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

Chapter THREE

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

Chapter FOUR

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

Chapter FIVE

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

Project 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.


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