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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.

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.

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.

The vehicle body sideslip angle (VBSSA) is a key variable in vehicle dynamics indicating critical driving situations. It is, e.g., essential in vehicle dynamics control concepts. Since it cannot be measured with standard sensors, it has to be determined via a model based approach. Thereto an Extended Kalman Filter will be presented that is capable of describing the VBSSA with high accuracy. The filter design is based on a nonlinear double track model combining the longitudinal and lateral dynamics. Starting point is a double track model with three state variables, that are the velocity in the center of gravity, the VBSSA and the yaw rate. Then, the longitudinal dynamics are incorporated, yielding the velocity and the longitudinal forces at the individual wheels. The resulting nonlinear state space model only requires information that is provided by the standard sensors available in series production vehicles. On basis of this nonlinear model an Extended Kalman Filter is derived.

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.

In this paper the vehicle body side slip angle (VBSSA) is determined by means of non-linear state space observers. First, an adaptive non-linear double track model is presented. Validation with real measurement data shows that the model accuracy is sufficient for observer design. On basis of this model two observers are derived. One observer is based on a linearization of the vehicle model around the currently estimated state vector. The other observer adapts the dynamics of the non-linear estimation error to the one of a linear reference model. As this observer is restricted to systems of a specific structure, the adaptive non-linear double track model has to be restructured accordingly. The presented observers are validated with real measurement data. They provide an accurate estimation of the VBSSA up to the stability limit of the vehicle.

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 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.

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.

The reproduction of the vehicle motion is a crucial element of accident reconstruction. Apart from the position of the center of gravity in an inertial coordinate system, the vehicle heading plays an important role. The heading is the sum of the yaw angle and the vehicle body side slip angle. In standard vehicles, the yaw angle can be determined using the yaw rate sensor and the wheel speeds. However, the yaw rate sensor is often subject to temperature drift. The wheel speed signals are forged at low speeds or due to slip. These errors result in significant deviations of reconstructed and real vehicle heading. Therefore, an intelligent combination of these signals is required. This paper describes a fuzzy system which is capable to increase the accuracy of yaw angle calculation by means of fuzzy logic. Before the data is applied to the fuzzy system, it is preprocessed to ensure the accuracy of the fuzzy system inputs.

In this paper we present the results of a project that concentrates on the design of distributed embedded systems for control-related applications. The OPTMAP (Optimal Mapping of Virtual Control Functions to a Distributed Architecture) framework supports the function allocation based on given constrains involving a feasible solution. The control systems we will consider use a time-triggered paradigm for sensor reading and event-driven behavior for inter-processor communication. Sensor values are read at fixed periods in time and data processing occurs after the control unit receives the proper message. The aim of the project is to get an optimized mapping which minimizes information traffic on the network and guarantees that all processing units are able to handle the distributed control functions in real time.