Research on Fault Analysis and Fault-Tolerant Control of EV/HEV Powertrain

International audienceThis paper presents research works in the topics of fault analysis and fault tolerant control of an electric vehicle powered by an inverter-fed induction motor drive and the usual sensors. The considered failures are mainly measurement error due to faulty sensors and power inverter malfunctions. When sensor failure occurs, both software and hardware redundancies have been investigated. Software redundancy has been evaluated in case of speed sensor failure. Hardware redundancy has been used in the case of power inverter failures with a fault-tolerant 4-leg topology. This topology exploits the induction motor neutral accessibility for fault-tolerant purposes. The proposed fault-tolerant approach brings a significant improvement compared to the phase-leg topology. This paper also presents the experimental validation of an efficient reconfiguration mechanism (transition strategy) at sensor fault occurrence

A Fuzzy-Based Strategy to Improve Control Reconfiguration Performance of a Sensor Fault-Tolerant Induction Motor Propulsion

International audienceThis short paper deals with the transition performance improvement of a sensor fault-tolerant controller devoted to automotive applications. Indeed, improvements are brought over a previously developed technique that exhibit abrupt changes in the torque if a sensor fault is detected and after a transition from a control technique to another one [1]. The Fault-Tolerant Control (FTC) system firstly concerns the sliding mode control technique since better performances are obtained with an encoder to get the speed information. In the event of unavailability of the speed sensor, a sensorless fuzzy control technique is applied. In the proposed active fault-tolerant control approach a short and a smooth transition are achieved from the encoder-based control technique to the sensorless one using an appropriate fuzzy logic decision approach

Integration of fault tolerance and hardware redundancy techniques into the design of mobile platforms

This work addresses the development of a fault-tolerant mobile platform. Fault-tolerant mechanical system design is an emerging technology that attempts to build highly reliable systems by incorporating hardware and software architectures. For this purpose, previous work in fault-tolerant were reviewed. Alternate architectures were evaluated to maximize the fault tolerance capabilities of the driving and steering systems of a mobile platform. The literature review showed that most of the research work on fault tolerance has been done in the area of kinematics and control systems of robotic arms. Therefore, hardware redundancy and fault tolerance in mobile robots is an area to be researched. The prototype constructed as part of this work demonstrated basic principles and uses of a fault-tolerant mechanism, and is believed to be the first such system in its class. It is recommended that different driving and steering architectures, and the fault-tolerant controllers\u27 performance be tested on this prototype

A Control Reconfiguration Strategy for Post-Sensor FTC in Induction Motor-Based EVs

International audienceThis paper deals with experimental validation of a reconfiguration strategy for sensor fault-tolerant control (FTC) in induction-motor-based electric vehicles (EVs). The proposed active FTC system is illustrated using two control techniques: indirect field-oriented control (IFOC) in the case of healthy sensors and speed control with slip regulation (SCSR) in the case of failed current sensors. The main objective behind the reconfiguration strategy is to achieve a short and smooth transition when switching from a controller using a healthy sensor to another sensorless controller in the case of a sensor failure. The proposed FTC approach performances are experimentally evaluated on a 7.5-kW induction motor drive

Virtual-Sensor-Based Maximum-Likelihood Voting Approach for Fault-Tolerant Control of Electric Vehicle Powertrains

International audienceThis paper describes a sensor fault-tolerant control (FTC) for electric-vehicle (EV) powertrains. The proposed strategy deals with speed sensor failure detection and isolation within a reconfigurable induction-motor direct torque control (DTC) scheme. To increase the vehicle powertrain reliability regarding speed sensor failures, a maximum-likelihood voting (MLV) algorithm is adopted. It uses two virtual sensors [extended Kalman filter (EKF) and a Luenberger observer (LO)] and a speed sensor. Experiments on an induction-motor drive and simulations on an EV are carried out using a European urban and extraurban driving cycle to show that the proposed sensor FTC approach is effective and provides a simple configuration with high performance in terms of speed and torque responses

Fault-tolerant control of electric vehicles with in-wheel motors using actuator-grouping sliding mode controllers

Although electric vehicles with in-wheel motors have been regarded as one of the promising vehicle architectures in recent years, the probability of in-wheel motor fault is still a crucial issue due to the system complexity and large number of control actuators. In this study, a modified sliding mode control (SMC) is applied to achieve fault-tolerant control of electric vehicles with four-wheel-independent-steering (4WIS) and four-wheel-independent-driving (4WID). Unlike in traditional SMC, in this approach the steering geometry is re-arranged according to the location of faulty wheels in the modified SMC. Three SMC control laws for longitudinal velocity control, lateral velocity control and yaw rate control are designed based on specific vehicle motion scenarios. In addition the actuator-grouping SMC method is proposed so that driving actuators are grouped and each group of actuators can be used to achieve the specific control target, which avoids the strong coupling effect between each control target. Simulation results prove that the proposed modified SMC can achieve good vehicle dynamics control performance in normal driving and large steering angle turning scenarios. In addition, the proposed actuator-grouping SMC can solve the coupling effect of different control targets and the control performance is improved

Prognostics and health aware model predictive control of wind turbines

Wind turbines components are subject to considerable stresses and fatigue due to extreme environmental conditions to which they are exposed, especially those located offshore. Also, the most common faults present in wind turbine components have been investigated for years by the research community and that has led to propose a fault diagnosis and fault tolerant control wind turbine benchmark which include a set of faults that affect the sensors and actuators of several wind turbine components. This thesis presents some contributions to the fields of fault diagnosis, fault-tolerant control, prognostics and its integration with wind turbine control which leads to proposing a control approach called health-aware model predictive control (HAMPC). The contributions are summarized below: - Model-based fault diagnosis: to perform fault detection and isolation interval-based observers together with a set of analytical redundant relations (ARRs) are obtained based on a structural analysis and the fault signature matrix that relates the ARRs with the faults. - Fault tolerant control: it is proposed a fault tolerant control scheme that integrates fault detection and an algorithm for fault accommodation. The scheme has the objective to avoid the increment of blades and tower loads when a fault in the rotor azimuth angle sensor occurs using the individual pitch control technique (IPC). - Wind turbine blades fatigue prognostics and degradation: fatigue is assessed using the rainflow counting algorithm which is used to estimate the accumulated damage and for degradation, it is used a stiffness degradation model of blades material which is used to make predictions of remaining useful life (RUL). - Wind turbines health control: the module for the health of the system based on fatigue damage estimation and RUL predictions is integrated with model predictive control (MPC) leading to the proposed control approach (HAMPC). The contributions presented in this thesis have been validated on a wind turbine study case that uses a 5MW wind turbine reference model implemented in a high fidelity wind turbine simulator (FAST).Els components dels aerogeneradors estan sotmesos a considerable estrès i fatiga, degut a les condicions ambientals extremes a les quals estan exposats, especialment els localitzats en alta mar. Per aquest motiu, al comunitat científica durant els últims anys ha investigat les averies més comunes presents en els aerogeneradors, fet que ha portat a proposar un cas d'estudi de diagnosi i control tolerant de fallades que inclou un conjunt de fallades que afecten a diversos components dels aerogeneradors. Aquesta tesi presenta algunes contribucions en els camps de la diagnosi de fallades, el control tolerant de fallades i la prognosi, així com la seva integració amb el control d'aerogeneradors, fet que ha portat a proposar una tècnica de control anomenada control predictiu basada en models conscients de la salut del sistema (HAMPC). Concretament les aportacions es poden resumir en: - Diagnosi de fallades basada en models: per a la detecció s'utilitzen observadors intervalars i l'aïllament de la fallada es fa en base el conjunt d'ARRs obtinguts de l'anàlisi estructural i de la matriu de signatures de fallades que relaciona les ARRs amb les fallades. - Control tolerant de fallades: es proposa un esquema de control tolerant a fallades que integra la detecció de fallades i algoritme d'acomodació de fallades, i té per objectiu evitar l'augment de càrregues en la pala i la torre quan es produeix una fallada en el sensor azimuth quan es fa un control individual de la inclinació de les pales (IPC). - Prognosi de la fatiga i la degradació de les pales: la fatiga s'avalua amb un algorisme denominat "rainflow counting" amb el qual es fa estimació del dany acumulat i per a la degradació es fa servir un model de degradació de la rigidesa del material amb el qual es fan prediccions de la vida útil restant (RUL). - Control de la salut d'aerogeneradors: s'ha integrat la gestió de la salut del sistema basat en danys per fatiga o prediccions de RUL amb control predictiu basat en models (MPC) donant lloc al control que anomenem HAMPC. Les contribucions presentades en aquesta tesi han sigut validades en un cas d'estudi d'aerogeneradors basat en un aerogenerador de referència de 5MW de potència implementat en el simulador d'aerogeneradors d'alta fidelitat conegut amb el nom de FAST.Postprint (published version

Highly redundant and fault tolerant actuator system: control, condition monitoring and experimental validation

This thesis is concerned with developing a control and condition monitoring system for a class of fault tolerant actuators with high levels of redundancy. The High Redundancy Actuator (HRA) is a concept inspired by biomimetics that aims to provide fault tolerance using relatively large numbers of actuation elements which are assembled in parallel and series configurations to form a single actuator. Each actuation element provides a small contribution to the overall force and displacement of the system. Since the capability of each actuation element is small, the effect of faults within the individual element of the overall system is also small. Hence, the HRA will gracefully degrade instead of going from fully functional to total failure in the presence of faults. Previous research on HRA using electromechanical technology has focused on a relatively low number of actuation elements (i.e. 4 elements), which were controlled with multiple loop control methods. The objective of this thesis is to expand upon this, by considering an HRA with a larger number of actuation elements (i.e. 12 elements). First, a mathematical model of a general n-by-m HRA is derived from first principles. This method can be used to represent any size of electromechanical HRA with actuation elements arranged in a matrix form. Then, a mathematical model of a 4-by-3 HRA is obtained from the general n-by-m model and verified experimentally using the HRA test rig. This actuator model is then used as a foundation for the controller design and condition monitoring development. For control design, two classical and control method-based controllers are compared with an H_infinity approach. The objective for the control design is to make the HRA track a position demand signal in both health and faulty conditions. For the classical PI controller design, the first approach uses twelve local controllers (1 per actuator) and the second uses only a single global controller. For the H_infinity control design, a mixed sensitivity functions is used to obtain good tracking performance and robustness to modelling uncertainties. Both of these methods demonstrate good tracking performance, with a slower response in the presence of faults. As expected, the H_infinity control method's robustness to modelling uncertainties, results in a smaller performance degradation in the presence of faults, compared with the classical designs. Unlike previous work, the thesis also makes a novel contribution to the condition monitoring of HRA. The proposed algorithm does not require the use of multiple sensors. The condition monitoring scheme is based on least-squares parameter estimation and fuzzy logic inference. The least-squares parameter estimation estimates the physical parameters of the electromechanical actuator based on input-output data collected from real-time experiments, while the fuzzy logic inference determines the health condition of the actuator based on the estimated physical parameters. Hence, overall, a new approach to both control and monitoring of an HRA is proposed and demonstrated on a twelve elements HRA test rig