Estimation of Thermal Properties of Solid–Liquid Phase Change Material Using Fuzzy Inference Methods

Abstract

The accurate measurement of thermal properties in phase change materials holds significant importance for engineering applications. This research introduces fuzzy inference methods to estimate the thermal properties of phase change materials. The solution to the coupled heat transfer involving radiation and conduction in material is achieved through a hybrid approach, which combines the finite volume method with the discrete ordinate method. The estimation process is structured as an inverse problem, where the temperature on the material surface acts as the measurement signal for conducting the inverse analysis. Both the fuzzy inference method and the decentralized fuzzy inference method are utilized to address the inverse heat transfer problem. This enables the determination of latent heat and thermal conductivities for both solid and liquid regions within the phase change material. Retrieval results demonstrate that the thermal properties of phase change materials can be accurately estimated using fuzzy inference methods. While both two fuzzy inference methods perform similarly in estimating a single parameter, the fuzzy inference method has limitations in multiparameter estimation tasks. Conversely, the decentralized fuzzy inference method yields accurate results in simultaneous estimation problems. Furthermore, this method proves robust in estimating the thermal properties of phase change materials, even in the presence of noisy data.