Method for determining the initial vehicle speed of a vehicle

Abstract

A procedure for determining the initial vehicle speed of a vehicle is described, comprising the following steps: - Determining a second vehicle speed based on wheel speed sensor readings of the vehicle; - Determining vehicle acceleration as a function of the determined second vehicle speed; - If the measured vehicle acceleration exceeds and / or falls below a predefined acceleration limit, limit the measured vehicle acceleration to the predefined acceleration limit; and - Determining the initial vehicle speed as a function of the vehicle acceleration.

Description

[0001] The present invention relates to a method for determining a first vehicle speed of a vehicle according to the independent claim. State of the art

[0002] The wheel slip is adjusted to a specific percentage (wheel speed relative to vehicle speed) to achieve maximum braking force. This percentage is highly dependent on the tire and can be in the low double-digit percentage range for winter and standard summer tires, e.g., 20%.

[0003] In order to calculate the slippage, the vehicle speed is calculated using a mathematical model, and this model is corrected with a vehicle speed calculated using wheel speed sensors.

[0004] When braking very hard or when the wheels slip due to a slippery road surface, the speed measured by the wheel speed sensors is much lower than the actual vehicle speed. This significantly distorts the model value when correcting it using the vehicle speed value measured by the wheel speed sensors. As a result, the slip is calculated incorrectly, and the wheels are overbraked; that is, the slip is set too high, and the maximum possible deceleration, and therefore the shortest possible braking distance, cannot be achieved.

[0005] German patent application DE 195 27 531 A 1 describes a system for determining vehicle speed that can accurately determine a reference vehicle speed for an all-wheel-drive vehicle when all wheels are slipping or locked. An integration value of a longitudinal acceleration is used to determine the reference vehicle speed when the vehicle is accelerating and the change in a lowest wheel speed is negative, or when the vehicle is decelerating and the change in a highest wheel speed is positive.

[0006] The publication EP 3 409 512 A2 describes a method and device for tamper-proof speed determination, as well as a bicycle equipped with such a device. A dynamic pressure sensor signal, i.e., a time-dependent profile of pressure changes, is recorded in a vehicle tire. The evaluation of this dynamic pressure sensor signal allows the tire speed to be derived. Disclosure of the invention Advantages of the invention

[0007] A method for determining a first vehicle speed of a vehicle with the features of the independent patent claim is disclosed.

[0008] A second vehicle speed is determined based on wheel speed sensor readings. Subsequently, the vehicle acceleration is calculated based on this second vehicle speed.

[0009] If the measured vehicle acceleration exceeds and / or falls below a predefined acceleration limit, the measured vehicle acceleration is limited to the predefined acceleration limit.

[0010] The initial vehicle speed is then determined as a function of the vehicle acceleration. This method is advantageous because it leads to a more robust and accurate estimate of the initial vehicle speed.

[0011] Further advantageous embodiments of the present invention are the subject of the dependent claims.

[0012] It is expedient to continue determining the first vehicle speed as a function of the second vehicle speed. This is advantageous because it allows for a more precise determination of the first vehicle speed by taking into account both the measured data and the determined first vehicle speed.

[0013] It is advantageous to define a predefined acceleration value based on road conditions and / or vehicle characteristics. This allows for a more precise determination of the initial vehicle speed by considering both vehicle-inherent and external factors when setting the limit. The acceleration limit can, for example, be set at the acceleration due to gravity. This limit can also be increased if the vehicle is capable of generating particularly high acceleration due to special tires, strong downforce from spoilers or diffusers, or road conditions. Conversely, the acceleration limit can be reduced if, for example, weather conditions such as wet or snowy surfaces prevent the acceleration from exceeding a certain value.

[0014] It is advantageous to filter the measured vehicle acceleration before limiting it, particularly using a low-pass filter. This increases the accuracy of the speed measurement, as limiting the acceleration can lead to errors due to measurement noise, especially when the average acceleration is close to the limit, resulting in intermittently limited acceleration values.

[0015] Advantageously, the determined initial vehicle speed is used in an estimation algorithm to recalculate the initial vehicle speed, particularly in a Bayesian estimator. This improves the estimation accuracy of the initial vehicle speed calculation in the Bayesian estimator, and in particular increases its accuracy.

[0016] The estimation algorithm conveniently uses a measurement noise parameter, the value of which is determined as a function of the difference between the second and first vehicle speeds. This is advantageous because it increases the measurement noise in situations where the already determined first vehicle speed is inaccurate and does not provide reliable values. In such cases, the squared deviation between the first and second vehicle speeds, derived from the wheel speed sensor readings, can be used to calculate the measurement noise. With weighted mean filters, such as a Kalman filter, the influence or strength of the model correction due to the second vehicle speed decreases, and therefore the potentially erroneously determined second vehicle speed cannot distort the model value as significantly.

[0017] The measurement noise parameter is expediently determined as a function of the difference between the measured vehicle acceleration and the filtered vehicle acceleration. This is advantageous because driving situations in which the vehicle is braked hard and the wheel speeds change significantly result in a high measurement noise parameter value, thus reducing the influence of wheel speed sensor readings on the estimation algorithm. Situations such as the aforementioned braking situations, in which the vehicle's wheels become unstable, lead to large changes in wheel acceleration. Therefore, as mentioned, it is also beneficial to include the squared deviation between the unfiltered and filtered acceleration in the measurement noise calculation.The squared deviation between the unfiltered and filtered acceleration is scaled with the square of the integration time step, particularly in discrete-time integration, and is also low-pass filtered. This results in situations involving heavy braking and significant changes in wheel speeds leading to a high measurement noise parameter.

[0018] Advantageously, the second vehicle speed is calculated for a virtual wheel located at the vehicle's center of gravity or at the midpoint of the vehicle's axles, based on wheel speed sensor readings. This is beneficial because it reduces the influence of individual wheel variations, for example, due to slippage or uneven road surfaces.

[0019] Furthermore, the invention relates to a device for determining a first vehicle speed of a vehicle, comprising at least one means, in particular an electronic control unit, which is configured to carry out a method according to the invention. Thus, the aforementioned advantages can be achieved.

[0020] Furthermore, the invention relates to a computer program comprising instructions which, when executed by a computer, cause the computer to perform all steps of a method according to the invention. Thus, the aforementioned advantages can be achieved.

[0021] Furthermore, the invention relates to a machine-readable storage medium on which a computer program according to the invention is stored. Thus, the aforementioned advantages can be achieved. Brief description of the drawings

[0022] Advantageous embodiments of the invention are shown in the figures and explained in more detail in the following description. Fig. 1 a flowchart of a method according to the invention in a first embodiment; Fig. 2 a block diagram of the inventive method according to the first embodiment, illustrating individual steps by way of example; Fig. 3 a block diagram of a method according to the invention in a second embodiment; Fig. 4 a block diagram of a method according to the invention in a third embodiment; and Fig. 5 A schematic representation of a device for determining a first vehicle speed of a vehicle according to one embodiment. Embodiments of the invention

[0023] The same reference numerals denote the same device components or the same process steps in all figures.

[0024] Fig. 1 and Fig. 2 are described together for a better understanding of the invention.

[0025] Fig. Figure 1 shows a flowchart of a method according to the invention for determining a first vehicle speed of a vehicle according to a first embodiment.

[0026] In a first step (S11), a second vehicle speed is determined based on wheel speed sensor readings from the vehicle. This can be done, for example, as in Fig. 2. This process is carried out by a first block 11. The first block 11 receives wheel speed sensor readings and converts them into the second vehicle speed using the corresponding wheel circumference. This can be done individually for each wheel. Then, to combine the individual wheel speeds and determine the second vehicle speed, for example, an average can be calculated, a weighted average can be calculated (e.g., depending on the steering angle), or a calculation can be performed for a virtual wheel located at the vehicle's center of gravity or at the center of the vehicle's axles.

[0027] In a second step S12, the vehicle acceleration is determined as a function of the calculated second vehicle speed. This can be done, in particular, by differentiating, especially numerically differentiating, the second vehicle speed. This can be done, for example, as in Fig. 2 by a second block 12, which differentiates the vehicle speed determined in the first block 11.

[0028] In a third step, S13, if the measured vehicle acceleration exceeds or falls below a predefined acceleration value, the measured vehicle acceleration is limited to the predefined acceleration limit. This can be done as in Fig. 2. This is represented by a third block 13. Different limit values ​​16, 17 for positive and negative accelerations can be specified here, for example. The acceleration can be limited to the acceleration due to gravity, and this limit can be increased if the vehicle can generate a particularly high acceleration due to special tires, strong downforce from spoilers or diffusers, or road conditions. Likewise, the limit can be reduced if, for example, weather conditions such as wetness or snow prevent the acceleration from exceeding a certain value.

[0029] In a fourth step S14, the initial vehicle speed is determined as a function of the vehicle acceleration. This can be done, for example, by means of numerical integration, as shown in a fourth block 14, whereby appropriate initial conditions must be set.

[0030] Fig. Figure 2 shows a fifth block 15, by which the first vehicle speed determined in this way can be multiplied. This can also be done in a further block 18. In a summation block 19, both values ​​determined in this way can be added to obtain an improved first vehicle speed 20. Thus, the determination of the first vehicle speed can be improved if necessary.

[0031] Correcting a modeled speed using the improved first vehicle speed, for example in a Kalman filter, also requires the use of a measurement noise parameter. Ideally, the value of the measurement noise parameter is increased in situations where the first vehicle speed is inaccurate and does not provide reliable values. Therefore, as described, the squared deviation between the second and first vehicle speeds can be used to calculate the measurement noise. With weighted mean filters, such as a Kalman filter, the influence or strength of the model correction due to the wheel-based vehicle speed decreases, and therefore the potentially erroneously measured vehicle speed cannot distort the model value as much.

[0032] Fig. Figure 3 shows a block diagram of a method according to a second embodiment of the invention. The upper part corresponds to the first embodiment already described. In the added lower part, a measurement noise parameter is determined. For this purpose, a difference between the second vehicle speed and the first vehicle speed is determined in block 21 and the difference is squared. Subsequently, the result is filtered in block 22 using a filter, in particular a low-pass filter, and optionally provided with an offset value from block 24 in a summation block 23, from which a measurement noise parameter 25 is determined.

[0033] Fig. Figure 4 shows a block diagram of a method according to a third embodiment of the invention. The upper and middle sections correspond to the embodiments already described. In the further added lower section, a difference between the determined vehicle acceleration and the filtered vehicle acceleration is calculated and squared in block 26. Subsequently, the result is integrated twice over time in block 27 and filtered in block 28 using a filter, in particular a low-pass filter. The result is then added as a further summand to the aforementioned summation block 23, which determines the measurement noise parameter 25.

[0034] Situations where the wheels become unstable lead to significant changes in wheel acceleration. Therefore, it is particularly advantageous to also include the squared deviation between the unfiltered and filtered acceleration in the calculation of the measurement noise. Ideally, the squared deviation between the unfiltered and filtered acceleration is scaled quadratically with the duration of the time step dt and also low-pass filtered. This ensures that situations involving heavy braking, and consequently large changes in wheel speeds, result in a high measurement noise parameter value.

[0035] Fig.Figure 5 shows a schematic representation of a device 50 for determining a first vehicle speed of a vehicle according to one embodiment. The device 50 comprises at least means 51, in particular an electronic control unit, which is configured to perform all steps of a method according to the invention. QUOTES INCLUDED IN THE DESCRIPTION

[0000] This list of documents cited by the applicant was automatically generated and is included solely for the reader's convenience. The list is not part of the German patent or utility model application. The DPMA accepts no liability for any errors or omissions. Cited patent literature

[0000] DE 195 27 531 A

[0005] EP 3 409 512 A2

[0006]

Claims

[1] Method for determining a first vehicle speed of a vehicle, comprising the steps: - Determining a second vehicle speed based on wheel speed sensor readings of the vehicle; - Determining vehicle acceleration as a function of the determined second vehicle speed; - If the measured vehicle acceleration exceeds and / or falls below a predefined acceleration limit, limit the measured vehicle acceleration to the predefined acceleration limit; and - Determining the initial vehicle speed as a function of the vehicle acceleration. [2] Method according to the preceding claim, wherein the first vehicle speed is further determined as a function of the second vehicle speed. [3] Method according to one of the preceding claims, wherein the predefined acceleration limit is determined depending on a road condition and / or a vehicle characteristic. [4] Method according to one of the preceding claims, wherein the determined vehicle acceleration is filtered before limiting, in particular by means of a low-pass filter. [5] Method according to one of the preceding claims, wherein the determined first vehicle speed is used in an estimation algorithm to determine the first vehicle speed again, in particular in a Bayes estimator. [6] Method according to the preceding claim, wherein the estimation algorithm uses a measurement noise parameter and wherein the value of the measurement noise parameter is determined as a function of a difference between the second vehicle speed and the first vehicle speed. [7] Method according to the preceding claim, wherein the value of the measurement noise parameter is further determined as a function of a difference between the determined vehicle acceleration and the filtered vehicle acceleration. [8] Method according to one of the preceding claims, wherein the second vehicle speed for a virtual wheel located at the center of gravity of the vehicle or at the center of the vehicle axles is determined as a function of wheel speed sensor measurements of the vehicle. [9] Device (50) for determining a first vehicle speed of a vehicle, comprising at least means (51), in particular an electronic control unit, which is configured to perform all steps of the method according to any one of claims 1 to 8. [10] Computer program comprising instructions which, when executed by a computer, cause the computer to perform all steps of the method according to any one of claims 1 to 8. [11] Machine-readable storage medium on which the computer program according to claim 10 is stored.

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