基于UEGO传感器的空燃比自学习控制策略研究  

Air-fuel Ratio Self-learning Control Strategy Based on UEGO Sensor

作　　者：孟武强[1] 甘海云[2] 唐岚[1] 

机构地区：[1]西华大学交通与汽车工程学院,四川成都610039 [2]中国汽车工程研究院有限公司,重庆400039

出　　处：《车用发动机》2010年第6期33-36,41,共5页Vehicle Engine

摘　　要：从传统的开关型氧传感器和宽域氧传感器的物理特性和基本工作原理出发,提出了基于宽域氧传感器的电控增压稀燃CNG发动机的空燃比自学习算法策略,并将所编写的控制代码用于试验发动机上。台架标定试验表明,所设计的算法能够有效补偿发动机出现的磨损、疲劳、老化等状态,可提高实际空燃比的控制精度。Beginning with the physical characteristic and basic working principle of traditional switch-typed exhaust gas oxygen（EGO） sensor and universal exhaust gas oxygen（UEGO） senor,the air-fuel ratio self-learning control strategy of electronic-controlled turbocharged lean-burn CNG engine was put forward based on UEGO sensor.Then the compiled control codes were applied to the testing engine.The result shows that the designed algorithm can compensate for the wear,fatigue and aging state,which can improve the control accuracy of air-fuel ratio.

关 键 词：宽域氧传感器 空燃比 自学习 控制策略 

分 类 号：TP273.22[自动化与计算机技术—检测技术与自动化装置]