JP5126048B2 - Tire pressure monitoring device - Google Patents

Description

  The present invention relates to a tire air pressure monitoring device that monitors a decrease in air pressure of each tire mounted on a vehicle wheel, and in particular, even when a vehicle tire is replaced with one having characteristics different from a genuine product, The present invention relates to a tire air pressure monitoring device capable of maintaining a determination accuracy related to a decrease in tire air pressure at a high level.

  Conventionally, a tire pressure monitoring system (TPMS: Tire Pressure Monitoring System) that monitors the air pressure of each tire mounted on a vehicle wheel in real time and warns the occupant when a decrease in air pressure is detected is known. .

  This TPMS can be classified from the viewpoint of air pressure detection method. Each tire has a built-in air pressure sensor to directly measure tire air pressure, and the detection value of ABS (Anti-lock Brake System) wheel speed sensor. There is an indirect type that indirectly estimates the tire pressure based on.

  Among these, the former direct TPMS can realize highly accurate air pressure detection, but has a problem that its configuration is complicated and expensive, and such a difficulty has been a factor in stopping its adoption. .

  Therefore, the indirect TPMS that is simpler and lower in cost than the direct type is attracting attention. The indirect TPMS mainly estimates the tire air pressure based on the relative wheel rotational speed difference based on the wheel speed data from the wheel speed sensor, and the wheel (tire) resonance based on the wheel speed data. Some estimate the tire pressure from the frequency.

  Of these, the former is a wheel fitted with a tire with reduced air pressure, and the wheel with a smaller tire diameter, ie, Dynamic Load Radius, is fitted with other normal pneumatic tires. This is based on the principle that the wheel speed is higher than that (see Patent Document 1, for example).

  On the other hand, the latter is based on the principle that the resonance frequency is lower in a wheel equipped with a tire having a reduced air pressure compared to when the tire has a normal air pressure (see, for example, Patent Document 2).

  According to the related arts disclosed in Patent Documents 1 and 2, a dynamic load radius or resonance frequency based on wheel speed data during normal traveling and a determination threshold value for reducing tire air pressure (for example, preset by an automobile manufacturer). Based on the above, it is possible to indirectly determine whether or not the tire air pressure has decreased without requiring an air pressure sensor.

  However, in the indirect TPMS according to the above-described prior art, for example, when a vehicle tire is replaced with one having a characteristic different from that of a genuine product (for example, a tire having a different diameter or tread width, or a winter tire), Due to the difference in tire characteristics, there is a concern that the determination accuracy related to the decrease in air pressure in TPMS may deteriorate.

That is, for example, when 50 kPa is preset in the TPMS as the determination threshold for reducing the air pressure, if the dynamic load radius of the tire is reduced by 1 mm when the air pressure is reduced by 50 kPa, the TPMS is When a decrease in the dynamic load radius for 1 mm is detected, a warning related to a decrease in air pressure is issued. Under such a premise, when a genuine tire is replaced with a tire having a characteristic that the dynamic load radius of the tire is reduced by 1 mm when the air pressure is reduced by 100 kPa, the TPMS is changed when the air pressure is reduced by 50 kPa. When the air pressure drops by 100 kPa (the dynamic load radius of the tire in this case is 1 mm), the warning about the air pressure drop is finally given. Will do. As described above, in the indirect TPMS, when the vehicle tire is replaced with one having a characteristic different from that of the genuine product, the relationship between the determination threshold for lowering the air pressure and the evaluation index (the dynamic load radius of the tire in the above example) matches. As a result, there is a possibility that the determination accuracy related to the decrease in air pressure in TPMS may deteriorate.
JP-A-6-92114 JP-A-8-72514

  The problem to be solved is that, in the conventional indirect TPMS, for example, when the vehicle tire is replaced with one having a characteristic different from that of a genuine product, there is a possibility that the determination accuracy related to the decrease in air pressure in the TPMS may deteriorate. .

It is an object of the present invention to provide a tire pressure monitoring device capable of maintaining a high level of determination accuracy related to a decrease in tire air pressure even when a vehicle tire is replaced with one having a characteristic different from that of a genuine product. Vehicle speed detecting means for detecting the vehicle speed of the vehicle, wheel speed detecting means for detecting a wheel speed of a wheel provided in the vehicle, and air pressure of a tire mounted on the wheel based on a detection output of the wheel speed detecting means Evaluation index deriving means for deriving an evaluation index for evaluating the vehicle, vehicle speed detected from the vehicle speed detecting means in a state where the air pressure is adjusted to a predetermined recommended air pressure, and an evaluation index derived from the evaluation index deriving means, A vehicle that is detected from the vehicle speed detection means in a state in which the air pressure is adjusted to a predetermined excess air pressure that is higher than the recommended air pressure. And an evaluation index derived from the evaluation index deriving means in association with each other and learning, the learning result by the normal condition learning means and the learning result by the excess condition learning means with reference to the learning result of the vehicle Air pressure drop monitoring means for monitoring the air pressure drop based on the vehicle speed detected from the vehicle speed detection means during normal traveling and the evaluation index derived from the evaluation index deriving means, and the vehicle has a plurality of wheels. The normal state learning unit and the excess state learning unit simultaneously perform learning on different wheels, and the air pressure decrease monitoring unit decreases the air pressure of tires mounted on the plurality of wheels. It is the main feature that it is configured to monitor each .

In the tire pressure monitoring apparatus according to the present invention, the evaluation index deriving unit derives an evaluation index for evaluating the air pressure of the tire mounted on the wheel based on the detection output of the wheel speed detecting means. Next, the normal state learning unit learns by associating the vehicle speed detected from the vehicle speed detecting unit with the evaluation index derived from the evaluation index deriving unit in a state where the tire pressure is adjusted to a predetermined recommended air pressure. On the other hand, the excess state learning means includes a vehicle speed detected from the vehicle speed detection means and an evaluation index derived from the evaluation index deriving means in a state where the tire air pressure is adjusted to a predetermined excess air pressure higher than the recommended air pressure. Learn by associating. The air pressure drop monitoring means refers to the learning result by the normal state learning means and the learning result by the excess state learning means, and derives the vehicle speed detected from the vehicle speed detection means during normal driving of the vehicle and the evaluation index. The air pressure drop is monitored based on the evaluation index derived from the means. The vehicle has a plurality of wheels, and the normal state learning means and the excess state learning means simultaneously execute learning on different wheels, and the air pressure drop monitoring means is provided on each of the plurality of wheels. Each of the mounted tires is configured to monitor a decrease in air pressure. Therefore, even when the vehicle tire is replaced with one having a characteristic different from that of a genuine product, the determination accuracy related to the decrease in tire air pressure can be maintained at a high level.

  Even if the vehicle tire is replaced with one having a characteristic different from that of the genuine product, the normal state learning is aimed at obtaining a tire pressure monitoring device capable of maintaining the judgment accuracy relating to the tire pressure drop at a high level. The air pressure based on the vehicle speed detected from the vehicle speed detection means during normal driving of the vehicle and the evaluation index derived from the evaluation index deriving means with reference to the learning result by the means and the learning result by the excess state learning means This was realized by means of air pressure drop monitoring means for monitoring the drop in pressure.

  Hereinafter, a tire pressure monitoring apparatus according to an embodiment of the present invention will be described in detail with reference to the drawings.

[Schematic configuration around the tire pressure monitoring device]
FIG. 1 is an overall configuration diagram of a vehicle equipped with a tire pressure monitoring device according to an embodiment of the present invention.

  A vehicle 11 shown in FIG. 1 is a four-wheeled vehicle having four wheels: a right front wheel W-FR, a left front wheel W-FL, a right rear wheel W-RR, and a left rear wheel W-RL.

  Each wheel W (W-FR, W-FL, W-RR, W-RL) is equipped with a tire T (T-FR, T-FL, T-RR, T-RL) and corresponding to each. The wheel speed sensor S (S-FR, S-FL, S-RR, S-RL) is provided. These four wheel speed sensors S are originally sensors provided for ABS (Anti-lock Brake System), but in the present invention, they correspond to wheel speed sensors ("wheel speed detecting means" of the present invention). .) By using the detected value of S, an evaluation index (dynamic load radius and resonance frequency) for evaluating the air pressure of the tire T is derived. In the following description, FR attached to various symbols (S, T, W) indicates a right front wheel, FL indicates a left front wheel, RR indicates a right rear wheel, and RL indicates a left rear wheel.

  The four wheel speed sensors S are, for example, general sensors that generate wheel speed pulses using Hall elements or the like, and corresponding wheels (W-FR, W-FL, W-RR, W-RL), respectively. The wheel speed pulse is output as a wheel speed signal. The wheel speed pulse generated by each wheel speed sensor S increases as the wheel speed increases, and the number of pulses per unit time increases as the wheel speed decreases. The wheel speed can be measured based on the wheel speed pulse. It should be noted that the wheel speed obtained from the wheel speed pulse increases as the dynamic pressure radius decreases as the tire air pressure decreases.

  An ECU 15 is connected to these four wheel speed sensors S via a communication line 13, and an ignition switch (hereinafter abbreviated as “IG switch”) 17 and an operation at the start of learning to be described later are connected to the ECU 15. Reset switch (hereinafter abbreviated as “RST switch”) 19, a vehicle speed sensor 21 for detecting the absolute speed of the vehicle, a display 23 for displaying various information relating to the vehicle, and a sound relating to a decrease in air pressure. A speaker 25 used for issuing an alarm is connected to each other.

  ECU15 which has the function which performs the overall control of the electrical system of the vehicle 11, and comprises the principal part of the tire pressure monitoring apparatus which concerns on this invention is the wheel speed signal (wheel speed pulse) output from each wheel speed sensor S, respectively. Based on the evaluation index deriving unit (corresponding to the “evaluation index deriving means” of the present invention) 31 for deriving an evaluation index for evaluating the air pressure of the tire T mounted on each wheel W, and the tire T Learning by associating the vehicle speed detected by the vehicle speed sensor 21 with the evaluation index derived by the evaluation index deriving unit 31 in a state where the air pressure is adjusted to a predetermined recommended air pressure (specifically, for example, a recommended value of an automobile manufacturer) A normal state learning unit (corresponding to “normal state learning means” of the present invention) 32 and a vehicle speed control in a state where the air pressure of the tire T is adjusted to a predetermined excess air pressure higher than the recommended air pressure. An excess state learning unit (corresponding to “excess state learning means” of the present invention) 33 that learns by associating the vehicle speed detected by the sensor 21 with the evaluation index derived by the evaluation index deriving unit 31; and a normal state A tire based on the vehicle speed detected by the vehicle speed sensor 21 and the evaluation index derived by the evaluation index deriving unit 31 when the vehicle 11 is traveling normally with reference to the learning result by the learning unit 32 and the learning result by the excess state learning unit 33 And an air pressure drop monitoring unit (corresponding to “air pressure drop monitoring means” of the present invention) 35 for monitoring the air pressure drop of T.

  In addition, the air pressure drop monitoring unit 35 includes a data storage unit 41 for storing various data such as evaluation index data derived for each of a plurality of different air pressure values and for each of a plurality of vehicle speed ranges, and normal state learning. The tire T based on the vehicle speed detected by the vehicle speed sensor 21 and the evaluation index derived by the evaluation index deriving unit 31 with reference to the learning result by the unit 32 and the learning result by the excess state learning unit 33. The warning necessity / non-necessity determination unit 43 that determines whether or not the air pressure of the tire T needs to be reduced. And a notification control unit 45 that performs notification control such as notifying an occupant of a warning message related to a decrease in the air pressure of the tire T via the speaker 25.

[Operation of tire pressure monitoring device]
Next, the operation of the tire pressure monitoring device according to the embodiment of the present invention will be described in detail separately for the learning travel and the normal travel. Among these, the operation of the tire pressure monitoring device during the learning run will be described in detail separately for the first embodiment and the second embodiment.

[Operation of Tire Pressure Monitoring Device During Learning Travel According to Example 1]
First, the operation of the tire air pressure monitoring device during learning travel according to the first embodiment will be described with reference to FIGS.

  2 is an operation flowchart showing the flow of the main routine program during the learning run according to the first embodiment. FIG. 3 is an operation flowchart showing the flow of the subroutine program during the learning run according to the first embodiment. 1) is an explanatory diagram showing the adjusted air pressure of each tire T during the first learning run according to the first embodiment, and FIG. 4 (2) is a diagram of each tire T during the second learning run according to the first embodiment. FIG. 5 is an explanatory diagram showing the adjusted air pressure, FIG. 5 is an explanatory diagram showing an evaluation index (dynamic load radius) characteristic according to a change in air pressure at a vehicle speed of 60 km / h, and FIG. 6 (1) is a modification of the first embodiment. FIG. 6B shows the adjusted air pressure of each tire T during the second learning travel according to the modified example of the first embodiment. It is explanatory drawing.

  For example, when the vehicle tire is replaced with a winter tire (studless tire) having a characteristic different from that of a genuine product prior to the arrival of a full-fledged snowfall season, the operator must confirm that the tire T is at a normal temperature. After confirmation, the air pressure of all tires T is adjusted to a specified pressure (corresponding to the “recommended air pressure” of the present invention) predetermined in the present system (step S201). Specifically, as shown in FIG. 4 (1), the operator adjusts the air pressure of all tires T to the recommended air pressure (recommended air pressure of the automobile manufacturer) related to the vehicle 11. When the air pressure adjustment work for all the tires T in step S201 is completed, preparation for the first learning run (corresponding to the “first learning run” of the present invention) is completed.

  The ECU 15 constantly monitors the on / off state of the IG switch 17 and the on / off state of the RST switch 19 (steps S202 to S203). If both the IG switch 17 is turned on ("Yes" in step S202) and the RST switch 19 is turned on ("Yes" in step S203) are detected during this monitoring, the ECU 15 performs a predetermined learning travel. Of the number of times (2 times in the present embodiment 1), the number of times of the learning run this time is checked by checking the value of “n” related to the n-th learning run (step S204). Here, since learning travel has not yet started (n = 0, “No” in step S204), the ECU 15 advances the process flow to the next step S205. In addition, as a memory for holding the value of “n” related to the n-th learning run, for example, NVRAM (Non Volatile RAM) from a request to hold the stored contents regardless of whether or not power is supplied from an in-vehicle battery (not shown). ) And the like can be suitably used.

  In step S205, the ECU 15 sets “1” to the value of “n” related to the n-th learning travel. As a result, the ECU 15 causes the flow of processing to jump to the subroutine program SUB (see FIG. 3) related to the first learning run (first learning run).

  In the subroutine program SUB, as shown in FIG. 3, processing related to the first learning travel (first learning travel) is sequentially performed.

  That is, the ECU 15 displays on the display screen of the display 23 that the first learning run is started (step S301), thereby notifying the passenger of that fact. In response to this, the occupant starts the first learning run.

  The ECU 15 constantly monitors the on / off state of the IG switch 17 and the vehicle speed pulse of the vehicle speed sensor 21 (step S302). If both the ON state of the IG switch 17 and the output of the vehicle speed pulse are detected during this monitoring, the ECU 15 determines that the first learning run has been started by the occupant ("Yes" in step S302). Note that the driver may travel while changing the speed according to traffic conditions in the learning travel (hereinafter the same) as in the normal travel.

  Next, the evaluation index deriving unit 31 included in the ECU 15 is based on a wheel speed signal (wheel speed pulse) output from each wheel speed sensor S, and a plurality of predetermined vehicle speed ranges (for example, 30 km / h, 60 km / h, 90 km / h, etc.) are used for evaluation indices (specifically, dynamic load radius data and resonance frequency data) for evaluating the air pressure of the tire T mounted on each wheel W. Evaluation index data derived for each of a plurality of vehicle speed ranges is stored in a predetermined storage area (a storage area for evaluation index data during the first learning travel) in the data storage unit 41 built in the ECU 15. (Steps S303 to S304). At this time, the normal state learning unit 32 uses the vehicle speed detected by the vehicle speed sensor 21 and the evaluation index derived by the evaluation index deriving unit 31 in the first learning traveling (a state in which the air pressure of the tire T is adjusted to the recommended air pressure). Learn by associating.

  In obtaining dynamic load radius data in step S303, the width of the wheel speed pulse is measured based on the wheel speed signal (wheel speed pulse) output from each wheel speed sensor S, and the measured value is obtained. It may be acquired as dynamic load radius data, or the number of wheel speed pulses per unit time may be counted, and the count value may be acquired as dynamic load radius (correlation) data.

  In addition, when acquiring the resonance frequency data in step S304, the wheel speed for each wheel W is calculated for each predetermined time based on the wheel speed signal (wheel speed pulse) output from each wheel speed sensor S. In order to extract the frequency component from the waveform signal at the wheel speed, for example, fast Fourier transform (FFT) calculation is performed, the frequency analysis is performed to obtain the resonance frequency, and the resonance frequency thus obtained is used as resonance frequency (correlation) data. Get it. By the way, when traveling on the road surface, the tire T vibrates by receiving force due to minute unevenness on the road surface, and a torsional moment, vertical force, longitudinal force, lateral force, etc. are generated around the tire axle. From the relationship between the direction spring and the mass (moment of inertia), the tire T is in a resonance state. The resonance frequency at that time strongly correlates with the air pressure of the tire T. When the air pressure of the tire T increases, the resonance frequency also increases. When the air pressure of the tire T decreases, the resonance frequency also decreases. Therefore, the state of the air pressure of the tire T can be known by monitoring the transition of the resonance frequency data.

  Next, the ECU 15 checks the acquisition status of the evaluation index data based on the stored contents of the memory area (step S305).

  As a result of the data acquisition status check in step S305, when it is determined that the data acquisition is not yet completed, the ECU 15 refers to the elapsed time from the start of the first learning travel to the current time in advance. It is checked whether or not a predetermined learning travel time (for example, a time that can be appropriately changed, such as 30 minutes) has elapsed (step S306).

  When it is determined that the learning travel time has not yet elapsed (time-up) as a result of the learning travel time elapse check in step S305, the ECU 15 returns the process flow to step S303 and performs the following processing. Is executed.

  On the other hand, as a result of the data acquisition status check in step S305, it is determined that the data acquisition is completed, or as a result of the learning travel time elapse check in step S305, the learning travel time has elapsed (time up). When the determination is made, the ECU 15 notifies the occupant of the fact by displaying on the display screen of the display device 23 that the first learning run has been completed (step S307). In response, the occupant knows that the first learning run has ended.

  Next, the ECU 15 sets the fact that the first learning travel has ended in the nth learning travel end flag, and then returns the processing flow to the main routine program (step S308). The n-th learning travel end flag is a flag indicating that the n-th learning travel has ended, and is used when determining whether or not the n-th learning travel has ended in step S206 described below. .

  Now, returning to the main routine and continuing the description, in step S206 shown in FIG. 2, the ECU 15 checks the set value of the n-th learning travel end flag to obtain “n (in this case, n = 1) -th learning. It is determined whether or not “travel” has ended (step S305).

  As a result of the determination in step S305, when it is determined that “n (in this case, n = 1) th learning run” has not yet been completed, the ECU 15 returns the processing flow to the subroutine program SUB, The following processing is executed.

  On the other hand, as a result of the determination in step S305, when it is determined that “n (in this case, n = 1) th learning travel” is completed, the ECU 15 sets the value of “n” related to the nth learning travel. Increment (in this case, “n = 1 + 1 = 2”).

  Next, the ECU 15 checks whether or not the value of “n” related to the n-th learning travel exceeds a preset number of times of learning travel, thereby determining whether or not all the learning travels have ended. This is performed (step S208). In this example, the preset number of times of learning travel is “2”, the value of “n” related to the n-th learning travel is “2”, and the value “2” of “n” is preset. Since the number of times of learning travel “2 times” has not yet been exceeded, it is determined that all the learning travels have not yet been completed. In step S208, when the value of “n” related to the n-th learning run becomes “3”, it is determined that all the learning runs have been completed.

  As a result of the determination in step S208, when it is determined that all the learning runs have not been completed, the ECU 15 returns the process flow to step S201, and sequentially executes the following processes.

  That is, when the description is continued along the above-described processing flow, in this case, the first learning travel is finished, and the second learning travel (corresponding to the “second learning travel” of the present invention) is performed. Since this is a scene to be performed, the operator adjusts the air pressure of all tires T to a designated pressure (corresponding to “excess air pressure” of the present invention) that is predetermined for the second learning run (step S201). Specifically, as shown in FIG. 4B, the worker adjusts the air pressure of all tires T to a value obtained by adding 30 kPa to the recommended value related to the vehicle 11. When the air pressure adjustment work for all the tires T in step S201 is completed, the preparation for the second learning travel is completed.

  The ECU 15 constantly monitors the on / off state of the IG switch 17 and the on / off state of the RST switch 19 (steps S202 to S203). If both the IG switch 17 is turned on ("Yes" in step S202) and the RST switch 19 is turned on ("Yes" in step S203) are detected during this monitoring, the ECU 15 performs a predetermined learning travel. Of the number of times (2 times in the present embodiment 1), the number of times of the learning run this time is checked by checking the value of “n” related to the n-th learning run (step S204). Here, since the second learning run is started (n = 2, “Yes” in step S204), the ECU 15 changes the processing flow to the subroutine program SUB related to the second learning run (second learning run). Jump to (see FIG. 3).

  In the subroutine program SUB, as shown in FIG. 3, processing related to the second learning travel (second learning travel) is sequentially performed.

  That is, the ECU 15 notifies the occupant of the fact by displaying on the display screen of the display 23 that the second learning travel is started (step S301). In response to this, the occupant starts the second learning run.

  The ECU 15 constantly monitors the on / off state of the IG switch 17 and the vehicle speed pulse of the vehicle speed sensor 21 (step S302). If both the ON of the IG switch 17 and the output of the vehicle speed pulse are detected during this monitoring, the ECU 15 determines that the second learning travel has been started by the occupant ("Yes" in step S302).

  Next, the evaluation index deriving unit 31 included in the ECU 15 is based on a wheel speed signal (wheel speed pulse) output from each wheel speed sensor S, and a plurality of predetermined vehicle speed ranges (for example, 30 km / h, 60 km / h, 90 km / h, etc.) are used for evaluation indices (specifically, dynamic load radius data and resonance frequency data) for evaluating the air pressure of the tire T mounted on each wheel W. Evaluation index data derived for each of a plurality of vehicle speed ranges is stored in a predetermined storage area (a storage area for evaluation index data at the time of second learning travel) in the data storage unit 41 built in the ECU 15 ( Steps S303 to S304). At this time, the excess state learning unit 33 uses the vehicle speed detected by the vehicle speed sensor 21 and the evaluation index derived by the evaluation index deriving unit 31 in the second learning travel (a state in which the air pressure of the tire T is adjusted to the excess air pressure). Learn by associating.

  Next, the ECU 15 checks the acquisition status of the evaluation index data based on the stored contents of the memory area (step S305).

  As a result of the data acquisition status check in step S305, when it is determined that the data acquisition is not yet completed, the ECU 15 refers to the elapsed time from the start of the second learning travel to the current time in advance. It is checked whether or not a predetermined learning travel time (for example, a time that can be appropriately changed, such as 30 minutes) has elapsed (step S306).

  When it is determined that the learning travel time has not yet elapsed (time-up) as a result of the learning travel time elapse check in step S305, the ECU 15 returns the process flow to step S303 and performs the following processing. Is executed.

  On the other hand, as a result of the data acquisition status check in step S305, it is determined that the data acquisition is completed, or as a result of the learning travel time elapse check in step S305, the learning travel time has elapsed (time up). When the determination is made, the ECU 15 notifies the occupant of the fact by displaying on the display screen of the display 23 that the second learning travel has ended (step S307). In response, the occupant knows that the second learning run has ended.

  Next, the ECU 15 sets the n-th learning travel end flag to the effect that the second learning travel has ended, and then returns the processing flow to the main routine program (step S308).

  Now, returning to the main routine and continuing the description, in step S206 shown in FIG. 2, the ECU 15 checks the set value of the n-th learning travel end flag to obtain “n (in this case, n = 2) -th learning. It is determined whether or not “travel” has ended (step S305).

  As a result of the determination in step S305, when it is determined that “n (in this case, n = 2) th learning run” has not yet ended, the ECU 15 returns the processing flow to the subroutine program SUB, The following processing is executed.

  On the other hand, as a result of the determination in step S305, when it is determined that “n (in this case, n = 2) th learning travel” is completed, the ECU 15 sets the value of “n” related to the nth learning travel. Increment (in this case, “n = 2 + 1 = 3”).

  Next, the ECU 15 checks whether or not the value of “n” related to the n-th learning travel exceeds a preset number of times of learning travel, thereby determining whether or not all the learning travels have ended. This is performed (step S208). In this example, the preset number of times of learning travel is “2”, the value of “n” related to the n-th learning travel is “3”, and the value “3” of “n” is preset. Therefore, it is determined that all the learning runs have been completed (“Yes” in step S208).

  As a result of the determination in step S208, when it is determined that all the learning runs have been completed, the air pressure drop monitoring unit 35 included in the ECU 15 is a normal state learning unit during each of the first and second learning runs. The evaluation index data derived for each of the recommended air pressure and the excess air pressure (recommended air pressure + 30 kPa) and for each of the plurality of vehicle speed ranges, which are respectively learned by the 32 and the excess state learning unit 33, are read from the data storage unit 41. In addition, the read evaluation index data and a predetermined air pressure decrease determination threshold value (boundary value for determining that the air pressure decrease has occurred by how much (30 kPa in the present embodiment 1) based on the recommended air pressure). Based on the above, an estimation index corresponding to the determination threshold value is estimated and calculated for each of a plurality of vehicle speed ranges. The air pressure decrease monitoring unit 35 sets / registers the air pressure decrease determination threshold value of the evaluation index corresponding to each of the plurality of vehicle speed ranges, which is calculated as described above, in the data storage unit 41 (step S209). As a result, during normal driving, the determination threshold value for decreasing air pressure of the evaluation index corresponding to each of a plurality of vehicle speed ranges registered in the data storage unit 41 is used as reference data when performing the determination of decreasing air pressure.

  In step S210, the operator adjusts the air pressure of all the tires T to the original recommended air pressure, and ends the series of processes upon completion of the adjustment work.

  Here, the estimation calculation of the evaluation index related to the determination threshold for air pressure decrease, which is executed by the air pressure decrease monitoring unit 35 according to the first embodiment, will be specifically described with reference to FIG. That is, for example, in the first learning run (vehicle speed: 60 km / h), 250 mm (see point A in FIG. 5) is derived as an evaluation index (dynamic load radius) at 200 kPa (recommended air pressure). When 251 mm (see point B in FIG. 5) is derived as an evaluation index (dynamic load radius) at 230 kPa (recommended air pressure + 30 kPa) at (vehicle speed: 60 km / h), the determination threshold value for determining a decrease in air pressure is 30 kPa. Then, the evaluation index (dynamic load radius) related to the determination threshold value for air pressure decrease at 170 kPa (recommended air pressure-30 kPa) represented by the point C in FIG. 5 is the slope of the line segment connecting the points A and B, By considering the air pressure difference between the A point and the B point and the air pressure difference between the A point and the C point, it can be obtained in a proportional distribution. Specifically, the evaluation index (dynamic load radius) may decrease by 1 mm when the air pressure decreases by 30 kPa due to the slope of the line connecting point A and point B and the air pressure difference between points A and B. Recognize. This relationship is applied to the relationship between the known A point and the C point to be estimated. Note that the slope of the line connecting point A and point B, that is, the evaluation index (dynamic load radius) characteristic according to the change in air pressure, is the same vehicle speed (the example in FIG. 5 is the vehicle speed: 60 km / h, It shows an evaluation index (dynamic load radius) characteristic according to the change in air pressure.) Under conditions, it is known that it changes almost linearly (it can be expressed by a linear function). Therefore, since the air pressure difference between the known A point and the C point to be estimated is 30 kPa, 249 mm obtained by subtracting 1 mm from 250 mm, which is the evaluation index (dynamic load radius) at the A point, is used as the air pressure lowering determination threshold value. It can be estimated and calculated as an evaluation index (dynamic load radius).

  In Example 1 described above, in the first learning run, the air pressure of all tires T is adjusted to 200 kPa, which is the recommended air pressure (recommended value of the automobile manufacturer) of the tire, while in the second learning run, all Although the example of adjusting the air pressure of the tire T to 230 kPa (excess air pressure) obtained by adding 30 kPa to the recommended air pressure of the tire has been described, the present invention is not limited to this example.

  That is, in the learning run according to the present invention, the tire T air pressure is adjusted to a plurality of predetermined different values that are equal to or higher than the recommended pressure of the automobile manufacturer, and As long as the air pressure satisfies the condition that the air pressure is sequentially executed in at least two stages including the first learning run adjusted to the first value and the second learning run adjusted to the second value. Any modification is included in the scope of the technical scope of the present invention.

  Specifically, as a modification of the first embodiment, as shown in FIGS. 6 (1) to 6 (2), in contrast to the first embodiment, in the first learning run, the air pressure of all tires T Is adjusted to 230 kPa (excess air pressure) obtained by adding 30 kPa to the recommended air pressure of the tire, while in the second learning run, the air pressure of all tires T is adjusted to 200 kPa which is the recommended air pressure of the tire. The present invention may be configured. In this way, in the first embodiment, after completion of the series of learning runs, the work of adjusting the air pressure of all the tires T to the original recommended air pressure is necessary, whereas the above-described operation according to the first embodiment is performed. In the modified example, since the air pressure of all the tires T is adjusted to the original recommended air pressure at the end of a series of learning runs, the final air pressure adjustment work can be omitted. It can be said that this is advantageous compared to Example 1.

  Further, as the learning travel according to the first embodiment, the first learning travel in which the air pressure of the tire T is adjusted to the first value (recommended air pressure) and the second that is adjusted to the second value (excess air pressure). However, the present invention is not limited to this example. For example, in addition to the above-described two stages, the air pressure of the tire T is The third learning run adjusted to the third value, the fourth learning run adjusted to the fourth value, the fifth learning run adjusted to the fifth value, etc., by an appropriate number of steps Additional modes are also included in the scope of the technical scope of the present invention.

  Further, in the learning travel according to the first embodiment, the recommended air pressure is set as the first air pressure value adjusted during the first learning travel, and the recommended air pressure is set as the second air pressure value adjusted during the second learning travel. Although the example which employ | adopts what added 30 kPa (determination threshold value for air pressure reduction) was mentioned and demonstrated, this invention is not limited to this example, The air pressure of the tire T is predetermined or more than a recommended air pressure. Any air pressure may be adopted as long as it is adjusted to a plurality of values different from each other without any particular limitation.

[Operation of Tire Pressure Monitoring Device During Learning Travel According to Example 2]
Next, the operation of the tire air pressure monitoring device during learning travel according to the second embodiment will be described with reference to FIGS.

  FIG. 7 is an operation flowchart showing the flow of processing during learning driving according to the second embodiment, FIG. 8 is an explanatory diagram showing the adjusted air pressure of each tire T during learning driving according to the second embodiment, and FIG. FIG. 10 is an explanatory diagram showing the adjusted air pressure of each tire T during learning travel according to a modification of Example 2.

  For example, when the vehicle tire is replaced with a winter tire (studless tire) having a characteristic different from that of a genuine product prior to the arrival of the full-fledged snowfall season, the worker must confirm that the tire T is in a normal temperature state. After confirmation, the air pressures of all the tires T are respectively adjusted to designated pressures predetermined in this system (step S701). Specifically, as shown in FIG. 8, the operator sets the air pressure in all tires T, the right front tire T-FR to the recommended air pressure, the left front tire T-FL to the recommended air pressure +10 kPa (excess air pressure), The right rear tire T-RR is adjusted to a recommended air pressure +20 kPa (excess air pressure), and the left rear tire T-RL is adjusted to a recommended air pressure +30 kPa (excess air pressure). When the air pressure adjustment work for all the tires T in step S701 is completed, preparation for learning travel is completed.

  The ECU 15 constantly monitors the on / off state of the IG switch 17 and the on / off state of the RST switch 19 (steps S702 to S703). During the monitoring, when both the IG switch 17 is turned on ("Yes" in step S702) and the RST switch 19 is turned on ("Yes" in step S703), the ECU 15 starts learning travel. The fact is displayed on the display screen of the display 23 (step S704), so that the passenger is informed. In response to this, the occupant starts learning travel.

  The ECU 15 constantly monitors the on / off state of the IG switch 17 and the vehicle speed pulse of the vehicle speed sensor 21 (step S705). When both the ON state of the IG switch 17 and the output of the vehicle speed pulse are detected during the monitoring, the ECU 15 determines that the learning travel is started by the occupant (“Yes” in step S705).

  Next, the evaluation index deriving unit 31 included in the ECU 15 is based on a wheel speed signal (wheel speed pulse) output from each wheel speed sensor S, and a plurality of predetermined vehicle speed ranges (for example, 30 km / h, 60 km / h, 90 km / h, etc.) are used for evaluation indices (specifically, dynamic load radius data and resonance frequency data) for evaluating the air pressure of the tire T mounted on each wheel W. The evaluation index data derived for each of the plurality of vehicle speed ranges is stored in a predetermined storage area (evaluation index data storage area during learning travel) in the data storage unit 41 built in the ECU 15 (step S706). ~ S707). At this time, the normal state learning unit 32 detects the vehicle speed detected by the vehicle speed sensor 21 and the evaluation index derived by the evaluation index deriving unit 31 in a state where the air pressure of the tire T (right front tire T-FR) is adjusted to the recommended air pressure. Learning by associating. The excessive state learning unit 33 is detected by the vehicle speed sensor 21 in a state where the air pressure of the tire T (left front tire T-FL, right rear tire T-RR, and left rear tire T-RL) is adjusted to the excessive air pressure. The vehicle speed and the evaluation index derived by the evaluation index deriving unit 31 are learned in association with each other.

  Next, the ECU 15 checks the acquisition status of the evaluation index data based on the stored contents of the memory area (step S708).

  As a result of the data acquisition status check in step S708, when it is determined that the data acquisition is not yet completed, the ECU 15 is determined in advance by referring to the elapsed time from the start of the learning travel to the current time. It is checked whether or not a learning travel time (for example, a time that can be appropriately changed, such as 30 minutes) has elapsed (step S709).

  When it is determined that the learning travel time has not yet elapsed (time-up) as a result of the check of the learning travel time in step S709, the ECU 15 returns the process flow to step S706 and performs the following processing. Is executed.

  On the other hand, as a result of the data acquisition status check in step S708, it is determined that the data acquisition has been completed, or as a result of the learning travel time elapse check in step S709, the learning travel time has elapsed (time up). When the determination is made, the ECU 15 displays on the display screen of the display 23 that the learning travel has ended (step S710), thereby notifying the passenger of that fact. In response to this, the occupant knows that the learning travel has ended.

  Next, the air pressure drop monitoring unit 35 included in the ECU 15 has a first air pressure value (right front tire T-FR: recommended air pressure) learned by the normal state learning unit 32 and the excess state learning unit 33 during the learning travel. The second air pressure value (left front tire T-FL: recommended air pressure +10 kPa), the third air pressure value (right rear tire T-RR: recommended air pressure +20 kPa), and the fourth air pressure value (left rear tire T-RL: (Recommended air pressure +30 kPa) and the evaluation index data acquired for each of a plurality of vehicle speed ranges are read from the data storage unit 41, the read evaluation index data, and a predetermined air pressure decrease determination threshold value Based on the above, the evaluation index corresponding to the determination threshold is estimated and calculated in the same procedure as in the first embodiment. The air pressure decrease monitoring unit 35 sets / registers the air pressure decrease determination threshold value of the evaluation index corresponding to each of the plurality of vehicle speed ranges in the data storage unit 41 (step S711). As a result, during normal driving, the determination threshold value for decreasing air pressure of the evaluation index corresponding to each of a plurality of vehicle speed ranges registered in the data storage unit 41 is used as reference data when performing the determination of decreasing air pressure.

  In step S712, the operator adjusts the air pressures of all the tires T to the original recommended air pressures, and ends the series of processing steps when the adjustment work is completed.

  In the second embodiment of the present invention, the air pressure of the tire T is adjusted to a plurality of predetermined different values that are equal to or higher than the recommended value related to the vehicle 11, and As long as the learning traveling is performed, the condition that the air pressure of each tire mounted on the plurality of wheels is adjusted to a plurality of values including the first value and the second value is satisfied. Any modification is included in the scope of the technical scope of the present invention.

  Specifically, as a modified example according to the first embodiment, as shown in FIG. 9, each air pressure in all the tires T is changed to a recommended air pressure for the front tires (the right front tire T-FR and the left front tire T-FL). The present invention may be configured such that the rear wheel tires (the right rear tire T-RR and the left rear tire T-RL) are adjusted to the recommended air pressure +30 kPa (excess air pressure), respectively. In this way, since the learning travel can be performed in a state where the front tires closely related to the steering feeling and the braking feeling are adjusted to the recommended air pressure, the driver does not feel uncomfortable during the learning travel.

[Operation of tire pressure monitoring device during normal driving]
Next, the operation of the tire pressure monitoring device during normal travel will be described with reference to FIGS.

  FIG. 10 is an operation flowchart showing the flow of processing during normal running, and FIG. 11 is an explanatory diagram showing evaluation index (dynamic load radius) characteristics according to changes in vehicle speed under a constant air pressure condition.

  The ECU 15 constantly monitors the on / off state of the IG switch 17 (step S1001). If the IG switch 17 is turned on ("Yes" in step S1001) during this monitoring, the ECU 15 advances the process flow to the next step S1002.

  The ECU 15 constantly monitors the on / off state of the IG switch 17 and the vehicle speed pulse of the vehicle speed sensor 21 (step S1002). If both the ON state of the IG switch 17 and the output of the vehicle speed pulse are detected during this monitoring, the ECU 15 determines that normal traveling has been started by the occupant ("Yes" in step S1002).

  Next, the evaluation index deriving unit 31 included in the ECU 15 is based on the wheel speed signal (wheel speed pulse) output from each wheel speed sensor S, and the evaluation index (for each tire W mounted on each wheel W) ( Specifically, dynamic load radius data and resonance frequency data) are derived, respectively, and current evaluation index data derived for each of a plurality of vehicle speed ranges is stored in a predetermined storage area (in a data storage unit 41 built in the ECU 15). It is stored in the evaluation index data storage area during normal driving (steps S1003 to S1004).

  Next, the warning necessity determination unit 43 included in the ECU 15 reads out the evaluation index data derived in steps S1003 to S1004 from the data storage unit 41, and estimates and calculates the read current evaluation index data as described above. 11 for each of the dynamic load radius or the resonance frequency based on the determination threshold value for lowering the air pressure of the evaluation index corresponding to each of a plurality of vehicle speed ranges set and registered in the data storage unit 41. As shown in the example of the radius, it is determined whether or not the current evaluation index has reached the evaluation index related to the air pressure decrease determination threshold (step S1005). The warning necessity determination unit 43 determines whether or not a warning is required for a decrease in the air pressure of the tire T based on the current evaluation index data and the evaluation index related to the determination threshold value for reducing the air pressure registered in the data storage unit 41. In this case, the evaluation index data relating to the determination threshold for air pressure drop corresponding to the current vehicle speed region (in the example of FIG. 11, if the current vehicle speed is 60 km / h, for example, the vehicle speed is 60 km / h) The evaluation index data relating to the determination threshold value for lowering air pressure) is read from the data storage unit 41, and the warning determination is executed.

  As a result of the determination in step S1005, when it is determined that the current evaluation index has not reached the evaluation index related to the determination threshold for lowering air pressure (air pressure has not decreased) ("No" in step S1005) The ECU 15 returns the process flow to step S1002 and sequentially executes the following processes.

  On the other hand, as a result of the determination in step S1005, when it is determined that the current evaluation index has reached the evaluation index related to the air pressure decrease determination threshold (air pressure has decreased) ("Yes" in step S1005), The notification control unit 45 included in the ECU 15 performs notification control for notifying an occupant of a warning message related to a decrease in the air pressure of the tire T via the display 23 and the speaker 25 (step S1006). Thereby, since the passenger | crew can know in real time that the air pressure of the tire T fell, it can take appropriate measures, such as deceleration rapidly. After the end of the warning operation in step S1006, the ECU 15 returns the process flow to step S1001, and repeatedly executes the following process from the beginning.

[Effect of Example]
In the tire pressure monitoring apparatus according to Examples 1 and 2 of the present invention, the evaluation index deriving unit 31 determines the air pressure of the tire T attached to the wheel W based on the rotation state of the wheel detected by the wheel speed sensor S. An evaluation index for evaluation is derived. The evaluation index derived in this way is referred to when estimating and calculating the evaluation index related to the determination threshold for decreasing air pressure through learning traveling, or when actually monitoring the decrease in air pressure of the tire T during normal traveling.

  That is, the normal state learning unit 32 learns by associating the vehicle speed detected by the vehicle speed sensor 21 with the evaluation index derived by the evaluation index deriving unit 31 in a state where the air pressure of the tire T is adjusted to a predetermined recommended air pressure. On the other hand, the excess state learning unit 33 calculates the vehicle speed detected by the vehicle speed sensor 21 and the evaluation index derived by the evaluation index deriving unit 31 in a state where the air pressure of the tire T is adjusted to a predetermined excess air pressure higher than the recommended air pressure. Learn by associating.

  The air pressure drop monitoring unit 35 refers to the learning result from the normal state learning unit 32 and the learning result from the excess state learning unit 33, and the vehicle speed and evaluation index deriving unit detected by the vehicle speed sensor 21 when the vehicle 11 is traveling normally. Based on the evaluation index derived at 31, the decrease in the air pressure of the tire T is monitored.

  Here, in the related arts according to Patent Documents 1 and 2, a set value by an automobile manufacturer is used as it is as a determination threshold value for tire air pressure reduction, whereas in the present invention, actual tire characteristics are obtained through the learning. The evaluation index that is faithfully reflected is adopted.

  For this reason, for example, when the rigidity of the tire T after replacement is higher than that of the genuine product, the change width of the evaluation index when the air pressure drop occurs in the tire T after replacement is smaller than that of the genuine product, An evaluation index in which actual tire characteristics are faithfully reflected through the learning travel is estimated and calculated, and the relationship between the determination threshold for reducing air pressure and the evaluation index can be matched. On the contrary, when the tire T after replacement has a lower rigidity than that of the genuine product, the change width of the evaluation index when the air pressure drops in the tire T after replacement becomes larger than that of the genuine product. Similarly, an evaluation index in which actual tire characteristics are faithfully reflected through the learning travel is estimated and calculated, and the relationship between the determination threshold for lowering air pressure and the evaluation index can be matched.

  Therefore, for example, even when the tire T of the vehicle is replaced with one having a characteristic different from that of the genuine product, the determination accuracy related to the decrease in the air pressure of the tire T can be maintained at a high level.

  Further, according to the tire pressure monitoring apparatus according to the first and second embodiments of the present invention, for example, even when the dynamic load radius is changed due to wear of the tire T, the actual tire characteristics are faithfully reflected through the learning travel. As a result of estimating the calculated evaluation index and matching the relationship between the determination threshold for reducing air pressure and the evaluation index, the determination accuracy relating to the decrease in air pressure of the tire T can be maintained at a high level.

  Further, in the tire pressure monitoring apparatus according to the first and second embodiments of the present invention, the first value is a value obtained by adding a predetermined value to the recommended air pressure (excess air pressure), the second value is the recommended air pressure, When the determination threshold value for decreasing the air pressure is adopted as the predetermined value, the calculation procedure for estimating the evaluation index related to the determination threshold value for decreasing the air pressure can be simplified. The accuracy can be further increased.

  Then, according to the tire pressure monitoring device according to the second embodiment, compared with the first embodiment, the evaluation index related to the determination threshold for lowering the air pressure in which the actual tire characteristics are faithfully reflected through the single-stage learning traveling is estimated. As a result, it is possible to reduce the annoyance associated with learning travel.

[Others]
The present invention is not limited to the above-described embodiments, and can be appropriately changed within the scope of the invention or the technical idea that can be read from the entire claims and the specification, and the tire pressure accompanying such changes can be changed. Monitoring devices are also encompassed within the scope of the present invention.

  That is, for example, in the description of the embodiment of the present invention, the embodiment in which the embodiment 1 and the embodiment 2 are separately adopted is illustrated and described. However, the present invention is not limited to this embodiment, and the embodiment 1 Needless to say, even the embodiment according to the combination with Example 2 is included in the range of the technical scope of the present invention.

FIG. 1 is an overall configuration diagram of a vehicle equipped with a tire pressure monitoring device according to an embodiment of the present invention. FIG. 2 is an operation flowchart illustrating the flow of the main routine program during learning travel according to the first embodiment. FIG. 3 is an operation flowchart illustrating the flow of a subroutine program during learning travel according to the first embodiment. FIG. 4A is an explanatory diagram illustrating the adjusted air pressure of each tire T during the first learning travel according to the first embodiment, and FIG. 4B is a diagram illustrating each adjustment air during the second learning travel according to the first embodiment. FIG. 5 is an explanatory diagram illustrating an adjusted air pressure of a tire T. FIG. 5 is an explanatory diagram showing an evaluation index (dynamic load radius) characteristic according to a change in air pressure at a vehicle speed of 60 km / h. FIG. 6A is an explanatory diagram illustrating the adjusted air pressure of each tire T during the first learning travel according to the modification of the first embodiment, and FIG. 6B is a second diagram according to the modification of the first embodiment. It is explanatory drawing showing the adjustment air pressure of each tire T at the time of learning driving | running | working. FIG. 7 is an operation flowchart illustrating the flow of processing during learning travel according to the second embodiment. FIG. 8 is an explanatory diagram illustrating the adjusted air pressure of each tire T during the learning travel according to the second embodiment. FIG. 9 is an explanatory diagram illustrating the adjusted air pressure of each tire T during learning travel according to a modification of the second embodiment. FIG. 10 is an operation flowchart showing the flow of processing during normal travel. FIG. 11 is an explanatory diagram showing an evaluation index (dynamic load radius) characteristic according to a change in vehicle speed under a constant air pressure condition.

Explanation of symbols

11 Vehicle 13 Communication Line 15 ECU
17 Ignition switch (IG switch)
19 Reset switch (RST switch)
21 Vehicle speed sensor (vehicle speed detection means)
23 Display 25 Speaker 31 Evaluation Index Deriving Unit (Evaluation Index Deriving Unit)
32 Normal state learning unit (normal state learning means)
33 Excess state learning unit (excess state learning means)
35 Air pressure drop monitoring unit (air pressure drop monitoring means)
41 Data storage unit 43 Warning necessity determination unit 45 Notification control unit S Wheel speed sensor (wheel speed detection means)
T tire W wheel

Claims (5)

Vehicle speed detecting means for detecting the vehicle speed of the vehicle;
Wheel speed detecting means for detecting wheel speeds of wheels provided in the vehicle;
Evaluation index deriving means for deriving an evaluation index for evaluating the air pressure of the tire mounted on the wheel based on the detection output of the wheel speed detection means;
Normal state learning means for learning by associating the vehicle speed detected from the vehicle speed detection means with the evaluation index derived from the evaluation index deriving means in a state where the air pressure is adjusted to a predetermined recommended air pressure;
Excess state learning means for learning by associating a vehicle speed detected from the vehicle speed detection means with an evaluation index derived from the evaluation index deriving means in a state where the air pressure is adjusted to a predetermined excess air pressure higher than the recommended air pressure. ,
A vehicle speed detected from the vehicle speed detecting means during normal driving of the vehicle with reference to a learning result by the normal state learning means and a learning result by the excess state learning means, and an evaluation index derived from the evaluation index deriving means; Air pressure drop monitoring means for monitoring the air pressure drop based on
The vehicle has a plurality of wheels;
The normal state learning means and the excess state learning means simultaneously perform learning for different wheels,
The air pressure drop monitoring means is configured to monitor a drop in air pressure of a tire mounted on each of the plurality of wheels.
Tire pressure monitoring device characterized by that. The tire pressure monitoring device according to claim 1,
The air pressure drop monitoring means sets an air pressure drop determination threshold value of an evaluation index corresponding to a vehicle speed with reference to a learning result by the normal state learning means and a learning result by the excess state learning means;
Tire pressure monitoring device characterized by that. The tire pressure monitoring device according to claim 1 or 2,
The evaluation index is at least one of a dynamic load radius or a resonance frequency of the tire,
Tire pressure monitoring device characterized by that. The tire pressure monitoring device according to any one of claims 1 to 3,
A switch operated at the start of the learning,
Tire pressure monitoring device characterized by that. The tire pressure monitoring device according to any one of claims 1 to 4,
The first learning run for learning by the normal state learning means and the second learning run for learning by the excess state learning means are executed in two stages, and each learning is executed sequentially.
Tire pressure monitoring device characterized by that.