The unique feature of Q-Bat is its speed and 3-D accuracy. A transient simulation of an entire EV battery pack for the complete driving or charging profile goes within a few minutes on a desktop computer. And it produces 3-D temperature distribution like a CFD solver. Using Q-Bat means:
- real-time simulation of the entire EV battery pack,
- finite element formulation of the heat transfer problem,
- modelling all battery nonlinearities,
- import of 3-D CAD geometry or mesh files,
- integration with MATLAB, Simulink and others.
Q-Bat is like a CFD solver. The workflow starts with the CAD geometry of the battery pack. Alternatively, it can import CFD meshes. Next, you define material properties, boundary conditions and the electric current profile. Then, Q-Bat calculates finite element matrices, and the unique feature is its 3-D model order reduction to the eigenvectors space. Thanks to that, your desktop computer is able to generate time-dependent 3-D temperature distribution in each battery pack component within a few minutes. A good example?
- EV battery pack CFD mesh with 5 million finite elements,
- Simulation of a 30 minutes long driving profile,
- Less than 2 minutes on the Intel i7 PC.
Due to its speed and accuracy Q-Bat allows for:
- CFD thermal modelling of battery pack components,
- geometry optimization,
- detailed battery cooling investigation in system-level simulations of the entire electric powetrain.
Q-Bat is used for applications in automotive industry, for electric aircraft battery modelling or power tools industry.
Electric bus, e-motorcycle, and forklift batteries are further examples of our customer projects.
We have helped a German car maker bring Q-Bat to the simulation workflow. Q-Bat imports CFD meshes and generates a Simulink block for vehicle-level simulations. Still 3-D and very quick.
We have used Q-Bat to help Green Cubes Technology optimize their forklift battery packs for optimal heat removal during rapid charging.
Battery Packs of power tools are usually passive cooled. Q-Bat coupled with MATLAB Simulink allowed defining a complex electric current load and get the time evolution of 3-D temperature distribution.
We had previously worked with another CFD company to calculate the thermal behavior of our battery packs and they needed to make plenty of simplifications. That's why I was eager to start cooperation with QuickerSim who claimed to have 3-D battery thermal simulation technology that can handle transient cases and nonlinear properties. The results were accurate and reliable.
The team was very communicative and available to answer any questions at any time. I'm glad I decided to work with them, and I happily recommended QuickerSim
Functions & Models
You can import battery pack CAD geometry from a *.step file or the mesh files. We support Ansys Fluent, Nastran, Star CCM+, Ansa and *.cgns mesh formats.
Building a battery simulation model in Q-Bat is quick. The setup wizard automatically detects repeating components (like electrochemical cells) and all contact surfaces.
Contrary to many CFD solvers or reduced-order models, Q-Bat already has equivalent circuit models of cells. Also, it accounts for varrying mass flow rate of the coolant or dependence of internal resistance on temperature and SOC.
The finite element dicretization makes it work like a CFD solver. The model-order reduction to the eigenvectors space makes it 100-1000x quicker than CFD. Still it gives 3-D temperature results with accuracy better than 1 degree C.
Q-Bat is a bridge between CFD and system-level battery simulations. The 3-D finite element thermal model can be exported as a Simulink block. Then, you can use it in any Simulink simulation as a detailed 3-D thermal battery model.
Q-Bat is built in MATLAB environment. Most functions also can be used in Simulink. You can also couple Q-Bat with Simscape Electrical for advanced electrical simulations. Or with Batemo cell models for detailed cell simulations.
Webinars & Tutorials:
Is it real 3D?
Yes. You get all the 3D data, just as in regular CFD tools.
What is the error compared to CFD / tests?
The price in accuracy loss we need to pay for the enormous speed up in simulation time is quite low. The usual error we see is 2-5% compared to full CFD results.
Explain the Model Order Reduction
The brief explanation is short. Q-Bat starts with the CAD geometry (or the mesh), assembles the finite element matrices (as each CFD solver would do), and you apply the boundary conditions (external temperatures, electric load, mass flow rate of the coolant). Next, however, it does not start solving the discretized equations but runs automatic model order reduction. To do so, Q-Bat calculates eigenvectors of the heat conduction problem and generates 1-D finite volumes in the cooling channels. By doing so, the number of unknowns in the system is usually reduced approximately 1000 times. Then, Q-Bat starts time iterations in the reduced vector space and visualizes the 3-D temperature results back on the full 3-D mesh
Simulation time with coarse vs dense mesh / simplified vs detailed geometry
Mesh density has little effect on simulation time. It can, however, proportionally extend the time needed for the model order reduction phase.
What is the cell model?
You can use 0th or 1st order equivalent circuit model. The model data can be dependent on temperature and SOC.
What data is needed to simulate?
You will need the same data as with regular CFD simulations: material data on all of the simulated components, battery cell model, 3D geometry of the battery or its mesh.
Is there a limit to several components/meshes elements?
No, there is no limit to the number of components or mesh elements, as long as your PC has enough RAM to handle the model.