http://www.silviosimani.it/isermann-FDI-2006.pdf

Model-based fault-detection and diagnosis - status and applications §

The article begins with a review of electronic driver assisting systems such as ABS, traction control, electronic stability control, and brake assistant. We then review drive-by-wire systems with and without mechanical backup. Drive-by-wire systems consist of an operating unit with an electrical output, haptic feedback to the driver, bus systems, microcomputers, power electronics, and electrical actuators. For their design safety, integrity methods such as reliability, fault tree and hazard analysis, and risk classification are required. Different fault-tolerance principles with various forms of redundancy are considered, resulting in fail-operational, fail-silent, and fail-safe systems. Fault-detection methods are discussed for use in low-cost components, followed by a review of principles for fault-tolerant design of sensors, actuators, and communication. We evaluate these methods and principles and show how they can be applied to low-cost automotive components and drive-by-wire systems. A brake-by-wire system with electronic pedal and electric brakes is then considered in more detail, showing the design of the components and the overall architecture. Finally, we present conclusions and an outlook for further development of drive-by-wire systems.

Fault-tolerant drive-by-wire systems

Precise dynamic models of processes are required for many applications, ranging from control engineering to the natural sciences and economics. Frequently, such precise models cannot be derived using theoretical considerations alone. Therefore, they must be determined experimentally. This book treats the determination of dynamic models based on measurements taken at the process, which is known as system identification or process identification. Both offline and online methods are presented, i.e. methods that post-process the measured data as well as methods that provide models during the measurement. The book is theory-oriented and application-oriented and most methods covered have been used successfully in practical applications for many different processes. Illustrative examples in this book with real measured data range from hydraulic and electric actuators up to combustion engines. Real experimental data is also provided on the Springer webpage, allowing readers to gather their first experience with the methods presented in this book. Among others, the book covers the following subjects: determination of the non-parametric frequency response, (fast) Fourier transform, correlation analysis, parameter estimation with a focus on the method of Least Squares and modifications, identification of time-variant processes, identification in closed-loop, identification of continuous time processes, and subspace methods. Some methods for nonlinear system identification are also considered, such as the Extended Kalman filter and neural networks. The different methods are compared by using a real three-mass oscillator process, a model of a drive train. For many identification methods, hints for the practical implementation and application are provided. The book is intended to meet the needs of students and practicing engineers working in research and development, design and manufacturing.

Identification of Dynamic Systems: An Introduction with Applications

Mechatronic semi-active and active vehicle suspensions

In this paper, an optimal control technique for n-phase permanent-magnet (PM) machines under various open circuit faults is presented. Under the fault conditions, the currents in the healthy phases are controlled to compensate phase loss and to produce the required output torque. The proposed control technique ensures continuous operation of the machines while producing minimum torque ripples and minimum stator ohmic loss. The control technique is based on the instantaneous power balance theory. To set the summation of the phase currents equal to zero, a constraint is incorporated in the derivation of the control technique. A five-phase PM machine is considered to demonstrate the proposed open circuit fault-tolerant control strategy. Simulation and experimental results are provided for validation.

An Optimal Control Technique for Multiphase PM Machines Under Open-Circuit Faults

In comparison to classical DC motors, brushless DC motors are very reliable, Nevertheless, they can also fail, caused by, e.g., overheating or mechanical wear. This paper proposes a parameter estimation technique for fault detection on this type of motor. Simply by measuring the motor's input and output signals, its parameters can be estimated. This method is based on a mathematical model of the process. In the presented work, a square-wave motor is considered. An appropriate model is derived. To be able to implement the method also on low-cost microcontroller-based control units, only the power inverter supply voltage, DC current, and the motor's angular velocity have to be measured. The parameter estimation technique provides information about the electrical resistance and the back-EMF constant as well as about the mechanical parameters. Comparing the nominal with the computed parameters, faults can be detected. The approach might be applied to both end-of-line and online fault detection. Results for simulated data demonstrate the capabilities of the proposed procedure. Finally, a real-world application-an actuation system with a brushless DC motor mounted to a gearbox-is given.

Application of model-based fault detection to a brushless DC motor

A real time fault detection for a brushless DC motor driving a mechanical actuation system is presented. The brushless DC motor is controlled by a PWM inverter using rectangular current excitation. After an introduction into fault detection with parameter estimation, a mathematical model for the actuator with special emphasis on the motor itself is derived. The application of the estimation algorithm to detect electrical parameter changes in the motor using single phase currents is described. The fault detection scheme is implemented on a digital signal processor controlling the actuator. Finally experimental results are given.

Model-based fault detection for a brushless DC motor using parameter estimation

Design and Application of Digital FIR Differentiators Using Modulating Functions

Mikrocontrollerbasierte Fehlererkennung für mechatronische Komponenten am Beispiel eines elektromechanischen Stellantriebs

The method involves applying a voltage step to the coil (4) and measuring the coil current and voltage variations, computing the Ohmic resistance, computing the chained magnetic flux as a function of time and from it the change in chained magnetic flux as a function of current, whereby the function of the chained magnetic flux contains a gradually changing component of the differential coil inductance.

Reconstruction of armature movement of electromagnetic actuator, e.g. for hydraulic valve, involves computing chained magnetic flux as function of time, change in chained magnetic flux as function of current

Olaf Moseler

Papers

Application of model-based fault detection to a brushless DC motor

Model-based fault detection for a brushless DC motor using parameter estimation

Design and Application of Digital FIR Differentiators Using Modulating Functions

Mikrocontrollerbasierte Fehlererkennung für mechatronische Komponenten am Beispiel eines elektromechanischen Stellantriebs

Reconstruction of armature movement of electromagnetic actuator, e.g. for hydraulic valve, involves computing chained magnetic flux as function of time, change in chained magnetic flux as function of current