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Today's vehicle networks are mainly based on the event-triggered CAN-bus. In future FlexRay, which is a TDMA-based bus, will more and more be used for the implementation of safety-relevant real-time systems due to its determinism. In order to configure a CAN-based network the priorities of the messages sending via the external bus have to be defined. In this paper an approach will be presented allowing automated priority determination. Subsequently it will be shown how to adapt this method to automated cycle configuration in case of a FlexRay-based system. In order to ensure determinism not only in TDMA-based but also in event-triggered networks, a method will be presented adapting priorities of messages intending to exceed their deadline. This can be easily realized without changing the CAN protocol.

The integration of a Dual Mass Flywheel (DMF) in the conventional vehicle driveline leads to various benefits, and hence today it has established its position in many passenger cars and light trucks. Transmission and driveline oscillations are reduced by mechanically decoupling the transmission from the periodic combustion events that excite the engine crankshaft, improving driving comfort and reducing transmission stresses. For systems with conventional single mass flywheel (SMF) reliable engine control systems have already been developed. However, the complexity of the driveline increases with the integration of a DMF. Hence, in the future conventional engine control systems may require adaptation, modification or even replacement, in order to guarantee the optimal control of engines equipped with advanced DMF systems.

Today, in many passenger cars and light trucks, the conventional driveline is extended by a dual mass flywheel (DMF). The DMF reduces driveline oscillations by mechanically decoupling the crankshaft and the transmission. Existing engine control systems are general designed for use with conventional single mass flywheel (SMF) systems. In the future, to facilitate the optimal control of engines equipped with advanced DMF systems, these conventional control systems may require adaptation, modification or even replacement. In the past, misfire detection has been done by expensive dedicated sensors; seismic, ion current measurement at the spark plugs or even by measuring in-cylinder pressures directly. Typically misfire detection is performed using signals derived from the crankshaft position sensor, which works well for engines with a limited number of cylinders and which are connected to relatively simply drivelines.

In this paper two new approaches are presented how to partition an amount of functions distributed in automotive electronic systems. In contrast to common partitioning algorithms as Kernighan-Lin, Best-Gain-First, Simulated-Annealing, a.s.o., these algorithms are real multi-partitioning ones. With respect to ECU (electronic control unit) characteristics, the software functions to be partitioned will be allocated automatically onto the available hardware. Main motivation is the reduction of the resulting bus-load which is provoked by the communication between such functions. Moreover these algorithms optimize the final partitioning solution to achieve a reduced number of ECUs. Reducing bus-load and the number of ECUs can lead to significant cost reduction. In order to validate partitioning results, a CAN as well as a FlexRay model was developed in Matlab/Simulink determining the bus-load over time.

Electronic systems in vehicles characteristically consist of several distributed electronic control units (ECUs) from different suppliers. This situation hinders the integration of automotive systems and increases the overall costs due to individual solutions coming from each supplier. In order to get rid of these disadvantages, the French-German project OSEK/VDX was founded and is now drawing attention worldwide. OSEK/VDX worked out a respective specification to standardize services and protocols of communication, network management and a real-time operating system. An overview of the current state of OSEK/VDX including specifications and harmonization process with ISO is given. Furthermore a description of the Modistarc project working on methodologies and tools for conformance testing of commercial OSEK/VDX implementations is contained.

One goal of modern power train control systems in heavy trucks is to damp driveline oscillations using appropriate controllers. Modern control algorithms like state-space controllers are based on a state-space model, which should accurately characterize the real process behavior. Otherwise, optimal control can not be guaranteed. These state-space models include a huge number of parameters, which have to be identified by an identification process. However, existing driveline models contain two serious problems: an increasing offset over time between measured and simulated data and an inadequate detection of the longitudinal dynamics of the truck. Therefore, this article deals with two goals: to optimize the offline identification process for the special use in driveline systems and to establish an online adaptation of the model parameters to guarantee an optimal model fit.

There are a number of tools available to assist the engineer during the automotive electronics design process, for example when transferring a graphical specification to a real time rapid prototyping environment. One step in this tool chain however is largely ignored by automated design tools: mapping a large monolithic model to a distributed system, more specifically the mapping of several functions on only a few electronic control units (ECUs) which are connected by a bus. In this paper we will present a method to analyze the underlying functional structure of a given model, partition it using a heuristic algorithm and verify the results with a model of the CAN bus. Based on a given functional model, we will show how to extract an algebraic representation of the communication behavior, the adjacency matrix. Using the adjacency matrix, the heuristic algorithm Best Gain First can be applied to map functions to ECUs.

Future vehicle electrical systems will differ substantially from current ones due to rising requirements. For example driver-assistance and drive-by-wire systems will lead to novel and demanding electrical load profiles which in turn will pose new requirements on the electrical system. Furthermore safety concepts, reliability, availability and diagnosis are getting increasingly important in such systems and thus also in the vehicle's electrical system. In order to meet the upcoming requirements new concepts for future vehicle electrical systems have to be developed such that the new powernet is able to adapt flexibly to different situations or failures by routing the energy through different channels. For efficiency the corresponding development process should be based on modeling and simulation techniques. Depending on the design or analysis task, the powernet is represented through different modeling descriptions.

As future drive-by-wire systems have no mechanical fallback level, the increased safety requirements need to be met by software-based solutions. The task of the software is to provide services in the field of fault detection and compensation as well as control of redundant hardware structures. Particularly the implementation of fault detection and error correction avoids fatal output of drive-by-wire control units caused by erroneous input signals. This article describes the implementation of a module compensating faults in the input signals of a vehicle function, which controls the longitudinal dynamics of a truck. The error correction is achieved by means of data fusion. Sensing units consisting of the sensor as well as the preprocessing unit often are provided by external suppliers. In some cases information regarding the characteristics of their output data written on the CAN bus is not available.

This paper treats the complete robust H∞ controllers design. The whole synthesis is exemplified by the idle speed control problem at passenger cars and light trucks. Subsequently the robustness of the designed controller is tested and compared to conventional P and PI controllers. The main steps of controller synthesis are described detailed in this work. First, a closed loop structure has to be chosen. For this purpose, basic principles will be introduced. After this, the weighting matrices for the cost functions have to be defined. Finally, the choice of the calculation algorithm is important. In this approach, the idle speed control is done with the Mixed-Sensitivity design and a derivation of the Doyle-Glover (DGKF) algorithm. The choice for the weighting matrices is depicted clearly in the frequency domain. Finally, a comparison between conventional P(I)- controllers and the introduced H∞ - method is demonstrated and discussed.

In this paper the problem of fault detection in distributed systems is addressed. Due to the trend that these systems are incorporating an increasing number of subsystems from different suppliers fault detection is becoming an essential part of distributed system design. While meeting the typical constraints of the automotive industry there is the demand on increased safety and improved availability. Because of the connection of different subsystems, errors propagate through the system and may affect other subsystems where they can be detected. The key task which is dealt with in this paper is to detect the origin of these errors. Therefore, Hierarchical Colored Bayesian Petri-Nets are introduced to fulfill fault detection according to Bayesian networks. To reduce calculation efforts, the principle of clustering is included.

The formulation of software tasks as parallel processes allows their implementation within distributed microcontrollers. The requirements for Automotive Networks to support these applications are discussed. By introduction of a locality measure, a classification of networks can be made either into interactive distributed realtime processing or into classical communication. Given a sufficiantly small locality, the physical network extension does not have an impact on the implementation. A concept i presented how to integrate process dispachting and synchronization. Based upon this concept, functions may be formulated independant of their location in a specific microcontroller.

In this approach a nonlinear controller for the lateral vehicle dynamics is designed. The basis for the design is a nonlinear model of the lateral vehicle dynamics in state space representation consisting of three states: The vehicle velocity, the yaw rate as well as the vehicle body sideslip angle (VBSSA). As control variables the yaw rate and the VBSSA are chosen. To assure the vehicle follows the driver's directional intent, the yaw rate is adapted to a desired reference value determined by means of a linear single track model. The second control variable -the VBSSA- is utilized to reduce the lateral forces. Incorporating the VBSSA, the controller's behavior can be significantly improved. Thus, a nonlinear controller is designed which is capable to stabilize the vehicle in critical driving situations. This nonlinear controller is based on an adaptation of a quality function for the nonlinear model to the one for a linear reference system.

In this paper an approach is presented to determine an adequate number of clusters automatically in case of clustering a distributed automotive electronic system. Hereby, this approach is based on the ISODATA clustering algorithm. Its advantages are its flexibility and less computational effort in comparison to normally used partitioning algorithms. In order to cluster a distributed automotive electronic system with respect to a reduced external communication the input data normally used for partitioning algorithms has to be adapted. Besides, a new overall quality criterion is introduced to validate the results of clustering in reference to the busload before test stage.

Today, in many passenger cars and light trucks, the conventional driveline is extended by a dual mass flywheel (DMF). The DMF reduces driveline oscillations by mechanically decoupling the crankshaft and the transmission. Existing engine control systems are designed for conventional single mass flywheel (SMF) systems. In the future, to facilitate the optimal control of engines equipped with advanced DMF systems, such conventional control systems may require adaptation, modification or even replacement. The design and testing of appropriate new control systems has required the development of various types of engine models. In this paper, various engine modeling techniques are introduced and compared in respect to their capabilities for both driveline simulation and control system development.

In this paper an approach to clustering of complex electronic systems using Self-Ordering Maps (SOMs) is presented. SOMs are neural networks which learn through a competitive learning algorithm. In order to use SOMs for the clustering of electronic networks, a representation of the communication behavior in n-dimensional space is developed. The SOM is then used as a nonlinear projection of this space onto a two-dimensional plane. Two examples of clustering are given. The more complex of the two is verified by comparing the behavior of the clustered system and the unclustered system on a simple model of the CAN bus. It is shown that SOMs can be used to effectively cluster complex electronic systems.

The new aerial communication protocol “Controller Area Network” (CAN) efficiently supports distributed realtime control in automotive applications. In order to unload CPUs from high-speed message transfer, dedicated CAN hardware handles messages up to the communication object level. In multiplex wiring message rates are one to two orders of magnitude lower, allowing to implement the upper communication level more cost-effectively in software. This reduces CAN interface hardware to bitwise protocol handling only. It may be incorporated even into low-end microcontrollers without significantly increasing chip size. Thus the same CAN protocol supports the entire range of serial automotive communication, matching implementation costs to requirements at each performance level.

The aim of OSEK/VDX is an industry standard for open architectures in vehicles. Originally founded as a Franco - German joint project, OSEK/VDX is now drawing worldwide attention. In the project, services and protocols are specified to standardize Communication, Network Management and a real-time Operating System. Its architecture offers a network-independent interface while taking into account the constraints of automotive applications in terms of size and cost. A structured and modular software implementation based on standardized interfaces and protocols as proposed by OSEK/VDX is a necessary condition for portability and extendibility, and thus reusability of existing software. An overview of the current status of OSEK/VDX is presented.

Bus systems like CAN or FlexRay allowed great advances in automotive electronics over the last 20 years. In order to function in an environment which requires the communication medium to tolerate one safety-relevant fault, these bus systems require a second, redundant bus to act as a backup for the original unit. With the network approach presented in this paper (SafeNet) it is possible to use the network intrinsic redundancy to keep the network fail-safe after at least one safety relevant fault in the network. To ensure this, messages are relayed to every node in the network. Even though the message delivery times in the network are not deterministic, it is shown that it is suitable for safety-relevant applications like drive-by-wire. Due to the simple point-to-point connections used to connect the nodes, high speeds can be achieved. The network approach is compared to both CAN and FlexRay under different aspects.

Over more than 20 years 50 million LuK dual mass flywheels (DMF) have been produced for use in passenger cars and light trucks. A typical DMF consists of two flywheels connected by long travel arc-springs. It is located between the combustion engine and the clutch or automatic transmission. The DMF reduces driveline oscillations by mechanically decoupling the transmission from the periodic combustion events that excite the engine crankshaft. Existing engine control systems are generally designed for conventional single mass flywheel (SMF) systems. In the future, to facilitate the best possible control of engines equipped with DMF systems, these conventional control systems may require modification or even replacement. With the integration of the highly non-linear DMF, the complexity, and thus the order of the powertrain system increase.