An in-depth study of nonlinear parametric characterization for thermoelectric generator modules. (1st August 2021) - He, Hailong; Fang, Zhenxuan; Niu, Chunping; Wu, Yi; Rong, Mingzhe
Graphical abstract: Highlights: Five typical characterization methods are verified by a common test rig and compared. Irreversible factors hinder the material-level thermoelectric parameters' acquisition. All five methods can characterize the temperature-dependent thermoelectric parameters. Spatial-independence assumption causes the inaccuracy of high-temperature parameters. Quasi steady state characterization method shows the highest accuracy and feasibility. Abstract: Thermoelectric (TE) parameters provide indispensable data for the optimal design, accurate modeling, and performance assessment of off-the-shelf TE modules. However, the lack of unified characterization methods for these nonlinear data creates challenges for the design of large-scale TE systems. This paper aims at a thorough exploration of the accuracy, efficiency, and applicability of five typically reported characterization methods in terms of temperature-dependent material-level TE parameters (Seebeck coefficient, thermal conductivity and electrical resistivity). A common test setup was built and specifically improved for the convenient and high-precision measurement of heat rate. The four methods except for the Buist's modified Harman method can characterize the satisfactory material-level TE parameters only if the thermoelectric generator (TEG)'s irreversible factors are considered including the thermal resistances of substrates and interlaminar contact resistances. The applicability of each method in a large temperature range is discussed by simulation beyond their inherent limits of adopted setups in this paper. Most methods show significant deviations at high temperatures due to their inherent parametric spatial-independence assumptions. From the perspective of their theoretical feasibility and practical accuracy, the quasi steady-state method is more advantageous than others. This research can guide the employment of characterization methods and assist the design and optimization of large-scale TE systems.