Date: April 30, 2016

This project implemented, validated and documented an automated system for training virtual refrigerant charge sensors for rooftop unit ACs. The system automatically tunes empirical parameters of a virtual sensor for estimating the amount of refrigerant in a system. The engineering time and costs associated with calibrating a virtual sensor are reduced because of the automated testing in an open laboratory and the reduced number of tests.