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International Journal of Trend in Scientific Research and Development (IJTSRD)
Volume: 3 | Issue: 3 | Mar-Apr 2019 Available Online: www.ijtsrd.com e-ISSN: 2456 - 6470
@ IJTSRD | Unique Paper ID – IJTSRD23357 | Volume – 3 | Issue – 3 | Mar-Apr 2019 Page: 1295
Analysis of Air Conditioning System used in Automobile
Dr. S. Sreenatha Reddy1, P. Akhil2, N. Raju2, K. Vishnu2, N. Ashok2
1Principal, 2Student
1,2Department of Mechanical Engineering, Guru Nanak Institute of Technology, Hyderabad, India
How to cite this paper: Dr. S. Sreenatha
Reddy | P. Akhil | N. Raju | K. Vishnu | N.
Ashok "Analysis of Air Conditioning
System used in Automobile" Published
in International Journal of Trend in
Scientific Research and Development
(ijtsrd), ISSN: 2456-
6470, Volume-3 |
Issue-3, April 2019,
pp.1295-1298, URL:
https://www.ijtsrd.c
om/papers/ijtsrd23
357.pdf
Copyright © 2019 by author(s) and
International Journal of Trend in
Scientific Research and Development
Journal. This is an Open Access article
distributed under the terms of the
Creative Commons
Attribution License
(CC BY 4.0)
(http://creativecommons.org/licenses/
by/4.0)
ABSTRACT
Air conditioning has great importance in many areas of life. Especially it is
crucial in transportation sector. Many people spend long time in an automotive
cabin (during business, travel, shopping, etc.,) every day. The aimof thisstudyis
to analyze the performance of a bus shell by considering identifying practical
solutions in order to reduce the impact of air conditioning on bus, consumption
and, therefore, on air pollution. The analysis is carried considering several
parameters, including passenger capacity, local climatic conditions, fuel
consumptions, and latitude and longitude of starting destination of the places.
For the analysis, a bus with passenger capacity of 60 people is selected and then
it’s heat load capacity will be determined by consideringdifferentconditionslike
seasons and various loads. The influence of the refrigerant decrease and the
change of the air temperature which gets to exchangers on the refrigeration
efficiency of the system to be analyzed. Also, its effectiveness and the power
required to drive the compressor will be analyzed. The entire model,itsanalysis
and results are discussed in the below work.
KEYWORDS: Refrigerant, Effectiveness, Efficiency
I. INTRODUCTION
The bus air conditioning system mainly consists of the
condenser, evaporator, compressor, magnetic clutch,
alternator, fresh air device, blower, fan, return air grille,
control panel, pipeline system and electric-controlled
system. The reservoir, filter direr, sight glass, cut-off valve,
expansion valve, and fresh air device are in the interior of
the evaporator.
The compressor is mounted on the side of the engine, and
the climate control panel of the bus air conditioning system
has its own starting system, which is located beside of the
instrument board.
The rooftop mounted evaporator assembly of bus air
conditioning are adopting the SMC housing to protect its
components and remain a good insulation performance
(Most bus air conditioning system’s evaporator use the
traditional FRP housing, but Guchen adoptstheSMCand LFT
housing materials which is lighter, higher strengthand more
environmental). The condenser is mainly divided into new
design Multi-flow-condenser (microchannel condenser) and
traditional copper and fin condenser, the condenser fan
blows the air through the condenser coil, in order to aid the
heat dissipation better.
When you press the ON/OFF button on control panel of bus
air conditioning in the driver’s cabin, relying on an inter
connecting electrical system, thecompressor isdrivenby the
electromagnetic clutch via the belt which connected to
driven pulley of engine, then the compressor circulates
refrigerant through the internal connecting hoses system.
The cycle is shown in the below figure 1.
Fig 1: Refrigeration cycle
II. LITERATURE SURVEY
IJTSRD23357
International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
@ IJTSRD | Unique Paper ID - IJTSRD23357 | Volume – 3 | Issue – 3 | Mar-Apr 2019 Page: 1296
M. Hegar examines how to verify experimentallywhether an
air conditioning system meets design and comfort
requirements. An experimental study was conducted on a
prototype bus and was tested when driving on the Adana-
Ceyhan highway in Turkey. The internal and external
temperatures, evaporator inlet and outlet temperaturesand
relative humidity values were measured. Thermalsensation
values were calculated by using empirical correlationsgiven
by ASHRAE [1].
Kutlu C Studied theoretical investigation of two-evaporator
ejector refrigeration system was carried out using R134a
and alternative refrigerants. The relative increase in COP
with respect to the conventional refrigeration system was
analyzed. Also, exergy analyses of systems were examined,
and results were showed.[2]
Paul Maina investigated the influence of variables such as;
refrigerant amount, chilling and cooling water temperature,
throttle valve opening, cooling and chilling water flow rates,
on the efficiency of a water to water carbon dioxide heat
pump. It was observed that cooling water temperature had
the highest influence followed by the chilling water
temperature. Surprisingly, theamountof therefrigerantwas
third followed by the throttle valve opening.
Understandably, chilling water flow rate had the least effect
on the COP [3].
J. Brusey proposed that energy-efficient vehicle comfort
control as a Markov Decision Process, which is then solved
numerically using Sarsa and an empiricallyvalidated,single-
zone, 1D thermal model of the cabin.Theresultingcontroller
was tested in simulation using 200 randomly selected
scenarios and found to exceed the performance of bang-
bang, proportional, simple fuzzy logic, and commercial
controllers with 23%, 43%, 40%, 56%increase,respectively
[4].
Solmaz O studied the Artificial Neural Networks method for
prediction hourly cooling load of a vehicle. For ANN model,
seven neurons determinate as input signals of latitude,
longitude, altitude, day of the year, hour of the day, hourly
mean ambient air temperature and hourly solar radiation
were used for the input layer of the network. One neuron
producing an output signal of the hourly cooling load was
utilized in the output layer [5].
III. METHODOLOGY
The given process is followed in basis of calculation of load
calculation
A. Collection of the required meteorological data:
meteorological data for calculation A typical
meteorological year (TMY) was created and the hourly,
monthly and annual values of solar radiation processed.
B. Cooling load calculation:Determinewhatkindof cooling
and how much of cooling needed.
C. Design and sizing of the air conditioning system: Using
the weather data, and the selecteddesign conditions,the
components of the system could be sized.
D. Optimization of the system: The aim was to use least
cost energy, so the designed system was optimizedwith
that in mind.
E. Material procurement and construction of the
experimental system: Once the system had been
optimized, the components were procured, and the
system was constructed and tested.
F. Performance evaluation and economic analysis: The
energetic and economical effectiveness of the system
was evaluated. The life cycle costs for solar cooling
system were calculated and competitiveness with
regards to price and thermal efficiency for domestic
applications determined. g) Analysis of results and
making of recommendations:Theresultswere analyzed,
andnecessaryimprovements recommended. Options for
improving technical effectiveness and economic
competitiveness were suggested. Ways of improving
research and development efforts in this field were also
investigated.
We consider a lumped model of a typical vehicle cabin. The
net heat gain by the cabin can be classified under nine
different categories. The total load as well as each of these
loads can either be positive (heating up the cabin) or
negative (cooling down the cabin) and may depend on
various driving parameters. In the following, the models
developed for each of these load categories are presented
and discussed. Some of the correlations used in the present
model are based on experiments performed on certain
vehicles, which are used here for general validation of the
model. New correlations can be readily plugged into the
present model can be tailored to any new vehicle, after
specifying those correlations for the case.
Designing of Automobile by CATIA V5
Starting of CATIA V5 is with a new name which will be
displayed on the screen.
Close the product1 file and start a new file in the part design
workbench.
After choosing to close the file menu, then start screen of
CATIA is displayed.
Start >> Mechanical Design >> select Sketcher or partdesign
To start a new file in the part design workbench, choose file
from the menu bar. The new dialog box is displayed. After
accomplishment all thenecessarycuttingsand modifications
of the Air Filter, the ultimate model looks as shown in
figures.
Fig 2: Wireframe Model
International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
@ IJTSRD | Unique Paper ID - IJTSRD23357 | Volume – 3 | Issue – 3 | Mar-Apr 2019 Page: 1297
Fig 3: 3D Model
IV. RESULTS AND DISCUSSIONS
1. METABOLIC LOAD
The metabolic load can be calculated by
QMet = ∑ MADu
Where M is passenger metabolic heat production rate
=85 W/m2 for driver
=55 W/m2 for passenger
M=85+55*59 (no. of passengers)
=3330 W/m2
ADu=Body surface area
ADu=0.202W0.425H0.725
where W and H are the passenger weight and height
=0.202*650.425*1.70.725
=1.749504 m2
QMet = 3330*1.749504
= 5825.84832 W
2. RADIATION LOAD
Direct radiation is that part of the incident solar radiation
which directly strikes a surface of the vehicle body, which is
calculated from
QDir = ∑ SτiDir cos ө
According to ASHRAE 2007-chapter 33 Table no. 20
Peak load = 1417 W/m
iDir = 1417 W/m2
Glass surface area S= 30 m2
τ = 0.5
ө = 750
QDir = 30*0.5*1417*cos (750)
= 5501.19 W
QDif = ∑ SτiDif
iDif = CiDir (1+cos ∑)/2
=0.103*1417*(1+cos 900)/2
=72.97 W/m2
QDif = 30*0.5*72.97
= 1094.55 W
QRef = ∑ SτiRef
iRef = (iDir+iDif)*ρg*(1-cos ∑)/2
= (417+72.97) *0.2*(1-cos 900)/2
= 148.997 W/m2
QRef = 30*0.5*148.997
= 2234.9555 W
QS.Rad = Sα (iDircosө+iDif+iRef)
=30*0.3(1417*cos750+72.97+148.997) for glass
= 5298.422 W
QS.Rad=37.36*0.4(1417*cos750+72.97+148.997) for surface
= 8797.73 W
QS.Rad = 5298.422+8797.93
= 14096.352 W
3. AMBIENT LOAD
The ambient load is the contribution of the thermal load
transferred to the cabin air due to temperature difference
between the ambient and cabin air.
QAmb = ∑ SU(Ts-Ti)
For glass S = 30 m2
Speed = 60 kmph
V = 60*5/18 = 16.66 m/s
Where U is the overall heat transfer coefficientof thesurface
element
U = 1/R
Where R =1/h0+χ/k+1/hi
R is the net thermal resistance for a unit surface area. hoand
hi are the outside and inside convection coefficients, k is the
surface thermal conductivity, and λ is the thickness of the
surface element.
h = 0.6+6.64(V)0.5
Where h is the convection heat transfer coefficient in
W/m2K, and V is the vehicle speed in m/s.
hi = 0.6
h0 = 0.6+6.64(16.66)0.5
= 27.70
For glass k = 1.05, χ = 0.003 m
R = 1/27.70 + 0.003/1.05 + 1/0.6
R = 1.705 m/W/m. K
U = 1/1.705 = 0.586 W/m2.K
QAmb = 30*0.586*(60-30)
= 527.4 W
For surfacek = 0.2, χ = 10, S = 37.36 m2
R = 1/27.70 + 0.01/0.2 + 1/0.6
= 1.753 m/W/m. K
U = 1/1.753 = 0.570 W/m2.K
QAmb = 37.36*0.570*(60-30)
= 638.856 W
QAmb = Glass + Surface
= 527.4 + 638.856
= 1166.256 W
4. EXHAUST LOAD
The exhaust heat load entering the cabin can be written as
QExh = SExhU(TExh-Ti)
TExh = 0.138RPM-17
= 0.138*6000-17
International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
@ IJTSRD | Unique Paper ID - IJTSRD23357 | Volume – 3 | Issue – 3 | Mar-Apr 2019 Page: 1298
= 811 K
QExh = 15.3*0.570*(811-303)
= 6817.101 W
5. ENGINE LOAD
QEng = SEngU(TEng-Ti)
TEng = -2*10-6*RPM2+0.0355*RPM+77.5
= -2*10-6*60002+0.0355*6000+77.5
= 218.5 K
QEng = 1.7*0.570*(218.5-30)
=182.65 W
6. VENTILATION LOAD
According to psychrometric calculations, ventilation heat
gain consists of both sensible and latentloads.To accountfor
both these terms, assuming a known flow rate of fresh air
entering the cabin, the amount of thermal heat gain can be
calculated from
QVen = mVen(e0-ei)
Where mVen is the ventilation mass flow rate and eo and ei
are the ambient and cabin enthalpies, respectively.
Enthalpies are calculated from
e = 1006*T+(2.501*106+1770T) X
e0=1006*40+(2.501*106+1770*40)0.3 (T0=40,
X=0.3)
= 811780 J/kg
ei = 1307230 J/kg (Ti = 30, X=0.5)
Where T is air temperature and X is humidity ratio in gram
of water per gram of dry air.
mVen = 0.02 kg/s
QVen = 0.02(811780-1307230)
= -9909 W
7. AC LOAD
QAC=(QMet+QDir+QDif+QRef+QS.Rad+QExh+QEng+QVen)-(maca+DTM)
(Ti-TComf)/tc
Here ma = 44.488 kg
ca = 1.005
DTM = 5.6 kJ/kg
TComf = 20
Ti = 30
tc = 600 sec
QAC = -27003.70382-0.8348 W
= -27.838 kW
1 TR = 0.284 kW
QAC = 27.838*0.284
= 7.906 TR
A graph is drawn in below figure 4 according to the TR
values obtained by the analysis using excel sheets.
Fig 4: TR variation curve
According to the layout of automobile wehavedone analysis
by taking the number of people 60, 30 and 02 in the bus in
three seasons like summer, winterandrainyseasons. Within
these conditions we have calculated the various loads and
TR. The obtained total load for the automobile is 27.84 kW
and the TR is 7.90696. The best suitable refrigerant which
removes the calculated amount of heat with minimum
torque is R-134a. The compressor which consumes least
torque from the engine selected is Valeo TM65 based on the
TR value obtained.
References
[1] M. Hegar M., M. Kolda, M. Kopecka, V. Rajtmajer, A.
Ryska, Bus HVAC energy consumption test method
based on HVAC unit 85ehavior, InternationalJournalof
Refrigeration, 36 (2013) 1254-1262.
[2] Kutlu Ç., Ünal Ş., Erdinç M. T... Thermodynamicanalysis
of bi-evaporator ejector refrigeration cycle usingR744
as natural refrigerant. Journal of Thermal Engineering,
2,735-740, 2016.
[3] P. Maina, Z. Huan, Effects of various parameters on the
efficiency of a CO2 heat pump: Astatistical approach,
journal of thermal engineering, 1(4) (2015), 263-278.
[4] Hintea, D., Brusey, J., Gaura, E., Kemp, J., Beloe, N.,2013.
Comfort in cars estimating equivalent temperature for
comfort drivenheating,ventilation andair conditioning
(HVAC) control. In: Conference Proceedings of the
Informatics in Control, Automation and Robotics
(ICINCO 2013).
[5] Ozgoren M, Solmaz O, KahramanA.Prediction of hourly
cooling load capacity of an automotiveair-conditioning
system. In: International ege energy symposium and
exhibition (IEESE-5), 27–30 June 2010, Pamukkale
University, Denizli-Turkey.

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Analysis of Air Conditioning System used in Automobile

  • 1. International Journal of Trend in Scientific Research and Development (IJTSRD) Volume: 3 | Issue: 3 | Mar-Apr 2019 Available Online: www.ijtsrd.com e-ISSN: 2456 - 6470 @ IJTSRD | Unique Paper ID – IJTSRD23357 | Volume – 3 | Issue – 3 | Mar-Apr 2019 Page: 1295 Analysis of Air Conditioning System used in Automobile Dr. S. Sreenatha Reddy1, P. Akhil2, N. Raju2, K. Vishnu2, N. Ashok2 1Principal, 2Student 1,2Department of Mechanical Engineering, Guru Nanak Institute of Technology, Hyderabad, India How to cite this paper: Dr. S. Sreenatha Reddy | P. Akhil | N. Raju | K. Vishnu | N. Ashok "Analysis of Air Conditioning System used in Automobile" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456- 6470, Volume-3 | Issue-3, April 2019, pp.1295-1298, URL: https://www.ijtsrd.c om/papers/ijtsrd23 357.pdf Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/ by/4.0) ABSTRACT Air conditioning has great importance in many areas of life. Especially it is crucial in transportation sector. Many people spend long time in an automotive cabin (during business, travel, shopping, etc.,) every day. The aimof thisstudyis to analyze the performance of a bus shell by considering identifying practical solutions in order to reduce the impact of air conditioning on bus, consumption and, therefore, on air pollution. The analysis is carried considering several parameters, including passenger capacity, local climatic conditions, fuel consumptions, and latitude and longitude of starting destination of the places. For the analysis, a bus with passenger capacity of 60 people is selected and then it’s heat load capacity will be determined by consideringdifferentconditionslike seasons and various loads. The influence of the refrigerant decrease and the change of the air temperature which gets to exchangers on the refrigeration efficiency of the system to be analyzed. Also, its effectiveness and the power required to drive the compressor will be analyzed. The entire model,itsanalysis and results are discussed in the below work. KEYWORDS: Refrigerant, Effectiveness, Efficiency I. INTRODUCTION The bus air conditioning system mainly consists of the condenser, evaporator, compressor, magnetic clutch, alternator, fresh air device, blower, fan, return air grille, control panel, pipeline system and electric-controlled system. The reservoir, filter direr, sight glass, cut-off valve, expansion valve, and fresh air device are in the interior of the evaporator. The compressor is mounted on the side of the engine, and the climate control panel of the bus air conditioning system has its own starting system, which is located beside of the instrument board. The rooftop mounted evaporator assembly of bus air conditioning are adopting the SMC housing to protect its components and remain a good insulation performance (Most bus air conditioning system’s evaporator use the traditional FRP housing, but Guchen adoptstheSMCand LFT housing materials which is lighter, higher strengthand more environmental). The condenser is mainly divided into new design Multi-flow-condenser (microchannel condenser) and traditional copper and fin condenser, the condenser fan blows the air through the condenser coil, in order to aid the heat dissipation better. When you press the ON/OFF button on control panel of bus air conditioning in the driver’s cabin, relying on an inter connecting electrical system, thecompressor isdrivenby the electromagnetic clutch via the belt which connected to driven pulley of engine, then the compressor circulates refrigerant through the internal connecting hoses system. The cycle is shown in the below figure 1. Fig 1: Refrigeration cycle II. LITERATURE SURVEY IJTSRD23357
  • 2. International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470 @ IJTSRD | Unique Paper ID - IJTSRD23357 | Volume – 3 | Issue – 3 | Mar-Apr 2019 Page: 1296 M. Hegar examines how to verify experimentallywhether an air conditioning system meets design and comfort requirements. An experimental study was conducted on a prototype bus and was tested when driving on the Adana- Ceyhan highway in Turkey. The internal and external temperatures, evaporator inlet and outlet temperaturesand relative humidity values were measured. Thermalsensation values were calculated by using empirical correlationsgiven by ASHRAE [1]. Kutlu C Studied theoretical investigation of two-evaporator ejector refrigeration system was carried out using R134a and alternative refrigerants. The relative increase in COP with respect to the conventional refrigeration system was analyzed. Also, exergy analyses of systems were examined, and results were showed.[2] Paul Maina investigated the influence of variables such as; refrigerant amount, chilling and cooling water temperature, throttle valve opening, cooling and chilling water flow rates, on the efficiency of a water to water carbon dioxide heat pump. It was observed that cooling water temperature had the highest influence followed by the chilling water temperature. Surprisingly, theamountof therefrigerantwas third followed by the throttle valve opening. Understandably, chilling water flow rate had the least effect on the COP [3]. J. Brusey proposed that energy-efficient vehicle comfort control as a Markov Decision Process, which is then solved numerically using Sarsa and an empiricallyvalidated,single- zone, 1D thermal model of the cabin.Theresultingcontroller was tested in simulation using 200 randomly selected scenarios and found to exceed the performance of bang- bang, proportional, simple fuzzy logic, and commercial controllers with 23%, 43%, 40%, 56%increase,respectively [4]. Solmaz O studied the Artificial Neural Networks method for prediction hourly cooling load of a vehicle. For ANN model, seven neurons determinate as input signals of latitude, longitude, altitude, day of the year, hour of the day, hourly mean ambient air temperature and hourly solar radiation were used for the input layer of the network. One neuron producing an output signal of the hourly cooling load was utilized in the output layer [5]. III. METHODOLOGY The given process is followed in basis of calculation of load calculation A. Collection of the required meteorological data: meteorological data for calculation A typical meteorological year (TMY) was created and the hourly, monthly and annual values of solar radiation processed. B. Cooling load calculation:Determinewhatkindof cooling and how much of cooling needed. C. Design and sizing of the air conditioning system: Using the weather data, and the selecteddesign conditions,the components of the system could be sized. D. Optimization of the system: The aim was to use least cost energy, so the designed system was optimizedwith that in mind. E. Material procurement and construction of the experimental system: Once the system had been optimized, the components were procured, and the system was constructed and tested. F. Performance evaluation and economic analysis: The energetic and economical effectiveness of the system was evaluated. The life cycle costs for solar cooling system were calculated and competitiveness with regards to price and thermal efficiency for domestic applications determined. g) Analysis of results and making of recommendations:Theresultswere analyzed, andnecessaryimprovements recommended. Options for improving technical effectiveness and economic competitiveness were suggested. Ways of improving research and development efforts in this field were also investigated. We consider a lumped model of a typical vehicle cabin. The net heat gain by the cabin can be classified under nine different categories. The total load as well as each of these loads can either be positive (heating up the cabin) or negative (cooling down the cabin) and may depend on various driving parameters. In the following, the models developed for each of these load categories are presented and discussed. Some of the correlations used in the present model are based on experiments performed on certain vehicles, which are used here for general validation of the model. New correlations can be readily plugged into the present model can be tailored to any new vehicle, after specifying those correlations for the case. Designing of Automobile by CATIA V5 Starting of CATIA V5 is with a new name which will be displayed on the screen. Close the product1 file and start a new file in the part design workbench. After choosing to close the file menu, then start screen of CATIA is displayed. Start >> Mechanical Design >> select Sketcher or partdesign To start a new file in the part design workbench, choose file from the menu bar. The new dialog box is displayed. After accomplishment all thenecessarycuttingsand modifications of the Air Filter, the ultimate model looks as shown in figures. Fig 2: Wireframe Model
  • 3. International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470 @ IJTSRD | Unique Paper ID - IJTSRD23357 | Volume – 3 | Issue – 3 | Mar-Apr 2019 Page: 1297 Fig 3: 3D Model IV. RESULTS AND DISCUSSIONS 1. METABOLIC LOAD The metabolic load can be calculated by QMet = ∑ MADu Where M is passenger metabolic heat production rate =85 W/m2 for driver =55 W/m2 for passenger M=85+55*59 (no. of passengers) =3330 W/m2 ADu=Body surface area ADu=0.202W0.425H0.725 where W and H are the passenger weight and height =0.202*650.425*1.70.725 =1.749504 m2 QMet = 3330*1.749504 = 5825.84832 W 2. RADIATION LOAD Direct radiation is that part of the incident solar radiation which directly strikes a surface of the vehicle body, which is calculated from QDir = ∑ SτiDir cos ө According to ASHRAE 2007-chapter 33 Table no. 20 Peak load = 1417 W/m iDir = 1417 W/m2 Glass surface area S= 30 m2 τ = 0.5 ө = 750 QDir = 30*0.5*1417*cos (750) = 5501.19 W QDif = ∑ SτiDif iDif = CiDir (1+cos ∑)/2 =0.103*1417*(1+cos 900)/2 =72.97 W/m2 QDif = 30*0.5*72.97 = 1094.55 W QRef = ∑ SτiRef iRef = (iDir+iDif)*ρg*(1-cos ∑)/2 = (417+72.97) *0.2*(1-cos 900)/2 = 148.997 W/m2 QRef = 30*0.5*148.997 = 2234.9555 W QS.Rad = Sα (iDircosө+iDif+iRef) =30*0.3(1417*cos750+72.97+148.997) for glass = 5298.422 W QS.Rad=37.36*0.4(1417*cos750+72.97+148.997) for surface = 8797.73 W QS.Rad = 5298.422+8797.93 = 14096.352 W 3. AMBIENT LOAD The ambient load is the contribution of the thermal load transferred to the cabin air due to temperature difference between the ambient and cabin air. QAmb = ∑ SU(Ts-Ti) For glass S = 30 m2 Speed = 60 kmph V = 60*5/18 = 16.66 m/s Where U is the overall heat transfer coefficientof thesurface element U = 1/R Where R =1/h0+χ/k+1/hi R is the net thermal resistance for a unit surface area. hoand hi are the outside and inside convection coefficients, k is the surface thermal conductivity, and λ is the thickness of the surface element. h = 0.6+6.64(V)0.5 Where h is the convection heat transfer coefficient in W/m2K, and V is the vehicle speed in m/s. hi = 0.6 h0 = 0.6+6.64(16.66)0.5 = 27.70 For glass k = 1.05, χ = 0.003 m R = 1/27.70 + 0.003/1.05 + 1/0.6 R = 1.705 m/W/m. K U = 1/1.705 = 0.586 W/m2.K QAmb = 30*0.586*(60-30) = 527.4 W For surfacek = 0.2, χ = 10, S = 37.36 m2 R = 1/27.70 + 0.01/0.2 + 1/0.6 = 1.753 m/W/m. K U = 1/1.753 = 0.570 W/m2.K QAmb = 37.36*0.570*(60-30) = 638.856 W QAmb = Glass + Surface = 527.4 + 638.856 = 1166.256 W 4. EXHAUST LOAD The exhaust heat load entering the cabin can be written as QExh = SExhU(TExh-Ti) TExh = 0.138RPM-17 = 0.138*6000-17
  • 4. International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470 @ IJTSRD | Unique Paper ID - IJTSRD23357 | Volume – 3 | Issue – 3 | Mar-Apr 2019 Page: 1298 = 811 K QExh = 15.3*0.570*(811-303) = 6817.101 W 5. ENGINE LOAD QEng = SEngU(TEng-Ti) TEng = -2*10-6*RPM2+0.0355*RPM+77.5 = -2*10-6*60002+0.0355*6000+77.5 = 218.5 K QEng = 1.7*0.570*(218.5-30) =182.65 W 6. VENTILATION LOAD According to psychrometric calculations, ventilation heat gain consists of both sensible and latentloads.To accountfor both these terms, assuming a known flow rate of fresh air entering the cabin, the amount of thermal heat gain can be calculated from QVen = mVen(e0-ei) Where mVen is the ventilation mass flow rate and eo and ei are the ambient and cabin enthalpies, respectively. Enthalpies are calculated from e = 1006*T+(2.501*106+1770T) X e0=1006*40+(2.501*106+1770*40)0.3 (T0=40, X=0.3) = 811780 J/kg ei = 1307230 J/kg (Ti = 30, X=0.5) Where T is air temperature and X is humidity ratio in gram of water per gram of dry air. mVen = 0.02 kg/s QVen = 0.02(811780-1307230) = -9909 W 7. AC LOAD QAC=(QMet+QDir+QDif+QRef+QS.Rad+QExh+QEng+QVen)-(maca+DTM) (Ti-TComf)/tc Here ma = 44.488 kg ca = 1.005 DTM = 5.6 kJ/kg TComf = 20 Ti = 30 tc = 600 sec QAC = -27003.70382-0.8348 W = -27.838 kW 1 TR = 0.284 kW QAC = 27.838*0.284 = 7.906 TR A graph is drawn in below figure 4 according to the TR values obtained by the analysis using excel sheets. Fig 4: TR variation curve According to the layout of automobile wehavedone analysis by taking the number of people 60, 30 and 02 in the bus in three seasons like summer, winterandrainyseasons. Within these conditions we have calculated the various loads and TR. The obtained total load for the automobile is 27.84 kW and the TR is 7.90696. The best suitable refrigerant which removes the calculated amount of heat with minimum torque is R-134a. The compressor which consumes least torque from the engine selected is Valeo TM65 based on the TR value obtained. References [1] M. Hegar M., M. Kolda, M. Kopecka, V. Rajtmajer, A. Ryska, Bus HVAC energy consumption test method based on HVAC unit 85ehavior, InternationalJournalof Refrigeration, 36 (2013) 1254-1262. [2] Kutlu Ç., Ünal Ş., Erdinç M. T... Thermodynamicanalysis of bi-evaporator ejector refrigeration cycle usingR744 as natural refrigerant. Journal of Thermal Engineering, 2,735-740, 2016. [3] P. Maina, Z. Huan, Effects of various parameters on the efficiency of a CO2 heat pump: Astatistical approach, journal of thermal engineering, 1(4) (2015), 263-278. [4] Hintea, D., Brusey, J., Gaura, E., Kemp, J., Beloe, N.,2013. Comfort in cars estimating equivalent temperature for comfort drivenheating,ventilation andair conditioning (HVAC) control. In: Conference Proceedings of the Informatics in Control, Automation and Robotics (ICINCO 2013). [5] Ozgoren M, Solmaz O, KahramanA.Prediction of hourly cooling load capacity of an automotiveair-conditioning system. In: International ege energy symposium and exhibition (IEESE-5), 27–30 June 2010, Pamukkale University, Denizli-Turkey.