Method for modeling and predicting the electrical consumption of an aircraft comprising at least one electric motor, along a flight plan

Abstract

A method for predicting the electrical consumption of an aircraft comprising at least one electric motor, along a flight plan comprising the following steps: loading (1) the flight plan; performing a calculation (2), updated in real time, predicting the electrical consumption of the aircraft at all points along the flight plan to the destination. Figure for the abstract: [Fig.1]

Description

Title of the invention: Method for modeling and predicting the electrical consumption of an aircraft comprising at least one electric motor, along a flight plan

[0001] The invention relates to a method for predicting the electrical consumption of an aircraft comprising at least one electric motor, along a flight plan.

[0002] The release of carbon dioxide into the air is at the heart of all the problems, and aeronautics is no exception.

[0003] Fuel has long been the only source of energy, but in the current context, electrical energy is challenging the way aircraft operate. While we wait for the aircraft to evolve towards electric power, other aircraft are already electric, such as drones. They are evolving rapidly and can, in particular, penetrate dangerous places, carry loads and eventually transport people. Aeronautical companies are therefore very anchored in the drone industry in parallel with the announced evolution of aircraft towards electric power.

[0004] For the latter, we have already had the replacement of hydraulics by electric for many avionics systems. For some aircraft, the engines have already gone electric.

[0005] In the aviation field, there are systems on the ground or on board aircraft such as the FMS system, which stands for "Flight Management System", capable of calculating fuel consumption predictions on a flight. These precise predictions are based on the performance of the aircraft and are calculated along the flight plan followed by the aircraft using the fuel consumption model of the engines as a function of the speeds and drag characteristics of the aircraft.

[0006] In the terrestrial domain, there are systems for cars capable of calculating predictions of the distance that can be covered with the fuel remaining in the tank. These predictions are more crude since the route plan is little or not known and the system does not know the characteristics of the route followed, in particular in terms of levels, climbs or descents.

[0007] For a land vehicle, the risk of no longer having the energy to continue moving forward is a risk with no safety impact, which results in a potential stop in the middle of nowhere with no means of recharging the vehicle with energy. An aircraft cannot stop in flight and must therefore know precisely its energy reserve and its capacity to reach a place where it can land safely.

[0008] For electric land vehicles, systems giving achievable distances give values ​​that are just as approximate as for vehicles with thermal engines.

[0009] In the aviation sector, there is a system, the FMS, capable of calculating fuel consumption predictions.

[0010] Since aircraft power supply is new, the problem is anticipated empirically, firstly by estimating the average hourly consumption and the average speed, which determined a rough and often conservative flight time and crossing distance. In addition, this creates the need for an emergency function to interrupt the flight and land the aircraft in an emergency.

[0011] There is a document EP 3 104 122 A1 which addresses a system for calculating predictions of electrical consumption but without addressing the problem of modeling the energy source battery.

[0012] There is no observation / alert function based on electrical predictions (due to the lack of reliability of these electrical consumption predictions).

[0013] Similarly, there is no optimization of trajectory management based on predictions of electrical consumption.

[0014] Current power consumption prediction capabilities for a mobile are not accurate in the absence of detailed power consumption modeling. While they are acceptable for a land mobile, they are incompatible with the needs of an air mobile or aircraft.

[0015] The empirical estimate therefore means that a drone is currently only operated with a large safety margin, which is really not optimal.

[0016] In the state of the art, no solution exists to envisage optimized flight planning and management in electric operation.

[0017] According to one aspect of the invention, there is proposed a method for modeling and predicting the electrical consumption of an aircraft comprising at least one electric motor, along a flight plan comprising the following steps: - load the flight plan; - perform a calculation, updated in real time, predicting the aircraft's electrical consumption at all points of the flight plan to the destination, in which: - a 2D or 3D trajectory with N segments remaining to be flown is calculated from the N+1 waypoints of the flight plan remaining to be flown and from the operating parameters and the external environment of the aircraft; - we iteratively perform, on each segment i of the N successive segments of the trajectory remaining to be flown: - an estimate of the electrical energy consumption consumed on the current segment i from a predetermined model; and - we add the estimate of the electrical energy consumption consumed on the current segment i to the estimate of the consumption estimated on all the previous segments.

[0018] According to one embodiment, the predetermined modeling of estimation of the consumption of electrical energy consumed on a trajectory segment by the aircraft depends on an estimated necessary power ("Compute Thrust Setting") for supplying the electric motor(s).

[0019] In one embodiment, the predetermined modeling for estimating the electrical energy consumption consumed on a trajectory segment by the aircraft is the result of a statistical synthesis of recorded flight data, flights during which the aircraft travels specific predefined segments (level, constant slopes in ascent or descent, with constant speed or in acceleration or deceleration) at different engine power regimes, according to previously defined meteorological conditions (without and with wind of different intensities and directions, variable high or low temperature).

[0020] According to one embodiment, the flight data comprises the altitude of the aircraft, and / or the static temperature of the aircraft, and / or the speed of the aircraft, and / or an engine power supplying electrical systems other than the electric motor.

[0021] In one embodiment, the estimated necessary power supply to the electric motor(s) is the result of a statistical synthesis of recorded flight data, flights during which the aircraft travels specific predefined segments at different power regimes of the electric motor, according to predefined meteorological conditions.

[0022] According to one embodiment, the method comprises a step of periodic calculation updated in real time, of the remaining electrical energy by subtracting from the available electrical energy the prediction of electrical consumption up to the destination.

[0023] In one embodiment, the method comprises a periodic step of monitoring or surveillance of the remaining electrical energy, and raising an alert when said remaining electrical energy is below a limit threshold of compatibility with the objective of the flight plan*.

[0024] According to one embodiment, the method comprises a step of optimizing operating or environmental parameters of the aircraft, including the altitude and / or the speed of the aircraft and / or the wind and / or the surrounding temperature, from the prediction of aircraft electrical consumption up to destination, depending on meteorological parameters

[0025] In one embodiment, the method comprises, when the aircraft also comprises at least one thermal engine, a step of calculating (10) updated in real time, the remaining fuel by subtracting from the available fuel the prediction of fuel consumption up to the destination.

[0026] The invention will be better understood by studying a few embodiments described as non-limiting examples and illustrated by the appended drawing in which [Fig. 1] schematically illustrates a mode of implementation of the method for predicting the electrical consumption of an aircraft comprising at least one electric motor, along a flight plan, according to one aspect of the invention.

[0027] Throughout the figures, elements having identical references are similar.

[0028] [Fig.l] represents an embodiment of the method for predicting the electrical consumption of an aircraft comprising at least one electric motor, along a flight plan comprising the following steps: - load 1 the flight plan; - perform a periodic calculation 2, updated in real time, predicting the aircraft's electrical consumption up to its destination, in which: - a 2D or 3D trajectory with N segments remaining to be flown is calculated from the N+1 waypoints of the flight plan remaining to be flown and from operating parameters and the external environment of the aircraft; - we iteratively perform 4, 7, 8, on each segment i of the N successive segments of the trajectory remaining to be flown: - an estimate 5 of the electrical energy consumption consumed on the current segment i from a predetermined model; and - we add 6 the estimate of the electrical energy consumption consumed on the current segment i to the estimate of the estimated consumption on all the previous segments.

[0029] Unlike fuel, which can be considered as a static energy, when the energy source is electrical energy supplied by a battery, it becomes dynamic. On the one hand, the discharge of a battery is not linear, and on the other hand, the battery has its own performance which depends on operating and environmental parameters, such as temperature or the age of its components. To the knowledge required previously, it is necessary to add knowledge of the energy performance of the battery.

[0030] The calculation of the electrical consumption on a segment i of trajectory is the result of a statistical synthesis of recorded flight data, flights during in which the aircraft travels specific predefined segments at different electric motor power regimes, according to predefined weather conditions.

[0031] In the case of a prediction of electrical consumption, the estimation is more complex than for fuel for a thermal engine. Indeed, unlike fuel which is a static energy source, the electrical energy source, in this case a battery, is a dynamic source.

[0032] The classic principle of fuel consumption on a trajectory segment uses an estimated necessary power, for a thermal engine, from parameters including the speed of the thermal engine, the altitude, the speed or mach, the use of power from the thermal engine for ancillary devices, such as defrosting and the various hydraulic circuits for system and cabin services, and a possible failure of an engine in the event of the presence of at least two thermal engines.

[0033] From this power the quantity of fuel consumed on the segment is calculated. A simple subtraction makes it possible to determine the remaining fuel.

[0034] The available electrical energy is data provided by the battery manufacturer, deduced from measurements of the electrical and physical parameters of the battery (voltage, impedance, intensity, temperature, etc.).

[0035] The available quantity of electrical energy, in other words the capacity of the battery, depends on the ambient temperature which can degrade its capacity to maintain electrical energy, its age which can degrade its storage capacity, and the quantity of energy required (the discharge of a battery is not linear).

[0036] Taking this last parameter into account underlines the novelty of the present invention since the electrical energy used does not simply come as a subtraction from the available energy but indirectly impacts the capacity of the battery itself.

[0037] The transition to electric energy requires a transitional phase or even hybrid operation like airplanes for which the enormous energy required to take off cannot be managed by batteries while maintaining flight once in the air requires much less energy.

[0038] To calculate energy consumption predictions on a trajectory segment with a thermal engine, a model of the engine and its fuel consumption is established as a function of the power required to travel this segment.

[0039] For an electric motor, the same approach to modeling its energy consumption is used to determine the power required to travel a trajectory segment and its associated energy consumption. But to calculate the remaining energy, it is necessary to model the battery and its discharge as a function of the energy demand.

[0040] In the present invention, the modeling of battery discharge is more complicated than emptying a tank, because, for example, the age of the battery can be considered as a penalty factor that degrades the energy consumption. The temperature is more of a performance factor affecting the maintenance of the level of the remaining energy over time. Finally, the energy demand is the input parameter but the amount of which is not simply subtracted from the battery charge but acts indirectly on the remaining charge by the fact that the electrical discharge of the battery is not a linear function.

[0041] The ability to predict (with a numerical precision depending on the validated model) the feasibility of the planned route using the proposed method of predicting electricity consumption makes it possible to implement the following monitoring and increasing alert levels: - real-time alert, in the medium / long term, of the loss of feasibility of the route, linked to insufficient autonomy to reach the destination according to the flight plan (including flight level and speed); - alert in the medium / long term in case of insufficient autonomy to reach the destination along a direct line by adopting the speed / altitude while minimizing electrical consumption; - alert in the short / medium term in the event of insufficient autonomy to reach each successive clearance area in a straight line from the current position; - short-term alert when the battery charge reaches a minimum threshold; - alert on the risk of not being able to carry out repetitive tactical patterns (for Search and Rescue - SAR - or camera inspection) after calculating a maximum endurance time or "max endurance time" in English; and - corollary alert (called "Bingo Battery") requiring the mission to be interrupted to land as quickly as possible.

[0042] Similarly, the ability to predict the feasibility of the planned route makes it possible to implement the following different electrical consumption optimization functions: - Points of no return between each departure and destination then between each run-off area and next run-off area depending on the trajectory, wind and modeled battery consumption; - Optimization of the best flight altitude taking into account the predicted electrical consumption and the predicted wind on the route; - Choice of trajectory optimizing battery autonomy / consumption (depending in particular on winds, temperature and speed); - In the case of a drone equipped with solar sensors to recharge the battery, optimization of the route maximizing solar illumination; - Consumption depending on speed, depends on the automatic switch to ECON mode (lowest consumption speed), upon detection of a low battery reserve (below a threshold) at the destination with the current trajectory and speed; - Alternatively, if the electrical reserve at the predicted destination is below a threshold, a search is implemented for the best altitude optimizing the wind, even if it means abandoning the mission if it is planned at a fixed altitude.

[0043] The present invention consists of making it possible to calculate electrical consumption predictions that are as precise and reliable as those currently provided in the context of aircraft with thermal engines for fuel consumption, taking into account the trajectory to be followed.

[0044] It makes it possible to deduce from environmental or flight parameters (wind, temperature, pressure) and performance or operation of the aircraft (drag, thrust, engine power, and energy available in fuel or electricity, the age of the battery which degrades the performance of the battery), the consumption of electrical energy along the trajectory, and therefore makes it possible to provide precise predictions in terms of consumption of electrical energy, which brings a considerable benefit and is essential to know at any time the performance of the mission (capacity to carry out the mission and reach the destination by following the planned trajectory).

[0045] The present invention makes it possible, in real time, to monitor or supervise and alert on overconsumption due to a headwind for example and affecting the planned movement.

[0046] It also allows the remote pilot to be warned when the battery charge becomes very low.

[0047] Thus, operators are no longer obliged to make rough estimates of electricity consumption, requiring them to take very large safety margins on travel time to compensate for not taking into account current weather (winds, temperature) and battery degradation over time.

[0048] The present invention may initially concern the specific case of drones, but also applies to electric aircraft. It may find applications in many other fields, such as: - For aircraft with electric motors: Monitoring of sporting events (Tour de France, Paris-Dakar, etc.) from a drone; Trajectories of future urban taxis or electric civil transport aircraft; Monitoring of ships or submersibles; Infrastructure monitoring (railways, highways, power lines, borders). For electric cars or electric boats.

Claims

1. Claims Method for modeling and predicting the electrical consumption of an aircraft comprising at least one electric motor, and an electric battery and a battery discharge modeling module, along a flight plan comprising the following steps: - load (1) the flight plan; - perform a calculation (2), updated in real time, predicting the aircraft's electrical consumption at all points of the flight plan to the destination, in which: - we calculate (3) a 2D or 3D trajectory with N segments remaining to be flown from the N+1 waypoints of the flight plan remaining to be flown and from operating parameters and the external environment of the aircraft; - we iteratively perform (4, 7, 8), on each segment i of the N successive segments of the trajectory remaining to be flown: - an estimate (5) of the electrical energy consumption consumed on the current segment i from a predetermined modeling of the electrical energy consumption consumed on a trajectory segment by the aircraft which is the result of a statistical synthesis of recorded flight data, flights during which the aircraft travels specific predefined segments at different power regimes of the electric motor, according to predefined meteorological conditions; and - we add (6) the estimate of the consumption of electrical energy consumed on the current segment i to the estimate of the consumption estimated on all the previous segments; - periodically calculate (9) and update in real time the remaining electrical energy by subtracting from the available electrical energy the prediction of electrical consumption up to the destination; and optimize the operating or environmental parameters of the aircraft, including the altitude and / or the speed of the aircraft and / or the wind and / or the surrounding temperature, from the prediction of aircraft electrical consumption up to destination, depending on meteorological parameters.

2. Method according to claim 1, in which the predetermined estimation model (5) of the consumption of electrical energy consumed on a trajectory segment by the aircraft depends on an estimated necessary power supply to the electric motor(s).

3. A method according to claim 2, wherein the flight data comprises aircraft altitude, and / or aircraft static temperature, and / or aircraft speed, and / or engine power supplying electrical systems other than the electric motor.

4. Method according to claim 3, in which the estimated necessary power supply to the electric motor(s) is the result of a statistical synthesis of recorded flight data, flights during which the aircraft travels specific predefined segments at different power regimes of the electric motor, according to predefined meteorological conditions.

5. Method according to one of the preceding claims, comprising a periodic step of monitoring or surveillance of the remaining electrical energy, and raising an alert when said remaining electrical energy is below a limit threshold of compatibility with the objective of the flight plan.

6. Method according to one of the preceding claims, comprising, when the aircraft also comprises at least one thermal engine, a step of calculating (10) updated in real time, the remaining fuel by subtracting from the available fuel a prediction of fuel consumption up to the destination.

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