Method, device and vehicle for influencing a wind turbine located at the roadside

Abstract

A method and a device for influencing the airflow towards a wind turbine (16) located at the edge of a roadway (12a) by means of a vehicle (14) passing on the roadway (12a), comprising an ADAS system (18) with at least one front camera (20) capturing the area in front of the vehicle, characterized by detecting a wind turbine (16) and determining a driving trajectory (26) of the vehicle (14), by which the rotational speed of the wind turbine (16) is changed towards the optimal operating point. This results in more efficient energy generation from track-based wind turbines.

Description

[0001] The invention relates to a method for influencing the airflow to a wind turbine located at the edge of a roadway by means of a vehicle passing on the roadway, which includes an ADAS (Advanced Driver Assistance System) with at least one front camera capturing the area in front of the vehicle, as well as a device for carrying out the method and a vehicle equipped with such a device.

[0002] From DE 38 32 997 A1 it is known to install axial wind turbines, preferably in the form of vertical wind turbines, along roadways in order to use the wind artificially generated by passing vehicles to generate electrical energy.

[0003] Various methods for improving the airflow to a wind turbine located at the edge of a roadway by means of a vehicle passing on the roadway are known from the state of the art.

[0004] For example, DE 101 51 525 A1 teaches that the steepness of the flanks of a bow wave from a single vessel depends on the vessel's speed. To improve the airflow to a wind turbine located at the edge of the roadway, it is proposed that the wind turbine be steered to follow the prevailing wind direction in a bow wave.

[0005] The publication HU, Wenyu [et a].]: Investigation on harvesting characteristics of convective wind energy from vehicle driving on multi-lane highway. In: Energy, Vol. 1, 263, 2023, Part E, Article no. 1 26062, 17 pp. ISSN 0360-5442, analyzes the generation of wind energy by different numbers and types of vehicles on a multi-lane highway in order to identify advantageous configurations for wind energy generation. Among other findings, it concludes that the lane position (lateral position) influences energy generation.

[0006] The object of the invention is to provide a method and a device with which the efficiency of energy generation of such a wind turbine can be increased.

[0007] The invention is defined by the features of the independent claims. Advantageous further developments and embodiments are the subject of the dependent claims.

[0008] The problem is solved according to claim 1 by a method characterized by monitoring the area in front of the vehicle for wind turbines by means of image processing of the image data from the front camera; upon detection of a wind turbine, determining its position relative to the vehicle and its rotational speed; determining the technical data of the wind turbine including the optimal operating point; determining a driving trajectory of the vehicle based on an airflow model of the vehicle, its own driving state and the relative position by which the rotational speed of the wind turbine is changed towards the optimal operating point, and acting the vehicle according to the determined driving trajectory, i.e. preferably by actuating vehicle actuators or controlling vehicle control units so that the vehicle follows the driving trajectory by longitudinal and / or lateral control.

[0009] The invention is based on the understanding that it is possible to detect wind turbines appearing in front of a vehicle using an ADAS system with a front-facing camera that captures the area in front of the vehicle, and to determine their position relative to the vehicle and their rotational speed by processing the image data. By using at least one information source (for example, entries in a navigation system in conjunction with a corresponding lookup table in a vehicle fleet backend), the technical data of the wind turbine, including the optimal operating point of a detected wind turbine, can be determined.

[0010] In a stored airflow model around the vehicle, the velocity contours for various speeds in the vehicle's immediate vicinity are known. From the turbine's rotation, the vehicle's own aerodynamic properties, and the optimal operating point, an optimal driving trajectory for passing the wind turbine can be determined. Such a trajectory adjustment requires only a relatively small lateral deviation from the normal driving trajectory, which, if the movement is initiated sufficiently early, is imperceptible or only minimally noticeable to the vehicle's occupants.

[0011] The advantage of the invention lies in increasing the efficiency of energy generation using road-mounted wind turbines, because the turbine's rotational speed is adjusted closer to the optimal operating point. Wear and tear on such turbines is also reduced. The method is independent of prevailing light and weather conditions and is not dependent on a dedicated camera. Furthermore, it is globally applicable and requires no user input, meaning it can be fully automated. In addition, the method can be integrated as an additional function into existing ADAS systems. Moreover, the method according to the invention is expected to scale significantly due to the planned proliferation of road-mounted wind turbines. The method can be implemented purely in software within the existing ADAS system, as it only utilizes existing hardware and is therefore easy to implement from a structural perspective.The procedure can therefore be integrated into the regulating ADAS function as an additional sub-function.

[0012] According to an advantageous embodiment of the invention, the vehicle trajectory includes a lateral movement. Thus, preferably within the existing lane, the vehicle passes the wind turbine at either a shorter or greater distance in a transverse direction to the direction of travel, taking into account the approach and exit of the lateral movement. If the vehicle is on a multi-lane road and the ADAS system determines that a lane change is possible because there is no vehicle nearby in the adjacent lane, the vehicle trajectory can also include a movement into the adjacent lane.

[0013] According to an advantageous embodiment of the invention, the driving trajectory additionally includes a change in the vehicle's speed. A reduction in speed can be achieved by briefly switching off the drive power in order to keep the acceleration forces as low as possible and thus minimize any impact on passenger comfort.

[0014] According to an advantageous embodiment of the invention, the rotational speed of the wind turbine is determined using Fast Fourier Transform operations, which is a simple and proven method of determination.

[0015] According to an advantageous embodiment of the invention, the rotational speed of the wind turbine is determined by means of a rear-view camera of the ADAS system after the vehicle has passed it, and the flow model is thus verified. Once the vehicle has passed the wind turbine, the rear-view camera can therefore record its actual rotational speed. The actual rotational speed can be compared with the previously calculated rotational speed, and any deviations can be used to optimize the computational model.

[0016] According to an advantageous embodiment of the invention, the technical data of the wind turbine is determined by means of image recognition, data from a navigation system, wireless communication with a fleet database, or wireless communication with vehicles in the vicinity. Thus, there are numerous possibilities for providing the relevant technical data of the wind turbine in front of the vehicle for calculating the driving trajectory after its location has been determined. Ideally, the device contains a database with the necessary data, similar to the map data in a navigation system.

[0017] According to a second aspect of the invention, the problem is solved by a device for a vehicle for carrying out the method, comprising at least one front camera capturing the area in front of the vehicle, characterized in that this camera is designed to detect wind turbines in front of the vehicle and to determine their relative position relative to the vehicle as well as their rotational speed, comprising - a wind turbine determination unit that is designed to determine the technical data of the wind turbine, including the optimal operating point, - a trajectory determination unit configured to determine a trajectory based on its own driving state and relative position, by which the rotational speed of the wind turbine can be varied to the optimal operating point, wherein the device is configured to actuate the vehicle according to the trajectory.

[0018] According to a third aspect of the invention, it relates to a motor vehicle comprising such a device.

[0019] Further advantages, features, and details will become apparent from the following description, in which at least one embodiment is described in detail with reference to the drawings. Identical, similar, and / or functionally equivalent parts are identified by the same reference numerals.

[0020] This shows: Fig. 1: a schematic top view of a roadway with a vehicle and a wind turbine; Fig. 2: a schematic representation of an ADAS system; Fig. 3: a flowchart illustrating the method according to the invention; Fig. 4: a diagram of the airflow around a vehicle.

[0021] Fig. Figure 1 shows a schematic top view of a two-lane roadway 10 with a first lane 12a, on which a vehicle 14 is located, and a second lane 12b, which can be a second lane (for example, of a motorway) for the vehicle 14 or an oncoming traffic lane. Outside the drivable edge of lane 12a is a wind turbine 16. Such a wind turbine 16 comprises at least one turbine wheel rotating about a vertical axis, which is coupled to or drives a generator for the production of electrical energy.

[0022] Vehicle 14 includes a Fig. 2 ADAS system 18 shown in more detail with at least one front camera 20, which continuously records the area in front of the vehicle up to about 150m in the vicinity of lane 12a and analyzes it by means of image processing in order to detect, recognize and categorize all types of objects such as vehicles driving ahead or oncoming vehicles or pedestrians or animals as well as objects located at the edge of the roadway.

[0023] When the vehicle 14 approaches a wind turbine 16 and this is recorded by the front camera 20, in particular registered as an object, image processing is used to determine, based on characteristic features of wind turbines, especially the rotating turbine wheel, by means of feature detectors (template matching) or by means of so-called CNN classifiers (convolutional neural network classifiers), that it is a wind turbine 16 and preferably which exact type it is.

[0024] The ADAS system 18 includes a wind turbine detection unit 22, which is configured to determine the relevant technical data of the wind turbine 16 from the available information, including at least its optimal operating point. For this purpose, the wind turbine detection unit 22 can access the images acquired by the front camera 20 and compare them with images stored in the ADAS system 18. Alternatively, it is also possible to incorporate position and identification data of wind turbines 16 into the map data, in particular a digital map, of the navigation system implemented in the vehicle, so that when approaching a wind turbine 16, the type information is already available and only the relevant technical data of the wind turbine 16, including its optimal operating point, needs to be determined in a lookup table.Such a look-up table can be stored in the ADAS system 18 or, for example, requested wirelessly from a vehicle fleet backend server. Using suitable measurement methods (radar and / or lidar and / or further image processing), the position of the wind turbine 16 relative to the vehicle 14 is determined. Furthermore, the rotational speed of the turbine wheel is determined by the ADAS system 18, preferably using FFT (Fast Fourier Transform) operations on several image frames of the wind turbine 16.

[0025] The ADAS system 18 further comprises a trajectory determination unit 24, which is configured to determine a trajectory 26 of the vehicle 14 approaching the wind turbine 16 based on a stored airflow model of the vehicle, its own driving state, and the relative position between the wind turbine 16 and the vehicle 14. This trajectory is used to change the rotational speed of the wind turbine towards its optimal operating point. From the rotational speed of the turbine wheel, or the deviation from the optimal operating point of the wind turbine 16, and the aerodynamic efficiency of the vehicle 14 derived from the airflow model, the appropriate lateral distance 30 of the vehicle 14 (more precisely, the vehicle's central axis) from the wind turbine 16 at the moment of passage can be determined. Subsequently, a complete trajectory 26 can be generated from this. Fig. 1) to be used for the passage of vehicle 14 along wind turbine 16.

[0026] After passing wind turbine 16, the rotational speed of the wind turbine 16 can be determined again using a rear-view camera 28 belonging to the ADAS system 18. This allows for validation of the determined target rotational speed and, if necessary, adjustment or optimization of parameters of the airflow model or behavior. Such parameter adjustments, as well as the calculated driving trajectory, can also be wirelessly transmitted to a vehicle fleet backend server to make these improvements available to other vehicles of the same type. This data can also be transmitted to radio-connected vehicles in the vicinity.

[0027] In Fig. Figure 3 shows a flowchart for an embodiment of the method according to the invention. In step 100, the area in front of the vehicle is monitored for wind turbines using the front camera 20 by processing the image data from the front camera 20 of the vehicle 14. If, in step 101, it is determined that a wind turbine 16 is located in front of the vehicle 14, then, in step 102, the type of wind turbine 16 is determined as described above. Instead of determining whether a wind turbine 16 is located in front of the vehicle 14 using the front camera 20, this determination could also be made using the digital map in combination with determining the GPS position of the vehicle 14.

[0028] In step 103, the position of the wind turbine 16 relative to the vehicle 14 is determined, and in step 104, the rotational speed of the wind turbine 16 is determined - preferably using FFT operations.

[0029] In step 105, based on the type of wind turbine 16 determined in step 102, its optimal operating point, i.e. the optimal rotational speed, is determined and compared with the rotational speed measured in step 104.

[0030] In step 106, based on the stored airflow model of the vehicle as well as its own driving state (speed, accelerations, etc.) and the relative position between the vehicle 14 and the wind turbine 16, an optimal lateral distance 30 or offset ( Fig. 1) calculated between the driving trajectory 26 to be determined, by which the rotational speed of the wind turbine 16 can be changed towards the optimal operating point.

[0031] In step 107, a preferably approximately arc-shaped travel trajectory 26 for the vehicle 14 is determined from this distance 30. In step 108, the vehicle 14 is controlled to follow the travel trajectory 26.

[0032] In step 109, the area behind the vehicle is monitored for the just-passed wind turbine 16 using the rear-view camera 28 and image processing. If the wind turbine 16 is detected in step 110, its current rotational speed is determined in step 111, analogous to step 104. In step 112, the effects are analyzed, i.e., the calculated target rotational speed is validated, and the parameters of the airflow behavior are adjusted if the rotational speed of the wind turbine 16, as recorded by the rear-view camera 28 after the vehicle 14 has passed, deviates from the calculated target rotational speed.

[0033] In step 113, the determined and specified data, starting with the data on the location and type of the wind turbine16 and, if necessary, adjusted parameters of the airflow model of the vehicle 14, can be wirelessly transmitted to a backend server or neighboring vehicles.

[0034] Fig. Figure 4 shows an example diagram of the airflow around a vehicle in a transverse plane as the vehicle 14 travels perpendicular to the plane of representation at a speed of 50 km / h. The shades of gray represent the change in flow velocity caused by the vehicle's movement. The number 1.01 signifies an increase in flow velocity of 1%. For example, when the vehicle 14 passes a wind turbine 16 at a certain speed (here 50 km / h) at a distance E1 (e.g., E1 = 3.5 m), this results in an increase in flow velocity of 4.7 m / s. At a distance E2 = 4.5 m, this would be 2.1 m / s, and at a distance E3 = 5.5 m, it would be 1.1 m / s.The values ​​of the flow velocity increase as a function of the vehicle speed and the respective distances E1, E2, E3 between the center of the vehicle 14 and the axis of the wind turbine 16 are preferably stored in a three-dimensional table, which is used to calculate the change in the influence on the rotational speed of the wind turbine 16. If the wind turbine 16 rotates at a speed significantly below the ideal operating point, the driving trajectory 26 - as shown in . Fig.Figure 1 shows the vehicle's trajectory being changed in the direction of the wind turbine 16 to reduce the lateral distance 30 and to increase the rotational speed through the airflow generated by the moving vehicle. However, if the measured rotational speed of the wind turbine 16 is already close to the ideal operating point and calculations indicate that the rotational speed will be negatively affected, the vehicle's trajectory 26 will be moved away from the wind turbine 16 to minimize the impact on the rotational speed and thus move it away from the ideal operating point.

[0035] Although the invention has been further illustrated and explained in detail by means of preferred embodiments, the invention is not limited by the disclosed examples, and other variations can be derived from them by a person skilled in the art without departing from the scope of protection of the invention. It is therefore clear that a multitude of possible variations exist. It is also clear that the embodiments mentioned as examples are truly only examples and are not to be understood in any way as limiting, for example, the scope of protection, the possible applications, or the configuration of the invention.Rather, the preceding description and the description of the figures enable the person skilled in the art to implement the exemplary embodiments in concrete terms, whereby the person skilled in the art, with knowledge of the disclosed inventive concept, can make various changes, for example with regard to the function or the arrangement of individual elements mentioned in an exemplary embodiment, without leaving the scope of protection defined by the claims and their legal equivalents, such as further explanations in the description. Reference symbol list 10 lanes 12a,b Lane 14 vehicles 16 wind turbines 18 ADAS system 20 Front camera 22 Wind turbine detection unit 24 Trajectory Determination Unit 26 Travel trajectory 28 Rear camera 30 lateral distance 100 - 113 process steps

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