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Advances in battery manufacturing, service, and management systems / / edited by Jingshan Li, Shiyu Zhou, Yehui Han
Advances in battery manufacturing, service, and management systems / / edited by Jingshan Li, Shiyu Zhou, Yehui Han
Pubbl/distr/stampa Hoboken, New Jersey : , : Wiley, [2017]
Descrizione fisica 1 online resource (411 p.)
Disciplina 621.31242
Collana IEEE Press series on systems science and engineering
Soggetto topico Electric batteries
ISBN 1-119-06087-7
1-119-06063-X
1-119-06074-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 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-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.
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.
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-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.
Record Nr. UNINA-9910135027703321
Hoboken, New Jersey : , : Wiley, [2017]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advances in battery manufacturing, service, and management systems / / edited by Jingshan Li, Shiyu Zhou, Yehui Han
Advances in battery manufacturing, service, and management systems / / edited by Jingshan Li, Shiyu Zhou, Yehui Han
Pubbl/distr/stampa Hoboken, New Jersey : , : Wiley, [2017]
Descrizione fisica 1 online resource (411 p.)
Disciplina 621.31242
Collana IEEE Press series on systems science and engineering
Soggetto topico Electric batteries
ISBN 1-119-06087-7
1-119-06063-X
1-119-06074-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 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-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.
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.
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-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.
Record Nr. UNINA-9910830229603321
Hoboken, New Jersey : , : Wiley, [2017]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui