- 基于先进模型的锂离子电池充电控制(英文版)(精)/节能与新能源汽车关键技术研究丛书
- - 作者：欧阳权//陈剑|责编:姚同梅
  - 出版社：华中科技大学
  - ISBN：9787577207988
  - 出版日期：2024/05/01
  - 页数：176
- 售价：63.2

内容大纲
可充电锂离子电池因其能量密度高、循环寿命长、成本下降等优点，已广泛应用于从电动汽车到微电网等众多行业的储能领域。充电是锂离子电池补充和储存能量的重要过程，充电策略的好坏极大地影响着锂离子电池的性能和寿命。用精确的数学模型进行分析和预测在充电过程中电池状态的变化，基于先进模型的充电策略可以提供优异的充电性能，如延迟电池寿命的退化。因此，研究基于先进模型的锂离子电池充电控制策略具有重要的工程和学术价值。基于此，本书将从基础理论到实际设计和应用，详细介绍目前最先进的基于模型的锂离子电池充电控制技术，特别是在电池建模、状态估计和最优充电控制方面。此外，还介绍了一些必要的设计考虑因素，如集中式和领导-追随结构的电池组充电控制，为提高充电性能和延长电池/电池组的寿命提供了出色的解决方案。本书所提供的丰富的材料和知识，可以让我们从理论设计到工程应用对电池充电控制技术有足够的了解。
作者介绍
目录
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 C？k 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 Strategies
  11.3  Wireless Charging Technologies

内容大纲

作者介绍

目录

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