Performance representation of variable-speed compressor for inverter air conditioners based on experimental data
ABSTRACT Variable speed control of compressors is one of the best methods to regulate the capacity of heat pumps and air conditioners. An analysis is conducted for modeling the variable speed compressor for simulation of inverter air conditioner and heat pump. Having scattered the real operation performance of inverter compressor into infinite operation performance of constant speed compressor, the map-based method is utilized to fit the performance curves of inverter compressor. The model is built at the basic frequency and the map condition as the second-order function of condensation temperature and evaporation temperature. Then it is corrected by the compressor frequency as the second-order function of frequency and by the actual operating condition as the actual specific volume of the suction gas. This method is used to set up simulation models of three different compressors. Compared with the data provided by the compressor manufacturers, the average relative errors are less than 2, 3 and 4% for refrigerant mass flow rate, compressor power input and coefficient of performance (COP), respectively. This model of variable speed compressor is suitable for the simulation of inverter air conditioner and heat pump systems. Based on the experimental data and simulation model, the frequency at zero mass flow rate and power input at zero frequency are discussed and the relation between COP and compressor frequency is analyzed.
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ABSTRACT: In this paper, a scroll compressor thermodynamic performance prediction was carried out by applying a hybrid ANN–PLS model. Firstly, an experimental platform with second-refrigeration calorimeter was set up and steady-state scroll compressor data sets were collected from experiments. Then totally 148 data sets were introduced to train and verify the validity of the ANN–PLS model for predicting the scroll compressor parameters such as volumetric efficiency, refrigerant mass flow rate, discharge temperature and power consumption. The ANN–PLS model was determined with 5 hidden neurons and 7 latent variables through the training process. Ultimately, the ANN–PLS model showed better performance than the ANN model and the PLS model working separately. ANN–PLS predictions agree well with the experimental values with mean relative errors (MREs) in the range of 0.34–1.96%, correlation coefficients (R2) in the range of 0.9703–0.9999 and very low root mean square errors (RMSEs).Applied Thermal Engineering 02/2015; 77. DOI:10.1016/j.applthermaleng.2014.12.023 · 2.62 Impact Factor
Procedia - Social and Behavioral Sciences 01/2012; 40:783-787. DOI:10.1016/j.sbspro.2012.03.265
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ABSTRACT: Variable speed technology was applied to compressors for rooftop units (RTUs) and heat pumps in recent years. Compressor power is a critical parameter to evaluate system performance and conduct fault detection and diagnosis (FDD). However, existing power models often use numerous parameters related to the compressor geometrical dimensions and refrigerant physical properties which makes the existing models hard to implement in the field. In this paper, a semi-theoretical compressor power model was developed for single-stage RTUs equipped with a variable speed compressor and a variable speed indoor fan, based on the theoretical analysis and experimental studies. Under the normal conditions, the compressor power is correlated to the outside air temperature and compressor speed with a relative error of ±8%. This model can be employed in the field to develop a compressor power baseline for real-time FDD on the Direct Expansion (DX) RTUs.Applied Thermal Engineering 03/2015; 78. DOI:10.1016/j.applthermaleng.2014.12.038 · 2.62 Impact Factor