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Hardware-in-the-Loop Simulation for the Design and Testing of Engine-control systems

IFAC Proceedings Volumes 1998年第4期31卷 1-10页

作者： R. Isermann J. Schaffnit S. Sinsel Institute of Automatic Control Laboratory of Control Engineering and Process Automation Technical University of Darmstadt Landgraf-Georg-Str. 4 D-64283 Darmstadt Germany

For the design, implementation and testing of control systems increasingly hardware-in-the-loop (HIL) simulation is required, where parts of the control loop components are real hardware and parts are simulated. Usually, the process is simulated because it is not available (simultaneous engineering), or experiments with the real process are too costly or require too much time. The sensors and actuators may be simulated or real and the controller is real hardware and software. The real-time requirements for the simulation depends on the time scale of the process and the simulated components. The contribution gives first an overview of the various kinds of real-time and HIL simulation. Then, two cases are considered. First the HIL simulation for relatively slow processes, like in basic industries or heating systems. Here, the simulation-speed may be limited either by the complexity of the processes or by the real controller hardware. Then, the HIL simulation of combustion engines both with transputers and digital signal processors is shown in detail. The required models for 6- and 8-cylinder diesel engines are described, including fuel injection and burning, pressure development, torque generation at the crankshaft, exhaust turbocharger dynamics and the vehicle dynamics. The HIL-simulator test bench consísts of a real-time computer system, sensor-interface, actuator interface, real injection pumps and the real control unit. Comparisons of real-time simulation with measurements on real diesel engines and trucks are shown. The goal of the HIL system is to develop new control algorithms and to investigate the effect of faults in sensors and actuators and the engine itself.

关键词： real-time simulation hardware-in-the-loop simulation diesel engine turbocharger vehicle dynamics transputers digital signal processors simulator testbench

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Neuro-Fuzzy Modeling of Automotive SI-Engine Characteristics

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IFAC Proceedings Volumes 1998年第1期31卷 149-154页

作者： H. Holzmann Ch. Halfmann R. Isermann Darmstadt University of Technology Institute of Automatic Control Laboratory for Control Engineering and Process Automation Landgraf-Georg-Strasse 4 D-64283 Darmstadt Germany Telephone: +49-6151-167407 Telefax: +49-6151-293604

In automotive technology, the behaviour of SI-combustion engines is often characterised by the dependency of the engine torque on the engine speed and the throttle angle. Especially for control and simulation purposes it is important to provide an easy possibility to extract a formal description of an engine characteristic map from data measured on an engine test stand. This paper describes a way to replace the conventionally used look-up-tables by neural network or fuzzy logic representations and to adapt them on-line to measured signals. In addition to that, a neuro-fuzzy approach is discussed as well.

关键词： Si-combustion engine 3-D maps neural networks fuzzy logic neuro-fuzzy

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Fault detection and diagnosis of components of the vehicle vertical dynamics

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MECCANICA 1997年第5期32卷 459-472页

作者： Weispfenning, T Darmstadt University of Technology Institute of Automatic Control Laboratory of Control Engineering and Process Automation D-64283 Darmstadt Germany

In this paper, model and signal-based methods for supervision of suspension elements of a car are presented. A model-based approach using parameter estimation is used to determine the current parameters of a vehicle suspension. Exploiting the analytical redundancy, different faults, like weak dampers or sensor faults, can be distinguished. For fault detection the use of parity equations is shown. In addition, a signal-based approach is presented which makes a detection of tire pressure loss possible. All presented results were drawn from a test rig or from a driving car.

关键词： vehicle dynamics diagnostics suspension signal analysis automotive applications

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Neuro-fuzzy systems for diagnosis

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FUZZY SETS AND systems 1997年第3期89卷 289-307页

作者： Ayoubi, M Isermann, R Darmstadt University of Technology Institute of Automatic Control Laboratory of Control Engineering and Process Automation Landgraf-Georg 4 64283 Darmstadt Germany

Knowledge-based fault detection and diagnosis is described from the analytic and heuristic symptom generation to diagnostic reasoning. The extension of the knowledge-based approach by adaptive neural networks allows us to tune the knowledge base in order to investigate undetermined parameters just as membership functions, relevance weights of antecedents and priority factors of rules. An overview of design methodologies of neuro-fuzzy systems is provided with a special focus on a hybrid neuro-fuzzy network with a neural logical operator. Finally, an application of the neuro-fuzzy system to the on-line monitoring of air pressure in vehicle wheels is described. (C) 1997 Elsevier Science B.V.

关键词： neuro-fuzzy systems fault detection and diagnosis automatic rule extraction

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Supervision of vehicles' tyre pressures by measurement of body accelerations

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control ENGINEERING PRACTICE 1997年第8期5卷 1151-1159页

作者： Halfmann, C Ayoubi, M Holzmann, H Institute of Automatic Control Darmstadt University of Technology Laboratory for Control Engineering and Process Automation Landgraf-Georg-Strasse 4 D-64283 Darmstadt Germany

Due to the rising consciousness of safety aspects, the supervision of vehicles' tyre pressures is a major aspect of improved active car safety. Therefore, in this paper a method for monitoring the tyre pressures is presented, using body acceleration signals. Analyzing the frequency spectrum of the virtual transfer function between the body acceleration at the front and rear wheel on one side of the vehicle, characteristic features are generated. Thereby, external interferences on the spectrum and their influences on the symptoms are discussed. To quantify the tyre pressure, a neuro-fuzzy classification of the characteristics is applied. Copyright (C) 1997 Elsevier Science Ltd.

关键词： supervision of tyre pressures virtual transfer functions signal processing spectrum analysis neuro-fuzzy classification

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Longitudinal and lateral control and supervision of autonomous intelligent vehicles

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control ENGINEERING PRACTICE 1997年第11期5卷 1599-1605页

作者： Holzmann, H Halfmann, C Germann, S Wurtenberger, M Isermann, R Darmstadt University of Technology Institute of Automatic Control Laboratory for Control Engineering and Process Automation Landgraf-Georg-Straβe 4 D-64283 Darmstadt Germany

As individual and commercial traffic flow on roads and highways grows enormously, the number of accidents increases as well. Therefore, modern vehicle research is focused on improving driving comfort as well as passengers' safety. Aiming at that, recent advances in control engineering and modern computer technology enable the engineer to design special control and supervision systems to support the driver. As an example, this contribution presents two possible solutions. An Adaptive Cruise control system assists the driver in highway traffic, whereas a vehicle-supervision method is applied to detect critical driving situations and sensor faults. Copyright (C) 1997 Elsevier Science Ltd.

关键词： vehicle modelling velocity control distance control vehicle dynamics motion supervision sensor fault detection

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Application of model-based fault detection and diagnosis to the quality assurance of an automotive actuator

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control ENGINEERING PRACTICE 1997年第5期5卷 703-708页

作者： Pfeufer, T Institute of Automatic Control Laboratory of Control Engineering and Process Automation Darmstadt University of Technology Landgraf-Georg.Str. 4 D-64283 Darmstadt Germany

The increased degree of automation of technical processes requires an increased number of mechanical-electronic components. In order to maintain the dependability and availability despite of the increased complexity, new methods for the quality assurance of mechanical-electronic systems are necessary. This paper describes an automatic diagnostic system for an automotive actuator. Analytic models of the process under investigation are used in order to extract detailed information about the process, using only the usually measured signals and evaluating the signals e.g. by parameter estimation and state estimation. However, some relations, especially the cause - effect relations between the underlying faults and the observable symptoms, are quite difficult to represent by analytic models. A rule-based approach is more suitable to acquire, represent and process the diagnostic knowledge base. In order to cope with uncertainty, a fuzzy structure is applied to the classification of faults. Copyright (C) 1997 Elsevier Science Ltd.

关键词： approximate reasoning decision making fault detection fault diagnosis parameter estimation fuzzy supervision electromechanical actuators

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Supervision, fault-detection and fault-diagnosis methods - An introduction

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control ENGINEERING PRACTICE 1997年第5期5卷 639-652页

作者： Isermann, R Institute of Automatic Control Laboratory of Control Engineering and Process Automation Darmstadt University of Technology Landgraf-Georg-Str. 4 D-64283 Darmstadt Germany

The operation of technical processes requires increasingly advanced supervision and fault diagnosis to improve reliability, safety and economy. This paper gives an introduction to the field of fault detection and diagnosis. It begins with a consideration of a knowledge-based procedure that is based on analytical and heuristic information. Then different methods of fault detection are considered, which extract features from measured signals and use process and signal models. These methods are based on parameter estimation, state estimation and parity equations. By comparison with the normal behaviour, analytic symptoms are generated. Human operators are another source of information, and support the generation of heuristic symptoms. For fault diagnosis, all symptoms have to be processed in order to determine possible faults. This can be performed by classification methods or approximate reasoning, using probabilistic or possibilistic (fuzzy) approaches based on if-then-rules. Copyright (C) 1997 Elsevier Science Ltd.

关键词： fault detection supervision monitoring parameter estimation state estimation parity equations technical processes actuators sensors fault diagnosis diagnostic reasoning fuzzy reasoning

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Trends in the application of model-based fault detection and diagnosis of technical processes

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control ENGINEERING PRACTICE 1997年第5期5卷 709-719页

作者： Isermann, R Balle, P Institute of Automatic Control Laboratory of Control Engineering and Process Automation Darmstadt University of Technology Landgraf-Georg. Str. 4 D-64283 Darmstadt Germany

After a short overview of the historical development of model-based fault detection, some proposals for the terminology in the field of supervision, fault detection and diagnosis are stated, based on the work within the IFAC SAFEprocess Technical Committee. Some basic fault-detection and diagnosis methods are briefly considered. Then, an evaluation of publications during the last 5 years shows some trends in the application of model-based fault-detection and diagnosis methods. Copyright (C) 1997 Elsevier Science Ltd.

关键词： fault detection fault diagnosis supervision actuator faults sensor faults process faults state observer parity space parameter estimation classification diagnostic reasoning

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Representation of 3-D mappings for automotive control applications using neural networks and fuzzy logic

Representation of 3-D mappings for automotive control applic...

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IEEE Conference on control Technology and Applications (CCTA)

作者： H. Holzmann C. Halfmann R. Isermann Institute of Automatic Control Laboratory for Control Engineering and Process Automation Darmstadt University of Technology Darmstadt Germany

Providing a simple and effective way to describe the nonlinear input-output behaviour of a system, three-dimensional mappings (3-D maps) have gained a lot of importance in modern automotive technology. Applications cover a wide range from real-time control systems up to the area of vehicle simulation. Replacing the conventional look-up-tables by neural network or fuzzy logic representations offers an easy possibility to generate 3-D maps by measured data and to adapt them online using measured signals. This paper describes the modelling of engine characteristics for vehicle control and simulation purposes by multilayer perceptron and radial-basis function networks. In addition to that, a neuro-fuzzy approach is discussed as well.

关键词： Automotive engineering Neural networks Fuzzy control Fuzzy neural networks Engines Vehicles Interpolation automatic control control systems Fuzzy logic

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