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Development of a black-box compressor model that captures vapor-injection compared against established black-box models.

Number: 1289

Author(s) : KHAN A., BRADSHAW C. R.

Summary

In high temperature gradients regions, vapor compression systems operate at very high-pressure ratios, results in higher discharge temperatures and a reduction in system performance. Economized vapor injection compressors are used to avoid these issues, yet a precise predictive map for various compressor technologies with minimal data and relatively better performance is unclear. This paper establishes a black-box compressor model to accurately predict compressor evaporator mass flow rate, injection mass ratio, and power in compressors with a single vapor injection port. This model is compared against three legacy models from literature and the ANN model, for reference. All five models are evaluated based on their ability to predict the aforementioned metrics. The proposed black-box model can predict the relevant metrics all within 5% Mean Absolute Percentage Error (MAPE). Additionally, a refrigerant sensitivity analysis is performed with the black-box model. The model is trained with data from R410A and used to predict the performance of the same compressor with R454B, and vice versa. The model can predict evaporator mass flow within 3%, power within 2%, and injection mass ratio within 3% MAPE.

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  • Original title: Development of a black-box compressor model that captures vapor-injection compared against established black-box models.
  • Record ID : 30033595
  • Languages: English
  • Subject: Technology
  • Source: 2024 Purdue Conferences. 27th International Compressor Engineering Conference at Purdue.
  • Publication date: 2024/07/18

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