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Addresses the methodology and theoretical foundation of battery manufacturing, service and management systems (BM²S²), 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 BM²S² 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…mehr
Addresses the methodology and theoretical foundation of battery manufacturing, service and management systems (BM²S²), 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 BM²S² 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 BM²S².
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JINGSHAN LI is a Professor in the Department of Industrial and Systems Engineering at the University of Wisconsin-Madison, USA. He received his PhD in Electrical Engineering - Systems at the University of Michigan, USA. SHIYU ZHOU is a Professor in the Department of Industrial and Systems Engineering at the Universityof Wisconsin-Madison, USA. He received his PhD in Mechanical Engineering at the University of Michigan, USA. YEHUI HAN is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Wisconsin-Madison, USA. He received his PhD in Electrical Engineering at the Massachusetts Institute of Technology, USA.
Inhaltsangabe
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
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
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