TIRE TEMPERATURE ANALYSIS METHODS AND SYSTEMS

Abstract

There is disclosed a method of analysing tire temperature data from a temperature sensor arranged to measure the temperature of a tire on a vehicle. The method comprises receiving tire temperature data from the temperature sensor; receiving further data indicative of at least one different parameter related to the vehicle. The method further comprises determining expected temperature data based at least on the further data; and comparing the tire temperature data to the expected temperature data.

Claims

1. A method of analysing tire temperature data from a temperature sensor arranged to measure the temperature of a tire on a vehicle, the method comprising: receiving tire temperature data from the temperature sensor; receiving further data indicative of at least one different parameter related to the vehicle; determining expected temperature data based at least on the further data; and comparing the tire temperature data to the expected temperature data.

2. The method according to claim 1, further comprising rectifying the tire temperature data based on the comparison of the tire temperature data to the expected temperature data.

3. The method according to claim 2, wherein comparing the tire temperature data and expected temperature data comprises determining a relationship between the tire temperature data and the further data and wherein rectifying the tire temperature data comprises adjusting the tire temperature data based on the relationship.

4. The method according to claim 1, wherein the further data comprises telematics data.

5. The method according to claim 1, wherein the further data comprises ambient temperature data relating to a temperature of an environment in which the vehicle is present.

6. The method according to claim 1, wherein the tire temperature data and further data relate to a period during which the vehicle was stationary and wherein the period begins following a predetermined time after the vehicle has become stationary.

7. The method according to claim 1, wherein the tire temperature data and further data comprise data that corresponds to a period during the night and whilst the vehicle was stationary.

8. The method according to claim 1, further comprising determining a tire-specific parameter based on the comparison of the tire temperature data and the expected temperature data.

9. The method as claimed in claim 1, wherein comparing the tire temperature data to the expected temperature data comprises determining whether the tire temperature data meets a deviation condition and further comprising issuing a warning if the tire temperature data does not meet the deviation condition.

10. The method as claimed in claim 9, wherein the deviation condition comprises a range of acceptable temperature values.

11. The method as claimed in 9, wherein the further data comprises vehicle motion data relating to movement of the vehicle and/or ambient temperature data relating to an environment in which the vehicle is present.

12. The method of claim 1, wherein the further data comprises data from at least one other vehicle.

13. A server, for analyzing temperature data from a temperature sensor arranged to measure the temperature of a tire of a vehicle, the server comprising a processor and a tangible memory storing computer-executable instructions that, when executed by the processor, cause the server to: obtain tire temperature data from a temperature sensor arranged to measure the temperature of a tire on a vehicle; obtain further data indicative of at least one different parameter related to the vehicle; determine expected temperature data based on the further data; and compare the tire temperature data to the expected temperature data.

14. The server according to claim 13, wherein the server is further caused upon execution of the instructions to rectify the tire temperature data based on the comparison of the tire temperature data to the expected temperature data.

15. The server according to claim 14, wherein comparing the tire temperature data and expected temperature data comprises determining a relationship between the tire temperature data and the further data and wherein rectifying the tire temperature data comprises adjusting the tire temperature data based on the relationship.

16. The server according to claim 13, wherein the server is further caused upon execution of the instructions to determine a tire-specific parameter based on the comparison of the tire temperature data and the expected temperature data.

17. (canceled)

18. A computer program product comprising computer-executable instructions embodied in a non-transitory computer readable medium which, when read by a machine, cause the machine to: obtain tire temperature data from a temperature sensor arranged to measure the temperature of a tire on a vehicle; obtain further data indicative of at least one different parameter related to the vehicle; determine expected temperature data based on the further data; and compare the tire temperature data to the expected temperature data.

19. The computer program product according to claim 18, wherein the machine is further caused to rectify the tire temperature data based on the comparison of the tire temperature data to the expected temperature data.

20. (canceled)

21. The server according to claim 13, wherein the further data comprises data from at least one other vehicle.

22. The computer program product according to claim 18, wherein the further data comprises data from at least one other vehicle.

Description

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

[0063] One or more non-limiting examples will now be described, by way of example only, and with reference to the accompanying figures in which:

[0064] FIG. 1 is a schematic overview of a vehicle comprising a plurality of temperature sensors arranged to measure the temperature of the tires on the vehicle;

[0065] FIG. 2 is a flowchart illustrating the rectification of tire temperature data as well as the determination of a tire related parameter;

[0066] FIG. 3 is a flowchart illustrating the issuing of a warning based on the tire temperature data;

[0067] FIG. 4 is a graph illustrating the comparison of tire temperature data to expected temperature data;

[0068] FIG. 5 is a graph illustrating calibration of tire temperature data; and

[0069] FIG. 6 is a graph illustrating the comparison of tire temperature data to expected temperature data over a period time.

DETAILED DESCRIPTION

[0070] FIG. 1 is a schematic representation of a vehicle 2 indicated by the dashed line which is connected to a server 18. The vehicle 2 comprises a plurality of tires 4. A temperature sensor 6 is arranged to measure the temperature of each tire 4 and a pressure sensor 8 is arranged to measure the pressure of each tire 4. The temperature sensors 6 and pressure sensors 8 are connected to a tire pressure monitoring system (TPMS) receiver 10. The TPMS receiver 10, temperature sensors 6 and pressure sensors 8 together form a TPMS. Whilst the vehicle 2 depicted comprises four tires 4, it will be appreciated that it may comprise any number of tires 4. Whilst each of the tires 4 is shown as having a temperature sensor 6 and pressure sensor 8, this is may not always be the case and in some examples only a subset of the tires 4 on the vehicle 2 may comprise temperature sensors 6 and pressure sensors 8. Additionally, the pressure sensors 8 may also be omitted.

[0071] The TPMS receiver 10 is operatively connected to a vehicle electronic control unit (ECU) 12, and a telematics device in the form of a telematics control unit (TCU) 14, via a vehicle bus 16. As depicted, the vehicle ECU 12 may be operatively connected to a vehicle temperature sensor 13 arranged to measure the ambient temperature of the vehicle 2. The ECU 12 may also be operatively connected to a user interface 11 on the vehicle 2. The user interface 11 may comprise a display in the vehicle 2 which outputs information to a driver of the vehicle 2. The TCU 14 may also comprise a TCU temperature sensor 15 which may be capable of detecting the temperature of the TCU 14 itself. In certain instances, the temperature of the TCU 14 may substantially correspond to the ambient temperature of the environment in which the vehicle 2 is present. As will be appreciated, the vehicle temperature sensor 11 and the TCU temperature sensor 15 may be sources of further data. Similarly, the ECU 12 may also be a source of further data as it may obtain data such as location, speed, acceleration, and/or braking data of the vehicle. The ECU 12 may be connected, via the vehicle bus 16 to various sensors on the vehicle 2 which collect further data. The TCU 14 may also be a source of further data. For example, the TCU 14 may comprise a GPS thus allowing the TCU 14 to generate location, speed, acceleration and/or braking data.

[0072] In the embodiment depicted, the TCU 14 is connected to a remote server 18. The TCU 14 may be connected in a wired or wireless manner to the server 18. The server 18 is operatively connected to a weather service 20, TCUs 22A, 22B on other vehicles and a user interface 24. The TCUs 22A, 22B, may provide the server 18, and optionally the ECU 12 and TCU 14, with further data from other vehicles. The weather service 20 may, for example, comprise a repository of information which may serve as further data. For example, the weather service 20 may comprise ambient temperature data and other data such as weather conditions, e.g. rain or snow, for a plurality of different locations. Through knowledge of the vehicles 2 location, it may be possible to interrogate the weather service 20 and obtain appropriate further data relating to the location of the vehicle 2. The server 18 may also be coupled to any other suitable source of further data which may be useful in the analysis of the tire temperature data obtained from the temperature sensors 6.

[0073] Exemplary methods in accordance with embodiments of the present invention will now be described below, with reference to the FIG. 1. The methods described below, unless indicated otherwise, may be performed by any suitable component or combination of components described above. For example, the method may be performed by the ECU 12, the TCU 14 or the server 18. Similarly, the method may be performed by one or more of the ECU 12, the TCU 13 or the server 18 described above. Any of the ECU 12, the TCU 14 or the server 18 may comprise a computer readable medium having a computer program product stored thereon to perform any of the methods described below. The method may also be performed by any other suitable device on the vehicle 2, or remotely of the vehicle 2, that is capable of receiving the tire temperature data and the further data.

[0074] FIG. 2 depicts a method in accordance with an embodiment of the present invention. In a first step tire temperature data 24 is received. The tire temperature data 24 may be received from one or more of the temperature sensors 6 arranged to measure the temperature of each tire 4. In another step, further data 26 indicative of at least one different parameter related to the vehicle 2 is received. The further data 26 may be received from any suitable source and comprise any suitable data. For example, the further data may comprise ambient temperature data received from the temperature sensor 13 connected to the ECU 12, the temperature sensor 15 connected to the TCU 14 or it may comprise ambient temperature data received from the weather service 20. Similarly, the further data may comprise any other suitable data, for example other telematics data such as location, speed, acceleration, braking and/or tire related data from the ECU 12 or the TCU 14.

[0075] In step 28, both the further data 24 and the tire temperature data 26 which corresponds to a period in which the vehicle is stationary and corresponding to a predetermined time after the vehicle becoming stationary is determined. Analysis of data which corresponds to the vehicle 2 being stationary may be achieved by suitably analysing the further data, e.g. location data, to determine when the vehicle 2 was stationary. Similarly, it may be possible to determine from the tire temperature data 24 when the vehicle 2 was stationary. In addition, or alternatively, in some embodiments the data which corresponds to a period during the night and whilst the vehicle 2 was stationary is analysed. Selection of the appropriate data in this instance may be achieved by interrogating a suitable data source, e.g. the weather service 20, to determine the sunset time at the location of the vehicle 2, and data after the sunset may then be used. Similarly, the sunrise time may also be determined and only data up until sunrise may be used in the subsequent analysis.

[0076] In step 30, expected temperature data 31 corresponding to the period in which the vehicle was stationary and after the predetermined time and/or during the night is determined. This expected temperature data 31 is determined based at least in part on the further data 26. For example, when the further data comprises ambient temperature data, the expected temperature data 31 may be determined to be the ambient temperature data. The further data may comprise other data which may impact the expected temperature data 31. For example, the further data may indicate that the vehicle 2 is currently in sunny conditions and so the expected temperature may be based on the ambient temperature data and may be further increased to reflect the additional heating which may occur due to the vehicle 2 being in the sun.

[0077] In step 32, a comparison between the tire temperature data and the expected temperature data is performed. As depicted, this comparison may involve the step 34 of determining a relationship between the tire temperature data and the expected temperature data 31. As discussed previously, this may involve using regression analysis. The exact form of the analysis performed may depend on the form of the relationship between the tire temperature data 24 and the expected temperature data 31. For example, the tire temperature data 24 and the expected temperature data 31 may have a linear relationship and it may be possible to determine an offset and a slope which relates the tire temperature data 24 to the expected temperature data 31. Of course, any other form of relationship may be determined.

[0078] Following the comparison of the tire temperature data 24 and expected temperature data 31, and optionally after the determination of the relationship in step 34, in step 36 the tire temperature data 24 may be rectified. This rectification may involve rectifying the tire temperature data 24 based on the relationship determined in step 34. This results in rectified tire temperature data 38. The rectified tire temperature data 38 may then be used in any required manner and may help to minimise the number of false positive warnings which are generated based on the rectified tire temperature data 38.

[0079] As will be appreciated, the steps described above may be performed in any suitable order. For example, whilst the determination of the expected temperature data 31 is depicted as occurring after the determination of data corresponding to a stationary period and after a predetermined time in step 28, the step 30 of determining expected temperature data may be performed prior to step 28.

[0080] The tire temperature data 24 may comprise any number of tire temperature readings, and the further data 26 may comprise sufficient data to allow for the determination of sufficient expected temperature data 31 in step 30.

[0081] In addition to formation of rectified tire temperature data 38, the method depicted in FIG. 2 also illustrates the optional steps of the determination of a tire related parameter 42. As depicted, the tire temperature data 24 and further data 26 which corresponds to a period during which the tires 4 are cooling may be identified in step 40. This may, for example, be achieved by analysing the tire temperature data 24 to monitor the change in the tire temperature readings within the tire temperature data 24. The data including tire temperature readings which are decreasing, up to the point where they stop decreasing, or at least to the point at which they stop decreasing as significantly, may be considered data which corresponds to a cooling period. The cooling period may also be identified through use of the further data. For example, when the further data comprises ambient temperature data, a threshold temperature which corresponds to the tires being in a cooled state may be determined based on the ambient temperature data. For example, the threshold temperature may correspond to the ambient temperature of the environment in which the vehicle 2 is present. This threshold temperature may thus be used to set the boundaries of the data which corresponds to the tires 4 cooling.

[0082] In step 42, a tire related parameter may be determined based on the data corresponding to the cooling period. The type of the further data 26 and the analysis that is performed may depend on the tire related parameter which is being determined. For example, in the exemplary case whereby a specific heat transfer coefficient for the tire 4 is determined, in addition to the steps depicted, expected temperature data, similarly with respect to step 31 described above, may also be determined. This expected temperature data may be compared to the tire temperature data 24 and analysis as to how the tire 4 cools may allow determination of the tire specific heat transfer coefficient. Additionally, whilst the Figure depicts the use of the original tire temperature data 24, steps 40 and 42 may be performed using the rectified tire temperature data 38. This may improve the analysis of the data and allow a tire related parameter to be determined more accurately.

[0083] FIG. 3 illustrates another embodiment which depicts the detection of tire temperature data 24 which indicates a tire related issue. Similarly with respect to the embodiment described above, tire temperature data 24 is received and further data 26 indicative of a different parameter related to the vehicle is also received. The tire temperature data 24 and further data 26 may be the same data used in the rectification process shown in FIG. 2. However, in some embodiments, the tire temperature data 24 and further data 26 may comprise different data. For example, the tire temperature data 24 and the further data 26 may comprise data which corresponds to the vehicle 2 when moving. Accordingly, the method depicted in FIG. 3 may be performed whilst the vehicle 2 is moving and thus indicate issues with a tire 4 during movement of the vehicle 2. Of course, the method may nonetheless be applied with the vehicle is stationary.

[0084] As depicted, in step 44 tire temperature data 24 and further data 26 is collected. In step 46, the expected temperature data 47 is determined based at least partially on the further data 26. The further data 26 may comprise any data which may be suitable for use in determining the expected temperature data 47, particularly data which is suitable for use when the vehicle 2 is in motion. The further data 26 may, for example, comprise ambient temperature data, which may be determined from the temperature sensors 13, 15, from the other TCUs 22A, 22B, or from the weather service 20, as well as other suitable data. The other data may, for example, comprise speed, acceleration, braking data as well as other data such as weight data, weather data and/or tire related data. All of this data may be used to form expected temperature data 47. The determination of the expected temperature data 47 may, for example, comprise taking the ambient temperature data and adjusting this data to account for the speed of the vehicle 2, as well as its recent braking conditions, and also potentially account for the possibility of weather conditions such as rain or snow which may impact the expected tire temperature. The use of all of this data may improve determination of the expected temperature data 47 and thus minimise the likelihood of the detection of false positives. As will be appreciated, the determination of the expected temperature data 47 performed in step 46 may utilise a model which accounts for the various different further data 26. The model used may be specific to the vehicle 2 being analysed.

[0085] In step 48 it is determined whether the tire temperature data 24 meets a deviation condition. As discussed previously, the deviation condition may be any condition that is used to indicate an issue with a tire 4. For example, it may comprise an acceptable deviation from the expected temperature data 47. For example, the deviation condition may stipulate that the tire temperature data can be within a specific temperate difference, e.g. 2° C., above or below the expected temperature data 47. The deviation condition may be a fixed deviation which is pre-set. However, in some embodiments, the deviation condition may be variable and may at least partially depend on the further data 26. For example, in situations whereby the vehicle is travelling at a variable speed, the deviation condition may allow for a greater variation in temperature to account for the possibility that the tire temperature may be varying. In contrast, when the vehicle 2 is travelling at a constant speed, variations in temperature may be less and so the range of acceptable temperature values set by the deviation condition may be smaller. This is just one example of how the further data may impact the deviation condition and the further data 26 may at least partially define the deviation condition in any suitable manner.

[0086] In the situation where the tire temperature data 24 does not meet the deviation condition, a warning may be issued in step 50. In some embodiments, this warning may be issued to a driver of the vehicle 2, for example by the ECU 12 causing the issuance of a warning to a user interface 11 on the vehicle 2. The warning may be issued via the user interface 11 irrespective of where the method described above is performed. For example, if the method is performed by the ECU 12, the ECU 12 may directly issue the warning. Where the method is performed by the TCU 12, the TCU 12 may communicate with the ECU 12 to issue the warning by the user interface 11. Similarly, where the method is performed by the remote server 18, the server 18 may also communicate with the ECU 12 to issue the warning via the user interface 11.

[0087] Similarly, the warning may also be issued to the user interface 24 connected to the server 18. When the server 18 performs the method described above, the server 18 may communicate directly with the user interface 24. In embodiments wherein the ECU 12, or the TCU 14 performs the method, the ECU 12 or TCU 14 may communicate the warning to the server 18 and the server 18 may go on to issue the warning to the user interface 24.

[0088] The use of a deviation condition which is assessed based on the expected temperature data which is formed based on the further data 26 may reduce the number of false positive warnings which are issued. In the embodiment depicted in FIG. 3, the tire temperature data 24 is the temperature data received from the temperature sensors 6 without being rectified. However, as will be appreciated, the tire temperature data 24 may be rectified to form rectified tire temperature data 38 as shown in FIG. 2, and the rectified tire temperature data 38 may instead be used in the method shown in FIG. 3. This may improve the analysis and further minimise the number of false positive warnings issued.

[0089] FIG. 4 shows a plot of measured tire temperature data against expected temperature data and illustrates the comparison of tire temperature data to expected temperature data. Expected temperature data 52 is illustrated by the solid line, and a deviation condition in the form of acceptable temperature range 54, 56 is illustrated by the dashed lines. Tire temperature data 58A, 58B illustrated by crosses is also plotted. For a given measured temperature value 56A, 56B, the expected temperature corresponding to the tire temperature value 56A, 56B is determined and the measured temperature value 56A, 56B is then plotted accordingly. As will be appreciated, the expected temperature for the given tire temperature data 58A, 58B, may be determined based on any suitable further data as described above. For example, for a given tire temperature data 56A, 56B value the expected temperature data 52 may be determined based on a one or more different items of further data, e.g. a combination of ambient temperature data, motion data relating to the vehicle and/or any other suitable further data such as tire related data, e.g. tire type, tire age etc.

[0090] When the expected temperature data 52 has been determined for the tire temperature data, the tire temperature data 58A, 58B is then plotted at the relevant points as illustrated. It is then determined whether the tire temperature data 58A, 58B meets a deviation condition. In the example depicted, it is determined whether the tire temperature data 58A, 58B falls within the acceptable temperature range 54, 56 illustrated by the dashed lines. As depicted, the tire temperature measurement 58A falls outside of the range of accepted temperature values 54, 56. As a result, a warning may be issued for this particular tire temperature measurement 58A. Comparatively, the tire temperature measurement 58B falls within the range of accepted temperature range 54, 56 and thus no warning may be issued based on this data point. The tire temperature data 58A, 58B, in the example depicted, may have been collected at different points in time which may be the reason for the different expected temperature data 52 for each of the tire temperature data points 58A, 58B.

[0091] As shown in FIG. 4, the range of accepted temperature values 54, 56 illustrated by the dashed lines may be dependent on the further data and may vary accordingly. For example, the range of accepted temperature values 54, 56 may change in a non-linear manner.

[0092] FIG. 5 shows a graph illustrating measured tire temperature, i.e. tire temperature data, plotted against ambient temperature, i.e. a form of further data which may correspond to expected temperature. The graph illustrates the rectification of tire temperature data. The data in the graph is illustrative of tire temperature data which corresponds to a period during which the vehicle is stationary and in which tire has cooled down to the ambient temperature of the environment in which it is present. When the tire is at the ambient temperature, the temperature of the tire should, at least theoretically, match the ambient temperature of the environment in which it is located. Accordingly, the dashed line 60 represents the measured tire temperature from an ideal temperature sensor. As shown, for such an ideal temperature sensor, the measured tire temperature matches the ambient temperature. However, as will be appreciated, real temperature sensors may not, for a variety of different reasons, necessarily output a temperature which directly corresponds to the ambient temperature.

[0093] The crosses 62, on FIG. 5, indicate measured tire temperatures and are plotted at the ambient temperature at the time at which they were measured. The solid line 68 represents a relationship between the measured tire temperature data and the ambient temperature data. The solid line 68 includes the offset and slope of the relationship. This relationship may be used to rectify the tire temperature data. The dashed lines 64, 66 represent the residuals, i.e. the remaining measurement error. Any measured tire temperature data that falls within the residuals indicated by the dashed lines 64, 66 will be considered to fall within acceptable rectification, i.e. calibration, margins.

[0094] Whilst ambient temperature is plotted in the graph described above, any suitable type of further data may be used in order to rectify the tire temperature data.

[0095] FIG. 6 shows a graph illustrating tire temperature data, i.e. measured tire temperatures, and expected temperature data over a period of time. As depicted, the expected temperature data 70 corresponding the period of time is plotted. Additionally, upper and lower limits of an acceptable range 72 for the expected temperature data 70 are also plotted. The acceptable range 72 represent a deviation condition. In the exemplary case illustrated, the time period may correspond to a time spanning part of the night and into the morning whereby the expected temperature data 70 indicates a gradual decrease and subsequent increase in expected temperature. The expected temperature data 70, and the acceptable range 72, may be formed on the basis of ambient temperature data, for example. Of course any other further data may also be utilised. Whilst the graph illustrates the expected temperature data and tire temperature data over a period of time spanning the night into the morning, it will be appreciated that any other period may be plotted and a similar analysis may be performed. For example, expected temperature data and tire temperature data corresponding to a period during which the vehicle is moving may be analysed.

[0096] In addition to the expected tire temperature data 70, tire temperature data 74A-74D, i.e. temperature data from a temperature sensor 6 arranged to measure the temperature of the tire 4, is also plotted on the graph and is depicted by crosses. As will be appreciated, when the tire temperature data 74A, 74C, for example, is within the acceptable range 72, it may be assumed that the tire temperature is acceptable, and thus no warning will be issued. However, as depicted, at certain times, the tire temperature data 74B, 74D may be outside of the acceptable range 72. Accordingly, the tire temperature data 74B, 74D may not meet a deviation condition and a warning may thus be issued. As discussed previously, the warning may be issued on any suitable user interface. When the tire temperature data 74B, 74D falls outside of the acceptable ranges 72 it may be concluded that the tire has become damaged, is too old, or has become worn. A user of the vehicle, or a fleet manager, may then arrange for replacement of the vehicle tire which may help to ensure the safety of the vehicle.

[0097] While the invention has been described in detail in connection with only a limited number of embodiments, it should be readily understood that the invention is not limited to such disclosed embodiments. Rather, the invention can be modified to incorporate any number of variations, alterations, substitutions or equivalent arrangements not heretofore described, but which are commensurate with the scope of the invention. Additionally, while various embodiments of the invention have been described, it is to be understood that aspects of the invention may include only some of the described embodiments. Accordingly, the invention is not to be seen as limited by the foregoing description, but is only limited by the scope of the appended claims.