This project focuses on reliability-oriented statistical lifecycle modelling of lithium-ion batteries used in electric vehicle applications.
The research investigates battery degradation behaviour, lifecycle stability, and durability characteristics using probabilistic and statistical analytical approaches. Reliability-based modelling frameworks were developed to evaluate degradation trends, failure probability, and long-term lifecycle behaviour under varying operational conditions.
Statistical lifecycle analysis techniques including Weibull-based reliability modelling were integrated with experimental battery datasets to support predictive maintenance strategies and durability-focused lifecycle assessment.
This repository presents the project architecture, statistical modelling framework, and reliability analysis methodology developed during academic research.
- Reliability-oriented battery lifecycle analysis
- Statistical degradation and failure probability modelling
- Weibull-based lifecycle reliability assessment
- Predictive maintenance and durability analytics
- Experimental degradation dataset integration
- MATLAB
- Weibull Distribution Modelling
- Statistical Reliability Analysis
- Experimental Battery Datasets
- Lifecycle & Durability Analytics
This project demonstrates how reliability engineering and statistical lifecycle modelling can support degradation forecasting, failure probability assessment, predictive maintenance planning, and long-term durability evaluation for electric vehicle battery systems.
The implementation used in this project was developed as part of academic research and related publications.
To maintain research integrity and comply with institutional and publication-related guidelines, the full source code and modelling configurations are not publicly released.
This repository is intended to present the project concept, reliability framework, and analytical methodology.
Code access may be shared upon request for academic collaboration or research discussion.