NREL, Freight Industry, Academia, and Technology Partners Develop Promising Solution To Cost-Effectively Increase Trucking Efficiency
Picture a truck delivering goods on the highway. Although you are seeing only a single vehicle, it represents just one component in a highly intricate system. That truck is specialized machinery, operated by a trained and specially licensed driver, part of a larger fleet delivering shipments across a particular region—with these logistics managed by other people directing where the trucks go and when.
The complexity of the trucking network makes it possible for us to get our goods quickly, but it also makes reducing costs challenging. Answering urgent questions such as “What aspects can we make more efficient?” or “How will one choice impact other aspects of the trucking system?” have become paramount to making progress.
Researchers at NREL looked for answers to these complex questions through the U.S. Department of Energy-funded Co-Optimization of Vehicles and Routes (CoVaR) project, alongside project lead PACCAR and its subsidiary Kenworth, and partners Esri, Kopius, and Ohio State University. CoVaR brings optimization tools to truck drivers’ dashboards and fleet operators’ computers, helping trucking companies save money and streamline logistics.
“In addition to leading the program, PACCAR facilitated a unique collaboration that combined NREL’s advanced modeling capabilities with PACCAR’s real-world, high-resolution data collection,” said Maarten Meijer, a senior advanced technologies engineering manager at PACCAR. “This approach enabled baseline assessment and improvement validation on existing truck fleets across the United States, as well as on near-production battery electric vehicles operated near the PACCAR Technical Center in Mount Vernon, Washington.”
Through the CoVaR project, the researchers explored a multipronged technology package that could allow fleet managers to optimize different aspects of fleet design and operation to reduce fuel usage and cost—all using ready-to-deploy tools and software that could be on vehicles now. Fleet managers and truck operators could interface with the CoVaR package via a web interface and a dashboard-mounted tablet.
“CoVaR has the opportunity and ability to impact trucking costs and energy use substantially, today,” said Andrew Kotz, a commercial vehicles researcher who worked on the project. “That could be a near-term win.”
“CoVaR was an opportunity to combine both technical expertise in commercial vehicle modeling and other capabilities, and experience understanding the needs of operators and fleet owners, to build solutions that are within reach and can effectively meet users’ needs,” said NREL’s Jason Lustbader, the NREL CoVaR project lead and manager of NREL’s commercial vehicle technologies group. “Our team was proud to bring our cutting-edge skills to both aspects of the work.”
A Deployable, Cohesive Package of Technologies
Vehicle manufacturers are making significant strides toward developing the next generation of heavy-duty vehicles. Further progress will rely on advances being made on advanced hybrid and range-extended platforms as well as electric charging equipment and batteries that can handle the power and reliability demands of trucks. While advanced trucks can save businesses money over their lifetimes, the CoVaR tool package can address other aspects of trucking that could increase efficiencies today.
“Optimizing the use of existing fleet vehicles through the CoVaR tool package is appealing as an immediate solution for energy savings,” said NREL’s Jake Holden, a senior vehicle systems researcher.
“CoVaR can identify the right applications for advanced vehicles today, while also helping to optimize traditional diesel powertrain applications,” added Setayesh Fakhimi, another NREL commercial vehicle technologies researcher on the project.
Here is how it works.
Vehicle Configuration Optimizer
As part of the CoVaR tool package, Ohio State University developed a vehicle configuration optimizer that would calculate the most efficient vehicles, as a combination of powertrain and vehicle specifications, for the routes and associated duty cycles the fleet would be subject to.
Real-world duty cycle data, including elements like how long each delivery trip is, road elevation along the route, vehicle cargo weight, and more, are used to train machine-learning models that can predict the energy consumption of various vehicle configurations. The optimizer then recommends an optimal selection of powertrains across the fleet. Fleet managers could use this tool to understand their options for adjusting their fleets using powertrain technologies that make the most operational sense for them.
Fuel-Efficient Routing
The CoVaR tool package can provide fleet managers with speedy recommendations for which vehicles to route to what locations to achieve the highest energy efficiency. NREL researchers combined their advanced tool capabilities with project partner Esri’s mapping software to develop a routing framework that fleet managers and truck operators could use to identify the most efficient routes for their operations based on the vehicles being driven. Through this project, Esri, which builds ArcGIS and other mapping and analytics software, incorporated energy-efficient use into its routing planning, considering various factors such as time, distance, grade, and traffic.
NREL researchers contributed existing, real-world fleet vehicle energy use data from the laboratory’s FleetREDI analysis platform and the Fleet DNA database. In addition, NREL’s FASTSim and Route Energy Prediction Model (RouteE) tools can estimate the energy required by specific vehicles traveling on entered routes. CoVaR has the potential to integrate these tools into an application to present data in a user-friendly format and timeframe, perfect for fleet managers working on tight timelines.
“If you want to calculate energy requirements on the go, you don’t want to wait for a very complex model to run. You want it to happen right away,” Kotz said. “That’s the power of these tools.”
Through developing the CoVaR tool package, the NREL team boosted the capabilities of RouteE. Previously, the tool only calculated vehicle energy consumption over given routes for light-duty vehicles like cars and pickup trucks. Now, with a new integration feeding cleaned and validated FleetREDI data to RouteE, RouteE can model energy requirements for heavy-duty vehicles, too.
Driver Coaching
When installed, drivers encounter the CoVaR system through a display on their truck’s dashboard. This in-vehicle interface was deployed with fleets as part of the CoVaR project.
The software on the truck’s display would not only provide route information but also provide a coaching platform that could help drivers most efficiently operate their vehicles. Using second-by-second data collected by the in-house-developed telematics on PACCAR’s model fleet, NREL researchers analyzed route and energy (diesel or electricity) consumption data. They used FASTSim to simulate energy use impacts of different driver behaviors to alter driving speed, acceleration, idling, and more. These analyses could inform recommendations to drivers. A coaching system could prompt operators to change their driving style based on the vehicle they are operating—while considering that with every shift, the driver could be moving different amounts of weight, impacting the handling of the vehicle.
Fleet Performance Dashboard
In a real-world setting, fleet managers would visualize the vehicles in their fleet using a digital dashboard to identify the most energy-efficient combination of vehicles to send out on a given day. Kopius developed the user interface. It leverages the fuel-efficient routing technology so fleet managers can plan their vehicles’ routes on a fleet level to enhance energy efficiency across the fleet and then send those route directions to drivers.
Adaptability Is Key
The CoVaR tool package serves up a variety of options to fleet managers, allowing them to decide for themselves what energy efficiency goals they want to achieve—while taking other important factors such as time constraints into account—to make the right choices for their fleet operations.
“A one-size-fits-all solution is all but impossible,” Holden said. “CoVaR addresses this challenge by studying fleet priorities and behaviors that might impact energy consumption and presenting the range of efficiency improvements that are possible.”
And improvements are indeed possible. Holden said the research team saw pathways toward energy efficiency improvements in a modeling environment (developed based on real-world-collected fleet data) through the four interventions of vehicle configuration optimization, efficient routing, driver coaching, and a fleet performance dashboard.
“The impact of different interventions on energy savings is dependent on the operations of the fleet,” Fakhimi said. “Reducing idling may have the biggest impact for one fleet, whereas lowering the maximum driving speed may be the most effective behavior change for another.”
While the CoVaR tool package must be validated and commercially launched to become available to fleet managers, the NREL team sees this as a near-term possibility. The researchers and other project partners have demonstrated that the package has the potential to be viable for improving energy efficiency today simply by aligning different elements of fleet operations and improving existing tools.
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