considered during

the engineering analysis, the Department made six assumptions about simulated R-410a

equipment. The Department based each assumption on detailed discussions with manufacturers

and engineering calculations.

The Department assumed that:

1. Although the design pressures of R-410a are higher than R-22, the diameter and

thickness of tubing will be the same. This is based on interviews with manufacturers

and comparisons of five-ton R-22 products to five-ton R-410a products.

2. R-410a compressors will cost approximately four percent more in the long term (i.e.,

high production volume) than R-22 compressors with similar capacities, according to

communications with an executive at a leading compressor manufacturer.

3. R-410a scroll compressors are less efficient than comparable R-22 scroll

compressors, but more efficient than low-efficiency R-22 reciprocating compressors,

based on product literature from leading compressor manufacturers.

4. Higher heat transfer coefficients of R-410a allow slightly lower condensing

temperatures than are possible with R-22. The minimum condensing temperature is

reduced by one degree Fahrenheit according to log-mean temperature difference

(LMTD) heat exchanger calculations that use a 15 percent higher heat transfer

coefficient. 

5. Evaporating temperature limits for R-410a systems are the same as for R-22 systems.

6. Long-term cost of R-410a refrigerant in bulk quantities will be approximately $3/lb,

according to personal communications with a leading refrigerant manufacturer.

5.9.4 Cost-Efficiency Curve for R-410a Equipment

In view of the alternative refrigerant analysis, there is no evidence that the general costefficiency behavior of R-410a equipment in the 7.5-ton and 15-ton equipment classes over the

range of efficiencies in this analysis is substantially different from the R-22 cost-efficiency

behavior. Figures 5.9.1 and 5.9.2 show the R-410a design option points overlaid on the R-22

cost-efficiency curves. In general, the cost-efficiency trends of R-22 and R-410a are similar.
5-24

-$250

$0

$250

$500

$750

$1,000

8.5 9.0 9.5 10.0 10.5 11.0 11.5 12.0 12.5

EER

Product Cost Delta ($)

ASHRAE 90.1-1999

Standard

R-410A Design Options

Industry Cost-Efficiency Curve (R-22)

95% Confidence Interval (R-22)

95% Prediction Interval (R-22)

Figure 5.9.1 7.5-ton R-22 Cost-Efficiency Curve with R-410a Design Option Points Overlaid

-$500

$0

$500

$1,000

$1,500

$2,000

8.5 9.0 9.5 10.0 10.5 11.0 11.5 12.0 12.5

EER

Product Cost Delta ($)

ASHRAE 90.1-1999

Standard

Industry Cost-Efficiency Curve (R-22)

95% Confidence Interval (R-22)

95% Prediction Interval (R-22)

R-410A Design Options

Figure 5.9.2 15-ton R-22 Cost-Efficiency Curve with R-410a Design Option Points Overlaid