Tire inflation optimization device, method of determining optimal inflation pressure, and aircraft

Abstract

A tire inflation optimization device is provided that is configured to determine an optimal inflation pressure for a tire mounted on an aircraft. The device includes a memory and a controller. The memory stores information associating tire gas properties with aircraft scheduling parameters and a reference pressure for the tire. The controller is configured to receive future scheduling information indicative of a future flight schedule of the aircraft and to determine an optimal inflation pressure for the tire based on the received future scheduling information, the stored information associating tire gas properties with aircraft scheduling parameters, and the stored reference pressure. A method of determining an optimal inflation pressure for an aircraft tire is also provided, as is an aircraft including a tire in combination with the foregoing tire inflation optimization device.

Description

Technical Field

[0001] This invention relates to tire inflation optimization equipment, a method for determining the optimal inflation pressure for aircraft tires, and an aircraft. Background Technology

[0002] Throughout the entire operation of the aircraft, the pressure of the gas in the aircraft tires must be maintained within a certain range to ensure safe operation. This pressure range is set by the aircraft manufacturer and tire manufacturer based on the characteristics of the aircraft and tires, and is specified in the aircraft's Aircraft Maintenance Manual (AMM).

[0003] Tire pressure varies with temperature, and specifically, increases with rising temperature. For example, the temperature of the tire gas at a specific point in a flight cycle may vary between flight cycles due to differences in ambient temperature. Furthermore, the optimal tire pressure (i.e., the pressure at which the tire deforms to the optimal amount during operation) varies depending on the load. Higher tire pressure is better for higher loads. For example, the load on the aircraft tires may also vary between flight cycles due to differences in the number of passengers and / or the amount of baggage carried. It is important that at any time during aircraft operation, the tires are not underinflated relative to the load on them, as this increases the risk of tire failure. Therefore, the pressure range defined in the AMM is conservatively set so that the tire pressure is not too low even when the aircraft is operating at very low ambient temperatures and / or at the aircraft's maximum weight.

[0004] This means that for aircraft that frequently operate in high ambient temperatures and / or at weights significantly below the maximum permissible level, tires are often slightly overinflated when inflation is performed according to the AMM (Aircraft Manufacturing Management) standard. While not a safety issue, this results in more frequent tire inflation and therefore more nitrogen usage and faster tire tread wear (and thus more frequent tire replacements). Therefore, it would be beneficial for operators to reduce the time their aircraft are operated with overinflated tires while still ensuring that underinflation does not occur. Summary of the Invention

[0005] A first aspect of the invention provides a tire inflation optimization device configured to determine the optimal inflation pressure for tires mounted on an aircraft. The device includes a memory and a controller. The memory stores information relating tire gas characteristics to aircraft scheduling parameters and a reference pressure for the tires. The controller is configured to receive future scheduling information indicating future flight plans for the aircraft, and to determine the optimal inflation pressure for the tires based on the received future scheduling information, the stored information relating tire gas characteristics to aircraft scheduling parameters, and the stored reference pressure.

[0006] Optionally, the controller is further configured to determine an optimal reinflation threshold for the tires based on received future scheduling information, stored information relating tire gas characteristics to aircraft scheduling parameters, and stored reference pressure. The optimal reinflation threshold is set such that tire reinflation is triggered when the tire pressure is measured to be lower than the reinflation threshold during a routine check.

[0007] Optionally, the determined re-inflation threshold corresponds to the determined optimal inflation pressure, because the determined re-inflation threshold is configured to trigger the first re-inflation after inflation to the determined optimal inflation pressure.

[0008] Optionally, tire gas characteristics are temperature and pressure.

[0009] Optionally, the aircraft scheduling parameters include any combination of the following: the airline operating the aircraft, the departure airport, the arrival airport, the route, the arrival time, the departure time, the arrival date, and the departure date.

[0010] Optionally, the stored information relating tire gas characteristics to aircraft scheduling parameters is created based on historical tire gas information covering a selected time period and historical aircraft scheduling information covering the selected time period.

[0011] Optionally, historical tire gas information includes the measured tire pressure value and the corresponding measured tire gas temperature value.

[0012] Optionally, at least a portion of the historical tire gas information is associated with the tire whose optimal inflation pressure needs to be determined.

[0013] Optionally, a portion of the historical tire gas information is associated with the aircraft's previous tires, which were installed on the same wheels of the aircraft before the tires whose optimal inflation pressure is to be determined were installed.

[0014] Optionally, the stored information relating tire gas characteristics to aircraft scheduling parameters includes one or more lookup tables, each of which links historical tire gas parameters to historical scheduling parameters from the same period.

[0015] Optionally, the stored information relating tire gas characteristics to aircraft scheduling parameters includes a mathematical relationship that links the tire gas characteristics to the aircraft scheduling parameters, which has been derived using historical tire gas information and historical scheduling information.

[0016] Optionally, the stored information relating tire gas characteristics to aircraft scheduling parameters includes a machine learning algorithm that has been trained using historical tire gas information and historical scheduling information.

[0017] Optionally, the machine learning algorithm has been further trained using one or more of the following:

[0018] Historical flight tracking information;

[0019] Historical weather information.

[0020] Optionally, the received future scheduling information covers at least one maximum time period up to the next tire inflation.

[0021] Optionally, the received future scheduling information covers at least 3 days.

[0022] Optionally, the received future scheduling information includes multiple scheduling parameters, which include any combination of the following: the airline operating the aircraft, the departure airport, the arrival airport, the route, the arrival time, the departure time, the arrival date, and the departure date.

[0023] Optionally, the controller is further configured to receive current measurements of tire gas temperature and tire gas pressure, as well as current scheduling information, and to update stored information that associates tire gas characteristics with aircraft scheduling parameters based on the received current measurements and current scheduling information.

[0024] Optionally, the memory also stores weight-scheduling information that associates the aircraft weight with aircraft scheduling parameters, and the controller is configured to additionally determine the optimal inflation pressure based on the received weight-scheduling information.

[0025] Optionally, the memory also stores tire gas-weather information that associates tire gas characteristics with weather conditions, and the controller is configured to receive future weather information for a time period covered by the received future scheduling information, and is further configured to determine the optimal inflation pressure based on the received weather forecast and the stored tire gas-weather information.

[0026] Optionally, the stored information relating tire gas characteristics to aircraft scheduling parameters is additionally created based on historical weather information covering the selected time period, which indicates the weather conditions at the locations where the aircraft was operating during the selected time period and at those times when the aircraft was in those locations.

[0027] A second aspect of the invention provides a method for determining the optimal inflation pressure for an aircraft tire. The method includes:

[0028] Receive future flight scheduling information associated with planned flights of aircraft, including those with tires;

[0029] Receive tire gas-scheduling information that associates tire gas characteristics with aircraft scheduling parameters;

[0030] Receive reference pressure for the tire; and

[0031] The optimal inflation pressure for the tires is determined based on the received future flight scheduling information, the received tire gas-schedule information, and the received reference pressure.

[0032] Optionally, the method is configured to be executed by a controller of the tire inflation optimization device according to the first aspect.

[0033] A third aspect of the invention provides an aircraft including a tire in conjunction with a tire inflation optimization device according to a first aspect, the tire inflation optimization device being configured to predict the optimal inflation pressure for the tire.

[0034] Optionally, the aircraft also includes a tire gas pressure sensor configured to measure the current pressure of the gas in the tire and a tire gas temperature sensor configured to measure the current temperature of the gas in the tire, and the tire gas pressure sensor and tire gas temperature sensor are configured to provide tire gas pressure information and tire gas temperature information to the tire inflation optimization device. Attached Figure Description

[0035] Embodiments of the invention will now be described by way of example only with reference to the accompanying drawings, in which:

[0036] Figure 1 This is a schematic diagram of an example tire inflation optimization device according to the present invention;

[0037] Figure 2 It is a schematic cross-section through a portion of the wheels of the example aircraft;

[0038] Figure 3a This is an example tire pressure profile for an aircraft tire inflated to a non-optimal inflation pressure.

[0039] Figure 3b This is an example tire pressure curve of an aircraft tire inflated to the optimized inflation pressure determined according to the present invention.

[0040] Figure 4 This is an example method for determining the optimal inflation pressure for aircraft tires according to the present invention; and

[0041] Figure 5 These are example aircraft and example tire inflation optimization devices according to the present invention. Detailed Implementation

[0042] The examples of the invention described herein each relate to a tire inflation optimization device configured to determine the optimal inflation pressure of a tire mounted on an aircraft. Each example device includes a memory and a controller. Stored in the memory are information relating tire gas characteristics to aircraft scheduling parameters (hereinafter referred to as tire gas-scheduling information) and a reference pressure for the tire. The controller is configured to receive future scheduling information indicating future flight plans for the aircraft; and to determine the optimal inflation pressure for the tire based on the received future scheduling information, the stored tire gas-scheduling information, and the stored reference pressure. In some examples, the controller is further configured to determine an optimal re-inflation threshold for the tire based on the received future scheduling information, the stored information relating tire gas characteristics to aircraft scheduling parameters, and the stored reference pressure. The optimal re-inflation threshold is set such that tire re-inflation is triggered when the tire pressure is measured to be less than the re-inflation threshold during a routine check.

[0043] The exemplary tire inflation optimization device according to the invention advantageously minimizes the time a tire spends in an overinflated state, while also ensuring that underinflation is prevented by taking into account how tire pressure changes during the actual operation of the aircraft equipped with the tire. For example, when the aircraft is operating on a specific route, or at a specific time of day and / or at a specific time of year, environmental conditions and / or the aircraft's load may deviate from the average in some predictable way, which affects tire pressure. This relationship is stored in tire gas-scheduling information stored by the optimization device, which is thus able to predict future tire gas pressure behavior when future scheduling information is provided. The predicted future behavior can then be used to determine an optimal inflation pressure that maximizes the time the tire pressure is within a preferred range (i.e., neither underinflated nor overinflated).

[0044] Figure 1 This is a schematic diagram of a general example tire inflation optimization device 1 according to the present invention. Device 1 is configured to determine the optimal inflation pressure of a tire mounted on an aircraft. Device 1 includes a controller 11 and a memory 12. The controller 11 includes a processor for executing computer program instructions, which may be stored in the memory 12 and / or received via control signals. The controller 11 is configured to receive data from the memory 12 and may also be configured to write data to the memory 12.

[0045] The memory 12 may include any suitable implementation of a computer-readable storage medium, such as a hard disk drive, flash memory, non-volatile memory, etc. Figure 1A memory 12 and a controller 11 are shown included in a single unit, which may, for example, include a single housing containing the controller 11 and the memory 12. However, the memory 12 may also comprise a separate unit from the controller 11, in which case the memory 12 would be connected to the controller 11 via a communication link (which may be wired or wireless). In some examples, the memory 12 may be located remotely from the controller 11. In some such examples, the memory 12 may be included in a cloud-based data storage system.

[0046] Memory 12 stores information that associates tire gas characteristics with aircraft scheduling parameters (tire gas-scheduling information). Tire gas characteristics are the temperature and pressure of the gases in the tires. The stored tire gas-scheduling information allows tire gas characteristics to be associated with one or more scheduling parameters. Scheduling parameters can be any parameter that may affect tire gas characteristics. Scheduling parameters can include, for example, any combination of the following: the airline operating the aircraft, departure airport, arrival airport, route, arrival time; departure time, arrival date, departure date. Scheduling parameters can be parameters routinely included in scheduling information provided by the airline.

[0047] The stored tire gas-scheduling information is configured to enable controller 11 to determine tire gas characteristics (i.e., temperature and pressure) corresponding to a specific set of scheduling parameters (e.g., a specific flight path at a specific time of year). The stored tire gas-scheduling information can take various forms, such as one or more lookup tables, one or more mathematical relations, and / or one or more machine learning algorithms. The stored tire gas-scheduling information is created based on historical tire gas information covering a selected time period and historical scheduling information for the aircraft covering the same selected time period. The stored information can be created by controller 11 or by a different system. Depending on the size and nature of the stored tire gas-scheduling information, it may have to be created by a system with greater computing power than the processor of controller 11.

[0048] Historical tire gas information—the information stored based on this historical tire gas information—may include measured tire pressure values ​​and corresponding measured tire gas temperature values. Each such measured tire pressure value can be associated with a simultaneously measured tire gas temperature value. Historical tire gas temperature information can therefore include pairs of pressure and temperature values. Historical tire gas information can be presented as a time series of values ​​(or pairs of values) that persist over a selected time period. The selected time period may end at the current time (i.e., the time when the optimization device 1 determines the optimal inflation pressure) or shortly before the current time. The most recent values ​​included in the historical tire gas information can be the most recently measured tire pressure and tire gas temperature values ​​by a sensor device configured to measure the pressure and temperature of the gas in the tire. Figure 2 An example of this sensor device is shown.

[0049] Figure 2 This is a cross-sectional view through a portion of an example aircraft wheel assembly 20, which includes wheels 21 and tires 22 mounted on the wheels 21. The wheel assembly is shown resting on the ground 26. An enclosed space 23 is formed between the wheels 21 and the tires 22, and this enclosed space 23 is filled with pressurized inert gas (typically nitrogen). An inflation port 24 is provided on the wheels 21 through which inert gas can be introduced to increase the pressure in the enclosed space 23. In the illustrated example, the wheel assembly 20 is included in the nose landing gear of the aircraft and therefore does not include brakes. A sensor device 25 suitable for measuring the pressure and temperature of the gas within the space 23 is installed on the wheels 21 and within the enclosed space 23 formed by the wheels 21 and the tires 22. The sensor device 25 is configured to continuously or periodically measure the temperature and pressure of the tire gas during operation of the aircraft including the wheel assembly 20. The sensor device 25 can also be configured to provide measurements to the tire inflation optimization device 1 in any suitable manner (e.g., via a wireless communication link). In such an example, the controller 11 of the optimization device 1 can be configured to update the stored tire gas-dispatch information based on the temperature and pressure values ​​recently received from the sensor device 25.

[0050] At least a portion of the historical tire gas information is associated with the tire for which its optimal inflation pressure is to be determined (the current tire). In some examples, all historical tire gas information is associated with the current tire. In such examples, the selected time period can begin from the time the tire was installed on the aircraft. In some examples, at least a portion of the historical tire gas information is associated with different tires of the aircraft, which are installed or have been installed on different wheels of the aircraft than the current tire. In such examples, the different tire is of the same type as the current tire. In other examples, at least a portion of the historical tire gas information may be associated with previous tires of the aircraft. In such examples, the previous tire is the tire that was installed on the same wheel of the aircraft as the current tire before the current tire was installed. The previous tire may be of the same type as the current tire. The previous tire may have substantially the same physical characteristics as the current tire. In some examples, historical tire gas information may be associated with multiple previous tires, each of which was installed on the same wheel of the aircraft as the current tire before the current tire was installed.

[0051] The stored tire gas-scheduling information is based on historical scheduling information that includes the values ​​of one or more scheduling parameters within a selected time period. These scheduling parameters may include, or be identical to, aircraft scheduling parameters from which the stored tire gas-scheduling information correlates tire gas characteristics with the aircraft scheduling parameter. Alternatively, the scheduling parameter included in the historical scheduling information may be a parameter from which aircraft scheduling parameters can be derived, from which the stored tire gas-scheduling information correlates tire gas characteristics with the aircraft scheduling parameter.

[0052] In an example where the stored tire gas-scheduling information includes one or more lookup tables, the lookup table (or each of the one or more lookup tables) correlates historical tire gas parameters for a given time (which are contained in the historical tire gas information) with at least one historical scheduling parameter for the same given time (which is contained in the historical scheduling information). For example, a lookup table could correlate regulated tire gas pressure (i.e., tire gas pressure values ​​that have been regulated according to the temperature at which each pressure value was measured) with the time of pressure measurement throughout the day. Such lookup tables could be provided for each of multiple routes operated by the aircraft. Many other ways exist to correlate tire gas characteristics with aircraft scheduling parameters using one or more lookup tables, which will not be listed here.

[0053] In an example where the stored gas tire scheduling information includes a mathematical relationship linking tire gas characteristics to aircraft scheduling parameters, this mathematical relationship has been derived using historical tire gas information and historical scheduling information. The mathematical relationship can be configured such that inputting future values ​​of one or more scheduling parameters produces predicted future tire pressure values. The mathematical relationship can also be configured such that inputting future values ​​of one or more scheduling parameters produces predicted future tire pressure values ​​and predicted future tire gas temperature values. The mathematical relationship can be derived using any suitable technique known in the art.

[0054] In some examples, the stored tire gas-dispatch information includes machine learning algorithms configured to be implemented via controller 11. Machine learning is a form of data analysis in which an algorithm automatically creates a model based on identifying patterns in training data, without any explicit instructions. Machine learning algorithms can be supervised, meaning they have been trained on data including labeled example input-output pairs. Alternatively, machine learning algorithms can be unsupervised, meaning they are configured to find previously unknown patterns in an unlabeled dataset.

[0055] In the example where the stored tire gas-scheduling information includes a machine learning algorithm, the algorithm has already been trained using historical tire gas and scheduling information. In addition to historical tire gas and scheduling information, historical flight-tracking information and / or historical weather information can also be used to train the machine learning algorithm. Each type of historical information includes a set of parameter values ​​covering a selected time period, where each parameter value is associated with a specific point in time.

[0056] Historical flight-tracking information can be obtained from flight tracking services such as Flight Radar 24. This information may include some or all of the same parameters as those in historical scheduling information, along with additional parameters. When historical flight-tracking information includes the same parameters as those included in historical scheduling information, machine learning algorithms can be configured to ignore those parameters from the historical scheduling information because the flight tracking information reflects the actual flight operated by the aircraft (which may deviate from the pre-scheduled flight for that aircraft) and is therefore more accurate.

[0057] Historical weather information indicates the weather conditions at the locations where the aircraft was operating during a selected time period, and at those times when the aircraft was in those locations. Historical weather information includes weather data recorded during the selected time period. Weather data may include values ​​for various parameters, such as temperature, humidity, atmospheric pressure, precipitation status, or any other weather-related parameters. Historical weather information can be obtained from one or more publicly available sources, such as weather reports generated by the national meteorological service of the country where the aircraft was operating during the selected time period. In an example where a machine learning algorithm has been trained using historical weather information, the tire inflation optimization device 1 may be configured to additionally receive future weather information, including predicted weather parameters for the locations where the aircraft is pre-scheduled to operate during the time period covered by the received future scheduling information, and the tire inflation optimization device 1 may be configured to additionally determine the optimal inflation pressure based on the received future weather information.

[0058] The memory 12 additionally stores the current tire reference pressure. The reference pressure is the ideal operating pressure of the tire, thus assuming the aircraft's maximum permissible load at room temperature and room pressure (RTP). The value of the reference pressure is set according to the tire type and the aircraft type. The recommended inflation pressure specified by the aircraft's AMM is set as a percentage of the reference pressure (typically 105%). The tire inflation optimization device 1 can be configured to determine the optimal inflation pressure as a percentage of the reference pressure, as will be explained further below.

[0059] As mentioned above, the optimal inflation pressure for aircraft tires varies depending on the aircraft's weight, thus higher inflation pressures are preferred for greater weights. The weight of an aircraft can vary between flight cycles, depending on factors such as the popularity and / or destination of a given route at a specific time of day, a specific day of week, and / or a specific time of year. For example, an aircraft operating summer routes on weekends may typically operate at maximum weight, while on the same flight during the week or off-season, the aircraft may typically operate at slightly less than maximum weight. Therefore, weight variations are at least somewhat predictable based on scheduling information. In some examples, the tire inflation optimization device 1 is configured to additionally determine its optimal inflation pressure based on the aircraft's weight. In such examples, the memory 12 may additionally store weight-scheduling information that associates the aircraft's weight with aircraft scheduling parameters.

[0060] Weight-dispatch information can be stored in any of the forms described above for tire gas-dispatch information. Except for associating weight values ​​with dispatch parameter values ​​rather than temperature and pressure values, weight-dispatch information can generally have the same characteristics as tire gas-dispatch information. Weight-dispatch information can include, or be based on, historical tire gas information, combined with load measurements acquired by one or more load sensors located on the aircraft. For example, load sensors can be located on each wheel assembly or on each landing gear of the aircraft.

[0061] In some examples, memory 12 may also store tire gas-weather information that correlates tire gas characteristics with weather conditions. As mentioned above, weather will affect the temperature and pressure of tire gases and will typically change between and within flight cycles in ways that cannot be predicted based on scheduling information. Tire gas-weather information may be stored in any of the forms described above related to tire gas-scheduling information. Except for relating weather parameter values, rather than scheduling parameter values, to tire temperature and pressure values, tire gas-weather information may generally have the same characteristics as tire gas-scheduling information. Tire gas-weather information may be based on historical weather information and historical tire gas information having the characteristics described above.

[0062] The tire inflation optimization device 1 may include a multi-functional device, such as a general-purpose computer or a multi-functional aircraft maintenance device, in which case the controller 11 may be embodied as the processor of the multi-functional device. The tire inflation optimization device 1 may be included in a portable device such as a tablet computer or a dedicated portable maintenance device.

[0063] Controller 11 is configured to receive future scheduling information. This future scheduling information indicates the aircraft's future flight schedule. The scheduling information covers a specific time period, which may be defined based on the aircraft's flight cycle or the number of calendar days. The received future scheduling information may cover at least one maximum time period until the next tire inflation. Aircraft tires are inflated when tires are changed and, if necessary, between tire changes. When tires are cold, tire pressure is typically checked daily. For business jets, re-inflation is typically required every 1-3 days, but this can sometimes take up to 10 days. Therefore, the received future scheduling information may cover a period of 10 calendar days.

[0064] The received future scheduling information includes multiple scheduling parameters, which may be the same as those included in the stored historical scheduling information. In fact, outdated future scheduling information can be stored as historical scheduling information in memory 12. Future scheduling information can be obtained from the same source as historical scheduling information, typically the airline operating the aircraft. Updated future scheduling information can be received periodically from this source by any suitable means. Updated future scheduling information can be stored on memory 12 by controller 11. In some examples, controller 11 may be configured to retrieve future scheduling information immediately before each new optimal inflation pressure is determined.

[0065] Controller 11 is configured to determine the optimal inflation pressure for the tire using received future scheduling information, stored tire gas-schedule information, and stored reference pressure. Controller 11 can also be configured to determine an optimal re-inflation threshold for the tire based on the received future scheduling information, stored tire inflation scheduling information, and stored reference pressure. In such an example, the optimal re-inflation threshold is set such that tire re-inflation is triggered when the tire pressure is measured to be below the re-inflation threshold during a routine check. Reference will now be made to... Figure 3a and Figure 3b Explain the principles upon which the determination process executed by controller 11 is based.

[0066] Figure 3a This illustrates how tire pressure changes for a specific aircraft tire between re-inflations. Line 31 plots the time series of tire gas pressure measurements and can therefore be considered a tire pressure curve. The pressure values ​​are absolute values ​​(i.e., these pressure values ​​are the actual pressures measured by pressure sensors on the wheel and are not adjusted for the temperature of the tire gas at the time of measurement). The thick horizontal line 34 represents the tire's reference pressure, while the thin horizontal lines 33 and 35 represent 105% and 95% of the reference pressure, respectively. The area between lines 33 and 35 is considered the ideal pressure range for the tire. i1 At that point, the tires were inflated to 105%. However, until t i2 Only then are the tires inflated again, because in t i2 Previously, during the pre-scheduled tire pressure check, the pressure was not below 100% of the reference pressure (which represents the re-inflation threshold). It can be seen that at t i1 With t i2 Between these periods, tire pressure experienced significant cyclical changes with an overall downward trend.

[0067] Most of the periodic pressure changes are caused by variations in tire gas temperature, which in turn are caused by changes in ambient temperature, heat generated by tire rolling, and heat generated during braking (if the tires are on the brake wheels). Each small peak represents a flight cycle of the aircraft, during which the overall pressure increases slightly due to the overall increase in tire gas temperature caused by the heat generated during braking during landing and taxiing. The broad peaks represent calendar days. Each broad peak contains seven smaller peaks because the specific example aircraft performed seven flight cycles per day during the period covered by pressure curve 31. The tire gas temperature (and therefore the pressure) drops significantly between calendar days because the aircraft is parked overnight, and during this time, the tire gas is not subjected to thermal effects. The overall downward trend of pressure curve 31 is caused by the gradual leakage of tire gas over time.

[0068] Figure 3a Pressure curve 31 represents the tires on an aircraft that performs a relatively large number of flight cycles per day, preventing the tire gas from cooling to ambient temperature between each flight cycle. This results in tire pressure at t i1 to t i2 For a significant portion of the time (more than half), the pressure was above 105% of the reference pressure (and therefore outside the ideal pressure range). Similar pressure curves would be observed for aircraft that primarily operate below maximum weight and for aircraft operating in extreme temperatures.

[0069] Figure 3b The pressure curves 32 of the same aircraft tires performing the same flight are shown, except that in this example, at t i1 At this point, the tire is inflated to 99% of the reference pressure. It can be seen that at t... i1 With t i2 For almost the entire period between these points, the tire pressure remained within the ideal range between line 33 and line 35. In this example, the re-inflation threshold was also set below [value missing]. Figure 3a The example uses 95% of the reference pressure. Due to the timing of the pressure check, this means the tire is slightly underinflated for a short period. This is acceptable, for example, if the aircraft is significantly below its maximum weight during this underinflation period. However, this period of underinflation can be avoided by setting the re-inflation threshold slightly higher, such as 96%-98% of the reference pressure.

[0070] Figure 4This is a flowchart illustrating a method 400 for determining the optimal inflation pressure for an aircraft tire. The controller 11 of the tire inflation optimization device 1 can be configured to execute method 400 to determine the optimal inflation pressure. Method 400 can be stored in memory 12 as computer program instructions. The controller 11 can be configured to initiate method 400 during tire inflation or re-inflation, in which case the resulting optimal inflation pressure is used for the next inflation or re-inflation of the tire. Alternatively, the controller 11 can be configured to initiate method 400 in response to the need for tire inflation or re-inflation, for example, when the tire pressure is measured to be below a predetermined re-inflation threshold. The controller 11 can be configured to initiate method 400 at any time between two consecutive inflations. Initiation of method 400 can be performed automatically by the controller 11 in response to the satisfaction of certain predetermined criteria, or it can be performed manually by an operator via the user interface of the tire inflation optimization device 1.

[0071] In the first block 401, the controller 11 receives future flight scheduling information associated with a planned flight of an aircraft including tires. The future flight scheduling information is received in the manner described above and has the characteristics described above.

[0072] In block 402, the controller receives tire gas-scheduling information that associates tire gas characteristics with aircraft scheduling parameters, such tire gas-scheduling information having the aforementioned characteristics. The tire gas-scheduling information is stored in memory 12, and therefore, the controller 11 receives the tire gas-scheduling information from memory 12.

[0073] In optional block 402a, the controller receives weight-scheduling information that associates the aircraft weight with aircraft scheduling parameters, the weight-scheduling information having the aforementioned characteristics. The weight-scheduling information is stored in memory 12, and therefore, the controller 11 receives the weight-scheduling information from memory 12.

[0074] In optional block 402b, controller 11 receives tire gas-weather information that associates tire gas characteristics with weather conditions, the tire gas-weather information having the aforementioned characteristics. The tire gas-weather information is stored in memory 12, and therefore, controller 11 receives the tire gas-weather information from memory 12. Optional block 402b is independent of optional block 402a, such that either block 402a or block 402b, both may be included in a given example of method 400, or neither may be included in a given example of method 400.

[0075] In the example executing optional box 402b, method 400 includes another optional box 402c. In box 402c, controller 11 receives future weather information. The future weather information includes predicted future values ​​of weather parameters. The weather parameters included in the future weather information are the same as those used in weather parameters such as tire gas – the weather information associates tire gas characteristics with that weather parameter. The future weather information covers the same selected time period as the future scheduling information. The future weather information can be received from the same source as historical weather information in any suitable manner.

[0076] In block 403, the controller receives a reference pressure for the tire, which has the characteristics described above. The reference pressure is stored in memory 12, and therefore, the controller 11 receives the reference pressure from memory 12.

[0077] In block 404, the controller determines the optimal inflation pressure for the tires based on received future flight scheduling information, received tire gas-schedule information, and received reference pressure. Controller 11 can be configured to determine the optimal inflation pressure by generating a predicted tire pressure profile over a time period covered by the received future scheduling information, which may be the entire time period covered by the received future scheduling information or a shorter time period.

[0078] The controller generates a predicted pressure profile based on the stored tire gas-schedule information in a manner suitable to the nature of the stored tire gas-schedule information. For example, if the tire gas-schedule information is in the form of one or more lookup tables, the controller 11 is configured to look up the tire pressure and temperature values ​​corresponding to the scheduling parameter values ​​contained in future scheduling information. The controller 11 may be configured to generate the predicted pressure profile based on a nominal initial inflation pressure, which may be (but does not have to be) a reference pressure. The nominal initial inflation pressure is stored in memory 22 and used by the controller 11 to generate the predicted pressure profile during each process performed by the controller 11 to determine the optimal inflation pressure.

[0079] The predicted pressure profile is additionally generated based on a nominal recharge threshold stored in memory 12. The nominal recharge threshold can be (but does not have to be) a reference pressure. Controller 11 can be configured to determine the predicted recharge time based on the nominal recharge threshold for the predicted pressure profile. For this purpose, controller 11 uses information relating to the timing of routine tire pressure checks to be performed on the aircraft during the time period covered by future scheduling information. Such information may be included in the received future scheduling information or may be stored in memory 12. Controller 11 determines the predicted tire pressure at each routine tire pressure check to be performed during the time period covered by the future scheduling information and compares these predicted tire pressures to the nominal recharge threshold. The earliest time at which the predicted tire pressure is found to be below the nominal recharge threshold is the predicted recharge time.

[0080] In an example where the method includes optional blocks 402b and 402c, controller 11 additionally generates a predicted pressure curve based on received tire gas-weather information and received future weather information. Controller 11 can generate the predicted pressure curve in any manner suitable to the nature of the tire gas-weather information. For example, controller 11 can be configured to calculate a time series of weather correction factors for tire gas temperature and pressure over a selected time period using the tire gas-weather information and future weather information. In such an example, predicted warmer weather at a given time during the selected time period would result in a correction factor that increases the predicted tire gas temperature and pressure at that given time. Similarly, predicted colder weather would result in a correction factor that decreases the predicted tire gas temperature and pressure. Controller 11 applies the calculated correction factors to data points on the predicted pressure curve to generate a weather-adjusted predicted pressure curve. The weather-adjusted predicted pressure curve is then used in a subsequent determination phase. Controller 11 can be configured to additionally generate a predicted pressure curve based on tire gas-weather information and future weather information in a variety of other ways using techniques known in the art.

[0081] As a next step in determining the optimal inflation pressure, controller 11 is configured to compare the predicted pressure curve with a predefined ideal pressure range for the tire stored in memory 12. The predefined ideal pressure range is based on a received reference pressure. The predefined ideal pressure range can typically be 95% to 105% of the reference pressure. Specifically, controller 11 is configured to use any suitable analytical techniques to determine how many values ​​in the predicted pressure curve are outside the predefined ideal pressure range (and in which direction). For this determination, controller 11 uses the portion of the predicted pressure curve between the time from initial inflation to the nominal initial inflation pressure and the predicted re-inflation time.

[0082] In some examples, controller 11 is configured to determine whether the amount of the predicted pressure curve found to be outside the ideal pressure range is acceptable based on predefined acceptable criteria stored in memory 12. The predefined acceptable criteria can be defined by the aircraft operator based on factors such as the type of aircraft, the flight path used by the aircraft, and the daily flight cycles scheduled for the aircraft. For example, the predefined acceptable criteria could be defined such that it is unacceptable for the predicted pressure curve to be below the lower limit of the ideal pressure range at any time, or unacceptable for the time below the lower limit of the ideal pressure range to exceed a predefined maximum amount of time. Similarly, the predefined acceptable criteria could be defined such that it is unacceptable for the predicted pressure curve to be above the upper limit of the ideal pressure range to exceed a predefined maximum amount of time.

[0083] In the example of method 400 including optional block 402a, the controller is configured to additionally determine, based on the received weight-scheduling information, whether the amount of the predicted pressure curve outside the ideal pressure range is acceptable. The controller 11 can be configured in this way in a variety of ways. For example, for the “peripheral” portion of the predicted pressure curve outside the ideal pressure range, the controller 11 can predict the aircraft’s weight during the time period of the “peripheral” portion based on the received weight-scheduling information and the received future flight scheduling information. This can be done in any suitable manner appropriate to the nature of the weight-scheduling information.

[0084] The controller 11 can then generate an acceptable pressure range based on the predicted aircraft weight. The ideal pressure range assumes a maximum weight; therefore, a predicted aircraft weight less than the maximum weight will result in an acceptable pressure range different from the predefined ideal pressure range. Specifically, the lower limit of the acceptable pressure range will be lower than the lower limit of the predefined ideal pressure range. If the predicted aircraft weight varies over time, the acceptable pressure range can also vary over time. The controller 11 then determines whether the outer portion of the predicted pressure curve is within the acceptable pressure range. If the outer portion of the predicted pressure curve is within the acceptable pressure range, the controller 11 is configured to determine that the predicted pressure curve is acceptable. If the outer portion of the predicted pressure curve is not within the acceptable pressure range, the controller 11 is configured to determine that the predicted pressure curve is unacceptable. Based on computational techniques known in the art, the controller 11 can consider the aircraft weight when determining whether the predicted pressure curve is acceptable in various other ways.

[0085] If the controller 11 finds that the predicted pressure curve is acceptable according to predefined criteria, the controller 11 can be configured to determine the optimal inflation pressure as the nominal initial inflation pressure. However, in some examples, the controller 11 can be configured to search for adjusted inflation pressure values ​​that cause a smaller portion of the predicted pressure curve to be outside the ideal pressure range. The controller 11 can perform this search in any suitable manner. For example, if the predicted pressure curve based on the nominal initial inflation value is above the upper limit of the ideal pressure range for a considerable period of time, the controller 11 can gradually decrease the initial inflation pressure value until the resulting predicted pressure curve fails to meet the predefined acceptable criteria. The lowest initial inflation pressure value that makes the resulting predicted pressure curve meet the predefined acceptable criteria is then determined as the optimal inflation pressure.

[0086] If the controller 11 finds that the predicted pressure curve is unacceptable according to a predefined acceptable standard, the controller is configured to search for an adjusted inflation pressure value as described above, which results in a predicted pressure curve that is acceptable according to the predefined acceptable standard. The obtained adjusted inflation pressure value can be determined as the optimal inflation pressure value, or a further optimized value can be sought as described above.

[0087] In some examples, method 400 includes an additional optional box 405. In optional box 405, controller 11 determines an optimal reinflation threshold for the tire. In some examples where the controller is configured to determine the optimal reinflation threshold, memory 12 stores a predefined inflation interval criterion, and controller 11 is configured to determine whether a predicted reinflation time is acceptable based on the predefined inflation interval criterion. For example, some aircraft operators may wish to avoid inflating tires too frequently. The predefined inflation interval criterion may be defined by the aircraft operator. The predefined inflation interval criterion may include a minimum inflation interval such that a predicted reinflation time later than the initial inflation time but less than the minimum inflation interval is determined to be unacceptable.

[0088] If the controller 11 finds that the predicted inflation time is acceptable according to a predefined inflation interval criterion, the controller 11 may be configured to determine the nominal reinflation threshold as the optimal reinflation threshold. However, in some examples, the controller 11 may be configured to search for an adjusted reinflation threshold that results in a later predicted reinflation time. The controller 11 may perform this search in any suitable manner. For example, if the predicted reinflation time is too early according to the predefined inflation interval criterion, the controller 11 may gradually decrease the reinflation threshold until the resulting predicted reinflation time meets the predefined inflation interval criterion. The highest reinflation threshold that makes the resulting predicted reinflation time meet the predefined inflation interval criterion is determined as the optimal reinflation threshold.

[0089] The controller 11 is configured to adhere to predefined acceptable criteria for predicting the pressure curve when searching for an optimal value for the re-inflation threshold, such that only re-inflation thresholds that result in an acceptable predictive pressure curve are allowed to be determined as the optimal re-inflation threshold.

[0090] If the controller 11 finds that the predicted inflation time is unacceptable according to the predefined inflation interval criteria, the controller 11 is configured to search for an adjusted re-inflation threshold that results in a predicted re-inflation time that is acceptable according to the predefined inflation interval criteria.

[0091] Controller 11 can be configured to execute blocks 404 and 405 simultaneously. In such an example, controller 11 may search for a combination of adjusted inflation pressure values ​​and adjusted recharge thresholds that result in an acceptable predicted pressure curve and an acceptable predicted recharge time. This may require a trade-off between the amount of the predicted pressure curve within an ideal range and the length of time preceding the predicted recharge time. Controller 11 can be configured to give greater weight to one or the other, depending on, for example, the preferences of the aircraft operator.

[0092] After method 400 is completed, controller 11 may be configured to output the determined optimal inflation pressure (and, if available, the determined optimal re-inflation threshold) in any suitable manner, making it available to vehicle operators and / or another system of the vehicle. For example, controller 11 may be configured to cause the display of the tire inflation optimization device to display the determined optimal inflation pressure (and, optionally, the determined optimal re-inflation threshold).

[0093] Figure 5 An aircraft 500 suitable for use with a tire inflation optimization device (e.g., tire inflation optimization device 1) according to an example is shown. The aircraft includes a fuselage 501 and a pair of wings 502a, 502b. The aircraft 500 is supported on the ground by a pair of main landing gear (MLGs) 505a, 505b and a nose landing gear (NLG) 506. Each landing gear assembly 505a, 505b, 506 includes a pair of wheel assemblies, each wheel assembly having a... Figure 2 The example wheel assembly 20 has the same overall configuration. Each MLG wheel assembly includes a brake (not visible). The NLG wheel assembly does not include a brake.

[0094] Each wheel assembly includes having Figure 2Example sensor device 25 is a sensor device with features. The aircraft has a total of six wheel assemblies; four wheel assemblies are part of MLG 505a, 505b, and two wheel assemblies are part of NLG 506. Therefore, the aircraft 500 may include up to six sensor devices in total. It is generally advantageous to provide sensor devices on each wheel assembly of the aircraft. Other models of aircraft may have different numbers of wheel assemblies, and therefore different numbers of sensor devices. The aircraft 500 may additionally include one or more load sensors (not shown) configured to measure load in a manner suitable for determining the weight of the aircraft. In some examples, the aircraft 500 includes a load sensor on each landing gear 505a, 505b, 506.

[0095] The sensor array on the aircraft 500 can be configured to communicate directly or indirectly with the tire pressure optimization device 520 according to the invention. The optimization device 520 has... Figure 1 The optimization device 520 has the same features as example 1. In the illustrated example, optimization device 520 is included in a portable maintenance device. In the illustrated example, two sensor devices on the wheels of NLG 506 are each configured to communicate with optimization device 520 via wireless communication links 530a and 530b. The NLG sensor devices can receive data from the MLG sensor devices and transmit the MLG data to optimization device 520. If the aircraft 500 includes one or more load sensors, the NLG sensor devices can additionally receive data from said one or more load sensors and transmit load data to optimization device 520. Other examples are possible, in which different sensor devices are configured to communicate with optimization device 520, or in which each sensor device on the aircraft communicates with optimization device 520 individually.

[0096] The aircraft 500 also includes various other systems, including avionics systems that can communicate with at least one of the sensor devices. The tire inflation optimization device 520 can be configured to communicate with one or more of these additional aircraft systems.

[0097] In some alternative examples, tire inflation optimization equipment may be included in the aircraft's onboard systems rather than in external devices.

[0098] Although the invention has been described above with reference to one or more preferred examples or embodiments, it is understood that various changes or modifications may be made without departing from the scope of the invention as defined by the appended claims.

[0099] Although the invention has been described above primarily in the context of applications in fixed-wing aircraft, it can also be advantageously applied to a variety of other applications, including but not limited to applications in vehicles such as helicopters, drones, trains, automobiles, and spacecraft.

[0100] Where the term “or” has been used in the preceding description, it should be understood as “and / or” unless otherwise expressly stated.

Claims

1. A tire inflation optimization device, the tire inflation optimization device being configured to determine the optimal inflation pressure for a tire to be mounted on an aircraft, the tire inflation optimization device comprising: The memory, wherein the memory stores: Information that correlates tire gas characteristics with aircraft scheduling parameters; as well as Reference pressure for the tire; as well as Controller, the controller is configured to: Receive future scheduling information indicating future flight scheduling for the aircraft; and The optimal inflation pressure for the tires is determined based on the received future scheduling information, the stored information relating tire gas characteristics to aircraft scheduling parameters, and the stored reference pressure.

2. The tire inflation optimization device according to claim 1, wherein, The controller is further configured to determine an optimal re-inflation threshold for the tire based on the received future scheduling information, the stored information relating tire gas characteristics to aircraft scheduling parameters, and the stored reference pressure, wherein the optimal re-inflation threshold is set such that re-inflation of the tire is triggered when the tire pressure is measured to be less than the re-inflation threshold during a routine inspection.

3. The tire inflation optimization device according to claim 2, wherein, The determined re-inflation threshold corresponds to the determined optimal inflation pressure, because the determined re-inflation threshold is configured to trigger the first re-inflation after inflation to the determined optimal inflation pressure.

4. The tire inflation optimization device according to any one of claims 1 to 3, wherein, The tire gas characteristics are temperature and pressure.

5. The tire inflation optimization device according to any one of claims 1 to 3, wherein, The aircraft scheduling parameters include any combination of the following: the airline operating the aircraft, departure airport, arrival airport, route, arrival time, departure time, arrival date, and departure date.

6. The tire inflation optimization device according to any one of claims 1 to 3, wherein, The stored information relating tire gas characteristics to aircraft scheduling parameters is created based on historical tire gas information covering a selected time period and historical scheduling information of the aircraft covering the selected time period.

7. The tire inflation optimization device according to claim 6, wherein, The historical tire gas information includes the measured tire pressure value and the corresponding measured tire gas temperature value.

8. The tire inflation optimization device according to claim 6, wherein, At least a portion of the historical tire gas information is associated with the tire for which its optimal inflation pressure is to be determined.

9. The tire inflation optimization device according to claim 6, wherein, A portion of the historical tire gas information is associated with the aircraft's previous tires, which were installed on the same wheels of the aircraft as the tires whose optimal inflation pressure was to be determined, before the tires to be installed.

10. The tire inflation optimization device according to claim 6, wherein, The stored information relating tire gas characteristics to aircraft scheduling parameters includes one or more lookup tables, each of which links historical tire gas parameters to historical scheduling parameters from the same period.

11. The tire inflation optimization device according to claim 6, wherein, The stored information relating tire gas characteristics to aircraft scheduling parameters includes a mathematical relationship that links the tire gas characteristics to the aircraft scheduling parameters, the mathematical relationship having been derived using the historical tire gas information and the historical scheduling information.

12. The tire inflation optimization device according to claim 6, wherein, The stored information relating tire gas characteristics to aircraft scheduling parameters includes a machine learning algorithm that has been trained using the historical tire gas information and the historical scheduling information.

13. The tire inflation optimization device according to claim 12, wherein, The machine learning algorithm has been further trained using one or more of the following: Historical flight tracking information; Historical weather information.

14. The tire inflation optimization device according to any one of claims 1 to 3, wherein, The received future scheduling information covers at least one maximum time period until the tire is next inflated.

15. The tire inflation optimization device according to any one of claims 1 to 3, wherein, The received future scheduling information covers at least 3 days.

16. The tire inflation optimization device according to any one of claims 1 to 3, wherein, The received future scheduling information includes multiple scheduling parameters, which include any combination of the following: the airline operating the aircraft, the departure airport, the arrival airport, the route, the arrival time, the departure time, the arrival date, and the departure date.

17. The tire inflation optimization device according to any one of claims 1 to 3, wherein, The controller is further configured to receive current measurements of tire gas temperature and tire gas pressure, as well as current scheduling information, and to update the stored information that associates tire gas characteristics with aircraft scheduling parameters based on the received current measurements and current scheduling information.

18. The tire inflation optimization device according to any one of claims 1 to 3, wherein, The memory also stores weight-scheduling information that associates the aircraft weight with aircraft scheduling parameters, and the controller is configured to additionally determine the optimal inflation pressure based on the received weight-scheduling information.

19. The tire inflation optimization device according to claim 6, wherein, The memory also stores tire gas-weather information that associates the tire gas characteristics with weather conditions, and wherein the controller is configured to receive future weather information within the time period covered by the received future scheduling information, and is further configured to determine the optimal inflation pressure based on the received future weather information and the stored tire gas-weather information.

20. The tire inflation optimization device according to claim 19, wherein, The stored information relating tire gas characteristics to aircraft scheduling parameters is additionally created based on historical weather information covering the selected time period, which indicates the weather conditions at the locations where the aircraft was operating during the selected time period and at those times when the aircraft was in those locations.

21. A method for determining the optimal inflation pressure for an aircraft tire, the method comprising, at a tire inflation optimization device: Receive future flight scheduling information associated with the planned flight of the aircraft including the tires; Tire gas-scheduling information that associates tire gas characteristics with aircraft scheduling parameters is retrieved from the memory of the tire inflation optimization device; The reference pressure for the tire is retrieved from the memory; and The optimal inflation pressure for the tires is determined based on the received future flight scheduling information, the retrieved and received tire gas-schedule information, and the retrieved and received reference pressure.

22. The method according to claim 21, wherein, The tire inflation optimization device includes a controller for the tire inflation optimization device according to any one of claims 1 to 20, the method being configured to be performed by the controller.

23. An aircraft comprising a tire in conjunction with a tire inflation optimization device according to any one of claims 1 to 20, the tire inflation optimization device being configured to predict the optimal inflation pressure for the tire.

24. The aircraft of claim 23, further comprising a tire gas pressure sensor configured to measure the current pressure of the gas in the tire and a tire gas temperature sensor configured to measure the current temperature of the gas in the tire, wherein the tire gas pressure sensor and the tire gas temperature sensor are configured to provide tire gas pressure information and tire gas temperature information to the tire inflation optimization device.

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