A new thermal management figure of merit for design of thermal energy storage with phase change materials

Abstract

Phase Change Materials (PCMs) are frequently employed in thermal management of systems with high heat fluxes because their high latent heat of phase change limits transient temperature rises and damps temperature fluctuations. In general, detailed numerical analysis is used to design such systems. However, for an efficient thermal design process, it is desirable to have an analytic method to perform a quick quantitative comparison between all the available PCMs considering potential design configurations. The previously developed Figure of Merit (FoMc) for PCMs only depends on the thermophysical properties of the PCM and does not account for other relevant information such as geometry, melting temperature, and boundary condition. In the present work, we develop a novel performance factor (f) that works in conjunction with the material property based FoM to gauge the performance of different PCM-based thermal management systems (TMSs). The performance factor f is based on the characteristic timescales for thermal diffusion and thermal storage in a PCM system. First, this work demonstrates the range of applicability of our new FoM (fFoMc) for various PCMs (3 metallic, 4 organic, and 3 inorganic materials) across different geometrical and boundary configurations. The PCM performance is evaluated using transient numerical simulations with the metric of the maximum temperature rise in the domain after a fixed heating time. For a single PCM in different geometries, the maximum temperature rise decreases with increased f. For a general PCM-based TMS (i.e., a random combination of PCM, geometry, and boundary condition), the maximum temperature rise generally decreases with increasing the newly proposed FoM (fFoMc). Second, we extend the analysis to a composite PCM (an aluminum foam impregnated with organic PCM) to estimate the optimum porosity (ϕopt) for different geometric configurations. The analytically estimated ϕopt agrees well with the values calculated from optimizing detailed finite element simulations. Furthermore, this approach can explain the effect of expected duration of the PCM use on the ϕopt value using the proposed FoM. Overall, the proposed approach can identify the best performing geometrical configuration for a certain PCM or shortlist best performing PCM for a given setup of PCM-based TMS without detailed numerical simulations, making the design process more efficient.