Optimization of Operating Parameters of a Scroll Expander Based on Response Surface and NSGA II

Adjusting the operating parameters to optimize the performance of the scroll expander has been a hot research topic among scholars. This paper innovatively combines the response surface method and NSGA۲ algorithm for parameter optimization. This novel method can accurately predict the optimal operating parameters of the scroll expander and improve the overall efficiency of the scroll expander. Initially, a three-dimensional transient simulation model of the scroll expander was established, and the effects of three key operating parameters (suction pressure, exhaust pressure, and rotational speed) on the output power and isentropic efficiency of the scroll expander were analyzed through numerical simulation. On this basis, the response surface model between the input parameters and the objective function  was established by using the response surface methodology. Consequently, three different optimization algorithms  were compared, and it was found that NSGA-II had a better performance both in terms of convergence and solution performance,. Threfore, the NSGA-II algorithm was used for the multi-objective optimization. Under the premise of considering the maximum output power and isentropic efficiency, based on the established response surface model, the Pareto optimal solution was used to determine the optimal combination of its operating parameters: suction pressure of ۱.۶۲ MPa, exhaust pressure of ۰.۴۵ MPa, and rotational speed of ۲,۰۹۹.۵۸ rpm.Finally, the numerical model is verified by the laboratory-built test bed of the Organic Rankine cycle low-temperature waste heat oil-free power generation system. The experimental results match well with the numerical simulation results and verify the model accuracy. The results from this pioneering and thorough thr study will provide a solid benchmark for the development and refinement of upcoming scroll machines.

کلیدواژه ها:

Output Power ، Isentropic efficiency ، Response Surface Methodology ، Multi-Objective Optimization