WO2003008211A1

WO2003008211A1 - Method and device for reducing tyre pressure loss recognition times by forming an average value and by means of combined evaluation of the front axle signals and rear axle signals

Info

Publication number: WO2003008211A1
Application number: PCT/DE2002/002484
Authority: WO
Inventors: Norbert Polzin
Original assignee: Robert Bosch Gmbh
Priority date: 2001-07-18
Filing date: 2002-07-06
Publication date: 2003-01-30
Also published as: DE10135022A1

Abstract

The invention relates to a device for monitoring the state of the tyres on the wheels of a motor vehicle. To this end, means are provided for detecting the rotational movements of the wheels and for producing first variables representing the detected rotational movements. Evaluation means are also provided, in which second variables are determined from the first variables by forming a difference, and in which a signal representing the tyre condition is emitted, according to at least one monitoring inquiry. The state of the tyres is indicated by display means, according to the signal of the evaluation means. The essence of the invention lies in the fact that the evaluation means are embodied in such a way that at least one third variable is determined from the second variables by forming an average value, and that in at least one of the third variables enters into at least one of the monitoring inquiries.

Description

_VERFA H _REN U _{ND VOR} R _{ICHTUNG Z} U _R VE _RK ÜRZUNG TIRE PRESSURE DROP DETECTION TIME _DURC HM _I T _T E _L W _G _ERT B _ILD UN UN _D combined evaluation of the ^front-AXIS AND BACKGROUND SIGNALS

State of the art

The invention is based on a system for monitoring the tire condition. Such devices and methods are known from the prior art.

From DE 196 19 393 AI a system for monitoring the tire condition on the wheels of a motor vehicle with means for detecting the rotational movements of the wheels is known. These means are generally sensors which detect quantities which represent the rotational speeds of the wheels. Evaluation means are also provided, by means of which the wheel speeds are compared with one another and by means of which, depending on the comparison result, a signal which represents the tire condition is emitted. Display means then show the tire condition in response to the signal. The essence of DE 196 19 393 AI is that the evaluation means are designed in such a way that quotients are formed from the quantities generated and these quotients are compared with one another. Depending on the comparison result, the signal representing the tire condition is then generated.

In DE 196 19 393 AI it is proposed that the signal, which represents the tire condition, only in certain Driving conditions, especially when driving straight ahead, is determined. This means that no signal representing the tire condition is also determined in certain driving conditions.

For example, when cornering, the inside wheels of the vehicle have higher wheel speeds than the outside wheels. When evaluating the wheel speeds, this could lead to the incorrect recognition of pressure loss in a tire. Driving on a lane where there are other adhesion factors on the left and right wheel tracks (μ-split lane) could also erroneously lead to pressure loss detection. The times in which, as a result of the present driving condition, the signal representing the tire condition is not determined and thus updated, are referred to as blind times in the following.

From DE 197 12 097 Cl a system for detecting a condition of the wheels of a motor vehicle is known. For this purpose, means are provided for generating speed signals, which represent the rotary movements of the wheels, and evaluation means, by means of which, depending on the signals generated, a signal is output that represents a display-relevant state. The essence of DE 197 12 097 C1 is that the evaluation means are designed in such a way that first, depending on the speed signals generated, first difference values for the speed differences of at least two vehicle wheels are formed on the two vehicle sides. Depending on a first comparison of the difference values formed with one another and / or with predeterminable first threshold values, the signal which represents a display-relevant state is then output. The features of the preamble emerge from DE 197 12 097. Cl.

Advantages of the invention

The invention relates to a device for monitoring the tire condition on the wheels of a motor vehicle. Means are provided for detecting the rotary movements of the wheels and generating first variables which represent the detected rotary movements. Evaluation means are also provided, in which further second variables are determined from the first variables by forming a difference and in which, depending on at least one monitoring query, a signal which represents the tire condition is emitted. The tire condition is indicated by the signal of the evaluation means in display means. The essence of the invention is that the evaluation means are designed in such a way that at least one further third variable is determined from the second variables by averaging and that at least one of the at least one monitoring query includes at least one of the third variables.

The averaging contained in the third quantities according to the invention has the advantage that short-term fluctuations of the second quantities can be compensated for. This shortens the detection intervals, i.e. a loss of tire pressure can be detected earlier.

It is advantageous to record the speeds of the wheels as the first variables that are dependent on the detected rotary movements. Since wheel speed sensors are available with every wheel slip control system, this does not require any additional sensor effort. Furthermore, it is advantageous if at least one of the at least one monitoring request is linked to at least two third sizes. In the case of a two-axle vehicle, for example, this enables the signals assigned to the wheels of the front axle and the signals assigned to the wheels of the rear axle to be linked.

The linking of at least two third sizes is advantageously an addition.

It is also advantageous if further monitoring queries are carried out. Advantageously, only a third variable is included in at least one further monitoring query.

Further advantageous embodiments of the invention can be found in the subclaims.

drawing

An embodiment of the invention is shown and explained in the following drawing. The drawing consists of Figures 1 to 4.

Fig. 1 shows schematically the structure of the device according to the invention

FIG. 2 shows in the form of a flow diagram the process sequence in the detection of tire pressure losses.

FIG. 3 shows block 24 of FIG. 2 in detail. 4 shows, using a specific example, the determination of a tire pressure loss using the device according to the invention or the method according to the invention.

embodiments

The present invention is a method and a device for shortening the tire pressure loss detection times by averaging and combined evaluation of the front and rear axle signals. The faster a tire pressure loss is displayed, the less likely critical driving conditions or thermal overload or damage to the tire are.

In order to get a rough overview, the very general Fig. 1 will be discussed first. 1 relates to a vehicle with two wheel axles and four wheels, but of course an application of the invention to vehicles with more than four wheels or more than two wheel axles is also conceivable.

Blocks 10 to 13 represent sensors. In the specific exemplary embodiment, these are supposed to be wheel speed sensors. For a two-axle vehicle, these deliver the output signals Nvl, Nvr, Nhl and Nhr. Are there

Nvl = wheel speed front left,

Nvr = wheel speed front right,

Nhl = rear left wheel speed,

Nhr = right rear wheel speed.

These wheel speed signals are input to the evaluation means 14. The evaluation means 14 deliver the output signal S, which activates a display device 15 in the event of a detected tire defect. This approach In the simplest case, the pointing device 15 can be a warning lamp which indicates whether a tire defect has been detected or not. However, a display device is also conceivable, for example, which emits acoustic signals.

The mode of operation of the evaluation means 14 is explained in more detail with reference to FIG. 2. After the start block 21, differences of the quantities corresponding to the sensor signals are formed in step 22. In the specific exemplary embodiment, the differences in the wheel speeds | Nvl - Nvr | = ΔNv and | Nhl - Nhr | = ΔNh formed. Thereby || an amount, ΔNv is the amount of the wheel speed difference on the front axle, ΔNh is the amount of the wheel speed difference on the rear axle. Instead of the wheel speed differences, it is also conceivable to use wheel speeds which are assigned to the wheel speeds and which can be denoted, for example, by Vvl, Vvr, Vhl and Vhr. The differences | Vvl - Vvr | = ΔVv and | Vhl - Vhr | = ΔVh.

In the following, for the sake of clarity, all versions refer to the wheel speeds, identified by the symbols Nvl, Nvr, Nhl and Nhr. However, all upcoming versions can also be effortlessly implemented and conceived with the wheel speeds Vvl, Vvr, Vhl and Vhr assigned to the wheel speeds.

In block 23 it is checked whether there is a valid driving state. If there are “extreme”, ie invalid, driving states, no further evaluation of the differences formed in block 22 takes place; instead, at a later time by the time increment Δt, differences are again generated with the current values that correspond to the sensor signals. chen, formed. The time increment by Δt takes place in block 26.

Invalid driving conditions and thus idle times can be characterized, for example, by the following features: high longitudinal acceleration or longitudinal deceleration values, large lateral acceleration, one-sided different adhesion factors (μ-split

Lane) large yaw rate tight cornering

The variables of lateral acceleration, yaw rate and the wheel speeds are available as measurement signals from sensors in a vehicle equipped with a vehicle dynamics control system (ESP). However, these and the other variables can also be calculated or estimated from the sensor signals using mathematical models. The longitudinal acceleration and the longitudinal deceleration can be calculated, for example, by differentiation from the longitudinal vehicle speed, which in turn is calculated from the wheel speeds.

If, on the other hand, there is a valid driving state, the mean values of all the differences since then in a given time window are calculated in block 24: M _ = 1 / n * Σ (ΔNv) and

M2 = 1 / n * Σ (ΔNh). n is the number of differences in the averaging. The differences ΔNv and ΔNh are stored in a ring buffer. That with each new determination of a difference in a valid driving state, the most recent difference in the ring memory is deleted.

The mean values 1 / n * Σ (ΔNv) and 1 / n * Σ (ΔNh) are explained below: If the vehicle is started, all memory locations in the ring buffer are assigned the entry zero, ie both variables 1 / n * Σ (ΔNv) and 1 / n * Σ (ΔNh) are each set to zero. The mean values that are determined or updated regularly or irregularly during the journey are now updated, provided a valid driving state was identified in block 23: the most recent time is deleted and the most recent difference is added to the ring memory.

In the following, 1 / n * Σ (ΔNv) and 1 / n * Σ (ΔNh) always mean the latest mean values.

In block 25, the two available mean values M ^ _ = 1 / n * Σ (ΔNv) and M ₂ = 1 / n * Σ (ΔNh) are used to carry out three independent monitoring queries using the mean values M _] _ and M2:

1. _] _ = 1 / n * Σ (ΔNv)> thresholdv

2. M ₂ = 1 / n * Σ (ΔNh)> thresholdh

3. M _x + M ₂ = 1 / n * (Σ (ΔNv) + Σ (ΔNh))> thresholdvh

N denotes the number of summands contained in the sums. This number is closely linked to the number of storage locations in the ring buffer.

The threshold values tresholdv, tresholdh and tresholdvh can be fixed or can be determined depending on the situation.

If at least one of the three monitoring queries is fulfilled, then a tire defect is recognized and a warning signal S is activated in block 28. However, if all three monitoring queries are not fulfilled at the same time, block 27 becomes the time Incremented by Δt and calculated a new difference in block 22.

Now it is also clearly understandable that long blind times should be avoided, because during the blind times - an invalid driving state is always recognized in block 23 and the mean values are no longer updated.

Block 24 of FIG. 2 is shown in detail in FIG. 3. The mean value is determined in steps 24a, 24b and 24c.

Step 24a: The most recent difference in the ring buffer is deleted.

Step 24b: The difference that has just been formed in block 22 (see FIG. 2) can be stored in the memory space that has become free as a result.

Step 24c: The mean value is formed from the differences contained in the ring buffer.

The process sequence shown in FIG. 2 can be repeated at regular or irregular time intervals.

The mode of operation of the present invention is clearly illustrated in FIG. 4 for a special case. It is a very simplified representation, which should nevertheless convey a qualitative understanding.

The left-hand column shows a roadway, which is composed of the sections 31, 32 and 33, and a vehicle 34 traveling thereon with the speed v at different times. The roadway consists of the following 3 sections:

1. Straight section 31 (drawn vertically)

2. Slight left turn 32

3. Straight section 33 (shown horizontally) The 3 sections are separated by dashed lines. The right column shows the mean values M ₁ , M ₂ and M _] _ + M ₂ as functions of time. The discrete times t _] _, t2 and t3 are along the x-axis. drawn. These points in time have the following descriptive meanings: t _] _: The vehicle is still in the straight section

31. -2 ■ at this point the vehicle changes from straight

Section 31 into the slight left curve 32 t: at this point the vehicle changes from the slight left curve 32 into the straight section 33.

In the left column, the vehicle is shown at an additional point in the middle of the left curve.

By the time t _] _ the vehicle had traveled a sufficiently long, straight section without air pressure differences in the tires, ie Mi- = M ₂ = M _! + M ₂ = 0.

First, the wheel speeds and their differences in the different sections of the route are shown. At time t _] _, a sudden loss of tire pressure in the left rear wheel caused a wheel speed difference (ΔNh) in the rear wheels. Result: The left rear wheel suddenly rotates at a higher wheel speed due to the smaller wheel circumference. This is in the straight section 31, ie for the times t_ <t <t2

(ΔNv) = 0 as well

(ΔNh)> 0.

The growth of M ₂ or M + M ₃ for t> t _] _ can be seen on the right in the middle and lower diagram. It is essential that the mean values increase, but not an abrupt change in the value (ΔNh). This is due to the fact that M ₂ = 1 / n * Σ (ΔNh). In the ring buffer there are still many zeros from the straight line in section 31, which of course also go into the averaging and are only now being successively deleted.

This is followed by a slight left turn 32, in which the left wheels are inside and have to travel a shorter geometric distance.

The front inner wheel rotates slower than the front outer wheel because of the shorter distance to be covered. The rear inner wheel would quickly ^'rotate (larger wheel speed) than the rear outer wheel for the smaller wheel diameter and it would also slow rotating (small wheel) as it leaves the shorter indoor track. For the sake of simplicity, these effects can be thought of as just compensating each other.

The consequences of these two effects:

(ΔNh) = 0 and

(ΔNv)> 0 are recognized. With the front wheel, the wheel speed of the inner wheel is lower because of the left turn.

Then straight ahead on the straight path

33:

Now is back

(ΔNv) = 0 as well

(ΔNh)> 0.

The following shows how the journey outlined above affects the three mean values M ^, M2 and M ^ + M ₂ and the three associated monitoring queries: 1. M = 1 / n * Σ (ΔNv)> thresholdv

2. M ₂ = 1 / n * Σ (ΔNh)> thresholdh

3. M ₁ + M ₂ = 1 / n * (Σ (ΔNv) + Σ (ΔNh))> thresholdvh

For the sake of clarity, let us assume tresholdv = - tresholdh = tresholdvh.

First, the first monitoring query regarding the front wheels, ie M_> thresholdv, is considered. In the two straight line segments 31 and 33, ΔNv = 0. Only in the slight left curve 32 is ΔNv> 0. However, the dwell time t3 - t2 of the vehicle 34 in the left curve 32 is not so large that the threshold value tresholdv is reached and thus on Warning signal S indicates a loss of tire pressure to the driver via a display means. The mean value M] _ begins to increase for t> t2, remains constant for a certain time for t> t3 and then subsides again, since ΔNv = 0 for t> t3. That M _] _ does not fade away immediately for t> t3, but remains constant at first, depends on the one already described

Ring buffer together. For t> t3, because of ΔNv = 0

Zero entries are written to the ring buffer, but the most recent entries in it still come from times for which t <t2.

This means that zero entries are also removed from the memory.

Next, the second monitoring request regarding the rear wheels, ie M2> thresholdh, is considered. ΔNh> 0 applies to t_ <t <t2 in section 31. M2 therefore assumes ever larger values because of the pressure difference in the rear wheels. Before the threshold trh is reached, however, the vehicle is in the time range t2 <t <t ^ _f, ie already in the left curve 32. There is ΔNh = 0, so that remains M2 initially constant and then becomes smaller again. Only when driving straight ahead in section 33 is ΔNh positive again. The mean value M2 initially remains constant and then begins to rise again.

Due to the left curve and the associated drop in size M2, the limit value tresholdh is reached more slowly than would have been the case without an intermediate left curve 32.

Finally, the third monitoring query follows, which combines the wheel speed differences of the front and rear wheels:

M] _ + M2> thresholdvh.

For times t <t2, the same value results for M] _ + M2 as for M2. However, while in the second monitoring query the value of M2 decreases undesirably during the left curve for t2 <t <t3, in the third monitoring query there is a contribution from the positive summand (ΔNv) and thus a further increase in the value] _ + M2 , Thus M] _ + M2 has already reached the threshold value tresholdvh in the concrete example earlier than 2 the threshold value tresholdh. This informs the driver of a tire pressure loss earlier, which means a concrete increase in safety.

In other words, the temporary drop in M ₂ does not significantly slow down the detection of a loss of tire pressure.

In the exemplary embodiment, the M_ + M2 was considered for the third monitoring query. Of course, other links between the wheel speed differences are also conceivable. The Limit values tresholdv, tresholdh and tresholdvh can of course be chosen freely and in no way need to be the same.

The mean values M _] _, M ₂ and M _] _ + M2 can also be calculated by an integrator, for example. The monitoring queries can then be viewed in a continuous form and are, for example, for M ^:

M _] _ = 1 / T * int (ΔNv * dt)

"Int" means an integral sign and T is the duration of the integration time. Here, too, the direct reference to the mean can be seen.

Claims

Expectations

1. Device for monitoring the tire condition on the wheels of a motor vehicle, wherein

Means (10, 11, 12, 13) for detecting the rotary movements of the wheels and generating first variables (Nvl, Nvr, Nhl, Nhr) which represent the rotary movements are dependent, and

Evaluation means (14) in which further second variables (Nvl-Nvr, Nhl-Nhr) are determined from the first variables (Nvl, Nvr, Nhl, Nhr) by forming a difference and in which a signal (S) is dependent on at least one monitoring query. that represents the condition of the tire is delivered, and

Display means (15), which display the tire condition in response to the signal (S) from the evaluation means (14), are provided, characterized in that the evaluation means (14) are designed in such a way that the second variables (Nvl-Nvr, Nhl- Nhr) is determined by averaging at least one further third variable (M _] _ = 1 / n * Σ (ΔNv), M ₂ = 1 / n * Σ (ΔNh)) and that in at least one of the at least one monitoring values. at least one of the third variables.

2. Device according to claim 1, characterized in that the first speeds (Nvl, Nvr, Nhl, Nhr), which represent the detected rotary movements, are the speeds of the wheels.

3. Device according to claim 1, characterized in that in at least one of the at least one monitoring request, a linkage of at least two third sizes is received.

4. The device according to claim 3, characterized in that it is an addition in the linking of at least two third sizes.

5. The device according to claim 3, characterized in that ^' only at least one third variable is included in at least one further monitoring query.

6. Method for monitoring the tire condition on the wheels of a motor vehicle, in which the rotary movements of the wheels are recorded in means (10, 11, 12, 13) and from them first variables (Nvl, Nvr, Nhl, Nhr), which record the detected rotary movements represent, are generated and in which further second variables (Nvl-Nvr, Nhl-Nhr) are determined from the first variables (Nvl, Nvr, Nhl, Nhr) in evaluation means (14) by forming the difference and in which in the evaluation means (14) depending on at least one monitoring query, a signal (S) representing the tire condition is emitted, and in which the tire condition is indicated in display means (15) in response to the signal (S) of the evaluation means (15), characterized in that in the Evaluation means (14) from the second quantities (Nvl-Nvr, Nhl-Nhr) determined by averaging at least one further third quantity (M} = 1 / n * Σ (ΔNv), M ₂ = 1 / n * Σ (ΔNh)) and that in at least one of the at least one Monitoring query receives at least one of the third variables.

7. The method according to claim 6, characterized in that the rotational speeds of the wheels are detected as first variables (Nvl, Nvr, Nhl, Nhr), which represent the detected rotary movements.

8. The method according to claim 6, characterized in that in at least one of the at least one monitoring request, a linkage of at least two third sizes is received.

9. The method according to claim 8, characterized in that it is an addition in the linkage of at least two third sizes.

10. The method according to claim 8, characterized in that only a third variable is included in at least one further monitoring query.