EP3789264A1 - Procédé et dispositif par la detection de glissement et véhicule ferroviaire - Google Patents

Procédé et dispositif par la detection de glissement et véhicule ferroviaire Download PDF

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Publication number
EP3789264A1
EP3789264A1 EP20191030.4A EP20191030A EP3789264A1 EP 3789264 A1 EP3789264 A1 EP 3789264A1 EP 20191030 A EP20191030 A EP 20191030A EP 3789264 A1 EP3789264 A1 EP 3789264A1
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EP
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Prior art keywords
speed
function
wheel set
rail vehicle
determined
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
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EP20191030.4A
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German (de)
English (en)
Inventor
Lars Johannes
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Siemens Mobility GmbH
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Siemens Mobility GmbH
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Publication date
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Publication of EP3789264A1 publication Critical patent/EP3789264A1/fr
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B61—RAILWAYS
    • B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L15/00—Indicators provided on the vehicle or train for signalling purposes
    • B61L15/0081—On-board diagnosis or maintenance
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B61—RAILWAYS
    • B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L15/00—Indicators provided on the vehicle or train for signalling purposes
    • B61L15/0058—On-board optimisation of vehicle or vehicle train operation

Definitions

  • the invention relates to a method for determining a correction value with the simultaneous exclusion of slip events on one or more axles of a ground-based vehicle.
  • the invention also relates to a device for carrying out such a method and a ground-based vehicle with such a device.
  • Rail vehicles are ground-based vehicles for which a vehicle speed and a path that can be derived from it must be precisely and reliably determined in manual or automatic driving mode.
  • speed sensors or travel incremental encoders are used, which are assigned to a wheel or wheel set of the rail vehicle in the case of the latter.
  • Such sensors cannot, however, directly detect a skidding or sliding of a wheel, so that the wheel can turn faster or turn slower than the rail vehicle is actually traveling.
  • a speed measured by means of the sensors may not correspond to a current vehicle speed of the rail vehicle.
  • the term "correction factor" is also used synonymously below as the correction value.
  • One object of the present invention is to create a method for slip detection in a wheel set for a rail vehicle, which enables a vehicle speed of a rail vehicle to be reliably and precisely determined and which can help to keep delays in the operation of the rail vehicle low.
  • a method for slip detection in a wheel set for a rail vehicle comprises detecting a plurality of measurement signals from the first and second speed sensors, which are each representative of a speed of the first and the second wheel set of the rail vehicle.
  • the method further comprises determining a respective speed value for the first and for the second wheel set as a function of a respective measurement signal from the first or the second speed sensor.
  • the method further comprises the formation of speed value pairs, each with a determined speed value for the first and the second wheel set.
  • the method further comprises comparing the respective speed values for the first and second wheel sets of a formed speed value pair with one another and determining a uniform correction factor for all determined speed value pairs as a function of the comparison.
  • the method further comprises determining speed deviations based on the uniformly valid correction factor and determining slip of the first and / or second wheel set as a function of the speed deviations.
  • the method also includes determining a plurality of correction factor deviations as a function of the determined correction factors and determining a slip of the first and / or second gear set based on the determined correction factor deviations.
  • a reliable detection of sliding or skidding of a wheel set is possible and it can contribute to an accurate determination of the vehicle speed.
  • the procedure enables a robust relative scale determination or correction factor determination with reliable slip and skid exclusion.
  • Such a correction factor determination takes into account the determined correction factors of various route sections and the speed deviations that arise in the process. In this way, slip areas in the form of outliers based on the calculated speed deviations and correction factors can be reliably identified.
  • the correction factors and correction factor deviations make it possible to determine speed deviations of a wheel set in order to obtain equality with regard to the speed of the wheel sets when using the correction factor.
  • the method includes controlling a vehicle speed of the rail vehicle as a function of the determined slip of the first and / or second wheel set.
  • Controlling the vehicle speed of the rail vehicle can in particular include providing a safety surcharge for a permissible vehicle speed of the rail vehicle as a function of the determined slip, so that the vehicle speed of the rail vehicle is also controlled as a function of the provided safety surcharge.
  • the method includes discarding one of the determined correction factors as a function of the determined speed deviations per correction factor or correction factor deviation between correction factors, and controlling a vehicle speed of the rail vehicle as a function of the remaining correction factors.
  • the determined speed deviations of the calculated correction factors as well as the correction factor deviations make it possible to precisely identify the phases and time ranges in which a wheel slips.
  • a correction factor of about 1.1 there is a speed difference between the two wheel sets that would justify a correction factor of about 1.1. If a correction factor of, for example, 4 is determined for a short time, this correction factor deviates significantly from the others and can be determined as a slip.
  • a uniform correction factor for example 2.55, is determined for the detection and any gaps or deviations in the individual correction factors per difference are shifted into respective speed deviations. The further the deviation from the uniformly calculated correction value, the greater the speed deviations.
  • the successively calculated correction factors for route sections and / or the speed deviations accordingly have a clear peak, which enables reliable slip detection. If the correction factors described were now averaged, this would cause an unjustified adjustment of the vehicle speed. A safety margin would be incorrectly applied to the vehicle speed.
  • the determination of the correction factor comprises a regression analysis.
  • Statistical analysis methods can be used with the aim of achieving the best possible averaging of the specific correction factors, for example by minimizing the speed deviations that occur as a result.
  • Such a regression analysis and adjustment calculation can, for example, be based on the method of least squares.
  • the method comprises specifying a deviation threshold value for a tolerable speed deviation and comparing the determined speed deviations with the predefined deviation threshold value.
  • the method accordingly further comprises determining a slip of the first and / or second wheel set as a function of the comparison of the determined speed deviations with the predefined deviation threshold value.
  • a slip range can thus be identified on the basis of a tolerable speed deviation in the form of a deviation threshold value which should not be exceeded during operation.
  • the first and the second speed sensor each have a path incremental encoder. Accordingly, determining a respective speed value for the first and for the second wheel set comprises providing circumferential values for a wheel of the first wheel set and a wheel of the second wheel set, which one of the incremental encoders is assigned to each. The method further comprises detecting a number of revolutions of the respective wheel of the first gear set and the second gear set and determining a respective speed value for the first gear set and for the second gear set as a function of the respective provided circumferential values and the respective detected number of revolutions.
  • determining a slip of the first and / or second wheel set as a function of the determined speed deviations includes detecting areas of the first and / or second wheel set that are influenced by and not influenced by slip depending on the correction factors determined and / or the determined speed deviations.
  • the control of a vehicle speed of the rail vehicle then also takes place as a function of the identified areas of the first and / or second wheel set that are influenced by and are not influenced by slip.
  • the method includes forming an arithmetic mean of the correction factors determined.
  • a vehicle speed of the rail vehicle is accordingly also controlled as a function of the arithmetic mean of the correction factors that is formed.
  • the identified slip areas are not included in the formation of the arithmetic mean, so that a falsification of the averaging is counteracted.
  • another averaging method or another value formation method can also be used for a summarizing correction factor, so that, for example, a weighting of the correction factors is also taken into account.
  • the arithmetic mean of the correction factors can also be stored for a subsequent travel cycle of the rail vehicle. Controlling a vehicle speed of the rail vehicle then takes place, for example, as a function of the stored arithmetic mean of the correction factors and is loaded, for example, when starting operation and directly included in the control of the vehicle speed.
  • the described method and the described developments of the method enable reliable and precise slip detection on a finely granular level. No additional sensors are required and there is no need for generous safety surcharges, which are included in advance in the speed and path calculation due to a possible occurrence of slip in order to counteract the corresponding sliding or skidding processes. There are therefore no general safety surcharges to be assumed and this can contribute to increased accuracy in determining the vehicle speed of the rail vehicle.
  • the method only requires two path incremental encoders, which are mounted on axles of the rail vehicle that are not mechanically coupled.
  • the vehicle speed and the route for the rail vehicle are determined.
  • data relating to wheel circumferences are provided.
  • the raw data for the calculated speeds of the first and second wheelset recorded by means of the measurement signals of the path incremental encoders deviate from the real vehicle speeds of the rail vehicle. These speed deviations can be accepted up to a given size.
  • the described method and the developments enable a high level of applicability regardless of a vehicle type of a rail vehicle and a route that is traveled by it.
  • the method implements a generic approach and does not require any information about the route, such as longitudinal inclination. Also, no information about a current acceleration or braking process is required.
  • the method described and the developments also provide a high level of acceptance by a user, since no interaction on the part of the user is necessary.
  • the method can in particular be carried out in an automated manner.
  • a gain in performance for adherence to a timetable can be achieved due to reducible delays and higher route utilization.
  • the method provides a clear approach which can contribute to the maintenance-friendly operation of a rail vehicle.
  • the method can be carried out inexpensively.
  • Existing path incremental encoders can be used to carry out the method and the method can be combined with other approaches for the detection of systematic deviations, such as sliding and slipping processes in path incremental encoders.
  • significant cost savings can be made possible.
  • the process is relatively future-proof, as there are few or no returns are to be expected. With returns, among other things, customer-side complaints and manufacturer-side improvements are referred to.
  • the method described contributes in particular to improved accuracy with regard to sliding and skid detection and meets high accuracy requirements with regard to determining the vehicle speed. It enables the evaluation of highly redundant information through adjustment and statistical tests, among other things with the aim of calculating a correction factor with high accuracy and then automatically detecting systematic errors in order to be able to exclude them so that they do not flow into the final correction factor determination. Furthermore, by means of the method described, a flexible target of accuracy with regard to the scale and thus also the speed is possible.
  • Another aspect of the invention relates to a device for slip detection in a wheel set for a rail vehicle, which device is set up to carry out one of the methods described above.
  • the device is implemented, for example, as an on-board computer or control unit of the rail vehicle, which has a computing unit and a data memory and enables the recorded measurement signals and the determined speed values to be evaluated and processed.
  • a device is implemented as a backend or external server unit that can communicate with the rail vehicle using signals.
  • a rail vehicle comprises a first set of wheels and a second set of wheels, which are mechanically decoupled from one another.
  • the wheel sets are coupled via one or more car bodies of the rail vehicle, but there is no direct mechanical coupling between the wheel sets, for example by means of a gearbox.
  • the rail vehicle further comprises a first speed sensor and a second speed sensor, the one are assigned to the respective wheelset.
  • the speed sensors each have a travel incremental encoder and the measurement signals from the speed sensors are each representative of a speed of the first wheel set and the second wheel set.
  • the rail vehicle has the device described above, which is coupled to the speed sensors for signaling purposes.
  • the device and the rail vehicle are set up to carry out one of the methods described above, the described properties and features of the method are also disclosed for the device and for the rail vehicle, and vice versa.
  • Figure 1 shows a schematic side view of a rail vehicle 1 with a control unit 3, which is signal-coupled to a first speed sensor 5 and a second speed sensor 6.
  • the speed sensors 5 and 6 are travel incremental encoders for the wheelsets 7 and 8.
  • the wheelsets 7 and 8 have respective wheels and axles that are not mechanically coupled directly to one another.
  • the speed sensors 5 and 6 enable the acquisition of measurement signals that are each representative of a speed of the first wheel set 7 and the second wheel set 8 of the rail vehicle 1.
  • the path incremental encoders mounted on the axles can usefully be used to generate a to enable reliable and precise detection of sliding and skidding of the wheels of the first and / or second wheel set 7 and 8.
  • a method for slip detection in one of the wheel sets 7, 8 for the rail vehicle 1 can be carried out according to the method shown in FIG Figure 2 or the in Figure 3 flowchart shown in the control unit 3 can be performed.
  • a step S1 a plurality of measurement signals from the first speed sensor 5 and the second speed sensor 6 are recorded.
  • a respective speed value for the first wheel set 7 is determined as a function of a respective measurement signal from the first speed sensor 5 and a respective speed value for the second wheel set 8 is determined as a function of a respective measurement signal from the second speed sensor 6. Furthermore, speed value pairs are formed, each with a determined speed value for the first and the second wheel set 7, 8. If a predetermined number of usable speed value pairs has been determined or formed, the method is continued in a step S3. For example, a measurement signal from the first and second speed sensors 5 and 6 is recorded every half second for a period of one minute, so that 120 speed value pairs are formed.
  • step S3 the respective speed values for the first and second wheelsets 7, 8 of a respective speed value pair formed are compared with one another and a correction factor is determined for all speed value pairs as a function of the comparison.
  • step S4 speed deviations are determined as a function of the determined correction factor.
  • a statistical model can be used for the evaluation.
  • a regression analysis or a compensation calculation takes place in step S4, which is based, for example, on the method of least squares, which carries out a minimization method with regard to the smallest possible deviation of the determined speed deviations with regard to a correction factor for all value pairs.
  • v_messessen_Sensor1_i correction factor * v_messessen_Sensor2_i.
  • the mathematical value "correction factor” is only available once and this is automatically set by the minimization method.
  • step S5 a slip of the first and / or second wheel set 7, 8 is determined as a function of the determined deviations for the measured speeds with respect to a calculated correction factor and the vehicle speed of the rail vehicle 1 is determined as a function of the detected slip, taking into account the previously calculated correction factor controlled.
  • step S1 it is checked whether the default conditions for the variables to be processed are met. If this is not the case, the method is continued in a step S2. If the default conditions are met, the method is continued in step S3.
  • step S3 measurement signals from the path incremental encoders are recorded and speed values are determined for the respective axles or wheel sets 7 and 8. Furthermore, speed value pairs are formed which each contain a speed value for the first and the second wheel set. If a predetermined number of evaluable speed value pairs has been formed, the method is continued in a step S5. Otherwise, the method is ended or started again in step S1.
  • a k PSSA section factor is determined or adapted.
  • the k PSSA section factor represents a correction factor that is calculated for all pairs of measured values, for example 120 pairs of measured values, which form a section, by minimizing the speed deviations with respect to a sensor.
  • v_messessen_Sensor1_i + v_ge messenger_Sensor1_Aberstoffung_i correction factor * v_messessen _Sensor2_i, where "i" runs from 1 to 120, for example.
  • the correction factor k PSSA section factor is estimated or calculated by the adjustment.
  • the acronym "PSSA" refers to the English term “pseudo static scale adjustment" and can be referred to in German as pseudo-static scale adjustment.
  • a step S7 the mathematical and stochastic model on which the adjustment is based is checked.
  • the mathematical model includes the assumption that there is only one scale factor k PSSA-Section for, for example, all 120 speed pairs, and the stochastic model includes that Assumption of the accuracy of the measured speeds.
  • the accuracy of the correction factor calculated from the previous step S5 is compared with a predetermined threshold value. If a desired accuracy is fulfilled and the assumptions in the mathematical and stochastic model are not refuted, the method can be continued in a step S9. If a desired accuracy is not met and / or the assumptions of the model tests are refuted, the method is continued in a step S8.
  • step S8 the current data and determined speed values are discarded.
  • the method is ended and, when new speed values arrive, it is started again in step S1.
  • step S9 it is checked whether kfactorsInSeries are available. For example, kfactorsInSeries has the value 3. If corresponding correction factors that are valid 3 times have been calculated in a row, the method is continued in a step S11. Otherwise, the correction factor k PSSA-Section is stored, the method is ended and then restarted in step S1 when new measured values arrive.
  • the variables kfactorsInSeries represent a number of the successively calculated and valid correction factors.
  • a correction factor is calculated from, for example, 120 pairs of values. It is possible that a valid correction factor was calculated in the first minute and none in the following minute. Then there is a valid correction factor. But you need 3 to progress in the process. In the third minute, for example, a valid one is calculated. If there are 3 it continues.
  • step S11 all possible combinations of two of the determined k PSSA section factors are set up. With three k PSSA section factors there are 3 combinations of two: 12, 13 and 23.
  • a step S13 it is checked whether the calculated correction factors of the respective combinations are the same in the sense of agreeing within tolerable deviations. This includes the comparison of the determined correction factors. If the correction factors match within a predefined tolerance range, the method is continued in a step S15. Otherwise, the method is ended and started again in step S1.
  • Each combination includes two different correction factors that are compared with one another. With a value of 3 for the kfactorsInSeries, there are 3 independently calculated correction factors, which can be created within 3 minutes or extend over a longer period of time, for example 148 minutes.
  • step S15 an arithmetic mean is calculated and the k PSSA factor is provided for a real-time method for slip and skid exclusion.
  • the k PSSA factor is the arithmetic mean of the k PSSA section factors. With a value for the kfactorsInSeries of 3, there are exactly 3 pieces.
  • the method described relates to a quasi-static scaling adjustment and is preferably used in connection with a method for sliding and skidding exclusion.
  • the control unit 3 implements a processing unit which enables the distance incremental encoder to be scaled to a referencing distance incremental encoder.
  • the illustrated algorithmic relationships between various variables are taken into account in the slip detection as follows:
  • the first, topmost graph according to Figure 4 shows the vehicle speed of the rail vehicle 1 over time according to the measurement signals of the first and second path incremental encoder.
  • One the two position incremental encoders act as reference incremental encoders.
  • the second graph according to Figure 4 shows an associated time representation of the calculated k PSSA section factors.
  • the illustration indicates that only speed value pairs are taken into account for further processing which have a value that is greater than a predefined threshold value v PSSA limit .
  • the v PSSA limit is a threshold value.
  • pairs of measured values are only formed if both measured speeds are above this value.
  • a correction factor can be calculated with high accuracy if the vehicle is moving fast enough. If the 120 pairs of measured values of a section were also to be filled at low speeds, the target accuracy for k PSSA factor in step S7 may not be achieved under certain circumstances.
  • the third graph shows whether the k PSSA factors of the combinations are equal (point below the top line) or not equal (point above the top line). Each point stands for a combination.
  • the lower dashes or lines in the lower area of the third graph indicate whether the k PSSA factor is generally valid, see S7, in order to be able to be used for the formation of the combination. If there is no line in the area, this means that the corresponding factor should not be processed any further.
  • the lower line or the lower line is derived from the further graphs, the fourth and fifth graphs, the Figure 4 from. If there are lines below the solid line, a corresponding lower line is drawn in the third graph.
  • the fourth graph shows the statistically determined deviation according to a statistical test based on the results of the least squares method ( ⁇ 2 test). A check for each area is fulfilled when the specified limit or the specified deviation threshold value (visualized by a solid line) is not exceeded by the determined values (illustrated as individual line sections).
  • the fifth graph in FIG. 5, counted from above, shows the accuracy of the k PSSA section factors for each area. A corresponding requirement is met if the accuracy of the k PSSA section factor (individual line sections ) does not exceed a specified accuracy limit for the k PSSA section factor according to the illustrated variable ⁇ kPSSAsection limit (solid line).
  • the sixth graph shows that the k PSSA section factor deviates significantly from zero.
  • the k PSSA section factor corresponds to the correction factor described above.
  • the relationships shown in the third graph are relevant for the method described.
  • the line sections shown below the points show the range of the k PSSA section factors that meet the mathematical stochastic model analysis and a specified accuracy. These k PSSA section factors are used to compare the correction factors. Outliers are discarded and not taken into account.
  • the points associated with the k PSSA section factors are arranged in the third graph below the upper solid line.
  • the areas used for this comparison are the line segments shown below the points that are to be assigned to the k factorsInSeries.
  • the k PSSA section factors are the correction factors; In principle, correction factor deviations are only calculated for non-linear problems in order to iteratively arrive at the correct correction factor. In the present case, however, it is a linear problem, see equation, where the correction factor is is calculated directly. In this calculation, the deviations arise in the measured speeds of a sensor, because there may only be one correction factor for 120 value pairs, for example. These deviations are taken in order to conclude that slip (sliding / skidding) is occurring and the section is then discarded (steps S7 and S8). For example, how much speed is to be added or subtracted from the first sensor, for example, so that the speed of the reference sensor is multiplied by the correction factor.
  • One optimization criterion is the minimization of such deviations to the square. However, other criteria for an optimization calculation are also acceptable, such as absolute values.

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  • Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Health & Medical Sciences (AREA)
  • Biomedical Technology (AREA)
  • General Health & Medical Sciences (AREA)
  • Electric Propulsion And Braking For Vehicles (AREA)
  • Regulating Braking Force (AREA)
EP20191030.4A 2019-09-06 2020-08-14 Procédé et dispositif par la detection de glissement et véhicule ferroviaire Pending EP3789264A1 (fr)

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DE102019213586.2A DE102019213586A1 (de) 2019-09-06 2019-09-06 Verfahren, Vorrichtung und Schienenfahrzeug

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Cited By (1)

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Publication number Priority date Publication date Assignee Title
US20220334142A1 (en) * 2021-04-20 2022-10-20 Siemens Mobility GmbH Sensor arrangement, apparatus for position determination, rail vehicle and method for position determination for a rail vehicle

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Publication number Priority date Publication date Assignee Title
AU2005234619A1 (en) * 2004-11-17 2006-06-01 Alstom Transport Technologies Device and method for controlling the speed of a rail vehicle and system comprising devices of this type
DE102005010118A1 (de) * 2005-03-02 2006-09-14 Knorr-Bremse Systeme für Schienenfahrzeuge GmbH Steuereinrichtung eines Schienenfahrzeugs

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SE423368B (sv) * 1980-09-15 1982-05-03 Volvo Flygmotor Ab Forfarande for att forhindra slirning eller glidning mellan drivhjul och underlag vid serskilt fleraxliga fordonsdrivsystem med hydrostatisk kraftoverforing
DE102010014003A1 (de) * 2010-03-30 2011-10-06 Siemens Aktiengesellschaft Verfahren zum Betreiben eines Fahrzeugs, Anordnung für ein Fahrzeug sowie Fahrzeug
DE102014204814A1 (de) * 2014-03-14 2015-09-17 Bombardier Transportation Gmbh Betrieb eines Schienenfahrzeugs mit Steuerung und/oder Regelung einer Zugkraft zwischen Rad und Fahrschiene
DE102014214652A1 (de) * 2014-07-25 2016-01-28 Siemens Aktiengesellschaft Verfahren und Anordnung zum Überwachen des Fahrzustands eines Fahrzeugs und Fahrzeug mit einer solchen Anordnung

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AU2005234619A1 (en) * 2004-11-17 2006-06-01 Alstom Transport Technologies Device and method for controlling the speed of a rail vehicle and system comprising devices of this type
DE102005010118A1 (de) * 2005-03-02 2006-09-14 Knorr-Bremse Systeme für Schienenfahrzeuge GmbH Steuereinrichtung eines Schienenfahrzeugs

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20220334142A1 (en) * 2021-04-20 2022-10-20 Siemens Mobility GmbH Sensor arrangement, apparatus for position determination, rail vehicle and method for position determination for a rail vehicle

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