TY - GEN
T1 - Heat exchanger structure Optimization of Vehicle thermoelectric Power Generation System Based on RSM and NSGA-II
AU - Wang, Mengyu
AU - Zhang, Tong
AU - Wang, Wei
AU - Li, Gang
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - In recent years, energy shortages have been increasing due to the overuse of fuels. The thermoelectric generator (TEG) system can be used to recycle exhaust gases from driving vehicles. In this study, a novel heat exchanger structure is proposed, which is located in the middle of the whole TEG system, with thermoelectric pieces uniformly distributed on the top and bottom. Based on the developed TEG system, the design parameters (number of ribs located in different regions, distance between ribs and diameter of ribs) and responses (temperature difference at the heat exchanger surface, hot air pressure drop and power generation) were analyzed by the response surface method. Multi-objective optimization of the five design parameters using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) algorithm produces a set of Pareto fronts. The results show that when the number of rib columns is 2, 6, and 7, respectively, the rib column spacing is 55.1 mm, and the rib column diameter is 9.66 mm, the three response variable weight parameters are 0.28, 0.37, and 0.35. Thus, resulting in the optimal TEG system with a heat exchanger temperature difference of 27 K, the pressure drop is 1069.14 Pa, and the power generation is 88.26 W.
AB - In recent years, energy shortages have been increasing due to the overuse of fuels. The thermoelectric generator (TEG) system can be used to recycle exhaust gases from driving vehicles. In this study, a novel heat exchanger structure is proposed, which is located in the middle of the whole TEG system, with thermoelectric pieces uniformly distributed on the top and bottom. Based on the developed TEG system, the design parameters (number of ribs located in different regions, distance between ribs and diameter of ribs) and responses (temperature difference at the heat exchanger surface, hot air pressure drop and power generation) were analyzed by the response surface method. Multi-objective optimization of the five design parameters using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) algorithm produces a set of Pareto fronts. The results show that when the number of rib columns is 2, 6, and 7, respectively, the rib column spacing is 55.1 mm, and the rib column diameter is 9.66 mm, the three response variable weight parameters are 0.28, 0.37, and 0.35. Thus, resulting in the optimal TEG system with a heat exchanger temperature difference of 27 K, the pressure drop is 1069.14 Pa, and the power generation is 88.26 W.
KW - genetic algorithm
KW - heat exchanger
KW - thermoelectric power generation system
UR - https://www.scopus.com/pages/publications/105031137921
U2 - 10.1109/ICEEPS66790.2025.11239625
DO - 10.1109/ICEEPS66790.2025.11239625
M3 - Conference contribution
AN - SCOPUS:105031137921
T3 - 2025 4th International Conference on Energy and Electrical Power Systems, ICEEPS 2025
SP - 867
EP - 871
BT - 2025 4th International Conference on Energy and Electrical Power Systems, ICEEPS 2025
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th International Conference on Energy and Electrical Power Systems, ICEEPS 2025
Y2 - 17 July 2025 through 19 July 2025
ER -