吉林大学学报(工学版) ›› 2021, Vol. 51 ›› Issue (1): 49-62.doi: 10.13229/j.cnki.jdxbgxb20190906

• 车辆工程·机械工程 • 上一篇    下一篇

柴油发动机燃烧过程数据驱动建模与滚动优化控制

胡云峰1,2(),丁一桐2,赵志欣3,蒋冰晶2,高金武1,2()   

  1. 1.吉林大学 汽车仿真与控制国家重点实验室，长春 130022
    2.吉林大学 通信工程学院，长春 130022
    3.长春师范大学 数学学院，长春 130032
  • 收稿日期:2019-09-23 出版日期:2021-01-01 发布日期:2021-01-20
  • 通讯作者: 高金武 E-mail:huyf@jlu.edu.cn;gaojw@jlu.edu.cn
  • 作者简介:胡云峰(1983-)，男，教授，博士.研究方向：发动机建模与优化控制.E-mail:huyf@jlu.edu.cn
  • 基金资助:
    国家自然科学基金项目(U1864201);吉林省科技厅自然科学基金项目(20180101037JC);吉林省教育厅科学技术研究项目(JJKH20180144KJ);吉林大学省校共建项目(SXGJSF2017-2-1-1)

Data-driven modeling and receding optimization control of diesel engine combustion process

Yun-feng HU1,2(),Yi-tong DING2,Zhi-xin ZHAO3,Bing-jing JIANG2,Jin-wu GAO1,2()   

  1. 1.State Key Laboratory of Automotive Simulation and Control，Jilin University，Changchun 130022，China
    2.College of Communication Engineering，Jilin University，Changchun 130022，China
    3.School of Mathematics，Changchun Normal University，Changchun 130032，China
  • Received:2019-09-23 Online:2021-01-01 Published:2021-01-20
  • Contact: Jin-wu GAO E-mail:huyf@jlu.edu.cn;gaojw@jlu.edu.cn

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摘要：

针对柴油发动机燃烧过程复杂、机理建模难、动力学耦合且存在约束等问题，以降低燃油消耗率和扭矩跟踪为目标、以氮氧化物排放及控制量限制为约束，提出了柴油发动机燃烧过程数据驱动建模与滚动优化控制方法。首先，以商用发动机模拟软件GT-suite中的一款2 L排量的柴油发动机为被控对象，分析了VGT和EGR控制阀开度、喷油角度和喷油量这4个因素对燃油消耗率、氮氧化物排放以及曲轴输出扭矩的影响；其次，利用输入和输出数据，采用子空间辨识方法得出了面向控制的预测模型；然后，以降低燃油消耗率、扭矩跟踪误差为目标，以氮氧化物排放及控制量限制为约束，通过对优化问题的在线优化求解，得到了最优的控制输入；最后，运用MATLAB与GT-suite联合仿真，验证了数据驱动滚动优化控制方法的有效性和优越性。

关键词: 动力机械工程, 柴油发动机, 子空间辨识, 数据驱动, 滚动优化控制

Abstract:

Aiming at the problems of diesel engine combustion process complexity， mechanism modeling difficulty， dynamic coupling and constraints， a data-driven modeling and rolling optimization control method for diesel engine combustion process was proposed to reduce fuel consumption and torque tracking， and to limit NOx emission and control volume. First， a 2L diesel engine model in GT-suite is chose as a plant. The influences of VGT and EGR control valve opening， injection angle and injection amount on fuel consumption rate， NOx emission and crankshaft output torque are analyzed. Second， using input and output data， a control-oriented data-driven prediction model is obtained by using subspace identification method. Third， to reduce the fuel consumption rate and torque tracking error， and the NOx emission and control input are considered as constraint， the optimal control input is obtained by solving a multi-objective optimal control problem. Finally， the co-simulation based on MATLAB and GT-suite is presented to verify the effectiveness and superiority of the data-driven receding optimization control method.

Key words: power machinery engineering, diesel engine, subspace identification, data-driven, receding optimization control

中图分类号: 

  • TK411

图1

GT-suite中2 L的柴油机模型"

图2

动力学分析输入数据"

图3

动力学分析输出数据"

图4

数据驱动滚动优化算法"

图5

模型验证输入数据"

图6

模型验证结果对比"

图7

模型验证误差曲线"

图8

ETC工况下的发动机转速"

图9

ETC工况下的扭矩"

图10

控制输入（城市工况）"

图11

系统输出（城市工况）"

图12

扭矩跟踪误差对比"

图13

控制输入（乡村工况）"

图14

系统输出（乡村工况）"

图15

扭矩跟踪误差对比"

图16

控制输入（高速公路工况）"

图17

系统输出（高速公路工况）"

图18

扭矩跟踪误差对比"

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