ESO-based iPI Common Rail Pressure Control of
High Pressure Common Rail Injection System
Haoping WANG, Yang TIAN*, Dong ZHENG
Nanjing University of Science & Technology (NJUST), School of Automation,
Sino-French International Joint Laboratory of Automatic Control and Signal Processing (LaFCAS),
Nanjing 210094, China
* Corresponding author
Abstract: This paper presents an ESO-based iPI control for common rail pressure. First, a detailed mathematical model of High Pressure Common Rail Injection System (HPCRIS) is built. The mathematical model is validated by the software Matlab and commercial software AMESim. For the considered HPCRIS, an effective model free controller which is called Extended State Observer – based intelligent Proportional Integral (ESO-based iPI) controller is designed. And this proposed ESO-iPI controller is composed mainly of the referred ESO observer, and the iPI controller. Finally, to demonstrate the performances and effectiveness of the proposed controller, the proposed controller is implemented and compared with a conventional PID controller and Active Disturbance Rejection Control (ADRC), and their corresponding simulations are carried out.
Keywords: High pressure common rail injection system, common-rail pressure, ESO, iPI controller, ADRC, AMESim.
CITE THIS PAPER AS:
Haoping WANG, Yang TIAN*, Dong ZHENG, ESO-based iPI Common Rail Pressure Control of High Pressure Common Rail Injection System, Studies in Informatics and Control, ISSN 1220-1766, vol. 25(3), pp. 273-282, 2016. https://doi.org/10.24846/v25i3y201601
In recent years, serious air pollutions have affected people’s daily life. According to the survey of the environment protection department in 2015, one of the main emission resources of NOx and C is from the transportation section, in which the emissions of diesel engine occupy the most important part. Thus improvement of the emission performance of diesel engine becomes a rigorous and important task. High Pressure Common Rail Injection System (HPCRIS) is a key technology to reduce the emission of diesel engine. Its function determines not only the injection-fuel pressure, but also the emission measurement of fuel-injection. High and steady common-rail pressure is important to diesel engine.
To study the control of common-rail pressure, a model that can describe the dynamics of the common-rail pressure is required firstly. Many researchers have built different common-rail pressure models, like an empirical common-rail pressure model in , a hybrid common-rail injection system model in , and a controloriented model in  which is adopted by
In , Lino et al based on the referred control-oriented model proposed a sliding mode rail pressure controller, while many other researchers based on classical PID controller, propose derived PID controllers for common rail pressure control, such like RBF neural network adaptive PID control in , feed forward fuzzy PID control in , and genetic algorithm nonlinear PID control in , etc.
For the pressure wave in the common rail caused by the discontinuous inlet fuel flow and the discontinuous outlet fuel flow, some different control methods have been applied to the rail pressure control, such as the QFT (quantitative feedback theory) method is introduced to regulate and control rail pressure , and a
coordinated control strategy for the rail pressure using a metering unit and a pressure control valve in proposed in .
More recently, to improve the control performance of the considered common rail system, particularly with the consideration of the uncertainties, and external disturbance such as measurement noise, etc in system dynamics, a novel disturbance estimation and rejection control is designed for rail pressure control in . From the above overview of the rail pressure control, the requirements for the rail pressure controller are: simple parameters tuning, good rejection to external disturbances, and easy adaptation to variable working conditions.
Thus in this paper, an Extended State Observer – based intelligent Proportional Integral (ESObased iPI) controller is designed for common rail pressure of HPCRIS. This proposed ESObased iPI control is based on new results from intelligent PID Control which employs an ultralocal model and algebraic based derivatives estimation of systems output signals [4-5]. While for the referred algebraic based derivatives estimation, it needs complex calculation steps and easily perturbed by external measurement noises. To improve the entire method performance, an extended state observer (ESO) which are derived from [8, 14] is proposed via the knowledge of the control and output signals .
The following paper is organized as follows: a detailed nonlinear model of HPCRIS is proposed in section 2, which is followed in section 3, the referred mathematical model of HPCRIS is validated both by MATLAB/Simulink and AMESim software. Then in Section 4, for the considered HPCRIS, a new ESO-based iPI controller is designed. Moreover to validate the proposed entire control, its corresponding simulation results which are implemented in both Matlab/Simulink and AEMSim environment, and compared with classic PID controller and ADRC are illustrated in section 5. Finally, some conclusions and future work comments are summarized in section 6.
- ARSIE, I., F. Di GENOVA, C. PIANESE, Development and Identification of Phenomenological Models for Combustion and Emissions of Commonrail Multi-jet Diesel Engines, SAE Tech Paper, 2004.
- BALLUCHI, J. A., A. BICCHI, E. MAZZI, Hybrid Modelling and Control of the Common Rail Injection System, Hybrid Systems: Computers and Control, Springer Berl Heide, 2006, pp. 79-92.
- CHATLATANAGULCHAI, W, T. AROONSRISOPON, K. WANNATONG, Robust Common-rail Pressure Control for a Diesel-Dual-Fuel Engine using QFT-based Controller, SAE Paper. 2009.
- FLIESS, M., C. JOIN, Model-free Control and Intelligent PID Controllers: Towards a Possible Trivialization of Nonlinear Control, IFAC Proceedings., vol. 15, 2009, pp. 1531-50.
- FLIESS, M., C. JOIN, Stability Margins and Model-free Control: A First Look, Proceedings of European Control
Conference, (ECC), 2014, pp. 454-9.
- FLIESS, M., H. SIRA-RAMÍREZ, An Algebraic Framework for Linear Identification, ESAIM Control Optim Calc Var, Vol. 9, 2003, pp. 151-68.
- GÉDOUIN, P. A., E. DELALEAU, J. M. BOURGEOT, C. JOIN, S. A. CHIRANI, S. CALLOCH, Experimental Comparison of Classical PID and Model-free Control: Position Control of a Shape Memory Alloy Active Spring, Control Eng Pract., Vol. 19, 2011, pp. 433-41.
- HAN J., From PID to Active Disturbance Rejection Control, IEEE Trans. Ind. Electron., vol. 56, 2009, pp. 900-6.
- HONG, S., H. SHIN, J. SOHN, I. PARK, M. SUNWOO, Coordinated Control Strategy for the Common-rail Pressure using a Metering Unit and A Pressure Control Valve in Diesel Engines, Journal of Auto Engineering, 2014, pp. 1-13.
- JI, Z., X. XIE, Z. SUN, P. CHEN, Rail Pressure Control of Common Rail Diesel Engine based on RBF Neural Network Adaptive PID Controller, Proc 2011 Int Conf Electron Mech Eng Inf Technol, 2011, pp. 1122-5.
- KOUREMENOS, D. A., D. T. HOUNTALAS, A. D. KOUREMENOS, Development and Validation of a Detailed Fuel Injection System Simulation Model for Diesel Engines, SAE Technical Paper, 1999.
- LINO, P., B. MAIONE, A. RIZZO, Nonlinear Modelling and Control of a Common Rail Injection System for Diesel Engines, Appl Math Model, vol. 31, 2007, pp. 1770-84.
- LINO, P., B. MAIONE B, A. RIZZO, A Control-oriented Model of a Common Rail Injection System for Diesel Engines, 10th IEEE Conf, Emer Tech and Fact Auto, 2005, pp. 1-7.
- LI. M., D. LI, J. WANG, C. ZHAO, Active Disturbance Rejection Control for Fractional-order System, ISA Trans vol. 52, 2013, pp.365-74.
- LINO. P., B. MAIONE, A. RIZZO, A Control-oriented Model of a Common Rail Injection System for Diesel Engines, 2005 IEEE Conf Emerg Technol Fact Autom , 2005.
- LIU, Q., X. GONG, Y. HU, H. CHEN, Active Disturbance Rejection Control of Common Rail Pressure for Gasoline Direct Injection Engine, Proc Ame Control Conf, 2013, pp. 2202-2207.
- LI, M., D. LI, J. WANG, C. ZHAO, Active Disturbance Rejection Control for Fractional-order System, ISA Trans., Vol. 52, 2013, pp. 365–74.
- MENHOUR, L., B. d’ANDREA-NOVEL, M. FLIESS, H. MOUNIER, Multivariable Decoupled Longitudinal and Lateral Vehicle Control: A Model-free Design, Proceedings of IEEE Conference on Decision Control, 2013, pp. 2834-9.
- PAN, D., F. GAO, Y. MIAO, Cosimulation Research of a Novel Exoskeleton-human Robot System on Humanoid Gaits with Fuzzy-PID/PID Algorithms, Adva in Eng Soft, vol. 79, 2015, pp. 36-46.
- REN, W., X. SHI, S. JIAO, C. ZHU, Q. ZHANG, Research on Rail Pressure Control of Diesel Engine based on Genetic Algorithm Nonlinear PID, 2011 IEEE Int Conf Comput Sci Autom Eng, 2011, pp. 67-71.
- SU, H., G. HAO, P. LI, X. LUO, Feed Forward Fuzzy PID Controller for Common-Rail Pressure Control of Diesel Engine, Meas Technol Mechatronics Autom (ICMTMA), 2010.