Altair Case Studies Ford Battery Group's Adoption of RADIOSS Cut Methodology for Enhanced Simulation Performance

	Ford Battery Group's Adoption of RADIOSS Cut Methodology for Enhanced Simulation Performance Altair

Ford Battery Group's Adoption of RADIOSS Cut Methodology for Enhanced Simulation Performance

Altair

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
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. Read More
About 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. Read More
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. Read More Log in to view content
Contents

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

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 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.

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.

Impact #1	The adoption of the RADIOSS cut methodology by Ford's battery core team resulted in several operational benefits. The team was able to create detailed CAE models of battery arrays that could be simplified for use by full vehicle teams, resolving the conflicting requirements of the two teams. This approach also allowed for a quick turnaround time, enabling the team to run optimization and design exploration more efficiently. Furthermore, the use of a common interface facilitated the sharing of data between different departments, improving collaboration and efficiency. Finally, the detailed modelling improved the accuracy of the simulations, leading to better design and performance of the battery modules and components.

Impact #1

The adoption of the RADIOSS cut methodology by Ford's battery core team resulted in several operational benefits. The team was able to create detailed CAE models of battery arrays that could be simplified for use by full vehicle teams, resolving the conflicting requirements of the two teams. This approach also allowed for a quick turnaround time, enabling the team to run optimization and design exploration more efficiently. Furthermore, the use of a common interface facilitated the sharing of data between different departments, improving collaboration and efficiency. Finally, the detailed modelling improved the accuracy of the simulations, leading to better design and performance of the battery modules and components.

Benefit #1	50% reduction in modelling efforts.
Benefit #2	Performance benefit by having suitable models for different purposes.
Benefit #3	Sharing of light interface data between the battery zone and vehicle across different departments.

Benefit #1

50% reduction in modelling efforts.

Benefit #2

Performance benefit by having suitable models for different purposes.

Benefit #3

Sharing of light interface data between the battery zone and vehicle across different departments.

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Overview

Ford Battery Group's Adoption of RADIOSS Cut Methodology for Enhanced Simulation Performance

Operational Impact

Quantitative Benefit