Optimization of single phase microchannel heat exchanger in electric vehicle

Abstract

Finding the optimal shape and dimensions for a microchannel can improve the efficiency of the microchannel heat exchanger so that the heat transfer coefficient is maximized while the pressure drop across the channel is minimized. Computational Fluid Dynamics (CFD), Response Surface Methodology (RSM), and Multi-Objective Genetic Algorithm (MOGA) were used to optimize the microchannel heat exchanger. In this process optimization, the input variable consisted of three geometric parameters for the rectangular microchannel, two geometric parameters for the re-entrant microchannel while output objectives include maximizing the heat transfer coefficient, h, and minimizing the pressure drop, Pdrop at Reynolds numbers from 100 to 2300. By using Central Composite Design (CCD) for each Reynolds number, 15 design points were initially generated and RSM was then used to generate models to approximate the parameters’ relation to the objective by using the second-order polynomial. Different manifold shapes are investigated to study the changes in the heat exchanger performance. In addition, sinusoidal wave microchannels with different periods and amplitudes for a specific length was studied and optimized as well.