Thermal Performance Modeling and Calibration of an Improved Cookstove with Integrated Thermal Energy Storage

Abstract

In Nigeria, where access to reliable cooking energy is challenging, improving the efficiency of traditional cookstoves is important for reducing fuel consumption and mitigating environmental impacts. This study was motivated by the need to develop a predictive model for an improved cookstove incorporating thermal energy storage (TES) to enhance thermal performance and extend cooking capability. By integrating experimental data from Water Boiling Tests with computational modeling, this research develops and calibrates a MATLAB-based simulation of heat transfer processes in a multi-layered cookstove design. The model incorporates detailed geometry of combustion chamber, air gap, granite rock TES, and fiberglass insulation layers, implementing energy balance equations to predict temperature profiles, fuel consumption, and efficiency metrics. Calibration against experimental data yielded close alignment, with simulated overall final efficiency of 12.6% compared to experimental 26.3%, boil time of 36.8 minutes compared to experimental boil time of 57.9 minutes, and fuel consumption of 0.905 kg identical to measured values. The energy distribution analysis revealed that about 35% of fuel energy contributed to water heating, about 50% remained stored in TES, while the remainder represented system losses. Comparative analysis with conventional charcoal stoves shows the improved TES design achieves Tier 3 low-power specific consumption (0.023 MJ/min/L), outperforming most conventional stoves in simmering efficiency. These findings demonstrate the model's capability to predict cookstove performance while identifying opportunities for efficiency improvement through design optimization. This research contributes to the development of computational tools for cookstove design optimization, offering a path for enhanced energy efficiency in household cooking applications.