Embedded impedance based state-of-charge estimation

 

Table Of Contents


Chapter ONE

INTRODUCTION

  • 1.1Introduction
  • 1.2Background of study
  • 1.3Problem Statement
  • 1.4Objective of study
  • 1.5Limitation of study
  • 1.6Scope of study
  • 1.7Significance of study
  • 1.8Structure of the research
  • 1.9Definition of terms

Chapter TWO

LITERATURE REVIEW

  • 2.1Overview of Impedance-Based State-of-Charge Estimation
  • 2.2Historical Development of Impedance Techniques
  • 2.3Impedance Spectroscopy in Battery Management
  • 2.4State-of-Charge Estimation Models
  • 2.5Challenges in State-of-Charge Estimation
  • 2.6Comparative Analysis of Impedance-Based Methods
  • 2.7Applications of Impedance-Based State-of-Charge Estimation
  • 2.8Future Trends in Impedance-Based Techniques
  • 2.9Impact of Impedance-Based Techniques on Battery Technology
  • 2.10Summary of Literature Review on Impedance-Based State-of-Charge Estimation

Chapter THREE

RESEARCH METHODOLOGY

  • 3.1Research Design and Approach
  • 3.2Selection of Study Participants
  • 3.3Data Collection Methods
  • 3.4Instrumentation and Equipment
  • 3.5Data Analysis Techniques
  • 3.6Validation of Results
  • 3.7Ethical Considerations
  • 3.8Limitations of the Research Methodology

Chapter FOUR

DATA PRESENTATION AND ANALYSIS

  • 4.1Analysis of Data Collected
  • 4.2Comparison of Impedance-Based Models
  • 4.3Interpretation of Results
  • 4.4Discussion on State-of-Charge Estimation Accuracy
  • 4.5Impact of Temperature on Impedance-Based Techniques
  • 4.6Influence of Battery Age on Estimation Performance
  • 4.7Implications for Battery Management Systems
  • 4.8Recommendations for Future Research

Chapter FIVE

SUMMARY, CONCLUSION AND RECOMMENDATIONS

  • 5.1Summary of Findings
  • 5.2Conclusion
  • 5.3Contributions to the Field
  • 5.4Implications for Practice
  • 5.5Recommendations for Further Study

Project Abstract

<p> </p><p>Estimating the battery state-of-charge is an important aspect of prolonging battery life and optimizing discharge cycles. In this thesis, a hybrid method for estimating state-of-charge for lead-acid batteries is developed and implemented in a motor controller.</p><p>The method uses a combination of impedance measurements and a linear regression model for estimation. Measurements are done at stand-still. The method does not require sensors that are external to the motor controller or auxiliary battery connections other than terminal connections. The final estimation model shows good results but exhibits a slight ambient temperature dependence.</p> <br><p></p>

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