Thermoelastic cooling, Zero GWP, Elastocaloric effect, Thermodynamics, Dynamic model
Traditional vapor compression cooling refrigerants are considered as high global-warming-potential (GWP) gases which face more and more legislation pressure nowadays. As an alternative option other than using synthetic low GWP refrigerants and natural refrigerants, solid-state cooling technologies show their advantages of zero GWP, and therefore recently attract more attentions. Apart from those well-studied solid-state cooling technologies, such as thermoelectric cooling, thermoacoustic cooling and magnetic cooling, thermoelastic cooling, a.k.a. elastocaloric cooling, is still under development and shows potential of better thermal performance compared with its competitors. In fact, from material perspective, it was estimated by literatures that the COPs for elastocaloric materials are 20% - 120% higher than other solid-state cooling materials under the same operating conditions. This study introduces the thermoelastic cooling concept at the beginning, and then demonstrates one method to operate the compression thermoelastic cooling cycle for air-conditioning application based on the reverse Martensitic phase transition principle. A dynamic model is developed to measure the temperature within the cycle in cyclic operation mode. The cyclic operation is a Brayton cycle consisting of an adiabatic Martensite-Austenite phase transition process, a constant strain heat transfer process between the solid-state refrigerant and the heat sink/source, and a heat recovery process aiming to improve the overall performance. The model uses experimental curve-fitted data to predict the work required to drive the cycle. The coefficient of performance (COP) and cooling capacity are then evaluated based on the power prediction. Parametric studies are conducted to investigate the influence of several significant parameters on the COP and cooling capacity from the model. It is found that the cycle duration parameters, the solid state refrigerant thickness, and operating flow rates are major contributing factors to the performance indices. Based on the parametric study results, a design guideline is then provided for the future researches.