Common rail injection system on-line parameter calibration for precise injection quantity control

Abstract

This paper presents an iterative learning control (ILC)-based method to on-line calibrate the high-pressure common-rail (HPCR) injection system parameters for achieving precise injection quantity control for Diesel engines. Given the strongly increasing demands on engine fuel economy and emissions, precise injection quantity control is of importance for realizing desired combustion, particularly advanced combustion modes, on a cycle-by-cycle basis. Current Diesel engine injection quantity control methods heavily rely on pre-calibrated static tables or injector models, which cannot handle the effects of the rail pressure sensor reading inaccuracy and injector aging on injection quantity. In this paper, by using an exhaust manifold oxygen fraction model, an ILC-based HPCR injection system parameter on-line adaptation algorithm was developed to actively adjust the injection duration command for injection quantity correction. Simulation results based on a high-fidelity GT-Power engine model show the effectiveness of the designed injection quantity correction algorithm.