Encyclopedia of Robotics

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| Editors: Marcelo H. Ang, Oussama Khatib, Bruno Siciliano

Solar-Powered Unmanned Aerial Vehicles

  • Philipp OettershagenEmail author
  • Thomas Stastny
  • Roland Siegwart
Living reference work entry
DOI: https://doi.org/10.1007/978-3-642-41610-1_69-1
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Synonyms

Definition

Solar-powered unmanned aerial vehicles (UAVs) are uninhabited aircraft that leverage sun radiation to partially or completely power their onboard systems. The reduced load on batteries or other energy storage systems increases both flight endurance and range. When properly designed, the aircraft’s solar panels can generate excess power that recharges the battery over the day. In suitable environmental conditions, the batteries are recharged enough to keep the aircraft airborne throughout the night. This continuous discharge-recharge cycle allows solar-powered multi-day flight and, from an energy perspective, leads to a perpetual flight capability. Robotic technologies optimally complement this long-endurance flight capacity. By providing the aircraft with accurate and robust automatic flight control and guidance, the workload of the operators is reduced significantly.

Overview

History and State of the Art

Solar-powered flight is not a new concept but dates back to the 1970s. A comprehensive historical overview is provided by Boucher (1984) and Noth (2008b). Sunrise (Fig. 1a) performed the first solar-powered flight, whereas Gossamer Penguin (Fig. 1d) performed the first manned flight. Solar aviation remained a niche in the following years, but more recently advances in structures, batteries, solar cells, and avionics have accelerated progress. In manned solar aviation, the 5-day flight across the Pacific (British Broadcasting Corporation (BBC), 2016) by Solar Impulse (Fig. 1e), which is part of an around-the-world flight (Ross, 2008), is the state of the art. In unmanned aviation, the High-Altitude Long-Endurance (HALE) capability and the prospective use of solar UAVs as atmospheric satellites, e.g., for telecommunications relay, have received significant interest. The ground work in this area was laid by NASA’s ERAST program (Colella and Wenneker, 1996). Notable current examples are Solara (Ackerman, 2013) and Zephyr (Fig. 1b). The latter holds the current overall flight endurance world record with a continuous 14-day (Federation Aeronautique Internationale, 2010) and more recent 25-day (Kucinski, 2018) summer flight. It has also shown an 11-day flight in winter (Sion Power, 2014) and is the first solar-powered HALE UAV to enter commercial operations (Osborne, 2016). However, due to the physics of the upper atmosphere, solar-powered HALE vehicles are comparatively large (wingspan> 20 m), complex, and thus expensive.
Fig. 1

Selected milestones in solar-powered flight history. The date indicates when the specified flight performance was achieved. (a) Sunrise (1974). First-ever solar-powered flight (20 min). (b) Zephyr (2010). Flight endurance world record for all aircraft (14 & 25 days). (c) SoLong (2005). First-ever perpetual solar-powered flight in history (48 h). (d) Gossamer Penguin (1980). First solar-powered manned flight. (e) Solar Impulse (2016). Manned solar flight endurance world record (118 h). (f) AtlantikSolar (2015). Flight endurance world record for aircraft < 50 kg (81 h)

Small-scale solar UAVs designed for Low-Altitude Long-Endurance (LALE) applications have therefore recently gained more attention. Though faced with the more challenging meteorological phenomena of the lower atmosphere (clouds, rain, wind gusts, and thermals), low-altitude UAVs provide the advantages of higher-resolution imaging with reduced cloud obstruction, lower complexity and cost, and simplified handling, e.g., through hand-launchability. As a result, solar-powered LALE UAVs aiming to reach flight times up to 14 h have been studied in academia (Weider et al., 2007; Malaver et al., 2015) and industry (AeroVironment, 2013; ByeAerospace, 2015). Research targeting perpetual endurance in these small-scale robotic aircraft has been relatively sparse. Solar-powered perpetual flight has been demonstrated by SoLong (Cocconi, 2005) (Fig. 1c), which performed a continuous 48-h flight while actively seeking out thermal updrafts, and SkySailor (Noth, 2008a), which demonstrated a 27-h flight without the use of thermals. In addition, AtlantikSolar has demonstrated a continuous 81-h flight (Oettershagen et al., 2017) and a fully autonomous 26-h flight with a day-/night-capable payload in a mock-up search and rescue mission (Oettershagen et al., 2018b). Nevertheless, these UAVs were mainly developed for demonstrating the feasibility of perpetual flight, but not for performing actual applications.

Design and Performance Metrics

Solar-powered UAV development emphasizes flight efficiency considerations. Lightweight structures, aerodynamically efficient airframes, and an optimal combination of solar modules and onboard energy storage are required to realize flight endurance and range advantages. Noth (2008a) provides a comprehensive reference on solar UAV design with a focus on low-altitude flight, while Colella and Wenneker (1996), Romeo et al. (2007), and Nickol et al. (2007) cover high-altitude solar UAV design. Zhu et al. (2014) provide a more recent overview over solar aircraft and performance-driving technologies such as solar module and battery types.

As shown in Fig. 2, the UAV design and the environmental conditions determine whether a solar-powered UAV is capable of perpetual flight or not. In Fig. 2a, the collected battery energy Ebat is not sufficient to stay airborne over the full night. The aircraft still exhibits a significant flight endurance
$$\displaystyle \begin{aligned} T_{\text{end}}=T(E_{\text{bat}}>0)|{}_{E_{\text{bat}}(t_{\text{launch}})=E_{\text{bat}}^{\text{max}}} \; ,\end{aligned} $$
(1)
which is defined as the maximum time the aircraft can stay airborne (Ebat > 0) when launching at the optimal launch time tlaunch with full batteries. In Fig. 2b, the collected battery energy Ebat is sufficient for perpetual flight. The metrics describing the perpetual flight performance are the excess time
$$\displaystyle \begin{aligned} T_{\text{exc}}=\frac{E_{\text{bat}}(t=t_{\text{eq}})}{P_{\text{out}}^{\text{nom}}} \Big|{}_{P_{\text{solar}}(t>t_{\text{sr}})=0}\end{aligned} $$
(2)
with nominal power consumption \(P_{\text{out}}^{\text{nom}}\), sunrise time tsr and power-equality time \(t_{\text{eq}}=t(P_{\text{solar}}^{\text{nom}}=P_{\text{out}}^{\text{nom}})\) in the morning. Perpetual flight requires Texc > 0, i.e., that battery capacity is available at t = teq to continue flight, for instance, in case of cloud coverage. An alternative performance metric stating the same fact is the minimum battery state of charge
$$\displaystyle \begin{aligned} \sigma_{\text{bat}}^{\text{min}}=\min\left(\frac{E_{\text{bat}}(t)}{E_{\text{bat}}^{\text{max}}}\right) \end{aligned} $$
(3)
where we require that \(\sigma _{\text{bat}}^{\text{min}}>0\) throughout the whole flight but specifically at t = teq in the morning. The last performance metric is the charge margin
$$\displaystyle \begin{aligned} T_{\text{cm}} = T(E_{\text{bat}}=E_{\text{bat}}^{\text{max}}) \; , \end{aligned} $$
(4)
which is a safety margin that indicates how much unused charging time remains after reaching full charge before the battery discharge begins again. In case of decreased solar power income, Tcm > 0 provides additional margin before a decrease in excess time occurs.
Fig. 2

Solar power income (green lines), required power (red lines), and energy taken from (red fill) or charged into (light blue fill) the battery for a UAV which is not perpetual flight capable (left) and one that is perpetual flight capable (right). In this visualization, only the battery size determines the perpetual flight capability. (a) Non-perpetual flight. (b) Perpetual flight

Key Research Findings

Given the similarity of their flight operations, non-solar UAVs and solar UAVs that are not perpetual flight capable face similar challenges and can share most hardware (airframe, sensors, autopilot) and software (estimation, flight control, path planning) (AeroVironment, 2013). In contrast, perpetual flight-capable solar UAVs face specific challenges such as low energetic safety margins, low payload capacity, high operational complexity, and limited autonomy without environment awareness. The research performed to solve these issues is outlined below.

System Design Approaches for Higher Energetic Margins and Payload Capacity

Issue: Today’s solar-powered UAV designs have limited energetic safety margins and payload capacity. For example, SoLong (Cocconi, 2005) had only 2 h of excess time, and SkySailor (Noth, 2008a) only had 5.8 % of battery energy remaining at the end of the night. As a result, the robustness against deteriorated weather (e.g., clouds) and the payload capacity are low.

Current research: First, many authors focus on model-based conceptual design approaches for solar UAVs (Brandt and Gilliam, 1995; Shiau et al., 2010; Leutenegger et al., 2010; Morton et al., 2015; Morton and Papanikolopoulos, 2016). Some recent methodologies (Morton et al., 2013; Oettershagen et al., 2017) emphasize perpetual flight robustness, i.e., high energetic safety margins under deteriorated weather conditions. Second, less authors present detailed system design studies and flight tests. For HALE UAVs, a number of publications (Romeo et al., 2007; Nickol et al., 2007) exist, but only the initial work by NASA (Flittie and Curtin, 1998) has led to published flight results. Important design studies for LALE UAVs are presented by Morton et al. (2015), Noth (2008a), Cocconi (2005), Weider et al. (2007), and Oettershagen et al. (2017, 2018b). Overall, recent demonstrations indicate significant progress: whereas the Zephyr HALE UAV performed both a continuous 14-day summer flight (Federation Aeronautique Internationale, 2010) and an 11-day winter flight (Sion Power, 2014), the AtlantikSolar LALE UAV achieved an 81-h-long summer flight that increased the minimum state of charge from the ≤10% of SoLong and SkySailor to about 39% (Oettershagen et al., 2017). In addition, AtlantikSolar achieved the first multi-day flight with a meaningful, i.e., day-/night-capable, sensing payload at low altitude (Oettershagen et al., 2018b). Third, battery and solar module research is performed outside of the UAV community. Especially battery improvements (Zu and Li, 2011), which are motivated by the use of mobile devices and electric vehicles, were shown to automatically lead to significant solar UAV performance improvements (Oettershagen et al., 2017).

Flight Automation for Less Operational Complexity

Issue: The central design differences of high-performance solar UAVs to standard UAVs are (a) a lightweight yet fragile structure, (b) a large wingspan for low induced drag, (c) a large wing area for low cruise speed but large solar cell area, and (d) the distribution of battery mass in a span-loader concept along the wing. As a result, these UAVs fly slowly and tend to have slow and undamped dynamics especially around the yaw axis. Together with their structural fragility (represented by vertical load factor limits of only 2–5 g’s), these characteristics make them very hard to fly. For example, SoLong’s 48-h flight required six highly trained pilots.

Current research: Flight control for fixed-wing UAVs has made significant progress in the past years. In addition to linear control techniques, approaches such as robust control, model-based control, model predictive control, and adaptive control have been presented (How, 2014). However, the challenging flight dynamics of solar UAVs require specific adaptations that are not comprehensively discussed in the literature. An exception is Oettershagen et al. (2017), which integrates a simple yet robust flight control system incorporating airspeed-dependent gain scheduling and trims, coordinated turn control, overspeed protection, and both static and dynamic structural overload protection. In Oettershagen et al. (2018b) this functionality is extended to allow a fully autonomous multi-day solar-powered flight that did not require a single pilot intervention. Large HALE UAVs in addition have to deal with aeroelastic effects which led to the NASA Helios crash (Noll et al., 2004). Aeroelastic models and flight controllers (Patil et al., 2001; Frulla, 2004; Mardanpour and Hodges, 2015) have been developed to manage those effects.

Increased Flight Autonomy Through Fully Environment-Aware Navigation

Issue: For fully autonomous operation, UAVs need to be aware of terrain. In addition, solar UAVs in particular are susceptible to weather: wind gusts, precipitation, clouds, or thunderstorms can damage the aircraft or reduce its performance and thus have to be avoided. However, the current literature does not provide navigation methods that properly consider weather. As a result, today, UAVs and solar UAVs can only be operated in closely controlled environments.

Current research: Literature on weather-aware UAV path planning is sparse. The necessary elements (e.g., wind dependence, sun dependence) are only considered separately in relatively unrelated fields of research. On the one hand, wind-aware planning using forecasted wind data and 3D wind fields exists (Rubio and Kragelund, 2003; Chakrabarty and Langelaan, 2013). Rubio et al. (2004) extend temperature and icing effects. All these planners however do not include solar models. On the other hand, research that incorporates solar models often neglects wind, assumes a perfectly clear sky or constant sun position, and thus solves a very simplified problem (Klesh and Kabamba, 2007, 2009; Spangelo et al., 2009; Hosseini et al., 2013; Dai, 2013). Recently, a planning approach that considers all safety and performance-relevant aspects (terrain, system state, and up-to-date meteorological weather data including thunderstorms, precipitation, humidity, winds, gusts, sun radiation, and clouds) was released, and the first-ever real-world large-scale mission with a solar UAV above the Arctic Ocean was shown (Oettershagen et al., 2018a).

Examples of Application

All applications that require data to be collected or distributed consistently or on a large scale can benefit from the long-endurance flight capabilities of solar-powered UAVs. In today’s data-driven society, many such applications exist (Colella and Wenneker, 1996; Zhu et al., 2014). Solar-powered UAVs could therefore be of pivotal societal and commercial use in large-scale disaster relief support, e.g., after earthquakes or floods (Rudin et al., 2017), meteorological surveys in remote and otherwise inaccessible areas (Runge et al., 2007), continuous border or maritime patrol (Romeo et al., 2007), telecommunications relay (Tozer and Grace, 2001), or large-scale agricultural or industrial aerial inspection (Herwitz et al., 2004).

Future Directions for Research

Solar-powered UAVs have made significant progress since the first perpetual flight by SoLong (Cocconi, 2005). Nevertheless, their widespread use by non-experts in complex real-life applications requires further research. Flight control, perception, and path planning research results can be shared with non-solar UAVs. The future solar-UAV-specific research closely aligns with section “Key Research Findings”. First, a remaining system design challenge is to increase the UAV’s operational and handling robustness while reducing the complexity and preserving the energetic performance. The steady advances in battery and solar module technology (Zu and Li, 2011; National Renewable Energy Laboratory, 2016), combined with research on novel concepts such as a 2-m-wingspan perpetual-flight-capable solar UAV (Morton and Papanikolopoulos, 2016) or vertical takeoff and landing (VTOL) solar UAVs (D’Sa et al., 2016), can be leveraged to achieve this goal. Second, the robotics research challenge is to implement reliable real-time weather-aware navigation for fully autonomous operation in cluttered terrain or adverse weather.

Cross-References

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2020

Authors and Affiliations

  • Philipp Oettershagen
    • 1
    Email author
  • Thomas Stastny
    • 1
  • Roland Siegwart
    • 1
  1. 1.Autonomous Systems LabETH ZurichZurichSwitzerland

Section editors and affiliations

  • Aníbal Ollero
    • 1
  1. 1.GRVC Robotics Labs. SevillaEscuela Técnica Superior de Ingeniería, Universidad de SevillaSevillaSpain