How to start your new electrification program faster with smart performance targets
 
Performing vehicle benchmarking studies is a key and mandatory element in a standard product development cycle in order to achieve the first step of target-settings at sub-system levels. The electrification of vehicles generates an increased number of architectures possibilities to meet stringent energy efficiency levels and performance targets. Powertrain thermal management and battery cooling are key aspects of those architectures. The technology choices - air cooling, liquid cooling, refrigerant cooling through chillers, or a more advanced system with the cabin cooling involved - have a strong impact on the overall energy balance. Getting early insights on the performance target levels for any possible configuration is critical to get a competitive edge. Accessing hundreds of vehicle architectures in limited timeframes requires a new development methodology where simulation and testing are essential.
 
In this webinar, our experts will introduce an all-in-one approach to perform vehicle benchmarking studies and support target setting & requirements definition and decision-making on technologies and architectures to successfully balance and optimize seemingly conflicting requirements. We’ll detail our post-processing approach that enables fast data exploitation, and our testing and simulation framework that enables to get even better insights on possible innovations and architecture choices to win the competition race.
 
How to implement the right vehicle benchmarking studies framework for optimized vehicle energy management
What will you learn in this webinar?
 
- A workflow to ensure consistent and standardized data and model generation between available and future tested vehicles
- How to make the right choices to select the relevant benchmark vehicles 
- How you can participate in the initiative and be aboard /have control over instrumentation for the next vehicles 
- How we support the complete process while enhancing the raw data by developing and validating 1D simulation models of the vehicles to deliver even more insights and generate new valuable data to the design departments.

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