Battery-Development-project

This project is a PySpark-based solution for processing battery data, performing forward and backward interpolation for missing values, and spatial interpolation using Radial Basis Functions (RBF). The final output is a CSV file containing the interpolated data.

Features

Data Preprocessing: Handles data cleaning and renaming for consistent column names.

Forward and Backward Interpolation: Fills missing values in battery sensor data by leveraging forward and backward windows.

Radial Basis Function (RBF) Interpolation: Applies RBF interpolation to estimate spatially distributed sensor values on a battery grid.

Output to CSV: Saves the processed and interpolated data into a CSV file for further analysis.

Prerequisites

Ensure the following tools and libraries are installed before running the project:

Tools

Python 3.8+

Apache Spark 3.0+

Python Libraries

Install the required Python libraries using pip:

pip install pyspark pandas numpy scipy

Installation

Clone the repository:

git clone https://github.com/your-repo/battery-data-interpolation.git cd battery-data-interpolation

Place your input CSV file (sample_battery_data.csv) in the project directory.

Update the data_path_csv variable in the script if the file path differs.

Project Structure

├── battery_interpolation.py # Main PySpark script

├── sample_battery_data.csv # Input data file

├── requirements.txt # required libraries to pip install

├── README.md # Project documentation

How to Run

Start the Spark environment.

spark-submit battery_interpolation.py

The processed output will be saved as battery_interpolation.csv in the specified directory.

Key Components

Forward and Backward Interpolation

Radial Basis Function (RBF) Interpolation

Sample Output Data

The output CSV contains interpolated values for all sensor data columns, including spatially interpolated values for a 104-point grid.

Contribution

Feel free to fork this repository, submit pull requests, or report issues for any suggestions or improvements.

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🙋 Author

LinkedIn: http://www.linkedin.com/in/SwapnilTaware

GitHub: https://github.com/itsSwapnil

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License

This project is licensed under the MIT License. See the LICENSE file for details.