Dirk Abel

Model Predictive Control of a Parallel Hybrid Vehicle Drivetrain

Hybrid vehicles gain importance and attention as the need for more fuel-efficient propulsion concepts increases. This article describes the modelling and the control of the longitudinal dynamics of a hybrid vehicle with a parallel configuration. The key aspect of the displayed hybrid concept is the smooth but quick transition between pure electrical driving and hybrid driving which has to occur without interruption of the demanded driving power and jerk. A model predictive control concept is presented for solving this task.

LMI-based control of vehicle platoons for robust longitudinal guidance

Abstract This paper presents a novel approach to control layout for longitudinal guidance of platoons with a limited number of vehicles. It accounts for both the reduction of spacing errors and a limitation in velocities and accelerations of following vehicles to avoid saturations. All criteria can be expressed using a mixed H2/H∞ problem formulation. The objectives are formulated as one set of linear matrix inequalities that are solved for the controller. The optimization is presented for different control structures and the effectiveness of reducing overshoots in velocities or accelerations is shown through simulation results. This work also considers structural constraints concerning the information available to the controller and evaluates a sequential control algorithm applying the same layout method. Finally, the effects of changing parameters of the vehicles drivetrain are analyzed and robustness of the presented controllers is investigated.

A Model Based Predictive Attempt to Control Boost Pressure and EGR-Rate in a Heavy Duty Diesel Engine

Abstract this paper introduces a model based predictive attempt for simultaneous control of boost pressure and EGR-rate for a heavy duty diesel engine. The basic linear controller structure is extended with a gain scheduling approach to consider the non-linearities of the engine process. A mainly automated application procedure has been developed. This work is part of the project ATECS (Advanced Truck Engine Control System), founded by the European Community. In the course of the project non-linear simulation models of two truck diesel engines have been desgined in Matlab/Simulink® by the Institute of Automatic Control (IRT) of the Aachen University (RWTH) in cooperation with the Institute of Combusition Engines (VKA) of the Aachen University (RWTH). The control strategy has been tested in the simulation and has been implemented in cooperation with the VKA and the FEV on the test bench engine.

Semi-Solid Forging of 100Cr6 and X210CrW12 Steel

Semi-solid forging of the steel grades 100Cr6 and X210CrW12 reveals advantages compared to conventional manufacturing process technologies like casting and forging. These advantages result from the thixotropic flow behaviour prevailing when the material condition is varied. Two different strategies to generate a semi-solid precursor material are investigated. With the first strategy conventional rod material is inductively heated into the desired state and subsequently forged. For this purpose a fully automated semi-solid forging plant has been developed. The second strategy consists of producing the semi-solid precursor material directly from a slightly overheated melt with subsequent forced nucleation by means of a cooling slope. The results of the experimental work are presented and an outlook to both process variants is given.

LTV-MPC approach for lateral vehicle guidance by front steering at the limits of vehicle dynamics

In this paper, a linear time-varying model-based predictive controller (LTV-MPC) for lateral vehicle guidance by front steering is proposed. Due to the fact that this controller is designed in the scope of a Collision Avoidance System, it has to fulfill the requirement of an appropiate control performance at the limits of vehicle dynamics. To achieve this objective, the introduced approach employs estimations of the applied steering angle as well as the state variable trajectory to be used for successive linearization of the nonlinear prediction model over the prediction horizon. To evaluate the control performance, the proposed controller is compared to a LTV-MPC controller that uses linearizations of the nonlinear prediction model that remain unchanged over the prediction horizon. Simulation results show that an improved control performance can be achieved by the estimation based approach.

Combustion model reduction for diesel engine control design

Abstract The subject of this work is the derivation of a simulation model for premixed charge compression ignition (PCCI) combustion that can be used in closed-loop control development. For the high-pressure part of the engine cycle, a detailed three-dimensional computational fluid dynamics model is reduced to a stand-alone multi-zone chemistry model. This multi-zone chemistry model is extended by a mean value model accounting for the gas exchange losses. The resulting model is capable of describing PCCI combustion with stationary exactness, and is at the same time very economic with respect to computational costs. The model is further extended by the identified system dynamics that influence the stationary inputs. For this purporse, a Wiener model is set up that uses the stationary model as a non-linear system representation. In this way, a dynamic non-linear model for the representation of the controlled plant diesel engine is created.

Modeling and simulation of the cardiovascular system: a review of applications, methods, and potentials / Modellierung und Simulation des Herz-Kreislauf-Systems: ein Überblick zu Anwendungen, Methoden und Perspektiven

Abstract Proper function of the cardiovascular system is indispensible to human survival. However, this system is dominated by complex interactions between different physiological processes and control mechanisms. A structured analysis and a mathematical description of this system can provide more insight, and a computer-based simulation of dynamic processes in the cardiovascular system could be applied in numerous tasks. This article gives a review of different approaches to cardio-circulatory modeling and discusses methodological aspects and fields of application for several classes of models. Zusammenfassung Die Funktion des Herz-Kreislauf-Systems ist eine wichtige Voraussetzung für das Überleben des Menschen. Dieses System ist jedoch bestimmt von komplexen Wechselwirkungen zwischen verschiedensten physiologischen Prozessen und Regelungsmechanismen. Eine strukturierte mathematische Beschreibung und ein dynamisches Simulationsmodell können helfen, das Herz-Kreislauf-System besser zu verstehen. Dieser Artikel bietet einen Überblick zu verschiedenen Ansätzen in der kardiovaskulären Modellbildung und vergleicht methodische Aspekte und Anwendungsgebiete der einzelnen Modellarten.

Energy Management of Parallel Hybrid Electric Vehicles based on Stochastic Model Predictive Control

Abstract This paper proposes a control approach for the energy management of parallel hybrid electric vehicles based on stochastic model predictive control (SMPC). Apart from minimizing fuel consumption, the controller additionally accounts for CO 2 emissions. Considering the vehicles velocity to be time-varying, the limits for both propulsion machines of the hybrid vehicle are determined over a multiple prediction horizon. The stochastic approach has the advantage that the future driving profile does not have to be known in advance but is predicted based on an underlying stochastic model of the driver behavior. Simulation results obtained on standard driving cycles such as NEDC demonstrate the potential of the SMPC approach compared to a MPC controller with a-priori knowledge of the driving cycle.

An Instability of Diluted Lean Methane/Air Combustion: Modeling and Control

In order to study possibilities of Model Predictive Control (MPC) to low temperature combustion, the authors performed a numerical study of combustion with a lean highly diluted methane/air mixture in a perfectly stirred reactor using a detailed chemical kinetic model. Chosen conditions are the following: equivalence ratio 0.6, residence time of mixture in reactor 0.5 s; molar fraction of Nitrogen 0.9, temperature of incoming unburned gases and reactor 1100 K, and heat loss coefficient 2 × 10−3 cal/(cm2Ks). At these conditions strong oscillations are predicted in agreement with previous experimental findings of M. de Joannon et al. (2004). It is found that, at low temperatures (<1300 K), reactions forming CH3O and CH3O2 from CH3 had a strong influence on the oscillations. Once these reactions were subtracted from the kinetic model, no oscillations were observed. A virtual MPC suppressed the oscillations at low temperatures successfully and demonstrated extremely low NO and N2O emissions (<0.1 ppm).

Adaptive EKF-Based Vehicle State Estimation With Online Assessment of Local Observability

In this paper, an extended Kalman filter-based estimator adopting a dynamic vehicle model for determining the vehicles longitudinal and lateral velocity as well as the yaw rate is proposed. Two additional adaptation states are introduced to scale longitudinal and lateral tire forces if necessary to account for uncertainties in the tire/road contact. As excitation plays a vital role as far as observability is concerned, the suggested approach assesses local observability online and keeps an unobservable adaptation state constant by introducing the respective state as a virtual measurement variable when losing local observability. Furthermore, the filter is part of a Global Navigation Satellite System (GNSS)-based estimation framework. It exploits the availability of a GNSS-based horizontal velocity estimate instead of wheel speeds as aiding measurement, thus being independent of wheel slip. Experimental results for scenarios with different kinds of excitation show the effectiveness of the proposed estimator in the nominal as well as in the perturbed vehicle parameter case requiring filter adaptation.