Method for operating a rail vehicle and rail vehicle

Abstract

The rail vehicle (Z) according to the invention has a variable-shape traction nose (ZN) and an actuator (A) for changing the shape of the traction nose (ZN). Furthermore, the rail vehicle (Z) has a controller (CTL) for detecting position data (PD) specifying a relative position of the rail vehicle (Z) to a tunnel and for controlling the actuator (A) depending on the position data (PD). Based on the detected position data (PD), an aerodynamically optimized shape of the traction nose (ZN) is determined by means of a fluid dynamic simulation.

Description

[0001] Modern rail vehicles and their infrastructure are often aerodynamically adapted to their intended use. High-speed trains, in particular, are equipped with a relatively tapered nose to reduce air resistance, energy consumption, and noise. Accordingly, tunnels, especially on high-speed lines, are built with larger diameters to avoid stronger pressure waves when high-speed trains enter.

[0002] However, such adaptations often require technical compromises, as a variety of boundary and operational conditions must be taken into account. Increasing tunnel diameters also generally involves increased construction effort.

[0003] From the publication EP 1 547 897 A1, a rail vehicle is known with air inlet openings arranged on the train nose, which are opened when entering a tunnel in order to reduce pressure waves.

[0004] Furthermore, the document JP 2004-161 085 A describes a rail vehicle whose nose is extended at higher speeds and shortened at lower speeds.

[0005] The publication DE 10 2004 013 336 A1 further discloses a vehicle which can be operated in opposite directions and whose end sections can be adjusted differently depending on the direction of travel in order to improve the flow.

[0006] Furthermore, a rail vehicle is known from the publication DE 10 2012 207 521 A1, the nose of which can be extended in the longitudinal direction to improve aerodynamics.

[0007] The publication DE 10 2014 212 233 A1 further discloses a rail vehicle with a 3D image capture device for capturing an environment of the rail vehicle.

[0008] It is an object of the present invention to provide a method for operating a rail vehicle and a rail vehicle by means of which pressure waves can be reduced more efficiently when entering a tunnel.

[0009] This object is achieved by a method for changing the shape of a train nose having the features of patent claim 1 and by a rail vehicle having the features of patent claim 4.

[0010] Advantageous embodiments and further developments of the invention are specified in the dependent claims.

[0011] According to the invention, a method for changing the shape of the traction nose during travel of a rail vehicle is implemented, which comprises a variable-shape traction nose, an actuator for changing the shape of the traction nose, and a controller for detecting position data specifying a relative position of the rail vehicle to a tunnel and for controlling the actuator depending on the position data. Based on the detected position data, an aerodynamically optimized shape of the traction nose is determined using a fluid dynamic simulation, and the traction nose is brought into the optimized shape by means of the actuator.

[0012] The position data can be acquired, in particular, using a satellite navigation system, e.g., GPS, Galileo, or GLONASS. In particular, an absolute position of the rail vehicle determined by a satellite navigation system can be correlated with an absolute position of a tunnel retrieved from a database.

[0013] In particular, the simulation can simulate the flow behavior of a rail vehicle entering a tunnel for different train nose shapes. Based on the simulation results, a train nose shape can then be selected that optimizes a given optimization criterion. The optimization criteria can include, in particular, minimizing pressure waves, pressure differences, and / or pressure forces; minimizing air resistance; and / or minimizing changes in the train nose's shape.

[0014] To implement the method, a rail vehicle, in particular a passenger train, a freight train, or a magnetic levitation train, is provided with a shape-variable train nose and an actuator for changing the shape of the train nose. Furthermore, the rail vehicle has a controller for detecting position data specifying a relative position of the rail vehicle to a tunnel and for controlling the actuator depending on the position data.

[0015] A particular advantage of the invention is that the variable-shape drawbar can be given a profile specifically adapted to the current driving situation. The profile can preferably be adjusted during travel, particularly to the flow conditions during tunnel entry or passage. In many cases, this allows for higher transit speeds and / or reduces the need for structural modifications to existing tunnels.

[0016] In contrast, existing rail vehicles, especially their nose cones, generally have a fixed geometry. This is often optimized for a specific application scenario. Beyond this specific application scenario, however, such a fixed geometry is often suboptimal or even detrimental. In many cases, the fixed geometry is also designed for different application scenarios, but is often not optimal for all of them.

[0017] According to an advantageous development of the invention, an optimized temporal progression of the shape of the train nose can be determined in advance for a predefined time window using fluid dynamic simulation. The above optimization criteria can be used for this purpose. By minimizing changes in the shape of the train nose, in particular by minimizing the number, amplitude, and / or speed of successive changes in the shape of the train nose, oscillations on the rail vehicle can generally be effectively avoided or reduced. During the simulation over a predefined time window, speed changes and / or wind conditions planned for this time window can also be taken into account.

[0018] According to a further advantageous development of the invention, a fluid-dynamic preliminary simulation of a rail vehicle entering a tunnel can be carried out for a plurality of position data values and / or other data values. The preliminary simulations can in particular also be carried out for a plurality of different geometric data values, aerodynamic data values, wind data values and / or weather data values. Based on the resulting simulation results, a model-reduced simulator can be generated and / or a machine learning system, e.g., a neural network, can be trained. The fluid-dynamic simulation can then be carried out during the journey using the model-reduced simulator and / or the machine learning system.Since a model-reduced simulator or a trained machine learning system usually requires considerably fewer computing resources than a detailed simulation, fluid dynamic simulation can in many cases be executed in real time.

[0019] According to an advantageous embodiment of the invention, the controller can be configured to acquire further data and to actuate the actuator depending on the acquired further data. The further data can comprise movement data specifying a movement of the rail vehicle, geometry data specifying a tunnel geometry, aerodynamic data specifying aerodynamics of the rail vehicle, current wind data, and / or current weather data. In particular, data about a current speed of the rail vehicle and / or vibrations of the rail vehicle can be acquired as movement data. In particular, data about a tunnel diameter or a tunnel length can be acquired as geometry data. The geometry data can be retrieved, for example, from a database or online, or acquired by sensors.By recording and taking into account the additional data, the shape of the train nose can be specifically adapted to a train speed, a tunnel geometry, the aerodynamics of the rail vehicle and / or to current wind or weather conditions.

[0020] According to a further advantageous embodiment of the invention, a database can be provided in which aerodynamically optimized shapes of the traction nose and / or associated control data for the actuator are stored for a plurality of position data values and / or other data values. The controller can be configured accordingly to retrieve an aerodynamically optimized shape of the traction nose and / or associated control data for the actuator from the database depending on the detected position data and / or other detected data. The aerodynamically optimized shapes of the traction nose can preferably be calculated in advance using fluid dynamic simulations and stored in the database. Retrieving stored, parameterized optimal shapes requires only minimal effort and can usually be done in real time.

[0021] According to an advantageous embodiment of the invention, a shaped element can be provided on the exterior of the rail vehicle, which can be changed in shape or moved depending on the position data and / or other data. The shaped element can be arranged at the rear, on the floor, on the roof, or on the sides of the rail vehicle and can be designed as an air deflector, as an attachment, and / or as a spoiler. A change in shape or movement of the shaped element can be achieved according to the same principles as a change in shape of the traction nose.

[0022] An embodiment of the invention is explained in more detail below with reference to the drawings, each of which shows a schematic representation: Fig. 1 a rail vehicle according to the invention with a train nose shaped for travel on open track, and Fig. 2 the rail vehicle according to the invention with the traction nose shaped for tunnel entry or tunnel passage.

[0023] Where the same or corresponding reference symbols are used in the figures, they refer to the same or corresponding entities.

[0024] The Fig. 1 and Fig. 2 each show a schematic representation of a rail vehicle Z according to the invention, for example a passenger train, freight train, or another rail-guided vehicle, such as a magnetic levitation train guided by a magnetic rail. According to the invention, a front part of the rail vehicle housing is designed as a shape-variable traction nose ZN. According to the invention, the traction nose ZN changes its shape, in particular depending on whether the rail vehicle Z is traveling on an open track or entering or passing through a tunnel.

[0025] Fig. 1 illustrates the rail vehicle Z with the train nose ZN shaped for travel on open track, while Fig. 2 illustrates the rail vehicle Z with the train nose ZN shaped for tunnel entry or tunnel passage.

[0026] To change the shape of the traction nose ZN, the rail vehicle Z has one or more actuators A. For reasons of clarity, only one actuator A is explicitly shown in the figures. The actuator A acts mechanically on the traction nose ZN or parts thereof in order to deform them, in particular while in motion. Such a change in shape can be brought about by the actuator A, in particular, by moving guide vanes, wind deflectors or other shaped elements arranged on and / or as part of the traction nose ZN. Alternatively or additionally, the geometry of the traction nose ZN can also be elastically changed by the actuator A. For the purposes mentioned, the traction nose ZN can preferably have individually controllable, movable or deformable surface sections or other shaped elements, which are optionally spanned by a flexible material. Such surface sections or other shaped elements can be connected via joints, e.g. pivot joints or sliding joints.Alternatively or additionally, an outer skin that is at least partially elastic, plastic, or flexible can be provided as a deformable mold element. Furthermore, electrically or thermally deformable materials, such as shape memory alloys, can be used.

[0027] Actuator A deforms the tension lug ZN by exerting pressure or tension on these shaped elements. For this purpose, actuator A can be equipped with hydraulic, pneumatic, mechanical, and / or electromechanical components.

[0028] To control actuator A and thus the shape of the train nose ZN, the rail vehicle Z has a controller CTL coupled to the actuator A. The controller CTL is coupled to a sensor system S of the rail vehicle Z. The sensor system S is used to measure or record position data PD specifying a relative position of the rail vehicle Z to a tunnel, movement data BD specifying a movement of the rail vehicle Z, and other data DAT. The position data PD, movement data BD, and other data DAT are transmitted by the sensor system S to the controller CTL.

[0029] The position data PD can quantify a distance of the rail vehicle Z to the tunnel ahead on the route, a position of the rail vehicle Z in the tunnel and an absolute position of the rail vehicle Z, e.g. determined using a satellite navigation system. From an absolute position of the rail vehicle Z, a relative position of the rail vehicle Z to the tunnel can be determined based on a known position of the tunnel. The position relative to the tunnel can be specified in particular relative to a tunnel entrance and / or a tunnel exit. The respective position of a tunnel can be taken, e.g., from a database DB of the rail vehicle Z or queried online. In addition, the position data PD can also include information about whether the rail vehicle Z is currently in a tunnel or on an open track.This information can be detected, for example, by the S sensor.

[0030] The movement data BD include in particular an indication of the current speed of the rail vehicle Z.

[0031] The additional data DAT recorded by the sensor system S can include, in particular, current wind data, weather data, and / or temperature data. Furthermore, additional data DAT relevant for controlling the actuator A can be retrieved from the database DB or online. Such control-relevant additional data DAT can be, for example, geometric data about a tunnel geometry, in particular about a tunnel diameter or a tunnel length, as well as aerodynamic data about the aerodynamics of the rail vehicle Z or the tunnel.

[0032] According to the invention, the control unit CTL is intended to control the actuator A depending on the currently recorded position data PD, movement data BD, and other data DAT in such a way that the traction nose ZN is brought into an aerodynamically favorable or optimized shape for the current driving situation. For this purpose, the control unit CTL determines suitable control data CD for the actuator A and transmits it to the actuator A.

[0033] The aerodynamically optimized shapes are advantageously determined through fluid dynamic simulations. In many cases, it turns out that an elongated, low shape of the ZN train nose can effectively reduce tunnel noise when entering a tunnel, while on open track, a more wedge-shaped ZN train nose is more advantageous. These two basic shape variants of the ZN train nose are also used in the Fig. 1 and Fig. 2 illustrates.

[0034] Preferably, a plurality of fluid dynamic simulations are performed in advance for a variety of possible driving situations in order to determine a driving situation-specific, aerodynamically optimized shape of the traction nose ZN. To parameterize the possible driving situations, a parameter space with the following parameters is preferably selected: - a speed of the rail vehicle Z, - an indication of whether the rail vehicle Z is on open track or in a tunnel, - a tunnel diameter and - a position of the rail vehicle Z in front of or in the tunnel.

[0035] For a large number of representative discrete points in this parameter space, an aerodynamically optimized shape of the intake nose ZN is then calculated offline using a preliminary fluid dynamic simulation. The optimization criteria can be the minimization of pressure waves, pressure differences, pressure forces, and / or vibrations, and / or the minimization of air resistance. A variety of efficient standard simulation and optimization methods are available for this type of optimization.

[0036] For a respective aerodynamically optimized shape of the pull nose ZN, those control data CD for the actuator A can preferably also be determined by which the pull nose ZN is brought into this optimized shape.

[0037] The simulation results of the preliminary simulations can be used in different ways.

[0038] Thus, according to a first embodiment variant, the aerodynamically optimized shapes of the train nose ZN and / or the respective associated control data CD can be stored in the database DB in association with the respective parameter point. This means in association with the information as to whether the rail vehicle Z is on open track or in a tunnel, the speed of the rail vehicle Z, the tunnel diameter and the position of the rail vehicle Z in front of or in the tunnel. During the journey, the control system CTL can then use the currently recorded position data PD, movement data BD and, if applicable, further data DAT specifying the current driving situation to retrieve from the database DB a shape of the train nose ZN assigned to these parameters and aerodynamically optimized for the current driving situation, or the associated control data CD. Preferably, one or more train nose shapes orControl data are retrieved from the database DB whose assigned parameter points are closest to the parameter point formed from the current position data PD, movement data BD, and other data DAT. The current shape of the traction nose ZN or the currently applicable control data CD can then be determined by interpolation from the retrieved traction nose shapes or control data.

[0039] According to a second embodiment of the invention, a model of the flow behavior of the rail vehicle Z can be determined using the preliminary simulations performed for the plurality of parameter points, which model is then reduced. Efficient standard numerical methods, such as so-called POD methods (POD: Proper Orthogonal Decomposition) or other principal component analysis methods, can be used for such model reductions. In this way, a model-reduced simulator SIM is generated, which is preferably implemented in the CTL controller.

[0040] Alternatively or additionally, a machine learning system can be trained to reproduce the results of the preliminary simulations and / or aerodynamically optimized shapes of the traction nose ZN or correspondingly optimized control data CD as accurately as possible based on specified parameter points. A variety of standard machine learning methods are available for this purpose.

[0041] The model-reduced simulator SIM uses the current position data PD, movement data BD, and other data DAT to simulate the flow behavior, particularly when the rail vehicle Z enters a tunnel. Preferably, a short-term forecast of this data and / or a planned driving cycle of the rail vehicle Z are also taken into account. Using the fluid dynamic simulation performed by the model-reduced simulator SIM and / or the trained machine learning system, the aerodynamically optimized shape of the train nose ZN or the associated control data CD can be determined in real time during the journey. In particular, the optimization criteria mentioned above can be used here.

[0042] In both versions, the optimized control data CD are transmitted from the control CTL to the actuator A in order to bring the traction nose ZN into the shape optimized for the current driving situation.

[0043] Preferably, an optimized temporal progression of the shape of the train nose ZN can be determined in advance for a specified time window using the model-reduced simulator SIM and / or the trained machine learning system. In addition to the optimization criteria mentioned above, the number, amplitude, and / or speed of shape changes of the train nose ZN can also be minimized. Oscillations on the rail vehicle Z can generally be effectively avoided or reduced using the latter optimization criterion. When predictively determining the progression of the optimized train nose shape, planned speeds of the rail vehicle Z and current wind conditions within the specified time window can advantageously also be taken into account.

[0044] In addition to adapting to tunnel passages, the ZN train nose can also be deformed depending on the situation, particularly speed, environment, wind, or weather, in order to reduce pressure waves, pressure differences, pressure forces, air resistance, oscillations, driving noise, and / or energy consumption. The above effects can often be further optimized by one or more additional shaped elements attached to the exterior of the rail vehicle Z, which are moved or deformed in a similar way to the ZN train nose. List of reference symbols Z rail vehicle ZN pull nose A actuator CTL control S Sensors PD position data BD movement data DAT Further data DB database CD control data for the actuator SIM model-reduced simulator

Claims

[1] Method for changing the shape of a train nose (ZN) during travel of a rail vehicle (Z), which has a variable-shape train nose (ZN), an actuator (A) for changing a shape of the train nose (ZN) and a controller (CTL) for detecting position data (PD) specifying a relative position of the rail vehicle (Z) to a tunnel and for controlling the actuator (A) depending on the position data (PD), wherein a) an aerodynamically optimized shape of the traction nose (ZN) is determined on the basis of the recorded position data (PD) by means of a fluid dynamic simulation, and b) the pulling lug (ZN) is brought into the optimized shape by means of the actuator (A). [2] Method according to claim 1, characterized bythat by means of the fluid dynamic simulation an optimized temporal progression of the shape of the traction nose (ZN) is determined in advance for a given time window, whereby the optimization criterion used is a minimization of pressure waves, pressure differences and / or pressure forces; a minimization of air resistance and / or a minimization of changes in the shape of the traction nose (ZN). [3] Method according to claim 1 or 2, characterized by , that a flow-dynamic preliminary simulation of a rail vehicle (Z) entering a tunnel is carried out for a plurality of position data values and / or further data values, that a model-reduced simulator (SIM) is generated and / or a machine learning system is trained based on the resulting simulation results, and that the fluid dynamic simulation is carried out using the model-reduced simulator (SIM) and / or the machine learning system during the journey. [4] Rail vehicle (Z) arranged to carry out a method according to one of the preceding claims. [5] Rail vehicle (Z) according to claim 4, characterized by that the controller (CTL) is set up to acquire further data (DAT) and to control the actuator (A) depending on the acquired further data (DAT), wherein the further data (DAT) comprise movement data (BD) specifying a movement of the rail vehicle (Z), geometry data specifying a tunnel geometry, aerodynamic data specifying an aerodynamics of the rail vehicle (Z), current wind data and / or current weather data. [6] Rail vehicle (Z) according to claim 4 or 5, characterized bya database (DB) in which aerodynamically optimized shapes of the pull nose (ZN) and / or associated control data (CD) for the actuator (A) are stored for a plurality of position data values and / or further data values, wherein the controller (CTL) is set up to retrieve an aerodynamically optimized shape of the pull nose (ZN) and / or associated control data (CD) for the actuator (A) from the database (DB) depending on the detected position data (PD) and / or further detected data (DAT). [7] Rail vehicle (Z) according to one of claims 4 to 6, characterized by a shaped element arranged on an outer side of the rail vehicle (Z) which can be changed in shape or moved depending on the position data (PD) and / or further data (DAT).

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