AI Summary & Key Takeaways
AI InsightThe results demonstrate rapid convergence in single-stage nonlinear iterations and stable long-term convergence in multi-cycle iterative simulations.
📌 3 Key Takeaways
Abstract
Accurate prediction of thermoelectric generator performance requires reliable estimation of coupled thermal–electrical fields and effective control of numerical and measurement errors. In this work, an iterative error analysis method is developed and applied to a Bi₂Te₃ based thermoelectric generator by using COMSOL Multiphysics. The proposed approach systematically updates temperature and electrical fields through segregated and conjugate gradient solvers to minimize discrepancies arising from temperature-dependent material properties, junction effects, and multiphysics coupling. Detailed modeling of heat transfer and electric current transport, including Seebeck and Peltier effects, is performed by using realistic geometric dimensions and material parameters. The results demonstrate rapid convergence in single-stage nonlinear iterations and stable long-term convergence in multi-cycle iterative simulations. Heat transfer errors are reduced from the order of 10-1.8 to 10-4.4, while electric current and potential errors decrease from approximately 10-0.1 to 10-3.9. Multistage conjugate gradient analysis further confirms the robustness of the method under strong nonlinear coupling conditions. The proposed iterative error analysis framework significantly improves numerical stability, accuracy of internal temperature estimation, and prediction of voltage, current, and efficiency. This study establishes iterative error correction as a powerful and computationally efficient strategy for reliable thermoelectric generator modeling and optimization.
Özet
Accurate prediction of thermoelectric generator performance requires reliable estimation of coupled thermal–electrical fields and effective control of numerical and measurement errors. In this work, an iterative error analysis method is developed and applied to a Bi₂Te₃ based thermoelectric generator by using COMSOL Multiphysics. The proposed approach systematically updates temperature and electrical fields through segregated and conjugate gradient solvers to minimize discrepancies arising from temperature-dependent material properties, junction effects, and multiphysics coupling. Detailed modeling of heat transfer and electric current transport, including Seebeck and Peltier effects, is performed by using realistic geometric dimensions and material parameters. The results demonstrate rapid convergence in single-stage nonlinear iterations and stable long-term convergence in multi-cycle iterative simulations. Heat transfer errors are reduced from the order of 10-1.8 to 10-4.4, while electric current and potential errors decrease from approximately 10-0.1 to 10-3.9. Multistage conjugate gradient analysis further confirms the robustness of the method under strong nonlinear coupling conditions. The proposed iterative error analysis framework significantly improves numerical stability, accuracy of internal temperature estimation, and prediction of voltage, current, and efficiency. This study establishes iterative error correction as a powerful and computationally efficient strategy for reliable thermoelectric generator modeling and optimization.