吉林大学学报(工学版) ›› 2025, Vol. 55 ›› Issue (6): 1854-1861.doi: 10.13229/j.cnki.jdxbgxb.20240829

• 车辆工程·机械工程 • 上一篇    下一篇

基于高斯过程回归进气量预测的空燃比控制

赵靖华1,2(),刘妲1,周宇麒1,闻龙1,刘倩妤1,刘捷3,解方喜2()   

  1. 1.吉林师范大学 数学与计算机学院,吉林 四平 136000
    2.吉林大学 汽车仿真与控制国家重点实验室,长春 130022
    3.吉林交通职业技术学院 交通信息学院,长春 130012
  • 收稿日期:2024-07-23 出版日期:2025-06-01 发布日期:2025-07-23
  • 通讯作者: 解方喜 E-mail:zhaojh08@mails.jlu.edu.cn;xiefx@jlu.edu.cn
  • 作者简介:赵靖华(1980-),男,教授,博士.研究方向:先进控制理论应用.E-mail:zhaojh08@mails.jlu.edu.cn
  • 基金资助:
    吉林省科技厅项目(20240601034RC);吉林省教育厅项目(JJKH20241144KJ)

Air⁃fuel ratio control of engines based on Gaussian process regression intake prediction

Jing-hua ZHAO1,2(),Da LIU1,Yu-qi ZHOU1,Long WEN1,Qian-yu LIU1,Jie LIU3,Fang-xi XIE2()   

  1. 1.Mathematics and Computer College,Jilin Normal University,Siping 136000,China
    2.State Key Laboratory of Automotive Simulation and Control,Jilin University,Changchun 130022,China
    3.Transportation Information College,Jilin Communications Polytechnic,Changchun 130012,China
  • Received:2024-07-23 Online:2025-06-01 Published:2025-07-23
  • Contact: Fang-xi XIE E-mail:zhaojh08@mails.jlu.edu.cn;xiefx@jlu.edu.cn

摘要:

针对传统基于模型预测技术对于进气量的连续变化以及随机性分析不足的问题,提出了一种基于高斯过程回归(GPR)进气量预测的空燃比反馈控制方法。仿真分析结果表明:相比于进气量传感器实时反馈控制方法,两种发动机瞬态工况下本文控制方法的lambda平均误差分别降低了12%和29%,有效提高了空燃比的控制精度,同时又具有较强的抗干扰性。

关键词: 高斯过程回归, 实时反馈控制, 进气量预测, 空燃比控制

Abstract:

To address the problem of insufficient analysis of continuous changes and randomness in traditional model-based prediction techniques, a engine air-fuel ratio feedback control method based on Gaussian Process Regression (GPR) intake quantity prediction is proposed. The simulation analysis results show that compared with the real-time feedback control method of the intake air sensor, the lambda average error of the control method proposed in this paper is reduced by 12% and 29% respectively under the transient operating conditions of the two engines, effectively improving the control accuracy of the air-fuel ratio, while also having strong anti-interference ability.

Key words: Gaussian process regression, real-time feedback control, intake prediction, air-fuel ratio control

中图分类号: 

  • TP273

表1

发动机模型参数"

参数数值
发动机气缸数/个4
发动机总排量/L1.998
额定转速/(r·min-15 000
最大净功率/(kW·r·min-172/6 000
进气歧管体积/L2

图1

发动机模型验证结果"

图2

进气量传感器实时PID反馈控制框图"

图3

GPR进气量预测流程图"

图4

瞬态工况进气量预测效果"

图5

基于GPR进气量预测的空燃比反馈控制框图"

图6

200 s瞬时工况条件下两种方法的对比结果"

图7

800 s瞬时工况条件下两种方法的对比结果"

表2

两种瞬态工况下进气量预测及lambda控制效果"

方法200 s瞬态工况800 s瞬态工况平均值
GPR进气量预测MAE/(kg·h-133.1438.6535.890
lambda控制平均误差/(kg·h-1PID反馈0.0590.0610.060
GPR反馈0.0520.0430.048
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