This application is a National Phase filing of PCT International Application No. PCT/IB2018/054224, having an International Filing Date of Jun. 12, 2018, claiming priority to Italian Patent Application No. 102017000064371, having a filing date of Jun. 12, 2017 each of which is hereby incorporated by reference in its entirety.
The present invention relates to methods for controlling the adhesion value between the wheels of a railway vehicle and a rail. In particular, the present invention relates to methods for assessment of contamination and cleaning of a rail, in particular, for a railway vehicle.
Electronic systems are installed on board most modern rail vehicles, which typically include wheel skid control subsystems, intended to intervene both when the vehicle is in the traction phase and when it is in the braking phase. These subsystems are known as anti-skid or anti-slide systems, or also WSP (Wheel Slide Protection) systems.
A system for controlling the adhesion of the wheels, as an anti-skid function, according to the prior art, is schematically represented in
In the drawings, only one wheel of each axle is generally illustrated.
The WSP system of
The electronic control unit ECU is arranged to carry out a modulation of the torque applied to each axle according to a predetermined algorithm if, in the case of applying torque during traction or braking in a degraded adhesion situation, the wheels of one or more axles end up in a possible incipient skidding condition. Torque modulation is implemented in such a way as to prevent a total locking of the axles, possibly so as to bring each axle into a situation of controlled sliding with the intention of recovering adhesion and, in any case, for the entire duration of the degraded adhesion situation.
In
It has been found experimentally that the values of δ at the adhesion peaks a1, a2, a3 vary with the change in the adhesion conditions, moving along a curve as indicated at A in
Fm·R=FA·R−J·{dot over (ω)} (2)
where:
FA=μ·m·g (3)
whereby:
Fm=μ·m·g−J/R·{dot over (ω)} (4)
where Fm is the tangential force applied to a wheel by the traction and/or braking system, R is the radius of the wheel, J is the moment of inertia of the axle, m is the mass resting on the wheel-rail contact point, {dot over (ω)} is the instantaneous angular acceleration of the axle.
It is clear that, at the same instantaneous angular acceleration, the maximum applicable force Fm is obtained at the maximum adhesion value μ, i.e. at the points lying on the curve A of
If one decides to slide the axle in conditions such as those corresponding, for example, to point b in
P(δ)=FA(δ)·(Vv−Vr)=μ(δ)·m·g·(Vv-Vr)=μ(δ)·m·g·δ·Vv. (5)
The expression (5) above indicates how an increase of the power applied to the wheel-rail contact point is obtained by increasing δ. This injection of energy causes an overheating of the wheel with a consequent cleaning effect of the point of contact, improving the instantaneous adhesion value μ for the next wheel.
It is moreover known that significant cleaning effects are obtained in case of moisture or rain, while in presence of lubricants or rotten leaves, the cleaning effect is less pronounced.
The current systems for recovering adhesion between wheels and rails impose a fixed sliding value δ, typically between 0.2 and 0.3, the specific value being calibrated in a definitive way during the vehicle approval tests. The selected value of δ is therefore optimized for the type of lubricant used to cause the condition of skidding during the tests, as prescribed, for example, in EN 15595:2009+A1, Railway Applications-Braking-Wheel Slide Protection, para. 6.4.2.1, and is, on the other hand, not optimal for all types of materials that may cause conditions of skidding during the normal service of the vehicle.
The graph of
If, on the other hand, one brings the axles to slide with an adhesion corresponding to the slide δ2 as in
As qualitatively shown in
The above also applies to a vehicle or train with n axles.
Since the curves which express the adhesion u as a function of the sliding δ may not be formulated mathematically in an analytical way and vary continuously with the change in the conditions that cause skidding, the geometry of the contact point, and the external ambient conditions, it is not possible a priori, to calculate analytically the optimal sliding value δ.
However, an excellent adhesion control and possible recovery system should be able to analyze the instantaneous adhesion conditions in real time and verify the trend thereof with the change in δ and identify the value of δ such as to maximize
In order to obviate the disadvantages described above, WO2006/113954A describes a slide control for railway vehicles, implemented continuously over time, which requires the identification, in optimal adhesion conditions, of the parameters necessary in view of the subsequent desired performance in skid conditions. Such method further requires the overall deceleration of the system to be known.
Furthermore, the process of adjusting the optimum sliding values requires significantly long times. This adjustment process being implemented at the beginning of a skidding phase, i.e. when the vehicle is traveling at high speed, the distance covered by the latter is increased considerably.
In addition, the processes and systems realized according to the prior art are based on the assumption that the wheel adhesion curves are always curves having an adhesion peak μp at small sliding values, for example on the order of 1-2%.
Wheel adhesion curves are not always curves having an adhesion peak μp at small sliding values; they may be curves having an adhesion peak μp at higher sliding values, such as values on the order of 20-25%.
Consequently, if one erroneously acts as if the curve is a curve having an adhesion peak μp at small sliding values, that is, a small sliding value is imposed between the wheels and the rails to obtain peak wheel adhesion, the desired benefit is not achieved. In effect, in small slides, this curve, having an adhesion peak of μp at higher sliding values, such as, for example, values on the order of 20-25%, exhibits poor levels of adhesion and poor rail cleaning effects (given that the slide imposed is low).
Therefore, the average adhesion value, considering every single adhesion value of the wheels, will not be the optimal one.
An object of the present invention is to propose a method for assessing the contamination of a rail which allows to determine the position of the adhesion peak along the adhesion curve of the wheels belonging to a plurality of controlled axles of a vehicle and, consequently, to obtain improved control and possible recovery of the adhesion of the wheels of a controlled axle of a railway vehicle, and for better assessing the cleaning effect among various successive axles of a railway vehicle.
The aforesaid objects and other advantages are achieved, according to an aspect of the present invention, by a method for assessing contamination and cleaning of a rail having the features described and claimed herein. Preferential embodiments of the invention are also described.
Further features and advantages of the present invention will become apparent from the detailed description that follows, provided by way of non-limiting example with reference to the drawings.
Before describing in detail a plurality of embodiments, it should be clarified that the present invention is not limited in its application to the details of construction or to the configuration of the components provided in the following description or illustrated in the drawings. The invention may assume other embodiments and may be implemented or achieved in essentially different ways. It should also be understood that the phraseology and terminology have descriptive purposes and should not be construed as limiting. The use of “include” and “comprise” and the variations thereof are to be understood as encompassing the elements stated hereinafter and the equivalents thereof, as well as additional elements and the equivalents thereof.
The method according to the present invention allows to determine the position of the adhesion peak along the adhesion curves of the wheels belonging to a plurality of controlled axles of a vehicle, and, consequently, to obtain improved control and possible recovery of the adhesion of the wheels of a controlled axle of a railway vehicle.
Initially referring to adhesion curves shown in
Defining δp as the sliding value for which the adhesion peak μp is obtained, it is clear that:
In order to maximize the average adhesion of the axles, two factors should be considered when choosing sliding points to make the axles work:
Conversely, in case of an adhesion curve as shown
In such case:
In the case of adhesion curves such as those of
Based on the above concepts, the method for assessing contamination of a rail, particularly for a railway vehicle, comprises the steps of:
The step of determining the trend of the adhesion curve between the wheels W belonging to a plurality of controlled axles An of the railway vehicle and the rail may comprise the steps of measuring the first adhesion value μ1 between the wheels of said first axle A1 and the rail, and the second adhesion value μ2 between the wheels of said second axle A2 and the rail;
By way of example, the first predetermined threshold t1 may coincide with a sliding value of about 5%, and the first sliding value δ1 less than the first predetermined threshold between the wheels of a first controlled axle A1 and a rail may be about 1-2%. The second predetermined threshold t2 may coincide with a sliding value between about 15% and 25%, and the second sliding value δ2, greater than the second predetermined threshold between the wheels of at least one second controlled axle A2 and the rail may be comprised between 20%-25%.
Preferably, the second sliding value δ2 does not exceed a limit sliding value δlimit equal to about 25%.
The method for assessing contamination of a rail, if it has been determined that the adhesion curve between the wheels W belonging to a plurality of controlled axles An of a railway vehicle and the rail is an adhesion curve having an adhesion peak μp at a sliding value greater than the second predetermined threshold t2, may comprise the step of:
On the other hand, the method for assessing contamination of a rail, if it has been determined that the adhesion curve between the wheels W belonging to the plurality of controlled axles An of a railway vehicle and the rail is an adhesion curve having an adhesion peak μp at a sliding value δp less than the first predetermined threshold t1, may comprise the steps of:
The method for assessing contamination of a rail, if it has been determined that the adhesion curve of the wheels W belonging to a plurality of controlled axles An of a railway vehicle is an adhesion curve having an adhesion peak μp at a sliding value δp less than the first predetermined threshold t1, may comprise the step of:
Due to this last step described above, it may be noted that the cleaning effect of the rail that was exhibited in the first axles according to the direction of travel no longer involves an increase in adhesion for the following axles (for example, because now the rail is completely clean), and consequently, it is appropriate to impose on the following axles the sliding value corresponding to the adhesion peak and not a sliding value useful for cleaning the rail.
By way of example, considering the second axle as the previous axle An and the at least one third axle as the following axle An+1, after having imposed a second sliding value δ2 greater than the second predetermined threshold t2 between the wheels of all the controlled axles and the rail, due to the non-predominance of the value of the adhesion difference Δμclean generated by the cleaning effect of the wheels with respect to the value of the adhesion difference Δμslide multiplied by an adaptive factor Fad, a first sliding value δ1 may be imposed less than the first predetermined threshold t1 between the wheels of the axles following the third and the rail, if the adhesion value μ2 of the wheels of the second axle A2 (previous axle An) coincides with the adhesion value μ3 of the wheels of the at least one third axle (following axle An+1).
By way of example, the method for assessing contamination of a rail may be repeated after a predetermined time interval (for example every 30 seconds) or it may be repeated after a predetermined distance has been traveled by the railway vehicle.
The present invention comprises moreover a method for assessing cleaning of a rail for a railway vehicle, comprising the steps of:
The aforesaid step of determining the effectiveness of the cleaning of the rail may comprise the steps of:
In the following is reported by way of example, an illustrative case wherein the total number of axles of the railway vehicle is four.
Considering
The adhesion μ1 available for the first axle δ1 is not influenced by the cleaning, such axle being the first to encounter the rail. The adhesion μ1 depends only on the conditions of the rail, i.e. the ambient/contaminant conditions that will be indicated in the following with “amb”.
The adhesion μ1 engaged by the first axle is a function of the local sliding δ1 of the first axle on the rail:
μ1=f(μmax,δ1)=f(amb,δ1)
Conversely, the adhesion μ2 available for the second axle depends on the cleaning produced by the previous first axle (Δμ12).
μ2,max=μmax+Δμ12
The cleaning produced by the first axle in favor of the second axle Δμ12 is a function of the sliding δ1 of the first axle on the rail, as well as of the cleaning characteristics typical of the contaminant (contaminant more or less easy to remove with the same sliding), which are indicated hereinafter with the term “cleaning”.
μ2,max=μmax+f(clean,δ1)
The adhesion μ2 engaged by the second axle is a function of the local sliding δ2 of the second axle on the rail.
μ2=f(μ2,max,δ2)=f(amb,δ1,cleaning,δ2)
Likewise, the adhesion μ3 engaged by the at least one third axle depends on the local sliding δ3 and on the cleaning produced by the previous axles, hence by δ1, δ2 and by cleaning.
Likewise, the adhesion μ4 engaged by the fourth axle depends on the local sliding δ4 and on the cleaning produced by the previous axles, hence by δ1, δ2, δ3 and by the cleaning.
According to these considerations:
μaverage=¼*(f(amb,δ1)+f(amb,δ1,δ2,cleaning)+f(amb,δ1,δ2,δ3,cleaning)+f(amb,δ1,δ2,δ3,δ4,cleaning))
In the case of an adhesion curve such as the one illustrated in
Δμ12=Δμ23=Δμ34=0
and therefore
μ2,max=μ3,max=μ4,max=μ1,max
All the axles thus find the same adhesion as the head axle finds (first axle in the direction of travel), as no axle cleans the rail.
Thus:
μaverage=μ1,max
In the case of an adhesion curve such as that of
With reference to
Δμ12=Δμ23=Δμ34=Δμclean
Therefore:
μ2,max=μ1,max=Δμclean
μ3,max=μ2,max=Δμclean=μ1,max=2*Δμclean
μ4,max=μ3,max=Δμclean=μ1,max=3*Δμclean
At the same time, each axle, sliding at a δ far from the peak value δp, will not exploit all the locally available adhesion μ.
With reference to
μ1=μ1,max−Δμslide
μ2=μ2,max−μΔslide=μ1,max+Δμclean−Δμslide
μ3=μ3,max−μΔslide=μ1,max+2*Δμclean−Δμslide
μ4=μ4,max−μΔslide=μ1,max+3*Δμclean−Δμslide
Calculating the average adhesion of the vehicle:
μaverage=μ1,max+3/2*Δμclean−Δμslide
Comparing the average adhesion obtained in the case of an adhesion curve such as the one illustrated in
In the examples given above, the adaptive factor is equal to ⅔. For example, in the case of five axles, the adaptive factor is equal to ½.
In the case of adhesion curves such as those of
According to such management of the sliding points we have (see
μ1=μ1,max
μ2=μ1,max+Δμclean
μ3=μ1,max+2*Δμclean
μ4=μ1,max+3*Δμclean
Thus, the average vehicle-level adhesion is:
μaverage=μ1,max+3/2*Δμclean
From the analysis of the preceding cases, (case of an adhesion curve such as the one illustrated in
FACTOR 1: Type of adhesion curve: i.e. if the adhesion peak is obtained for small sliding values (
FACTOR 2: Δμslide (parameter defined only for the curve illustrated in
FACTOR 3: Δμclean, i.e. the effectiveness of the cleaning effect from which the axle (n+1) benefits when the axle n is made to slide with a slide greater than the second predetermined threshold t2, close to δlimit.
In the case of a railway vehicle moving on rails, the assessment of these three factors and the consequent choice of the sliding point, according to the criteria described above, must take place in real time during the braking of the vehicle in order to maximize the average adhesion engaged by the vehicle, thereby maximizing the deceleration of the vehicle and thereby minimizing the stopping distance of the vehicle.
To assess the effectiveness of cleaning (FACTOR 3) it is therefore necessary to impose a significant slide, i.e. a slide greater than the second predetermined threshold t2 (δ≈δlimit) on the axle n and to verify the potential gain of adhesion on the axle (n+1).
At the same time, by sliding the axle with a slide greater than the second predetermined threshold t2, close to δlimit, the rail conditions are modified for the following axles and it becomes impossible to assess the adhesion value relative to small slides, i.e. with a slide less than the first predetermined threshold t1 (δ<5%). Therefore, factors 1 and 2 cannot be assessed.
The object of the invention is to manage the sliding of the vehicle axles as follows:
The first axle, the head axle, is controlled in a small slide. In this way, by measuring the adhesion engaged by the first axle, the adhesion value relative to small slides is obtained
μ1=(1−2%)
without producing cleaning, i.e. without changing the characteristics of the rail for following axles.
The second axle, on the other hand, is controlled in a significant slide, i.e. greater than the second predetermined threshold t2. In this way, by measuring the adhesion engaged by the second axle, the adhesion value relative to large slides is obtained
μ2=μ(20%)
producing a possible cleaning for the following axle, cleaning that will depend on the characteristics of the contaminant (cleaning factor 3).
The third axle is controlled at the same sliding value imposed for the second axle.
In this way, by measuring the adhesion engaged by the third axle, it is possible to assess the effectiveness of the cleaning by calculating the cleaning factor:
Δμclean=μ3−μ2
Moreover, by comparing the measured adhesion for the first and second axles, the type of adhesion curve may be determined (FACTOR 1) and possibly Δμslide (FACTOR 2) may calculated.
If (μ2>μ1), it is a case of an adhesion curve of the type illustrated in
The most appropriate choice is therefore that of bringing all the axles into large slides, that is to say, a sliding greater than the second predetermined threshold t2 (δ≈20%≈δlimit);
If (μ2>μ1), it is a case of an adhesion curve of the type illustrated in
Δμslide=μ1−μ2
At this point, noting all the factors, one may choose the optimal sliding point:
If (Δμclean>⅔*Δμslide)
the most appropriate choice is therefore that of bringing all the axles into large slides, that is to say, a slide greater than the second predetermined threshold t2 (δ≈20%≈δlimit);
if (Δμclean<⅔*Δμslide):
the most appropriate choice is to control the axles on the adhesion peak, i.e. with a slide less than the first predetermined threshold t1 (δ<5%).
The principle of the invention remaining the same, embodiments and details of construction may be varied with respect to those described by way of non-limiting example, without thereby departing from the scope of the invention as described and claimed herein. It is understood, moreover, that each embodiment may be combined with any other embodiment.
Number | Date | Country | Kind |
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102017000064371 | Jun 2017 | IT | national |
Filing Document | Filing Date | Country | Kind |
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PCT/IB2018/054224 | 6/12/2018 | WO | 00 |
Publishing Document | Publishing Date | Country | Kind |
---|---|---|---|
WO2018/229638 | 12/20/2018 | WO | A |
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20190001822 | Tione | Jan 2019 | A1 |
20190111951 | Tione | Apr 2019 | A1 |
20200101993 | Frea | Apr 2020 | A1 |
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102006057813 | Jun 2008 | DE |
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Number | Date | Country | |
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20200101993 A1 | Apr 2020 | US |