摘要
汽车废气氧(EGO)传感器模型是实现发动机空燃比闭环控制的关键技术之一。传统采用的继电器模型,存在一定的不足。采用实验建模的方法,建立了过量空气系数、温度与输出电压之间的软测量模型。利用三段和法对模型参数进行初步估计,得到参数的粗略值,然后利用粒子群优化算法,寻找最优参数,并对所得结果进行检验。仿真结果表明:该软测量模型结构简单,预测精度高,可以用于空燃比闭环控制系统的仿真研究。
The model of automotive exhaust gas oxygen sensor is one of the key technologies in the engine air-fuel ratio control system.There exists some deficiencies of the traditional relay model.Adopting a modeling method with tests,a soft sensor model was built between excessive air coefficient,temperature and output voltage.Rough estimation of the parameters were conducted with three-sum methods,and the optimum parameters were found by particle swarm optimization algorithm（PSO）.And the verification of the model was showed with experimental data.The simulation results show that the model of the sensor has the advantage of simple structure and higher predictive accuracy.It can be used in simulation research of the engine air-fuel ratio control system.
出处
《仪表技术与传感器》
CSCD
北大核心
2013年第6期124-127,共4页
Instrument Technique and Sensor
基金
国家自然科学基金资助项目(601143005
61273069)
福建省产学研重大项目(2011H6019)
关键词
废气氧传感器
软测量模型
粒子群算法
exhaust gas oxygen sensors
soft sensor model
particle swarm optimization algorithm
