Simulation and characterization of indium gallium arsenide thermophotovoltaic cell for harvesting waste heat with different spectral irradiances

• Main Author: Mansur Mohammed Ali Gamel
• Format: text::Thesis
• Language: English
• Published: 2023
• Subjects: SIMULATION AND CHARACTERIZATION OF INDIUM GALLIUM ARSENIDE THERMOPHOTOVOLTAIC CELL

Thermophotovoltaic (TPV) converts thermal energy from fuel combustion, waste heat, or nuclear energy into electricity. Indium gallium arsenide (In0.53Ga0.47As) semiconductor material is considered to be suitable for large scale TPV production due to its high crystal quality, physical properties, lattice-matched to InP substrate and mature fabrication method. The optimization of TPV cell efficiency is essential since it leads to a significant increase in the output power. The reported efficiencies of In0.53Ga0.47As TPV cell mostly remain < 15% since minimum optimization works were conducted. Typically, the optimization of In0.53Ga0.47As TPV cell has been limited to a single-variable such as the emitter thickness, while the effects of the variation in other design variables are assumed to be negligible. Furthermore, minimal effort has been made in characterizing the output performances of In0.53Ga0.47As TPV cell under various radiation’s spectrums. Therefore, this work aims to characterize and optimize the In0.53Ga0.47As TPV structure under different waste heat temperatures ranging from 800 to 2000 K. TCAD Silvaco software was used to simulate the output performance of the TPV cell. The simulation results were validated with the reported experimental results. The materials parameters of In0.53Ga0.47As and InP were studied and determined, and the simulation results were successfully correlated to the absorption coefficients of the materials. A comprehensive study was then carried out, with 8000 simulations and model executions, to optimize and characterize the In0.53Ga0.47As TPV cell under various spectral’s irradiances. Single-variable optimization is defined as changing one design variable (thicknesses and doping concentrations) of the cap, front surface field, emitter, base, back surface field and buffer layers. It enables the identification of the non-dominant variables in In0.53Ga0.47As TPV structure and to identify the boundaries and performance trend for each variable. However, In0.53Ga0.47As cell performance depends collectively on all the design variables, and a more heuristic optimization that considers the effect of all important variables for the In0.53Ga0.47As TPV cell is necessary to achieve the optimum cell efficiency. Therefore, multi-variable optimization was carried out using real coded genetic algorithm (RCGA) for different radiation temperatures from 800 to 2000 K. It was found that the efficiency of the TPV cell increased by an average of 13% as compared to the reference structure. The maximum increase in efficiency was reported at 1200 K, with efficiency increased from 8.42% to 22.99%. While the minimum increase in efficiency was reported at 2000 K, with efficiency increased from 9.92% to 19.81%. In addition, this work demonstrated that the In0.53Ga0.47As TPV cell efficiency increases with increasing illumination intensity for blackbody temperatures lower than 1400 K. For example, at 1000 K the efficiency increased from 19.6% to 22.9% when the illumination intensity increased from 0.0378 W/cm2 to 0.3780 W/cm2 This project contributes to the understanding of illumination intensity effect on the performance of In0.53Ga0.47As TPV cell as well as to provide useful guidelines to fabricate high-performance In0.53Ga0.47As TPV cell for various waste heat temperatures.