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Introduction

In recent years, the adoption of electric vehicles (EVs) has been on the rise due to the increasing awareness of the environmental impact of traditional internal combustion engine vehicles. However, one of the key challenges in the widespread adoption of EVs is the degradation of the battery system over time, leading to decreased performance and range. To address this issue, predictive maintenance using artificial intelligence (AI) has emerged as a promising solution to optimize the maintenance of electric vehicle batteries.

Chapter One: Introduction

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 Thesis
1.9 Definition of Terms

Chapter Two: Literature Review

2.1 Overview of Predictive Maintenance
2.2 AI in Predictive Maintenance
2.3 Predictive Maintenance for Electric Vehicle Batteries
2.4 Battery Degradation Mechanisms
2.5 State-of-the-Art Technologies in Battery Health Management
2.6 Machine Learning Algorithms for Predictive Maintenance
2.7 Challenges in Implementing AI-powered Predictive Maintenance
2.8 Case Studies on AI-powered Predictive Maintenance for EV Batteries
2.9 Future Trends in AI-powered Predictive Maintenance
2.10 Summary of Literature Review

Chapter Three: Research Methodology

3.1 Research Design
3.2 Data Collection
3.3 Data Preprocessing
3.4 Feature Selection
3.5 Model Development
3.6 Model Evaluation
3.7 Performance Metrics
3.8 Validation Techniques

Chapter Four: Discussion of Findings

4.1 Overview of Data Analysis
4.2 Performance Evaluation of AI Models
4.3 Comparison with Traditional Maintenance Approaches
4.4 Interpretation of Results
4.5 Implications for EV Battery Maintenance
4.6 Recommendations for Future Research
4.7 Practical Applications of AI-powered Predictive Maintenance
4.8 Limitations of the Study

Chapter Five: Conclusion and Summary

5.1 Summary of Findings
5.2 Conclusions
5.3 Contributions to the Field
5.4 Implications for Industry
5.5 Future Directions for Research

Overall, this thesis will explore the potential of AI-powered predictive maintenance for electric vehicle batteries, aiming to enhance the reliability and efficiency of EVs. By leveraging advanced AI algorithms and predictive analytics, this research seeks to address the challenges associated with battery degradation and optimize maintenance schedules to prolong battery life and improve overall vehicle performance.

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