This paper discusses the development and testing of asingle-speed direct expansion (DX) air coil model to predictcompressor power, heat capacity, coefficient of performance(COP), and supply air temperature and humidity ratio as afunction of airflow rate, air conditions entering the coil, andoutdoor air temperature. The proposed model is calibratedusing a nonlinear regression analysis of online data collectedfrom a typical building automation system, if installed; shortterm data measurements; or manufacturer's data. The modelparameters are determined through nonlinear regressioninstead of traditional methods, with parameters defined atrating conditions. To test the model, experiments wereconducted on a fully instrumented, three-ton DX split-systemair-conditioning unit. The unit ran over the course of severalmonths to get a wide range of operating data. The testingresults showed that the model can accurately capture theperformance of DX air-conditioning system as compared to theexisting EnergyPlus DX model. This proposed model can be apowerful tool used for several intelligent applications such asenergy assessment, fault detection and diagnosis, and systemperformance optimization.