Dennis Ritter

Nonlinear MPC for a two-stage turbocharged gasoline engine airpath

Innovative charging concepts such as two-stage turbocharging for gasoline engines, cause high demands on the process control due to the complex, nonlinear system behavior. For complex, nonlinear systems Nonlinear Model-based Predictive Controllers (NMPC) offer a high potential. They are capable of handling coupled multiple-input systems while achieving high control quality and respecting constraints of the system. In the case of turbocharging, considerations to protect components can introduce the necessity to constrain certain system values. This paper presents a two-stage turbocharged gasoline airpath modeling approach which is suited to be used in a NMPC implementation. The control implementation is based on direct optimal control using an online Sequential Quadratic Programming (SQP) type algorithm. For validating the control performance, simulations are conducted. The computation time of the algorithm is determined by implementation on a control prototyping platform for validation of the real-time capability.

Model Based Control of Gasoline Controlled Auto Ignition

Innovative low-temperature combustion modes for internal combustion engines, such as gasoline-controlled auto-ignition, impose very high requirements on the process control. On one hand, fast reference tracking for the engine load and the combustion phasing is needed, while at the same time, numerous disturbances acting on the highly sensitive process have to be rejected in order to guarantee stable operation at a wide operating range. Model-based predictive control concepts have a great potential to fulfill these requirements. In this contribution, a model-based predictive control consisting of a stationary and dynamic optimization stage is introduced. It is able to account for the characteristic cycle-to-cycle dynamics which occur in gasoline-controlled auto-ignition and also handle constraints imposed on the manipulated and controlled variables of the process.

In-Vehicle Realization of Nonlinear MPC for Gasoline Two-Stage Turbocharging Airpath Control

Innovative charging concepts, such as two-stage turbocharging for gasoline engines, cause high demands on the process control. The open-loop process is characterized by a complex, nonlinear system behavior. In addition, the requirements on the closed-loop system are challenging: fast reference tracking has to be achieved without overshoots while respecting constraints on the turbocharger speeds in order to prevent damaging of the components. Nonlinear model predictive control (NMPC) offers a high potential for this purpose. It is capable of handling coupled multiple-input systems while achieving high control quality and respecting constraints on system states. This paper presents an NMPC scheme for a two-stage turbocharged gasoline airpath, which is based on a physically driven reduced-order model formulated as a set of differential-algebraic equations. The online optimal control algorithm uses the real-time iteration scheme and is implemented on a control prototyping platform. For validation of the algorithm, it is tested based on simulations and vehicle experiments. These experiments have been conducted on a vehicle dynamometer as well as on an automotive testing track. For this purpose, a modified production vehicle is used in which the airpath concept is implemented.

Nonlinear MPC for Combustion Engine Control: A parameter study for realizing real-time feasibility

Nonlinear Model Predictive Control (NMPC) schemes offer the possibility to handle complex system dynamics and advanced requirements on control, such as the consideration of constraints for a multiple input multiple output system. The major bottleneck for these algorithms is the computation time. In this paper it is shown how the different ingredients of NMPC have to be designed such that a fast NMPC algorithm can be realized which allows real-time feasibility. As the numerical example, an engine control task is investigated with high demands on the control requirements. Fast reference tracking has to be realized, while respecting constraints on the system states to prevent damages. At the same time a very nonlinear behavior is present.

Reduced Order Modeling for Multi-scale Control of Low Temperature Combustion Engines

Internal combustion engines face tightening limits on pollutant and greenhouse gas emissions. Therefore, new solutions for clean combustion have to be found. Low Temperature Combustion is a promising technology in this regard, as it is able to reduce pollutant emissions while increasing the engine’s efficiency. Recent research has shown that closed-loop control manages to stabilize the process. Nevertheless, sensitivity to varying boundary conditions and a narrow operating range remain unfavorable. To investigate new control concepts such as in-cycle feedback, computationally feasible cycle-resolved models become necessary. This work presents a low order model for Gasoline Controlled Auto Ignition (GCAI) that is continuous in time and computes the pressure trace over the entire combustion cycle. A comparison between simulation and measurement supports the suitability of the modeling approach. Furthermore, the model captures the characteristic transition of system dynamics in case GCAI during late combustion.

Modellbasierte Regelung einer zweistufigen Abgasturboaufladung für einen Ottomotor

Zusammenfassung Zur Wirkungsgradsteigerung von Verbrennungsmotoren spielen verbesserte Luftpfadkonzepte eine Schlüsselrolle. Insbesondere für Ottomotoren stellt das Konzept der zweistufigen Abgasturboaufladung eine vielversprechende Technologie dar. In diesem Beitrag wird die Regelung eines solchen Luftpfadkonzeptes untersucht. Dabei handelt es sich um einen Modellbasierten Prädiktiven Regelungsansatz, der in der Lage ist, den Mehrgrößencharakter des Regelungsproblems zu handhaben, die inhärente Totzeit des Systems zu kompensieren und Limitierungen für die Drehzahlen der beiden Turboladerstufen zu berücksichtigen. Desweiteren wird der Applikationsaufwand zur Parametrierung der Regelung verringert. Das untersuchte Regelungskonzept wurde für ein Versuchsfahrzeug mit dem beschriebenen Aufladekonzept auf einem Prototypen-Steuergerät implementiert und auf einem Abgasrollenprüfstand validiert.

Hybrid multi-objective MPC for fuel-efficient PCCI engine control

In the present paper the closed-loop control of an innovative combustion engine is investigated. The investigated combustion engine is characterized by the ability of handling different combustion modes, such as Premixed Charge Compression Ignition (PCCI), which are applied depending on the operating point. In the paper the challenges related to the increased complexity of the control algorithm and the corresponding calibration effort are addressed. For this reason a tailored hybrid multi-objective MPC algorithm is developed based on a piecewise affine (PWA) model. The MPC algorithm consists of a 2-staged approach, including a stationary and a dynamic optimization. With this algorithm a nonlinear optimization is performed in every time step considering the task of tracking reference values and minimizing values i.e. fuel consumption, such that the optimal combustion mode is chosen automatically. The developed algorithm is finally validated in simulation.