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Ford Battery Group's Adoption of RADIOSS Cut Methodology for Enhanced Simulation Performance
Technology Category
- Other - Battery
- Robots - Autonomous Guided Vehicles (AGV)
Applicable Industries
- Automotive
- Packaging
Applicable Functions
- Procurement
- Product Research & Development
Use Cases
- Transportation Simulation
- Vehicle Performance Monitoring
The Challenge
Ford's battery core team was faced with a challenge when working in tandem with vehicle development. The vehicle electrification engineering teams required a highly detailed CAE model of the battery arrays, including each cell and various packaging configurations considered in the design. This detailed model was necessary to predict the robustness of the battery structure using CAE simulation. However, the detailed model, which could grow to several million elements, needed to be significantly simplified when data was passed to full vehicle teams. The combination of a detailed battery model with the complexity of a full vehicle model significantly slowed the cycle time and hindered the ability to run optimization and design exploration for both teams.
About The Customer
The customer in this case study is Ford's battery core team. This team works in tandem with the vehicle development team and is responsible for creating detailed CAE models of battery arrays. These models include each cell and various packaging configurations that are considered in the design. The team's goal is to predict the robustness of the battery structure using CAE simulation. However, they also need to simplify these models when passing data to full vehicle teams, which presents a significant challenge.
The Solution
To resolve the conflicting requirements, Ford's battery core group adopted the cut methodology (sub-modeling option) in RADIOSS. They ran a full vehicle simulation after selecting a zone that included and surrounded the battery structure as a sub-model. This zone also contained a common interface to the full vehicle model. The full vehicle analysis was simulated using a generic simplified representation of the battery, which provided a quick turnaround time. The displacement and force history was imposed on the submodel boundaries, and this time history data was then extracted at the common interface that was selected previously. Subsequent analysis of a much more detailed battery model used the interface files as input produced from the sub-model analysis.
Operational Impact
Quantitative Benefit
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