Patent Description:
Conventionally, a method for predicting the wear state of a tire mounted on a vehicle such as an automobile has been known.

For example, a method has been established for predicting the wear state (wear life) of a tire on the basis of wear energy at free rolling, at the time applying a toe angle, at the time applying a lateral force, at the time applying a driving force, and at the time applying a braking force, and the wear amount per predetermined traveling distance (See Patent Literature <NUM>. Attention is also drawn to the disclosure of <CIT>.

According to Patent Literature <NUM>, it is possible to predict the wear state of a tire mounted on a vehicle, that is, the amount of wear of the tire with a certain degree of accuracy. However, the following problems occur in the actual operating environment of the vehicle.

Specifically, in order to prevent uneven wear of a tire mounted on a vehicle and to wear the tire uniformly to some extent, the position of a wheel mounted is generally rotated (tire rotation) during the use.

Since the method for predicting the wear state of the tire predicts the wear state from the new tire mounted at the predetermined wheel position, when the tire rotation is performed as this manner, it becomes difficult to accurately predict the wear amount of the tire.

Furthermore, particularly in the case of a heavy load tire mounted on a truck, a bus or the like, the tire is often replaced with another tire in stock, specifically, a new or used tire, or a tire of a different brand or type (Studless tires, etc.) at the time of tire rotation, and it becomes more difficult to predict the wear amount of the heavy load tire.

Accordingly, an object of the present invention is to provide a tire wear prediction system capable of accurately predicting the wear state of a tire even when the tire mounted on a vehicle is rotated or replaced with another tire.

The present invention provides a tire wear prediction system as claimed in claim <NUM>.

Hereinafter, an embodiment will be described based on the drawings. It should be noted that the same or similar reference numerals are given to the same functions and structures, and the description thereof will be omitted as appropriate.

<FIG> is a functional block diagram of the tire wear prediction system <NUM>. A tire wear prediction system <NUM> predicts the wear state of a tire mounted at a predetermined wheel position of a vehicle. Specifically, the tire wear prediction system <NUM> predicts the wear amount from the tire in a new state based on a known prediction method, and accurately predicts the wear amount of the tire even when tire rotation and replacement with another tire are performed.

As known prediction methods, in addition to the aforementioned <CIT>, <CIT> and <CIT> are cited. However, the prediction method is not limited to these methods, and may be any method as long as the amount of wear of the tire mounted at a predetermined wheel position can be predicted based on the traveling state (Traveling speed, acceleration/deceleration/left-right G, steering angle, load, tire pressure, etc.) of the vehicle.

<FIG> is a schematic perspective view of a bus <NUM> equipped with a tire <NUM> to be an object of the tire wear prediction system <NUM>. As shown in <FIG>, the bus <NUM> is a vehicle having two axles, a front wheel axle <NUM> F and a rear wheel axle <NUM> R. The front wheel axle <NUM> F and the rear wheel axle <NUM> R are mounted with a plurality of tires <NUM>.

The front wheel axle <NUM> F is a steering axle, and the tire <NUM> mounted on the front wheel axle <NUM> F is called a steering wheel (steered wheel). The rear wheel axle <NUM> R is a drive axle, and the tire <NUM> mounted on the rear wheel axle <NUM> R is called a drive wheel.

The bus <NUM> is a kind of vehicle to be managed by the tire wear prediction system <NUM>, and is a large vehicle (heavy load vehicle) capable of transporting a large number of passengers. The tire <NUM> mounted on the bus <NUM> is a tire for heavy load.

The bus <NUM> includes various sensors for detecting the value of a parameter (See below. ) indicating the traveling state of the bus <NUM>. Specifically, the bus <NUM> includes sensors for detecting the traveling speed, acceleration, deceleration, left and right G, steering angle, load, and tire pressure. These sensors may be shared with the installation of the bus <NUM> (including tire pressure monitoring systems (TPMS)), or may be installed for predicting the wear state of the tire <NUM>.

<FIG> is an explanatory diagram of the axle configuration of the bus <NUM>. As shown in <FIG>, at the wheel position # <NUM> (POS. <NUM>, position of front left wheel ((<NUM>) in the figure)), the tire <NUM> identified as Tire <NUM> is mounted. At the wheel position # <NUM> (POS. <NUM>, position of front right wheel ((<NUM>) in the figure)), a tire <NUM> identified as Tire <NUM> is mounted.

Similarly, each of POS. <NUM> to <NUM> (left outer rear wheel, left inner rear wheel, right inner rear wheel, right outer rear wheel, ((<NUM>) to (<NUM>) in the figure) is mounted with a tire <NUM> identified as Tire <NUM> - <NUM>.

As shown in <FIG>, the tire wear prediction system <NUM> includes a wear prediction unit <NUM>, a change history acquisition unit <NUM>, a tire database <NUM>, a wear state correction unit <NUM>, and a wear state display unit <NUM>.

These functional blocks are implemented by executing a computer program (Software) on hardware such as a server computer. Specifically, the tire wear prediction system <NUM> includes, as hardware elements, a processor <NUM>, a memory <NUM>, an input device <NUM>, a display <NUM>, and an external IF <NUM>.

The wear prediction unit <NUM> predicts the wear state of the tire <NUM>. Specifically, the wear prediction unit <NUM> predicts the wear state of the new tire <NUM> using the known prediction method described above.

More specifically, the wear prediction unit <NUM> predicts, based on the traveling state of the bus <NUM> (Vehicle), the wear state of the tire <NUM> mounted at a predetermined wheel position (Pos. <NUM>-<NUM> in <FIG>) of the bus <NUM>.

The traveling state of the bus <NUM> is a state of the bus <NUM> determined mainly based on the following parameters. Specifically, Traveling speed, traveling distance, acceleration/deceleration/left-right G, driving force, braking force, lateral force, steering angle, yaw rate, roll rate, pitch rate, load (carrying capacity), and the like can be cited. A wear prediction unit <NUM> predicts the wear state of the tire <NUM> by using part or all of these parameters.

A wear prediction unit <NUM> acquires a parameter indicating the traveling state of the bus <NUM> via a communication network. Specifically, the wear prediction unit <NUM> acquires measurement data from various sensors mounted on the bus <NUM> via a wireless communication network or a combination of a wireless communication network and a wired communication network.

The wear prediction unit <NUM> uses the acquired measurement data to predict the wear state of the tire <NUM> mounted at each wheel position, but the prediction may not necessarily be performed in real time. That is, the prediction of the wear state of the tire <NUM> may be executed as a batch process every predetermined period (For example, on a daily or weekly basis).

The wear state of the tire <NUM> is, in short, the wear amount of the tire <NUM>. Based on the predicted wear state of the tire <NUM>, the depth of the groove formed in the tread of the tire <NUM> (residual groove depth) may be indicated.

The wear prediction unit <NUM> predicts the wear state of the tire <NUM> based on a reference of the wear state corrected by the wear state correction unit <NUM>. Specifically, the wear prediction unit <NUM> acquires the presence/absence of tire rotation or the presence/absence of replacement with another tire from the wear state correction unit <NUM>.

The tire rotation means to change the wheel position of the tire <NUM> (rotation) mounted on the bus <NUM> to the other wheel position among the plurality of tires <NUM> mounted on the bus <NUM>.

Replacement with another tire means replacement with another tire that was not attached to the bus <NUM> (New or used). This includes changes to different tire brands (Product name, etc.) or types (Summer tires and studless tires (winter tire), etc.).

The wear prediction unit <NUM>, when acquiring the information from the wear state correction unit <NUM>, that is, when acquiring the reference of the corrected wear state, refers to the tire database <NUM> as necessary, and changes a prediction method of the wear state of the tire <NUM> and a value of a parameter used for the prediction of the wear state.

Further, when the wear of the tire <NUM> progresses to a certain degree, the remaining groove depth of the tread is reduced to increase the block rigidity of the tread, and therefore, the wear prediction unit <NUM> can switch to a prediction method for delaying the progress of the wear state after the wear of the tire <NUM> progresses to a certain degree (referred to as "tread rigidity modification").

A change history acquisition unit <NUM> acquires a change history of a tire <NUM> mounted on the bus <NUM>. Specifically, the change history acquisition unit <NUM> acquires a change history including the rotation of the wheel position (tire rotation) on which the tire <NUM> is mounted or the content of replacement with another tire.

The change history may be automatically acquired using the ID of the TPMS measurement unit provided on the tire <NUM> (Specifically, tire <NUM> assembled to a rim wheel), or may be acquired by manual or semi-manual input (Use of a hand-held module for reading the ID of the tire <NUM>, etc.) by a user or the like.

The tire database <NUM> comprises items related to tires <NUM> that may be mounted on the bus <NUM>.

<FIG> shows an example of the tire database <NUM>. As shown in <FIG>, the tire database <NUM> includes items of "Tire ID", "Tire type", "Size", "Brand", "residual groove amount", and "wear characteristic".

The "Tire ID" is unique identification information given to the tire <NUM>. "Tire type" is a type corresponding to the performance of the tire <NUM> (In <FIG>, summer, all seasons and studless). The type may depend on the value of rolling resistance, the rigidity of the tread rubber, etc..

"Size" is the size of the tire <NUM> (tread width, wheel diameter), and "Brand" corresponds to a product name of the tire <NUM> (brand name), etc. "residual groove amount" is the remaining groove depth of a groove formed in the tread of the tire <NUM>. In the case of a new one, N. (Not Applicable) is set.

"wear characteristic" is the characteristic (Tread rubber material and rigidity, etc.) of the tire used to predict the wear state of the tire. The wear characteristics are different depending on the axle on which the tire <NUM> is mounted (Front axle <NUM> F (steering axle) or rear axle <NUM> R (drive axle)).

The tread rigidity correction described above is also performed using the "wear characteristic". For example, "A'" and "C'" in <FIG> show wear characteristics after the wear of the tire progresses to a certain degree.

A wear state correction unit <NUM> corrects the standard of the wear state of the tire <NUM> predicted by the wear prediction unit <NUM> based on the change history of the tire <NUM> acquired by the change history acquisition unit <NUM>.

Specifically, when the change history of the tire <NUM> is the rotation of the wheel position (Pos. <NUM>-<NUM> in <FIG>), the wear state correction unit <NUM> corrects the reference of the wear state based on the wheel position after the rotation. For example, when the tire <NUM> is moved from the front wheel axle <NUM> F (POS. <NUM>) to the rear wheel axle <NUM> R (POS. <NUM>), the wear characteristics for the steering wheel are changed to the wear characteristics for the driving wheel. Thus, the reference of the wear state of the tire <NUM> is corrected. In the case of tire rotation, the wear state correction unit <NUM> may automatically change the wear characteristics by using a parameter indicating the traveling state of the bus <NUM>.

Further, when the change history of the tire <NUM> is replacement with another tire, the wear state correction unit <NUM> corrects the standard of the wear state on the basis of at least one of the brand, the type and whether or not the tire is new.

For example, when the tire <NUM> mounted on the POS. <NUM> is replaced from the summer tire of "ABC" (See tire ID = <NUM> in <FIG>) to the summer tire of "ABC" (see tire ID = <NUM>), the wear state correction unit <NUM> changes the wear characteristics used for predicting the wear state of the tire <NUM> from "A" to "A'". As described above, the "A'" indicates the wear characteristics (Tread rigidity has been modified) after the wear of the tire progresses to a certain degree. Thus, the reference of the wear state of the tire <NUM> is corrected.

An abrasion state display unit <NUM> displays the abrasion state of the tire <NUM> predicted by the abrasion prediction unit <NUM>. Specifically, the wear state display unit <NUM> displays the wear state of the tire <NUM> for each wheel position.

<FIG> shows a display example of the wear state of the tire <NUM> by the wear state display unit <NUM>. The horizontal axes (<NUM>) to (<NUM>) of the graph shown in <FIG> correspond to the wheel positions shown in <FIG>. The vertical axis of the graph indicates the wear amount (Units: mm) of the tire <NUM> mounted at each wheel position. The "limit of use" of the wear amount corresponds to the state in which the tread of the tire <NUM> is worn to the limit in which it can be legally used. Typically, the tread-ware indicator is exposed to the tread surface.

In <FIG>, "ideal" is an amount of wear when the vehicle travels the distance at the speed in an ideal state where no excessive wear occurs. In other words, the ideal state is an optimum state in which the operation of the bus <NUM> does not impose an unnecessary burden on the tire. In predicting the wear amount corresponding to the "ideal", the shape of the road on which the bus <NUM> has actually traveled (Road type, road curvature, etc.) may be taken into consideration.

"driving wheel application" is the amount of wear caused by the driving wheels added to the amount of wear of "ideal". "steering wheel application" is the amount of wear caused by the steering wheel applied to the amount of wear of the "ideal". That is, "driving wheel application" means the wear amount increased by the excessive accelerator operation by the driver, and "steering wheel application" means the wear amount increased by the sudden steering operation by the driver.

"load application" is the amount of wear attributable to the load applied to the amount of wear of the "ideal". Specifically, the amount of wear caused by exceeding the standard loading capacity of the bus <NUM> (Number of passengers, etc.).

Thus, the wear state display unit <NUM> can display the wear state of the tire <NUM> for each wear cause.

Next, the operation of the tire wear prediction system <NUM> will be described. Specifically, the prediction operation of the wear state of the tire <NUM> by the tire wear prediction system <NUM> will be described.

<FIG> shows a prediction operation flow of the wear state of the tire <NUM> by the tire wear prediction system <NUM>. As described above, in the present embodiment, the tire <NUM> mounted on the bus <NUM> is rotated or replaced with another tire during use.

As shown in <FIG>, the tire wear prediction system <NUM> predicts the wear amount of the tire <NUM> at each wheel position of the bus <NUM> (S <NUM>). Specifically, as described above, the tire wear prediction system <NUM> predicts the wear state of the tire <NUM> using a parameter indicating the traveling state of the bus <NUM>.

Next, the tire wear prediction system <NUM> checks the existence of the change history of the tire <NUM> (S <NUM>). Specifically, the tire wear prediction system <NUM> checks the presence or absence of tire rotation and replacement with another tire.

When there is a change history of the tire <NUM>, the tire wear prediction system <NUM> determines whether or not the change history is a tire rotation (S <NUM>).

In the case of tire rotation, the tire wear prediction system <NUM> resets the wheel position after rotation and the wear amount of the tire <NUM> up to the rotation (S <NUM>). The tire wear prediction system <NUM> changes the wear characteristics (Steering or driving axle-related, see description of <FIG>) of the tire <NUM> as necessary based on the wheel position after rotation.

When the tire is not rotated, that is, when the tire is replaced with another tire, the tire wear prediction system <NUM> determines whether or not the tire is replaced with a new tire (S <NUM>).

In the case of replacement with a new tire, the tire wear prediction system <NUM> resets the wear amount of the tire <NUM> at the wheel position (S <NUM>).

On the other hand, in the case of replacement with a used tire, that is, replacement with a tire worn over a certain degree, the tire wear prediction system <NUM> acquires the wear amount of the replaced tire (S <NUM>). The replaced tire is both a tire <NUM> mounted on the bus <NUM> before replacement and a used tire newly mounted on the bus <NUM>. Thus, the wear amount of the removed tire <NUM> can be displayed and the wear state of the used tire can be accurately predicted.

The tire wear prediction system <NUM> determines whether the tire after replacement is the same brand and the same size as the tire <NUM> before replacement (S <NUM>).

When the tire after replacement is not the same brand and the same size as the tire <NUM> before replacement, that is, when any of the type, brand or size is different, the tire wear prediction system <NUM> changes the wear characteristics (See the description associated with <FIG>) of the tire <NUM> after replacement (S <NUM>). Specifically, the tire wear prediction system <NUM> changes the wear characteristics corresponding to the brand and size of the replaced tire <NUM>.

<FIG> conceptually shows the prediction of the wear state of the tire <NUM> by the tire wear prediction system <NUM>. As shown in <FIG>, the tire wear prediction system <NUM> starts predicting the wear state of the tire <NUM>. Here, a new tire <NUM> is mounted on the bus <NUM>.

The tire wear prediction system <NUM> predicts the wear state of the tire <NUM> based on the traveling state (Traveling speed, acceleration/deceleration/left-right G, steering angle, load, tire pressure, etc.) of the bus <NUM>. As a result, it is predicted that the amount of residual (remaining) groove amount (residual groove depth) of the tire <NUM> decreases along the straight line α1.

Thereafter, the tire rotation of the tire <NUM> is performed. As described above, the tire wear prediction system <NUM> changes the wear characteristics used for predicting the wear state of the tire <NUM> based on the wheel position, tire type, size, brand (including distinction between new and used), and residual groove amount (Used) on which the tire <NUM> is mounted.

As a result, it is predicted that the remaining groove amount decreases along the straight line α2 after the tire rotation.

In addition, the tire wear prediction system <NUM> can display the wear state of the tire <NUM> as shown in <FIG> at any timing of the above-described steps <NUM> to <NUM>.

According to the embodiment described above, the following effects can be obtained. Specifically, the tire wear prediction system <NUM> corrects the reference (Tire rotation or replacement with another tire) of the predicted wear state of the tire <NUM> based on the acquired change history (wear characteristic) of the tire <NUM>. The tire wear prediction system <NUM> predicts the wear state of the tire <NUM> based on the reference of the corrected wear state.

Therefore, even when the tire <NUM> mounted on the bus <NUM> is rotated or replaced with another tire, the wear state of the tire <NUM> can be accurately predicted using a known prediction method.

In particular, commercial vehicles such as trucks and buses have high frequency of tire rotation and replacement with other tires, and are often replaced with new or used tires or tires of different brand or type (Studless tires, etc.). The tire wear prediction system <NUM> can accurately predict the wear state of the tire <NUM> even in such a case because it corresponds to both tire rotation and replacement with another tire.

In the present embodiment, the tire wear prediction system <NUM> can display the wear state of the tire <NUM> for each wear cause (see <FIG>). Therefore, the driver of the bus <NUM> and the operating body of the bus <NUM> (Bus companies, etc.) can promote the operation of the bus <NUM> and the improvement of the operating method of the bus <NUM>. Thus, the wear life of the tire <NUM> can be extended.

While the contents of the present invention have been described in accordance with the above embodiments, it will be apparent to those skilled in the art that the present invention is not limited to these descriptions and that various modifications and improvements are possible.

For example, in the embodiment described above, the tire for heavy load mounted on the bus <NUM> has been described as an example, but it may be a large-sized vehicle other than the bus such as a truck or a vehicle (Especially for business use).

In the above-described embodiment, the tire wear prediction system <NUM> corresponds to the tire rotation and the replacement with another tire, but may correspond to only one of the tire rotation and the tire replacement depending on the type of the target vehicle.

In the above-described embodiment, the tire wear prediction system <NUM> displays the wear state of the tire <NUM> according to the cause of wear, but such display is not essential. Further, it is possible to indicate only a part of a plurality of causes of wear.

Claim 1:
A tire wear prediction system (<NUM>), comprising:
a wear prediction unit (<NUM>) for predicting a wear state of a tire (<NUM>) mounted at a predetermined wheel position of a vehicle (<NUM>) based on a traveling state of the vehicle;
a change history acquisition unit (<NUM>) for acquiring a change history including rotation of the wheel position on which the tire (<NUM>) is mounted or a content of replacement with another tire; and
a wear state correction unit (<NUM>) for correcting wear characteristics of the tire (<NUM>) predicted by the wear prediction unit (<NUM>) based on the change history, wherein
the wear prediction unit (<NUM>) predicts the wear state of the tire (<NUM>) based on wear characteristics corrected by the wear state correction unit (<NUM>),
characterized in that:
the wear prediction unit (<NUM>) switches to a prediction method for delaying a progress of the wear state after the wear of the tire (<NUM>) has progressed to a certain degree.