US Department of Energy — Urban Fleet Energy Optimization

Summary

The UPLIFTS Phase I project was a physics-based feasibility study of software-only velocity schedule optimization for urban electric fleet operations. The analysis spanned 22 drive cycles representing dense-urban, urban-suburban, vocational, and boundary operating conditions, paired with five electric vehicle archetypes covering passenger cars through heavy articulated buses. Energy savings were modeled as physics-based upper bounds under idealized execution, with a conservative 10–30% real-world planning range carried into commercialization.

Context

Urban freight and transit operations dissipate kinetic energy at every deceleration between stops. Regenerative braking recovers part of this loss in electrified powertrains. It cannot recover energy that an efficient velocity schedule would have avoided in the first place. Across medium- and heavy-duty vehicles alone, urban operations account for billions of vehicle-miles annually.

Software-based velocity schedule optimization addresses the source of this inefficiency directly — no infrastructure modifications, no dedicated lanes, no vehicle-to-vehicle communication. The Phase I project evaluated the technical feasibility of this approach and the conditions under which it produces meaningful savings.

The work was funded by the U.S. Department of Energy through SBIR Award DE-SC0024972, administered by the Vehicle Technologies Office Energy Efficient Mobility Systems program.

What the analysis did

The study modeled energy consumption across four operating regimes, using 22 drive cycles drawn from the NREL DriveCAT library and five electric vehicle archetypes spanning the heterogeneity range from passenger vehicles to heavy articulated buses.

Regime 1 — Dense urban. Greater than four stops per mile, average speed below 13 mph. Transit agencies, municipal bus operators, urban fixed-schedule service.

Regime 2 — Urban-suburban mixed. One to four-and-a-half stops per mile, average speed 14–25 mph. Mixed urban fleets, suburban delivery, regional transit, campus shuttles.

Regime 3 — Vocational and last-mile delivery. One-and-a-half to ten-and-a-half stops per mile, average speed 6–20 mph. Last-mile logistics, parcel delivery, refuse, utility fleets.

Regime 4 — Highway and high-speed arterial. Fewer than two stops per mile, average speed above 25 mph. Operational boundary — not a primary target, but included to define deployment screening limits.

For each regime, the study quantified:

• Energy consumption under reference drive cycles
• Energy consumption under physics-optimized velocity schedules, under equal segment travel-time constraints
• Savings envelope across all five vehicle archetypes
• Sensitivity of savings to vehicle and operating parameters
• Grouping behavior under coordinated versus independent optimization

What the numbers showed

Dense-urban operations produced the largest savings envelope: 31–64% across the five archetypes, with an average of 45%. The Manhattan Bus Cycle — the most demanding stop-and-go profile in the validation set — produced 35–44% across all five vehicle classes.

Urban-suburban operations produced 18–28% savings, averaging 23%. Vocational and last-mile delivery operations produced 8–49%, averaging 32%. Highway and high-speed arterial operations produced 0–37%, averaging 16%, defining the operational boundary of the approach.

These results are physics-based upper bounds under idealized execution. They are not guaranteed real-world outcomes. Actual savings under operational conditions — driver variability, road grade, ambient temperature, sensor noise, data-quality variation — remain to be quantified under Phase II. The conservative real-world planning range is 10–30%, which is what commercialization modeling is built on.

Sensitivity analysis established acceleration capability as the primary vehicle-level driver of savings magnitude. Vehicle mass showed low sensitivity to percentage savings, indicating that day-to-day loading has limited impact on achievable performance.

Deliverables

The Phase I effort produced:

• Physics-based energy modeling framework applied across 22 drive cycles and five vehicle archetypes
• Four-regime deployment targeting envelope with savings gradients and operational boundaries stated explicitly
• Sensitivity analysis identifying primary vehicle parameters driving savings magnitude
• Fleet grouping analysis establishing coordinated versus independent optimization behavior
• Customer discovery findings from more than 60 structured interviews with transit agencies, fleet operators, OEMs, telematics providers, and policy organizations, conducted under the DOE Phase Shift I program
• Commercialization pathway grounded in the dense-urban electric transit beachhead market
• Phase I Final Report submitted to the Vehicle Technologies Office

Primary source

DOE SBIR Phase I Final Report, Award DE-SC0024972, submitted to the U.S. Department of Energy Vehicle Technologies Office. Phase II prototyping pathway in development.