同济大学学报（自然科学版）2023，Vol.51Issue(12)：1949-1958,10.DOI:10.11908/j.issn.0253-374x.22133
并联式混合动力发动机神经网络法转矩预测与闭环控制
Torque Estimation and Closed-Loop Control of Parallel Hybrid Engine Using ANN Method
摘要
Abstract
In this paper,a joint simulation model of GT-suite and MATLAB/Simulink was constructed by using the calibration data of the actual engine and a collaborative control module for estimated torque feedback based on intake air and engine state parameters was established.A comparison was made between the estimation results errors of the ANN method and the Map method for estimating the steady state,transient torque variation,upshift and downshift of the engine.The results show that the Map method is more reliable under steady-state conditions,and the error of ANN method is small at low,medium,and high engine speeds,with errors of 1.31%,1.09%,and 1.52%lower than the ANN method,and the error of the ANN method is 5.62%and 1.32%lower than that of the Map method under torque transient conditions,and 1.93%and 0.84%lower than that of the Map method under lifting conditions.关键词
混合动力/转矩预测/神经网络(ANN)法/Matlab/Simulink软件/GT-Suite/联合仿真Key words
hybrid engine/torque estimation/artificial neural network(ANN)/Matlab/Simulink/GT-Suite/joint simulation分类
交通工程引用本文复制引用
楼狄明,唐远贽,房亮,施雅风,张允华,仇杰,杨芾..并联式混合动力发动机神经网络法转矩预测与闭环控制[J].同济大学学报（自然科学版）,2023,51(12):1949-1958,10.基金项目
"十四五"国家重点研发计划(2021YFB2500800) （2021YFB2500800）
