Multi-Sensor Data Fusion Prediction Model of Air Inflow Velocity Under Transitional Working Condition of Gasoline Engine

作者：Hou Zhixiang^*; Wei Liang

来源：Sensor Letters, 2011, 9(4): 1477-1481.

DOI：10.1166/sl.2011.1677

• Gasoline Engine
• Multi-Sensor Data Fusion
• Neural Network
• Air Inflow Velocity
• Modeling

A neural network-based multi-sensor data fusion prediction model of air inflow velocity under working condition is proposed and a neural network topology of air inflow velocity prediction under transitional working condition is set in this paper to mitigate the air-fuel ratio control inaccuracy resulting from air flow sensor lag. Simulation is conducted on the basis of HQ495 engine experimental data, which shows that neural network-based multi-sensor data fusion prediction model of air inflow velocity, with better accuracy, excels engine average value model.

• 出版日期2011-8
• 单位长沙理工大学