A review on machinery diagnostics and prognostics implementing condition-based maintenance

There is an increasing demand for dynamic systems to become safer and more reliable This requirement extends beyond the normally accepted safety-critical systems such as nuclear reactors and aircraft, where safety is of paramount importance, to systems such as autonomous vehicles and process control systems where the system availability is vital It is clear that fault diagnosis is becoming an important subject in modern control theory and practice Robust Model-Based Fault Diagnosis for Dynamic Systems presents the subject of model-based fault diagnosis in a unified framework It contains many important topics and methods; however, total coverage and completeness is not the primary concern The book focuses on fundamental issues such as basic definitions, residual generation methods and the importance of robustness in model-based fault diagnosis approaches In this book, fault diagnosis concepts and methods are illustrated by either simple academic examples or practical applications The first two chapters are of tutorial value and provide a starting point for newcomers to this field The rest of the book presents the state of the art in model-based fault diagnosis by discussing many important robust approaches and their applications This will certainly appeal to experts in this field Robust Model-Based Fault Diagnosis for Dynamic Systems targets both newcomers who want to get into this subject, and experts who are concerned with fundamental issues and are also looking for inspiration for future research The book is useful for both researchers in academia and professional engineers in industry because both theory and applications are discussed Although this is a research monograph, it will be an important text for postgraduate research students world-wide The largest market, however, will be academics, libraries and practicing engineers and scientists throughout the world

Robust Model-Based Fault Diagnosis for Dynamic Systems

https://users.encs.concordia.ca/~ymzhang/publications/ARC32-2-98Zhang_pp.229-252.pdf

Bibliographical review on reconfigurable fault-tolerant control systems

This paper reviews the current status and implementation of battery chargers, charging power levels, and infrastructure for plug-in electric vehicles and hybrids. Charger systems are categorized into off-board and on-board types with unidirectional or bidirectional power flow. Unidirectional charging limits hardware requirements and simplifies interconnection issues. Bidirectional charging supports battery energy injection back to the grid. Typical on-board chargers restrict power because of weight, space, and cost constraints. They can be integrated with the electric drive to avoid these problems. The availability of charging infrastructure reduces on-board energy storage requirements and costs. On-board charger systems can be conductive or inductive. An off-board charger can be designed for high charging rates and is less constrained by size and weight. Level 1 (convenience), Level 2 (primary), and Level 3 (fast) power levels are discussed. Future aspects such as roadbed charging are presented. Various power level chargers and infrastructure configurations are presented, compared, and evaluated based on amount of power, charging time and location, cost, equipment, and other factors.

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Review of Battery Charger Topologies, Charging Power Levels, and Infrastructure for Plug-In Electric and Hybrid Vehicles

An introduction to heat transfer

Structural analysis for fault detection and isolation (FDI) is an efficient method for designing structured residual generators for model-based diagnosis. It generates a number of diagnostic test candidates, whose number may be large in case of complex systems. This paper proposes a method for selecting residual generators from a possibly large number of candidate equation sets using a diagnosability index that measures the degree of diagnosability in a diagnostic system. The selection process of residual generators is aimed at reducing the solution sets for achieving the optimal diagnostic performance, i.e, maximizing the detectability and isolability of various faults. The approach for selecting residual generators is applied to a permanent magnet synchronous machine (PMSM) drive system in an electrified vehicle to show that the proposed methodology is effective in automatically downsizing the candidate equation sets for diagnostic tests from a relatively larger number of choices derived from the structural analysis algorithms.

Selection of residual generators in structural analysis for fault diagnosis using a diagnosability index

Powertrain neutral idle control is a technology aimed at improving fuel economy during urban driving, as well as reducing engine vibrations transmitted to the passenger compartment. A new coordinated engine-transmission control approach for the neutral idle input clutch application phase is presented in this paper. Due to the Multi-Input Multi-Output (MIMO) nature of the control problem, an optimal Linear Quadratic Regulator (LQR) with Explicit Model Following (EMF) is used to allow the system dynamic response to track two desired trajectories for engine and turbine speeds. The results show that the proposed control strategy can achieve satisfactory performance.

Optimal engine-transmission control of neutral-idle clutch application

Mixed-Mode HCCI-DI Combustion on Common-Rail Diesel Engines: Experimental Characterization and Detailed Kinetic Modeling

In electrified powertrain control, meeting the torque demands and ensuring efficient Electrical Machine (EM) operations are two essential but conflicting demands. A multi-objective Linear Parameters Varying (LPV) controller is proposed to address the problem of these conflicting objectives. The synthesis of multi-objective controller is based on the selection of optimal weighting functions optimized by Genetic Algorithm (GA). The effectiveness of the proposed controller is tested and evaluated for an electrified powertrain operating in a standard urban driving cycles. The stability of the proposed Multi-Objective Controller (MOC) is established. The nonlinear simulation of the proposed controller delivers the robust performance and better efficiency of an EV Induction Machine (IM) based electric drive over the entire driving cycle.

Giorgio Rizzoni

Papers

Selection of residual generators in structural analysis for fault diagnosis using a diagnosability index

Optimal engine-transmission control of neutral-idle clutch application

Mixed-Mode HCCI-DI Combustion on Common-Rail Diesel Engines: Experimental Characterization and Detailed Kinetic Modeling

Genetic algorithms optimized multi-objective controller for an induction machine based electrified powertrain

A sensor array for control of engine exhaust after-treatment systems