Abstract
Based on Bi2Te3 thermoelectric modules, a kind of automobile exhaust thermoelectric generator (AETEG) with a single-column cold-source structure was designed. To enhance its net power and efficiency, the output performance of all the thermoelectric modules was tested with a temperature monitoring unit and voltage monitoring unit, and modeled using a back-propagation (BP) neural network based on various hot-source temperatures, cold-source temperatures, load currents, and contact pressures according to the temperature distribution of the designed heat exchanger and cooling system. Then, their electric topology (series or parallel hybrid) was optimized using a genetic algorithm to achieve the maximum peak power of the AETEG. From the experimental results, compared with when all the thermoelectric modules were connected only in series or parallel at random, it is concluded that the AETEG performance is evidently affected by the electric topology of all the single thermoelectric modules. The optimized AETEG output power is greatly superior to the other two investigated designs, validating the proposed optimized electric topology as both feasible and practical.
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