New optimal sizing and accelerated testing to reliably and cost-effectively improve and predict freezer energy performance

Abstract

Challenges in terms of developing increasingly efficient systems for cooling and freezing agricultural or pharmaceutical products, are intensifying due to the requirements related to preserving the quality and quantity of products during their storage, transport and distribution on the one hand. And on the other hand, due to the constraints related to the optimal design of systems for producing and maintaining cold, in quantity, over time, regulated, environmentally friendly and cost-effective. Therefore, the major contribution in this work is based on the optimization of the energy performance of cooling and freezing systems, like freezers. To do this, the proposed methodology consists first of establishing a thermal balance of the freezer studied, in order to determine the overall heat transfer coefficients of the walls of the freezer cabin. Then, the formalism combining both the Cobb Douglas type utility function and the Lagrange equation resolution method is used to maximize the heat transfer coefficients of the walls that constitute the freezer compartment. A 99-liter freezer of the RCF-120-B brand is used for the study and data collection under the manufacturer's operating conditions (T in = −19 °C and T ex = 30.4 °C). In addition, to analyze and predict the operating reliability of the freezer, we rely on an accelerated Weibull and Vaca-trigo test model which uses 5 samples of 335 measured values (5 * 335) respectively of internal and external temperatures (T in and T ex ), internal and external relative humidity (RH in and RH ex ), and each time interval (Δt). In addition, the evaluation of the reliability of maintaining the refrigerating capacity when the freezer is stopped is based on a Brownian model which uses the reliability results of Weibull and Vaca-trigo, as well as the 3 samples of 347 measured values (3 * 347) respectively of internal and external temperatures, and each time interval. It appears that the maximum values of the pairs of heat transfer coefficients obtained for the walls of the 99 liter, 200 liter and 282 liter compartments are respectively the following: (K 199max = 0.459 W/m 2 K and K 299max = 1.23 W/m 2 K), (K 1200max = 0.641 W/m 2 K and K 2200max = 1.243 W/m 2 K) and (K 1282max = 0.97 W/m 2 K and K 2282max = 0.9832 W/m 2 K). These maximum values allow the 110 W compressor to be used instead of the 125 W and 200 W compressors respectively in the 200 liter and 282 liter compartments of conventional freezers. The accelerated test simulations show that, unlike the 282-liter freezer which operates for 63 min at 110 W to reach the standard temperature level, the 200-liter freezer at 110 W operates for about 44 min before reaching the standard temperature of −19 °C. However, the 282-liter freezer at 110 W has more advantages, including an optimal volume for preserving products and an effective autonomy of 103 min for maintaining cold in its cabin, compared to 58 min for maintaining cold in the 200-liter cabin. Therefore, the proposed strategy for the optimal design of freezers offers better performance in terms of good autonomy for maintaining cold in the cabin, good volume for storing and transporting products, and a better reduction in electrical energy consumption. • Designs and sizes efficient refrigeration and freezing systems. • Uses thermal balance and Lagrange method with Cobb Douglas utility function. • Optimizes wall heat transfer to reduce freezer energy consumption. • Predicts cooling reliability via Weibull, Vaca Trigo, and Brownian models. • Supports freezer design optimized for photovoltaic energy sources.