⚡🚗 SOC-Based Range Estimation for Electric Vehicles

📌 Project Overview

This project focuses on predicting the estimated range of an electric vehicle (EV) based on its State of Charge (SOC) and other relevant parameters using machine learning. The goal is to assist EV users and manufacturers in optimizing range predictions for better energy management and decision-making.

🛠 Features

• 🔹 Machine Learning Model: Supervised learning algorithms for SOC-based range estimation
• 🔹 Real-World Data Collection: Dataset obtained from a Mahindra XUV 400
• 🔹 Input Parameters: Voltage, current, SOC, temperature, and other key factors
• 🔹 Python-Based Implementation for model training and prediction
• 🔹 Data Visualization & Analysis

📊 Applications

✅ Battery Management Systems (BMS) – Improve EV range estimation
✅ Energy Optimization – Enhance driving efficiency based on SOC predictions
✅ Real-Time EV Monitoring – Provide accurate range predictions for users

🚀 Getting Started

1. Clone the repository

   git clone https://github.com/Srihari334/SOC-estimation-of-Ev-battery.git