Electric Bus Battery Management Repository

This repository contains files associated with the management of electric bus batteries, addressing various aspects related to data assessment, degradation optimization, and energy retrieval. Each file serves a distinct purpose in achieving the main objective. Below is an overview of the key files:

1. clean_data_assessment 🧹

Purpose:

This file is dedicated to the initial data cleaning and assessment phase. It focuses on preparing the data required for subsequent stages in the electric bus battery management process.

Usage:

• Data cleaning and preprocessing procedures.
• Initial assessment of data quality.
• Preparing the dataset for degradation optimization and energy retrieval.

2. EB-opt_degradation ⚙️

Purpose:

The EB-opt_degradation file is integral to the degradation optimization process. It addresses challenges related to battery lifespan, capital expenditure, and operational efficiency.

Usage:

• Calculation and optimization of degradation costs for electric bus batteries.
• Implementation of strategies to extend battery lifespan.
• Utilization of degradation models and optimization frameworks.

3. energy_retrieval 🔋

Purpose:

This file focuses on the retrieval of energy from electric bus batteries, exploring opportunities such as Vehicle-to-Grid (V2G) technology.

Usage:

• Assessment of energy retrieval strategies.
• Integration of electric buses with the grid through V2G technology.
• Optimization of energy retrieval processes for grid resilience and additional revenue streams.

4. semiempiric_results 📊

Purpose:

The semiempiric_results file is dedicated to the presentation and analysis of results obtained through the semi-empirical degradation model.

Usage:

• Presentation and analysis of results derived from the tailored semi-empirical degradation model.
• Detailed insights into battery health and degradation over time.
• Consideration of weather impacts, especially extreme temperatures.

Instructions for Use:

1. Data Cleaning and Assessment:

   • Open and run clean_data_assessment for initial data preparation.

2. Degradation Optimization:

   • Utilize EB-opt_degradation for calculating and optimizing degradation costs.

3. Energy Retrieval:

   • Explore energy_retrieval for strategies related to energy retrieval and V2G technology.

4. Results Analysis:

   • Refer to semiempiric_results for a detailed analysis of results obtained through the semi-empirical degradation model.

Feel free to explore each file for more specific instructions and details on their respective functionalities. This repository aims to provide a comprehensive solution for managing electric bus batteries, addressing key challenges and optimizing operational efficiency.