Model predictive air path control for a two-stage turbocharged spark-ignition engine with low pressure exhaust gas recirculation

Abstract

Innovative air path concepts for turbocharged spark-ignition engines with exhaust gas recirculation impose high demands on the control due to nonlinearities and cross-couplings. This contribution investigates the control of the air and exhaust gas recirculation paths of a two-stage turbocharged spark-ignition engine with low pressure exhaust gas recirculation. Using exhaust gas recirculation at high loads, the in-cylinder temperature can be lowered, reducing the knock tendency, while at the same time preventing the need for the enrichment of the air/fuel ratio. Air and exhaust gas recirculation paths are cross-coupled and show different delay times. To tackle these challenges, a data-based two-stage model predictive controller is proposed: The target selector accounts for the overactuated system structure, while the dynamic controller adjusts the charging pressure and exhaust gas recirculation rate. The prediction model setup is based on a small amount of dyno-run measurement data. To ensure real-time capability, the model is kept as simple as possible. This allows for fast turnaround times of the algorithm, while maintaining the necessary accuracy in steady-state and transient operation. This study focuses on a two-stage control concept based on a target selector for optimal stationary control inputs and the dynamic controller considering the dynamic behavior of the air and exhaust gas recirculation paths. Subsequently, the control concept for the two-stage turbocharged spark-ignition engine with low pressure exhaust gas recirculation is validated via experimental tests under real-driving conditions on an automotive test track, using a prototype test vehicle. Results show that boost pressure as well as exhaust gas recirculation rate setpoints are met without overshoot and control deviation with settling times being close to the boundaries set by the hardware.

Keywords

Turbocharged gasoline engine sequential turbocharging low pressure exhaust gas recirculation model predictive control target selector data-based engine modeling

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References

Dingelstadt

Ewert

Werz

Tremble

. Potenziale der Abgasrückführung beim Ottomotor. MTZ Motortech 2014; 75(9): 56–61.

Moulin

Grondin

Fontvieille

. Control of a two stage turbocharger on a diesel engine. In: Proceedings of the 48h IEEE conference on decision and control (CDC), Shanghai, China, 15–18 December 2009, pp.5200–5206. New York: IEEE.

Chen

Wang

Chen

Ren

. Nonlinear model predictive controller design based on learning model for turbocharged gasoline engine of passenger vehicle. Mech Syst Signal Pr 2018; 109: 74–88.

Albin

Ritter

Liberda

Pischinger

Abel

. Two-stage turbocharged gasoline engines: experimental validation of model-based control. IFAC-PapersOnLine 2015; 48(15): 124–131.

Albin

Ritter

Liberda

Quirynen

Diehl

. In-vehicle realization of nonlinear MPC for gasoline two-stage turbocharging airpath control. IEEE Trans Contr Syst Technol 2018; 26(5): 1606–1618.

Xiao

Buckland

Karnik

. Frequency separation control of series sequential boosting system with electric supercharger and turbocharger. In: Dynamic systems and control conference, Tysons, VA, October 11–13, 2017. New York: American Society of Mechanical Engineers.

Bemporad

Bernardini

Long

Verdejo

. Model predictive control of turbocharged gasoline engines for mass production. SAE technical paper 2018-01-0875, 2018.

Wiese

Stefanopoulou

Buckland

Karnik

. Modelling and control of engine torque for short-circuit ﬂow and EGR evacuation. SAE technical paper 2017-01-0606, 2017.

Wiese

Stefanopoulou

Karnik

Buckland

. Model predictive control for low pressure exhaust gas recirculation with scavenging. In: 2017 American control conference (ACC), Seattle, WA, 24–26 May 2017, pp.3638–3643. New York: IEEE.

10.

Zhu

Koli

Feng

Onori

Prucka

. Nonlinear model predictive air path control for turbocharged SI engines with low pressure EGR and a continuous surge valve. In: 2017 American control conference (ACC), Seattle, WA, 24–26 May 2017, pp.4741–4746. New York: IEEE.

11.

Nuss

Wick

Andert

De Schutter

Diehl

Abel

Albin

. Nonlinear model predictive control of a discrete-cycle gasoline-controlled auto ignition engine model: simulative analysis. Int J Engine Res 2019; 20(10): 1025–1036.

12.

Ritter

Andert

Abel

Albin

. Model-based control of gasoline-controlled auto-ignition. Int J Engine Res 2017; 19(2): 189–201.

13.

Wick

Bedei

Gordon

Wouters

Lehrheuer

Nuss

, et al. In-cycle control for stabilization of homogeneous charge compression ignition combustion using direct water injection. Appl Energy 2019; 240: 1061–1074.

14.

Ritter

Korkmaz

Pitsch

Abel

Albin

. Optimization-based fuel injection rate digitalization for combustion rate shaping. In: 2019 American control conference (ACC), Philadelphia, PA, 10–12 July 2019, pp.5103–5110. New York: IEEE.

15.

Adomeit

Sehr

Glück

Wedowski

. Zweistuﬁge Turboauﬂadung — Konzept für hochaufgeladene Ottomotoren. MTZ Motortech 2010; 71(5): 362–367.

16.

Albin

Ritter

Liberda

Abel

. Boost pressure control strategy to account for transient behavior and pumping losses in a two-stage turbocharged air path concept. Energies 2016; 9(7): 530.

17.

Moulin

Chauvin

. Modeling and control of the air system of a turbocharged gasoline engine. Control Eng Pract 2011; 19(3): 287–297.

18.

Eriksson

Nielsen

. Modeling and control of engines and drivelines (Automotive series). Chichester: John Wiley, 2014.

19.

Isermann

Münchhof

. Identiﬁcation of dynamic systems: an introduction with applications. Heidelberg: Springer, 2010.

20.

Morari

Maeder

. Nonlinear offset-free model predictive control. Automatica 2012; 48(9): 2059–2067.

21.

Simon

. Optimal state estimation: Kalman, H infinity, and nonlinear approaches. Hoboken, NJ: John Wiley & Sons, 2006.

22.

Andersson

JAE

Gillis

Horn

Rawlings

Diehl

. CasADi: a software framework for nonlinear optimization and optimal control. Math Prog Comp 2019; 11: 1–36.

23.

Keviczky

Bars

Hetthssy

Bányász

. Control engineering. Cham: Springer-Verlag, 2018.

24.

Rawlings

Mayne

Diehl

. Model predictive control: theory, computation, and design. 2nd ed. Madison, WI: Nob Hill Publishing, LLC, 2017.

25.

Trimboli

Cairano

Bemporad

Kolmanovsky

. Model predictive control for automotive time-delay processes: an application to air-to-fuel ratio control. IFAC Proc Vol 2009; 42(14): 90–95.

26.

Domahidi

Jerez

. FORCES professional. Embotech AG, 2014–2019, https://embotech.com/FORCES-Pro.

27.

Zanelli

Domahidi

Jerez

Morari

. FORCES NLP: an efﬁcient implementation of interior-point methods for multistage nonlinear nonconvex programs. Int J Cont 2020; 93: 13–29.

28.

Diehl

Bock

Schlöder

. A real-time iteration scheme for nonlinear optimization in optimal feedback control. SIAM J Cont Optim 2005; 43: 1714–1736.