Optimization of Chamber Structure and Ignition of a Rotary Engine Based on the Multi-Population-Subgroup Genetic Algorithm

Abstract

The rotary engine (RE) is characterized by high-speed and a long and narrow combustion chamber. This leads to problems such as uneven distribution of the fuel–air mixture, difficulty in the ignition, and difficulty in rapid propagation of the flame to the trailing side of the combustion chamber, which in turn has an adverse impact on its combustion efficiency. In view of this, this study proposed a multi-population-subgroup genetic algorithm (MPSGA) with a faster convergence rate and more significant optimization based on the multi-population genetic algorithm. The performance of the optimization method was verified by test functions. This method is applied to the comprehensive matching optimization of chamber structure and ignition of the RE to significantly improve the combustion performance. The results showed that compared to the original scheme, the best matching scheme of the chamber structure parameters and ignition parameters of the RE obtained by using the MPSGA increased the explosive pressure by 39.3% and the thermal efficiency by 9.8%.