The Research And Design Of Air Fuel Ratio Self-Learning Control Strategy Of CNG Engine Based On UEGO Sensor

In the Electronic Control Fuel Injection(EFI) system of engine, it often adopts the strategy that uses the Exhaust Gas Oxygen(EGO) sensor installed on exhaust pipe to obtain the feedback information of oxygen content in exhaust gas, which could improve efficiency of the Three-Way-Catalytic converter(TWC) cleaning the exhaust gas and meet the ever-stringent emission regulations. And then it implements closed-loop correction to fuel injection pulse so as to keep the practical Air Fuel(A/F) ratio close to stoichiometric A/F ratio, this is the so called"A/F ratio Closed-Loop Control". Meanwhile, when the vehicle is running with engine working for much long time, the air and fuel supplying system may encounter wearing, tiring and aging, which is also likely to result in practical A/F ratio deviating too much relative to stoichiometric A/F ratio.In view of this, the traditional engine control strategy is to combine a A/F ratio Self-learning control(also called BLM) algorithm based on switch-type EGO sensor with Closed-loop PI adjustment which is used to compensate the fuel pluse width(PW) in order to meet the requirement of precise control with A/F ratio. However, since the measuring range of the traditional EGO sensor is small and its output signal possess switching characteristics, in the process of ECU controlling the A/F ratio, it just increases or reduces the PW step by step based on EGO sensor's output signal and untill reaches the stoichiometric A/F ratio at the end. The A/F ratio control process is slow when used traditional EGO sensor, and it neither optimizes the transient response of the engine nor further improves emission of the engine. When it comes to turbocharging CNG engine, the common switch type oxygen sensor is unable to meet the requirements of large range A/F ratio closed loop control. Consequently, this paper applies BLM control algorithm that is based on the Universal Exhaust Gas Oxygen(UEGO) sensor to the tested turbocharged lean-burn CNG engine. Because the UEGO sensor could provide more accurate A/F ratio feedback signal of different mixture conditions to engine ECU, therefore the BLM control algorithm that is designed based on UEGO sensor could compensate such as wearing,aging which resulted in a large excursion of A/F ratio.This paper's research work is a part of the project "Special Equipment's Key Technology Development of Alternative Fuel Vehicle". It is one of National High-tech Research and Development Plans (863 plans). In this project used CY4102 turbocharged intercooling Diesel engine(a production of DongFeng CHAOYANG diesel company) as the prototype, and launched electronic controlled CNG engine theory and critical technical research work. This paper researched and designed A/F ratio BLM control algorithm which was on the basis of the former developed A/F ratio closed-loop control system of turbocharged lean- burn CNG engine.combing closed-loop control with BLM control working together, it could implement much more accurater A/F ratio control, and further improves the emissions and economic performance of the electronic controlled CNG engine.