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State of Health estimation for power lithium ion batteries and safety predictions in its power supply

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目录

声明

1. INTRODUCTION

1.1 Background

1.2 Problem Statement

1.3 Research Objectives

1.4 Significance of this Study

1.5 Thesis Structure

2. MATHEMATICALANALYSIS

2.1 Introduction of Lithium battery

2.1.1 Lithium battery composition

2.1.2 The chemical reactions of Lithium batteries

2.1.3 Outline classification of lithium batteries

2.2 Direct method of SOH estimation

2.2.1 Capacity or Energy Measurement (AH counting)

2.2.2. Ohmic resistance

2.2.3 Impedance Measurement

2.2.4 Cycle number counting

2.2.5 Destructive methods

2.3 Indirect method

2.3.1 Charging curve method

2.3.2 ICA Method

2.3.3 DVA Method

2.3.4 Other heath index methods

2.4 Model-Based Methods (Adaptive State Estimation Methods)

2.4.1 Equivalent circuit model based methods

2.4.2 Electrochemical Model

2.4.3 Combined Model methods

2.5 Data-driven methods

2.5.1 Empirical and fitting methods

2.5.2 Optimization algorithms

2.5.3 Sample Entropy Methods

2.6 Degradation in li-ion batteries

2.6.1 Degradation in negative electrodes

2.6.2 Degradation in positive electrodes

2.7 The Chapter Summary

3. MODEL BUILDINGAND DEVELOPMENT

3.1 Data Collection and Experiments

3.1.1 Capacity test

3.1.2 The Hybrid Power Pulse Characteristic (HPPC) test

4.1.3 Charging and discharging test

3.2 Modelling

3.2.1 Battery Characterization

3.2.2 Selection of Model

3.2.3 Parameter Estimation

3.2.4 Validation of Parameters

3.2.5 Mathematical Analysis

3.3 Model Construction

3.3.1 Algorithm used (Extended Kalman Filter)

3.3.2 Construction of simulation model

3.3.3 Battery Model

3.4 Comprehensive Health State estimation

3.5 The Chapter Summary

4. DATAPRESENTATIONAND DISCUSSION

4.1 Results from Capacity test

4.1.1 Capacity at various temperature

4.1.2 Function relationship

4.2 Results from HPPC test

4.2.1 The Open Circuit Voltage curve

4.2.2 The Parameter verification results

4.2.3 The Estimation of State of Charge results by EKF algorithm

4.2.4 The Estimation of State of Health using the Kalman Filter

4.3 Safety Predictions and precautions

4.3.1 Ambient Temperature

4.3.2 Knowledge of battery capacity before usage

4.4 The Chapter Summary

5. CONCLUSIONAND SUMMARY

参考文献

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著录项

  • 作者

    Coffie-Ken James;

  • 作者单位

    西南科技大学;

  • 授予单位 西南科技大学;
  • 学科 Control Science and Engineering
  • 授予学位 硕士
  • 导师姓名 Wang Shunli;
  • 年度 2020
  • 页码
  • 总页数
  • 原文格式 PDF
  • 正文语种 chi
  • 中图分类 TV7TV;
  • 关键词

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