Electric vehicle battery thermal management is one of the most challenging multiphysics problems in modern engineering. The battery pack must maintain optimal operating temperatures (typically 25-35°C) across all cells, under conditions ranging from cold starts at -20°C to sustained high-power charging in summer heat.
Why Conjugate Heat Transfer?
Conjugate Heat Transfer (CHT) simulation couples fluid dynamics with solid conduction, enabling accurate prediction of temperature distributions. Unlike simplified thermal models, CHT captures the complex interplay between:
- •Coolant flow through channels
- •Heat generation in cells
- •Heat spreading through structural components
Electrochemical-Thermal Coupling
Battery cells exhibit spatially and temporally varying heat generation rates that depend on:
| Factor | Impact |
|---|---|
| State of Charge (SoC) | Varies heat generation profile |
| Current Rate (C-rate) | Quadratic increase in heat |
| Temperature | Affects internal resistance |
Our Modeling Approach
We use experimentally validated reduced-order battery models that capture these dynamics without the computational expense of full electrochemical simulation.
Heat Generation Model:
Q = I²R(T, SoC) + I·T·(dU/dT)
↑ ↑
Joule heating Entropic heating
Liquid Cooling System Design
Liquid cooling system design involves careful optimization of:
- •Channel geometry for uniform flow distribution
- •Flow rates balancing cooling vs. pumping power
- •Coolant properties (viscosity, specific heat)
CFD enables virtual prototyping of hundreds of design variations, identifying configurations that minimize temperature gradients while meeting packaging, weight, and cost constraints.
Parametric Optimization Workflow
Our parametric optimization workflows automate this exploration:
Input Parameters → CFD Simulation → Response Surface → Optimization
↓ ↓ ↓ ↓
Channel width Temperature Surrogate model Optimal design
Flow rate Pressure drop (Kriging/RBF) identified
Inlet position Uniformity
Phase Change Materials (PCMs)
Phase change materials offer passive thermal buffering that complements active cooling. Simulating PCM behavior requires accurate modeling of:
- •Latent heat absorption during melting
- •Thermal conductivity changes during phase transition
- •Long-term cycling stability
"We have developed specialized simulation methodologies validated against calorimetric testing."
Fast Charging: The Ultimate Stress Test
Fast charging is the ultimate stress test for thermal management systems. Peak heat generation rates can exceed 10x normal operation, and the cooling system must prevent thermal runaway while minimizing charging time.
Our transient simulations predict worst-case scenarios:
| Charging Scenario | Peak Heat Rate | Max ΔT Allowed |
|---|---|---|
| Normal (1C) | 100% baseline | 10°C |
| Fast (2C) | 400% baseline | 8°C |
| Superfast (3C) | 900% baseline | 5°C |
These insights guide the design of robust thermal management strategies.
Key Takeaways
- •CHT simulation captures the full complexity of battery thermal behavior
- •Electrochemical-thermal coupling is essential for accurate heat generation modeling
- •Parametric CFD enables rapid optimization of cooling system designs
- •PCM simulation requires specialized methodologies for phase transition modeling
- •Fast charging scenarios drive the most demanding thermal requirements
Designing an EV battery thermal management system? Let's talk about your thermal challenges.
