How to design the Intelligent Control System in Air Conditioning Unit?

How to design the Intelligent Control System in Air Conditioning Unit?

1. Introduction

The conventional air conditioning systems used manual controlling system that is on and off controllers. In case temperature drops below the set value the controlling system is turned off automatically, whereas temperature rises above the set value, the system may turn on. Example like if the temperature rise to 27?, then controlling system turn on and spread cooling air  in order to reduce the temperature of the specific area. Similarly, if working area get cooled at 20 to 18? then it turning off in order to stop spreading cooling air that terminate the power for buffer time. The total power save through this system will considerable as require performance of air conditioning system.  This way the machine become smother and less wear and tear of air conditioning system.  More consistence performance that increase efficiency of the entire unit.
The intelligence control system enhance performance of the BMS system, the ICS play important role to manage all instrument such as mechanical and electric device associate with the organization.  With the help of ICS system, the organization control the requirement of particular mechanical component require or not with present of person and different time slot as per schedule of working. I.e. save power and efficiency when system may not require to perform operation.  Therefore organization decide to use automatic system which control that system without interference of human operation.  The artificial intelligence can help to manage automatic control system which can manage all operation as per requirement of the mechanical or electric component power or performance output. 
In this project, demonstrate air conditioning system which provide cooling effect as per requirement of cooling at particular area. That result will enhance total performance of intelligence control system, also reduce the total operating cost of the system, less maintenance cost,  can place alternate system which enhance performance, less power consume and provide long life operation which require from the system. 

2. Design of air conditioning system

In order to provide cooling effect to 1300 m2 area, it is require centralize system which provide cooling effect to the particular area.  In order to provide cooling effect at the office location, I prepare CAD model in solidworks software. The system place at the top most central location of the office where need to provide cooling effect.  The following figure demonstrate the air conditioning system place at the office top most central position where that system can supply cooling effect to every department.   Design prepare using solidworks software in order to provide real scenario at office place.  I decide to use aluminium alloy foil to prepare air conditioning system which helps to keep low temperature and there are considerable low thermal expansion through aluminium alloy. the fibre material also good application in order to design air conditioning system, we can also place fibre material for design air conditioning system because it light weight,  thermal expansion is low, corrosion resistance, easy to assemble and easy to place at compact area. 
In order to evaluate performance of air conditioning system, it is require to perform analysis or need to perform practical experiment.  For this project practical experiment was difficult part and need special permission and expert guidance in order to satisfied objective of project. So simulation is sufficient tool in order to obtain specific parameter which require for the project objective.  The above figure present about the simulation perform through CAD and CAE tool solidworks. The objective function of this simulation is to obtain pressure variation at fixed cycle.  The above figure demonstrate about the air cooled inside the system with pressure variation.  Air pressure and temperature variation affect the performance of the air conditioning system. The simulation result present pressure different inside the air conditioning system. The pressure varies from maximum to minimum such as 101324.12 Pa to 101324.85 Pa which was neglected variation in pressure.
The pressure induce was equal to the atmospherically pressure and there were not such pressure different notice at 46 iteration. The pressure change remains constant through the complete simulation and we can conclude that temperature also remains equal if pressure will not increase or decrease. The ICS system can associate with design system in order to kept temperature constant or variable as per convenience operation of air conditioning system. We can conclude that the air can maintain humidity throughout the path of air flow at the destination. 

3. Thermal Analysis

Temperature analysis perform in order to obtain behaviour of refrigerant with number of person present at working location or at office place.  The following figure demonstrate the coming effect change with increasing length from source of air refrigeration system.  The experiment result or simulation result obtained from excel solution with the collecting data of numbers of person present at the office location.
The above figure demonstrate result of temperature change with gradually increasing length from the source of air conditioning system. The average temperature remains 293.3108 K throughout the area of working location. The result obtained with the presents of one person only at the working site. For thermal or temperature analysis we were perform three experiment in order to obtain specific conclusion and should be satisfied objective of the project.  Further experiment perform with the presence of two persons.  The following figure demonstrate the result obtain through experiment.
The above figure demonstrate about the temperature change with the presence of two persons. The result of second experiment was considerable difference from previous experiment. The average temperature throughout the cycle was 293.1669 K. the result indicate that cooling at working location affected through presence of numbers of persons. There were noticeable temperature difference with numbers of persons increase or change, if consider entire unit at working location. The following figure demonstrate about the change in temperature without person presence inside the working location. The average temperature at this condition was 293. 153 K at length increase from 0 to 4 metre at the specific region.
There were noticeable temperature with the presence of number of person and without presence of number of person at the office premises or fixed region. The results have significant change in temperature in order to numbers of persons present at the working region.  In case, there were no person then temperature considerable low, and further temperature increase gradually as numbers of persons increases.

4. Simulation of ICS air conditioning system

In order to enhance the performance and change the design of air conditioning unit, there are considerable control system take place while design such system. The aim of the system is to increase efficiency as we can with respect to time domain i.e. improve entire Building management system in order to develop new system which enhance air conditioning system. There are several controlling option were considered that presence controller sensor which would be turn on or off when people are presence or absence at the room where air conditioning system installed.  The temperature also change as per the presence and absence of the numbers of person at the working place and sensor detect that signal and change the efficient output from the air conditioning system.
According to observation of the current conventional air conditioning unit performance,  there is not such controlling unit which control the cooling effect with respect the surrounding temperature at the working place. Therefore it require control of air condition cooling automatically, also  that require feedback control system which monitor temperature with respect to the data input from sensor.
The report presents about the air conditioning temperature control system through existing temperature at the working place and outside temperature. The variation of two temperature sense through sensor and that affect the performance output of the entire system and can manage to achieve comfortable point. That happen when the difference presence from the current condition and variable condition that affect the sensor and the sensor controller change the cooling effect automatically. The purpose of the system will enhance performance through air conditioning unit by placing automatic control unit.
In order to perform simulation, there are construct geometry of ICS refrigeration system.  Figure.1 present about the air conditioning system allocated to intelligent control system. In order to obtain time versus temperature analysis. It is require to perform simulation through solidworks CAD and CAE software. The material of the air conditioning system assign as aluminium alloy which have low thermal insulation. Further applying boundary condition and loading condition in order to obtained behaviour of the ICS system attached with air conditioning system. Considering air conditioning system is enclosed in all direction.
  • Neglecting human error. 
  • Simulation perform with the presence of number of person.
  • Material property assign aluminium alloy to air conditioning system.
  • Consider air condition unit affect through environment condition.
  • Time to obtain temperate is not relevant to practical approach.
In order to enhance performance of air conditioning unit, there are perform simulation such as time based transient analysis using Computer aided engineering tool such as solidworks. The simulation perform with two stage as define below. Initially perform for 300 seconds simulation and further perform for 1800 seconds. The temperature of the air conditioning unit set for the simulation is 24?. The convection unit assign as 100 W/m2K and the Heat power per unit 8.3. In order to perform simulation the above boundary condition have used. The time and temperature based analysis have used at ICS and BMS system. Further obtain graph of time-temperature based analysis.
The maximum temperature obtained through given system was 293 K. The simulation have perform for 300 seconds and obtained result for temperature variation with time. Above both figures are obtained through simulation of refrigeration system. Both system have similar refrigeration system but perform at different boundary condition. The both figure shows noticeable difference in ICS and BMS system. The temperature increase as the time increases in BMS system, whereas temperature of air refrigeration system decrease with respect to time.
Time set for the simulation was 10 to 300 seconds in order to obtain significant difference. It is obvious that ICS system need to provide cooler air then BMS with specific time limit. The solidworks simulation results provide ICS system serve quick response compare to BMS system. Simulation perform for 300 to 1800 seconds, and following results obtained through transient analysis in order to obtained time versus temperature graph.The above figure obtained through solidworks simulation at the variable section of the air conditioning unit in ICS system.
The time versus temperature graph plotted for the 1800 seconds at the different section of the unit. The plotted graph are useful for intelligent control system, in order to enhance the total performance of the intelligence control system. As shown in above figure.4 & 5, the graph plotted at the variable section of the intelligence control system. The figure.5 graph at the BMS unit area where temperature increase with increase the time period of the BMS area. Whereas figure. 4 obtained through intelligence control unit merge with air conditioning unit and temperature decrease with respect to time which is require for the intelligence control system. 

5. Flow simulation of air conditioning system

In order to obtained behaviour of the intelligence control system with the air conditioning unit, there are performing flow simulation at the air conditioning unit. The air conditioning performance depends on the mechanical properties such as temperature, pressure and velocity of fluid.  In order to obtained behaviour of the air conditioning unit which is allocated to intelligent control system. It is require to perform flow simulation. The result are plotted in terms of velocity profile and pressure variation throughout the process. Also obtained about the match number and humidity of the air conditioning unit.
The working fluid used for the system was air in order to perform simulation, it can be water or air used for the complete system. The following figure present about the closed boundary of the air conditioning unit in intelligence control system.  It is consider that surrounding atmospherically condition also affect to the air conditioning unit and intelligence control system. The performance of air conditioning unit affect to the intelligence control system and building management system also. For this case, it would be vice a versa.
The above figure indicate the air conditioning system enclosed with surrounding medium and surrounding medium consider as unstable air or turbulence air. 
As shown in above figure consider the air refrigerant flow inside the system and spread air to the organization premises for cooling.  In order to enhance the total performance of intelligence control system, it is require to obtain maximum pressure, maximum flow velocity, match number and surrounding temperature. The air temperature obtained in previous simulation where maximum temperature occur 300 K which is moderate temperature.
Further, the flow simulation is perform to obtain maximum pressure and velocity of the air through air conditioning system. As shown in above figure, the pressure profile plot in two dimension for observe maximum pressure occur at the planner condition.  It is observe that maximum pressure occur at the exit of the air conditioning system. The maximum pressure occur at the refrigeration system was 226421.40 Pa whereas minimum should be above the atmospheric condition. 
Lowest pressure occur at the surrounding area and the surface of the air conditioning system. the intelligence control system require to manage pressure of the air conditioning unit. If the organization department have fixed working hour then control system can place automatic in order to change temperature and pressure of the air conditioning unit.  For this case, the flow of air assume to be 30 m/s and allow to flow of air through air conditioning unit. The flow of air consider as two dimension only, so that velocity profile also plotted in two dimension only.
The maximum velocity induce during simulation was 33 m/s and it can be controlled through intelligence control system. The flow simulation and thermal analysis provide mechanical properties and value of that properties which lies between maximum to minimum value. The Mach number is the dimensionless properties, it is play important role in flow simulation in order to obtained behaviour of the system. For intelligence control unit these are the sufficient parameter which can control through control system or automatic system and can increase performance of intelligence control system by place fixed cycle which can produce specific range of pressure, velocity and temperature at the working organization. 
The Mach number obtained through flow simulation and it value above the 1, so the velocity of air is supersonic. The velocity of air need to control for sufficient cooling at the working place. The velocity of air can be manage through trial or error method or need to obtain through theoretical calculation. In order to design intelligence control system in air conditioning unit, it is require to control temperature with automatic control system. Therefore, in order to control temperature of air conditioning unit of intelligence control system, it is require to place fuzzy logic control system. it is recommend for future work of the project in order to control the  intelligence control system fully automatic, it is assemble fuzzy logic system.

6. Conclusion

In order to enhance the performance of intelligence control system in air conditioning unit. It is require to obtain associate parameter which affect the performance of intelligence control system attached with air conditioning unit. The air conditioning unit associate with the difference parameter and that parameters are affect lot for the output of the system. the parameters associate with this system is temperature, pressure and velocity of the air  or refrigerant circulate inside the system.
The thermal and transient analysis provide the result of temperature change with respect to time and flow simulation provide result of maximum pressure induce inside the system, also  flow velocity can be controllable through intelligence control system. If all parameter can fixed with the intelligence control system then maximum output obtained through air conditioning unit and minimum power can utilized through control system.

7. Future work

The conventional air conditioning unit is always cool the workplace through manual control and require to keep change temperature of system through manual, it is not automatic control and may not conform as require for the work place. That will be individual and personal perspective, apart from that the temperature and cooling efficiency will looking to change with the presence of person at the work place. It means cooling require low as numbers of person less as compare to usual person exist at the work place.  In the central air conditioning control unit require good intelligence, high reliability and real-time performance experience by different researcher. The conventional PID controller still perform up to the mark for the controlling process. The air controlling unit become area of new invention to improve performance through intelligence control system along with Adaptive Fuzzy controller. 

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8. References

Afram, A., & Janabi-Sharifi, F. (2018). Theory and applications of HVAC control systems – A review of model predictive control (MPC). Retrieved 7 March 2018.
Chua, K., Chou, S., Yang, W., & Yan, J. (2018). Achieving better energy-efficient air conditioning – A review of technologies and strategies. Retrieved 7 March 2018.
Doukas, H., Patlitzianas, K., Iatropoulos, K., & Psarras, J. (2018). Intelligent building energy management system using rule sets. Retrieved 7 March 2018.
Dounis, A., & Caraiscos, C. (2018). Advanced control systems engineering for energy and comfort management in a building environment—A review. Retrieved 7 March 2018.
Shaikh, P., Nor, N., Nallagownden, P., Elamvazuthi, I., & Ibrahim, T. (2018). A review on optimized control systems for building energy and comfort management of smart sustainable buildings. Retrieved 7 March 2018.
Soyguder, S., Karakose, M., & Alli, H. (2018). Design and simulation of self-tuning PID-type fuzzy adaptive control for an expert HVAC system. Retrieved 7 March 2018.
US6349883B1 - Energy-saving occupancy-controlled heating ventilating and air-conditioning systems for timing and cycling energy within different rooms of buildings having central power units - Google Patents. (2018). Retrieved 7 March 2018, from

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