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Embedded impedance based state-of-charge estimation

 

Table Of Contents


Chapter ONE

1.1 Introduction
1.2 Background of Study
1.3 Problem Statement
1.4 Objective of Study
1.5 Limitation of Study
1.6 Scope of Study
1.7 Significance of Study
1.8 Structure of the Research
1.9 Definition of Terms

Chapter TWO

2.1 Overview of State-of-Charge Estimation
2.2 Historical Development of State-of-Charge Estimation
2.3 Impedance-Based State-of-Charge Estimation Techniques
2.4 Mathematical Models for State-of-Charge Estimation
2.5 Challenges in State-of-Charge Estimation
2.6 Applications of State-of-Charge Estimation
2.7 Comparison of Different State-of-Charge Estimation Methods
2.8 State-of-Charge Estimation in Electric Vehicles
2.9 State-of-Charge Estimation in Energy Storage Systems
2.10 Future Trends in State-of-Charge Estimation

Chapter THREE

3.1 Research Methodology Overview
3.2 Research Design and Approach
3.3 Data Collection Methods
3.4 Sampling Techniques
3.5 Data Analysis Procedures
3.6 Validity and Reliability of Data
3.7 Ethical Considerations
3.8 Limitations of the Research Methodology

Chapter FOUR

4.1 Analysis of State-of-Charge Estimation Techniques
4.2 Evaluation of Mathematical Models
4.3 Comparison of Experimental Results
4.4 Interpretation of Data Findings
4.5 Discussion on Implications of Findings
4.6 Practical Applications of State-of-Charge Estimation
4.7 Recommendations for Future Research
4.8 Conclusion of Findings

Chapter FIVE

5.1 Summary of Research Findings
5.2 Conclusion and Interpretation
5.3 Contributions to the Field
5.4 Implications for Practice
5.5 Recommendations for Further Study
5.6 Conclusion and Final Remarks

Thesis Abstract

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.

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.


Thesis Overview

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