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Faults in the intake and exhaust path of turbocharged common-rail Diesel engines can lead to an increase of emissions and performance losses. Standard fault detection strategies based on plausibility checks and trend checking of sensor data are not able to detect and isolate all faults appearing in the intake and exhaust path without employing additional sensors. By applying model based methods a limited sensor configuration can be used for fault detection. Therefore a model based fault diagnosis concept with parity equations is considered, [1]. In this contribution the fault diagnosis system, which comprises semi-physical thermodynamic turbocharger model, models of gas pressure in the intake and exhaust manifold, residual generation, residual to symptom transformation and fault diagnosis is presented.

The complexity of the air path of modern common rail diesel engines is rapidly increasing and simultaneously, the demand on air and turbocharger control performances is becoming more challenging. To meet the upcoming emission regulations, the usage of a low pressure exhaust gas recirculation (EGR) circuit in addition to the standard high pressure EGR circuit is often considered. This kind of architecture usually requires a more sophisticated air control system in which a precise control of the EGR flow delivered by the two recirculation branches is required. Moreover, as an alternative or in addition to the low pressure EGR, the implementation of a NOx reduction system e.g. a NOx trap is possible. To proper maintain the correct efficiency of this kind of after-treatment system, special regeneration strategies are adopted where a rich combustion is used instead of the standard Diesel lean mode.

Faults in the intake and exhaust path of turbocharged common-rail diesel engines lead to an increase of emissions and to performance losses. Fault detection strategies based on plausibility checks, threshold based trend or limit checking of sensor data are not able to detect and isolate all faults appearing in the intake and exhaust path without increasing of the number of sensors. The need to minimize mass and reduce cost, including the number of sensors, while maintaining robust performance leads to higher application of models for intake and exhaust path components. Therefore a concept of model based fault detection with parity equations is considered. It contains the following parts: modeling, residual generation with parity equations using parallel nonlinear models, fault to symptom transformation with masking of residuals dependent on the operating point and limit violation checking of the residuals.

Physical based air path models lead to a substructuring of the highly complex engine systems into several interacting submodels of low order. They offer detailed process information, support advanced control system design and allow to significantly reduce the calibration effort. Hence, physical approaches are predestinated to cope with the rise in system complexity and with the increasingly challenging demands concerning air system performance. Whereas the basic model equations are known a general methodology to obtain the model parameters is lacking. The purpose of this paper is to shed light on the identification procedure and to offer the automotive engineer helpful advice to gain well calibrated simulation models. Analysing the air path equations the determining factors on the parameter quality are investigated. Based on the results sensible modifications of the test bed setup and the measurement strategy are presented.

To reduce accidents and fatalities on the roads, active safety systems which can avoid accidents or mitigate their effects are increasingly required. Contrary to already available driver assistance systems a future system can be a Collision Avoidance System which will be able to solve many critical traffic situations by warning, braking or steering. This paper will present a system consisting of environment sensing and situation analysis blocks as well as intervening strategy blocks. The main focus will be put on the scene interpretation of a situation and its optimization. Therefore a rule-based Fuzzy System will be described. Furthermore the Strategy Selection and the Path Planning in case of system intervention will be shown by simulation. The system has been developed during the work at the Adam Opel GmbH.

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.

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.

Cylinder pressure signals contain valuable information for closed loop engine control. For using this information low-cost cylinder pressure sensors with high long-term stability have been developed and are starting to be installed into production engines [1,2,3,4]. This paper presents new algorithms to estimate cylinder air mass, to control exhaust gas recirculation and to estimate the air-fuel ratio distribution between different cylinders of a SI engine. The proposed control algorithms avoid additional calibration expense by using adaptive, model based control strategies and learning feed-forward control. They have been implemented on a dSPACE rapid control prototyping system [5] and have been evaluated through studies using a 1.0 liter 3 cylinder SI engine on a dynamic engine test stand.

In the near future, technical demands for powerful electric motors integrated into the drive train can be fulfilled. These motors combine the functionality of starter and alternator offering a higher electric power than conventional alternators. At low engine speed, they can work as a motor and introduce an additional driving torque in the drive train (booster). The required introduction of suitable electrical storage devices enables regenerative braking to reduce fuel consumption significantly. In this paper, for homologation tests and customer use, the potential savings of regenerative braking are shown for a variety of engines, vehicles and test cycles.

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.

Modern Diesel injection systems have to serve different demands. Beside the improvement of the injection timing and assignment special concentration is focused on increasing injection pressure to improve combustion and lower exhaust gas emissions. With the higher complexity of these systems and the high burden on the pump components especially in the high pressure part of the injection pumps, the wish for supervision of delicate components occurs. Therefore suitable and efficient supervision methods have to be developed to early detect initiating faults. Because of the correlation between combustion and injection, one way to detect faults in the injection system is to supervise the combustion in the individual cylinders. This can be done by evaluating the crankshaft speed at the flywheel. Speed is directly related to combustion by the indicated pressure and the indicated torque respectively, the crankshaft drive and the resulting torque at the crankshaft.

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.