Artificial intelligent models for thermodynamic properties of R152a and R134a refrigerants in automobile air conditioning systems

With the increase in environmental awareness, the quest for alternative refrigerants for automobile air conditioning systemsis a necessity for the protection of the ozone layer and the prevention of global warming. Therefore, it is important that the refrigerant to be used as an alternative must be at least thermodynamically sufficient and within specified environmental limits. In this study, R152a refrigerant which is an alternative gas for R134a that's use in automobile air conditioning systems will be removed within a certain schedule has been examined thermodynamically. Artificial intelligent model was generated and compared by using data obtained from the examination. Through this model, system was tested with untrained data. The generated model has been very close to test data and successful in high precision.