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.

/pdf/review-of-battery-charger-topologies-charging-power-levels-85yy2igx2w.pdf

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

An introduction to heat transfer

Due to the increasing demands on improved fuel economy and stringent government regulations on tailpipe emissions, many automotive industries and research institutes have been looking for alternative solutions, such as diesel engines, hybrid-electric vehicles, and fuel cell technologies, over conventional port fuel injection (PFI) gasoline engines to meet the demands. On the other hand, many people in the automotive community also realize that there are still a lot of room for improvements in gasoline engine technologies, such as utilizing direct injection and/or variable valve actuation. In order to fully realize the potential benefits of such advanced technologies in gasoline engines, a well-coordinated complex control system design is essential. This paper describes the development and validation of a control-oriented mean-value model for a spark-ignition direct-injection (SIDI) engine to assist and accelerate such coordinated control system design and calibration processes via use of an engine model. The performance and accuracy of the dynamic engine model are evaluated and validated against a set of data for an engine running on a transient driving cycle.Copyright © 2003 by ASME

Development and Validation of a Control-Oriented Model of a Spark-Ignition Direct-Injection Engine

Intelligent Control of the Ohio State University Hybrid-Electric Vehicle

/pdf/a-method-for-the-characterization-of-off-road-terrain-5d4bs0c6to.pdf

A Method for the Characterization of Off-Road Terrain Severity

The control problems that arise in connection with hybrid powertrains are significant, and pose great challenges to power-train control engineers. Big obstacles to the control design are the model complexity, and the necessity of a knowledge “a priori” of torque and velocity profiles for optimal fuel consumption and exhaust emissions. The aim of this paper is to propose a robust approach to the development of supervisory control strategies for hybrid-electric drivetrains. The objective is to determine an output feedback controller that minimize fuel consumption with respect to a family of possible torque/power input profiles, e.g. urban driving cycles. Sufficient conditions for the existence of a robust controller satisfying stability, L 2 gain attenuation between inputs and outputs of interst, and input/output bound constraints are derived by means of a set of linear matrix inequalities (LMIs).Copyright © 2003 by ASME

Supervisory Robust Control of Hybrid Electric Vehicles

The introduction of hybrid vehicle architectures into the mass car market has dramatically increased fault detection and mitigation strategies seen in vehicles to match the growth in potential failures coming from increasingly complex powertrain architectures. To meet this increased demand for fault detection and mitigation of multiple powertrain components, advanced methodologies have been developed to determine the functional safety of systems. This paper focuses on the use of one of those advanced methodologies, structural analysis, to develop the design, implementation, diagnostics, and control of a prototype automated manual transmission. Structural analysis is the concept of analyzing the mathematical structure of a system to determine the diagnostic coverage of sensors in the system. From this information, a controls strategy can be developed to address potential failure modes of a system utilizing the derived equations and knowledge of which sensors provide coverage for failure modes analyzed. Additionally, lack of coverage for failure modes can be seen through this analysis and the need for additional sensors determined to provide coverage in those areas. Using structural analysis, the Ohio State University EcoCAR 3 research team carried out a diagnostic and mitigation study during the development of their automated manual transmission.

Giorgio Rizzoni

Papers

Development and Validation of a Control-Oriented Model of a Spark-Ignition Direct-Injection Engine

Intelligent Control of the Ohio State University Hybrid-Electric Vehicle

A Method for the Characterization of Off-Road Terrain Severity

Supervisory Robust Control of Hybrid Electric Vehicles

System Diagnosis and Fault Mitigation Strategies for an Automated Manual Transmission