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Gaussian Process Regression Feedforward Controller for Diesel Engine Airpath

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Abstract

Gaussian Process Regression (GPR) provides emerging modeling opportunities for diesel engine control. Recent serial production hardwares increase online calculation capabilities of the engine control units. This paper presents a GPR modeling for feedforward part of the diesel engine airpath controller. A variable geotmetry turbine (VGT) and an exhaust gas recirculation (EGR) valve outer loop controllers are developed. The GPR feedforward models are trained with a series of mapping data with physically related inputs instead of speed and torque utilized in conventional control schemes. A physical model-free and calibratable controller structure is proposed for hardware flexibility. Furthermore, a discrete time sliding mode controller (SMC) is utilized as a feedback controller. Feedforward modeling and the subsequent airpath controller (SMC+GPR) are implemented on the physical diesel engine model and the performance of the proposed controller is compared with a conventional PID controller with table based feedforward.

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Abbreviations

P i :

nomenclature

P x :

intake manifold pressure

P c :

exhaust manifold pressure

P a :

compressor power

R :

ambient pressure

R :

ideal gas constant

T i :

intake manifold temperature

T x :

exhaust manifold temperature

T a :

ambient temperature

V i :

intake manifold volume

τ :

turbocharger time constant

W ci :

compressor mass airflow

W xi :

exhaust gas recirculation mass flow

W ie :

engine inlet gas mass flow

W xt :

turbine inlet gas mass flow

W f :

fuel mass flow

η c :

isentropic compressor efficiency

η T :

turbine total efficiency

c :

specific heat of air

u ff :

feedforward control term

u fb :

feedback control component

Ar EGR :

exhaust gas recirculation valve area

h xt :

exhaust gas enthalpy

u 1 :

controlled input 1, area of EGR

u 2 :

controlled input 2, area of VGT

μ :

isentropic ratio

r VGT :

VGT vane position

r EGR :

EGR valve position

References

  • Aran, V. and Unel, M. (2016). Feedforward mapping for engine control. Proc. IEEE Industrial Electronics Society, IECON Annual Conf., 154–159

    Google Scholar 

  • Bischoff, B., Nguyen-Tuong, D., Koller, T., Markert, H. and Knoll, A. (2013). Learning throttle valve control using policy search. Lecture Notes in Computer Science, 8188, 49–64

    Article  Google Scholar 

  • Calandra, R., Peters, J., Rasmussen, C. E. and Deisenroth, M. P. (2014). Manifold gaussian processes for regression. arXiv: 1402.5876v4 [stat.ML].

    Google Scholar 

  • Heywood, J. (2000). Internal Combustion Engine Fundamentals. McGraw-Hill. New York, USA.

    Google Scholar 

  • Jankovic, M. and Kolmanovsky, I. (1998). Robust nonlinear controller for turbocharged diesel engines. Proc. American Control Conf., Philadelphia, Pennsylvania, USA.

    Google Scholar 

  • Jung, M., Glover, K. and Christen, U. (2005). Comparison of uncertainty param-eterisations for H infinity robust control of turbocharged diesel engines. Control Engineering Practice 13, 1, 15–25

    Article  Google Scholar 

  • Kolmanovsky, I. (1997). Issues in modelling and control of intake flow in variable geometry turbocharged engines. Proc. 18th IFIP Conf. System Modeling and Optimization, 436–445

    Google Scholar 

  • Mancini, G., Asprion, J., Cavina, N., Onder, C. and Guzzella, L. (2014). Dynamic feedforward control of a diesel engine based on optimal transient compensation maps. Energies 7, 8, 5400–5424

    Article  Google Scholar 

  • Nieuwstadt, M. J., Kolmanovsky, I. V., Moraal, P. E., Stefanopoulou, A. and Jankovic, M. (2000). EGR-VGT control schemes: Experimental comparison for a highspeed diesel engine. IEEE Control Systems 20, 3, 63–79

    Article  Google Scholar 

  • Rasmussen, C. E. and Williams, C. (2006). Gaussian Processes for Machine Learning. MIT Press. Cambridge, Massachusetts, USA.

    MATH  Google Scholar 

  • Sabanovic, A., Sabanovic, N. and Jezernik, K. (2003). Sliding modes in sampled data systems. Automatika: J. Control, Measurement, Electronics, Computing and Communications 44, 3–4, 163–181

    MATH  Google Scholar 

  • Schreiter, J., Nguyen-Tuong, D. and Toussaint, M. (2016). Efficient sparsification for Gaussian process regression. Neurocomputing, 192, 29–37

    Article  Google Scholar 

  • Tietze, N. (2015). Model-based Calibration of Engine Control Units Using Gaussian Process Regression. Ph. D. Dissertation. Technical University Darmstadt. Darmstadt, Germany.

    Google Scholar 

  • UN ECE (2013). E/ECE/324/Rev.1/Add.48/Rev.6-E/ECE/TRANS/505/Rev.1/Add.48/Rev.

  • Unver, B., Koyuncuoglu, Y., Gokasan, M. and Bogosyan, S. (2016). Modeling and validation of turbocharged diesel engine airpath and combustion systems. Int. J. Automotive Technology 17, 1, 13–34

    Article  Google Scholar 

  • Wahlstrom, J. and Eriksson, L. (2011). Modelling diesel engines with a variable-geometry turbocharger and exhaust gas recirculation by optimization of model parameters for capturing non-linear system dynamics. Proc. Institution of Mechanical Engineers, Part D: J. Automobile Engineering 225, 7, 960–986

    Google Scholar 

  • Wahlstrom, J. and Eriksson, L. (2013). Output selection and its implications for MPC of EGR and VGT in diesel engines. IEEE Trans. Control Systems Technology 21, 3, 932–940

    Article  Google Scholar 

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Correspondence to Mustafa Unel.

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Aran, V., Unel, M. Gaussian Process Regression Feedforward Controller for Diesel Engine Airpath. Int.J Automot. Technol. 19, 635–642 (2018). https://doi.org/10.1007/s12239-018-0060-x

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  • DOI: https://doi.org/10.1007/s12239-018-0060-x

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