ADVANCED MODEL-BASED CHARGING CONTROL FOR LITHIUM -ION BATTERIES

In this book, the most state-of-the-art advanced model-based charging control technologies for lithium-ion batteries are explained from the fundamental theories to practical designs and applications, especially on the battery modelling, user-involved, and fast charging control algorithm design. Moreover, some other necessary design considerations, such as battery pack charging control with centralized and distributed structures, are also introduced to provide excellent solutions for improving the charging performance and extending the lifetime of the batteries/battery packs. Finally, some future directions are mentioned in brief. This book summarizes the model-based charging control technologies from the cell level to the battery pack level. From this book, readers interested in battery management can have a broad view of modern battery charging technologies. Readers who have no experience in battery management can learn the basic concept, analysis methods, and design principles of battery charging systems. Even for the readers who are occupied in this area, this book also provides rich knowledge on engineering applications and future trends of battery charging technologies. Preface Contents Acronyms 1 Introduction 1.1 Brief Introduction of Lithium-Ion Batteries 1.1.1 Comparison with Other Commonly Used Batteries 1.1.2 Applications of Lithium-Ion Batteries 1.2 Format Comparison of Lithium-Ion Batteries 1.3 Electrochemical Mechanism of Lithium-Ion Batteries 1.3.1 Composition of Lithium-Ion Batteries 1.3.2 Charging-Discharging Mechanism 1.4 Motivation of Advanced Model-Based Battery Charging Control 1.4.1 Non-model-based Charging Control 1.4.2 Model-Based Charging Control References 2 Lithium-Ion Battery Charging Technologies: Fundamental Concepts 2.1 Definitions Related to Battery Charging 2.1.1 Basic Performance Parameters 2.1.2 State Indicators 2.2 Charging Objectives and Constraints 2.2.1 Charging Objectives 2.2.2 Safety-Related Constraints References 3 Lithium-Ion Battery Models 3.1 Electrochemical Models 3.1.1 Pseudo-Two-Dimensional Model 3.1.2 One-Dimensional Model 3.1.3 Single Particle Model 3.2 Equivalent Circuit Models 3.2.1 Rint Model 3.2.2 Thevenin Model 3.2.3 PNGV Model References 4 Neural Network-Based State of Charge Observer for Lithium-Ion Batteries 4.1 Battery Model 4.2 Neural Network-Based Nonlinear Observer Design for SOC Estimation 4.2.1 Neural Network-Based Nonlinear Observer Design 4.2.2 Convergence Analysis 4.3 Experimental Results 4.3.1 Experiment for Parameter Extraction 4.3.2 Experiments for SOC Estimation References 5 Co-estimation of State of Charge and Model Parameters for Lithium–Ion Batteries 5.1 Battery Model 5.2 Co-estimation of Model Parameters and SOC 5.2.1 On-line Battery Model Parameter Identification 5.2.2 Robust Observer for SOC Estimation 5.2.3 Summary of the Overall SOC Estimation Strategy 5.3 Experimental Results 5.3.1 Experimental Results for Battery Model Parameter On-line Identification 5.3.2 Experimental Results for SOC Estimation References 6 User-Involved Battery Charging Control with Economic Cost Optimization 6.1 Battery Model and Constraints 6.1.1 Battery Model 6.1.2 Safety-Related Constraints 6.2 Charging Tasks 6.2.1 User-Involved Charging Task 6.2.2 Economic Cost Optimization 6.2.3 Energy Loss Reduction 6.2.4 Multi-objective Formulation 6.3 Optimal Battery Charging Control Design 6.3.1 Optimal Charging Control Algorithm 6.3.2 Optimal Charging Current Determined by Barrier Method 6.4 Simulation Results 6.4.1 Charging Results 6.4.2 Comparison with Other Commonly Used Optimization Algorithms 6.4.3 Comparison with Charging Control Strategy without Economic Cost Optimization 6.4.4 Comparison with Charging Control Strategy Without Energy Loss Optimization 6.4.5 Simulation Results for Different Weight Selections 6.4.6 Simulation Results for Different User Demands 6.4.7 Comparison with Traditional CC-CV Charging Methods 6.5 Experimental Results References 7 Charging Analysis for Lithium-Ion Battery Packs 7.1 Cell Equalization Analysis 7.2 Multi-module Battery Pack Charger 7.2.1 Model and Control of Battery Pack Charger 7.2.2 Performance Validation 7.3 Battery Pack Charging System Combining Traditional Charger and Equalizers 7.3.1 Classification of Equalization Systems 7.3.2 Bidirectional Modified Cûk Converter-Based Equalizer 7.3.3 Modified Isolated Bidirectional Buck-Boost Converter-Based Equalizer References 8 User-Involved Charging Control for Battery Packs: Centralized Structure 8.1 Battery Pack Model and Constraints 8.1.1 Battery Pack Model 8.1.2 Charging Constraints 8.2 User-Involved Charging Control Design for Battery Packs 8.2.1 Charging Objectives 8.2.2 Optimal Battery Pack Charging Control Design 8.3 Simulation Results 8.3.1 Charging Results 8.3.2 High Current Charging 8.3.3 Effect Analysis of Weight Selection 8.4 Experimental Results References 9 User-Involved Charging Control for Battery Packs: Leader-Followers Structure 9.1 Charging Model and Constraints 9.1.1 Battery Pack Model 9.1.2 Safety-Related Charging Constraints 9.2 User-Involved Optimal Charging Control Design 9.2.1 User-Involved Charging Task Formulation 9.2.2 Optimal Average Charging Trajectory Generation 9.2.3 Distributed SOC Tracking-Based Charging Control 9.2.4 Different Sampling Period Setting for Two Control Layers 9.3 Simulation Results and Discussions 9.3.1 Charging Results 9.3.2 Discussions References 10 Fast Battery Charging Control for Battery Packs 10.1 Charging Model for the Battery Pack 10.1.1 Charging Current Model 10.1.2 Battery Pack Model 10.2 Control Objectives and Constraints 10.2.1 Charging Objectives 10.2.2 Charging Constraints 10.3 Fast Charging Control Strategy Design 10.3.1 Charging Control Algorithm Formulation 10.3.2 Two-Layer Optimization Algorithm 10.4 Simulation Results 10.5 Experimental Results References 11 The Future of Lithium-Ion Battery Charging Technologies 11.1 Multi-objective Optimization-Based Charging Technologies 11.2 High Efficient Battery Pack Charging Technologies 11.3 Wireless Charging Technologies