International Scientific Journals
of Scientific Technical Union of Mechanical Engineering "Industry 4.0"

This paper presents a method for predicting the performance of compressors in HVAC/R systems using 2-D quadratic spline interpolation. Compared to traditional third-order polynomial interpolation, the spline model provides smoother and more accurate approximations, especially useful when limited manufacturer data is available. Using real-world compressor data, we constructed mathematical models and evaluated their performance through key statistical indicators. Results indicate that the spline-based model yields lower RMSE values with reduced model order, improving its integration in system simulations. This study also provides a comparative analysis against a polynomial-based model developed in earlier research.

This paper talks about how we can use math to create better models based on actual compressor experiments. The goal? To bridge the gap between what we see happening in real life and what we can predict, ultimately helping us optimize HVAC systems for better performance.
Within these systems, parts like compressors, fans, and electrical components play crucial roles. Compressors, especially, are quite dynamic, especially in heat pump setups.
However, the problem is that manufacturers usually only give real-world data on how compressors perform, without detailed models for understanding how they work in different situations. Hopefully in this paper we will try to construct a detailed model in order to be able to evaluate a HVAC system without the necessity of real-world data. Also, we will evaluate two different mathematical models, two dimensional interpolation and approximation in order to see who perform better.