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Decision-making Algorithm in Case of Failure of the Electric Motor of a Multi-rotor Unmanned Aerial Vehicle

Authors:
  • Yuriy Fedkovych Chernivtsi National University

Abstract and Figures

The safety of unmanned aerial vehicle (UAV) flights depends on many factors, such as the absence of failures or malfunctions of aviation equipment, the absence of exposure to adverse environmental phenomena, and the absence of errors by the aircraft crew and engineering personnel. In uncontrolled airspace by the internal affairs authorities, when the flight is carried out at altitudes below 500 feet above ground level (AGL), this task is even more complicated, since at the moment there are no monitoring services and procedures for monitoring VTOL-UAV (Vertical TakeOff and Landing unmanned aerial vehicle) performing operations at the specified altitude range. In this case, the only link of control is the remote pilot, who directly monitors his unmanned aerial vehicle (UAV) when flying in Visual Line-of-Sight (VLOS) mode. Some components of an unmanned vehicle are difficult to control from the point of view of preventing the risk of the likelihood of an incident, which is difficult to prevent due to its high potential danger and the speed of its occurrence. In this paper, we propose an algorithm that is simple for software implementation and does not require mathematical calculations, the implementation of which requires the presence of devices for measuring the speed of rotation of engines, which are proposed to use Hall sensors installed on each engine of a multi-rotor VTOL-UAV. To prevent the program from crashing when polling sensors, a double redundancy of sensor readings is provided. Also, in case of confirmation of an engine failure, a module has been introduced into the algorithm that provides for a preliminary shutdown of an engine that is symmetrical to the one whose failure is confirmed. After turning off the remaining engines, the parachute compartment is activated for an accurate landing at low speed.
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DecisionmakingAlgorithminCaseofFailureoftheElectric
MotorofaMultirotorUnmannedAerialVehicle
Vitaliy Larina, Heorhii Rozorinovb, Oleksandr Hresc, Volodymyr Rusync, Sergey Subbotind,
Nina Chichikalob and Katerina Larinab
a National Aviation University, L. Huzara ave, 1, Kyiv, 03058, Ukraine
b National Technical University of Ukraine “Igor Sikorsky Kyiv Politechnic Institute”, Peremohy ave, 37, Kyiv,
03056, Ukraine
c Yuriy Fedkovych Chernivtsi National University, Kotsybynsky str., 2, Chernivtsi, 58012, Ukraine
d National University “Zaporizhzhia Politechnic”, Zhukovsky str., 64, Zaporizhzhia, 69063, Ukraine
Abstract
The safety of unmanned aerial vehicle (UAV) flights depends on many factors, such as the
absence of failures or malfunctions of aviation equipment, the absence of exposure to adverse
environmental phenomena, and the absence of errors by the aircraft crew and engineering
personnel. In uncontrolled airspace by the internal affairs authorities, when the flight is
carried out at altitudes below 500 feet above ground level (AGL), this task is even more
complicated, since at the moment there are no monitoring services and procedures for
monitoring VTOL-UAV (Vertical Take-Off and Landing unmanned aerial vehicle)
performing operations at the specified altitude range. In this case, the only link of control is
the remote pilot, who directly monitors his unmanned aerial vehicle (UAV) when flying in
Visual Line-of-Sight (VLOS) mode. Some components of an unmanned vehicle are difficult
to control from the point of view of preventing the risk of the likelihood of an incident, which
is difficult to prevent due to its high potential danger and the speed of its occurrence.
In this paper, we propose an algorithm that is simple for software implementation and does
not require mathematical calculations, the implementation of which requires the presence of
devices for measuring the speed of rotation of engines, which are proposed to use Hall
sensors installed on each engine of a multi-rotor VTOL-UAV.
To prevent the program from crashing when polling sensors, a double redundancy of sensor
readings is provided. Also, in case of confirmation of an engine failure, a module has been
introduced into the algorithm that provides for a preliminary shutdown of an engine that is
symmetrical to the one whose failure is confirmed. After turning off the remaining engines,
the parachute compartment is activated for an accurate landing at low speed.
Keywords1
Algorithm, motor failure, aviation incident, VTOL-UAV
1. Introduction
The safety of unmanned aerial vehicle (UAV) flights depends on many factors, such as the absence
of failures or malfunctions of aviation equipment, the absence of exposure to adverse environmental
phenomena, and the absence of errors by the aircraft crew and engineering personnel. These factors
are classified in the International Civil Aviation Organization (ICAO) risk matrix [1].
In controlled airspace, any manned aerial vehicle is under constant control of the crew and air
traffic control units. The controllability of an unmanned aerial vehicle is a much more difficult task,
since its crew- the remote pilot's team - are at a considerable distance and can assess the
CMIS-2022: The Fifth International Workshop on Computer Modeling and Intelligent Systems, Zaporizhzhia, Ukraine, May 12, 2022
EMAIL: vjlarin@gmail.com (A. 1); grozoryn@gmail.com (A. 2); o.hres@chnu.edu.ua (A. 3); rusyn_v@ukr.net (A. 4);
subbotin@zntu.edu.ua (A. 5); Hni312123@lll.kpi.ua (A. 6); l.katerina@gmail.com (A. 7)
ORCID: 0000-0002-5042-2426 (A. 1); 0000-0002-6095-7539 (A. 2); 0000-0002-8465-193X (A. 3); 0000-0001-6219-1031 (A. 4); 0000-
0001-5814-8268 (A. 5); 0000-0002-3619-5992 (A. 6); 0000-0002-2315-0891 (A. 7)
© 2022 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org) Proceedings
controllability of their aircraft based on telemetry data that comes along the downstream branch of the
C2 channel.
In uncontrolled airspace by the internal affairs authorities, when the flight is carried out at altitudes
below 500 feet above ground level (AGL), this task is even more complicated, since at the moment
there are no monitoring services and procedures for monitoring VTOL-UAV (Vertical Take-Off and
Landing unmanned aerial vehicle) performing operations at the specified altitude range. This altitude
range is currently of particular interest to users, since it allows one to implement new or update
existing high-tech production and economic processes. In this case, the only link of control is the
remote pilot, who directly monitors his unmanned aerial vehicle (UAV) when flying in Visual Line-
of-Sight (VLOS) mode, or based on telemetry data, with various Radio Line-of-Sight (RLOS) mode
options. Some components of an unmanned vehicle are difficult to control from the point of view of
preventing the risk of the likelihood of an incident, which is difficult to prevent due to its high
potential danger and the speed of its occurrence. These components include the UAV electric motor.
Failure of the UAV motor (sudden or partial) is referred to the group of aviation equipment failures.
2. Relatedworks
In manned aviation, special attention is paid to assessing the risks of aircraft flight deviation from
a given flight trajectory. To assess such risks, various methods are often used based on calculating the
probability density function, while many publications on the topic of aviation risk assessment suggest
a complex use of various options for calculating the probability density function. In particular, in [2],
they propose to use a complex model called by the authors Triple Univariate Generalized Error
Distribution (TUGED), which is supported by the Maximum Likelihood Method. The authors, by
modeling, confirm the effectiveness of the proposed model by checking its compliance with the Chi-
square, Bayesian and Akaike criteria.
In [3], it is indicated that the failure rate for various reasons for unmanned aircraft is 1/103 per
flight hour, which is two orders of magnitude higher than the value of the same indicator for manned
civil (commercial) aviation. Considering the above, the task of developing a decision-making
algorithm in the event of a failure of the VTOL-UAV electric motor during flight is an urgent task to
reduce the risk of an incident and, accordingly, increase the safety of VTOL-UAV flight.
According to [4], failures due to engine failure account for 411 cases per 1000 failures in general
due to failures of various UAV components. It should be noted that this statistics took into account
only the failures of internal combustion engines, which are now used on VTOL-UAV, performing
long flights, more than one hour. In addition, the data takes into account the type of VTOL-UAV of
the traditional aircraft type. In the same source, at the level of the components of the propulsion
system, various failures are detailed - failures of the engine itself (63 cases), failures of the ignition
system (97 cases); fuel system failures (120 cases), temperature control system failures (48 cases);
failures of the management apparatus (83 cases).
As for the VTOL-UAV with an electric motor system, such statistics are either absent or not
found. However, according to the experience of the authors, during experimental studies to determine
the discharge rate of a LiON battery [5], brushless motors were used as a load, which are widely used
as VTOL-UAV engines for vertical take-off and landing of VTOL and small HTOL (abbreviated as
VTOL - Vertical Take-Off Landing [6]), weighing less than 25 kg. During the experiments, one of the
engines suddenly failed for an unknown reason and was replaced with another. This case occurred
under laboratory tests. It is obvious that under conditions of environmental changes during the flight,
the probability of motor failure will increase.
In [7], a failure risk assessment was carried out for two VTOL-UAV designs: one VTOL-UAV
design for vertical take-off and landing of VTOL (VTOL-UAV of this type is shown in Fig. 1) and
another VTOL-UAV design for horizontal take-off and landing of HTOL (VTOL -UAV of this type
is shown in Fig. 2, 3).
Figure1:MultienginehelicopterforcargotransportationPKM14"Saturn"[8]
Figure2:TwinengineunmannedaerialvehicleM7V5"SkyPatrol"[9]
Figure3:UnmannedcomplexofhybridtypeZalaAeroZalaVtol
Zala Aero Zala Vtol is a hybrid unmanned complex, which, according to the developers, reduces
the role of the human factor, the number of used and maintained equipment in the flight task, and
fully automate flight processes. During operation, the equipment relies on the computing power of the
on-board computer ZX1, which uses artificial intelligence technology, which allows to process data in
Full HD and transmit HD video and photos via encrypted communication channels to NSU, ensuring
effective monitoring before landing. . According to the developers, the versatility of the Zala Vtol
design makes it fully compatible with all existing Zala target loads, and also allows the installation of
additional surveying equipment.
According to preliminary calculations, the crash probability density (CPD) was calculated, which
made it possible to determine the frontal impact area, which, in turn, was used to calculate the number
of incidents (Expected Level of Safety) over a normalized time range using the Weibel and Hansman
model of collision with the ground [10] (an incident in this model is understood as the number of
impacts of an emergency board with a person, which leads to his injury or even death). Thus, for the
push-type VTOL-UAV of horizontal take-off and landing with one diesel engine, ELSHTOL=1.4710-9
incidents/hour was obtained, and for the VTOL of vertical take-off and landing (quadrotor-in-
quadrotor (QIQ) octocopter model) ELSVTOL=4,9610-8 incidents/hour. Whence it follows that the
calculated incident rate for VTOL is almost an order of magnitude higher than for HTOL. The authors
of [5] propose the calculation of the safety corridor when planning the flight trajectory, the width of
which will depend on the obtained value of the accident probability density. For example, when a
VTOL-UAV QIQ model is flying at an altitude of 122 m (400 ft) at a speed of 10 m/s, the width of
such a corridor will be 38 m. In this case, the flight trajectory should not run through populated areas
or crowded areas.
However, when used within dense urban areas with a high population density, it will be incredibly
difficult to plan such a safe route, which will significantly complicate the implementation of the U-
space concept.
The concept of constructing a trajectory based on the assessment of multiple risks in the U-space
was also proposed in [11]. The authors proposed an extended structure of the UTM Risk Assessment
Framework (URAF), which implies its use just for predicting the occurrence of the risk of an incident
within the boundaries of a densely populated urban area from a multi-rotor VTOL-UAV. The onboard
system, the hardware implementation of which is called the core Flight System, built on the Bayesian
trust model, assumes, among other types of assessing the performance of various VTOL-UAV
components, including monitoring the VTOL-UAV engine parameters. At the same time, the
proposed flight risk assessment system, according to the authors, should be within the competence of
the UAS Traffic Management (UTM) service, which, in fact, has not yet been created.
Implementation of the proposed system would be an almost ideal solution to ensure security, but the
declared implementation of the system in real time on board a specific VTOL-UAV, in our opinion,
seems to be a difficult task, most likely not so much because of the large number of auxiliary
hardware components, but also huge volumes of data that will only come from external sources. For
example, data on the current population density in the flight area, or data on the strength of the
protective coating (strength of the roof material). In addition, the authors did not take into account the
very low degree of controllability of the multi-rotor VTOL-UAV in the event of a sudden failure of
one of the engines. If such a failure occurs, the remote pilot will not be able to perform a touchdown
operation at a new system-defined landing point or return to a departure point.
3. Problemstatement
For unmanned aerial vehicles with vertical take-off and landing, there is no algorithm for ensuring
the required safety during flight in the event of failure of one (or more) engines.
It is this type of VTOL-UAV that will be used for flights at very low level altitudes (VLL) and
within dense urban areas (U-space). Since VTOL-UAV of this type is the most vulnerable to loss of
control due to various failures, the development of decision-making algorithms in the event of failure
of critical VTOL-UAV components, which include engines, is relevant, since it will help prevent an
aviation incident.
4. Results
4.1. Expectedriskofanincidentduetomotorfailure
Consider how high the risk of an incident is in the event of a brushless motor failure. For technical
devices, the most convenient reliability characteristics are failure rate and mean time between failures.
Failure rate - λ (t) is the conditional density of the uptime distribution for time t, provided that no
failure of the device has occurred before time t.
)(
)(
)( tP
ta
t
,(1)
where a(t) is failure rate, P(t) is probability of failure-free operation. For practical purposes, the
following statistical expression for the failure rate can be used
tN
tn
t
av
)(
)(
,
(2)
where )( tn is the number of devices that failed over time, 2
1
ii
av
NN
N is the average number
of devices that work without failure over time t.
From [12] we know the boundary generalized values of the failure rate for small electrical
machines, which include brushless motors - they are in the range from 0.01 to 8 10-4 1 / h.
The mean time between failures is defined as the mathematical expectation of the device operation
until the first failure
T
t
MTBF
N
i
i
1,
(3)
where ti is the uptime of the i-th device (until the first failure), h; T is the total operating time of the
device.
According to the same source, MTBF for small electrical machines is in the range of 1.000 to
20.000 hours. MTBF performance of high-quality brushless motors is the best among this group.
However, there are two factors, the influence of which, according to [12], significantly reduces the
specified reliability characteristics. The first factor is the increased rotational speed expressed in rpm.
Thus, at a nominal rotation speed of 2500 rpm, the guaranteed uptime is 3000 hours, and when the
speed rises to 9000 rpm (more than three times), the uptime is reduced to a value from 200 to 600
hours. That is, when the rotational speed is increased by three times, the failure-free operation is
reduced by a factor of five or more! Therefore, taking this factor into account is mandatory when
assessing the risk of an incident in the event of an engine failure.
The second factor that can significantly increase the likelihood of failure is the ambient
temperature. Higher ambient temperatures also reduce guaranteed uptime. The dependences of the
decrease in the uptime with a rise in temperature coincide significantly with the dependences under
the influence of the factor of increased rotation speed. Thus, when assessing the risk of an incident,
the temperature factor must also be taken into account. Moreover, the elimination of the influence of
the first negative factor can be achieved by maintaining the nominal speed mode during manual
remote piloting, or by introducing algorithmic restrictions when piloting in the autopilot mode. But
the influence of the second factor, which is external to the unmanned aviation system, does not
depend in any way on the remote pilot's command and thus must be taken into account when creating
various algorithms for on-board systems that make it possible to increase the safety of VTOL-UAV
flight.
4.2. Additionalhardwaretooltorealizationofdevelopedalgorithm
To implement the algorithm, it is necessary to have a device for monitoring the speed of rotation
of the propeller, which is installed on the electric motor. As a similar device, one can use a speed
sensor that operates on the basis of the magnetoelectric Hall effect. Some manufacturers of higher
quality brushless motors already integrate Hall sensors into the motor design, which also serve as a
positioning support. In this case, the task of providing motor control is simplified. But even if there
are no sensors in the design of a brushless electric motor, it is possible to perform local design
modifications by connecting an external sensor to each unit.
Figure4:HallsensorSS41FfromSECElectronicInc.in3leadSIPpackage[13]
Such a sensor will record every change in the level of the magnetomotive force, which is induced
due to the appearance of an electric current in the stator coils. Thus, information about the speed of
each propeller from the Hall sensors will be transmitted to the VTOL-UAV microprocessor-based
flight control system. To implement the algorithm, the number of sensors will be required, depending
on the number of electric motors on the VTOL-UAV, since it is necessary to control the rotation
speed of each electric motor using its own sensor. The main task of the developed algorithm is to
monitor the performance of electric motors even in case of failure, which will be identified in the
event of either no rotation or insufficient rotation speed of one of the motors. Since such a failure will
immediately lead to a loss of control and the emergence of a conflict-hazardous situation, it is
necessary to automatically work out a decision on the immediate termination of the VTOL-UAV
mission and its landing.
The next device required for the implementation of the algorithm is a software module - a
microprocessor or microcontroller. On board VTOL-UAV such a module is mandatory, and very
often not alone - one microprocessor provides processing of navigation data from different navigation
sensors, the second microprocessor is the core of the flight control system - autopilot. Since modern
embedded microprocessors have a high degree of integration and contain several cores on their chip,
both of these functions can be assigned to a single, high-performance microprocessor. However, many
autopilot designers do separate navigation and control functions. Moreover, the latest trends in the
development of on-board systems provide for equipping VTOL-UAV with microprocessors with a
battery management system (BMS) [14, 15], which makes it possible to increase the level of VTOL-
UAV flight safety. Since the microprocessor of the BMS system interacts with the electric motor, its
software will require minor modifications by adding the code of the developed algorithm, which, due
to the introduction of hardware controls, will be quite simple and compact in terms of the program
code.
4.3. Designofthealgorithm
With regard to the choice of the necessary hardware, the block diagram of the decision-making
algorithm will have the following form, shown in Fig. 5. At the first step of the software
implementation of the algorithm, it is necessary to set the failure counter - x for the i-th engine. The
counter of events (motor failures) can take the values of x[i]={0, 1, 2}. The event counter is reset to
zero during the initialization of the onboard control system before starting the flight. As a failure
criterion, we will consider an event whereby the current value of the rotation speed of the i–th engine
Vrot[i] measured with the i-th sensor (sensor [i]) will be less than the required value of the speed
Vreqrmnt[i] or even equal to zero, necessary to ensure the controlled flight of VTOL-UAV. As long as
the flight is in progress - the algorithm provides for a cyclic poll of the rotation sensors and compares
the current measured speed value with the set value generated by the control system. In the case of the
first fixation of a failure of one of n electric motors, the counter of the i-th motor failure is
incremented for the first time and takes the value x [i] = 1. After the initial setting of the failure
counter, a re-confirmation check is performed, and if this check gives a negative result, the transition
to the next step of the algorithm is performed. In this case, such an electric motor is considered to be
conventionally failed, and information is sent to the control system about the repeated sending of a
control action to this engine in order to establish the required value of its rotation speed. The control
action is usually a PWM signal, the required pulse width of which is set by the processor of the
VTOL-UAV control system.
If the condition Vrot[i] < Vreqrmnt[i], is repeatedly satisfied, then the failure counter takes the value x
[i]=2 and the transition to the algorithm branch responsible for the emergency termination of the flight
occurs, since when one electric motor is inoperative, the probability of the origin of an aviation
incident increases.
The emergency command block must contain two sequential procedures. In the event of a failure
of one of the engines, the multi-rotor type VTOL-UAV immediately loses stability and begins to
rotate around a horizontal or vertical axis. If at this moment in time all the engines are stopped at once
and then the parachute compartment is opened for such an unstable VTOL-UAV, the parachute will
get entangled around the hull and the VTOL-UAV will still make an uncontrolled fall, thus increasing
the risk of an incident many times over.
In case of failure of one of the engines of the propeller-driven group, to stabilize the multi-rotor
aircraft, it is necessary to immediately shut down the symmetrical engine, which is located diagonally
opposite the suddenly failed engine according to the diagram shown in Fig. 6 where symmetric
engines for a six-screw VTOL-UAV (hexacopter) are connected by a blue, red or green dashed line,
respectively. After such a shutdown, the motors remaining in working condition will stabilize and
prevent an uncontrolled fall for some time.
Thus, in the branch of the emergency subroutine, the emergency engine is first assigned a zero
index - j = 0, then x [0]. Following that, the symmetrical (diagonal) motor is turned off. The index of
such an engine for a quadcopter will be x[2], for a hexacopter x[3], for an octacopter x[4]. To unify
the algorithm in the block diagram of the algorithm, the symmetric motor index is denoted as simmetr.
After this operation, a short time delay of no more than 3 s is required to stabilize the aircraft. The
block-diagram of the algorithm shows this delay as the _delay statement.
Further execution of the program involves sending a command to the flight control system to
simultaneously turn off all other electric motors, which in a formalized form can be represented as a
command Vrot[i] = 0, executed in a cycle. Next, the sending of the current coordinates is initiated, at
which the flight is forcibly interrupted, via the downstream C2 subchannel to the remote pilot to
notify him of the location of the VTOL-UAV, and a command is sent to the control system that
initiates the opening of the parachute compartment and the release of the parachute. Then VTOL-
UAV makes landing.
Figure5:BlockdiagramofthedecisionmakingalgorithmincaseoffailureoftheVTOLUAVelectric
motor
Figure6:Diagramshowingpairsofsymmetricalmotorsforahexacopter
5. Conclusions
Based on the analysis of sources, two negative factors have been identified that significantly
reduce the standard indicators of the uptime of brushless motors and thus increase the risk of an
incident: increased values of the speed of rotation of the rotor of the electric motor, which will be
present in case of need for high-speed flight mode of VTOL-UAV and increased ambient
temperature.
Taking into account the limited time for making a decision and preventing the risk of an incident,
an algorithm that is simple for software implementation has been developed that does not require
mathematical calculations, for the implementation of which it is necessary to have devices for
measuring the speed of rotation of engines. For this purpose it is proposed to use Hall sensors
installed on each engine of a multi-rotor VTOL-UAV.
To prevent the program from failure when polling sensors, double redundancy of sensor readings
is provided. Also, in case of confirmation of engine failure, a module has been introduced into the
algorithm providing for preliminary shutdown of the engine symmetrical to the one who has
confirmed the failure. After turning off the rest of the engines, the parachute compartment is activated
for an accurate landing at low speed.
6. References
[1] ICAO Annex 19 ‘Safety Management’, first edition. 2013. 44 p.
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[3] E. Petritoli, F. Leccese, L. Ciani, Reliability and Maintenance Analysis of Unmanned Aerial
Vehicles. Sensors 18 (2018) 1-16. doi:10.3390/s18093171.
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[5] Larin V.J., Shcherban, A.P., Ryzhykh V.M., V.P. Maslov, N.V. Kachur Use of infrared
thermography method to develop discharging rules for lithium-polymer batteries.
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[9] Twin-engined unmanned aerial vehicle M-7V5 “Sky patrol”. URL: - http://uav.nau.edu.ua/m-
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[10] Weibel, R. E., Hansman, R. J., Jr., Safety Considerations for Operations of Different
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[12] J. F. Gieras, Permanent Magnet Motor Technology: Design and Applications. 3rd
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ResearchGate has not been able to resolve any citations for this publication.
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Unmanned aerial vehicles (UAVs) are sufficiently mature to operate in manned airspace. Failure analysis with a risk assessment is critical to aviation safety. Performance criteria are analyzed to determine how UAVs can be operated more safely. Any failures can cause casualties. This study assesses the crash probability density (CPD) using Newton’s laws of motion and Galileo’s free fall. Different UAVs that use horizontal and vertical takeoff and landing are studied with different classes of wing, weight, velocity, and altitude to simulate failure due to a crash. Different failure scenarios are simulated using MATLAB Simulink. Dynamic characteristics with disturbance are used to determine the probable coverage of impact on the ground. The results are used to construct a new type of path planning for a UAV, which uses the CPD radius to avoid highly populated areas. A risk assessment uses the expected level of safety (ELS) for the frontal impact area of UAVs. Using CPD path planning, the results show that the Fatality rate and the expected level of safety for a UAV correspond to a risk level of 10−8 events/flight hour. This allows safer UAV flight planning.
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The results of using the infrared thermography method for studying the discharging process in lithium polymer batteries have been presented in this article. The general rules of discharging a lithium polymer battery are shown in the maximum mode of drone engine operation, namely, regardless of the external temperature, the process of heating the battery has a nonlinear character with a clear maximum temperature. In the course of operation of unmanned aerial vehicles under reduced temperatures, special attention is required before making a decision to connect an additional battery and fulfilling the “home” command. Testing the battery temperature during a flight with an autonomous control system can be carried out not by a thermographic camera, but by means of temperature sensors.
Triple Probability Density Distribution Model in the Task Of Aviation Risk Assesment
  • I Ostroumov
  • K Marais
  • N Kuzmenko
  • N Fala
I. Ostroumov, K. Marais, N. Kuzmenko, N. Fala, Triple Probability Density Distribution Model in the Task Of Aviation Risk Assesment. AVIATION 24 (2020) 57-65. doi:/10.3846/aviation.2020.12544.
Safety Considerations for Operations of Different Classes of UAVs in the NAS
  • R E Weibel
  • R J Hansman
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Weibel, R. E., Hansman, R. J., Jr., Safety Considerations for Operations of Different Classes of UAVs in the NAS, AIAA 3rd "Unmanned Unlimited" Technical Conference, Workshop and Exhibit, AIAA Paper 2004-6244, 2004.
System for monitoring the state of the battery of an unmanned aerial vehicle
  • A Shcherban
A. Shcherban System for monitoring the state of the battery of an unmanned aerial vehicle. PhD thesis. Institute of Electrodynamics of NAS of Ukraine, Kyiv, 2020.
Intelligent System for Temperature Control of Li-Pol Battery
  • A Shcherban
  • V Larin
  • V Maslov
  • N Kachur
  • T Turu
A. Shcherban, V. Larin, V. Maslov, N. Kachur, T. Turu. Intelligent System for Temperature Control of Li-Pol Battery [on-line]. International Journal of Automation, Control and Intelligent Systems 4 (2018) 24-28.