Sensor-based detection of a sliding feed line of an

Abstract

The invention relates to a method for sensor-based detection of a contact line (3) of an overhead line (20). In the method, at least two-dimensional sensor data (SDP, SPD) is acquired by sensor-based mapping of a sub-region of the surroundings of the vehicle (1) that can be supplied with energy by means of the overhead line (20), in which sub-region the overhead line (20) is expected to be located. Furthermore, on the basis of the sensor data (SDP, SPD) and on the basis of a geometric model (PM) of the overhead line (20), an expected position (PS) of the trolley feeder (3) and of the sling (11) of the overhead line (20) is estimated. Furthermore, a verification result (VE) of the estimation is determined by checking the consistency of the geometric model (PM) and checking the consistency of the sensor data (SDP, SPD) with the geometric model (PM). Finally, the position (P) of the slip feed (3) is determined on the basis of the estimation and the verification result (VE). A detection device (70) is also described. Furthermore, a vehicle (1) is described.

Description

Technical Field

[0001] The invention relates to a method for sensor-based detection of a trolley feeder of an overhead line. The invention also relates to a detection device. The invention also relates to a vehicle. Background Art

[0002] The electrical operation of vehicles with large payloads over long distances using only batteries or accumulators is difficult to achieve because, for the foreseeable future, the energy density of batteries will remain too low for the amount of energy required for such missions.

[0003] Therefore, in addition to transporting such loads by rail, there are also options for equipping long-distance highways with a power grid with overhead lines and supplying electrical vehicles, particularly trucks, with electricity from outside via these lines. This approach is already being implemented, for example, in eHighway projects such as ENUBA, ELISA2, and FESH. Figure 1 A heavy-duty truck (LKW) is shown with a pantograph for energy supply via an overhead line.

[0004] Unlike rail vehicles, road vehicles with a pantograph, i.e. a pantograph, for supplying energy via an overhead line can determine their own direction of travel and, for example, change lanes or stop at the roadside. It must be noted that the pantograph can only be extended or maintained in contact with the trolley feeder of the overhead line when the road vehicle is also in the appropriate position below such an overhead line. In order to avoid damage to the overhead line, when changing lanes, the pantograph must first be released from its contact position with the overhead line and lowered, also known as "unhooking". Lanes are then changed. Afterwards, the pantograph must be moved back to its contact position with the overhead line above the new lane, also known as "hooking". In order to perform the hooking and unhooking operations at the correct time, the relative position of the relevant overhead line with respect to the vehicle must be known. In particular, it should also be prevented from extending the pantograph upwards when there is a very large offset between the vehicle and the overhead line.

[0005] Unlike in railway operations, overhead lines for DC grids for road vehicles typically consist of two live trolley wires, which are located at a largely constant distance from one another, parallel to one another within a defined altitude range, and at the same height. Road vehicles draw power from the DC grid via pantographs. To maintain a nearly constant distance from the ground, these trolley wires are tensioned using suspension cables. The suspension cables run in a hyperbolic pattern in the vertical direction. Figure 2A side view of an overhead line with a feeder cable and a cable is shown. The cable is tensioned laterally at the curve. This arrangement results in the overhead line forming four points, representing the corners of a parallelogram, in a frontal cross-sectional view. The two upper points are associated with the cable, and the two lower points are associated with the feeder cable. Because object detection radar can theoretically detect the feeder cable and cable at any time due to diffraction effects, the corners of this parallelogram can also be found during radar measurements.

[0006] However, when radar sensors are used to detect overhead lines, there is a problem: it is impossible to detect both trolley wires and both suspension cables simultaneously at any given time; only a portion of them can always be detected. Trolley wires are more difficult to detect than suspension cables. This difference in detectability is related to the fact that trolley wires are very smooth, while suspension cables are braided. Another reason for this difference in detectability is that trolley wires are closer to the sensors used to monitor the vehicle's surroundings. Therefore, interfering near-field effects already occur when detecting trolley wires. These interfering near-field effects are less pronounced when detecting suspension cables, which are located further away from the vehicle's sensors. Summary of the Invention

[0007] In other words, the technical problem to be solved is to enable reliable and robust sensor-based detection, in particular localization, of the overhead line's trolley supply lines from a vehicle supplied with power via the latter.

[0008] This object is achieved by a method for sensor-based detection of a trolley feeder of an overhead line according to claim 1 , a detection device according to claim 12 , and a vehicle according to claim 13 .

[0009] In the method according to the invention for sensor-based detection of a trolley feeder of an overhead line, at least two-dimensional sensor data is acquired by performing sensor-based mapping of the overhead line. As already mentioned, the trolley feeder carries electrical power, which an electrified vehicle can draw by contacting the trolley feeder with a pantograph. It should be explicitly mentioned that when a trolley feeder or a cable is mentioned in this application, both a singular trolley feeder and a singular cable as well as a plural trolley feeder and a plural cable should always be included, as should the combination of one trolley feeder with multiple cables and the combination of multiple trolley feeders with one cable. Conversely, when multiple trolley feeders and multiple cables are mentioned, in any case, when the description of the features specific to these components in the plural does not exclude the selection of these components in the singular, these components in the singular should generally not be excluded. It is particularly preferred, but not limited to, to apply the method according to the invention to the detection of two trolley feeders and two cables of an overhead line. It should also be mentioned here that the method according to the invention is preferably used with road vehicles and overhead line systems of DC grids, but other operating modes, such as energy supply with AC power or multiphase power, in particular three-phase power, are also included.

[0010] Sensor data is acquired in or from a portion of the vehicle's surroundings that can be supplied with energy via overhead lines. The portion is selected so that, based on prior information, the overhead lines are expected to be located there. This information may include the vehicle's posture and trajectory, as well as prior information regarding the arrangement and orientation of the overhead lines within the area being traveled. This information may also be continuously updated, for example, through vehicle self-positioning. In particular, it is known that the overhead lines are always located above the vehicle. Furthermore, the search for overhead lines focuses only on the portion above and in front of the pantograph, so detection can be limited to these portions of the surroundings. Throughout this application, it will be assumed that the acquisition of sensor data for components used to locate the overhead lines is performed quickly, such that the vehicle's position relative to the overhead lines does not change significantly during the time required for acquisition. This applies to at least one set of such sensor data. However, it is entirely advantageous and desirable to acquire a set of sensor data at different points in time to track changes in the relative position of the vehicle relative to the overhead lines or one or more trolley feeders of the overhead lines over time, and to periodically update the position data of the one or more trolley feeders relative to the vehicle.

[0011] Furthermore, the expected positions of the trolleys and suspension cables of the overhead line are estimated based on the acquired sensor data and on the basis of a geometric model of the overhead line. A geometric model is to be understood as a parameterizable virtual geometric object that represents the geometric properties of the overhead line or a mapping thereof. The expected position includes the relative position of the pantograph relative to the vehicle. As will be explained in detail later, for an overhead line having at least three components, i.e., trolley cables and suspension cables, a polygon is suitable as the geometric model, and in the case of four components, in particular two trolley cables and two suspension cables, a parameterized parallelogram is particularly preferably suitable as the geometric model.

[0012] Furthermore, the result of the estimation verification is determined by checking the consistency of the geometric model and the acquired sensor data with the geometric model. The consistency of the geometric model is checked using prior knowledge of the value ranges within which specific model parameter values ​​of the geometric model should lie. The geometry of the arrangement of the trolley feeder and the cable, or of a plurality of trolley feeders and a plurality of cables relative to one another, is generally known. To check the consistency of the sensor data with the geometric model, the proportion of sensor data that is consistent with the geometric model is checked. The more sensor data points that are determined to be "on the geometric model" based on the sensor data, the higher the consistency of the sensor data with the geometric model.

[0013] The position of the trolley feeder is determined based on the estimate or the estimated parameterized geometric model and the verification results.

[0014] Finally, the determined position of the trolley feeder and the associated verification result are output. If the verification result classifies the determined position as not valid enough, the output of the determined position can also be stopped and further processing can be carried out, for example, using the position data of the trolley feeder previously determined. The position data can be used to control the hooking of the pantograph to the trolley feeder of the overhead line. It is important here that the conductive bars of the pantograph correctly hit the trolley feeder during the hooking. Robust positioning of the trolley feeder or, if necessary, a plurality of trolley feeders is advantageously achieved, wherein information about the reliability of the result is also added to the result of the method so that this information can be advantageously taken into account when the result is further processed. The model-based method according to the invention takes into account, in particular, the problem that the sensor-based acquisition of the trolley feeder is generally incomplete, so that positioning based solely on sensor data is often difficult and uncertain. This problem is solved by using a geometric model and incorporating the sling into this geometric model.

[0015] The detection device according to the present invention comprises a sensor unit for acquiring at least two-dimensional sensor data by performing sensor-based mapping of a subregion of the surroundings of a vehicle that can be supplied with energy via an overhead line. The subregion is selected as the subregion of the surroundings in which the overhead line is expected to be located based on previously known information.

[0016] The detection device according to the invention further comprises an estimation unit for estimating the expected positions of the trolley feeders and the suspension cables of the overhead line based on the sensor data and on a geometrical model of the overhead line.

[0017] As will be explained in greater detail below, the estimation unit is preferably configured to determine model parameter values ​​of the geometric model based on the sensor data and to associate sensor data that are consistent with the parameterized geometric model with the parameterized geometric model.

[0018] Furthermore, the detection device according to the present invention has a verification unit for determining a verification result of the estimation by checking the consistency of the geometric model and checking the consistency of the acquired sensor data with the geometric model.

[0019] As will be explained in more detail later, the geometric model itself is preferably checked for consistency by comparing the determined model parameter values ​​with reference data, and the acquired sensor data is checked for consistency with the geometric model based on the degree of match between the sensor data and the geometric model parameterized using the model parameter values.

[0020] Furthermore, the detection device according to the invention has a positioning unit for determining the position of the trolley feeder based on the estimation and verification results. The detection device according to the invention shares the advantages of the method according to the invention for sensor-based detection of trolley feeders of overhead lines.

[0021] The vehicle according to the invention, preferably an electric road vehicle, has a pantograph for contacting a trolley feeder of an overhead line of an electrical energy supply network, a traction unit for driving the vehicle using electrical energy drawn from the electrical energy supply network via the pantograph, and a detection device according to the invention, the vehicle according to the invention sharing the advantages of the detection device according to the invention.

[0022] Some of the aforementioned components of the detection device according to the present invention can be implemented completely or partially as software modules in a processor of a corresponding computing system, for example, in a control unit of a vehicle, particularly a road vehicle, or in an existing computing system. Implementing the system in software, if possible, has the advantage that previously used computing systems can be easily retrofitted to operate in accordance with the present invention via a software update. In this regard, the aforementioned technical problem is also solved by a corresponding computer program product having a computer program that can be directly loaded into a computing system and includes program segments for executing the following steps of the method according to the present invention when the program is executed in the computing system: estimating the expected position of the overhead line feeder and the suspension cable, determining a result of the estimation, and determining the position of the feeder based on the estimation and the verification result. In addition to the computer program, such a computer program product may also include additional components, such as documentation, and / or additional components, as well as hardware components for using the software, such as a hardware key (dongle, etc.).

[0023] For transmission to a computing system and / or for storage on or in a computing system, a computer-readable medium, such as a memory stick, a hard disk, or other removable or permanently mounted data carrier, on which program segments of a computer program are stored that are readable and executable by a computing system, can be used. For this purpose, the computing system can include, for example, one or more cooperating microprocessors.

[0024] The dependent claims and the following description accordingly contain particularly advantageous embodiments and developments of the invention. In particular, claims from one claim category can also be developed similarly to dependent claims from another claim category and their descriptions. Furthermore, within the scope of the invention, various features of different embodiments and claims can also be combined to form new embodiments.

[0025] In a particularly preferred variant of the method according to the invention, in the step of estimating the expected position of the trolley feeder and the suspension cable of the overhead line, model parameter values ​​of a geometric model are preferably determined based on the acquired sensor data, and the sensor data that corresponds to the geometric model parameterized by the model parameter values ​​are preferably associated with the parameterized geometric model. Advantageously, by determining the model parameter values, existing a priori knowledge about the relative arrangement of the trolley feeder and the suspension cable is combined with the currently determined information about the vehicle's surroundings from the sensor data, thereby making it available for later checking and verification.

[0026] It is also particularly preferred that, when determining the verification result, a consistency check between the geometric model and the model parameter values ​​is performed by comparing the model parameter values ​​of the determined geometric model with the reference data. It is also preferred that, in the process of determining the verification result, a consistency check between the geometric model and the sensor data is performed based on the degree of matching between the sensor data and the geometric model parameterized by the model parameter values. The reference data particularly includes information about the ranges within which the model parameter values ​​should lie. In addition, it is determined how many of the sensor data or sensor data points are located on the geometric object spanned by the geometric model or are consistent with the geometric object. By means of these consistency checks, unreliable estimation results caused by gross measurement errors can advantageously be classified accordingly. That is, these unreliable estimation results are either eliminated or given a lower weight in subsequent evaluations or further processing.

[0027] In a preferred variant of the method according to the invention, the geometric model comprises one of the following model types:

[0028] - 2D geometric models,

[0029] - 3D geometric models.

[0030] The two-dimensional geometric model is characterized by its particular simplicity. Since, when positioning one or more trolley feeders of the overhead line, one is usually only interested in their height difference relative to the vehicle's pantograph, and in particular their lateral offset relative to the vehicle's pantograph, two-dimensional information is usually sufficient to coordinate the movement of the vehicle and its pantograph with the position of the one or more trolley feeders of the overhead line.

[0031] The 3D geometric model enables the use of a large amount of sensor data, particularly distributed along the path of the trolley line, to parameterize the geometric model. Furthermore, the 3D geometric model enables the inclusion of the 3D course of the trolley feeders and suspension cables of the trolley line into the model.

[0032] It is particularly preferred that the sensor data acquired in the first step of the method according to the invention include one of the following data types:

[0033] - Actively collected sensor point data,

[0034] - Passively collected image data.

[0035] Actively acquired sensor point data enables three-dimensional scanning of objects. This sensor point data can be acquired by actively scanning sensors, particularly radar sensors, lidar sensors, or infrared sensors, which scan their surroundings using a sensor beam. Active sensors operate independently of time and visibility conditions. However, interference can occur, necessitating the selection of an appropriate frequency range or wavelength, or the implementation of other interference suppression measures.

[0036] Passively acquired image data is obtained by passive sensors, which image the detected object using the incidence of beams or waves emitted by an external source that are reflected on the detected object. Such passive sensors include, in particular, stereo cameras for obtaining stereo image data. Passive sensors are technically simpler than active sensors, but their functionality, accuracy, and reliability are often affected by changing boundary conditions, such as line of sight.

[0037] It is particularly preferred that the sensor data acquired in the first step of the method according to the present invention include sensor point data, and the expected positions of the trolleys and suspension cables of the overhead line are estimated by performing a density analysis on the sensor point data. The sensor point data are acquired by scanning the environment in a grid format using active sensors. The sensor point data can advantageously be used to create a three-dimensional image of the scanned environment. The density of the scanned points in the sensor point data can be used as an indicator of the presence of trolleys or suspension cables, wherein, when these points are projected onto a vertical elevation plane, clusters are expected to appear at the penetration points, preferably four penetration points, of the trolleys and suspension cables through the plane. The density analysis therefore involves determining the largest cluster of sensor point data, which is then used to identify the trolleys and suspension cables.

[0038] However, in most cases, all the overhead line cables and feeders are not detected at the same time, and the sensor point data in the plane is usually incomplete. To compensate for this incompleteness, the proposed geometric model is used to replace the missing sensor data points with the geometric model.

[0039] If the overhead line includes at least three components, namely, a trolley and a suspension cable, then in such a geometric model, particularly in a front view of the overhead line, the clustered regions of sensor data points can be interpreted as corners of a polygon. In other words, it is particularly preferred that the geometric model include polygons, and the estimated positions of the trolleys and suspension cables of the overhead line are estimated by determining the geometric properties of a polygon spanned by the expected positions of the trolleys based on the aforementioned cluster of corner points of the polygon, checking the geometric properties of the polygon by comparing the determined geometric properties with reference data, and correcting the estimated polygon if necessary based on the comparison. The additional information used as reference data is advantageously used to check the plausibility of the measurement data, particularly the sensor data, and their interpretation, and to correct the geometric model if necessary, thereby achieving an increased plausibility of the geometric model.

[0040] Particularly preferably, determining the verification result includes determining an estimated confidence value based on a comparison of the geometric properties of the corrected polygon with reference data and based on the number of sensor data points that can be associated with the corrected polygon, and determining the position of the trolley feeder based on the determined confidence value. To enable appropriate processing of the obtained information, a measure of the reliability of the measurement data or sensor point data that may have uncertainty and the geometric model derived therefrom is advantageously determined. If there is insufficient confidence, the sensor point data may be discarded or weighted less heavily in determining the position of the trolley feeder than sensor point data with a higher confidence value.

[0041] Particularly preferably, the geometric properties checked include the lengths of the sides of the spanned polygon and / or the angles between the sides. Advantageously, based on the properties determined in this way, the parameterized geometric model can be checked for consistency using known properties of the polygon. For example, parameters of the geometric model can be associated with certain value ranges, within which the parameter values ​​must lie.

[0042] In one embodiment of the method according to the present invention, correcting the estimate includes supplementing sensor data points and / or searching for additional polygons spanned by the sensor data points of the sensor point data. Correction after the first estimate can advantageously be performed to compensate for measurement errors or errors in the density analysis.

[0043] In one embodiment of the method according to the invention, if a polygon cannot be determined, the current (relative) position of the overhead line's trolley feeders and cables relative to the vehicle is estimated based on the sensor data points and the temporally previously determined positions of the trolley feeders and cables of the overhead line. Alternatively, or in combination with the measures described above, the current (relative) position of the overhead line's trolley feeders and cables relative to the vehicle is preferably determined based on time-dependent tracking of their positions in conjunction with a kinematic model. Such a kinematic model allows for the extrapolation of past position data to the present, thus enabling the current position of the cables and trolley feeders to be estimated based on their past positions.

[0044] In the method according to the invention, it is particularly preferred that the determined position of the trolley line of the overhead line is output at the end together with the determined confidence value. The information about the reliability of the output information advantageously allows an assessment of the value and reliability of the obtained result, which can be taken into account during the further processing of the obtained information about the position of the trolley line. Preferably, during the further processing of the results, the obtained results are weighted or weighted averaged over time, depending on the determined validity and reliability of the individual results.

[0045] In the method according to the invention, it is particularly preferred that the polygon or the parameterizable geometric model comprises one of the following types of polygons:

[0046] - triangle,

[0047] - quadrilateral,

[0048] - Trapezoidal,

[0049] - Parallelogram.

[0050] The selection of a suitable model can advantageously depend on the number of trolley wires and suspension cables and their relative position and orientation. A particularly common method is to approximate the front cross-section of an overhead line having two suspension cables and two trolley wires with a parallelogram, wherein the corners of the parallelogram are approximated by the two trolley wires and the two suspension cables.

[0051] If the sensor unit of the detection device according to the invention is constructed as an active sensor unit, it is particularly preferred that the detection device includes a sensor unit for acquiring at least two-dimensional sensor point data by performing a sensor-based scan of a partial area of ​​the surroundings of a vehicle that can be supplied with energy via an overhead line, in which partial area the overhead line is expected to be located.

[0052] Furthermore, it is preferred that the detection device according to the present invention comprises an estimation unit for estimating the expected positions of the trolley feeders and the suspension cables of the overhead line by performing a density analysis on the sensor point data.

[0053] It is also preferred that the detection device according to the invention comprises a cluster determination unit which is configured to determine clusters of sensor data points in the sensor point data, preferably based on a RANSAC method, and to select the largest cluster as a corner point of the geometric model.

[0054] Furthermore, a model unit is preferably part of the detection device according to the invention, which is used to determine the geometric properties of a geometric model, preferably a polygon, spanned by the expected positions of the trolley feeder. Advantageously, by determining the values ​​of the model parameters of the geometric model, existing a priori knowledge about the relative arrangement of the trolley feeder and the suspension cable is combined with the currently determined information from the sensor data about the vehicle's surroundings, thereby making it available for later checking and verification.

[0055] Furthermore, the detection device according to the invention preferably comprises a comparison unit for comparing the determined geometrical properties of the geometrical model, preferably of the polygon, with reference data. The reference data particularly include information about the ranges within which the values ​​of the model parameters of the geometrical model should lie.

[0056] Furthermore, the detection device according to the invention preferably comprises a correction unit configured to correct the geometry of the geometric model, preferably a polygon. The correction is preferably performed by supplementing the corner points of the objects of the geometric model or, alternatively, by determining new objects of the geometric model based on further aggregation of the sensor data points.

[0057] The detection device according to the present invention also preferably includes an extrapolation unit configured to determine currently measured sensor data points that can be used for the current geometric model based on the geometric model at a previous point in time. Advantageously, past position data of the trolley feeder and sling can be used to estimate the current position of the trolley feeder and sling. This approach is useful when it is not possible to generate a geometric model based solely on the current sensor data. For example, by tentatively translating the past geometric model, currently measured sensor data points can be identified that lie on the translated geometric model.

[0058] The detection device according to the invention also preferably includes a tracking unit that calculates a current geometric model based on the recorded past course or position of the overhead line and based on a motion model of the vehicle. Advantageously, the past position data of the trolley wires and the suspension cables can also be used to determine the current position of the trolley wires and the suspension cables of the overhead line, taking into account changes in the vehicle's position since the receipt of the past sensor data.

[0059] If the detection device according to the invention acquires sensor point data of the surrounding environment, the verification unit of the detection device according to the invention is constructed to determine an estimated confidence value based on a comparison of geometric properties of a geometric model with reference data and based on the sensor point data associated with the geometric model or the number of sensor data points of the sensor point data.

[0060] If the geometric model includes a polygon, an estimated confidence value is determined based on a comparison of geometric properties of the corrected polygon with reference data and based on a number of sensor data points associated with the corrected polygon.

[0061] In this variant, the positioning unit of the detection device according to the invention is preferably designed to determine the position of the overhead line based on a determined confidence value. The determined confidence value can advantageously be taken into account during further processing of the position data, for example by discarding the position data or weighting the position data in relation to the confidence value.

[0062] In a variant of the detection device according to the invention, the detection device according to the invention further comprises an output unit or an output interface for outputting the determined position of the overhead line together with the determined confidence value. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Hereinafter, the present invention will be described in detail again with reference to the accompanying drawings using embodiments. In the accompanying drawings:

[0064] Figure 1 A schematic diagram showing a truck supplied with electrical energy via an overhead line,

[0065] Figure 2 shows a schematic side view of an overhead line,

[0066] Figure 3 shows a graph illustrating sensor point data and model parameters of a parallelogram model,

[0067] Figure 4 A flow chart illustrating a method for sensor-based detection of a trolley feeder of an overhead line according to an embodiment of the present invention is shown.

[0068] Figure 5A flow chart illustrating the steps for estimating the expected location of trolley feeders and hangers of an overhead line is shown.

[0069] Figure 6 shows a flowchart illustrating the steps for determining a validation result of an estimate,

[0070] Figure 7 shows a schematic diagram of a detection device according to an embodiment of the present invention,

[0071] Figure 8 A schematic diagram of a road vehicle according to an embodiment of the invention is shown. DETAILED DESCRIPTION

[0072] Figure 1 A schematic diagram 10 shows a truck 1 having an electric drive and a pantograph 2 for contacting a power line or overhead cable feeder 3 of an electrical energy supply network. Due to the continuous supply of electrical energy, the truck 1, powered by the electric drive, can easily travel long distances while still maintaining the same maneuverability as a conventional truck 1 with an internal combustion engine. This is achieved, for example, by making the pantograph 2 flexible, allowing the vehicle 1 to move within a certain range transverse to the roadway. If the vehicle 1 wishes to leave the lane containing the power line or cable feeder 3, the pantograph 2 can be swung downward, i.e., unhooked. Overtaking maneuvers and travel on non-electrified roads can be accomplished, for example, with the aid of an additional small energy storage device or a hybrid system.

[0073] Figure 2 FIG. 2 shows a side view of an overhead line 20. The overhead line 20 has two parallel-arranged sliding feeders 3 ( Figure 2 Only one sliding feeder is shown).

[0074] The sliding feeder 3 is suspended on the suspension cable 11 by a vertically extending suspension cable 25. The suspension cable 11 is fixed to the cantilever 24 of the overhead wire pole 23 installed at the edge of the roadway 21. Figure 2 As can be seen in the figure, the sling has a hyperbolic direction.

[0075] For simplicity, in Figure 2In the figure, only one trolley feeder 3 is depicted for each lane. However, this trolley feeder represents two parallel trolley feeders with different polarities. As already mentioned, in road electrification systems, two parallel DC lines with different polarities are used for power supply. The sling 11, together with the suspension cable 25 and the trolley feeder 3, forms a chain structure. Lateral movement is prevented by lateral supports (not shown) designed as cantilevers, preventing the trolley feeder 3 from moving laterally even when in contact with the pantograph.

[0076] Figure 3 A diagram 30 is shown, which illustrates sensor point data or sensor data points SDP and model parameters MP of a parallelogram model PM. Diagram 30 shows sensor point data SPD as small solid dots, grouped around the circular corner points EP of a model-based parallelogram PG. The corner points EP are determined as the centroids of the sensor data points SDP of the sensor point data SPD. The angles w between the sides of the parallelogram PG and the sides K of the parallelogram PG are determined by determining the corner points EP. The sides K, the angles w, and the corner points EP represent the model parameters MP of the parallelogram model PM. In diagram 30, the lengths in the x and y directions are given in meters, abbreviated to "m."

[0077] Figure 4 A flow chart 400 is shown, which illustrates a method for sensor-based detection of a trolley feeder 3 of an overhead line 20 according to an embodiment of the present invention.

[0078] In step 4.1, a road vehicle 1, for example Figure 1 The sensor point data SPD of the truck's surroundings are shown for a subregion in which an overhead line 20 is assumed to be located. The subregion includes the region of the road vehicle's surroundings that extends in front of the pantograph 2 of the road vehicle 1 and above the road vehicle 1 .

[0079] In step 4.II, the expected positions PS of the trolley feeders 3 and the suspension cables 11 of the overhead line 20 are determined based on the sensor point data SPD and based on the 2D model of the overhead line 20 in the form of a parallelogram PG. In particular, the model parameters MP, such as the side length 1 and the angle w of the parallelogram PG formed by the two trolley feeders 3 and the two suspension cables 11, and the position PS of the parallelogram PG are determined based on the sensor point data SPD. Figure 5 Describe the details of the estimation step 4.II.

[0080] In step 4.III, the verification result VE is determined based on the determined model parameters MP. The details of this determination step 4.III are given in Figure 6 Detailed description will be given in the related description.

[0081] In step 4.IV, the position P of the trolley feeder 3 is determined based on the estimation of the model parameters MP and based on the verification result VE. If the verification result VE indicates that the estimated model parameters MP are invalid, instead of determining the position P it can also be determined that no valid position P exists.

[0082] In step 4.V, the determined position P of the trolley feeder 3 and the verification result VE are output, for example, to the control device 13 of the pantograph 2 (see Figure 8 Then, the control device 13 can control the hooking process of the pantograph 2 to the trolley feeder 3 of the overhead line 20 based on the knowledge of the position P of the trolley feeder 3 .

[0083] Figure 5 A flow chart illustrating step 4.II for estimating the expected position PS of the trolley feeder 3 and the suspension cable 11 of the trolley line 20 is shown.

[0084] In step 4.IIa, clusters of sensor data points SDP of the sensor point data SPD are first determined using the RANSAC method. The largest cluster is then selected as the center of gravity SWP of these clusters to determine the corner points EP of the parallelogram PG. The RANSAC algorithm is used as a clustering algorithm to estimate a model within a series of measurements with outliers and gross errors. Due to its robustness against outliers, the RANSAC algorithm is particularly used in the evaluation of automated measurements. By calculating a data set cleared of outliers, the so-called consensus set, RANSAC supports compensation methods that typically fail with a large number of outliers.

[0085] Subsequently, a center of gravity SWP is determined based on the set of sensor data points SDP associated with these clusters and is determined as the corner point EP.

[0086] In step 4.IIb, a model-based parallelogram PG is estimated based on the determined center of gravity SWP or corner points EP.

[0087] In step 4.IIc, the estimated model parameter values ​​MP of the parallelogram PG, ie in particular the side length l, the angle w and the position P of the parallelogram PG, are compared with the reference parameter values ​​MP R If the estimated model parameter value MP is the same as the reference parameter value MP R Consistent enough, this Figure 5 If the estimated model parameter value MP is equal to the reference parameter value MP, the estimated parallelogram PG is classified as a confirmed parallelogram PE and released for verification in step 4.III. R are not sufficiently consistent, i.e., they are not consistent with the reference parameter value MP R The deviation is too large (for example, exceeds a predetermined threshold). Figure 5 If it is indicated by "n (no)", proceed to step 4.IId.

[0088] In step 4.11d, the geometry of the estimated parallelogram PG is corrected, for example by adding further sensor data points SDP as support points for a supplementary parallelogram PE or by determining a new parallelogram PGA, for example based on an aggregation with fewer sensor data points SDP.

[0089] In step 4.IIe, it is rechecked whether the newly estimated or supplemented parallelogram PE, PGA or its parameter values ​​MPPE, MPPGA are consistent with the reference parameter values ​​MP R If the supplemented or newly estimated model parameter values ​​MPPE, MPPGA are consistent with the reference parameter values ​​MP R Consistent enough, this Figure 5 If the supplemented or newly estimated model parameter values ​​MPPE, MPPGA are different from the reference parameter values ​​MP R Not consistent enough, this Figure 5 If "n" is used in the expression, the process goes to step 4.IIf.

[0090] In step 4.1If, the measured sensor point data SPD is verified using the solution of the previous time step of the measurement. That is, the parallelogram PG created at an earlier time point is verified. V is compared with the current sensor point data SPD and based on the comparison, if possible (this is Figure 5 y) will be combined with the old parallelogram PG V The consistent sensor point data SPD serve as supporting data for the newly determined parallelogram PE.

[0091] For cases where no supporting data was found (this is in Figure 5(denoted by "n" in the figure), then the process proceeds to step 4.11g. In step 4.11g, the overhead wire 20 is tracked in conjunction with the motion model BM. That is, based on the previous parameter values ​​MP of the overhead wire and the motion model BM of the road vehicle 1, for example, in conjunction with the position data, speed data, orientation data, or acceleration data of the road vehicle 1, the future position or relative position of the overhead wire 20 or the parallelogram PE to be determined relative to the road vehicle 1 is determined.

[0092] Figure 6 A flow chart illustrating step 4.III for determining a verification result VE for the estimate is shown.

[0093] In step 4.IIIa, by comparing with the reference data MP R The comparison is performed to determine a first validity value VE1 for the model parameters MP of the determined parallelogram PE. For example, it can be checked whether the side length l, angle w, and position of the determined parallelogram PE are within an expected value range, and how close the values ​​of the model parameters MP are to the expected values. The first validity value VE1 is determined based on this comparison.

[0094] In step 4.IIIb, the number Z of sensor data points SDP located on the model-based parallelogram PE provided with the model parameter values ​​MP is determined. In other words, the degree of match between the sensor point data SPD or the sensor data points SDP of the sensor point data SPD and the geometric model PM parameterized with the model parameter values ​​MP is determined.

[0095] In step 4.IIIc, a validity value VE is calculated based on the first validity value VE1 and based on the number Z(SDP) of sensor data points SDP lying on the determined parallelogram PE.

[0096] Figure 7 FIG. 7 is a schematic diagram showing a detection device 70 according to an embodiment of the present invention.

[0097] The detection device 70 has a radar sensor unit 71 configured to detect the vehicle 1 that can be supplied with energy via the overhead line 20 (see Figure 1 、 Figure 8 ) of the surroundings of the embodiment of the present invention, wherein the overhead line 20 is expected to be located in the sub-area.

[0098] The detection device 70 further comprises an estimation unit 72 . The estimation unit 72 is configured to estimate the expected position PS of the trolley feeder 3 and the suspension cable 11 of the trolley line 20 based on the sensor point data SPD and based on the parallelogram model PG of the trolley line 20 .

[0099] To this end, the estimation unit 72 includes a cluster determination unit 72a configured to determine clusters of sensor data points SDP in the sensor point data SPD based on a RANSAC method and select the largest cluster as a corner point EP of the parallelogram model PM.

[0100] Furthermore, the estimation unit 72 comprises a model unit 72 b configured for determining model parameter values ​​MP of the parallelogram model PM based on the determined corner points EP.

[0101] Furthermore, the estimation unit 72 comprises a comparison unit 72 c which is configured for checking the geometry of the estimated parameterized geometric model PM or the geometry of the parallelogram PG corresponding to the model PM.

[0102] Furthermore, the estimation unit 72 comprises a correction unit 72d configured for correcting the geometry of the parallelogram model PM, for example by supplementing corner points, or alternatively determining a new parallelogram based on other aggregations of sensor data points SDP.

[0103] Furthermore, the estimation unit 72 includes an extrapolation unit 72e configured to determine currently measured sensor data points SDP that can be used for the current parallelogram model PM based on the parallelogram model PM at a previous time point. This approach is useful when it is impossible to generate the parallelogram model PM based solely on the current sensor data. For example, by tentatively translating the previous parallelogram model PM, currently measured sensor data points can be identified that are located on the translated parallelogram model PM.

[0104] Finally, the estimation unit 72 also includes a tracking unit 72f, which calculates the current parallelogram model PM based on the recorded past positions and directions of the overhead wire 20 and the motion model BM of the vehicle 1. The tracking unit 72f considers multiple parallelogram models PM determined in the past and the knowledge of the motion of the vehicle 1 to calculate the translation of the past parallelogram model PM. Tracking may be useful when the result of the extrapolation unit 72e is ambiguous and multiple possible parallelogram models PM can be determined based on tracking the direction of the overhead wire 20.

[0105] In addition, the detection device 70 includes a verification unit 73, which is used to verify the model parameter value MP by comparing it with the reference data MP. Rand determines the verification result VE of the estimation based on the degree of matching between the sensor point data SPD and the parallelogram model PM parameterized by the model parameter value MP.

[0106] Finally, the detection device 70 also has a positioning unit 74 for determining the position P of the contactor 3 based on the estimation and verification result VE.

[0107] The determined position P of the trolley line 3 and the verification result VE are output to the control device 13 via an output interface 75 , which is also part of the detection device 70 , so that the pantograph can be hooked up to the trolley line 3 .

[0108] Figure 8 A schematic diagram 80 of a vehicle 1 according to an embodiment of the present invention is shown. The vehicle 1, in this case a truck, has a pantograph 2, with which it contacts two parallel trolley feeders 3 of an overhead line. Furthermore, the vehicle 1 includes a detection device 70 according to the present invention. The detection device 70 according to the present invention scans a partial area of ​​the surroundings around the pantograph 2 and determines the position P of the trolley feeders 3 and a verification result VE therewith. A control device 13, also part of the vehicle 1, is used to control the pantograph 2 as a function of the determined position P of the trolley feeders 3 and the verification result VE.

[0109] Finally, it should be pointed out again that the methods and devices described above are only preferred embodiments of the present invention and that those skilled in the art may make changes thereto without departing from the scope of the invention as predefined by the claims. For the sake of completeness, it should also be pointed out that the use of the indefinite article "a" or "an" does not exclude that the relevant features may also exist in plural form. Similarly, the term "unit" does not exclude that the unit is composed of multiple components, which may also be distributed in space if necessary. Regardless of the grammatical gender of a particular term, people with male or female gender identity are included.

Claims

1. A method for sensor-based detection of a trolley feeder (3) of an overhead line (20), comprising the following steps: - acquiring at least two-dimensional sensor data (SDP, SPD) by sensor-based mapping of a sub-region of the surroundings of the vehicle (1) which can be supplied with energy via the trolley line (20), in which sub-region the trolley line (20) is expected to be located, - estimating the expected position (PS) of the trolley feeder (3) and the sling (11) of the overhead line (20) based on the sensor data (SPD) and based on the geometric model (PM) of the overhead line (20), - determining a verification (VE) of the estimate by checking the consistency of the geometrical model (PM) and checking the consistency of the sensor data (SDP, SPD) with the geometrical model (PM), - Determining the position (P) of the trolley feeder (3) based on the estimated position (PS) and the verification result (VE).

2. The method according to claim 1, wherein In the step of estimating the expected position (PS) of the trolley feeder (3) and the suspension cable (11) of the overhead line (20), - determining model parameter values ​​(MP) of the geometric model (PM) based on the sensor data, and - Associate sensor data (SDP, SPD) that are consistent with the parameterized geometric model (PM) with the parameterized geometric model (PM).

3. The method according to claim 2, wherein: - By comparing the determined model parameter value (MP) with the reference data (MP R ) for comparison, and - Based on how well the sensor data matches the geometric model (PM) parameterized by the model parameter values ​​(MP), to determine a verification result (VE) for the estimate.

4. A method according to any one of the preceding claims, wherein The sensor data (SDP, SPD) includes sensor point data (SPD), and the expected position (PS) of the trolley feeder (3) and the suspension cable (11) of the overhead line (20) is estimated by performing density analysis on the sensor point data (SPD).

5. The method according to claim 4, wherein The density analysis includes determining the largest clusters of sensor point data (SPD).

6. The method according to claim 4 or 5, wherein: The geometric model (PM) comprises polygons (PG), and estimating the expected positions (PS) of the trolley feeders (3) and the slings (11) of the overhead line (20) comprises the following steps: - determining the geometrical properties of the polygon (PG) formed by the expected positions (PS) of the feeder (3) and the sling (11), - Checking the geometrical properties by comparing the determined geometrical properties with reference data and, if necessary, correcting the estimate based on the comparison.

7. The method according to claim 6, wherein: - determining a verification result (VE) comprising determining a confidence value for the estimate based on a comparison of geometrical properties of the corrected polygon (PG) with reference data and based on a number (Z) of sensor data points (SDP) that can be associated with the corrected polygon (PG), and - determining the position (P) of the contact feeder (3) based on the determined confidence value.

8. The method according to claim 6 or 7, wherein: The geometrical properties (MP) examined include the lengths of the sides (K) of the spanned polygon (PG) and / or the angles (w) of the sides (K).

9. The method according to any one of claims 6 to 8, wherein Corrections to the estimates include: - Supplemental Sensor Data Points (SDP), and / or - Search for another polygon (PGA) spanned by the sensor data points (SDP) of the sensor point data (SPD).

10. The method according to any one of claims 6 to 9, wherein For cases where the polygon (PG) cannot be determined, - estimating the current position (P) of the trolley feeder (3) and the sling (11) of the trolley line (20) based on sensor data points (SDP) and based on the position of the trolley line (20) previously determined in time, and / or - Based on time-dependent tracking of the positions of the trolley feeder (3) and the suspension cable (11) of the trolley line (20) and in combination with a motion model (BM), the current position (P) of the trolley feeder (3) and the suspension cable (11) of the trolley line (20) is determined.

11. The method according to any one of claims 6 to 10, wherein A polygon (PG) includes one of the following types of polygons: - triangle, - quadrilateral, - Trapezoidal, - Parallelogram.

12. A detection device (70), comprising: - a sensor unit (71) for acquiring at least two-dimensional sensor data (SDP, SPD) by sensor-based mapping of a sub-region of the surroundings of a vehicle (1) that can be supplied with energy via an overhead line (20), wherein the overhead line (20) is expected to be located in the sub-region, - an estimation unit (72) for estimating the expected position (PS) of the trolley feeder (3) and the sling (11) of the overhead line (20) based on the sensor data (SDP, SPD) and based on a geometric model (PG) of the overhead line (20), - a verification unit (73) for determining a verification result (VE) of the estimation by checking the consistency of the geometric model (PM) and by checking the consistency of the sensor data (SDP, SPD) with the geometric model (PM), - a positioning unit (74) for determining the position (P) of the trolley feeder (3) based on the estimated position (PS) and the verification result (VE).

13. A vehicle (1), comprising: - a pantograph (2), a sliding feeder (3) for contacting an overhead line (20) of an electrical energy supply network, - a traction unit for driving the vehicle (1) using electrical energy drawn from the electrical energy supply network via the pantograph (2), and - A detection device (70) according to claim 12.

14. A computer program product comprising instructions which, when executed by a computer, cause the computer to perform the following steps of the method for sensor-based detection of a trolley feeder (3) of an overhead line (20) according to any one of claims 1 to 11: estimating an expected position (PS) of the trolley feeder (3) and a suspension cable (11) of the overhead line (20), determining a verification result (VE) of the estimation, and determining a position (P) of the trolley feeder (3) based on the estimated position (PS) and the verification result (VE).

15. A computer-readable storage medium comprising instructions which, when executed by a computer, cause the computer to perform the following steps of the method for sensor-based detection of a trolley feeder (3) of an overhead line (20) according to any one of claims 1 to 11: estimating an expected position (PS) of the trolley feeder (3) and a suspension cable (11) of the overhead line (20), determining a verification result (VE) of the estimation, and determining a position (P) of the trolley feeder (3) based on the estimated position (PS) and the verification result (VE).

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