ML-11-026 -- Parameter Estimation of Dynamic Vapor Compression System Models Using Limited Sensor Information PDF

This paper presents a novel approach for identifying critical parameters in dynamic vapor compression system models using limited sensor information. Because the system dynamics are extremely sensitive to changes in refrigerant mass flow rate, accurate expansion valve and compressor models are essential to creating effective dynamic models. However, mass flow rate information is not commonly available for installed systems. This work presents models for electronic and thermostatic expansion valves (EEVs and TEVs), evaporators, and compressors. An integrated approach is used to identify model parameters using only temperature and pressure sensors. Two numerical search algorithms, nonlinear least squares and simplex search, are used to estimate the parameters, and the approach is validated on three distinct experimental systems. These techniques are enabling tools for creating effective models for dynamic analysis, control design, and fault detection. An additional contribution of this work is the quantitative validation of a simple model of a TEV-controlled system, which has been lacking in the literature.