# 🔋 AI Battery Simulation

Physics-based battery modeling using **PyBaMM, electrochemistry, and AI**

This repository accompanies my **AI Battery Simulation** series exploring how electrochemistry, physics-based modeling, and AI come together to simulate and understand batteries.

---

## 🎯 Goal

Build a step-by-step bridge from:

**Electrochemistry → Physics-based Models → AI-ready Digital Twins**

This repository moves from:

- Fundamental equations  
- Equivalent circuit models  
- Single particle models  
- Pseudo-2D (DFN) models  
- Parameter presets  
- AI-ready simulations  

---

## 📚 Series Overview

### 📘 Part 1 — Electrochemistry & Battery Modeling

Fundamental equations:

- Nernst equation  
- Butler–Volmer kinetics  
- Fick diffusion  

Foundation of physics-based battery models.

---

### 📗 Part 2 — Solid-State Diffusion

Lithium diffusion inside electrode particles:

- Rate limitations  
- Performance impact  
- Aging mechanisms  

---

### 📙 Part 3 — Battery Model Overview

Comparison of:

- ECM  
- SPM  
- Pseudo-2D  
- AI-based models  

---

### 📘 Part 4 — Equivalent Circuit Models (ECM)

- RC networks  
- Thevenin models  
- Real-time simulation  

---

### 📗 Part 5 — Battery Simulation in Python

- PyBaMM introduction  
- Model execution  
- Visualization  
- Analysis  

---

### 📙 Part 6 — Single Particle Model (SPM)

Physics-based model:

- Solid diffusion  
- Reaction kinetics  
- Voltage prediction  

---

### 📘 Part 7 — Building SPM in PyBaMM

Notebook:

SPM_full_guide.ipynb

Includes:

- Running simulation  
- Parameter inspection  
- Visualization  

---

### 📗 Part 8 — Pseudo-2D (DFN) Model

Full electrochemical model:

- Electrolyte transport  
- Solid diffusion  
- Reaction kinetics  
- Spatial gradients  

---

### 📙 Part 9 — Building Pseudo-2D (DFN) in PyBaMM

Notebook:

DFN_comparison.ipynb

Includes:

- DFN simulation  
- Model comparison  
- Result analysis  

---

### 📘 Part 10 — PyBaMM Parameter Sets

Available parameter presets:

| Parameter Set | Chemistry |
|---------------|-----------|
| Chen2020 | NMC811 / Graphite |
| OKane2022 | NMC / Graphite |
| ORegan2022 | High-energy NMC |
| Prada2013 | LFP |
| Chayambuka2022 | Sodium-ion |

Files:

Chen2020.csv OKane2022.csv ORegan2022.csv Prada2013.csv Chayambuka2022.csv

---

## 🧠 Why This Repository

Battery modeling enables:

- Digital twins  
- Faster development  
- Reduced experimental cost  
- AI integration  
- Better battery design  

This repository demonstrates how to move from:

**Physics → Simulation → AI**

---

## 🛠 Tools

- PyBaMM  
- Python  
- NumPy  
- SciPy  
- Matplotlib  
- Jupyter Notebook  

---

## 🚀 Future Work

Upcoming topics:

- Hybrid physics-ML models  
- Parameter estimation  
- Battery digital twins  
- SoH prediction  
- Real-world data integration  

---

## 👨‍🔬 Author

**Dmitrii Makhov**  
Electrochemist | Battery Modeling | AI  

---

## ⭐ Support

If you find this repository useful:

- Star the repository  
- Share with colleagues  
- Follow the series