The High-side Pressure Setpoint Algorithm of a $CO_2$ Automotive Air Conditioning System by using a Lagrange Interpolation Method and a Neural Network

라그랑즈 보간법과 신경망을 이용한 $CO_2$ 자동차에어컨시스템의 고압설정알고리즘

In order to protect the environment from the refrigerant pollution, the $CO_2$ may be regarded as one of the most attractive alternative refrigerants for an automotive air-conditioning system. Control methods for a $CO_2$ system should be different because of $CO_2$'s unique properties as a refrigerant. Especially, the high-side pressure of a $CO_2$ system should be controlled for the effective operation of the system. In this study, the high-side pressure setpoint algorithm was developed by using a neural network and a Lagrange interpolation method. These methods were compared. Simulation results showed that a Lagrange interpolation method was more effective than a neural network in the respect of its easiness of programming and shorter execution time.