A Hybrid Taguchi-Regression Algorithm for a Fuel Injection Control System

Abstract

The fuel injection system is one of the key components of an in-cylinder direct injection engine. Its performance directly affects the economy, power and emission of the engine. Previous research found that the Taguchi method can be used to optimize the fuel injection map and operation parameters of the injection system. The electronic control injector was able to steadily control the operation performance of a high-pressure fuel injection system, but its control was not accurate enough. This paper conducts an experimental analysis for the fuel injection quantity of DI injectors using the Taguchi-Regression approach, and provides a decision-making analysis to improve the design of electronic elements for the driving circuit. In order to develop a more stable and energy-saving driver, a functional experiment was carried out. The hybrid Taguchi-regression algorithm for injection quantity of a direct injection injector was examined to verify the feasibility of the proposed algorithm. This paper also introduces the development of a high-pressure fuel injection system and provides a new theoretical basis for optimizing the performance of an in-cylinder gasoline direct injection engine. Finally, a simulation study for the fuel injection control system was carried out under the environment of MATLAB/Simulink to validate the theoretical concepts.