A mission that has to close
The course-design problem is a fixed-wing long-endurance UAV supplied by solar energy, a Li-ion battery and a hydrogen fuel cell. The nominal mission target is at least 24 hours; several simulation versions use a 24.5-hour mission window.
The core problem is not simply adding stored energy. Additional energy-system mass raises the required power, which in turn changes the required energy and mass. The project studies that loop together with energy management and hardware constraints.
Aircraft, power & mass closure
Aircraft and aerodynamic assumptions feed the flight-power requirement. Propulsion efficiencies and auxiliary loads determine the electrical demand; the source model then sizes the energy system and updates total mass.
| Model layer | Role | What must be checked |
|---|---|---|
| Mission & aircraft | Flight condition and operating timeline | Mission window, mass, geometry and units. |
| Aerodynamics & power | Translate flight conditions into demand | Drag assumptions, propulsive efficiency and takeoff feasibility. |
| Source sizing | Solar / Li-ion / hydrogen contribution | Irradiance, usable capacity, fuel-cell behavior and storage mass. |
| Mass closure | Feed energy-system mass back into power | Existence of a feasible solution under the stated assumptions. |
| Hardware limits | Apply the available components | Motor, battery, photovoltaic and controller limits. |
A theoretical feasible design and the endurance of the current hardware are distinct questions. A mass-closure result must be interpreted within the assumptions that generated it.
Three sources, different roles
| Source | Modeled contribution | Engineering constraint |
|---|---|---|
| Solar | Irradiance-dependent power and possible battery charging | Available area, real panel output and conversion losses. |
| Li-ion | Stored energy and support during source shortfalls | Usable capacity, voltage and allowed charge/discharge conditions. |
| Hydrogen fuel cell | Energy supply coupled to hydrogen storage | Fuel-cell capability and the mass of the storage system. |
Single-, dual- and triple-source cases are compared with consistent mission and mass accounting. A two- or three-fold endurance advantage is not assumed as a target result.
Energy management, in simulation and hardware
The MATLAB / Simulink framework uses Stateflow to describe source coordination. EMS studies examine when solar power can serve the load or charge the battery, when the battery or fuel cell supplies power, and how source or voltage limits alter the operating decision.
The first hardware direction is deliberately simple: solar and fuel-cell paths feed the bus through their conversion stages, while the Li-ion path supplies the bus directly through its protection and switching branch. No bidirectional DC–DC stage is introduced.
- Keep the voltage sensing and overvoltage charging cutoff explicit.
- Record MOSFET switching, fusing and reverse-current protection against the actual schematic.
- Cross-check simulation decisions and the hardware implementation instead of treating them as automatically equivalent.
The version history
- v1.x
First coupled estimates
Initial sizing and source representation raised questions about mass provenance and whether all three sources were included.
- v2.x
Reproducible Simulink workflow
Model generation, contract checks and a repeatable run pipeline made the simulations more auditable.
- v3.x
Closer to the task requirements
Power demand and model assumptions were revised. Mission failures became part of the evidence rather than being hidden.
- v4.x
Feasibility, comparisons & hardware limits
Drag and storage assumptions, single/dual/triple-source comparisons, mass/endurance sweeps and minimum propulsion-power questions were examined.
- v5.0
Actual PV & current hardware
The latest recorded report studies correction for the actual photovoltaic hardware and endurance with the current components. Its detailed figures are not republished without the source results.
What the parameter studies resolve
Earlier investigations compare drag-coefficient assumptions, hydrogen-storage mass fractions and geometry. Later studies examine how maximum endurance changes with mass, and distinguish an energy limit from a propulsion-power or takeoff limit.
A sweep that stops because the configured motor cannot satisfy takeoff does not by itself demonstrate an energy-only endurance boundary. The follow-up framing therefore separates unconstrained propulsion-power studies from the minimum power needed for takeoff at each mass.
Results & their limits
The project has produced successive simulation frameworks, feasibility investigations and an EMS hardware design. Some model versions fail the mission target; the archive retains these failures and the assumptions that lead to them.
- Do not compare configurations using different statistical windows or hidden mass assumptions.
- Check unmet load as well as final battery state and total source energy.
- Keep predicted endurance separate from measured endurance.
- Apply real photovoltaic and propulsion limits before making a current-hardware claim.
No 24-hour flight demonstration or guaranteed source-combination advantage is claimed on this page.
Selected deliverables
MATLAB / Simulink / Stateflow framework
Versioned model and EMS studies, energy and mass investigations, controller schematic and PCB work.
电推进课设_v5.0_实物PV修正与当前硬件续航研究报告
An existing report recorded in the project archive. The document is not uploaded to this web package.
Next evidence to publish
Connect the final model revision, audited figures and hardware-test records to their source data. Public code and reports should use the actual repository or document links once verified, with the mission assumptions visible beside the results.
