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.

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.

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