VTO Lab Call AOI 3- Truck R&D (Text Version)

This is the text version for the "VTO Lab Call AOI 3- Truck R&D" video.

Video opens with variety of trucks and horn honking.

Narrator: There are a lot of trucks on the road, and there will be many more in the future. Trucks drive the nation's economy, from the many services they provide and jobs they support.

Video cuts to theoretical research building and researcher.

Narrator: So how can we make them cleaner and more efficient? And what research is critical to getting us where we want to be?

Video cuts to animation data flying around the screen.

Narrator: It all starts with data—lots of data—on how trucks are actually used. But how do we make sense of, and know whether we have the right data?

Video cuts to animation of medium- and heavy- duty trucks.

Narrator: The traditional ways to classify trucks – class 3-8 or by vocation – are not sufficient to capture the complexities of how trucks are used in the real world.

Video cuts to data visuals and researchers in a lab studying the data.

Narrator: We need to take advantage of the latest advances in data analytics, machine learning, and high performance computing—as well as the smartest researchers—to capture the greatest insights.

Video cuts to animation of complex data network process.

Narrator: One promising approach is data driven clustering, which uses machine learning techniques based on artificial neural networks to organize complex, multi-dimensional data into self-organizing maps.

Video cuts to animation of various trucks.

Narrator: The result is a grouping of vehicles by how they’re actually used.

Video cuts to animation of a chromosome, paired with groups of trucks by size.

Narrator: What we call a “vocational chromosome”. Each “chromosome” represents a cluster of vehicles that operate similarly, regardless of traditional class or vocation.

Pair each vocational chromosome with the right data— data that is representative of how each cluster of trucks operates across the country.

Fill in any data gaps, and then you have a powerful tool to do a lot of important things.

Video of trucks driving and being used for various work on roads and in real life.

Narrator: The data lets us understand the operating characteristics for each cluster, including how fast the trucks are driven, how much stop-and-go traffic they experience, and how much power they require.

Video of internal truck workings, including powertrains.

Narrator: This information is critical for models used to optimize powertrains, develop components, understand mobility patterns, develop supporting infrastructure models, and understand total cost of ownership.

Visual representation of national data repository, and animation showing how data can be used by researchers.

Narrator: It also provides the framework for a comprehensive and easily accessible national data repository which, combined with high performance computing and the latest computational analytics, can help researchers across the country develop energy efficient commercial vehicle technologies and systems.

Video cuts to visual representing research options for vehicle designs.

Narrator: OEMs have a lot of options for combining engines, transmissions, and other powertrain components into a range of efficient vehicle architectures that meet the needs of their customers —sometimes too many options.

Video of transportation research facility.

Narrator: And that’s where high performance computing, innovative analytics, and state of the art experimental facilities can help.

Video of trucks driving on roads.

To accelerate the development of commercially viable efficient trucks, we need a research tool that identifies the optimal powertrain for each vocational chromosome.

Video cuts to visual of vocational chromosome and vehicle modeling data research for future designs of vehicles.

Narrator: This tool should be a collaborative, open source software platform that enables variable-fidelity and multi-physics full vehicle modeling across distributed computation resources.

Video of supporting animation of researcher and representative of the hypothetical tool designed by research.

Narrator: This will create a highly flexible simulation environment that can fully utilize modern computational resources and connect a wide range of laboratory and industry models. The result is a powerful tool for optimizing overall design and selecting the right powertrain for the right job.

Video cuts to visuals and animation of vocational chromosome(s).

Narrator: That's just some of the possibilities unlocked by having representative data for just one vocational chromosome.

But we can repeat this process for each vocational chromosome …and develop new understanding of how trucks are used and what opportunities are available for optimizing them efficiently and effectively.

Video of inner workings of trucks and animations of truck inner workings.

Narrator: Collectively we can optimize battery, power electronic, and electric machine requirements across all vocational chromosomes to harmonize these components.

Video of trucks driving and operating on roads.

Harmonization will facilitate designs that meet the broadest range of commercial vehicle applications, allowing for larger volumes, simplified maintenance through standardization, and significant cost reductions.

Video of research visuals and charging stations for electric vehicles.

Narrator: We can also identify opportunities to tailor improvements to conventional powertrain components , and address the lack of charging infrastructure for commercial vehicles along major freight corridors.

Video cuts to researchers in a laboratory and futuristic data visuals of trucks.

Narrator: So, There are lot of ways that VTO-funded commercial vehicle research can leverage national lab expertise in high performance computing, innovative analytics, machine learning, state of the art experimental facilities, and world-class researchers to develop the right technology for the right applications and pave the way to a cleaner and more efficient future, for all of us.


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