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Webinar Abstract & Topics :

• Early-stage Battery Selection & Sizing Trade-off studies
• Identify aging effects under all operating conditions
• Identification of routes that drive aging with a digital twin
• Push conflicting goals of the BMS to a secure limit and choose the best trade off
• Integrate predictive AutoLion battery models with AI data analytics & cloud monitoring

When it comes to battery selection, integration and developing of controls strategy many unknown factors of vehicle in use phase need to be considered. Common limitations today make it difficult to gain control over lifetime, warranty and fleet prediction.

Learn how to complement data driven insights and early-stage cell testing with AutoLion digital twins for safer, longer & powerful battery operation. The approach is based on electro-chemical thermal models which do not only enable for predictions of fleet range and aging, but as digital twins can identify damaging scenarios or routes that drive aging in the control's strategy.

Enable a future multi-technique approach. Integrate fully predictive AutoLion battery models with AI data analytics & cloud monitoring.

In the webinar Michael Vallinder will present some use cases of how AutoLion battery models are applied at the electric powertrain development at Scania, impacting different development stages from first battery selection all the way down to thermal and controls strategy.