ENGINE CALIBRATION USING "EIGENVARIABLES"

被引:0
|
作者
Hu, Yiran [1 ]
Haskara, Ibrahim [1 ]
Chang, Chen-Fang [1 ]
Sadabadi, Kaveh Khodadadi [2 ]
Rezaeian, Ayyoub [2 ]
Midlam-Mohler, Shawn [2 ]
机构
[1] Gen Motors Res & Dev, Prop Syst Res Lab, Pontiac, MI 48340 USA
[2] Ohio State Univ, Ctr Automot Res, Columbus, OH 43212 USA
关键词
IGNITION ENGINE; COMBUSTION;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
To meet the more stringent emissions and fuel economy regulations, engine control system has become significantly more complex than before. As a result of this, engine calibration on the dynamometer now occupies one of the longest time sections in the vehicle development process. One strategy automakers have adopted is to use the same engine in multiple applications to reduce the calibration effort. Even then, vehicle design constraints often require changes to be made to the engine's external components such as the intake and exhaust manifolds. These changes can create variations in the engine combustion behavior so that the engine must be recalibrated on the dyno, resulting in additional cost and effort. This paper explores the potential of reusing existing engine dyno data for a modified engine in these scenarios through the use of the so-called eigenvariable to describe engine operating conditions. Traditionally, engine dyno data is referenced by engine load and speed along with actuator positions (such as camphaser positions). The proposed approach describes dyno data using eigenvariables or variables that describe the engine in-cylinder condition prior to combustion. Eigenvariables are invariant with respect to external engine hardware. This invariance enables the same dyno data to be applied to a modified engine with the same combustion system design.
引用
收藏
页数:8
相关论文
共 50 条
  • [1] Engine calibration using nonlinear dynamic modeling
    Röpke, Karsten
    Baumann, Wolf
    Köhler, Bert-Uwe
    Schaum, Steffen
    Lange, Richard
    Knaak, Mirko
    Lecture Notes in Control and Information Sciences, 2012, 418 : 165 - 182
  • [2] Engine Calibration Using Nonlinear Dynamic Modeling
    Roepke, Karsten
    Baumann, Wolf
    Koehler, Bert-Uwe
    Schaum, Steffen
    Lange, Richard
    Knaak, Mirko
    IDENTIFICATION FOR AUTOMOTIVE SYSTEMS, 2012, 418 : 165 - +
  • [3] AN AUTOMOTIVE ENGINE CALIBRATION SYSTEM USING MICROCOMPUTER
    WATANABE, K
    TUMER, M
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 1984, 33 (02) : 45 - 50
  • [4] Optimization using a genetic algorithm in engine calibration
    Lin, W
    Wu, MH
    ADVANCES IN MANUFACTURING TECHNOLOGY - XVII, 2003, : 311 - 315
  • [5] Engine Model Calibration Using Extremum Seeking
    Tan, Qingyuan
    Divekar, Prasad
    Tan, Ying
    Chen, Xiang
    Zheng, Ming
    IFAC PAPERSONLINE, 2016, 49 (11): : 730 - 735
  • [6] Internal combustion engine calibration using optimization algorithms
    Yu, Xunzhao
    Zhu, Ling
    Wang, Yan
    Filev, Dimitar
    Yao, Xin
    APPLIED ENERGY, 2022, 305
  • [7] Development of an Engine Calibration Model Using Gaussian Process Regression
    Pan, Tianhong
    Cai, Yang
    Chen, Shan
    INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY, 2021, 22 (02) : 327 - 334
  • [8] Development of an Engine Calibration Model Using Gaussian Process Regression
    Tianhong Pan
    Yang Cai
    Shan Chen
    International Journal of Automotive Technology, 2021, 22 : 327 - 334
  • [9] AUTOMATED ENGINE CALIBRATION OPTIMIZATION USING ONLINE EXTREMUM SEEKING
    Singh, Ripudaman
    Mansfield, Andrew
    Wooldridge, Margaret
    PROCEEDINGS OF THE ASME INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION, 2018, VOL 8A, 2019,
  • [10] Optimization and calibration strategy using design of experiment for a diesel engine
    Park, Sangki
    Kim, Youngkun
    Woo, Seungchul
    Lee, Kihyung
    APPLIED THERMAL ENGINEERING, 2017, 123 : 917 - 928