What is a battery thermal model?
A mathematical simulation that predicts how heat is generated, distributed, and dissipated inside a lithium-ion cell during operation
Rather than relying on surface thermocouples or manufacturer datasheets, a thermal model calculates the internal temperature field of a cell in real time, accounting for electrochemical heat generation, heat conduction through the cell geometry, and the effect of your cooling system on temperature evolution.
The critical insight: the hottest point in a cell is rarely at the surface. It is at the core. Core temperature governs degradation rate, lithium plating risk, and thermal runaway onset, with a critical influence on predictions of cell resistance and terminal voltage.
Model spectrum
0D
Lumped
Single thermal mass
Treats the cell as one thermal mass, predicting average temperature. Sufficient for cell comparison and first-pass cooling system sizing.
1D
Through-thickness
Core-to-surface gradient
Resolves temperature along a single axis, typically radial. The minimum fidelity needed to assess lithium plating risk and internal degradation rate.
2D
Through-thickness
Radial and axial
Predicts the full temperature distribution through a slice of the cell geometry, capturing radial and axial gradients whilst remaining tractable for real-time use.
3D
Full field
All spatial dimensions
Resolves temperature across all three spatial dimensions, capturing hotspots, tab effects, and asymmetric cooling. Essential for pack-level design and safety-critical validation.
For pack and systems engineers, the real value is this: evaluate tab cooling versus surface cooling, active versus passive strategies, in simulation before a single prototype is built. Make thermal management decisions on robust data, not assumed margins and physical trial and error.
The problem with designing blind
Most pack engineers start with a lumped thermal model or a thermocouple on the cell surface. Both tell you the same thing: average temperature, or a reading at one surface location. Neither tells you what is happening at the core.
The result is a design built on incomplete information. Your cooling system is sized for a temperature you can measure, not the temperature that actually determines cell health.
Core temperatures routinely run 10 to 15°C hotter than the surface during high-rate discharge. That gap is where packs overheat, degrade ahead of schedule, and fail warranty.
The fallback is physical testing. But physical testing at pack level is expensive, slow, and gives you answers too late in the programme to act on them cheaply. By the time a thermal issue surfaces in hardware, the fix requires a cooling architecture change, not a parameter tweak.
The over-engineering trap
Weight
Heavier cold plates
Excess mass added to compensate for unknown core temperatures. Margin stacked on margin because the model cannot be trusted.
Cost
More coolant flow
Pump and circuit sizing driven by worst-case assumptions rather than a real picture of the internal thermal field.
BOM
Expensive-grade TIM
Premium thermal interface material specified without confidence in the actual thermal path from core to cooling surface.
The pack ships over-weight, over-cost, and under-performing. The thermal model could not be trusted. A spatially resolved battery thermal model closes that gap: core temperature, the gradients, and how sensitive both are to your cooling strategy, before you cut metal or order cells.
How engineering teams are using it
A spatially resolved battery thermal model is a design tool, not a research tool. These are the five use cases where customers are using it to make better decisions earlier in the programme
Cooling strategy selection
Lock in your cooling architecture at concept stage, not validation stage. Compare tab, surface, and immersion cooling on the same cell before committing to hardware.
Pack design and TIM sizing
Ship a pack at the weight and cost it was designed to. Feed cell-level heat flux into Simulink, COMSOL, or Ansys and right-size your TIM and cold plate from first principles, not margins.
BMS thermal state estimation
Estimate core temperature, state of charge, and available power simultaneously under dynamic load. Integrates natively with Simulink and Simscape for real-time BMS deployment.
Fast charging validation
Demonstrate thermal safety compliance before hardware testing begins. Validate protocols against core temperature limits, not surface proxies, for any cell in the library.
Mission simulation
Reduce cell shortlisting time and catch thermal issues before touching hardware. Simulate full mission profiles across variable load phases, predicting peak core temperatures for any duty cycle.
Which thermal model do you need?
Not every application needs the same level of thermal fidelity. Explore the table below to see which is the best fit.
For most engineering challenges, a 1D or 2D thermal model is the right starting point. Both resolve core temperature and outperform a lumped model on every metric that matters for pack concept design, cooling architecture decisions, and degradation risk assessment, at a fraction of the computational cost of a full 3D model.
The fallback is physical testing. But physical testing at pack level is expensive, slow, and gives you answers too late in the programme to act on them cheaply. By the time a thermal issue surfaces in hardware, the fix requires a cooling architecture change, not a parameter tweak.
How About:Energy builds its thermal models
Most battery thermal models are only as good as their input parameters. Specific heat capacity, thermal conductivity in the radial and axial directions, and internal heat generation rates are notoriously difficult to measure accurately. The majority of models on the market use literature values or manufacturer datasheets for these parameters. About:Energy does not.
The result is a design built on incomplete information. Your cooling system is sized for a temperature you can measure, not the temperature that actually determines cell health.
Every thermal model is parameterised from physical characterisation of the specific commercial cell, carried out at About:Energy's 3,000 square foot London facility. Thermal parameters are measured using a patented measurement technique developed through doctoral research focused specifically on how batteries generate and dissipate heat. This is not a general-purpose measurement approach adapted for batteries. It was invented for batteries.
The characterisation programme covers heat generation across a representative range of temperatures, C-rates, and states of charge. Parameterisation data is supplied in full alongside every model in CSV, Python, and Simulink-compatible formats, so engineers can inspect every value, understand where it came from, and validate it against their own measurements if needed.
Validation is carried out against experimental temperature measurements across the cell surface and, where available, internal thermocouple data, and is documented and supplied with every model. The methodology is grounded in research programmes at two leading UK universities and developed with funding from the Faraday Battery Challenge programme.
What makes About:Energy's thermal model different
Patented measurement technology
The parameterisation behind every model comes from a measurement method invented specifically for batteries, not adapted from general-purpose calorimetry. No other commercial battery model supplier offers this.
White-box, fully documented
Every equation, boundary condition, and parameter value is visible, documented, and supplied with the model. Modify it, validate it against your own data, or integrate it directly into your existing simulation environment.
Cell-specific, not literature-based
Parameters are measured from the actual commercial cell in your design, not estimated from published values or manufacturer datasheets. Thermal conductivity, specific heat capacity, and heat generation rates are all cell and condition specific.
Native toolchain integration
Models are delivered in CSV, Python, Simulink, and Simscape compatible formats. Drop them into your existing workflow without format conversion or manual re-implementation.
Coupled electrothermal simulation
About:Energy's thermal model couples directly to About:Energy's ECM, giving you a full electrothermal simulation that predicts voltage, current, and core temperature simultaneously under dynamic load profiles.
Validated and documented
Every model ships with validation data covering surface and internal temperature measurements across a range of temperatures and C-rates. You can see exactly how the model performs before you build anything around it.
Trusted by engineers who cannot afford to get it wrong
About:Energy's battery thermal models are used by engineering teams across motorsport, drone, aviation, space, and automotive. Applications where thermal failure is not a warranty claim. It is a safety event, a lost race, or a failed mission.
Customers include McMurtry Automotive, EFT Mobility (part of Quantum Systems Group), MP Space, and teams across the full aerospace and high-performance vehicle spectrum.
Explore our Customer case studies
The pack ships over-weight, over-cost, and under-performing. The thermal model could not be trusted. A spatially resolved battery thermal model closes that gap: core temperature, the gradients, and how sensitive both are to your cooling strategy, before you cut metal or order cells.
Frequently asked questions (FAQs)
A lumped model predicts average cell temperature. A spatially resolved model predicts the full internal temperature distribution, including core temperature, radial gradients, and axial variation. If you are designing a cooling system, selecting TIM, or developing a BMS thermal observer, you need core temperature, not an average.
Because the hottest point in a cell is the core, not the surface. Under high-rate discharge, core temperatures routinely run 10 to 15°C above the surface reading. Size your cooling system around the surface and you are solving the wrong problem.
Yes. Both model tiers are available in Simulink and Simscape compatible formats, ready to drop into a model-based design workflow. Couple them to About:Energy's ECM for a full electrothermal simulation.
From physical characterisation of the specific commercial cell using a patented measurement technique, not manufacturer datasheets or literature values. Every parameter is supplied in full so you can inspect, validate, and modify it.
Yes. The coupled electrothermal model predicts voltage response and core temperature simultaneously under dynamic load, making it the standard approach for BMS thermal observer development and fast charging validation.
CSV, Python, Simulink, and Simscape. All formats are fully documented and compatible with your existing toolchain.
