In this study, a statistical correlation was established among the input
parameters, namely, ambient temperature (AT), oil injection orifice (OIO) size,
and cooling fan speed with free air delivery (FAD), input power (IP), and
discharge oil temperature (DOT) of an electric-powered twin screw air
compressor. Experiments were designed based on a central composite design (CCD).
A response optimizer is used to identify the combination of input operating
parameter settings that optimizes responses independently and collectively. A
model considering all responses together with equal priorities provides the
maximum FAD of 254.71 cfm and minimum IP of 44.16 kW by setting the compressor
with an AT of 44°C, OIO size of 4.0 mm, and a cooling fan speed of 1220 rpm.
Higher ambient conditions are achieved for experimental purposes by designing a
hot chamber wherein hot air from the cooling fan exhaust is mixed with the
ambient air. Confirmatory tests are conducted to validate the statistical model
proposed in this study. The mean percentage (%) error observed for FAD, IP, and
DOT are 0.29%, 0.48%, and 1.85%, respectively. The results show that the
proposed statistical models are robust and can be used to obtain the performance
characteristics of screw compressors.