Multi-Objective Optimization of Plate-Fin Heat Exchangers via Non-Dominated Sequencing Genetic Algorithm (NSGA-II)

The rules of heat transfer and fluid flow in plate-fin heat exchanger are intricate and complex, and the selection of boundary conditions is the key to giving full play to the performance of heat exchanger. In this paper, a multi-objective optimization based on computational fluid dynamics (CFD) and non-dominated sequencing genetic algorithm (NSGA-II) was carried out to obtain the optimal performance of a plate-fin heat exchanger for an extended-range hybrid vehicle engine. The angle of serrated staggered fin, oil flow rate, and water flow rate were taken as input parameters, and the heat transfer quantity, oil pressure drop, and oil outlet temperature were taken as objective functions to perform the optimization analysis of the heat exchanger. Support vector machine regression (SVR) was used to establish the objective function, and the NSGA-II algorithm was adopted to obtain the Pareto optimal solution set. The optimal solution was determined in the Pareto optimal solution set by comprehensive evaluation based on technique for order preference by similarity to an ideal solution (TOPSIS). The results showed that the best comprehensive performance of the heat exchanger was achieved at a fin angle of 63.01°, an oil flow rate of 9.7 L/min, and a water flow rate of 6.45 L/min. At this time, the heat transfer quantity was 9.79 kW, the oil pressure drop was 13.63 kPa, and the oil outlet temperature was 65.11 °C