1. Technical guides for owner/manager of an air conditioning
system: volume 8
How manufacturers could help
the unfortunate energy auditor

2. Team
France (Project coordinator)
Armines - Mines de Paris
Austria
Slovenia
Austrian Energy Agency
University of Ljubljana
Belgium UK
Université de Liège Association of Building
Engineers
Italy BRE
Politecnico di Torino (Building Research
Establishment Ltd)
Portugal
University of Porto Welsh School of
Architecture
Eurovent-Certification
Authors of this volume
Cleide Aparecida Silva (Université de Liège)
Cristian Cuevas (Université de Liège)
Jules Hannay (Université de Liège)
Jean Lebrun (Université de Liège)
Vladut Teodorese (Université de Liège)
The sole responsibility for the content of this publication lies with the authors. It does not
represent the opinion of the European Communities. The European Commission is not
responsible for any use that may be made of the information contained therein.
2

3. Introduction
As already demonstrated in other chapters of the present report, the energy audit of
a whole HVAC system is not a funny game. On site measurements are unavoidable
and cost a lot of time and money. Obviously, in most installations, the highest energy
consumers are the fans. The chillers are then coming in second position.
The nominal performances of these components are usually well identified in
laboratory and in manufacturers catalogues. But their average performances are
more questionable in actual conditions of use.
From other part, providing that these components are correctly identified and
modelled, they may become valuable measuring instruments.
The object of this chapter is to show how the components manufacturers could help
the auditor by allowing him to make a better use of the information they already have.
Using a fan as air flow meter
The principle
Airflow rates measurements are difficult in existing distribution networks: long enough
straight lines are seldom available or accessible and velocity profiles are usually not
uniform enough. A large series of measuring points is required and the final accuracy
is often disappointing. A much better solution consists in using the fan as an air flow
meter.
This can be done in two ways:
1) By taking profit of the well known characteristics of the fan and using easy
measurements, as supply and exhaust static pressures, rotation speed and/or
electrical power;
2) Even better, by measuring just one reference pressure drop at fan supply.
Both procedures are illustrated and validated hereafter.
Fan characteristics identified on the basis of manufacturer data
A fan is currently modelled with the help of similarity variables: flow, pressure and
power factors. These factors can be correlated to each other by polynomial
expressions.
The main output of a fan model can be the airflow rate, expressed in “specific” value
(in kg/s of dry air), as usually in air conditioning. Other outputs can be the different
factors, exhaust air speed, total pressure difference, isentropic power and (isentropic)
temperature increase across the fan (these two last outputs can be used as checking
information).
The fan is supposed to be characterised by the diameter of its impeller (scale
variable), its (fictitious) exhaust area and the coefficients of the polynomial
correlations.
Supply air conditions (temperature, pressure and moisture content), rotation speed
and static pressure difference are taken as input variables.
3

4. This gives the information flow diagram of Figure 1.
Figure 1: Example of fan polynomial model
The first equations of this model are built on the basis of the definitions of two (flow
and pressure) similarity factors:
Two dynamic pressures are considered: one at the exhaust and the other one at the
periphery of the impeller:
4

5. The other non-dimensional variables considered are the isentropic effectiveness and
the power factor:
The three factors are inter-correlated through polynomial laws such as:
This model is from long time well validated and easy to tune…Polynomials are fitted
to manufacturer’s performance data.
Total and static pressures have to be carefully distinguished at fan exhaust:
manufacturers present fan performance in terms of total pressure rise, whereas the
measurements are usually made in terms of static pressures.
Fan characteristics are generally provided by the manufacturers as “data sheets”,
showing the operating curves of the fan (relationships among the different variables
of the system).
A typical example of data sheet is presented in Figure 2.
This information might be better used if the manufacturers were giving:
The experimental points actually available;
The correlation equations actually used to generate the curves.
Still today, the fan simulation model built by the manufacturer is only “offered” to
“important” customers as manufacturers of air handling units. The equations are then
embedded inside black box selection and simulation software.
5

6. Figure 2 Fan characteristics as presented by the manufacturer
Some points can be selected in the diagram of Figure 2, in order to identify the
polynomial laws already presented. An example of selection is made on Figure 3; it
corresponds to three different rotation speeds.
Figure 3 Reference points selected for parameter identification
The phi-psi and lambda-psi regression curves identified on these points are
presented in Figure 4 and Figure 5.
6

7. Figure 4 Identification of the phi-psi characteristic
Figure 5 Identification of the lambda-psi characteristic
A phi – psi characteristic appears to be accurate enough for airflow rate
measurements, when the fan has backward-curved blades (as in the present case).
The airflow rate can be currently determined with an accuracy of about 5 %. In the
case of fans with forward-curved blades, the pressure rise is relatively insensitive to
airflow rate and a more accurate result can be obtained by using the efficiency
characteristic. The electrical consumption is then a better indicator of the flow rate.
However, this second approach requires a correct identification of all electrical losses
(electrical motor and frequency driver, if any).
Experimental validation
The fan
The validation is performed on the fan whose characteristics were already identified.
The fan considered in this study was originally installed in a box, downstream of a
“radiator”(Figure 6).
7

8. Figure 6 the tested fan
Tightness of the fan box
A first experimental arrangement (Figure 7) was made in order to verify the tightness
of the fan box.
The tightness test consisted in injecting air inside the box, thanks to an auxiliary fan,
after having closed both (supply and exhaust) openings.
Injected airflow rate and box-ambient over-pressure were simultaneously measured.
This allows identifying a fictitious leakage area.
An example of measuring result is shown in Figure 8. In the case considered, the
leakage flow rate is estimated to 16.8 g/s, which corresponds to a leakage (fictitious
isentropic nozzle throat) diameter of 27.3 mm.
Fan box
Small fan
Figure 7 Experimental identification of the fan box leakage area
8

9. φ 30/60 mm.
Fan box tamb = 20,5°C
HRamb = 54 %
∆P = 604 Pa Patm = 981 mbar
∆P = 350 Pa
Figure 8 Leakage measurement
Experimental characterization of the fan
The fan system is characterised at different rotation speeds; it’s equipped with a
frequency inverter working between 8.5 and 50.5 Hz.
The experimental arrangement is shown in Figures 9 to 11.
Three tests series have been performed: they correspond to three pressure drop
characteristics of the air circuit:
1) With coil and with a diaphragm used to measure the flow rate (highest
pressure drop)
2) With coil and with a nozzle used to measure the flow rate (medium pressure
drop)
3) Without coil and with a nozzle used to measure the flow rate (lowest pressure
drop).
∆Prad ∆Paf
∆Pop
tamb
HRamb
Patm
&
Win
Ninv
finv
&
Wm
I
Figure 9 Experimental characterization of the fan (principle schema)
9

10. Figure 10 Experimental arrangement (back view)
Figure 11 Experimental arrangement (front view)
The inverter is provided with direct measurements of the frequency and of the
electrical power supplied to the fan motor. The electrical power supplied to the
inverter and the fan rotation speeds are also measured in these tests. This makes
possible to identify the inverter loss and the frequency “sliding” of the electric motor.
The tests results are presented in Figure 12 and Figure 13.
Figure 12 Inverter loss and efficiency
10

11. Figure 13 Motor sliding
As it can be seen here, both the inverter loss and the motor sliding can be identified
through linear correlations.
By combining these measuring results with the characteristics already identified (from
manufacturer data), it’s also possible to identify:
1) The global electromechanical loss and corresponding efficiency of the inverter-
motor subsystem (Figure 14);
2) The same terms for the whole inverter-motor-fan system (Figure 15).
Such characteristics would be easy to combine with on site measurements.
Figure 14 Fan shaft power as function of motor electrical power
11

12. Figure 15 Global loss and global efficiency
The test results were also used to validate the laws identified from manufacturer
data.
An example of such checking is presented in Figure 16: simulated and measured
total pressure differences are compared for same flow rates and rotation speeds. The
agreement is considered as satisfactory (the actual total pressure at fan exhaust is
not directly measured here, but re-calculated by reference to a hypothetical exhaust
area).
Figure 16 Comparison among simulated and measured pressure differences
Validation of a much more expedient method
A much more expedient method is proposed by some manufacturers (as the present
one).
The fan selected for this study was equipped with openings and connecting pipes for
differential pressure measurements as shown in Figure 17 and Figure 18.
12

13. Figure 17 Differential pressure measuring device (principle)
Figure 18 Measuring device (outside the fan)
Figure 19 Measuring device (inside the fan)
The measuring principle is described in the manufacturer catalogue as follows:
13

14. This means that the fan inlet is used as a measuring nozzle. The “K” constant
“contains” the flow contraction effect.
The method can be validated with the test results available. A fictitious nozzle
exhaust diameter is identified at each regime.
Examples of results are presented in Figure 20.
Figure 20 Exhaust diameter of the (fictitious) fan supply nozzle
A (fairly constant) fictitious diameter of 193 mm is here identified. The actual diameter
is 257 mm. This corresponds to a contraction factor of (193/257)2 = 0.564 and is in
good agreement with the “K” value indicated by the manufacturer.
Using refrigeration compressor as enthalpy flow meter
The principle
Determining on site the cooling power actually provided by a chiller is also a delicate
matter. That power should correspond to the enthalpy flow of the secondary fluid
(usually water or brine) supplying the evaporator. But neither the flow rate, nor the
supply-exhaust temperature difference are easy to measure.
The measurements are not easier on refrigerant side.
14

15. An interesting alternative consists in using the chiller compressor as enthalpy flow
meter. But, as seen hereafter, this would require a better dialog with manufacturers…
Data provided by the manufacturers
Analysis
Each manufacturer seems having his own way to present data in his catalogue.
Unfortunately, this “personal” presentation can be a source of confusion.
Data available are nor fully clear, neither complete and the reader is, most of the
time, recommended to“…contact the local manufacturer office…” as solution.
Unfortunately, these offices are not always able to help: it may occur that the
information is just no more available, because of too old machines, no more
produced or replaced by new models.
Some examples of machine designations and physical data presentations used by
some manufacturers are presented hereafter, outlining the differences found among
them.
Examples
Figure 21 gives the designation data found in the catalogue data of manufacturer A.
Manufacturer A
Evaporator cooling capacity
Figure 21 Chiller designation of manufacturer A.
Figure 22 gives the designation data found in the catalogue of manufacturer B.
15

16. Reference evaporator cooling capacity – Nominal Tons
Figure 22: Chiller designation of manufacturer B
The presentation of physical data is not standardized, as seen in Figure 21 and
Figure 22. Here also, each manufacturer has his personalised presentation and
attention must be paid to each item presented (nominal loads, refrigerant type, fan
capacity, flow rates, etc.), when manipulating catalogues coming from different
manufacturers.
The units must be carefully identified: Some manufacturers use a “semi- SI” system
with kW, bar, kg/s, m³/h, etc. Other ones are still using Imperial units.
But other elementary questions must be answered, as, for example, if the data refers
to one, or to several devices (e.g. one or two condenser fans), to partial or global air
flow rate, etc.
16

17. !
n
ntio
Atte
Figure 23 Chiller physical data given by manufacturer A
17

18. Figure 24 Chiller, physical data given by manufacturer B
ARI and Eurovent standards
Hopefully, standardized ARI and/or Eurovent reference data are usually also
available in main manufacturer catalogues and can be freely downloaded from
Internet. This is a great advantage for the users. There exist other standards, but
they are not free!
18

19. Chiller modelling and parameter identification
Modelling
Various simulation models are currently available. An example of information flow
diagram used for chiller modelling is presented in Figure 22. It corresponds to the
model of a chiller with scroll compressor(s) and with air-cooled condenser. In this
model, the condenser and the evaporator are modelled as fictitious semi-isothermal
heat exchangers. A hypothetical proportional control law is applied to the condenser
fan.
Figure 25 Example information flow diagram
The same model can be used in two steps:
1) Parameter identification on one or several reference points;
2) Simulation in all other conditions of use.
Attention must be paid to the domain of validity of such model, after tuning: according
to the manufacturer: no extrapolation should be done outside the domain covered by
the catalogue.
Parameter identification
This is most delicate operation. If well done, simulation is no more a problem. Figure
26 shows the data usually found in the manufacturer catalogue. A “block diagram” of
the identification procedure is presented in Figure 27. The parameters identified are
indicated in
Figure 28.
The identification process can be done “manually” and iteratively, by considering the
result trends after each step. Default values are used as first guesses for each
component separately at the nominal point. These values are tuned in order to obtain
results that fit to all orders of magnitude. Finally the parameters are tuned again, in
order to obtain a better agreement with all experimental results and/or all
manufacturer data available.
19

20. The parameter identification is considered as satisfactory if all thermal and electrical
powers are predicted with accuracy of the order of ± 2 %.
20

21. cd – condenser
ev – evaporator
taex_cd
cp – compressor
e v – expansion valve
Air
tex_cd Condenser tsu_cd
taex_cp
Compressor
tsu_e v
tasu_cd
Expansion
valve
&
Wcp
Manufacturer data
&
Q ev tsu_cp
tex_e v
tsu_ev tex_ev R22
Evaporator
twex_ev twsu_ev
&
Mw
Figure 26 Data usually found in a manufacturer catalogue
Figure 27 “Block diagram” of the identification procedure
21

22. Figure 28 Parameters identified for chiller model
Simulation
At this stage, any user can introduce his proper data, in other to calculate the chiller
performances, as shown in Figure 29.
Figure 29 Chiller performances calculation
22

23. Examples of results
The examples of results presented hereafter are obtained with data provided by both
manufacturers (A and B) already selected. The agreement between simulation and
catalogue data is very satisfactory.
60000 20000
Qev Qev,ARI Qev,part-load,50% Wcp Wcp,ARI Wcp,part-load,50%
56000
52000
16000
48000
44000
40000 12000
Wcp [W]
Qev [W]
36000
32000
8000
28000
24000
20000 4000
16000
12000
0
12000 20000 28000 36000 44000 52000 60000 0 4000 8000 12000 16000 20000
Qev,man [W] Wcp,man [W]
Figure 30 Calculated versus catalogue data (manufacturer A)
50000 20000
Qev Qev ,ARI W WARI
45000 18000
40000 16000
Qev [W]
[W]
35000 14000
30000
W
12000
25000 10000
20000 8000
20000 25000 30000 35000 40000 45000 50000 8000 10000 12000 14000 16000 18000 20000
Qev,man [W] Wman [W]
Figure 31 Calculated versus catalogue data (manufacturer A)
Illustration of the measuring method by simulation
The compressor model (contained in the chiller model already presented) can be
used for an easy and accurate determination the chiller cooling power on site.
The two examples of simulation results presented in Figure 32 and Figure 33
demonstrate that very simple (linear) relationships could be used to determine the
chiller cooling power as function of the refrigerant pressure measured at compressor
supply. In full load and at constant rotation speed, this supply pressure is the almost
unique variable to be considered. A slight shift can be applied to this law as function
23

24. of a second variable: the temperature of the secondary fluid at condenser supply
(Figure 32) or, more directly, the condensing pressure (Figure 33).
Figure 32 Chiller cooling power as function of the compressor supply pressure (with
condenser supply air temperature as second independent variable)
Figure 33 Chiller cooling power as function of the compressor supply pressure (with
compressor exhaust pressure as second independent variable)
Such procedure is easy to apply on site, because, most of the time, both (evaporation
and condensation) pressures are actually given on the chiller control board…
24