🔋 Battery State of Charge Estimator

An interactive Battery State of Charge (SoC) Estimator built using Python, Streamlit, Pandas, NumPy, and Plotly. The application estimates battery State of Charge using configurable voltage profiles for multiple battery chemistries and presents the results through an interactive dashboard.

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🌐 Live Demo

🚀 Try the live application here:

battery-soc-estimator

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📸 Dashboard

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📖 Overview

Battery State of Charge (SoC) represents the remaining usable capacity of a battery and is one of the most important parameters in a Battery Management System (BMS).

This project estimates the remaining battery charge by comparing measured terminal voltage against configurable voltage-to-SoC lookup tables. Users can upload battery discharge datasets, visualize discharge behaviour, generate battery statistics, and export processed results through an interactive Streamlit dashboard.

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✨ Features

• 🔋 Supports Lithium-Ion, LiFePO₄, and Lead Acid battery chemistries
• 📂 Upload custom battery discharge datasets in CSV format
• ⚡ Voltage-based State of Charge estimation using interpolation
• 📊 Interactive battery summary
• 📈 Interactive Plotly visualizations
• 📥 Export processed battery data as CSV
• 🧩 Modular Python project structure
• 🌐 User-friendly Streamlit dashboard

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🖼️ Application Preview

Dashboard

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Processed Battery Data

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Configuration Panel

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⚙️ Workflow

Select Battery Profile
        │
        ▼
Upload Battery Discharge CSV
        │
        ▼
Load Battery Voltage Profile
        │
        ▼
Estimate SoC using Voltage Interpolation
        │
        ▼
Generate Battery Statistics
        │
        ▼
Interactive Dashboard
        │
        ▼
Download Processed CSV

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📁 Project Structure

Battery-SOC-Estimator/
│
├── app.py
├── README.md
├── requirements.txt
│
├── images/
│   ├── dashboard.png
│   ├── processed-data.png
│   └── sidebar.png
│
├── data/
│   ├── profiles/
│   │   ├── lithium_ion.csv
│   │   ├── lifepo4.csv
│   │   └── lead_acid.csv
│   │
│   └── raw/
│       ├── lithium_ion_discharge.csv
│       ├── lifepo4_discharge.csv
│       └── lead_acid_discharge.csv
│
├── src/
│   ├── data_loader.py
│   ├── profile_loader.py
│   ├── soc_estimator.py
│   ├── statistics.py
│   └── visualization.py
│
└── outputs/

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🚀 Installation

Clone the repository

git clone https://github.com/Shv8ank/Battery-SOC-Estimator.git

Move into the project directory

cd Battery-SOC-Estimator

Create a virtual environment

Windows

python -m venv .venv
.venv\Scripts\activate

macOS / Linux

python3 -m venv .venv
source .venv/bin/activate

Install dependencies

pip install -r requirements.txt

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▶️ Run the Application

streamlit run app.py

Open your browser and visit

http://localhost:8501

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📄 Sample Datasets

The repository contains sample discharge datasets and voltage profiles for:

• 🔋 Lithium-Ion
• 🔋 LiFePO₄
• 🔋 Lead Acid

These datasets can be found inside:

data/raw/

with their corresponding battery profiles located in:

data/profiles/

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🛠️ Technologies Used

Category	Technology
Programming Language	Python
Web Framework	Streamlit
Data Processing	Pandas, NumPy
Visualization	Plotly
Data Storage	CSV
Version Control	Git & GitHub

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🔮 Future Improvements

• 🤖 Machine Learning based SoC prediction
• 🔋 Battery State of Health (SoH) estimation
• 🌡️ Temperature-compensated battery models
• 📡 Real-time Battery Management System (BMS) integration
• 🌐 REST API support
• ☁️ IoT dashboard integration
• 📱 Mobile-friendly interface