This paper reviews the research activities within the subproject B1 Model Reduction for Low-Temperature Combustion Processes through CFD-Simulations and Multi-Zone Models of the Collaborative Research Centre SFB 686 – Model-Based Control of Homogenized Low-Temperature Combustion. The SFB 686 is carried out at RWTH Aachen University, Germany and Bielefeld University, Germany, and is funded by the German Research Foundation (DFG). This paper thereby summarizes the outcome of various publications by the authors, with the appropriate references given in the individual sections. Additionally, some new results are introduced. The particular subject of this work is a dynamic simulation strategy for premixed charge compression ignition (PCCI) combustion that can be used in closed-loop control development. A detailed multi-zone chemistry model for the high-pressure part of the engine cycle is extended by a mean value gas exchange model accounting for the low-pressure part. Thus, an efficient model capable of describing PCCI combustion is sufficiently well established. In order to capture cycle-to-cycle dynamics, identified system dynamics influencing the input parameters are incorporated. For this, a Wiener model is set up that uses the combustion model as a nonlinear system representation. In this way, a dynamic nonlinear model for the representation of the controlled plant Diesel engine is created. The model is validated against transient experimental engine data.

Recent research in modern combustion technologies, like partial homogeneous charge compression ignition (PCCI), demonstrates the capability of reducing pollutant emissions, e.g. soot and NOX. In addition to this advantage, a possibility to reduce fuel consumption and noise production by model-based optimal control is presented in this paper. In order to understand the basic properties of the PCCI mode, process measurements were conducted using a slightly modified series diesel engine. Control variables are engine combustion parameters: the indicated mean effective pressure, the combustion average and the maximum gradient of the cylinder-pressure. Control inputs are the parameters: quantity of injected fuel, start of injection and the intake manifold fraction of recirculated exhaust gas. The process has very fast, almost proportional behaviour over the engine's working cycles. Focusing on the static behaviour of the process, a nonlinear neural network model is used for identification. Successive linearization of the nonlinear network is used to build an affine internal controller model for the actual operating point. The presented controller structure is able to consider constraints by individual formulation of the cost function. With this configuration the closed-loop process is able to track the combustion setpoints with high control quality with minimal possible fuel consumption and combustion noise.

In this paper, a hybrid control approach for low temperature combustion engines is presented. The identification as well as the controller design are demonstrated. In order to identify piecewise affine models, we propose to use correlation clustering algorithms, which are developed and used in the field of data mining. We outline the identification of the low temperature combustion engine from measurement data based on correlation clustering. The output of the identified model reproduces the measurement data of the engine very well. Based on this piecewise affine model of the process, a hybrid model predictive controller is considered. It can be shown that the hybrid controller is able to produce better control results than a model predictive controller using a single linear model. The main advantage is that the hybrid controller is able to manage the system characteristics of different operating points for each prediction step.

New combustion methods for engines have been recently researched very intensively. In diesel engines, the homogenisation of the air-fuel mixture by early fuel injection has significant effects on emission reduction. The paper presents a model-based optimal control strategy for premixed charge compression ignition (PCCI) low temperature combustion in diesel engines. In order to understand the basic properties of the PCCI mode, static and dynamic measurements were conducted using a real conventional diesel engine. The main inputs of the combustion process are the exhaust gas recirculation rate and injection parameters. Outputs are the indicated mean effective pressure and the fuel mass conversion balance point. The process has very fast, almost proportional dynamics over the engine's working cycles. Focusing on the static behaviour of the process, a nonlinear neural network model is used for identification. Successive linearisation of the nonlinear network is used as predictive controller model. The presented controller structure is able to consider constraints and can be computed very fast. Finally, the controller is validated under real time conditions by experimental tests at the engine test bench. Although the controller structure contains a model and a convex optimisation step with regards to constraints, its implementation is very simple, as no observer is used, and the linearised model consists of static gains only.

When developing software-based control systems, knowledge and experiences in the relevant domain are of great importance. Small- and medium-sized enterprises (SMEs) that are most active here need to capture requirements under severe time and costs pressures. In previous work we have shown that a domain model based on the requirements formalism i* accelerates the requirements capture. Furthermore, the domain model-based similarity search supports the detection of reusable components from earlier projects. But due to the innovativeness, flexibility, and customer-orientation of control systems development, this domain model is subject to continuous change. Within this paper, we investigate the effects of model evolution on our domain model-based requirements engineering approach. Building on examples from industrial practice, we develop a classification of possible domain model modifications. For each such class, we analyze its impact on the similarity search and derive appropriate counter measures to limit these harmful impacts.

Subject of this work is a simulation model for PCCI combustion that can be used in closed-loop control development. A detailed multi-zone chemistry model for the high-pressure part of the engine cycle is extended by a mean value model accounting for the gas exchange losses. The resulting model is capable of describing PCCI combustion with stationary excactness. It is at the same time very economic with respect to computational costs. The model is further extended by identified system dynamics influencing the stationary inputs. For this, a Wiener model is set up that uses the stationary model as a nonlinear system representation. In this way, a dynamic nonlinear model for the representation of the controlled plant Diesel engine is created.

This article describes the development of a fast model predictive controller (MPC) for the air path of a diesel combustion engine. A basically fundamental model with a couple of measurement driven parts forms a nonlinear observer within an MPC. An online linearization algorithm allows a successive update of the linear model used for the prediction step and furthermore for the optimization to get the control input corrections. Two methods are presented to solve the used objective function - the analytical way and the application of a QP solver with the possibility to include constraints. For controller validation experimental tests with a diesel engine in PCCI (partial charge compression ignition) mode are made.

Hybrid Electrical Vehicles (HEV) are a very promising approach to save fuel and minimize exhaust emissions. The drive trains of HEV are equipped with at least one Electric Machine (EM) in addition to the Internal Combustion Engine (ICE). Therefore it is possible to operate the Internal Combustion Engine (ICE) in more efficient working points or to shut it down if the efficiency is too low. Despite of the fuel savings, the drivability can be increased by realizing gear shifts without an intermission in the wheel torque or a noticeable jerk. An important task for the HEV control is the start and the coupling of the ICE during electrical driving. This task has to also be done without an intermission in the wheel torque or a noticeable jerk to obtain a good drivability. In this paper we will describe a feedforward control for the launch clutch of a parallel HEV (pHEV) with an Automated Manual Transmission (AMT) and a dry clutch. The feedforward control is obtained using a simplified model of the drivetrain.

Since nowadays more and more control systems are realised within software on electronic control units, a conceptual integration of control systems engineering and software engineering must be aimed at. Within this work, we build on a proposal to use the software requirements formalism i* to enable a combined investigation of control systems' and software requirements. While i*'s modelling means have turned out to be sufficiently expressive, two characteristics of control systems still need to be addressed: firstly, how to incorporate domain knowledge especially about the system to be controlled in the requirements development process and secondly, how to specifically support small and medium-sized companies (SMEs) that are the main driver for innovations in this domain. Due to their innovativeness and flexibility, the SMEs usually follow a project-oriented customer-specific development approach. To be nonetheless cost-effective, especially during the offer development phase, we develop a mechanism and a tool to compare a current requirements model with requirements models of control systems from earlier projects. Altogether this reduces time and increases reliability in regard to the identification of reusable software artefacts.

Regelungstechnik und Softwaretechnik haben sich uber lange Zeit getrennt voneinander entwickelt. Aber immer haufiger werden heute Reglerfunktionen, etwa im Fahrzeug, in Software realisiert. Im Projekt ZAMOMO wird versucht, die immer noch getrennten Entwicklungsprozesse besser miteinander zu verzahnen. In diesem Beitrag wird dazu ein zielorientiertes Rahmenwerk zur Erfassung von Anforderungen aus der Softwaretechnik, i*, auf seine Eignung fur die Erfassung regelungstechnischer Probleme untersucht. Des Weiteren werden resultierende Herausforderungen fur die Werkzeugunterstutzung diskutiert. Insgesamt ermoglicht der Ansatz, die bereits weitreichend modellbasierte Reglerentwicklung auch in der Anforderungserfassung modellbasiert zu unterstutzen und zugleich den Weg fur eine gemeinsame Betrachtung regelungstechnischer und softwaretechnischer Anforderungen zu ebnen.

⊎ IT-Systemen für Automobile und für betriebliche Anwendungen haben sich sehr unterschiedlich entwickelt.

Applications in the automobile sector, wired or unwired, are today often integrated into a network of sensors and actors as well as in service functions, visualization, and entertainment. The paper presents an innovative platform, which is applicable for automative and automation applications.IT systems for autombiles and for business applications took a very different development direction.In the automotive sector a lot of proprietary IT systems have been developed.The increasing requirements of automotive applications require platform concepts, which are based on open standards.

We declare that the above specified devices are compliant with the regulations of the European Community, in terms of the design and the version fabricated by SMA. This especially applies for the EMC Regulation defined in 89/336/EWG and the low voltage regulation defined in 73/23/EWG.