内燃机工程2025，Vol.46Issue(5)：69-75,7.DOI:10.13949/j.cnki.nrjgc.2025.05.008
基于NARX神经网络的瞬态虚拟排温传感器
A Transient Virtual Exhaust Temperature Sensor Based on NARX Neural Network
摘要
Abstract
Based on the data collected by test bench,a diesel engine exhaust temperature computational model with transient characteristics was established by using nonlinear autoregressive model with exogenous input(NARX)neural network as a virtual sensor,and the model was trained by batch training method.The results were compared with the feedforward neural network,long short term memory(LSTM)neural network and the collected results of the exhaust temperature sensor of production engine.The results show that both neural networks can achieve high precision under steady states.Under the European transient cycle(ETC),the maximum deviation of the NARX neural network computation temperature was 6.6℃,and the maximum temperature deviation measured by the production engine exhaust temperature sensor was 45.9℃.The computation time required for the NARX neural network was approximately 2.5 times that of the exhaust temperature model in the existing electronic control unit(ECU).关键词
外部输入非线性自回归模型/神经网络/瞬态/柴油机/排气温度/虚拟传感器Key words
nonlinear autoregressive model with exogenous input(NARX)/neural network/transient/diesel engine/exhaust temperature/virtual sensor分类
能源科技引用本文复制引用
周圣凯,寇传富,叶宇,杜宇,戴振朝,陈美玲..基于NARX神经网络的瞬态虚拟排温传感器[J].内燃机工程,2025,46(5):69-75,7.基金项目
广西科技重大专项项目(AA23062041) Guangxi Science and Technology Major Program(AA23062041) （AA23062041）
