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[null,"1.","Record Nr.",null,"UNINA9910789972203321"]
[null,null,"Autore",null,"Talbot Kevin"]
[null,null,"Titolo",null,"Motor neuron disease [[electronic resource] /] / Kevin Talbot, Rachael Marsden"]
[null,null,"Pubbl/distr/stampa",null,"Oxford ; ; New York, : Oxford University Press, c2008"]
[null,null,"ISBN",null,"1-383-03461-3"]
[{"$nulls":4},"1-283-58229-5"]
[{"$nulls":4},"9786613894748"]
[{"$nulls":4},"0-19-154864-2"]
[{"$nulls":4},"0-19-160719-3"]
[null,null,"Descrizione fisica",null,"1 online resource (160 p.)"]
[null,null,"Collana",null,"The facts"]
[null,null,"Disciplina",null,"616.8/39"]
[null,null,"Soggetti",null,"Amyotrophic lateral sclerosis"]
[{"$nulls":4},"Motor neurons - Diseases"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Includes index."]
[null,null,"Nota di contenuto",null,"Contents; Preface; 1 What is motor neuron disease?; 2 The cause of motor neuron disease; 3 The individual patient journey; 4 The treatment of motor neuron disease and the management of specific symptoms; 5 Maintaining well-being; 6 Special situations in motor neuron disease; 7 Participating in research; 8 Decision-making and remaining in control; 9 Caring for people living with motor neuron disease; 10 Useful information; Index; A; B; C; D; E; F; G; H; I; J; L; M; N; O; P; Q; R; S; T; U; V; W"]
[null,null,null,"Sommario/riassunto","Motor neuron disease (MND) is a common but devastating disability that has a profound impact on people's lives. This book provides an easily-accessible guide to the disease for patients with motor neuron disease and their carers. The authors have organised it around a series of the commonest questions asked in their clinic, emphasising the variation in the course of MND and the individual nature of the patient journey through the disease. After an initial description of thesymptoms for MND and how neurologists make the diagnosis the authors describe what is known about the causes and how scien"]
[null,"2.","Record Nr.",null,"UNINA9910830229603321"]
[null,null,"Titolo",null,"Advances in battery manufacturing, service, and management systems / / edited by Jingshan Li, Shiyu Zhou, Yehui Han"]
[null,null,"Pubbl/distr/stampa",null,"Hoboken, New Jersey : , : Wiley, [2017]"]
[{"$nulls":4},"[Piscataqay, New Jersey] : , : IEEE Xplore, , [2016]"]
[null,null,"ISBN",null,"1-119-06087-7"]
[{"$nulls":4},"1-119-06063-X"]
[{"$nulls":4},"1-119-06074-5"]
[null,null,"Descrizione fisica",null,"1 online resource (411 p.)"]
[null,null,"Collana",null,"IEEE Press series on systems science and engineering"]
[null,null,"Disciplina",null,"621.31242"]
[null,null,"Soggetti",null,"Electric batteries"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references at the end of each chapters and index."]
[null,null,"Nota di contenuto",null,"PREFACE XV -- CONTRIBUTORS XIX -- PART I BATTERY MANUFACTURING SYSTEMS -- 1 LITHIUM-ION BATTERY MANUFACTURING FOR ELECTRIC VEHICLES: A CONTEMPORARY OVERVIEW 3 /Wayne Cai -- 1.1 Introduction 3 -- 1.2 Li-Ion Battery Cells, Modules, and Packs 4 -- 1.3 Joining Technologies for Batteries 8 -- 1.4 Battery Manufacturing: The Industrial Landscape 19 -- 1.5 Conclusions 25 -- 2 IMPROVING BATTERY MANUFACTURING THROUGH QUALITY AND PRODUCTIVITY BOTTLENECK INDICATORS 29 /Feng Ju, Jingshan Li, Guoxian Xiao, Ningjian Huang, Jorge Arinez, Stephan Biller, and Weiwen Deng -- 2.1 Introduction 29 -- 2.2 Literature Review 31 -- 2.3 Problem Formulation 33 -- 2.4 Integrated Quality and Productivity Performance Evaluation 35 -- 2.5 Bottleneck Analysis 46 -- 2.6 Conclusions 50 -- 3 EVENT-BASED MODELING FOR BATTERY MANUFACTURING SYSTEMS USING SENSOR DATA 57 /Qing Chang, Yang Li, Stephan Biller, and Guoxian Xiao -- 3.1 Introduction 57 -- 3.2 Sensor Networks for Battery Manufacturing System 58 -- 3.3 Event-based Modeling Approach 60 -- 3.4 Event-based Diagnosis for Market Demand / Driven Battery Manufacturing 68 -- 3.5 Event-based Costing for Market Demand / Driven Battery Manufacturing System 76 -- 3.6 Conclusions 77 -- 4 A REVIEW ON END-OF-LIFE BATTERY MANAGEMENT: CHALLENGES, MODELING, AND SOLUTION METHODS 79 /Xiaoning Jin -- 4.1 Introduction / 79 -- 4.2 Research Issues of Battery Remanufacturing / 82 -- 4.3 Modeling and Analysis for Battery-"]
[{"$nulls":4},"Remanufacturing Systems / 88 -- 4.4 Summary / 94 -- References / 94 -- 5 AN ANALYTICS APPROACH FOR INCORPORATING MARKET DEMAND INTO PRODUCTION DESIGN AND OPERATIONS OPTIMIZATION 99 /Chris Johnson, Bahar Biller, Shanshan Wang, and Stephan Biller -- 5.1 Introduction 99 -- 5.2 Design and Operational Decision Support 101 -- 5.3 Linkage to a Financial Transfer Function 104 -- 5.4 A Quantification of Risk in Design and Operations 110 -- 5.5 Exploration of Design and Operations Choices 113 -- 5.6 Manufacturing Operations Transfer Function: Throughput, Inventory, Expense, and Fulfillment 118."]
[{"$nulls":4},"5.7 Activity-based Costing 120 -- 5.8 Conclusion 123 -- PART II BATTERY SERVICE SYSTEMS -- 6 PROGNOSTIC CLASSIFICATION PROBLEM IN BATTERY HEALTH MANAGEMENT 129 /Junbo Son, Raed Kontar, and Shiyu Zhou -- 6.1 Introduction 129 -- 6.2 Failure Predictions by Logistic Regression and JPM 132 -- 6.3 Numerical Study 136 -- 6.4 Discussion of the Impact of Imbalanced Data 143 -- 6.5 Conclusion 146 -- 7 A BAYESIAN APPROACH TO BATTERY PROGNOSTICS AND HEALTH MANAGEMENT 151 /Bhaskar Saha -- 7.1 Introduction 151 -- 7.2 Background 152 -- 7.3 Battery Model for a Bayesian Approach 154 -- 7.4 Particle Filtering Framework for State Tracking and Prediction 156 -- 7.5 Battery Model Considerations for PF Performance 160 -- 7.6 Decision Making for Optimizing Battery Use 167 -- 7.7 Summary 171 -- 8 RECENT RESEARCH ON BATTERY DIAGNOSTICS, PROGNOSTICS, AND UNCERTAINTY MANAGEMENT 175 /Zhimin Xi, Rong Jing, Cheol Lee, and Mushegh Hayrapetyan -- 8.1 Introduction 175 -- 8.2 Battery Diagnostics 177 -- 8.3 Battery Prognostics 186 -- 8.4 Uncertainty Management 195 -- 8.5 Summary 207 -- 9 LITHIUM-ION BATTERY REMAINING USEFUL LIFE ESTIMATION BASED ON ENSEMBLE LEARNING WITH LS-SVM ALGORITHM 217 /Yu Peng, Siyuan Lu, Wei Xie, Datong Liu, and Haitao Liao -- 9.1 Introduction 217 -- 9.2 LS-SVM Algorithm 218 -- 9.3 LS-SVM Ensemble Learning Algorithm 220 -- 9.4 Experiment Verification and Analysis 224 -- 9.5 Conclusion 226 -- 10 DATA-DRIVEN PROGNOSTICS FOR BATTERIES SUBJECT TO HARD FAILURE 233 /Qiang Zhou, Jianing Man, and Junbo Son -- 10.1 Introduction 233 -- 10.2 The Prognostic Model 236 -- 10.3 Simulation Study 245 -- 10.4 Summary 251 -- PART III BATTERY MANAGEMENT SYSTEMS (BMS) -- 11 REVIEW OF BATTERY EQUALIZERS AND INTRODUCTION TO THE INTEGRATED BUILDING BLOCK DESIGN OF DISTRIBUTED BMS 257 /Ye Li, Yehui Han, and Liang Zhang -- 11.1 Concept of Battery Equalization 257 -- 11.2 Equalization Methods 258 -- 11.3 Introduction of Integrated Building Block Design of a Distributed BMS 264 -- 11.4 The Proposed Integrated Building Block Design of BMS 264."]
[{"$nulls":4},"11.5 System Implementation 268 -- 11.6 Tested System Description 270 -- 11.7 Functional Performance Evaluation 273 -- 11.8 Conclusion 276 -- 12 MATHEMATICAL MODELING, PERFORMANCE ANALYSIS AND CONTROL OF BATTERY EQUALIZATION SYSTEMS: REVIEW AND RECENT DEVELOPMENTS 281 /Weiji Han, Liang Zhang, and Yehui Han -- 12.1 Introduction 281 -- 12.2 Modeling of Battery Equalization Systems 282 -- 12.3 Performance Evaluation of Battery Equalization Systems 289 -- 12.4 Control Strategies for Battery Equalization Systems 292 -- 12.5 Summary 297 -- 13 REVIEW OF STRUCTURES AND CONTROL OF BATTERYSUPERCAPACITOR HYBRID ENERGY STORAGE SYSTEM FOR ELECTRIC VEHICLES 303 /Feng Ju, Qiao Zhang, Weiwen Deng, and Jingshan Li -- 13.1 Introduction 303 -- 13.2 Batteries for EVs 304 -- 13.3 Supercapacitors for EVs 305 -- 13.4 Battery-Supercapacitor Hybrid Energy Storage System 306 -- 13.5 Control Strategy for HESS 312 -- 14 POWER MANAGEMENT CONTROL STRATEGY OF BATTERY-"]
[{"$nulls":4},"SUPERCAPACITOR HYBRID ENERGY STORAGE SYSTEM USED IN ELECTRIC VEHICLES 319 /Qiao Zhang, Weiwen Deng, Jian Wu, Feng Ju, and Jingshan Li -- 14.1 Introduction 319 -- 14.2 Low-Level Hybrid Topologies 320 -- 14.3 High-Level Supervisory Control 323 -- 14.4 Conclusions 350 -- 15 FEDERAL AND STATE INCENTIVES HEIGHTEN CONSUMER INTEREST IN ELECTRIC VEHICLES 355 /William Canis -- 15.1 Introduction 355 -- 15.2 Electric Vehicles and the Federal Role 356 -- 15.3 Public Interest in HEVs and Electric Vehicles 358 -- 15.4 Federal Support for HEVs and Electric Vehicles 360 -- 15.5 Support for EVs in the Obama Administration 363 -- 15.6 Impact of GHG Regulations 366 -- 15.7 Vehicle Environmental Life Cycle Comparisons 368 -- 15.8 State Initiatives 369 -- 15.9 Prospects for Growth / 373 -- 15.10 Conclusion 376 -- Acknowledgment 376 -- References 376 -- INDEX 381."]
[null,null,null,"Sommario/riassunto","Addresses the methodology and theoretical foundation of battery manufacturing, service and management systems (BM 2</sup>S 2</sup>), and discusses the issues and challenges in these areas This book brings together experts in the field to highlight the cutting edge research advances in BM 2</sup>S 2</sup> and to promote an innovative integrated research framework responding to the challenges. There are three major parts included in this book: manufacturing, service, and management. The first part focuses on battery manufacturing systems, including modeling, analysis, design and control, as well as economic and risk analyses. The second part focuses on information technology's impact on service systems, such as data-driven reliability modeling, failure prognosis, and service decision making methodologies for battery services. The third part addresses battery management systems (BMS) for control and optimization of battery cells, operations, and hybrid storage systems to ensure overall performance and safety, as well as EV management. The contributors consist of experts from universities, industry research centers, and government agency. In addition, this book: . Provides comprehensive overviews of lithium-ion battery and battery electrical vehicle manufacturing, as well as economic returns and government support. Introduces integrated models for quality propagation and productivity improvement, as well as indicators for bottleneck identification and mitigation in battery manufacturing. Covers models and diagnosis algorithms for battery SOC and SOH estimation, data-driven prognosis algorithms for predicting the remaining useful life (RUL) of battery SOC and SOH. Presents mathematical models and novel structure of battery equalizers in battery management systems (BMS). Reviews the state of the art of battery, supercapacitor, and battery-supercapacitor hybrid energy storage systems (HESSs) for advanced electric vehicle applications Advances in Battery Manufacturing, Services, and Management Systems is written for researchers and engineers working on battery manufacturing, service, operations, logistics, and management. It can also serve as a reference for senior undergraduate and graduate students interested in BM 2</sup>S 2</sup>."]