Method and system for calculating the length of jumper cables in trains

Abstract

Computer-implemented method 100 for calculating the length of a jumper cable (1; Fig. 2B) connecting two train wagons (2; Fig. 2B) of a rail vehicle configured to be positioned on a track (3; Fig. 2B)

Description

TECHNICAL FIELD The present invention relates to a Computer implemented method for automatically calculating the length of at least one jumper cable connecting two train wagons of a rail vehicle configured to be positioned on a track. Also, the present invention relates to a computer program, comprising instructions which, when the program is executed by a computing device, cause the computing device to carry out the steps of said computer-implemented method and relates to a computer readable medium comprising a computer program for carry out said computer-implemented method. In addition, the present invention relates to a computing system for automatically calculating the length of at least one jumper cable connecting two train wagons of a rail vehicle configured to be positioned on a track. BACKGROUND Typically, trains use a system called "electrical coupler" to establish electrical connections between wagons. This coupler consists of two electrical connectors designed to align and connect with each other when the wagons are coupled together. The electrical connection allows for the transfer of electrical power, control signals, and data between the wagons. This enables various systems on the train, such as lighting, heating, air conditioning, communication, and braking, to function across the entire train. The connectors are located at each end on opposite sides of the longitudinal vertical center plane on the wall or on the locomotive body either on-top or on the bottom of the locomotive. An elongated jumper cable having connector heads at each end can couple one electrical connector on one wagon to the other electrical connector on the opposite wagon. The jumper cable or interconnecting cable typically consists of multiple conductors enclosed within a protective sheath to maintain safety and prevent damage. The specific design and specifications of the interconnecting cable can vary depending on the train manufacturer and the requirements of the electrical systems being connected. The length of the jumper cable is a crucial consideration to ensure proper electrical connections and functionality between the wagons. The length of this cable should be sufficient to reach between the electrical connection points on the wagons while allowing for the necessary flexibility and movement of the train. It is important to avoid excessive tension or strain on the cable, which could lead to damage or disconnection. Additionally, the length of the cable can affect the electrical resistance and signal integrity. Longer cables can introduce higher resistance, which may lead to voltage drops and signal degradation over the length of the cable. Therefore, it is important to determine an appropriate cable length. Methods for calculating the length of jumper cables are known in the art. However, these method usually employ purely deterministic calculations, without taking into account for variation or uncertainty in the parameters used. Also, a model for the stiffness of the jumper cable is not considered. In addition, known methods fail to consider a systematic approach to provide tolerancing for cable lengths. In particular, the following major technical challenges are present when the length of a jumper cable is calculated using the traditional methods: 1. Possible contradictions in the characteristics, like cable length and minimum bending radius of the cable; 2. Simulation at components level, system level considering different physics during the calculations (mechanical strengths of support structures, electrical characteristics, Kinematic consideration for train positions, track dynamics and cable behavior); 3. The calculation has to be validated by “V” model of Verifications and Validation (i.e. the components results validation and cascading the validation to system level); 4. There is frequent change of specifications parameters during the analysis which leads to restarting of the entire process which is very time consuming. Also, it is important from regulation standpoint to repeat the calculation for every minor change in the process; 5. The legacy drawings used as a specification, which makes the manual reading of the parameter very difficult; 6. Tracking the changes and keeping the versioning, to provide required clarity and reasoning for the change. 7. Since the methodology comprises of only theoretical calculations, one needs to integrate automatic testing of the simulated scenario through two Robot set up. The creation of these set up from manual dimension is time consuming and may lead to errors; 8. The tolerancing for cutting the cables is based on expert judgement. But there are a lot of assumptions and uncertainty involved with the parameters which can be also added to the final result of the calculation, that is the cable length. Examples of the present disclosure seek to address or at least alleviate the above problems. SUMMARY In a first aspect, there is provided a computer implemented method for automatically calculating the length of at least one jumper cable connecting two train wagons of a rail vehicle configured to be positioned on a track, the method comprising: processing input parameters by a simulation module including: defining a relative position between the track and the train wagons by a route analysis module to obtain route analysis output data; modelling the stiffness of the cable by a cable specification configurator module to obtain cable specification output data; and generating a 3D cable model by a cable length analysis module; wherein the route analysis output data and the cable specification output data are processed by an optimization module for an iterative optimization of said data, the optimization module outputting optimized route data and optimized cable data and wherein the optimized route data and the optimized cable data are processed by the cable length analysis module providing the length of the jumper cable between two holding points as final output data. In a second aspect there is provided a computer program, comprising instructions which, when the program is executed by a computing device, cause the computing device to carry out the steps of the computer-implemented method according to the first aspect. In a third aspect there is provided a computer readable medium comprising a computer program for carrying out the method according to the first aspect. In a fourth aspect there is provided a computing system for automatically calculating the length of at least one jumper cable connecting two train wagons of a rail vehicle configured to be positioned on a track, the system comprising: a simulation module for processing input parameters including: a route analysis module for defining a relative position between the track and the train wagons to obtain route analysis output data; a cable specification configurator module for modelling the stiffness of the cable to obtain cable specification output data; and a cable length analysis module for generating a 3D cable model, wherein the system further comprises an optimization module configured to process the route analysis output data and the cable specification output data for an iterative optimization of said data to obtain optimized route data and optimized cable data and wherein the cable length analysis module is configured to processes the optimized route data and optimized cable data for calculating the length of the jumper cable between two holding points as final output data. Other aspects and features are defined in the appended claims. Examples of the disclosure may provide a way to improve the accuracy in the calculation of jumper cable. In particular, the accuracy is improved regarding the modelling of the cable stiffness and the possibility to consider uncertainty and variation in the input parameters on the resulting cable length and constraints. BRIEF DESCRIPTION OF DRAWINGS Examples of the disclosure will now be described by way of example only with reference to the accompanying drawings, in which like references refer to like parts, and in which: Figure 1 is a flow diagram of the method for calculating the cable length according to an example; Figure 2A is a block diagram describing the processing steps of the method according to an example; Figure 2B is a schematic representation of a jumper cable connecting two wagons according to an example; Figure 3 is a schematic representation of the system according to an example; Figure 4 is representation of the input parameters and result outputs from each step of the method according to an example; and Figure 5 is a schematic representation of two wagons according to an example; Figure 6 is a flow chart of an optimization methodology according to an example. DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS A computer-implemented method and a computing system for automatically calculating the length of at least one jumper cable, a computer program and a computer readable method are disclosed. In the following description, a number of specific details are presented in order to provide a thorough understanding of the examples of the disclosure. It will be apparent however to a person skilled in the art that these specific details need not be employed in order to practice the examples of the disclosure. Conversely, specific details known to the person skilled in the art are omitted for the purposes of clarity in presenting the examples. Figures 1, 2A, and 2B serve to illustrate the process steps of the method 100 for calculating the length of a jumper cable 1. It is noted that the method 100 is used for calculating the length of a jumper cable 1 configured to connect two train wagons 2 of a rail vehicle positioned on a track 3. The jumper cable 1 extends between two holding points 14 located for example on the roof of the wagons 2 (see figure 2B). It is clear, however, that the holding points 14 can be located in other regions of the wagons, for example on a bottom or lateral region. Also, the vehicle can be provided with more than one jumper cable 1. According to the method 100, input parameters 4 are processed by a simulation module 5. This processing step includes the definition (S102) of a relative position between the track 3 and the train wagons 2 carried out by a route analysis module 6, the modelling (S103) of the cable stiffness carried out by a cable specification configurator module 8, and the generation (S104) of a 3D cable model 19 carried out by a cable length analysis module 10. It is noted that upon defining the relative position between track 3 and wagons, route analysis output data 7 are generated by the route analysis module 6 and upon modelling the cable stiffness, cable specification output data 9 are generated by the cable specification configurator module 8. Both the route analysis output data 7 and the cable specification output data 9 are then processed by an optimization module 11 for an iterative optimization of these data. The optimization module 11 outputs optimized route data 12 and optimized cable data 13, which are processed by the cable length analysis module 10 providing the length of the jumper cable 1 between two holding points 14 as final output data. In particular, the length of the jumper cable 1 is comprised in the 3D cable model 19. In one example, the method 100 further comprises extracting (S105) the input parameters 4 by a document processor module 15 and inputting the extracted input parameters 4 into the simulation module 5. In particular, the input parameters 4 can be extracted automatically using an optical character recognition system and a trained artificial intelligence model. For example, input parameters can be taken automatically using a transformer-based optical character recognition (TrOCR) and Al models (trained Al model using different layouts of tables). In another example, the method 100 can optionally use the length of the jumper cable 1 provided by the cable length analysis module 10 for generating (S106) a report by a report generator module 16. The input parameters 4 inserted into the simulation module 5 comprise train and track parameters. These parameters can include at least one, or a combination of, the following parameters: - the wagon dimensions; - the wagon position; - the inter-wagon distance; - the track curvature; - the track position; and - the track dimensions. More specifically, a user can provide the input train parameters either as a PDF with table and figure or as numerical parameter entry to the table. The data used to train these type of table are taken from the past project and few data sets are created by augmenting similar table created for test cases. Once the parameters are updated in the table, track analysis window opens and the user provides the curved tracks required. The calculations run and provide the wagon’s positions and geometry parameters. These can be shown on a schematic representation as in figure 5 illustrating a representation of two wagons 2 on a rail track 3 for a track analysis result. In this case, the two wagons are 7 connected by a mechanical coupler 21 which decides the connection between the wagons 2 and their relative position, Based on this analysis, it is possible to obtain the dimensions of extreme position assembly. The resulting geometry parameters are automatically transferred to the cable length analysis calculation module 10 to create 3D mockup arrangements. The user must input cable parameters, like the number of jumper cables, diameter of each cable and limits on the bending radius for each cable. A heuristic optimization methodology is run in the background and a final cable length is provided for user perusal. The final result can be summarized in the form of different tables and based on the limit set for each cell, the automatic conclusion is formulated. It is also possible to provide a final recommended tolerance on the calculated cable lengths based on the probabilistic calculation considering every uncertainty and variation. If user opted for the physical testing and validation, a robotic set up code (through G-Code) can be generated from the 3D CAD mock up and relative motion, as will be explained in the following with reference to figure 3. Figure 3 illustrates a representation of a system 17, i.e. a computing system 17, for automatically calculating the length of a jumper cable 1 connecting two train wagons 2 positioned on a track 3. The system 17 specifically comprises a simulation module 5 used for processing the input parameters 4. The simulation module 5 includes a route analysis module 6 for defining a relative position between the track 3 and the train wagons 2, a cable specification configurator module 8 for modelling the stiffness of the cable 1, and a cable length analysis module 10 for generating a 3D cable model. The system 17 additionally comprises an optimization module 11 (not shown in figure 3) configured to process the route analysis output data 7 and the cable specification output data 9 for an iterative optimization of these data. The optimized route data 12 and optimized cable data 13 coming from the optimization module 11 are processed by the cable length analysis module 10 for calculating the length of the jumper cable 1 between two holding points 14 as final output data. In one example, the system 17 can further comprise a document processor module 15 for extracting the input parameters 4 and inputting the extracted input parameters 4 into the simulation module 5. The system 17 can furthermore comprise a cable analysis robot configurator 18 for generating a robotic set up code, in particular through a G-Code, from the 3D cable model for providing physical testing and validation. Also, the system 17 can comprise a report generator module 16 configured for generating a report using the calculated length of the jumper cable 1. It is noted that the activity of these modules, i.e. the simulation module 5, the route analysis module 6, the cable specification configurator module 8, the cable length analysis module 10, the optimization module 11, the document processor module, the report generator module 16 is intended such that these modules are configured to process data, calculate data, output data, etc. Compared to the standard methods for calculating jumper cables length, the present method 100 goes beyond deterministic calculation and expert judgement (e.g. “gut feeling”) for final cable length for a given parameters. With the power of probabilistic distribution it is possible to scientifically determine the necessary and sufficient cable lengths for system of cables (e.g. plurality of jumper cables between locomotives / coaches) In one example, the length of the jumper cable 1 between two holding points 14 is calculated based on the minimum bending radius of the cable 1 and the minimum height of the cable 1 from the track 2 as constraints. Specifically, because of the optimization formulation, the length of the cable 1 is formulated as an objective and minimum bending radius and minimum height from the track are formulated as constraints, wherein these are independent cases. It is noted that lower resolution cameras can be employed as the goal is to capture the entire position rather than extracting certain delicate features. Therefore, the present method 100 can be carried out in a cost-effective manner. With reference to figure 4, the input and output parameters are identified in detail within the simulation and optimization modules 6, 8, 10, 11. The input parameters 4 include train and track parameters. As mentioned above, these parameters include size and dimensions related to the wagons 2 and track 3, such as the wagons length, the wagons width, the distance between wagons 2, the gauge, etc.. In one example, the route analysis output data 7 comprise at least one of the data including the angle between two wagons 2; the maximum and the minimum distance between two wagons 2; and the distances between the upper and lower endpoints of two wagons 2. Also, the cable specification output data 9 can comprise at least the data including minimum static and dynamic bending radius limit of the cable 1, number of cables 1 and parameters of each cable 1, and position of the cable 1. The iterative optimization methodology used in the method 100 involves problem formulations, where all the input parameters 4, track profiles and dynamic scenarios are defined for the length analysis. There are different scenarios as defined below which defines the intent of the optimization. According to an example, the iterative optimization is performed based on predefined constrains. These predefined constrains include at least a given minimum bending radius of the cable 1 for maintaining a safe minimum height of the cable 1 from the track 3. In alternative, the predefined constrains include at least a given length of the cable 1 for obtaining a minimum bending radius of the cable 1 and for maintaining a safe minimum height of the cable 1 from the track 3. In alternative, the predefined constrains include at least a given length of the cable 1 for obtaining the position of the two holding points 14, for maintaining a safe minimum height of the cable 1 from the track 3 and for maintaining the safe minimum bending radius of the cable 1. Based on the intent of the optimization methodology, input parameters 4, objective function and constraints are formulated. In one example, the interactive optimization is performed using the Genetic Algorithm or a gradient based optimization (for faster convergence). The iterative optimization is run until convergence of the results. The major technical element in the method 100 and the system 17 is the development of different analysis modules, as defined above. The document processor module15 extracts the input parameters 4 for the simulation and parses / analyzes the parameters 4 in the simulation module 5 at the backend. The simulation set up comprises of route analysis where the track parameters and train parameters are used to create the relate position and hence the geometry of the locomotive / coaches required for 3D mock ups. Next, the jumper cables 1 are modeled. Depending on the flexibility of the cable 1, it is possible to model the stiffness of the cable using a special beam element called Cosserat rod. Therefore, in one example, modelling the stiffness of the cable 1 by a cable specification configurator model 8 is performed using a Cosserat rod approximation. In this case, discrete beam elements, if modeled high in number with smaller rigidity modulus, can follow the behavior of highly flexible jumper cable 1. In case it is necessary to model a jumper cable 1 with conduit or less flexibility, the cable 1 can be modeled with more rigid beam elements. Here, cable bending limits for static and dynamic condition are also defined with fixed multipliers. These parameters are used to compare the minimum bending radius from the cable length analysis and automatic inference. A final step in the simulation is to create a 3D mock up as per route analysis and generate cable model between defined receptacle position. Based on the optimization methodology defined in figure 6, a maximum length which satisfies all the constraints is chosen for each cable. Then the maximum length is tried to fit for minimum coach positions to validate minimum bending radius and minimum track height. Once all the criteria are met, the final cable lengths are presented for final inference. In order to run a probabilistic simulation instead of a mere deterministic one, the method 100 can comprise generating a set of design of experiment, DOE, for all the input parameters 4 used by the simulation module 5. These parameters are used in the simulation run and final results with variations are summarized with suitable probability distribution. The output distribution on the length of the cable 1, the minimum bending radius and the minimum height of cable 1 from the track 3 are quantified and suitable margins are determined. With the help of these margins, a suitable safe operating range for each jumper cable 1 is determined. This gives an advantage over a standard cable length calculation since all the variation and uncertainties are taken into account in the analysis as in real world operating conditions, for example in case of errors in the parameters due to manufacturing, workmanship (i.e. assembly and labor work). Once the simulation is completed, the final inference and conclusion is automatically written in the report along with the results from each simulation modules with the help of a pre-determined report template. Different results are tabulated automatically and based on different conditions the conclusion remarks are written in the report and made available to the user for download. In one example, the method 100 further comprises providing a final tolerance value on the calculated length of the jumper cable 1 based on the iterative optimization. With reference in detail to figure 6, the entire method 100 with the optimization process of is described. As already mentioned, input parameters 4 can be taken automatically through different ways, i.e. OCR In alternative, the user can input the parameters manually. There are different inputs from different stages of the analysis to be filled by the user. As regards the track analysis, the method 100 allows to model different tracks, track curvatures and S-curves using geometric and algebraic relations. In order to create customized curvature definition, new metro lines and their built depos post new requirements for different curved routes and combinations can be used. As regards the cable simulation, the minimum bending radius considerations are provided based on materials and limit specified by cable supplier (as a user input). In addition, a spline function is generated, this function being as close as the real physics. For example, B-spline, Hermite Spline, and custom interpolation scheme can be used. The cable stock is considered along with the spline. A simple circular spline can be considered with Cosserat rod approximation. This helps in modeling the stiffness of the cable 1 very realistically. If the cable material is highly flexible, it is possible to model Cosserat rod with more element with low stiffness. If the cable 1 is conduit or highly stiff, it is possible to model with less flexible Cosserat rod and beam elements. Also, connectors and support are considered with suitable degrees of freedom. As regards a cable length analysis and validation, a mock-up creation is assembled for dynamic scenarios using automatic measurements from route analysis to assembly mock-up current in CAD-native implementation. Additional deviations are applied from each degree of freedom. The process proceeds with the generation of the lengths for all the cables for straight position under the constraint of static bending radius and the generation of the lengths for all dynamic scenarios under the constraints of dynamic bending radius. The maximum length is obtained for each cable from all the dynamic scenarios and the spline in generated for given length for each cable under the constraints of minimum height from the tracks. The minimum bending radius observed for each dynamic scenario is generated and pivot table is populated. Automatic inference is carried out based on a comparison of data table results. A G-code is generated from connector positions, relative positions from assembly mockup and dynamic cable routing and all configuration are loaded to a simulation software (e.g. KUKA software) for virtual testing. As regards the concept of probabilistic and uncertainty quantification, the track and train (coach) parameters are assumed to have a distribution since exact control of dimension is difficult to fabricate at the scale. Hence this variation is going to affect the cable length calculation. It is noted that by calculating the cable length using probabilistic approach, it is obtained a range (if it is uniform distribution) or mean+ standard deviation (if it is a normal distribution). The cable support is subjected to manufacturing deviation as well; hence the variation in jumper cable holding points 14 plays very critical role in minimum bending radius measurements and minimum height to be maintained from the tracks 3. These two are very important constraints required by the regulations from railways. Hence, a probabilistic distribution can provide the range or the confidence level for safe operation for these cables The cable characteristics are also dependent on material used for outer sheath. The stiffness is also determined with certain degree of certainty. Hence, a probabilistic model comes in handy for modeling cable behavior. Overall for the calculation, by using a probabilistic distribution assumption, it is possible to obtain range or variational cable length. This information can be used to reduce probability of failure in the field. With the present method 100 and system 17 several advantages can be achieved. First, the reuse the knowledge for future iteration and automation can be accomplished, by saving all the input parameters, the constraints, and the resulting output (Cable lengths, minimum Bending radius of the cables and the minimum height from the track). These inputs and results can be used to build an Al model which helps in the future project recommendation system for the same customer (learn from the past calculations / experience) Also, digital web application can be used to capture all the requirements from different levels of system and parse it correctly for dynamic simulations. The version tracking and version management in the web application helps customer to create a different analysis from the base analysis for any small variation in the parameter. This also helps application provider to control the license and charge the end user accordingly. The analysis versioning and iteration tracking can help users to go to a specific change that are made during the simulations. With customer comments and reasoning, helps to provide causality and reasoning from Al models for future iterations. In addition, an automatic export of simulation model (3D CAD) to a robotic set up (Computer Aided Manufacturing) can be done through G-Code export of the path for the Robotic arm movement. Furthermore, the automatic report generation could be very helpful for overviewing calculation and testing correlation. Finally, the method 100 allows a probabilistic approach of uncertainty quantification for all the input parameter variation to the output results distribution. The 5 output distribution on the results also can be used to provide a tolerancing of the final geometry of the jumper cables. Although a variety of techniques and examples of such techniques have been described herein, these are provided by way of example only and many variations and modifications on such examples will be apparent to the skilled person and fall within the 10 spirit and scope of the present invention, which is defined by the appended claims and their equivalents.

Claims

1. Computer implemented method (100) for automatically calculating the length of at least one jumper cable (1) connecting two train wagons (2) of a rail vehicle configured to be positioned on a track (3), the method (100) comprising:processing (S101) input parameters (4) by a simulation module (5) including:defining (S102) a relative position between the track (3) and the train wagons (2) by a route analysis module (6) to obtain route analysis output data (7);modelling (S103) the stiffness of the cable (1) by a cable specification configurator module (8) to obtain cable specification output data (9); andgenerating (S104) a 3D cable model (19) by a cable length analysis module (10); wherein the route analysis output data (7) and the cable specification output data (9) are processed by an optimization module (11) for an iterative optimization of said data, the optimization module (11) outputting optimized route data (12) and optimized cable data (13) and wherein the optimized route data (12) and the optimized cable data (13) are processed by the cable length analysis module (10) providing the length of the jumper cable (1) between two holding points (14) as final output data.

2. Computer implemented method (100) according to claim 1, further comprising: extracting (S105) the input parameters (4) by a document processor module (15) and inputting the extracted input parameters (4) into the simulation module (5); and / or using the length of the jumper cable (1) provided by the cable length analysis module (10) for generating (S106) a report by a report generator module (16).

3. Computer implemented method (100) according to any one of claims 1 to 2, wherein the input parameters (4) comprise train and track parameters including at least one, or a combination of, the following parameters:the wagon dimensions;the wagon position;the inter-wagon distance;the track curvature;the track position; andthe track dimensions.

4. Computer implemented method (100) according to any one of claims 1 to 3, wherein the length of the jumper cable (1) between two holding points (14) is calculated based on the minimum bending radius of the cable (1) and the minimum height of the cable (1) from the track (2) as constraints.

5. Computer implemented method (100) according to any one of claims 1 to 4, wherein the iterative optimization is performed based on predefined constrains, wherein said predefined constrains include at least:a given minimum bending radius of the cable (1) for maintaining a safe minimum height of the cable (1) from the track (3); ora given length of the cable (1)for obtaining a minimum bending radius of the cable (1) and for maintaining a safe minimum height of the cable (1) from the track (3); ora given length of the cable (1) for obtaining the position of the two holding points (14) for maintaining a safe minimum height of the cable (1) from the track (3) and for maintaining the safe minimum bending radius of the cable (1).

6. Computer implemented method (100) according to any one of claims 1 to 5, wherein the route analysis output data (7) comprise at least one of the following data: the angle between two wagons (2);the maximum and the minimum distance between two wagons (2); and the distances between the upper and lower endpoints of two wagons (2).

7. Computer implemented method (100) according to any one of claims 1 to 6, wherein the cable specification output data (9) comprise at least one of the following data: minimum static and dynamic bending radius limit of the cable (1);number of cables (1) and parameters of each cable (1); and position of the cable (1).

8. Computer implemented method (100) according to any one of claims 1 to 7, wherein modelling the stiffness of the cable (1) by a cable specification configurator model (8) is performed using a Cosserat rod approximation.

9. Computer implemented method (100) according to any one of claims 1 to 8, wherein the interactive optimization is performed using the Genetic Algorithm or a gradient based optimization.

10. Computer implemented method (100) according to any one of claims 1 to 9, further comprising extracting the input parameters (4) automatically using an optical character recognition system and a trained artificial intelligence model.

11. Computer implemented method (100) according to any one of claims 1 to 10, further comprising generating a set of design of experiment, DOE, for all the input parameters (4) used by the simulation module (5).

12. Computer implemented method (100) according to any one of claims 1 to 11, further comprising providing a final tolerance value on the calculated length of the jumper cable (1) based on the iterative optimization.

13. Computer implemented method (100) according to any one of claims 1 to 12, further comprising generating a robotic set up code, in particular through a G-Code, from the 3D cable model by a cable analysis robot configurator (18) for providing physical testing and validation.

14. Computer program, comprising instructions which, when the program is executed by a computing device, cause the computing device to carry out the steps of the computer-implemented method according to any one of the claims 1 to 13.

15. Computer readable medium comprising a computer program for carrying out the method (100) according to one of claims 1 to 13.

16. Computing system (17) for automatically calculating the length of at least one jumper cable (1) connecting two train wagons (2) of a rail vehicle configured to be positioned on a track (3), the system (17) comprising:a simulation module (5) for processing input parameters (4) including:a route analysis module (6) for defining a relative position between the track (3) and the train wagons (2) to obtain route analysis output data (7);a cable specification configurator module (8) for modelling the stiffness of the cable (1) to obtain cable specification output data (9); anda cable length analysis module (10) for generating a 3D cable model,wherein the system (17) further comprises an optimization module (11) configured to process the route analysis output data (7) and the cable specification output data (9) for an iterative optimization of said data to obtain optimized route data (12) and optimized cable data (13) and wherein the cable length analysis module (10) is configured to 5 processes the optimized route data (12) and optimized cable data (13) for calculating thelength of the jumper cable (1) between two holding points (14) as final output data.

17. Computing system (17) according to claim 15, further comprising:a document processor module (15) for extracting the input parameters (4) and inputting 10 the extracted input parameters (4) into the simulation module (5); and / ora report generator module (16) configured for generating a report using the calculated length of the jumper cable (1).15

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