Performance Optimization of Hydrogen Fueled Engines Based on Genetic Information Fusion Algorithm

Abstract

According to the research status of hydrogen fuel engine and the theory of information fusion algorithm, this paper proposes a hydrogen engine optimization model based on information fusion algorithm. Firstly, the genetic neural network information fusion model is constructed, and then the economic and dynamic characteristics of the hydrogen engine are optimized on the MATLAB experimental platform by using the model. Finally, the experimental results are analyzed and reasonable suggestions are put forward. Experimental results show that the method is feasible and accurate.