Braking systems and methods for determining dynamic braking data for a braking model for a train.

(54) Title: BRAKING SYSTEMS AND METHODS FOR DETERMINING DYNAMIC BRAKING DATA FOR A BRAKING MODEL FOR A TRAIN.

(54) Title: BRAKING SYSTEMS AND METHODS FOR DETERMINING DYNAMIC BRAKING DATA FOR A BRAKING MODEL FOR A TRAIN.

(57) Summary

A computer implemented method of determining dynamic braking data for use in a braking model of at least one train is described. The method includes: (a) determining at least one initial safety factor; (b) determining at least one dynamic braking adjustment factor based at least partially on (i) the expected dynamic braking force, and (ii) specified train retarding forces; and (c) determining at least one new safety factor based at least partially on the at least one initial safety factor and the at least one dynamic braking adjustment factor. Braking systems including dynamic braking are also described for a train that has at least one locomotive.

(57) Abstract

Disclosed is a computer-implemented method for determining dynamic braking data for use in a braking model of at least one train, the method including: (a) determining at least one initial safety factor; (b) determining at least one dynamic braking adjustment factor based at least partially on (i) the expected dynamic braking force, and (ii) specified retarding torces of the train; and (c) determining at least one new safety factor based at least partially on the at least one initial safety factor and the at least one dynamic braking adjustment factor. Also disclosed are braking systems including dynamic braking for a train having at least one locomotive.

IMPl £

<img file="MX359353B_D0001.tif" />

PATENT TITLE No. 359353

Headlines):

WABTEC HOLDING CORP.

Home:

Denomination:

Classification:

1001 Air Brake Avenue, Wilmerding, Pennsylvania, 15148, USA

BRAKING SYSTEMS AND METHODS FOR DETERMINING DYNAMIC BRAKING DATA FOR A BRAKING MODEL FOR A TRAIN.

CIP: B60T8 / 1 ?; B6af1772Í; ^ 0qp &lt;/ 00,

CPC: B60J8 / 170! S&gt; Bé0T17 / 2¿8 ',;

Inventors):

JAMES A..QSWALD; DENNIS ^ • SUTMERLAND

Number:

MX / a / 2014/001217

SOLKMYye / i.

: 29 ^^ 1: 0 ^ 2 ^ 4 '' i

Hour:

16:32 •&gt; Ncty · · demayode 2013

Number:

61/824,569

Country:

US

Validity: Vajtiteños · ')' í and '' ú ¡^!^F ' » _kJ * ·, 'v I

Expiration Date: January 29, 2034,

Issue Date: from seaUoníbre 2018 &lt;. &lt;&gt;.

The patent of reference with fundáffierito in adulos 1 laJ ^ ey de la Rfopjfe ^ Industrial.

.k. . of twenty-one ^ c ^ ftn extendable, counted to

In accordance with the haughtiness of the Property Law I as of the date of preserraséÉ 06 the soliiSbrfyeatfirá $ j0ta áfpS ^ WMfe'plrifa pat |) j | 0ffaqqryl§eijJ | p4&gt; 3 dereclíps ,,

Who subscribes to the present lotricko title based on lo 'üteiuesi. pej Lt ^ ír ^ l4fc 6 ° fraocKi ^ lll and 74Sts 2 of the Industrial Property Law (Official Gazette of the Federation φοϊφΐ! r 27 / SeñSÍdi; * '^) nnAa βΡ $ ά »&lt;1994. 10/25/3996, 12/26/1ί &amp; 7; Λ7Λ5 / 1999. 01/26/2004, 06/16/2005. 01/25/2006, 05/06/2009, 06/01/2010 ^ ra ^ / too¿28 / 06 / 3M »27 / fe / 20la; 0®o | t / 2012,, ei / 0 | ^ í % y 13¡03to) &lt;á ^ tofqtílos 1 °, 3 ° fraction V subsection a), 4 'and 12 ° fractions I and II! del Reglameháo'dal iiSpti ^ to MftX / éanó-dfli | a Property Indys ^ idí (DWF 14 / h? / Í₍099) timed on 07/01/2002, 07/15/2004, 07/28/2004 and 09/07/2007); 1st articles. 3 °, ¡ÍÜfWracotj ^ i tfanclso a ^ M®sbaaae »» s I yl) i-y30, del Watul0 »®Tgán¡co of the Mexican Institute of Industrial Property (DOF 12/27/1999, retoffnajle ^ f WWX26f ^ ^ S7 / ^) 04, 04/08 / 2je4 and 33 / Ο9Ώ0Ο7 ·) ·_Μone °, 3 'and 5 ° clause a) of the Agreement that delegates powers to the Deputy Directors General. Wp ^ eadqfcfMeiOMa Of^{| kitchens} Regional, Divisional Deputy Directors,

Departmental Coordinators and other subordinates'ifóliftigtidiiKi MeSgjiaó ¿

07/29/2004, 08/04/2004 and 09/13/2007).

nte jiatentejitíhg *)

I (DOF 12/15/1999, amended on 02/04/2000,

This letter is signed with an advanced electronic signature (FIEL), based on articles 7 BIS 2 of the Industrial Property Law; 3rd of its Regulations, and 1 section III, 2 section V, 26 BIS and 26 TER of the Agreement establishing the guidelines for the use of the Electronic Payment and Services Portal (PASE) of the Mexican Institute of Industrial Property, in the procedures indicated.

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DIVISIONAL DIRECTOR OF PATENTS NAHANNY CANAL REYES

Original string;

NAHANNY MARISOL CANAL REYES | 00001000000403252793 | Tax Administration Service | 1695 || MX / 2018/81862 | MX / a / 2014/001217 | Normal Patent Title | 1223 | GAGV | Page (s) | kOo / 6SbvALzXtCGEzmd / pKSKVSM =

Digital stamp:

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Mfs / KJC7356OF2Y4cxBW¡mqP86GtyzvUhn0q / + J9nrH9THextirkizKS9mL5NXjEww / sqCw / BaX1APfVBXkpZpBa0f

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9zc6hqywn ++ Yh + rQCJ8Wrx4RVQ5v9uJaD9qPS6 + Zr + QZQ / 82jOm5bNNxkufKQHMPgRIDXs5Q ==

Ai &lt;? .- i-.ai No. 550, I 'ico 1, Pueblo Sarita Mana (apopan, Xocliimilix, 16020, Mexico City.

(55) 53340700 toa »gob mx /&gt; mpi

<img file="MX359353B_D0003.tif" />

MX / 2018/81862

IMPI © oV

353353 Mexican INSTrryro, DE LA ---- BRAKING SYSTEMS AND METHODS FOR

<img file="MX359353B_D0004.tif" />

DYNAMIC BRAKING DATA PARÁTIM MUDELO BRAKING FOR A TRAIN

CROSS REFERENCE TO RELATED REQUESTS

This invention claims the benefit of US provisional application No. 61 / 824,569, filed on May 17, 2013, which is incorporated herein by reference in its entirety.

BACKGROUND OF THE INVENTION

Field of the Invention

The present invention relates generally to train braking and control systems, and in particular to braking systems and methods for determining dynamic braking data and information for use in a braking model or algorithm in an operating train.

Description of the related art

As known in the art, trains, which include at least one locomotive and typically multiple wagons, employ complex braking systems and arrangements to slow or stop the train in a variety of conditions and environments. Existing braking is shown and described in US Publication No. 2007/0142984 and US Patent No. 8,019,496; 6,314,358; 5,744,707; 4,562,543; 4,384,695; 4,235,402; 4,005,838; 4,005,837;

3,921,946; and 3,731,193. In addition, many train systems and networks use some form of computer controlled train management, such as a Positive Train Control (PTC) system (for example, the IETMS® from Wabtec Corporation). These computer controlled train management systems have on-board computers or controllers that are used to implement certain train control and management actions to ensure safe and effective train operation.

In addition, the computerized braking control system of the train management system uses a braking model or algorithm to construct or determine stopping distances while the train is traveling or traveling through the train network. These stopping distances are based on certain operating parameters based on specified trains and / or variable feedback from a number of sensor systems and / or auxiliary measurements or determinations, for example, grade of track, track curvature, train speed, weight train pressure, brake line pressure, brake system reservoir pressures, and the like. Consequently, the braking model must compensate for these different parameters, but must also compensate for the variation in the parameters

<img file="MX359353B_D0005.tif" />

OF INDUSTRIAL PROPERTY

<img file="MX359353B_D0006.tif" />

of the system while providing aNcttistaaoraNde ^Γ flf I Á MíWbPAn that has a very low probability of stopping the train beyond the selected location.

As also known, these stopping distances are used to construct a braking profile or curve that estimates or predicts when the train will stop, such as at a specified target point or area that is positioned ahead of the train. This braking profile is continually calculated using the braking model and using changing feedback and variable determinations to provide an updated braking profile or curve ahead of the train. In general, this braking profile or curve visually illustrates to the train operator whether the train is predicted to stop if a full service preventive brake application is started. Again, this braking profile or curve is continually updated (eg 1-3 times per second) so that the operator has a continuous understanding of how and when the train will stop during a preventive braking situation.

The braking model or algorithm is initially developed by running a multitude of scenarios under a wide variety of conditions and states related to all aspects of the train and its projected surrounding environment. In addition, and based on certain rules and / or regulations, a safety factor is determined for

<img file="MX359353B_D0007.tif" />

What last '' '' ffffefan ensure up to a specified probability required detection will be safely near όε1'ΤΈ] Τ £ ΓνοΤ'Πνΐ1? · ^ ύΠ73Γ ~ - ”during a preventive brake application, the braking model continues to monitor and predicting the stopping distance to the specified 5 target location. Although a prediction that the train will stop before or at the target location may not present a significant safety aspect, a predicted stop after the target location could prove to be problematic or unsafe.

To provide additional braking capacity and functionality, many trains are equipped with a Brake System.

Dynamic, which uses the traction motors of a train car as generators during the braking process. Specifically, this Dynamic Brake System provides additional braking force for the train by turning the motors that drive the wheels on generators and transferring power on resistors. In the past, and as described, the PTC braking model or algorithm has been developed to safely predict the stopping distance and characteristics of a train such that the PTC system can prevent the train from exceeding any speed restrictions. or limitation by authorities. Through years of development, this braking model or algorithm has been refined to achieve accurate results within the requirements for safe operation.

IMPI

<img file="MX359353B_D0008.tif" />

"MEXICAN INSTITUTE" f.

However, a force that is never compensated is the total dynamic braking forces produced by it ·; pnr the locomotive unit. Dynamic braking force has been largely excluded based on guidance from the Federal Railroad Administration (FRA) and its belief that it could not be safely compensated for or relied upon. The downside to train operators is that by excluding dynamic braking force, the PTC system becomes very conservative, and can reduce overall speed on the rail track due to excessive alerts and / or unnecessary law enforcement. Therefore, compensating for dynamic braking force in the PTC braking model or algorithm has the potential to improve emission from the rail network and reduce annoying warning and enforcement events for crews who are properly handling their train.

BRIEF DESCRIPTION OF THE INVENTION

Generally, braking systems and methods are provided to determine or derive accurate dynamic braking data for a train braking model that address and / or overcome some or all of the deficiencies and disadvantages identified above associated with existing train braking systems and System of

IMPI computer controlled train handling. "

MEXICAN INSTITUTE

<img file="MX359353B_D0009.tif" />

e provide braking systems and methods for determining or deriving accurate dynamic braking data for a train braking model that provide a more accurate braking model or algorithm for use in a train management system. Preferably, braking systems and methods are provided to determine or derive accurate dynamic braking data for a train braking model leading to a more productive train management system and improved railroad track emission.

Accordingly, and in a preferred and non-limiting embodiment, a computer-implemented method is provided for determining dynamic braking data to be used in a braking model of at least one train. The method includes: (a) determining at least one initial safety factor; (b) determining at least one dynamic braking adjustment factor based at least partially on (i) the expected dynamic braking force, and (ii) specified train retarding forces; and (c) determining at least one new safety factor based at least partially on the initial safety factor and the dynamic braking adjustment factor.

In another preferred and non-limiting embodiment, a braking system is provided that includes dynamic braking for a train having at least one locomotive with at least one computer at

<img file="MX359353B_D0010.tif" />

board configured or programmed to: (a) s a braking event, determine, detect and / or measure the operating status, performance, available force and / or condition of at least one of the following: (i) at least one locomotive ; (ii) at least one locomotive unit; (iii) at least one component of a dynamic brake system, or any combination thereof; and (b) adjust at least one variable of the on-board braking model based at least partially on the determined, detected and / or measured operating state, performance, available force and / or condition.

In a further preferred and non-limiting embodiment, a braking system is provided that includes dynamic braking for a train having at least one locomotive with at least one on-board computer configured or programmed to: (a) before or for at least one braking event, determining predicted acceleration or deceleration of the train based at least partially on an on-board braking model; (b) during the at least one braking event, determine the actual acceleration or deceleration of the train based at least partially on detectable, measured and / or calculated operating conditions; and (c) adjusting at least one variable of the on-board braking model based at least partially on a specified difference between the predicted acceleration or deceleration and the actual acceleration or deceleration.

<img file="MX359353B_D0011.tif" />

IMPI

These and other characteristics and fun'STüñffiáioi ^ ADl

INDUSTRIAL invention, as well as the methods of operation and functions of the related elements of structures and the combination of parts and manufacturing economies, will become more apparent after consideration of the following description and the appended claims with reference to the accompanying drawings, all which form a part of this description, where equal reference numbers designate corresponding parts in the different figures. However, it should be expressly understood that the drawings are for purposes of illustration and description only and are not intended to be a definition of the limits of the invention. As used in the description and in the claims, the singular forms of "one", "one", "he and" the "include plural referents unless the context clearly dictates otherwise.

BRIEF DESCRIPTION OF THE DRAWINGS

Fig. 1 is a flow diagram of one embodiment of a train braking system and method in accordance with the principles of the present invention.

IMPI

Figure 2 is a schematic diagram W ^ 3J $$ g $ g

INDUSTRIAL

<img file="MX359353B_D0012.tif" />

of a train control and braking system according to the principles of the present invention.

Figure 3 is a schematic diagram of a computer and network infrastructure according to the prior art.

DETAILED DESCRIPTION OF THE INVENTION

For the purposes of the description hereafter, the terms "extreme", "upper", "lower", "right", "left", "vertical", "horizontal", "up", "down", "lateral" , "Longitudinal" and derivatives thereof will refer to the invention as it is oriented in the drawing figures. However, it should be understood that the invention may assume other variations and alternate step sequences, except where otherwise expressly specified. It should also be understood that the specific process devices illustrated in the accompanying drawings, and described in the following description, are merely exemplary embodiments of the invention. Therefore, specific dimensions and other physical characteristics related to the modalities described here should not be considered as limiting.

ΙΜΡΪ

As used herein, the terms mm ^ ^ or ^ .ünfeíkáfen '^ / ^r INDUSTRY! '' Communicate '' refers to the reception, transmission or transfer of one or more signals, messages, commands or other data. That a unit or device is in communication with another unit or device means that the one unit or device is capable of receiving data from and / or transmitting data to the other unit or device. A communication can use a direct or indirect connection, and can be wired and / or wireless in nature. Furthermore, two units or devices can be in communication with each other even though the transmitted data 10 can be modified, processed, routed, etc., between the first and second unit or device. For example, a first unit may be in communication with a second unit even though the first unit passively receives data, and does not actively transmit data on the second unit. As another example, a first unit may be in communication with a second unit if an intermediate unit processes data from one unit and transmits the processed data to the second unit. It will be appreciated that numerous other arrangements are possible. Any electronic communication protocols and / or algorithms can be used such as, for example,

TCP / IP (including HTTP and other protocols), WLAN (including 802.11 and other radio frequency based protocols and methods), analog transmissions and / or the like. In addition, a variety of wired or wireless network devices can be used, including,

ΙΜΡΙ 0¾¾ but not limited to, a wireless network device »^^, ^ spelM} a ^ e wired network, a WiFi network device, _ a disnositivn 4_MrodBluetooth, a Zighee network device, a WirelessHART network device, a GPRS network device, an ultra-broadband network device, a wired network device, a broadband network device, a network device various radii, and the like.

As described, a main aspect of using dynamic braking is that force is not guaranteed as being present throughout a braking event. This force may be limited or non-existent due to mechanical failure, or intentional or unintentional deactivation. Unlike an air brake prevention, the crew could potentially manipulate dynamic braking force during a preventive stop. Since it is a retarding force, if the braking model or algorithm includes the force, and is not present or reduced in any way, the braking model or algorithm may not be accurate, leading to a greater potential to allow excessive speed or target override, which negatively impacts the security performance of the system. Accordingly, the present invention is directed to braking systems and methods for determining dynamic braking data for a train braking model, as shown in certain preferred and non-limiting embodiments, and in flow diagram and schematic form, in Figures 1 and 2.

<img file="MX359353B_D0013.tif" />

ΙΜΡΪ

Dynamic braking force is ^ íwuti

INDUSTRIAL dynamic locomotive traction motors in Exu generator this configuration, the generator will rotate freely until connected to a resistive load. When a generator is connected to a load it requires a mechanical force to rotate the generator, and this mechanical force is supplied by the moving locomotive. Consequently, the speed of the locomotive is retarded by this generated force, and the resulting energy is converted into heat in the resistive load. Existing dynamic braking systems and arrangements exhibit several practical and implementation constraints. First, the locomotive must be moving at a minimum speed. Above a certain maximum speed, there is no practical method of absorbing energy. For example, a particular locomotive can generate zero dynamic braking force below 5 km / h. Between 5 and 16 km / h, it can produce from 0 to

4,530 kilograms of force per traction motor, based on linear interpolation. Between 16 and 48 km / h the locomotive can produce about 4,530 kilograms of relatively constant force per traction engine. From 48 to 64 km / h, the force can again be linearly lowered to 0 kilograms. These intervals and speed forces 20 vary by locomotive model. As is known, the engineer has a control that can vary the dynamic brake application ratio from 100%. The “expected dynamic braking force” is therefore a function of the locomotive type, the number of locomotives, the number of

IMPI traction motors, current speed and dynamic braking control adjustment by engineer .____________

As used hereinafter, various terms may be defined or expressed as follows, without limitation. "Forces of

Total Delay ”may include: (1) Force of Degree - the force of gravity acting on the mass of the train going up a hill; (2) Curvature Force - friction of the side wheels as the train passes through curves; (3) Aerodynamic Force - the shape and contour of wagons and locomotives produce a force as a function of speed; (4)

Friction Force - mechanical friction of wagons and wheel bearings; and (5) Dynamic Brake Force - the forces generated by the dynamic brakes.

"Total Axis Count" refers to the sum of all axles that could produce dynamic brake force. For purposes of the present invention, and in a preferred and non-limiting embodiment, the total axle count is the product of the number of "Locomotives

Activated ”by the“ Axes by Locomotive ”. In another preferred and non-limiting modality, the "Total Axis Count" can be a sum of products. For example, two six-axle locomotives and two 20-axle box locomotives would be (2 * 6) + (2 * 4) = 20.

<img file="MX359353B_D0014.tif" />

ΙΜΡΙ®5 instituto mexican;

OS THE PROPERTY

Locomotive Activated ”refers to a locomotive wen tá-u that the operational controls of the locomotive are adjustable to produce dynamic braking force when requested. The opposite state is a "Deactivated Locomotive", which may physically be on the train, but when electrical problems, mechanical problems, operating policies and / or rules on the tracks can be reduced in an operational state for that locomotive that is known. it cannot produce a dynamic braking force. "Axis per Locomotive" refers to the count of axes on a per locomotive basis. Most locomotives have an axle drive motor (although other configurations are possible). Some locomotive manufacturers allow the deactivation of individual traction engines. Other locomotive manufacturers allow the deactivation of all traction engines in a bogie. As is known, all rail vehicles are limited to 32 tons (70,000 pounds) of axle weight. If this limit is exceeded, the rail can be crushed. Therefore, if a locomotive weighs 207 tons (414,000 pounds), it must have 414,000 / 70,000 = 5.91 axles (6 axles). This number of axles will determine the number of traction motors, and the resulting possibility of producing dynamic braking force.

"Dynamic Brake Axle Count" refers to the number of dynamic brake axles used in a particular calculation (in

IΜ ΡI

INSTITUTO MíXICang time) of dynamic braking effort (or force di ^ mfro4} '

The acceleration calculation results pnfwUMi tnriiirirgi »where the" Dynamic Brake Axis Count "remains the same, increases or decreases, as otherwise described herein. "Maximum Dynamic Axis Count per Rule" refers to the maximum allowable dynamic axis count. In particular, too much dynamic braking force in a locomotive can cause excessive or unsafe forces to develop in train cars. Some newer locomotives can produce more dynamic braking force than their physical axle count would indicate. When a locomotive power unit is assigned to a train, a railroad typically takes into account certain factors. Depending on the track classification system, a range from 24 axles to 28 axes is included in a rule for assigning locomotives to a train. For normal extended span dynamic brakes and a railroad with a maximum of 24 axles, six four-axle locomotives or 4 six-axle locomotives (or other combinations) could be considered as the maximum number of locomotives allowed to be in the locomotives with dynamic brake axle regulation. New locomotives with six highly effective dynamic brake axes can be rated as having twelve equivalent axles of normal dynamic brake effort. In this case, two of these locomotives could have all their dynamic brakes adjusted to meet a maximum 24-axle rule.

<img file="MX359353B_D0015.tif" />

IMPI

MIXICAN INSTITUTE ^N lihLA üUOITWAb ^T. »" Count of Axes of Decreased Capacity wogtfTfefieré-the dynamic axes that are excluded from the algorithm or 4 © t © fmÍTratfÓm7 as described hereinafter. When the acceleration calculation leads to the determination or prediction that too much dynamic brake force is or will be present, one or more dynamic brake axes are excluded from the determination, and added to the axle count of decreased capacity. Additional determinations can be maintained, added to, or subtracted from the axle count of decreased capacity. "Dynamic Axle Braking Force" is the expected or determined dynamic braking force on a per axle basis. The individual traction motor on each axle is the lowest unit of measure for which a dynamic braking force is either available or not available. At this level, the generated dynamic braking force is a function of the original design and speed of the train, that is, the expected dynamic braking force. At 100% drive, and in the most effective speed range, 4,530 kilograms of dynamic braking force are typical.

“Dynamic Braking Excitation Measurements” refer to determinations or measurements that relate to dynamic braking excitation. All locomotives in a unit must be involved in the same operation, controlled by the locomotive engineer. To facilitate this, and as it is known, there exists v IM PI faith,

MEXICAN INSTITUTE,, OF THE PROPERTY vS7r £ jg&gt;

one 27-terminal multi-unit cable qtí ^ Sbnecta ^ rra locomotive to the next. This cable intercon'éXlflfl 'and éT'aiWBráaó'eír each locomotive are collectively called the train line (TL). In one embodiment, train line 21 controls the excitation of dynamic brakes. The voltage on the TL varies from 0 to 74 volts. Whatever this voltage is, all locomotives respond in a similar way. If the voltage is 0 volts, the engineer's control lever is set to request 0% of the available dynamic brake force. If the voltage is set to 74 volts, the engineer's control lever is set to request 100% of the available dynamic brake force. The voltage at TL 21 is continuously detected to determine the expected percentage of dynamic brake force to use based on current speed.

The present invention is directed to braking systems and methods for determining dynamic braking data for a train braking model. The systems and methods described herein represent computer implemented systems and methods, and may also be referred to as a model, algorithm, process, method, or the like. Accordingly, and as described hereinafter, computers, servers, and devices represent specially programmed computers that have program instructions tailored to, configured for, programmable to

ΙΜΡΪ implement, or capable of implementing,

INDUSTRIAL described. For example, some or all of the systems or methods described here may be fully or partially implemented on or executed by a train's train-handling computer, a train's on-board computer, a remote server, a backup office system or similar.

<img file="MX359353B_D0016.tif" />

In a first preferred and non-limiting primary embodiment, the present invention includes a system and method that allow the safe use of dynamic braking in the braking model or algorithm, and the reduction of initial errors in dynamic braking force, by adjusting the safety factor (or displacement) in the brake model or algorithm according to the expected amount of dynamic braking. In a second preferred and non-limiting primary embodiment, the present invention includes a system and method that allow the safe use of dynamic braking in the braking model or algorithm, and reduces the effect of any possible failure of this force, by carrying out real-time monitoring of train behavior to “learn” and adjust the calculated dynamic braking force to a precise level. This also ensures that security considerations are met.

Regarding the first preferred and non-limiting primary modality, and since the braking curve is always a calculation or prediction of the future, the on-board computer or computer, for example, the train driving computer,

<img file="MX359353B_D0017.tif" />

MEXICAN INSTITUTE OF PROPERTY

INDUSTRIAL

<img file="MX359353B_D0018.tif" />

Similarly, it cannot determine what might happen to dynamic braking forces in the future. To compensate for this, the safety factor can be adjusted to compensate for the risk that dynamic braking may not be available. In a preferred and non-limiting embodiment, the method includes: (a) determining at least one initial safety factor; (b) determining at least one dynamic braking adjustment factor based at least partially on (i) the expected dynamic braking force, and (ii) specified train retarding forces; and (c) determining at least one new safety factor based at least partially on the initial safety factor and the dynamic braking adjustment factor. In another preferred and non-limiting embodiment, the system generates or modifies the braking model or algorithm by incorporating or using the at least one new safety factor, and this braking model or algorithm can be provided for at least one on-board computer of the train. Furthermore, some or all of the stages described above may be implemented or carried out on or by a computer on board the train.

In another preferred and non-limiting embodiment, the process, method, or algorithm adjusts the factor of safety (or displacement) by the ratio of the expected dynamic braking force compared to other retarding forces on the train. The greater the expected dynamic braking force, the greater the safety factor.

<img file="MX359353B_D0019.tif" />

that is added. In this modality, the initial process, method or algorithm uses a direct relationship as follows: new factor of safety = initial factor of safety * (1 + (dynamic braking force / total retarding forces). It is envisaged that this process, method or algorithm or calculation can be modified or otherwise refined within the spirit and scope of the present invention. Although the safety factor is being increased with dynamic brakes present, the total predicted stopping distance is reduced by compensating with the dynamic braking force in model or braking algorithm.

In the second preferred and non-limiting primary modality, and even though the braking curve generated by the braking model or algorithm is primarily a future prediction, it can be made much more accurate by applying real-time behavior measurement to make adjustments to expected future behavior. As is known, the current brake model or algorithm is based on Newton's first law of motion: F = n * aoa = F / m. The braking model or algorithm is continuously calculating the expected acceleration or deceleration of the train. If the real-time acceleration or deceleration of the train is monitored and compared against the predicted acceleration or deceleration of the train, then any mechanical failure or cut of the dynamic brakes can be compensated. These settings

IMPP jiwesta industry is not a significant security risk to operate the train.

can rapidly spread in future modeling ^ 'O ^ Afesw industrial

<img file="MX359353B_D0020.tif" />

Accordingly, in a preferred and non-limiting embodiment, a braking system is provided that includes dynamic braking for a train having at least one locomotive with at least one on-board computer configured or programmed to: (a) before or during at least one braking event, determining predicted train acceleration or deceleration of the train based at least partially on an on-board braking model; (b) during the at least one braking event, determine acceleration or deceleration of the actual train of the train based at least partially on detected, measured and / or calculated operating conditions; and (c) adjusting at least one variable of the on-board braking model based at least partially on a specified difference between the predicted train acceleration or deceleration and the actual train acceleration or deceleration. In a preferred and non-limiting embodiment, at least one of steps (a) - (c) is implemented or occurs substantially in real time. In one embodiment, the variable includes or is in the form of dynamic braking force data.

In another preferred and non-limiting embodiment, the on-board braking model or algorithm is generated based at least partially on a given retarding force provided by each axle

IMPI

MEXICAN INSTITUTE V

<img file="MX359353B_D0021.tif" />

MEXICAN INSTITUTE equipped or applicable to the train, and the delay force ^orSfe \ £ ^ $ ^ "alM5wí ^ partially at the level of brake excitation dinAminn and / n measured dynamic brake energy. In this modality, the lag force is determined based at least partially on determining, detecting and / or measuring the operating status, performance, available force and / or condition of at least one of the following: (i) the at least a locomotive; (ii) at least one locomotive unit; (iii) at least one component of a dynamic brake system, or any combination thereof.

Furthermore, the determination of the lag force can be based at least partially on disabled operating rules and / or deactivated axles.

As described, the dynamic braking portion of the braking model or algorithm is based on a lag force provided by each axle in the locomotive unit. The calculated force is based on the dynamic braking excitation level and / or the dynamic braking energy being measured. It also provides a maximum number of dynamic braking axles, as determined by rail operating rules. It also compensates for any known axes that are deregulated, based on the unit information. Accordingly, in a preferred and non-limiting embodiment, the retarding force generated by dynamic braking is determined using the following formulas:

<img file="MX359353B_D0022.tif" />

²³ IMPI

MEXICAN INSTITUTE total axis count = (number of loc ¥) ífi $ i¡ $$ ífi (s.

* (axles per locomotive), ........ ..........

if (total axis count&gt; maximum DB axis count per rule) then (total axis count = maximum axis count) 5 lag force = (total axis count - axle count of decreased capacity) * (DB force per axis)

In this embodiment, the dynamic braking portion of the braking model or algorithm initially assumes that the remaining axles are providing dynamic braking force in accordance with dynamic braking excitation measurements. The actual and predicted acceleration or deceleration are then accumulated over a period of time (eg, about 10 seconds), and, optionally, normalized. These normalized readings are then compared. In a preferred and non-limiting mode, if the actual acceleration is greater (eg .15 meters / sec / sec) than the predicted acceleration, a force "axis equivalent" is removed or decreased in capacity for future calculations in the braking model or algorithm. This immediately affects the braking distance by making it slightly or increasingly long and safe. In this mode, the dynamic braking portion of the braking model or algorithm is reset and another average is calculated. Again, if the actual acceleration is greater than the predicted acceleration, another axis is removed or decreased by

IMPIAS

MEXICAN INSTITUTE capacity. That process continues or repeats until the predicted and actual gu are balanced, or all the dynamic braking cjryTte have been removed or decreased in capacity.

In another preferred and non-limiting embodiment, the dynamic braking portion of the braking model or process, method or algorithm initially assumes a minimum number of axes that are providing dynamic braking force in accordance with dynamic braking excitation measurements. The actual and predicted acceleration or deceleration is then accumulated over a period of time (eg, about 10 seconds), and optionally normalized. These normalized readings are then compared. In a preferred and non-limiting embodiment, if the actual acceleration is less (eg .15 meters / sec / sec) than the predicted acceleration, a force axle equivalent is added for future calculations in the braking model or algorithm. This provides a conservative and reliable initial estimate of dynamic braking capacity, and then reduces this "conservatism" by making the predicted stopping distance shorter and shorter as validated by acceleration. In this mode, the dynamic braking portion of the braking model or algorithm is reset and another average is calculated. Again, if the actual acceleration is less than the predicted acceleration, another axis is added. This process continues or repeats until either the maximum number of available axes has been

IMPI

MfcXICANO INSTITUTE

<img file="MX359353B_D0023.tif" />

reached, or a certain specified limit has been reached ^^ Ifi ^ or below that number.

In another preferred and non-limiting embodiment, the computer-implemented method or process includes: (a) if the actual train deceleration 5 is less than the predicted train deceleration by a specified amount, the adjustment step (c) comprises: ( i) removing an equivalent of a force axis; or (ii) decrease capacity by one equivalent of force axle, in subsequent brake model calculations; or (b) if the actual train deceleration is greater than the train deceleration 10 predicted by a specified amount, the adjustment step (c) comprises at least one of: (i) adding a force axis equivalent; or (ii) classify a force axle equivalent, in subsequent brake model calculations. Furthermore, step (c) is repeated for the predicted train acceleration or deceleration and the actual train acceleration or deceleration for a subsequent period of time. After reducing the difference between the predicted train acceleration or deceleration and the actual train acceleration or deceleration to a specified level, the method and process of this mode adjust the braking model for subsequent braking events. In another preferred and non-limiting embodiment, the safety factor described above is generated by: (a) receiving or determining at least one initial safety factor; (b) receive or determine at least one dynamic braking adjustment factor with

IMPI bases at least partially on (i) the expected ^ iíp ^ K ^ o ^^ KHffiíco force, and (ii) specified lag forces dol tron; and (u) 'deteriiiÍÍiai' at least one new safety factor based at least partially on the initial safety factor and the dynamic braking adjustment factor.

In yet another preferred and non-limiting embodiment, a braking system is provided that includes dynamic braking for a train having at least one locomotive with at least one on-board computer configured or programmed to: (a) before or during the minus one braking event, determine, detect, and / or measure the operating status, performance, available force, and / or condition of at least one of the following: (i) at least one locomotive; (ii) at least one locomotive unit; (iii) at least one component of a dynamic brake system, or any combination thereof; and (b) adjust at least one variable of the on-board braking model based at least partially on the determined, detected and / or measured operating state, performance, available force and / or condition. Consequently, the system could also make use of other systems in the locomotive that report dynamic brake health and available force in the main locomotive and subsequent locomotives in the unit. This can be implemented using a dynamic brake monitoring system, and provides a base or platform for communication between locomotives in such a way

<img file="MX359353B_D0024.tif" />

This ^ SWd ^^^ e the engineer can see the status of the complete locomotive unit.

In another preferred and non-limiting embodiment, (a) if the actual train deceleration is less than the predicted train deceleration by a specified amount, the adjustment step (b) comprises: (i) withdrawing a force axle equivalent; or (ii) decrease in capacity an equivalent axis of force, in subsequent brake model calculations; or (b) if the actual train deceleration is greater than the predicted train deceleration by a specified amount, the adjustment step (b) comprises at least one of: (i) adding a force axis equivalent; or (ii) classify a force axle equivalent, in subsequent brake model calculations. This calculation process is then repeated for another period of time, and the process continues repeating until the predicted and actual decelerations are balanced or all dynamic braking axles have been removed or added, or decreased in capacity or rated.

Using these iterative processes, the braking model or algorithm "learns" the actual amount of dynamic braking force in a specified locomotive and / or unit. These learned data and information 20 can now be applied to all future stops that include dynamic braking. Also, this dynamic braking delay force data can be reset or cleared when appropriate,

IMPI

MEXICAN INSTITUTE OF PROPERTY

<img file="MX359353B_D0025.tif" />

such as when new drive information is pi'tfp'SÍ'óic system has been reset. As d VSU Γ1 b 10 ',' 'ΊΉ¹'po'fCTórr ^ ae dynamic braking model or braking algorithm can be easily modified to start with less assumed force, then add or subtract axes. Additionally, a security analysis will help determine the appropriate approach. It should be noted that these methods and systems can also compensate for any “phantom” forces that could be altering the acceleration or deceleration of the train, even though it is assumed to be a dynamic braking error. Furthermore, the variables and constants in the above formulas can be modified or revised without departing from the spirit and scope of the present invention.

In another preferred and non-limiting embodiment, the first and second primary modalities are combined, and work in conjunction with one another to minimize any "surprise" for the crew. Since the safety factor is based on the amount of dynamic braking expected, since the braking model or algorithm “learns” varying or reduced levels of dynamic braking, the effect is to lengthen the braking curve, but with a reduction in safety factor (or displacement). Thus, the stopping distance presented to the crew is only gradually changing, thus avoiding sudden or surprising warnings or applications. By implementing one or both of these approaches, a significant reduction in distance is provided

MEXICAN INCTEMPT OF THE OWN OWNED age of train predicted in degrees of slope^Dpronunciation where dynamic braking is used heavily. Furthermore, by implementing one or both of these approaches, alignment and / or convergence is improved between predicted train behavior and actual train behavior. This will improve crew confidence in the system, and improve overall performance on railroad tracks by avoiding unnecessary applications in scenarios where the crew is adequately controlling the train.

A preferred and non-limiting embodiment of the present invention is illustrated in Figure 1. In this embodiment, the system and method of the present invention are implemented for a braking algorithm that includes dynamic braking, and uses the train-in-time behavior. actual to adjust your calculations. In this mode, the safety factor is adjusted based on the dynamic braking level.

Referring to Figure 1, the process begins with a Determination of Maximum Axle Count Db (step 100), which determines the maximum available dynamic braking axle count. Total Possible DB Axes (step 102) are determined by reviewing the Number of Activated Locomotives, the number of Axles per Locomotive, as limited by any limit of Maximum DB Axes per Train for the calculation. The Total Possible DB Axes are then provided to a process that limits the total axes by a Count of Decreased Axes in Capacity and

<img file="MX359353B_D0026.tif" />

Then Calculate a DB Force per Rje (step 1 dynamic braking per axle that would be generated by each remaining axle, and add those dynamic braking forces. The result is the expected DB force that is generated by the train.

The process then Predicts Deceleration (step 106) that begins with the sum of forces, which adds the Expected DB Force and all other forces that have been calculated and / or are acting on the train, including, but not limited to, Grade Force, Curvature Force, Air Brake Force and Resistive Forces. Using the combined force and the Train Mass, a Predicted Slowdown is calculated. In addition, during the prediction process, a Ratio DB of the amount of dynamic braking force against other factors acting on the train is calculated to be used in determining a suitable safety factor for the braking distance. After iterating this calculation over time, a Predicted Stop Distance is determined (as described below).

Then, at step 108, the Predicted Deceleration is compared to the Actual Deceleration measured for the train. A determination is made manually or automatically (such as through the use of a configurable interval or range) as to how close the

Predicted Slowdown and Real Slowdown. If the slowdown

Predicted and Real Slowdown do not closely match or are

IMPI within the established range or margin, then eT'Süeew ^^

<img file="MX359353B_D0027.tif" />

Decreased in Capacity is adjusted up or down accordingly (at step 110). If the Predicted Deceleration is greater than the Actual Deceleration, the axle count decreased in capacity is increased by one. If the predicted deceleration is less than the actual deceleration, the count of axes decreased in capacity is reduced by one. The new axle count decreased in capacity is then fed back to the next iteration of the process, method or algorithm increased or thereby reducing the amount of expected dynamic braking force. If the actual and predicted decelerations match (i.e. are within the range or range), then the process, method, or algorithm will maintain the DB axis count (step 112). In parallel with the process of predicting deceleration, the DB ratio is used to adjust the safety factor for using DB (step 114), which will affect the braking distance of the train. The safety factor calculated from the air brake model (step 116) is optionally increased to the amount of dynamic braking force used in the braking distance calculations. This adjustment is then applied to the predicted stopping distance calculation (step 118). It should be noted that the components or variables of predicted deceleration and actual deceleration can be changed to predicted acceleration and actual acceleration, and the methodology adjusted accordingly.

IMPI

<img file="MX359353B_D0028.tif" />

INSTICTO ^ EXICANO

The systems and methods currently invented have been implemented in relation to a variety of types of railroad tracks. In a preferred and non-limiting embodiment, and as illustrated in Figure 2, the systems and methods described in this 5 may be implemented in a train with at least one locomotive 10 having an on-board computer system 12 (for example , on an on-board controller, an on-board computer, a train driving computer, and the like). The on-board computer system 12 includes a database 14 populated with track profile data 16 and 10 train data 18, and the on-board computer system 12 also includes the appropriate braking model and other software or programs to implement effectively the systems and methods according to the system of the invention. In this mode, the on-board computer system 12 receives real-time inputs from various control settings of 15 locomotive 20, dynamic brake settings 21, a GPS receiver 22 and / or at least one speed sensor 24. The On-board computer 12 is in communication, integrated with, or controls the braking system 26, which includes a preventive brake actuator 28 and an emergency brake actuator 30. Accordingly, the currently invented systems and methods can be effectively implemented and used by or on the locomotive 10 having the on-board locomotive system 12 and braking system 26, including a dynamic brake system or dynamic braking functionality. It is contemplated that any type of train management system (or sistJ ^ i ^ jLej ^ oi

MEXlCAf INSTITUTE has the train monsDAu (PTC)) and braking system and arrangement^L use within the context and scope of the present invention.

The present invention, including the different aspects and configurations implemented by computer and / or designed by computer, can be implemented in a variety of devices and computing systems, including client devices and / or server computers, where these computing devices include processing mechanisms and computer-readable media suitable for storing and executing computer-readable instructions, such as programming instructions, code, and the like. In addition, aspects of this invention may be implemented in existing controllers, control systems, and computers integrated with or associated with, or located in, locomotives. For example, the currently invented system or any of its functional components may be implemented in whole or in part in a train management computer, a positive train control (PTC) computer, an on-board controller or computer, a wagon computer, and Similar. Furthermore, certain aspects of the currently invented systems and methods can be implemented in a laboratory environment on one or more computers or servers. Furthermore, the computer-implemented functions and features of the

<img file="MX359353B_D0029.tif" />

<img file="MX359353B_D0030.tif" />

Γ.Ε THE PROPERTY

INDUSTRIAL '' to the present invention may be in the form of hardware, programmed control systems, microprocessors, and the like.

As shown in Figure 3, 5 computers 900, 944 are provided, in a 902 computer system environment. This 902 computer system environment may include, but is not limited to, at least one 900 computer having certain components for proper operation, code execution, and data creation and communication. For example, computer 900 includes a processing unit 904 (typically referred to as a central processing unit or CPU) that serves to execute received computer-based instructions in the appropriate form and format of data. Furthermore, this processing unit 904 may be in the form of multiple processors that execute code serially, in parallel, or in any other way for proper implementation of the computer-based instructions.

In order to facilitate proper data communication and information processing between the different components of the 900 computer, a system bus 906 is used. The system bus

906 it can be any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, or a local bus that uses any of a variety of

IMPIDO bus architectures. In particular, the bus communicates information data between the different computers (either internal or external to the computer 900) through a variety of interfaces, as described hereinafter.

Computer 900 can include a variety of discrete computer readable media components. For example, these computer readable media can include any media that can be accessed by computer 900, such as volatile media, nonvolatile media, removable media, nonremovable media, etc. As a further example, these computer readable media may include computer storage media, such as media implemented in any information storage method or technology, such as computer readable instructions, data structures, program modules, or other data, random access memory (RAM), read only memory (ROM), electrically erasable programmable read only memory (EEPROM), flash memory or any other memory technology, CD-ROM, digital versatile disc (DVD), or other optical disc storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other means that you can be used to store the desired information and which can be accessed by the 900 computer. In addition, these means

<img file="MX359353B_D0031.tif" />

Computer-readable IMPIs may include means of such as computer-readable instructions, structures of^faith date_fi - program modules or other data in other transport mechanisms and including any information delivery means, wired means (such as a wired network and a direct wired connection), and wireless means. Computer readable media can include all machine readable media with the sole exception of transient propagation signals. Of course, combinations of any of the above must also be included within the scope of computer readable media.

As seen in FIG. 3, computer 900 further includes system memory 908 with computer storage media in the form of volatile and nonvolatile memory, such as ROM and

RAM. A basic input / output system (BIOS) with proper computer-based routines helps transfer information between components within the 900 computer and is normally stored in ROM. The RAM portion of system memory 908 typically contains data and program modules that are immediately accessible by or are currently being operated by processing unit 904, for example, an operating system, application programming interfaces, application programs, program modules, program data and other instructions.

readable codes by

IMPI instituto méxiCano ^IW| XIA Pf.OPlKDAÜ

INpUSTWAL computer

<img file="MX359353B_D0032.tif" />

based

With continued reference to Figure 3, computer 900 may also include other removable or non-removable, volatile or non-volatile computer storage media products. For example, computer 900 may include a non-removable memory interface 910 that communicates with and controls a hard disk drive.

912, that is, a non-removable and non-volatile magnetic medium; and a removable, nonvolatile memory interface 914 that communicates with and controls a magnetic disk drive 916 (which reads from and writes to a removable non-volatile magnetic disk 918), an optical disc drive

920 (which reads from and writes to a removable, non-volatile 922 optical disc, such as a CD ROM), a Universal Serial Bus (USB) port

921 to be used in connection with a removable memory card, etc.

However, it is contemplated that other volatile or non-volatile and removable or non-removable computer storage media may be used in the 900 computer system environment example, including, but not limited to, magnetic tape cassettes, DVDs, tape digital video, solid state RAM, solid state ROM, etc.

These different removable or non-removable volatile or non-volatile magnetic media are in communication with the processing unit 904 and other components of the 900 computer via the system bus.

IMPI

906. The drives and their storage mediaSffl ^ SSiow ^^ · ora associated described above and illustrated in figure 3 prnpnxxü ^ jww storage of operating systems, computer readable instructions, application programs, data structures, program modules, program data and other computer-readable instruction-based code for computer 900 (whether or not duplicate of this information and data in 908 system memory).

A user may enter commands, information, and data into computer 900 through certain connectable or operable input devices, such as a 924 keyboard, 926 mouse, etc., through a 928 user input interface. Of course, a variety of these input devices can be used, for example, a microphone, a rotating ball, a joystick, a touch pad, a touch screen, a scanner, etc., including any arrangement that facilitates entry. data, and information to the 900 computer from an external source. As described, these and other input devices are commonly connected to processing unit 904 through user input interface 928 coupled to system bus 906, but can be connected by other interface and bus structures, such as a parallel port, game port, or a universal serial bus (USB). Furthermore, data and information may be presented or provided to a user in a form

IMPI ΐΜτίτυΐθ MEXICAN Vif * —Vi

IP.31 &lt;iv ly. , Ϊ&gt; ',. . ~ r'jr, · · ÜÉ LA moHEDAO, intelligible or formatted through certain dt ^ Sntia devices, such as a 930 monitor (to present visually it is iiifóllífacioñry'data in electronic form), a 932 printer (to physically present this information and data in printed form), a loudspeaker 934 (to audibly present this information and data in audible form), etc. All of these devices are in communication with computer 900 through an output interface 936 coupled to system bus 906. It is contemplated that any one of these peripheral output devices can be used to provide information and data to the user.

Computer 900 can operate in a 938 network environment through the use of a 940 communications device, which is integral to or far from the computer. This communication device 940 is operable by and is in communication with the other components of computer 900 through a communication interface 942. Using this arrangement, computer 900 can connect to or otherwise communicate with one or more remote computers, such as a remote computer 944, which can be a personal computer, a server, a router, a networked personal computer, a peer device or other common network modes, and typically includes many of all the components described above in connection with the 900 computer. Using suitable 940 communication devices, for example, a modem, a network interface or adapter, etc., the computer 900 pufis®cuT © ^ eF ^ q ^ gMWSá ^ pen communication over a local area network (LAN) and a wide area network (WAN), but it can also include other networks such as a virtual private network (VPN), an office network, a company network, an intranet, the Internet, etc. It will be appreciated that the network connections shown are examples and that other means can be used to establish a communication link between computers 900, 944.

As used herein, computer 900 includes or is operable to run custom-designed or conventional software suitable for carrying out and implementing the processing steps of the method and system of the present invention, thereby forming a system of specialized and particular computing. Accordingly, the presently invented method and system may include one or more computers 900 or similar computing devices having a computer-readable storage medium capable of storing computer-readable program codes or instructions that cause processing unit 902 to execute , configure or otherwise implement the methods, Transformation data processes and manipulations described hereinbelow in connection with the present invention. Furthermore, the 900 computer may be in the form of a personal computer, a personal digital assistant, a laptop, a laptop, a palmtop, a mobile device, a

<img file="MX359353B_D0033.tif" />

mobile phone, server, or any other compute that has the necessary processing hardware to adequately process data to effectively implement the currently invented method and computer implemented system.

Although the invention has been described in detail for purposes of illustration based on what is currently considered to be the most practical and preferred embodiments, it should be understood that this detail is for that purpose only and that the invention is not limited to the disclosed embodiments. Rather, on the contrary, it attempts to cover modifications and equivalent provisions that are within the spirit and scope of the appended claims. For example, it should be understood that the present invention contemplates that, to the extent possible, one or more features of any one embodiment may be combined with one or more features of any other embodiment.