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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.

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.

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.

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.

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.

In the scope of a research collaboration, Continental Teves (formerly ITT Automotive Europe) and Darmstadt University of Technology are developing control strategies for a low-cost Brake-by-Wire system, using no clamping-force or brake-torque sensor as feedback [1]. 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 Continental Teves' third generation brake actuator, which is still operated using an integrated clamping force sensor [2]. It introduces the development environment of Darmstadt University of Technology, consisting of a brake test stand, a complex brake actuator model, and a simplified brake actuator model.

The advancing electrification of the powertrain is giving rise to new challenges in the field of acoustics. Film capacitors used in power electronics are a potential source of high-frequency interfering noise since they are exposed to voltage harmonics. These voltage harmonics are caused by semiconductor switching operations that are necessary to convert the DC voltage of the battery into three-phase alternating current for an electrical machine. In order to predict the acoustic characteristics of the DC-link capacitor at an early stage of development, a multiphysical chain of effects has to be addressed to consider electrical and mechanical influences. In this paper, a new method to evaluate the excitation amplitude of film capacitor windings is presented. The corresponding amplitudes are calculated via an analytical strain based on electromechanical couplings of the dielectric within film capacitors.

Icing is a major hazard for aviation safety. Over the last decades an additional risk has been identified when flying in clouds with high concentrations of ice-crystals where ice accretion may occur on warm parts of the engine core, resulting in engine incidents such as loss of engine thrust, strong vibrations, blade damage, or even the inability to restart engines. Performing physical engine tests in icing wind tunnels is extremely challenging, therefore, the need for numerical simulation tools able to accurately predict ICI (Ice Crystal Icing) is urgent and paramount for the aeronautics industry, especially regarding the development of new generation engines (UHBR = Ultra High Bypass Ratio, CROR = Counter rotating Open Rotor, ATP = Advanced Turboprop) for which analysis methods largely based on previous engines experience may be less and less applicable. The European research project MUSIC-haic has been conceived to fill this gap and has started in September 2018.