Heating, refrigeration, and air conditioning systems account for 7.8% of global greenhouse gas emissions and 20% of global electricity consumption. Moreover, the demand for air conditioning is expected to triple by 2050. Magnetocaloric technology has emerged as a promising alternative, with the potential to eliminate the use of volatile fluids and reduce energy consumption. This study presents the design strategies, experimental evaluation, and key insights from the development and operation of a pilot-scale magnetocaloric air conditioner. The system was designed and optimized using Artificial Neural Networks and Genetic Algorithms, and incorporates a rotor-stator magnetic circuit, La(Fe,Mn,Si)13Hz refrigerants, and tube-fin heat exchangers. Three prototype generations were designed and commissioned, each incorporating modifications based on operational constraints. The performance evaluation highlights this prototype as achieving one of the highest cooling capacities and temperature spans reported in the literature. Also, it is the only system reported to successfully refrigerate a cold room without emulating the thermal load using heaters. The first-generation prototype delivered the best performance, achieving the required temperature spans for air conditioning (22–35 °C), although its cooling power was limited to a peak of 480 W. These results show the progress made and the obstacles that still need to be overcome to advance this technology.
Peixer et al. (Sun,) studied this question.