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Case Study

Complex Battery System Storage Modeling with Ansys Twin Builder and Ansys Fluent


Designing an entirely new energy storage system requires building a complex system model that can simulate and capture the thermoelectric and electrochemical behavior of the battery and the complicated transient heat transfer between multiple system components. The model must be able to accurately predict battery module temperature change in transient analysis (the calculation of a circuit’s response over a defined time period). Successful simulation depends on seamless data exchange between the system model and a unique software environment.


Engineering Solution

  • Input battery dynamic performance data to calculate and build a 6-parameter battery cell model based on the electric circuit model (ECM)
  • Built a chiller model to calculate power consumption and cooling capacity based on battery and coolant temperature
  • Generated and validated a reduced order model (ROM) from a fully converged computational fluid dynamics (CFD) model of the cold plate to solve conflicts between accuracy and computational speed
  • Combined the ECM and ROM models into a battery module to understand state of charge (SOC) as a function of power, coolant, and ambient temperatures to control battery charge and discharge rates
  • Combined model components, resulting in an accurate battery storage  system model  for testing and validation



Simulation enables the team to deliver an accurate, reliable model of the storage system that can be used for testing and validation of overall system performance over the life of the battery. With Ansys solutions, we can easily predict what is going to happen over the next five years. The simulation software provides intuitive, user-friendly tools that address system development and validation from every perspective. We use this comprehensive set of solvers at every stage during validation, whether working at the system level or capturing a specific electrical response. Twin Builder’s ROM technology also enables us to reduce simulation time from one day to 10 minutes with a high-fidelity representation of the CFD model, resulting in faster product development.

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