Method for finding a charging station for electric motor vehicles

Abstract

The invention relates to a method for finding a charging station for electric motor vehicles using at least one drone that has a monitoring device, said method comprising the following steps: generating control signals for controlling the at least one drone such that, when controlling the drone based on the generated control signals, the at least one drone monitors an environment of an electric motor vehicle by means of its monitoring device and outputs monitoring data based on the monitoring; outputting the generated control signals in order to control the at least one drone based on the generated control signals; after outputting the generated control signals, receiving the monitoring data from the at least one drone; analysing the monitoring data in order to find a charging station for electric vehicles; and outputting an analysis result of the analysis of the monitoring data. The invention also relates to an apparatus, a system for finding a charging station for electric motor vehicles, a computer programme, and a machine-readable storage medium.

Description

[0001] Description

[0002] title

[0003] Procedure for finding a charging station for electric vehicles

[0004] The invention encompasses a method for finding a charging station for electric vehicles, a system for finding a charging station for electric vehicles, a device, a computer program and a machine-readable storage medium.

[0005] State of the art

[0006] Electric vehicles have a traction battery. An electric vehicle charging station can be used to charge the traction battery.

[0007] Disclosure of the invention

[0008] The object underlying the invention is to provide a concept for efficiently finding a charging station for electric vehicles.

[0009] The object is achieved by means of the respective subject matter of the independent claims. Advantageous embodiments of the invention are the subject matter of the respective dependent subclaims.

[0010] According to a first aspect, a method for finding a charging station for electric vehicles using at least one drone having a monitoring device is provided, comprising the following steps: generating control signals for controlling the at least one drone such that, when the drone is controlled based on the generated control signals, the at least one drone monitors an environment of an electric vehicle by means of its monitoring device and outputs monitoring data based on the monitoring, outputting the generated control signals in order to control the at least one drone based on the generated control signals, receiving the monitoring data from the at least one drone after outputting the generated control signals, analyzing the monitoring data in order to find a charging station for electric vehicles, and

[0011] Output an analysis result of the monitoring data analysis.

[0012] According to a second aspect, an apparatus is provided which is configured to carry out all the steps of the method according to the first aspect.

[0013] According to a third aspect, a system for finding a charging station for electric vehicles is provided, comprising: at least one drone, wherein the at least one drone has a monitoring device, and the device according to the second aspect.

[0014] According to a fourth aspect, a computer program is provided which comprises instructions which, when the computer program is executed by a computer, for example by the device according to the second aspect and / or by the system according to the third aspect and / or by a drone comprising a monitoring device, cause the computer to carry out a method according to the first aspect.

[0015] According to a fifth aspect, a machine-readable storage medium is provided on which the computer program according to the fourth aspect is stored. The invention is based on and includes the finding that the above object can be achieved by using one or more drones to find a suitable charging station at which a drive battery of the electric vehicle can be charged. The at least one drone, i.e. the one or more drones, are controlled in such a way that they monitor the surroundings of the motor vehicle using their respective monitoring device and output monitoring data based on the monitoring. Thus, knowledge about the surroundings of the motor vehicle is advantageously and efficiently available. This knowledge is used to search for suitable charging stations for electric vehicles at which the drive battery can be charged.

[0016] The use of one or more drones for this purpose has the particular technical advantage that a drone's monitoring system can also monitor areas in the vehicle's surroundings that cannot be monitored by the vehicle's own environmental sensor or by the vehicle's own environmental sensors. For example, an environmental sensor of a motor vehicle has a certain range. The drone, however, can be controlled in such a way that it monitors an area of ​​the vehicle's surroundings that lies outside the range of the vehicle's environmental sensor. This provides information about the vehicle's surroundings that would not be available through the vehicle's own environmental sensors.

[0017] This provides the technical advantage that one or more suitable charging stations can be searched for efficiently, allowing even those charging stations in the vicinity of the vehicle that could not be found using the vehicle's own environmental sensor to be efficiently located. This advantageously allows for an efficient search for a free charging station suitable for the electric vehicle.

[0018] The drone's monitoring device can advantageously provide information that is not recorded in a digital map, for example, and / or of which, for example, a charging station center for managing one or more charging stations has not yet been aware.

[0019] For example, the search time for a charging station can be advantageously shortened, which in turn saves electrical drive energy, so that the range of the electric vehicle, for example, does not decrease as quickly as if time and drive energy had to be used for a long search for a charging station.

[0020] In summary, a concept for efficiently finding a charging station for electric vehicles is provided.

[0021] For example, if a charging station is found, the position of the found charging station is determined, in particular based on the monitoring data. This means, for example, that analyzing the monitoring data includes determining the position of the found charging station. The analysis result includes, for example, the determined position of the found charging station.

[0022] Finding something, in this case the charging station, means in particular that the something, in this case the charging station, is not known from the perspective of the searcher, in this case in particular from the perspective of the drone or electric vehicle, before it is found, but only becomes known through the finding. Instead of the term "find," the term "discover" can also be used, for example, and vice versa. The monitoring data is therefore analyzed in particular to discover a charging station. This means, for example, that before the surroundings of the electric vehicle are monitored, a charging station that may be present in the surroundings is not known from the perspective of the drone or electric vehicle, but is only found or discovered through the monitoring.

[0023] "Find" therefore means, in particular, "to encounter or stumble upon someone or something, in this case the charging station, either by chance or while searching." "Find" therefore means, in particular, "to discover someone or something."

[0024] Thus, the phrase "finding a charging station" can also be supplemented with "finding an unknown charging station." Thus, finding a charging station specifically means discovering a charging station by chance. "Finding" can also be replaced with "discovering by chance," for example.

[0025] When the singular is used for a drone in the description, the plural should always be included, and vice versa. Statements made in connection with one drone apply analogously to multiple drones, and vice versa.

[0026] The phrase "at least one" means "one or more." This means, in particular, that, for example, multiple drones can be used. Multiple drones can be identical, for example, or different.

[0027] For example, the surveillance devices of the drones are at least partially, in particular all, identical or are at least partially, in particular all, different.

[0028] A monitoring device within the meaning of the description comprises, for example, one or more environmental sensors. This means, in particular, that the drone, for example, has one or more environmental sensors. The drone is thus, in particular, equipped with one or more environmental sensors. An environmental sensor of a monitoring device, for example, detects the surroundings of the motor vehicle and outputs environmental sensor data based on this detection. Such environmental sensor data is, for example, included in the monitoring data.

[0029] This means in particular that monitoring within the meaning of the description includes detecting the surroundings of the motor vehicle by means of an environment sensor of the monitoring device.

[0030] When the singular is used for the environmental sensor, the plural should always be included, and vice versa. Statements made in connection with one environmental sensor apply analogously to multiple environmental sensors, and vice versa.

[0031] An environmental sensor within the meaning of the description is, for example, one of the following environmental sensors: LiDAR sensors, radar sensors, image sensors, in particular image sensors of a video camera or a stereo camera, ultrasonic sensors, infrared sensors and magnetic field sensors.

[0032] For example, environmental sensors can be identical or they can be different.

[0033] In one embodiment of the method, this comprises a step of controlling the at least one drone based on the output control signals.

[0034] In one embodiment of the method, this comprises a step of monitoring the surroundings of the motor vehicle by means of the at least one drone.

[0035] In one embodiment of the method, this comprises a step of detecting the surroundings of the motor vehicle using an environment sensor of the monitoring device. In one embodiment of the method, this comprises a step of wirelessly transmitting the output control signals to the at least one drone. Such wireless transmission comprises, for example, transmitting the control signals via a wireless communications network, for example, a cellular network and / or WLAN network.

[0036] Receiving the monitoring data comprises, for example, wirelessly receiving the monitoring data, in particular wirelessly receiving the monitoring data via a wireless communication network, for example a mobile network and / or a WLAN network.

[0037] In one embodiment of the method, this is a computer-implemented method.

[0038] The embodiments and exemplary embodiments described in the description can be combined with one another in any form, even if this is not explicitly described.

[0039] The analysis result indicates, for example, whether or not an electric vehicle charging station was found. If a charging station was found, the analysis result indicates, for example, the location of the charging station.

[0040] For example, multiple charging stations may be found. Statements made in connection with one charging station apply analogously to multiple charging stations, and vice versa.

[0041] A charging station within the meaning of the description is a charging station for electric vehicles.

[0042] An electric vehicle as defined in the description has a drive battery and an electric motor, which can be supplied with electrical energy by the drive battery. Analyzing the monitoring data includes, for example, processing the monitoring data. Processing the monitoring data is performed, for example, using one processor or multiple processors. This means, for example, that the analysis can be performed using one computer or multiple computers.

[0043] In one embodiment of the method, it is provided that dimension signals are received which represent one or more dimensions of the electric motor vehicle, wherein the monitoring data are analyzed based on the dimension signals, wherein the analysis comprises checking a found charging station to determine whether a drive battery of the electric motor vehicle can be charged in the found charging station based on its dimension or dimensions.

[0044] This provides the technical advantage, for example, that a charging station that has been found can be efficiently checked for its suitability, as to whether the motor vehicle can actually be parked at the charging station found due to its size, i.e. due to its dimensions, in order to charge a drive battery of the electric vehicle.

[0045] For example, a dimension is one of the following dimensions: length, width, height.

[0046] In one embodiment of the method, the analysis includes checking whether a charging station found is accessible for the electric vehicle.

[0047] This provides the technical advantage, for example, of being able to efficiently ensure that a charging station found is actually accessible for the motor vehicle, i.e. whether the motor vehicle can actually access the charging station found.Checking whether a charging station found is accessible for the motor vehicle at all includes, for example, checking whether an entrance to the charging station, in particular an entrance to a defined area within which the charging station found is located, is wide enough for the motor vehicle to drive through the entrance, and / or checking whether there are one or more objects in front of the charging station, for example a construction site marking or a pillar, for example a construction site pillar, which could hinder or prevent entry into the charging station, and / or checking whether the entry radius required for the motor vehicle to enter the charging station is possible due to a maximum possible steering angle of the motor vehicle.

[0048] In one embodiment of the method, it is provided that the analysis includes determining an occupancy status of a found charging station.

[0049] This provides the technical advantage, for example, of efficiently determining the occupancy status. An occupancy status can be, for example, free or occupied, or partially free or partially occupied. For example, it may already be known that a charging station is located in the vicinity of the vehicle. However, whether it is (partially) occupied or (partially) free may not be known. Using the drone, it is thus possible, and in particular, intended, to determine the current occupancy status even before the electric vehicle itself arrives at the charging station.

[0050] In one embodiment of the method, it is provided that the analysis comprises determining a position of a charging station found that is located within a defined area relative to the area.

[0051] This provides the technical advantage, for example, that the charging station can be efficiently located within the area. An area, for example, is an element selected from the following group of areas: parking lot, supermarket parking lot, rest area, roadside.

[0052] For example, one or more charging stations are located within the areas mentioned above as examples. The position of the found charging station relative to the area indicates where the found charging station is located within the area. For example, where the found charging station is located relative to a reference point or fixed point within the area. Such a reference point or fixed point is, for example, an entrance or exit. This makes it possible, for example, to determine where a charging station in a parking lot is located relative to the entrance or exit.

[0053] In one embodiment of the method, it is provided that, in the case of an analysis result which indicates that a charging station for the motor vehicle has been found, further control signals for controlling the at least one drone are generated in such a way that, upon further control of the drone based on the generated further control signals, the at least one drone monitors the found charging station by means of its monitoring device and outputs further monitoring data based on the monitoring, wherein the generated further control signals are output in order to further control the at least one drone based on the generated further control signals, wherein after the output of the further control signals the further monitoring data is received, wherein the further monitoring data is analyzed in order to determine a further analysis result, which is output.

[0054] This provides the technical advantage, for example, that the charging station found is further monitored, so that up-to-date information about it is still available. Analyzing the additional monitoring data includes, for example, determining whether the current occupancy status of the charging station has changed. For example, before the electric vehicle arrives at the charging station, it can be detected that a previously free charging station has since been occupied by another electric vehicle, requiring a search for a new charging station using the drone. This efficiently prevents the electric vehicle from driving to the charging station in vain.

[0055] Statements made in connection with controlling, monitoring and analyzing apply analogously to further controlling, further monitoring and further analyzing and vice versa.

[0056] In one embodiment of the method, it is provided that charging station route signals are generated which represent a charging station route from a starting position to a found charging station for the electric vehicle, wherein the generated charging station route signals are output.

[0057] This provides the technical advantage, for example, that the electric vehicle can be efficiently guided to the charging station it has found. In particular, the determined charging station route is provided to the electric vehicle, based on which the electric vehicle can drive to the charging station it has found.

[0058] The starting position could be, for example, the current position of the electric vehicle or a future position of the electric vehicle. The future position of the electric vehicle can, for example, be predicted.

[0059] In one embodiment of the method, the analysis includes determining the optimal charging station when multiple charging stations are found. This provides, for example, the technical advantage of efficiently ensuring that an optimal charging station for the electric vehicle is found with regard to charging the electric vehicle's drive battery.

[0060] An optimal charging station is, for example, the charging station that is closest to the electric vehicle and to the direction of travel of the electric vehicle. An optimal charging station is, for example, the charging station found that offers the most space for charging the electric vehicle's drive battery. An optimal charging station is, for example, the charging station found that is most easily accessible for charging the electric vehicle's drive battery. Best can mean, for example, that there are no objects that hinder or prevent access to the charging station. Best can, for example, in addition to or instead of, mean that the required approach radius is minimal relative to the required approach radius of the other charging stations.

[0061] In one embodiment of the method, it is provided that route signals are received which represent a current route of the electric vehicle on the basis of which the electric vehicle is currently traveling, wherein the control signals are generated based on the route signals and / or wherein the monitoring data are analyzed based on the route signals.

[0062] This results in the technical advantage, for example, that the control signals can be generated efficiently and / or that the monitoring data can be analyzed efficiently.

[0063] According to this embodiment, knowledge is available about where the electric vehicle intends to travel. Accordingly, the drone can be specified via the control signals which area in the vicinity of the electric vehicle the drone should monitor using its monitoring device, so that the drone subsequently monitors this area using its monitoring device in accordance with the control signals. For example, the drone is specified by the control signals to monitor an area in the vicinity of the electric vehicle that, according to the electric vehicle's current route, lies in front of the electric vehicle in the direction of travel.

[0064] If it is known where the electric vehicle intends to go, the area ahead of the electric vehicle in the direction of travel of the current route can also be analyzed for possible charging stations, so that the monitoring data can be analyzed efficiently.

[0065] In one embodiment of the method, it is provided that environmental signals are received which represent the environment of the electric motor vehicle, wherein the control signals are generated based on the environmental signals and / or wherein the monitoring data are analyzed based on the environmental signals.

[0066] This results in the technical advantage, for example, that the control signals can be generated efficiently and / or that the monitoring data can be analyzed efficiently.

[0067] According to this embodiment, additional knowledge about the surroundings of the electric vehicle is available, which can be used together with the monitoring data to search for suitable charging stations and locate them accordingly. If additional knowledge about the surroundings of the electric vehicle is available, the drone can be advantageously controlled in an efficient manner so that it does not collide with infrastructure objects, for example. An infrastructure object is, for example, a building, a traffic light, a mast, or a traffic sign. Objects with which the drone could collide include, for example, vegetation, such as trees and / or bushes. Knowledge about such vegetation can, for example, also be represented by the environmental signals.

[0068] In one embodiment of the method, it is provided that the environmental signals comprise environmental signals sent by another motor vehicle which is located in front of the electric vehicle with respect to a direction of travel of the electric vehicle.

[0069] This provides, for example, the technical advantage that particularly suitable environmental signals can be used for generating the control signals and / or for analyzing the monitoring data. According to this embodiment, the additional knowledge about the surroundings of the electric vehicle is thus provided by another motor vehicle ("another motor vehicle" because the electric vehicle is also a motor vehicle), which detects its own surroundings using its own environmental sensor(s). Naturally, this own environment is encompassed by the surroundings of the electric vehicle, so that corresponding knowledge about the surroundings of the motor vehicle located in the direction of travel can be provided efficiently.

[0070] In one embodiment of the method, it is provided that the environmental signals comprise map signals which represent a digital map of the surroundings of the electric vehicle, which indicates a respective position of one or more charging stations.

[0071] This provides, for example, the technical advantage that particularly suitable environmental signals can be used to generate the control signals and / or analyze the monitoring data. According to this embodiment, a digital map of the surroundings of the electric vehicle is thus provided.

[0072] Environmental signals can include, for example, environmental signals sent from a cloud infrastructure. For example, a charging station control center is implemented in the cloud infrastructure and / or cloud data on charging stations is stored.

[0073] In one embodiment of the method, it is provided that the environmental signals comprise environmental signals sent by a traffic control center and / or by a charging station control center.

[0074] This results in the technical advantage, for example, that particularly suitable environmental signals can be used to generate the control signals and / or to analyze the monitoring data. According to this embodiment, the additional knowledge about the environment of the electric vehicle is therefore provided by a traffic control center, the charging station control center should always be read along. This center usually has current knowledge about the environment of the electric vehicle, which has not yet been entered into a digital map of the environment, for example. For example, the traffic control center knows the position of a newly installed charging station that is not yet shown on the digital map. For example, the traffic control center knows that a charging station that is shown on a digital map no longer exists or has changed its position. This knowledge is represented by the environmental signals.

[0075] In one embodiment of the method, it is provided that one, several or all method steps are carried out on the electric vehicle side and / or the infrastructure side and / or the drone side.

[0076] This results in the technical advantage, for example, that the individual process steps can be carried out efficiently.

[0077] In one embodiment of the method, it is provided that the method is only started when a current state of charge of a drive battery of the electric vehicle is reached, wherein the current state of charge is less than or equal to a predetermined state of charge threshold value, or wherein the method is started proactively independently of the current state of charge of the drive battery of the electric vehicle.

[0078] This results in the technical advantage, for example, that the process can be carried out efficiently.

[0079] The proactive embodiment, for example, has the advantage that a charging station can be searched for and found regardless of the current or instantaneous charge level. For example, it can be determined that there is currently, i.e., now, a suitable charging station that is free, i.e., unoccupied, whereby, based on a motor vehicle's route, the charging stations following the suitable charging station are likely to no longer be free. "Probable" means, for example, with a probability that is greater than or equal to a predetermined probability threshold. The proactive embodiment is particularly advantageous if the drive battery must be charged at least once before reaching the destination of the route.

[0080] If the method is only started when the current state of charge is less than or equal to the predetermined state of charge threshold, the resources required for the method, particularly computing resources, can be used efficiently. For example, the drone's energy storage unit can be used efficiently. This is because, for example, it is only started when the current state of charge is less than or equal to the predetermined state of charge threshold.

[0081] In one embodiment of the method, based on the analysis result, infrastructure assistance data for infrastructure-supported assistance of the electric vehicle (505) during an at least partially automated journey to a found charging station is determined and sent to the electric vehicle (505). Infrastructure assistance data include, for example, a recommended course of action for the electric vehicle and / or include, for example, remote control commands for remotely controlling lateral and / or longitudinal guidance of the electric vehicle. Infrastructure assistance data include, for example, the analysis result. Infrastructure assistance data include, for example, the determined charging station route from the starting position to the found charging station.

[0082] In one embodiment of the method, it is provided that, based on the analysis result, electric vehicle control signals for at least partially automated control of a lateral and / or longitudinal guidance of the electric vehicle are generated and output.

[0083] This results in the technical advantage, for example, that the electric vehicle control signals can be generated efficiently.

[0084] In one embodiment of the method, this comprises a step of controlling a transverse and / or longitudinal guidance of the electric vehicle based on the output electric vehicle control signals.

[0085] In one embodiment of the method, it is provided that the monitoring data and / or the analysis result are sent to a traffic control center and / or to a charging station center.

[0086] This provides the technical advantage, for example, that the traffic control center, the charging station center should always be monitored, is efficiently enabled to plan one or more actions based on the analysis result and / or based on the monitoring data and, for example, to control and / or coordinate them accordingly.

[0087] In one embodiment of the method, it is provided that the control signals, in particular the further control signals, are generated in such a way that when controlling the at least one drone based on the generated control signals, the monitoring of the surroundings comprises live monitoring of the surroundings of the electric motor vehicle, so that the monitoring data, in particular the further monitoring data, comprise live monitoring data.

[0088] This provides the technical advantage, for example, that the surroundings of the electric vehicle are efficiently monitored so that suitable charging stations can be found efficiently.

[0089] For example, live monitoring includes live monitoring of one or more charging stations and / or live monitoring of the respective charging station surroundings of one or more charging stations. The (further) control signals are thus such that the at least one drone monitors a found charging station and / or its surroundings using its monitoring device. (Further) live monitoring data thus represents, for example, a found charging station and / or its surroundings.

[0090] Warning characteristics and / or system characteristics result analogously from corresponding process characteristics and vice versa.

[0091] Statements made in connection with the method and / or the device and / or the system apply analogously to statements made in connection with the system and / or the device and / or the method and vice versa.

[0092] In one embodiment of the method, it is provided that the at least one drone is assigned to the electric vehicle. This means, for example, that the at least one drone belongs to the electric vehicle and is used or deployed by the electric vehicle. This means, for example, that the at least one drone is controlled by means of the electric vehicle. This means, in particular, that the control signals are generated and output by the electric vehicle. The electric vehicle sends the generated and output control signals wirelessly, for example to the at least one drone in order to control it. For example, the at least one drone accompanies the electric vehicle and flies ahead of the electric vehicle, for example with respect to the direction of travel of the electric vehicle.For example, the electric vehicle starts at least one drone when the current state of charge of the drive battery is less than or equal to the predetermined state of charge threshold.

[0093] In one embodiment of the method, it is provided that the at least one drone is assigned to an infrastructure. This means, for example, that the at least one drone belongs to the infrastructure. The at least one drone is, for example, assigned to a charging area comprising one or more charging stations, i.e., for example, a street with one or more charging stations or a parking lot with one or more charging stations. This means, for example, that the at least one drone waits at a charging area for its deployment and is then activated accordingly. The at least one drone can, for example, fly continuously and, for example, also be used for other tasks if it is not currently intended to be used for the method for finding a charging station according to the first aspect. The control of the at least one drone can, for example, be carried out on the infrastructure side, i.e., by the infrastructure.This means that the control signals are generated and output by the infrastructure. The infrastructure sends the output control signals, for example, wirelessly to at least one drone. A charging park management and / or drone system can be provided within the infrastructure to handle this control.

[0094] In the embodiment according to which the drone is assigned to the infrastructure, the control can alternatively or additionally also be carried out by the electric vehicle.

[0095] The control signals are generated, for example, using a digital map of the electric vehicle's surroundings. The control signals can be generated, for example, based on a current route of the electric vehicle. For example, the control signals for the at least one drone can be generated based on possible routes of the electric vehicle. This means that the control signals can be generated, for example, based on possible routes of the electric vehicle.

[0096] In one embodiment of the method, the control signals are generated such that the at least one drone flies along all possible routes of the electric vehicle in front of the electric vehicle, relative to the direction of travel of the electric vehicle, and monitors them accordingly using its monitoring device. This means that according to this embodiment, the at least one drone searches for all possible charging stations in the vicinity of the electric vehicle that are located in front of the electric vehicle in relation to the direction of travel, without, however, knowing the specific route or a specific destination of the electric vehicle.

[0097] In one embodiment of the method, known data about road areas, generally about the surroundings of the electric vehicle, is provided to or sent to the at least one drone. Such known data includes, for example, data about road width, the position of charging stations, and the position of signs. Typically, this data includes data about stationary objects, for example, the location of a charging station.

[0098] According to one embodiment, the data comprises dynamic data, i.e. information about whether, for example, such a charging station is occupied or free. The monitoring device can check whether the charging station is actually occupied or not. In general, this known data can be validated by the at least one drone by analyzing and evaluating the monitoring data accordingly. In one embodiment of the method, it is provided that data from one or more other motor vehicles, which are located in front of the electric vehicle, in particular with regard to the direction of travel of the electric vehicle, are also used. This data is represented, for example, by the environmental signals described here, which are sent by another motor vehicle.

[0099] In one embodiment of the method, it is provided that the drones are used for validating known data, for example from the digital map and / or from the environmental signals that represent an environment of the electric motor vehicle, wherein these environmental signals are sent, for example, by another motor vehicle that is located in front of the electric vehicle with respect to a direction of travel of the electric vehicle.

[0100] In one embodiment of the method, it is provided that the at least one drone is completely controlled by the electric vehicle and / or the infrastructure.

[0101] In one embodiment of the method, the at least one drone is a smart drone. This means that the at least one drone can autonomously monitor the surroundings of the electric vehicle. The at least one drone controls and operates itself.

[0102] In one embodiment of the method, it is provided that the at least one drone learns with each use, in particular using machine learning methods.

[0103] For example, a machine learning process checks whether a planned goal could be achieved in an earlier version of the process. One goal might be that the charging station found was accessible and / or offered sufficient space, i.e., sufficiently large. A machine learning process checks, for example, whether the dimensions of the electric vehicle and the determined dimensions of the charging station matched in an earlier version of the process—i.e., whether the electric vehicle's drive battery could charge at the found charging station at that time, or whether the electric vehicle would have required a larger charging station at that time.

[0104] For example, a machine learning process checks whether a planned target trajectory for driving to the charging station by the electric vehicle could be followed at least partially automatically. If not, an algorithm can be adapted to determine such a target trajectory.

[0105] For example, a machine learning process simulates the execution of the process.

[0106] For example, a machine learning method uses data from one or more other motor vehicles and / or drones to determine one or more optimal control parameters for the drone control, so that the control signals for the drone are generated based on the one or more optimal control parameters.

[0107] For example, a result or results of a machine learning procedure are used in a current execution of the procedure.

[0108] According to one embodiment, the method comprises performing a machine learning method.

[0109] One embodiment of the method allows for any combination of a dumb drone and a smart drone. This means that the at least one drone can be a smart drone, but is additionally monitored by the electric vehicle and / or infrastructure. Communication between a drone and an electric vehicle, for example, is direct communication. This means that data and / or signals can be exchanged directly between the at least one drone and the electric vehicle.

[0110] In one embodiment of the method, communication between the drone and the electric vehicle is indirect communication. This means that data and / or signals are transmitted between the at least one drone and the electric vehicle via an external system, for example, a cloud and / or backend system or a local charging station system and / or a road management and / or drone system.

[0111] A backend system, for example, includes a server system located in an operations center. This means, in particular, that the location of the server system in a backend is known. A cloud system, for example, includes a server system whose location is unknown.

[0112] Cloud is also a server system where the location may not be known.

[0113] In one embodiment of the method, communication between drones and electric vehicles and infrastructure is provided via a secure connection. This means, for example, that the communication can be secured using certificates, in particular, encrypted.

[0114] The at least one drone has, for example, a monitoring device comprising one or more environmental sensors. These environmental sensors are, for example, environmental sensors based on different sensor technologies. These environmental sensors are, for example, radar sensors, image sensors, and / or LiDAR sensors. Thus, in addition to images, other information, such as distances and dimensions, can be determined for objects. In particular, safety is increased when multiple environmental sensors are used for redundancy and different environmental sensors for diversity.

[0115] In one embodiment of the method, the (further) monitoring data and / or the (further) analysis result and / or, for example, infrastructure assistance data are sent to a traffic control center and / or road control center. Such centers can then, for example, plan further actions. Such further actions include, for example, traffic diversions and / or updating occupancy data for the charging station and / or reserving a charging station and / or controlling and / or initiating and / or coordinating the release of an occupied charging station.

[0116] Whenever one of the terms "road traffic control center," "road control center," and "traffic control center" or "traffic control center" is used, the other terms should always be read along with the other. These are used synonymously.

[0117] A charging station center manages one or more charging stations. The charging station center is specifically designed to manage one or more charging stations.

[0118] In one embodiment of the method, it is provided that the surroundings of the electric vehicle are monitored live by means of the monitoring device of the at least one drone.

[0119] In one embodiment of the method, it is provided that one, several or all method steps are documented, in particular documented in a blockchain.

[0120] The system according to the third aspect is configured, for example, to perform all steps of the method according to the first aspect. In one embodiment of the method according to the first aspect, it is provided that it is performed using the system according to the third aspect.

[0121] A drone as defined is an unmanned aerial vehicle.

[0122] A drone is, for example, a quadrocopter, a helicopter, an octocopter, a hexacopter, or generally a multicopter.

[0123] In one embodiment, it is provided that the method and / or the device and / or the system and / or the storage medium and / or the electric vehicle and / or the drone are safe.

[0124] In the context of this description, "Sicher" specifically means "safe" and "secure." While these two English terms are typically translated into German as "sicher," they have somewhat different meanings in English.

[0125] The term "safe" is specifically focused on accidents and accident prevention. "Safe" therefore means, in particular, that measures are taken to ensure the correct functioning of the device and / or system and / or storage medium and / or the execution of the procedural steps.

[0126] The term "secure" is specifically directed at computer security and hacker protection, meaning, in particular, how secure are the device and / or storage medium and / or system and its components against unauthorized access and data manipulation by third parties, so-called "hackers"? A "secure" method and / or storage medium and / or device and / or system therefore has appropriate and sufficient computer security and hacker protection, particularly as a basis for carrying out the method steps and for the functionality of the device and / or system.

[0127] For example, safe means that one or more safety conditions are met.

[0128] For example, it is provided that one, several or all components, for example the electric vehicle and / or the drone, which are involved in carrying out the method and / or which are comprised by the device and / or which are comprised by the system, and / or the storage medium are secure, i.e., for example, they meet one or more security conditions.

[0129] This will in particular provide the technical advantage that the system and / or the method and / or the device and / or the storage medium are safe within the meaning of the description, i.e. in particular safe within the meaning of the English terms "safe" and "secure".

[0130] In one embodiment, it is provided that the one or more safety conditions are each an element selected from the following group of safety conditions: Presence of a predetermined minimum ASIL and / or minimum SIL in at least one of the components, Presence of redundancy in at least one of the components, Presence of diversity in at least one of the components, Presence of at least one plan which includes measures for reducing errors and / or measures in the event of failures of at least one of the components and / or measures for error analysis and / or measures in the event of misinterpretations, Presence of one or more fallback scenarios.

[0131] This results in the technical advantage, for example, of providing particularly suitable safety conditions.

[0132] The abbreviation "ASIL" stands for "Automotive Safety Integrity Level." "Automotive Safety Integrity Level" is a key component of the ISO 26262 standard. ASIL distinguishes between four different ASIL risk levels, designated ASIL-A, ASIL-B, ASIL-C, and ASIL-D.

[0133] The abbreviation "SIL" stands for "Safety Integrity Level." "Safety Integrity Level" is a key component of the IEC EN 61508 standard. SIL distinguishes between four different SIL risk levels, designated SIL-1, SIL-2, SIL-3, and SIL-4.

[0134] In one embodiment of the method, it is provided that one, several or all steps of the method are only carried out if one or more safety conditions, in particular one or more of the above safety conditions, are met.

[0135] For example, the procedure is only carried out if one or more safety conditions are met.

[0136] In one embodiment of the method, it is provided that the electric vehicle is an at least partially automated electric vehicle.

[0137] The phrase "at least partially automated" encompasses one or more of the following cases: assisted, partially automated, highly automated, or fully automated. The phrase "at least partially automated" therefore encompasses one or more of the following: assisted, partially automated, highly automated, or fully automated.

[0138] Assisted driving means that the driver of an electric vehicle continuously performs either the lateral or longitudinal control of the electric vehicle. The other driving task (i.e., controlling the longitudinal or lateral control of the electric vehicle) is performed automatically. This means that with assisted driving of the electric vehicle, either the lateral or longitudinal control is controlled automatically.

[0139] Partially automated driving means that the longitudinal and lateral guidance of the electric vehicle is automatically controlled in a specific situation (for example, driving on a highway, driving within a parking space, overtaking an object, driving within a lane defined by lane markings) and / or for a specific period of time. The driver of the electric vehicle does not need to manually control the longitudinal and lateral guidance of the electric vehicle. However, the driver must continuously monitor the automatic control of the longitudinal and lateral guidance in order to intervene manually if necessary. The driver must be ready to fully assume control of the vehicle at any time.

[0140] Highly automated guidance means that for a certain period of time in a specific situation (e.g. driving on a motorway, driving within a parking lot, overtaking an object, driving within a lane defined by lane markings), the longitudinal and lateral guidance of the electric vehicle is automatically controlled. The driver of the electric vehicle does not have to manually control the longitudinal and lateral guidance of the electric vehicle. The driver does not have to constantly monitor the automatic control of the longitudinal and lateral guidance in order to intervene manually if necessary. If necessary, a takeover request is automatically issued to the driver to take over control of the longitudinal and lateral guidance, in particular with a sufficient time reserve. The driver must therefore potentially be able to take over control of the longitudinal and lateral guidance.Limits of the automatic control of lateral and longitudinal guidance are automatically detected. With highly automated guidance, it is not possible to automatically achieve a risk-minimal state in every initial situation. Fully automated guidance means that in a specific situation (for example, driving on a highway, driving within a parking lot, overtaking an object, driving within a lane defined by lane markings), the longitudinal and lateral guidance of the electric vehicle are automatically controlled. The driver of the electric vehicle does not have to manually control the longitudinal and lateral guidance of the electric vehicle. The driver does not have to monitor the automatic control of the longitudinal and lateral guidance in order to be able to intervene manually if necessary.Before the automatic control of lateral and longitudinal guidance is terminated, the driver is automatically prompted to take over the driving task (controlling the lateral and longitudinal guidance of the electric vehicle), particularly with sufficient time in reserve. If the driver does not take over the driving task, the system automatically returns to a risk-minimal state. Limits of the automatic control of lateral and longitudinal guidance are automatically detected. In all situations, it is possible to automatically return to a risk-minimal system state.

[0141] A drive battery, which can also be referred to as a high-voltage storage battery, traction battery or cycle battery, is in particular an accumulator which is primarily intended to supply the electric motor of the electric vehicle, which provides propulsion, with electrical energy.

[0142] The invention is explained in more detail below using preferred embodiments. These show:

[0143] Fig. 1 is a flowchart of a method according to the first aspect,

[0144] Fig. 2 shows a device according to the second aspect,

[0145] Fig. 3 shows a system according to the third aspect, Fig. 4 shows a machine-readable storage medium according to the fifth aspect and

[0146] Fig. 5 shows an exemplary application of the method according to the first aspect.

[0147] In the following, the same reference symbols may be used for the same features.

[0148] Fig. 1 shows a flowchart of a method for finding a charging station for electric vehicles using at least one drone having a monitoring device, comprising the following steps:

[0149] Generating 101 control signals for controlling the at least one drone such that, when controlling the drone based on the generated control signals, the at least one drone monitors an environment of an electric motor vehicle by means of its monitoring device and outputs monitoring data based on the monitoring, outputting 103 the generated control signals in order to control the at least one drone based on the generated control signals, after outputting the generated control signals, receiving 105 the monitoring data from the at least one drone, analyzing 107 the monitoring data in order to find a charging station for electric vehicles, and

[0150] Output 109 an analysis result of the analysis of the monitoring data.

[0151] Fig. 2 shows a device 201. The device 201 is configured to perform all steps of the method according to the first aspect.

[0152] According to an embodiment not shown, the device 201 comprises an input which is configured to receive the signals and / or data described in the description. According to an embodiment not shown, the device 201 comprises one or more processors which are configured to carry out the steps of (further) analyzing and / or processing and / or determining described in the description. According to an embodiment not shown, the device 201 comprises an output which is configured to output the signals and / or data described in the description. For example, the device 201 comprises the input, the processor(s), and the output. The input comprises, for example, a wireless communication interface. The output comprises, for example, a wireless communication interface. For example, the input and output are identical.For example, the device 201 comprises a wireless communication interface for bidirectional communication, i.e. for receiving and transmitting the signals and / or data described in the description.

[0153] The device 201 may, for example, be implemented in a drone used for the method according to the first aspect.

[0154] Fig. 3 shows a system 301 for finding a charging station for electric vehicles.

[0155] The system 301 includes the device 201 according to Fig. 2.

[0156] The system 301 comprises a drone 303. The drone 303 comprises a monitoring device 305. The monitoring device 305 comprises a first video camera 307 and a second video camera 309, each of which comprises an image sensor (not shown) as an environment sensor.

[0157] In an embodiment not shown, the monitoring device 305 comprises further environmental sensors in addition to or instead of one or both video cameras 307, 309.

[0158] In an embodiment not shown, system 301 comprises a plurality of drones, which are, for example, identical or, for example, differently configured. Fig. 4 shows a machine-readable storage medium 401 on which a computer program 403 is stored. The computer program 403 comprises instructions that, when executed by a computer, cause the computer program 403 to execute a method according to the first aspect.

[0159] Fig. 5 shows an intersection 501, according to which a first street 503 and a second street 505 intersect. The first street 503 runs horizontally relative to the plane of the paper. The second street 505 runs vertically relative to the plane of the paper. Below the intersection 501, a third street 507 branches off from the second street 505 as a cross street.

[0160] An electric vehicle 509 comprising a drive battery 510 for an electric motor (not shown) of the electric vehicle 509 travels on the first road 503 in the direction of travel 511 toward the intersection 501. The direction of travel 511 of the electric vehicle 509 runs from left to right relative to the plane of the paper.

[0161] A first loading area 513, a second loading area 515, and a third loading area 517 are provided. The first loading area 513 is located above intersection 501, to the right of the second street 505. The second loading area 515 is located above intersection 501 and to the right of intersection 501 on the first street 503. The third loading area 517 is located below intersection 501 on the third street 507.

[0162] The three charging areas 513, 515, and 517 each comprise three parking spaces 519, where motor vehicles, in particular electric vehicles, can be parked. Each of the parking spaces 519 has its own charging station 521 for electric vehicles, at which a drive battery of an electric vehicle can be charged.

[0163] Some additional motor vehicles 522 are parked in parking spaces 519. Specifically, for the first loading area 513, another motor vehicle 522 is parked in the upper parking space 519, and another motor vehicle 522 is parked in the lower parking space 519. The middle parking space 519 is unoccupied.

[0164] For the second loading area 515, another motor vehicle 522 is parked on the left and middle parking spaces 519 in such a way that this additional motor vehicle 522 blocks both parking spaces 519. Furthermore, another motor vehicle 522 is parked on the right parking space 519 of the second loading area 515.

[0165] For the third loading area 517, another motor vehicle 522 is parked on each of the parking spaces 519.

[0166] A first drone 523, a second drone 525, and a third drone 527 are provided. The three drones 523, 525, and 527 each comprise a monitoring device 529, each of which comprises a video camera 531 and each has an image sensor 533.

[0167] Furthermore, a device 535 is provided, which is configured to carry out all steps of the method according to the first aspect. The device 535 comprises a wireless communication interface 537 and comprises a processor device 539, which may, for example, have one or more processors.

[0168] According to the concept described here, the three drones 523, 525, 527 are used to search for unoccupied parking spaces 519 in the loading areas 513, 515, 517 using their monitoring device 529. For example, the drones 523, 525, 527 can be used to determine and / or validate the occupancy status of the parking spaces 519.

[0169] For this purpose, it is provided that, for example, the drones 523, 525, 527 are controlled by means of the device 535. The processor device 539 generates, for example, the control signals. The control signals are sent wirelessly to the drones 523, 525, 527 via the wireless communication interface 537, which can comprise, for example, a WLAN communication interface and / or a mobile radio interface.

[0170] The drones 523, 525, 527, for example, fly over the loading areas 513, 515, 517 and can monitor the loading areas 513, 515, 517 using their respective monitoring device 520. Specifically, the video cameras 531 record video images of the loading areas 513, 515, 517, which can be sent, for example, to the device 535. These video images are, for example, monitoring data within the meaning of the description or are included therein. These video images are sent wirelessly to the device 535, which receives them via the wireless communication interface 537.

[0171] The processor device 539 analyzes the video images in order to, for example, determine and / or validate a respective occupancy status of the parking spaces 519.

[0172] Thus, for example, an analysis result is available that indicates the respective occupancy status of the parking spaces 519. This analysis result can be output via the wireless communication interface 537, in particular sent to the electric vehicle 509. The electric vehicle 509 can, for example, be an at least partially automated electric vehicle that can, for example, plan an at least partially automated journey based on the analysis result. For example, the electric vehicle 509 can select the first charging area 513 from the three charging areas 513, 515, 517 as the charging area to which the electric vehicle 509 will drive at least partially automatically, provided that this still has a free parking space 519 at whose charging station 521 the drive battery 510 of the electric vehicle 509 can be charged.In an embodiment not shown, it can be provided that at least one of the drones 523, 525, 527 or all of the drones 523, 525, 527 is or are controlled by means of the electric vehicle 509.

[0173] In an embodiment not shown, it is provided, for example, that instead of the drones 523, 525, 527, more or fewer drones are provided, for example only one drone.

Claims

Claims 1. Method for locating a charging station (521) for electric motor vehicles (509) using at least one drone (303, 523, 525, 527) having a monitoring device (305, 529), comprising the following steps: Generating (101) control signals for controlling the at least one drone (303, 523, 525, 527) such that when the drone (303, 523, 525, 527) is controlled based on the generated control signals, the at least one drone (303, 523, 525, 527) monitors the environment of an electric motor vehicle (509) by means of its monitoring device ((305, 529)) and outputs monitoring data based on the monitoring, Output (103) of the generated control signals to control the at least one drone (303, 523, 525, 527) based on the generated control signals, after outputting the generated control signals receiving (105) the monitoring data from the at least one drone (303, 523, 525, 527), Analyzing (107) the monitoring data to locate a charging station (521) for electric vehicles (509), and Output (109) of an analysis result of the analysis of the monitoring data.

2. Method according to claim 1, wherein dimensional signals are received which represent one or more dimensions of the electric vehicle (505), wherein the monitoring data are analyzed based on the dimensional signals, wherein the analysis comprises checking a detected charging station (521) to determine whether a traction battery of the electric vehicle (509) due to its dimensions or dimensions, it can be charged in the charging station (521) found.

3. Method according to claim 1 or 2, wherein the analysis comprises checking that a charging station (521) found is accessible to the electric vehicle (509).

4. Method according to one of the preceding claims, wherein the analysis comprises determining the occupancy status of a found charging station (521).

5. Method according to one of the preceding claims, wherein the analysis comprises determining the position of a charging station (521) located within a defined area.

6. A method according to one of the preceding claims, wherein, upon an analysis result indicating that a charging station (521) for the motor vehicle has been found, further control signals for controlling the at least one drone (303, 523, 525, 527) are generated such that, upon further control of the drone (303, 523, 525, 527), based on the generated further control signals, the at least one drone (303, 523, 525, 527) monitors the located charging station (521) by means of its monitoring device (305, 529) and outputs further monitoring data based on the monitoring, wherein the generated further control signals are output in order to further control the at least one drone (303, 523, 525, 527) based on the generated further control signals, wherein, after the output of the further control signals, the further monitoring data are received, wherein the further Monitoring data is analyzed to determine a further analysis result, which is then output.

7. Method according to any of the preceding claims, wherein charging station route signals are generated which define a charging station route from a starting position to a found charging station (511) for the Represent electric vehicle (509) and output the generated charging station route signals.

8. Method according to one of the preceding claims, wherein the analysis comprises determining the optimal charging station (511) from among several charging stations (521) found.

9. Method according to any of the preceding claims, wherein route signals are received which represent an instantaneous route of the electric vehicle (509) on which the electric vehicle (509) is currently driving, wherein the control signals are generated based on the route signals and / or wherein the monitoring data are analyzed based on the route signals.

10. Method according to any of the preceding claims, wherein environmental signals are received which represent the environment of the electric motor vehicle (509), wherein the control signals are generated based on the environmental signals and / or wherein the monitoring data are analyzed based on the environmental signals.

11. Method according to claim 10, wherein the environmental signals comprise environmental signals transmitted by a further motor vehicle (522) which is located in front of the electric motor vehicle (509) with respect to a direction of travel of the electric motor vehicle (509).

12. Method according to claim 10 or 11, wherein the environmental signals comprise map signals representing a digital map of the environment of the electric vehicle (509), which indicates a respective position of one or more charging stations.

13. Method according to one of claims 10 to 12, wherein the environmental signals comprise environmental signals sent from a traffic control center and / or from a charging station control center.

14. Method according to one of the preceding claims, wherein one, several or all method steps are carried out on the electric vehicle side and / or on the infrastructure side and / or on the drone side.

15. Method according to one of the preceding claims, wherein the method is only started when there is an instantaneous state of charge of a traction battery of the electric vehicle (509), wherein the instantaneous state of charge is less than or less than or equal to a predetermined state of charge threshold, or wherein the method is started proactively regardless of the instantaneous state of charge of the traction battery of the electric vehicle (509).

16. Method according to one of the preceding claims, wherein, based on the analysis result, infrastructure assistance data for infrastructure-supported assistance of the electric vehicle (509) during an at least partially automated journey to a found charging station (521) are determined and sent to the electric vehicle (509).

17. Method according to one of the preceding claims, wherein, based on the analysis result, electric vehicle control signals are generated and output for at least partially automated control of a lateral and / or longitudinal guidance of the electric vehicle (509).

18. Method according to one of the preceding claims, wherein the monitoring data and / or the analysis result are sent to a traffic control center and / or a charging station control center.

19. Method according to one of the preceding claims, wherein the control signals, in particular the further control signals, are generated such that when controlling the at least one drone (303, 523, 525, 527) based on the generated control signals, monitoring the environment includes live monitoring of the environment of the electric vehicle (509), such that the monitoring data, in particular the further monitoring data, includes live monitoring data.

20. Method according to one of the preceding claims, wherein one, several or all steps of the method are carried out only if one or more safety conditions are met.

21. Device (201, 535) configured to perform all steps of the method according to any of the preceding claims.

22. System (301) for finding a charging station (521) for electric motor vehicles (509), comprising: at least one drone (303, 523, 525, 527), wherein the at least one drone (303, 523, 525, 527) has a monitoring device (305, 515), and the device (201, 535) according to claim 21.

23. Computer program (403) comprising instructions which, when the computer program (403) is executed by a computer, cause it to execute a method according to any one of claims 1 to 20.

24. Machine-readable storage medium (401) on which the computer program (403) according to claim 23 is stored.

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