Cathode Energy

AI-Powered Simulation Platform for Li-ion Batteries

⚗️ Electrochemical Modeling of Li-Ion Batteries

Understanding and predicting the performance, degradation, and efficiency of lithium-ion batteries requires more than just electrical circuit models. While Equivalent-Circuit Models (ECMs) provide simplified representations, they cannot capture the complex physical and electrochemical phenomena occurring inside the battery.

To address this, electrochemical models are developed based on physics-based equations that describe:

These models offer a detailed view of battery behavior, from the electrode particle level to the full cell.


🧪 Key Electrochemical Modeling Approaches

Several electrochemical modeling strategies are widely used, each offering a different trade-off between accuracy and computational efficiency:

1. Doyle-Fuller-Newman (DFN) Model

2. Single Particle Model with Electrolyte (SPMe)

3. Single Particle Model (SPM)


🔬 Battery Cell Structure Overview

A schematic representation of a lithium-ion battery helps visualize how these models interact with physical components:

Electrochemical Models


🧾 Summary of Electrochemical Models

Model Accuracy Efficiency Electrolyte Effects Best Use Case
DFN ⭐⭐⭐⭐⭐ ✅ Yes High-fidelity simulation
SPMe ⭐⭐⭐⭐ ⭐⭐⭐ ✅ Yes Real-time capable with good accuracy
SPM ⭐⭐ ⭐⭐⭐⭐⭐ ❌ No Fast estimation and embedded applications

📌 Figure: Schematic illustration of Li-ion battery chemistry (a), and electrochemical models: DFN (b), SPMe (c), and SPM (d).


🔗 Explore these models interactively at cathode.energy — your AI-powered simulation hub for Li-ion batteries!

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