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<p>The operational parameters of an electrically powered compressor in an air-conditioning (AC) system for an electric vehicle affect its performance. The efficacy of the AC system was optimized by incorporating SiO<sub>2</sub>/POE nanolubricants using the response surface method (RSM). The quadratic models in RSM successfully identified notable associations between the input variables and the outcomes. The optimization of parameter values in the experiment was achieved using the desirability approach with a face-centered design. The findings indicated that optimal operational parameters could result in enhanced heat absorb, reduced compressor workload, lower discharge temperature from the expansion valve, and lower power consumption. The optimal values regarding expansion valve discharge temperature, heat absorb, power consumption, and compressor operation were found to be 10.28&#xa0;°C, 19.91&#xa0;kJ&#xa0;kg<sup>−1</sup>, 116.66 W, and 5.34&#xa0;kJ&#xa0;kg<sup>−1</sup>, respectively. The most effective operating conditions for the compressor were determined to be 1808&#xa0;rpm, an initial refrigerant charge of 160&#xa0;g, and a volume concentration of 0.013%. These parameters resulted in the highest desirability score of 0.941. The operational parameters were predicted and validated through a test run under optimal conditions. The results demonstrated substantial concordance between the predicted and validated values.</p>

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Response surface method optimization of SiO2/POE nanolubricant performance for electrically powered compressor of air-conditioning system

  • 期刊论文

  • 发表日期：

    2026年8月5日

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  • A. H. Hamisa,
  • W. H. Azmi,
  • N. N. M. Zawawi,
  • Hafiz Muhammad Ali

摘要

The operational parameters of an electrically powered compressor in an air-conditioning (AC) system for an electric vehicle affect its performance. The efficacy of the AC system was optimized by incorporating SiO2/POE nanolubricants using the response surface method (RSM). The quadratic models in RSM successfully identified notable associations between the input variables and the outcomes. The optimization of parameter values in the experiment was achieved using the desirability approach with a face-centered design. The findings indicated that optimal operational parameters could result in enhanced heat absorb, reduced compressor workload, lower discharge temperature from the expansion valve, and lower power consumption. The optimal values regarding expansion valve discharge temperature, heat absorb, power consumption, and compressor operation were found to be 10.28 °C, 19.91 kJ kg−1, 116.66 W, and 5.34 kJ kg−1, respectively. The most effective operating conditions for the compressor were determined to be 1808 rpm, an initial refrigerant charge of 160 g, and a volume concentration of 0.013%. These parameters resulted in the highest desirability score of 0.941. The operational parameters were predicted and validated through a test run under optimal conditions. The results demonstrated substantial concordance between the predicted and validated values.