Thomas Ganser

Data fusing for optimization of spark ignition engine control

In order to minimize exhaust emissions, modern spark ignition engines have a 3 way-catalyst and an electronically controlled fuel injection. To achieve a high efficiency of the catalyst the air-fuel-ratio must be exactly controlled at all operation conditions of the engine. The electronic fuel injection is often controlled by calculating the amount of fuel to be injected from the estimated air mass in the cylinder. This paper presents a method of data fusing in which all sensor signals that have a relationship to the mass of air in the cylinder are combined using an extended Kalman filter. The use of the redundant information contained in the different sensor signals (throttle air flow, throttle angle, manifold absolute pressure) results in a precise, reliable, and sensor fault tolerant operation of the outcoming algorithm. The use of a manifold pulsation disturbance model results in less phase error in the estimated air mass. Without disturbance model, the phase error increases up to 90 degrees crank angle particularly at high engine speeds and loads.