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Revisiting the benchmark problem of starting control of combustion engines

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Abstract

Starting of combustion engines is a typical transient operating mode that has significant influence to the engine performance. Due to the distinct variations in the pathes of air intake and fuel injection, the model of the engine system contains considerable uncertain parameters. To search effective control schemes that guarantee desired performance, engine starting control is proposed as a benchmark challenge problem. As a challenging result, a model-based control scheme is developed perviously. In this work, the benchmark problem is revisited and a modification for the fuel injection path control of the previous work is proposed by integrating a time sequence regressive based parameter tuning strategy. Validation by the benchmark problem simulator shows that although the new strategy has simple structure, similar control performance is obtained. Especially, the new strategy has potential extensibility with learning based methods to further improve the performance of the benchmark problem on engine starting control.

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Authors and Affiliations

  1. State Key Laboratory of Automotive Simulation and Control, Changchun Jilin, 130025, China

    Jiangyan Zhang & Jinwu Gao

  2. Department of Control Science and Engineering, Jilin University, Changchun Jilin, 130025, China

    Jinwu Gao

  3. College of Mechanical and Electronic Engineering, Dalian Minzu University, Dalian Liaoning, 116600, China

    Jiangyan Zhang

  4. Department of Engineering and Applied Sciences, Sophia University, Tokyo, 102-8554, Japan

    Zhenhui Xu

Authors
  1. Jiangyan Zhang
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  2. Zhenhui Xu
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  3. Jinwu Gao
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Corresponding author

Correspondence to Jinwu Gao.

Additional information

This work was supported by Foundation of State Key Laboratory of Automotive Simulation and Control (No. 20161101) and the National Natural Science Foundation of China (No. 61703179).

Jiangyan ZHANG received the B.E. and M.E. degrees in Electrical Engineering from Yanshan University, Qinhuangdao, China, in 2005 and 2008, respectively, and the Ph.D. degree in Mechanical Engineering from Sophia University, Tokyo, Japan, in 2011. She currently is an Associate Professor with the College of Mechanical and Electronic Engineering of Dalian Minzu University at Dalian, China. Her research interests are mainly in control theory and applications of control to the automotive powertrain systems.

Zhenhui XU received the B.Sc. degree in Automation (Excellent Engineers) from Chang’an University in 2014, and the M.Sc. degree in Control Engineering from University of Science and Technology of China in 2017. She is currently pursing the Ph.D. degree at Sophia University, Tokyo, Japan. Her research interests are in the fields of multiagent systems, nonlinear systems, and hybrid vehicles.

Jinwu GAO received the B.Eng. degree in the Department of Automation Measurement and Control Engineering, and the Ph.D. degree in the Department of Control Science and Engineering from Harbin Institute of Technology, Harbin, China, in 2005 and 2012. From 2012 to 2014, he was an Assistant Professor at Sun Yat-sen University, China. In July 2014, he held postdoctoral position in the Department of Engineering and Applied Science, Sophia University, Japan. Since November 2016, he has been an Associate Professor at Jilin University, China. His research interests include control theory and application in automotive powertrain.

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Zhang, J., Xu, Z. & Gao, J. Revisiting the benchmark problem of starting control of combustion engines. Control Theory Technol. 17, 148–155 (2019). https://doi.org/10.1007/s11768-019-8277-4

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  • DOI: https://doi.org/10.1007/s11768-019-8277-4

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