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The increasing complexity of distributed embedded systems, as found today in airplanes or cars, becomes more and more a critical cost-factor for their development. Model-based approaches have recently demonstrated their potential for both improving and accelerating (software) development processes. Therefore, in the project DECOS1, which aims at improving system architectures and development of distributed safety-critical embedded systems, an integrated, model-driven tool-chain is established, accompanying the system development process from design to deployment. This paper gives an overview of this tool-chain and outlines important design decisions and features.

In this paper we present an advanced knock detection approach. The detection concept consists of a two-level feature extraction step followed by neural network detector. A knock tendency index is estimated that takes into account the statistical behavior of the knock phenomena. The configuration of the neural network is based on a signal database that was acquired under almost ‘on-road’ conditions. The experimental set-up consisted of several measurement sessions in a special vehicle test cell. In order to achieve a most realistic knock database the test engine was mounted on an in-production car.

In the scope of a research collaboration, ITT Automotive Europe and Darmstadt University of Technology are developing control strategies for a low-cost Brake-by-Wire system. However, since there is a wide range of variation in the efficiency of the gear units used in electromechanical brakes, this becomes a demanding task. The paper first describes the assembly and operation of ITT's early generation brake actuator. It introduces a model of the electromechanical brake with its structure and subsystems as a major tool in the development process. A detailed analysis of the signals, already available from the brake and the vehicle, is discussed for their advantages and disadvantages with regard to a possible use in the controller design. Different approaches for clamping-force, peripheral-force and brake-torque sensing are compared. An integrated clamping force sensor for feedback control of prototype actuators was developed.

Faced with the need to reduce development time and cost, the hardware-in-the-loop (HIL) simulation increasingly proves to be an efficient tool in the automotive industry. It offers the possibility to investigate new engine control systems with fewer expensive engine dynamometer experiments and test drives. In the scope of a research collaboration, Daimler Benz and Darmstadt University of Technology are developing a hardware-in-the loop simulator for the investigation of the electronic engine management of the new Mercedes Benz truck engine series 500 and 900. This paper first describes the necessary models for real-time simulation of the subsystems Diesel engine, turbo charger and vehicle. Then the setup of the simulator test bench is introduced and the performance of the simulator is demonstrated by several experimental results.

This paper deals with physical modelling of a turbocharger with variable turbine geometry (VTG) and its real-time simulation based on dynamic artificial neural networks (ANN). Thermodynamic und fluiddynamic equations, describing the basic functionality and relations between pressure, mass flow and temperature at the inlet and outlet ports of compressor and turbine, build up a multiple input multiple output model (MIMO). A special kind of ANN, namely the LoLiMoT algorithm, is used for real-time simulation. Training the network using measurement and simulated data, the dynamic behaviour can be simulated with less computational effort than the physical model. The neural network may be used in engine control systems as observer for non measurable signals, like rotor speed or turbine and compressor torque, figure 1.

This paper illustrates the essential safety aspects of tools rotating at high speed. Based on a load analysis, the various types of tool failure are represented and are evaluated with respect to their hazard potential. Analytical calculation approaches and numerical methods are discussed as means for a safe design of such tools. On the basis of experimental results, concrete design aids for the tool design engineer are derived.

In the present work we investigated experimentally and computationally the unsteady flow around a BMW car model including wheels*. This simulation yields mean flow and turbulence fields, enabling the study aerodynamic coefficients (drag and lift coefficients, three-dimensional/spatial wall-pressure distribution) as well as some unsteady flow phenomena in the car wake (analysis of the vortex shedding frequency). Comparisons with experimental findings are presented. The computational approach used is based on solving the complete transient Reynolds-Averaged Navier-Stokes (TRANS) equations. Special attention is devoted to turbulence modelling and the near-wall treatment of turbulence. The flow calculations were performed using a robust, eddy-viscosity-based ζ - ƒ turbulence model in the framework of the elliptic relaxation concept and in conjunction with the universal wall treatment, combining integration up to the wall and wall functions.

Since 1989 the Automotive Engineering Department of Darmstadt University of Technology (fzd) has carried out measurements of tire tread deformations through the use of sensors which are integrated into the tire. With these tire sensors fzd has achieved the possibility to qualitatively and quantitatively measure forces acting on the tire, especially local slip effects, which are the basis for friction detection. To investigate local slip fzd designed a completely new measuring device. Utilization of available tire/road friction and local slip events were measured in a specially equipped test car. This paper describes the Darmstadt Tire Sensor, the theoretical vehicle system, the methods to study tire sensor behaviour as well as the results achieved so far.

As a consequence of the integration of additional systems to support and entertain drivers and passengers the interactions with those systems become more and more time consuming and distracting. It is therefore a basic requirement for the design of Human Machine-Interfaces to minimize the distraction from driving when interacting with those new assistance and entertainment systems. Whereas the safety is a Must-be for the design of HMI for automobiles the joy-of-use is an important aspect for the excitement of drivers. To fulfil the sometimes conflicting demands for safety and pleasure a human centred design approach for HMI design is needed.

Future on-board vehicle control systems can be further improved through new types of mechatronic systems. In particular, these systems'' capacities for interaction enhance safety, comfort and economic viability. The Automotive Engineering Department (fzd) of Darmstadt University of Technology is engaged in research of the mechatronic vehicle corner, which consists of three subsystems: sensor tire, electrically actuated wheel brake and smart suspension. By intercommunication of these three systems, the brake controller receives direct, fast and permanent information about dynamic events in the tire contact area provided by the tire sensor as valuable control input. This allows to control operation conditions of each wheel brake. The information provided by the tire sensor for example helps to distinguish between straightline driving and cornering as well as to determine μ-split conditions.

For the development of sophisticated digital (e.g., Finite-Element-models like CASIMIR) or physical (e.g.,ASPECT-Dummy) models of the mechanisms of human-seat-interaction it is very important to know the shape of the contact surface between the human buttocks and back and the seat cushion and backrest, respectively. Currently, these surfaces are usually determined by purely experimental procedures, that require complicated and expensive measuring equipment. This paper presents an alternative hybrid approach of standard experimental investigations of the pressure distributions between human body and seat (cushion and backrest) and proceeding numerical simulations with the Finite-Element-Method (FEM). Pressure distributions are measured with standard measuring equipment for individual persons or defined percentile groups. Due to the simplicity of these measurements, they can be performed for a larger number of individuals at low cost.

The use of model based approaches in areas such as simulation, control design, optimization, etc. is crucial for the development of highly sophisticated systems. This is especially true for typically very tight time-to-market frames. Physical modeling of IC engine emissions based on first principles is extremely complex and still requires by far too much calculation time. However, special fast neural networks represent a promising alternative for an accurate modeling of the emission behavior, even for dynamic conditions. This paper first describes the process of developing dynamic neural emission models. The required data is collected by a specially designed dynamic measurement strategy. The models themselves are then used for the optimization of the dynamic engine behavior concerning consumption, emissions and drivability.

Present and future assisting systems are meant to support the driver in coping with the difficulties of driving. The design of the system properties and their limits helps to influence on the road-driving behavior directly and through teach-back effects. On the other hand, there is a potential risk of negative effects on the safety due to a division of tasks between the driver and the technical system. Bearing this in mind, the Automotive Engineering Department and the Department of Ergonomics of Darmstadt University of Technology were engaged by BMW AG to investigate the distance behavior of vehicles with and without ACC (Adaptive Cruise Control) which is used to control the speed and distance maintained to vehicles ahead and turning into the traffic. This trial was made with the aim of a representative and objective investigation of the behavior of the total system of driver-vehicle-environment in road traffic.

Fault detection is increasingly an essential part of vehicle development. Integrating such fault detection subsystems raises the reliability, maintainability, and safety of automobile components. Weak shock absorbers can lead to significantly longer braking distances (up to 20%) and furthermore worsen the driving handling. Reduced tire pressure increases the wear of the tire dramatically and may lead to punctures due to an overheating of the tire. Recent studies show that 40% of all drivers have set wrong tire pressures (Wachter, 1994). Therefore, this paper presents fault detection algorithms for the suspension system implemented on a Hitachi SH7055 microcontroller. Real measurements of a vehicle are made to proof the algorithms.

Due to more severe exhaust gas regulations with sharper exhaust gas limitations and rising requirements for on-board diagnosis in this contribution a method for injection mass supervision in diesel engines using a fast broadband oxygen sensor will be presented. Based on a physical model the injected fuel mass can be determined by evaluating the measured air mass and oxygen concentration in the exhaust gas. Cylinder individual injection mass calculation becomes possible using an inverse model of the oxygen sensor dynamic. Thereby the sensor dynamic is specified by evaluating step responses of the oxygen concentration at jumps of the injection mass. For cylinder assignment the runtimes of the exhaust gas in the exhaust pipe have to be determined. They result from the calculation of the cross correlation function of the reconstructed fuel mass and measured mean indicated cylinder pressure.

Methods for model-based fault detection are presented which detect a wide range of faults using only common production sensors, namely air mass sensor, manifold pressure sensor, manifold temperature sensor and engine speed. Five suitable reference models for fault detection are set up and identified at the test stand. The developed fault detection algorithms use the dependencies of the four sensor signals based on the reference models. Thereby five residuals and five symptoms are calculated. The model-based fault detection algorithms are implemented with a dSPACE Rapid Control Prototyping system and verified at the test stand. Measurements of online fault detection are shown.

Automotive engineering requires dynamic system simulation software. To meet future legislated emission and con-sumption standards, a vehicle has to be considered as a group of interacting systems. NAGREMA is an automotive simulation software with the focal point on the accessory drive. Variations of the standard V-belt configuration can be compared with decentralized approaches using electric or electro-hydraulic drives. NAGREMA is implemented using MATLAB/Simulink, provides a graphical user interface and a set of vehicle, engine and accessory templates. It reduces model complexity by dividing the vehicle, the engine, the accessory drive and the control system into hierarchically organized subsystems.

This paper describes an approach of how to control the wheel slip of a vehicle using brake-by-wire actuators. The advantage of brake-by-wire actuators - such as the electro-hydraulic (EHB) and the electro-mechanical brake (EMB) - is that the caliper pressure or the clamping force, respectively, are known. It will be shown by measurement results that the wheels of a research vehicle equipped with an EHB system and the new control approach can be kept at any desired wheel slip on different surfaces, i.e. ice, snow, and dry asphalt.

Because of increasing requirements for low emissions and fuel consumption, combustion engines are getting more and more control inputs, like multiple injection, exhaust gas recirculation (EGR), turbocharger valve position (TVP), variable valve timing (VVT), etc. With the addition of manipulated variables, the required measurement time for obtaining the steady-state characteristics and control look-up tables rises exponentially. A comprehensive design of the measurement experiment is becoming more and more essential. The objective is to measure the engine characteristics and properties with a minimum number of measurement points (with firstly concentrating on the stationary behavior). A new methodology is presented to automatically determine characteristic mappings by incorporating prior knowledge. Since physical modeling of the engine behavior is mostly not appropriate, prior knowledge for experimental design is derived by evaluating measurement data.

For the cylinder-selective monitoring of combustion cycles in spark-ignition engines, the dynamic exhaust-gas pressure is analyzed. A time domain based diagnostic system for misfire detection has been developed and tested on data measured in a BMW 750i, V-12 engine. It uses features of the suitable low-pass-filtered exhaust-gas pressure signal by calculating differences of the locally determined extrema. For the detection and localization of all misfire combinations a simple inference system in the form of linguistic rules is used. It is shown that even within the operating areas of high engine speeds and low loads on engines with a high number of cylinders good classification rates can be obtained.