Funding

Multi-modal Charging Hub Development

Current support · ASPIRE Engineering Research Center

ASPIRE is a National Science Foundation Engineering Research Center headquartered at Utah State University, advancing electrified transportation and its supporting infrastructure. About ASPIRE

Overall Project Team

Principal Investigator: Prof. Hongjie Wang — Utah State University (USU)

Co-Principal Investigators
Prof. Tzu-Liang (Bill) Tseng — The University of Texas at El Paso (UTEP)
Prof. Ziqi Song — University at Buffalo (UB)
Prof. Yirong Lin — The University of Texas at El Paso (UTEP)
Prof. Chin-Yih Lin — The University of Texas at El Paso (UTEP)

My Research Contribution

Mission-Sufficient Charging and Shared-Power Scheduling for Truck–Drone Charging Hubs- $ 150 K Funded 

Within the broader project, my work focuses on charging decisions for electric trucks and cargo drones that share a power-limited charging hub. The goal is to give each vehicle enough energy and thermal headroom for its assigned mission, while coordinating charging power to meet individual departure deadlines.

Illustration of trucks and cargo drones sharing charging infrastructure.

Why Thermal Headroom Matters

Enough stored energy does not necessarily mean enough usable power. A truck or drone may have sufficient kWh for a mission yet begin too hot to sustain its demanding power segments. Charging also generates heat, while the mission adds further heat and the surrounding air affects cooling. The charging decision must therefore prepare both the vehicle’s energy and its thermal state for the work ahead.

Departure thermal headroom is the mission-specific maximum allowable departure temperature minus the vehicle’s departure temperature. That allowable starting temperature is calculated from the complete load profile and expected environment. It is not simply the gap between the current battery temperature and the equipment’s temperature limit.

Mission thermal margin is the equipment’s temperature limit minus the highest temperature reached during the complete mission. The scheduler coordinates charging power and timing to deliver enough energy while meeting the departure-temperature requirement. Where passive cooling and available time cannot achieve this, more charging power alone cannot make the task feasible.

How the Method Works

We first translate each mission, battery state, and expected environment into charging targets. A joint scheduler then allocates the hub’s limited power across the fleet. It executes only the next charging step, measures the delivered energy and battery temperature, and replans as mission requirements or charging capability change.

This connects three decisions: how much energy is enough, how much thermal headroom the mission needs, and how charging power and timing should adapt. Full-mission evaluation follows departure and is kept separate from the information available to earlier charging decisions.

Figure 4(a) · Four routes from one hub. The truck routes span 35.69–96.28 miles. Background colors estimate temperature at 08:30 MDT on September 6, 2026, using two weather stations.

Figure 4(b) · Conditions along the T2 mission. Segment colors show estimated temperature at the modeled time of first passage; node labels show first arrival. The complete mission evaluation also includes return travel and service stops.

The maps use constructed study routes on real roads. Temperature is estimated, not measured along every road; the routes are not observed fleet GPS tracks.

1. How Is Charging Power Shared and Updated?

How to read the figure: each row is a truck (T1–T4) or drone (D1–D6). Panel (a) shows charging power relative to each channel’s maximum; panel (b) shows stored battery energy. A vehicle can pause charging while retaining its accumulated energy. Blank cells follow its departure deadline. Panel (c) shows the total power drawn by the hub.

What it shows: the controller adapts to changed missions at minute 20 and reduced charger capability beginning at minute 25, using feedback received at minute 30. The main demonstration uses 679.906 kWh AC within an 800 kWh budget, and peaks at 473.727 kW below the 550 kW station limit.

2. Does the Charging Plan Support the Complete Mission?

How to read the figure: the upper panels split each vehicle’s departure energy into energy used during its task and energy remaining afterward. Trucks and drones use separate energy scales. The lower panels report the highest battery temperature and lowest cell-equivalent voltage reached during the complete mission; dashed lines mark the model’s limits.

What it shows: all 10 of 10 modeled missions pass the energy-reserve, voltage, temperature, and rated-output checks. This connects the charging decision to the work the vehicle must actually perform, beyond simply reaching a chosen battery percentage. Several drones reach the 3.0 V boundary, illustrating why energy alone is not the full readiness criterion.

Reading thermal margin: in panel (c), the vertical distance from each peak-temperature point to the 60°C model limit is its full-mission thermal margin. For example, D1 peaks at 45.62°C, leaving 14.38°C in this main simulation. This differs from departure thermal headroom, which is measured against the mission-specific allowable starting temperature.

3. What Does Joint Planning Improve?

We compare joint planning with a deadline-first rule that charges vehicles in order of departure. Both receive the same mission-sufficient targets. The comparison is repeated across five start windows using two ways of estimating demand: mileage and flight stages (Model A), and truck physics and drone rotor power (Model B).

How to read the figure: shorter bars mean lower peak demand on the charging hub. The labels show the full range across the five windows. Compare the two strategies within each demand model.

What it shows: both strategies complete 50 of 50 missions per model, while joint planning reduces peak charging power from 550 kW to 473.727–475.791 kW in Model A and 289.951–292.797 kW in Model B. The benefit is lower peak demand while preserving the same mission service.

Thermal Capability: Why More Charge Can Still Be Insufficient

In a controlled follow-up case, the revised D6 task requires 17.07 kW for two minutes. The left panels show departure energy and temperature; the right panel compares sustainable power with that requirement.

The higher-energy state still falls short. The frozen plan has 73.40% stored energy at 48.55°C, but supports only 14.95 kW. Updating energy and thermal requirements yields 66.55% at 35.16°C and supports 19.62 kW. Separate fixed-temperature checks in the study confirm that adding energy alone does not relax the thermal constraint.

The goal is mission-ready energy and thermal headroom together. Less charging is not inherently better. These are controlled E4 model results (Figure 26), separate from the road-based main demonstration and from measured battery-management-system behavior.