Model-based estimation of cold room temperatures in a supermarket refrigeration system

Food quality and energy consumption are important parameters for supermarket cold-room operations. Monitoring of status and data from supermarket energy and control systems provides a means for fault detection and diagnostics of these systems. However, data collection limitations with sensors, network bandwidth, and controller memory reduce the effectiveness and stability of these monitoring tools. This paper describes a model-based estimator for cold room temperatures in supermarket energy systems, an important measure of the quality of refrigerated goods. The estimator is created with limited on-line monitored data from a supermarket control system and a thermodynamic model of a cold room using a System Identification Method and Extended Kalman Filter. Estimated parameters are used for on-line prognostics. We present the methodology and approach for the estimator. We then present an example application in which a low temperature freezer cold room was modeled with field data.