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

Lithium ion (Li-ion) battery pack is a complex system consisting of numerous cells connected in parallel and series. The performance of the pack is highly dependent on the health of each individual in-pack cell. An overcharged or discharged cell connected in a parallel string could change the total capacity of the battery pack. In a pack, current-split estimation plays an important role to monitor the cell functions. Therefore, a scheme is required to estimate current-split accurately, which can thereby help to improve the overall pack performance. To what follows, a recursive weighted covariance-based estimation method (RWEM) was proposed to estimate the current-split of each set of parallel connected cells. RWEM assigns weights to the interconnected cell structure by using correlation information between battery parameters in order to estimate the current-split. This was achieved by first deriving the one-step prediction error method, where consistency for covariance was proved. Furthermore, iterative recursion for sparse measurements was also considered. Performance evaluations were conducted by analyzing sets of real-time measurements collected from Li-ion battery pack used in electric vehicles (EVs). Results show that the proposed filter accurately estimated the battery parameters even in the presence of faults and random-noise variances.

Current-Split Estimation in Li-Ion Battery Pack: An Enhanced Weighted Recursive Filter Method

In Chap. 4 we presented the DP as a numerical tool to solve the optimal control problem for hybrid electric vehicles as defined in Sect. 3.4.

Pontryagin’s Minimum Principle

One of the most important challenges for effective energy management in Hybrid Electric Vehicles (HEVs) applications is the capability of correctly estimate the batteries State of Charge (SoC). This task is particularly arduous to accomplish in real-time, due to the complexity and nonlinearities, as well as the inevitable presence of on-board measurements errors. The objective of this paper is to develop a NiMH battery model which accounts for the relevant dynamics related to HEV applications. A detailed series of experiments allowed for system identification to be performed in order to design an equivalent electrical circuit model of the battery, where capacitors take care of voltage relaxations, while resistors model all forms of energy losses. Experimental results are then compared with model prediction, resulting in variances limited to less than 3.5%. Finally, the validated model was inverted to serve as a main component of a proposed SoC estimator, whose performance is of key relevance for effectiveness of HEVs. Results during actual vehicle operations are shown delineating a successful application.Copyright © 2007 by ASME

NiMH Battery Characterization and State-of-Charge Estimation for HEV Applications

Refinement of a Parallel-Series PHEV for Year 3 of the EcoCAR 2 Competition

This paper presents the formulation of the optimal detection filter problem, for optimization with respect to process and measurement noises. The necessary conditions for the existence of the optimal detection filter are obtained, and a numerical solution technique is shown to be feasible by virtue of the uniqueness of the detection filter gains.

Giorgio Rizzoni

Papers

Current-Split Estimation in Li-Ion Battery Pack: An Enhanced Weighted Recursive Filter Method

Pontryagin’s Minimum Principle

NiMH Battery Characterization and State-of-Charge Estimation for HEV Applications

Refinement of a Parallel-Series PHEV for Year 3 of the EcoCAR 2 Competition

A New Interpretation of the Fault Detection Filter: The Optimal Detection Filter