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Design of a Model-Based Fuzzy-PID Controller with Self-Tuning Scaling Factor for Idle Speed Control of Automotive Engine

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Abstract

Automotive engines spend a considerable portion of their life in idle state, where their characteristics are highly nonlinear and time varying. Efficient control of the engine in idle state significantly improves fuel economy, emission level and drivability. In this work, we proposed a combined fuzzy-PID idle speed controller which improves stability, fuel consumption and emission level, during normal operation as well as transient loads. In order to study the performance of control algorithm, XU7-1761cc gasoline port fuel injection engine has been modeled in idle state. This model calculates engine speed as a function of idle air valve position and ignition angle. This model demonstrated maximum of 8% error during parallel model in the loop and engine in the loop operation. After tuning the membership functions, performance of fuzzy-PID controller has been compared with baseline PID controller of engine control unit. Model in the loop simulation demonstrated that fuzzy-PID controller is more accurate than baseline PID controller, unconditionally stable and is able to reduce fuel consumption in the order of 14% compared to baseline controller. Finally, an experimental setup for real-time control of idle air valve based on proposed controller has also been developed.

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References

  • Argonne National Laboratory (2015) Idling reduction savings calculator, 2015, October. http://www.anl.gov/sites/anl.gov/files/idling_worksheet.pdf

  • Ashok B, Ashok SD, Kumar CR (2016) A review on control system architecture of a SI engine management system. Ann Rev Control 41:94–118

    Article  Google Scholar 

  • Aubourg AMJ, Le Quellec JM, Raymond C, Siemens Automotive SA (1997) Method and device for controlling the speed of an internal combustion engine during a deceleration phase. U.S. Patent 5,662,085

  • Bhatti AI, Spurgeon SK, Dorey R (2000) Idle speed control of an automotive engine using a robust nonlinear controller–observer pair. Eur J Control 6(6):525–539

    Article  MATH  Google Scholar 

  • Butts KR, Sivashankar N, Sun J (1999) Application of l 1 optimal control to the engine idle speed control problem. IEEE Trans Control Syst Technol 7(2):258–270

    Article  Google Scholar 

  • Cairano SD, Yanakiev D, Bemporad A, Kolmanovsky IV, Hrovat D (2012) Model predictive idle speed control: design, analysis, and experimental evaluation. IEEE Trans Control Syst Technol 20(1):84–97

    MATH  Google Scholar 

  • Cho D, Hedrick JK (1989) Automotive powertrain modeling for control. J Dyn Syst Meas Contr 111(4):568–576

    Article  Google Scholar 

  • Chopra S, Mitra R, Kumar V (2008) Auto tuning of fuzzy PI type controller using fuzzy logic. Int J Comput Cogn 6(1):185

    Google Scholar 

  • Chrenko D (2015) Influence of hybridization on eco-driving habits using realistic driving cycles. IET Intel Transport Syst 9(5):498–504

    Article  Google Scholar 

  • Czarnigowski J (2010) A neural network model-based observer for idle speed control of ignition in SI engine. Eng Appl Artif Intell 23(1):1–7

    Article  Google Scholar 

  • Guzzella L, Onder C (2009) Introduction to modeling and control of internal combustion engine systems, 2nd ed. Springer Science & Business Media

  • Heywood JB (1988) Internal combustion engine fundamentals. Mcgraw-hill, New York

    Google Scholar 

  • Hsieh FC, Chen BC, Wu YY (2007) Adaptive idle speed control for spark-ignition engines (No. 2007-01-1197). SAE Technical Paper

  • Jurgen R (1995) Automobile electronics handbook. McGraw-Hill, New York

    Google Scholar 

  • Laurain T, Lauber J, Palhares R (2016) Advanced model based air path management using a discrete-angular controller in idle-speed context. IFAC-PapersOnLine 49(11):611–618

    Article  Google Scholar 

  • Nikzadfar K, Noorpoor A, Shamekhi AH (2012) Design of an optimal idle speed controller for a turbocharged diesel engine using fuzzy logic method. J Mech Sci Technol 26(8):2325–2336

    Article  Google Scholar 

  • Stotsky A (2007) Adaptive estimation of the engine friction torque. Eur J Control 13(6):618–624

    Article  MathSciNet  MATH  Google Scholar 

  • Thornhill M, Thompson S, Sindano H (2000) A comparison of idle speed control schemes. Control Eng Pract 8(5):519–530

    Article  Google Scholar 

  • Xiong Y, Yang S, Gou W, Jiang H, Tan K (2013) A fuzzy intelligent-integration PID idle control strategy for gas fueled SI engine. In: International conference on computer sciences and applications (CSA), 2013, pp 357–360

  • Xu F, Chen H, Gong X, Hu YF (2013) Engine idle speed control using nonlinear model predictive control. IFAC Proc 46(21):171–176

    Article  Google Scholar 

  • Xu F, Chen H, Jin W, Xu Y (2014) FPGA implementation of nonlinear model predictive control. In: IEEE Control and decision conference (2014 CCDC), the 26th Chinese, pp 108–113

  • Xu F, Chen H, Gong X, Mei Q (2016) Fast nonlinear model predictive control on FPGA using particle swarm optimization. IEEE Trans Ind Electron 63(1):310–321

    Article  Google Scholar 

  • Ye Z (2007) Modeling, identification, design, and implementation of nonlinear automotive idle speed control systems—an overview. IEEE Trans Syst Man Cybern C Appl Rev 37(6):1137–1151

    Article  Google Scholar 

  • Yildiz Y, Annaswamy AM, Yanakiev D, Kolmanovsky I (2011) Spark-ignition-engine idle speed control: an adaptive control approach. IEEE Trans Control Syst Technol 19(5):990–1002

    Article  Google Scholar 

  • Zhang J, Shen T, Marino R (2010) Model-based cold-start speed control scheme for spark ignition engines. Control Eng Pract 18(11):1285–1294

    Article  Google Scholar 

  • Zhao ZY, Tomizuka M, Isaka S (1992) Fuzzy gain scheduling of PID controllers. In: First IEEE conference on control applications, pp 698–703

  • Zhu D, Hu Y, Gong X, Chen H (2015) Idle speed control system design based on engine torque management. In: IEEE Chinese automation congress (CAC), pp 1809–1814

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Correspondence to Sasan Banarezaei.

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Banarezaei, S., Shalchian, M. Design of a Model-Based Fuzzy-PID Controller with Self-Tuning Scaling Factor for Idle Speed Control of Automotive Engine. Iran J Sci Technol Trans Electr Eng 43, 13–31 (2019). https://doi.org/10.1007/s40998-018-0095-z

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  • DOI: https://doi.org/10.1007/s40998-018-0095-z

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