Journal of Jilin University(Engineering and Technology Edition) ›› 2025, Vol. 55 ›› Issue (6): 1854-1861.doi: 10.13229/j.cnki.jdxbgxb.20240829

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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

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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

CLC Number: 

  • TP273

Table 1

Engine model parameters"

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-1）5 000
最大净功率/（kW·r·min-1）72/6 000
进气歧管体积/L2

Fig.1

Verification results of engine model"

Fig.2

Control diagram of real-time PID feedback with intake sensor"

Fig.3

Flowchart of GPR intake prediction"

Fig.4

Prediction effect of intake volume under transient operating conditions"

Fig.5

Diagram of air-fuel ratio feedback control based on GPR intake prediction"

Fig.6

Comparison results of two methods under transient operating conditions of 200 s"

Fig.7

Comparison results of two methods under transient operating conditions of 800 s"

Table 2

Results of intake prediction and lambda controlunder two transient operating conditions"

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-1）33.1438.6535.890
lambda控制平均误差/（kg·h-1）PID反馈0.0590.0610.060
GPR反馈0.0520.0430.048
[1] Liu J P, Xia X L, Wang Y, et al. Development of a fast response high accuracy virtual air flow meter for internal combustion engine applications[C]∥2011 Third International Conference on Measuring Technology and Mechatronics Automation,Shanghai, China, 2011: 1037-1041.
[2] Piqueras P, De La Morena J, Sanchis E J, et al. Impact of exhaust gas recirculation on gaseous emissions of turbocharged spark-ignition engines[J]. Applied Sciences, 2020, 10(21): No. 7634.
[3] 杜永波. 基于进气量预测的汽油机缸内高压喷水控制模型研究[D]. 重庆: 重庆大学能源与动力工程学院, 2022.
Du Yong-bo. Research on control mode l of in-cylinder high pressure water injection of gasoline engine based on prediction of air intake[D]. Chongqing: School of Energy and Power Engineering, Chongqing University, 2022.
[4] Zhao Y N, Shen T L, Jiao X H, et al. Air-fuel ratio transient control design for gasoline engines based on individual cylinder air charge estimation[C]∥SAE Technical Paper, 2013-01-0102.
[5] 孙铂奇. 增程器发动机进气量估计方法研究及实验验证[D]. 长春: 吉林大学汽车工程学院, 2020.
Sun Bo-qi. The study on intake flow estimation method of range-extender engine and experimental verification[D]. Changchun: College of Automotive Engineering, Jilin University, 2020.
[6] Lei M, Jie L, Xu Y, et al. Intake air mass observer design based on extended Kalman filter for air-fuel ratio control on SI engine[J]. Energies, 2019, 12(18): NO. 3444.
[7] 冯煜, 焦晓红. 汽油机非线性卡尔曼滤波暂态进气量气量估计及空燃比控制[J]. 控制理论与应用, 2015, 32(4): 546-553.
Feng Yu, Jiao Xiao-hong. Transient cylinder air charge estimation with nonlinear Kalman filter for air-fuel ratio control of gasoline engines[J]. Control Theory and Applications, 2015, 32(4): 546-553.
[8] Xie F Q. Gasoline engine intake flow forecast ctudy of chaotic RBF neural network[C]∥Seventh International Conference on Measuring Technology and Mechatronics Automation,Nanchang, China, 2015: 506-511.
[9] Wang Y M, Zhang F J, Cui T, et al. Fault diagnosis for manifold absolute pressure sensor (MAP) of diesel engine based on Elman neural network observer[J]. Chinese Journal of Mechanical Engineering, 2016, 29: 386-395.
[10] 张五龙, 李岳林, 杨得志, 等. 基于SVR的汽油机过渡工况进气量预测研究[J]. 车用发动机, 2023(1): 44-51.
Zhang Wu-long, Li Yue-lin, Yang De-zhi, et al. Research on gas intake prediction of gasoline engine under transition condition based on SVR[J]. Vehicle Engine, 2023(1): 44-51.
[11] Seeger M. Gaussian processes for machine learning[J]. International Journal of Neural Systems, 2004, 14(2): 69-106.
[12] 季廷炜, 查旭, 谢芳芳, 等. 基于高斯过程回归的空天飞行器多精度气动建模方法[J]. 浙江大学学报: 工学版, 2023, 57(11): 2314-2324.
Ji Ting-wei, Zha Xu, Xie Fang-fang, et al. Multi-fidelity aerodynamic modeling method of aerospace vehicles based on Gaussian process regression[J]. Journal of Zhejiang University (Engineering Science), 2023, 57(11): 2314-2324.
[13] 杨映荷, 魏汉迪, 范迪夏, 等. 基于高斯过程回归和深度强化学习的水下扑翼推进性能寻优方法[J].上海交通大学学报, 2023, 188: 1-16.
Yang Ying-he, Wei Han-di, Fan Di-xia, et al. Optimization method of underwater flapping foil propulsion preformance based on Gaussion process regression and deep reinforcement learning[J]. Journal of Shanghai Jiao Tong University, 2023, 188: 1-16.
[14] Shi X Y, Jiang D G, Qian W W, et al. Application of the Gaussian process regression method based on a combined kernel function in engine performance prediction[J]. ACS Omega, 2022, 7(45): No.41732.
[15] Eriksson L, Lindell T, Leufven O, et al. Scalable component-based modeling for optimizing engines with supercharging, E-boost and turbo compound concepts[J]. SAE International Journal of Engines, 2012, 5(2): 579-595.
[16] Eriksson L, Thomasson A, Ekberg K, et al. Look-ahead controls of heavy duty trucks on open roads-six benchmark solutions[J]. Control Engineering Practice, 2019, 83: 45-66.
[17] Willmott C J. Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance[J]. Climate Research, 2005, 30(1): 79-82.
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