Global energy crisis due to rapid population increase and industrialization is among the main problems facing the globe. Presently, fossils fuels are the main source of energy for different application. Unfortunately, its pollution nature has compelled policymakers and various stakeholders to impose stringent mitigation regulations to curb carbon emissions. This has led to the development of alternative renewable sources of energy with very low carbon emissions.
Despite being a promising solution, development and utilization of renewable energy sources is currently facing numerous challenges such as underdeveloped energy conversion technologies and cost competitiveness.
Among the available energy conversion technologies, thermoelectric devices have attracted significant attention of researchers because they are generally capable of converting heat into electricity and vice versa. For instance, they have been used in developing thermoelectric generators. To this end, in order to ensure efficient operation of thermoelectric generators, understanding their characteristics and thermoelectric materials properties is highly desirable. Currently, thermoelectric generator modeling is widely used despite the existing challenges that hinder the accurate determination of their performance. For instance, several models: electrical, numerical and analytical have been developed. However, these models face various concerns such as nonlinearity effects that hider their accuracy. As such, researchers have been looking for alternative methods for lowering the cost and optimizing the design of multi-parameter based thermoelectric modules and have thus identified a one-dimensional mathematical thermoelectric generator model as a promising candidate.
To this note, a group of Xi’an Jiaotong University researchers: Dr. Hailong He, Prof. Yi Wu, Weiwei Liu, Prof. Mingzhe Rong, Zhenxuan Fang, and Prof. Xiaojun Tang reported newly developed one-dimensional simulation model. To ensure the accuracy and efficiency of their model, numerical solution methods in MATLAB was used to solve the derived differential equations. Also, the authors took into consideration the effects of various factors such as Seebeck and Peltier effects. Their research work is currently published in the journal, Energy Conversion and Management.
In brief, the research team explored the available thermoelectric generator models and further assessed the feasibility of developing an efficient algorithm for multi-parameter optimization. Analytical and numerical modeling for different components are adopted but coupled to solve regarding their constant or non-linear physical properties. Secondly, they developed the one-dimensional thermoelectric generator model taking into account the temperature and spatial dependent material properties. Additionally, they examined the effects of irreversible factors: heat leakages and contact resistance on the thermoelectric generator characteristics by analyzing the impact mechanism. Eventually, they too developed a hill-climbing algorithm for geometric optimization of thermoelectric generators and analyzed its advantages.
The authors observed a slight deviation in the output power as compared to that previously reported in a three-dimensional model, thus validating the accuracy of the developed model. Consequently, the maximum output power and the heat leakage through the occupied zone exhibited equivalent magnitude order. In addition, the negligible discrepancy was reported regarding the characteristics of the thermoelectric module and output performance. This was attributed to better linearity in the output power. In summary, the Xi’an Jiaotong University-based research team provided essential information that will advance the development of efficient models for enhancing the performance of the thermoelectric generator.
He, H., Wu, Y., Liu, W., Rong, M., Fang, Z., & Tang, X. (2019). Comprehensive modeling for geometric optimization of a thermoelectric generator module. Energy Conversion and Management, 183, 645-659.Go To Energy Conversion and Management