基于遗传算法的温差发电系统模块布局优化设计

Optimization design of thermoelectric system module layout based on genetic algorithm

温差发电在航空航天等极端环境供电和汽车余热利用等领域具有重要的应用,然而低的热电转换效率严重限制了其发展。目前主要从提高材料本身性能和优化热电模块结构两方面提升性能。本文从整体出发,建立了基于遗传算法的温差发电系统模块布局优化设计方法。融合已有的解析模型,发展了能够快速获得系统电输出功率的性能评估方法;通过遗传算法,以废热气体的热电转换为例,实现了温差发电系统热电模块的布局(数量与位置)设计;讨论了废热气体流动速度和温度的影响规律。研究表明,相比于全覆盖热电模块设计方案,优化的布局方案以更少的热电模块获得了更高的电输出功率,从而证实并非布置的热电模块越多越好,存在最优的热电模块数量和位置。该研究为提升温差发电系统输出功率提供了一种可能的途径。

Thermoelectric generation has important potential applications such as power supply in extreme aerospace environment, waste heat utilization in automobile and others.However, their wide scale applications have been hindered due to low its thermal-to-electrical conversion efficiency.At present, the performance improvement is mainly made from two aspects: improving the material performance and optimizing the thermoelectric module structure.In this paper, a method of module layout optimization of a thermoelectric generator based on a genetic algorithm is proposed.By combining the existing analytical models, a performance evaluation method which can quickly obtain the electricity generation of the system is developed.Through the genetic algorithm, the thermal-to-electrical conversion of waste heat gas is taken as an example to realize the layout(number and location) design of the modules in the thermoelectric generator.The influence of waste heat gas flow velocity and temperature is discussed.Comparing with the fully covered thermoelectric module layout design, the optimized design achieves a higher electric power with fewer thermoelectric modules, which proves that including too many thermoelectric modules can have a negative effect, and that there is an optimal number and location of thermoelectric modules.This study provides a possible way to improve the electric output power in thermoelectric generation.