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

Composite electrode lithium-ion batteries can offer improved energy and power density, as well as increased cycle life compared to batteries with a single active material electrode. Both available power and cell life are functions of the local current allocated to each composite material, however there are no examples in literature of electrochemical-based models of composite electrode cells that are suitable for estimation and control. We present a reduced order, electrochemical model of a composite LiMn2O4 - LiNi1/3Mn1/3Co1/3O2 cell that predicts bulk and surface concentrations of each composite material, as well as the local current allocated to each material. Observability properties are analyzed by approximating the system as linear over certain operating conditions. A solution method is developed to use the model in an extended Kalman filter for online state of charge estimation, which is validated with experimental data.

Model-based state of charge estimation and observability analysis of a composite electrode lithium-ion battery

Modeling for drivability and drivability improving control of HEV

Fault detection and identification in dynamic systems with noisy data and parameter/modeling uncertainties

Natural gas has recently been proposed as an alternative fuel for transportation in the United States. Refueling infrastructure is the major technological barrier to the market penetration of passenger compressed natural gas (CNG) vehicles. Currently, there is about one natural gas refueling station every 150 gasoline pumps. Nevertheless, natural gas is widely available in American houses, and thus distributed residential refueling is seen as a viable solution.Generally, residential CNG refueling systems use compressors driven by electric motors. With a potential increase in the number of residential natural gas refueling systems over the next few years, the additional load that this system will introduce on the electric power infrastructure can be significant. In this paper, a system dynamic model of a residential refueling system has been developed and validated against data available in the literature. Ultimately, the model will allow for exploring the impact of residential refueling of CNG vehicles on the electric power infrastructure.Copyright © 2014 by ASME

Giorgio Rizzoni

Papers

Model-based state of charge estimation and observability analysis of a composite electrode lithium-ion battery

Modeling for drivability and drivability improving control of HEV

Fault detection and identification in dynamic systems with noisy data and parameter/modeling uncertainties

Modeling and Analysis of a CNG Residential Refueling System

Combustion Diagnostics in Methane-Fueled SI Engines Using the Spark Plug as an Ionization Probe