Taguchi optimization and analysis of variance for thermoelectric generators with forced convection air cooling

[Display omitted] •Taguchi method and ANOVA are used to analyze a thermoelectric generator (TEG) system.•Two commercial TEGs cooled by forced convection with wind speeds of 2.8–3.7 m·s−1 are studied.•The hot side temperature is the most influential parameter to the output power compared to the heat sink size and the wind speed.•The TEG with the shorter TE leg yields the highest output power overall.•The maximum output powers of the shorter and longer TEG legs are 0.656 W and 0.648 W, respectively. In recent years, humanity has experienced the effects of using unsustainable energy sources that pollute the environment while being inefficient. Most of the primary energy input used in energy conversion processes is lost in the form of heat. Thermoelectric generators (TEGs) have the potential to recover some of this wasted heat; however, their low energy conversion efficiency needs to be addressed. Previous literature has shown effective optimization of thermoelectric generation systems through statistical tools such as the Taguchi method that optimized all the parameters that affect the outcome of the system. To this date, no research has considered wind speed for convection heat transfer as one of the optimizable parameters. This study aims to optimize the operating conditions of commercially available TEGs that are cooled by forced convection simulating naturally occurring wind speeds and operate under low-quality waste heat temperatures to improve the TEG performance further. Two commercially available TEGs are optimized via the Taguchi method. The Taguchi method is implemented with three parameters and three levels, making an L9 orthogonal array. The objective function is the maximum output power. The optimized parameters are the hot side temperature, the heat sink size, and the wind airspeed. Analysis of variance (ANOVA) is used alongside the Taguchi orthogonal array for the statistical analysis of the results. The optimization results show that the hot side temperature is the most influential parameter to the output power. In addition, the change in the heat sink size also significantly influences the output power, whereas the impact of the wind speed is not as significant. In addition, interaction analysis between the parameters is performed. The Taguchi method yields satisfactory optimization results. The optimized system yields 0.65 W of power at 140 °C hot side temperature, Model K402 heat sink, and 3.7 m·s−1 wind speed. The influence of the air velo