Method for controlling slip of at least one wheel of a vehicle, controller, program for executing said method, and storage medium on which said program is stored

Abstract

The present invention relates to a method for controlling slip of at least one wheel (104) of a vehicle (100). [Solution] When the slip state (110) of the wheel (104) is outside a target slip range (118) of a matrix (112), the slip state (110) is used to read at least one parameter (114) of an action (116) to be performed from the matrix (112), a data field (120) of the matrix (112) assigned to the slip state (110) is determined to read the at least one parameter (114) from the data field (120), and the parameter (114) is used to activate at least one actuator (106, 108) of the vehicle (100) to perform the action (116).

Description

[Technical field]

[0001] The present invention relates to a method and a corresponding controller for controlling the slip of at least one wheel of a vehicle. [Background technology]

[0002] When the wheels of a vehicle roll on the roadbed, slippage occurs between the wheels and the roadbed if forces in the direction of rolling or in the direction opposite to the direction of rolling and / or transverse to the direction of rolling are transmitted to the roadbed. Slippage can be expressed as the ratio between the rotational speed of the wheel and the actual speed of movement of the wheel in the direction of rolling or in the direction opposite to the direction of rolling. Up to a certain slip value, the transmittable force increases. Beyond this value, the transmittable force decreases and the wheel starts to slip. In the direction of rolling, slippage can be called slippage. In the direction opposite to the direction of rolling, slippage can be called locking.

[0003] To prevent wheel spin, vehicles may have a traction control system that models the physics involved in the vehicle and limits the drive torque to the wheels before the wheels begin to slip. The traction control system may then activate the vehicle's braking system and / or the vehicle's drive system to limit the drive torque.

[0004] In order for a traction control system to be used in a vehicle, the parameters of the traction control system are adjusted by calibration engineers in a laborious optimization process. Summary of the Invention

[0005] Against this background, the approach presented here provides a method for controlling the slip of at least one wheel of a vehicle according to the independent claims, as well as a corresponding controller and finally a corresponding computer program product and a machine-readable storage medium. Advantageous further configurations and improvements of the approach presented here are evident from the description and are set forth in the dependent claims.

[0006] Embodiments of the present invention may advantageously enable a reduction in computational costs during interventions of a vehicle's traction control system, such that the traction control system can respond with short reaction times.

[0007] (Claim 1) A method is proposed for controlling slip of at least one wheel of a vehicle, where if the slip state of the wheel is outside a target slip range of a matrix, the slip state is used to read at least one parameter of an action to be performed from the matrix, whereby a data field of the matrix assigned to the slip state is determined for reading, and the at least one parameter is read from the data field, whereby the parameter is used to activate at least one actuator of the vehicle for performing the action.

[0008] The ideas for the embodiments of the present invention can be considered to be based, inter alia, on the ideas and realizations described below.

[0009] The slip condition may describe the instantaneous state of slip at one wheel of a vehicle. The slip condition may be detected using at least one sensor at the wheel. The slip condition may be determined for an axle of the vehicle. The slip condition may then be sensed for each wheel of the axle by at least one sensor. Multiple sensor signals of multiple sensors may be combined to determine the slip condition.

[0010] The matrix may be a table. The matrix may have multiple data fields. A data field may contain one parameter or multiple parameters. The coordinate axes of the data fields of the matrix may be assigned to the numerical values ​​of the slip state. The parameters may be scaling values ​​or scaling factors. In the data fields, the actions to be performed may be filed. The actuator may be the brake system of the vehicle. The actuator may be the drive system of the vehicle. The brake system may then be activated wheel by wheel. The drive system may be activated axle by axle in the usual case, but also wheel by wheel if appropriate. To activate the actuator, the parameters may be converted into a control signal or may be modulated into the control signal. The target slip range may be a subrange of the matrix. The target slip range may contain multiple data fields of the matrix. In the target slip range, the data fields may be empty.

[0011] For the slip condition, a value pair may be formed consisting of a wheel relative speed value and a wheel relative acceleration value. The numerical values ​​of the value pair may correspond to the coordinate axes of the data field to be selected. The relative speed value may represent the wheel slip speed. The slip speed may be the speed difference between the wheel and the roadbed. The relative acceleration value may represent the wheel slip acceleration. The slip acceleration may be the change in the slip speed. The slip speed and the slip acceleration may be determined by sensors and a reference speed of the vehicle. The reference speed may be available as a value in the vehicle.

[0012] The relative acceleration value can be determined using the course of the relative speed values ​​of the wheels. The slip acceleration can be the gradient of this course. The slip acceleration can be derived from the slip speed. Due to this derivation, only one sensor is required at the wheel.

[0013] The relative speed value may be determined using the wheel speed value of the wheel and other wheel speed values ​​of other wheels on the wheel's axle. The wheel speed value may represent the wheel speed of the wheel. The wheel speed may be detected by a simple and reliable sensor on the wheel. For example, a wheel speed sensor on the wheel may be used to detect the wheel speed. The slip speed may be the speed difference between the wheel speed and the wheel speed of other wheels on the axle.

[0014] The slip state may be used to select the action to be initiated. In particular, the action to be initiated may depend on the instantaneous change in the slip state. Different actions may be required to bring the slip state into the target slip range. For example, the wheel may be accelerated in the event of locking. This may be done, for example, by increasing the drive torque or reducing the brake torque. Conversely, in the event of spinning, the drive torque may be decreased or the brake torque increased. If the instantaneous slip state is static, different actions may be required than if the instantaneous slip state changes dynamically.

[0015] Different actions may be filed in the data fields of the matrix. The action to be activated can be read from the data field assigned to the slip state. For the transition from one slip state to another, adjacent data fields may be assigned to different actions.

[0016] A row range for the slip condition in the matrix may be determined by comparing a first value of a value pair characterizing the slip condition to a row value range of the target slip range, where an upper row range may be determined if the first value is greater than the row value range, a middle row range may be determined if the first value is within the row value range, and a lower row range may be determined if the first value is less than the row value range.

[0017] A column range for the slip condition in the matrix may be determined by comparing the second value of the value pair to the column value range of the target slip range, where a right column range may be determined if the second value is greater than the column value range, a middle column range may be determined if the second value is within the column value range, and a left column range may be determined if the second value is less than the column value range.

[0018] The determined row range and the determined column range may characterize one of eight possible matrix subranges of the matrix around the target range. An action to be activated may be selected using the characterized matrix subrange. Different matrix subranges may be assigned to different slip state ranges. Transitions between different actions filed may be located at the transitions between the matrix subranges.

[0019] A deviation of the next slip condition detected in time after the action has been performed from the target slip range may be detected. This deviation may be used to determine a correction factor for the parameter. The correction factor may be filed in a data field. If an action is performed with at least one parameter filed in the data field, the next slip condition detected in time should have reached the target slip range or should have changed in the right direction. If the slip condition has not reached the target slip range or has changed in the wrong direction, the parameter may not be suitable for the vehicle. The correction factor may change the parameter in such a way that at least one improvement is achieved in the next cycle. If it is worse in the next cycle, the sign of the correction factor may be changed. The correction factor allows a fully automatic optimization of the traction control system.

[0020] The method may be implemented, for example, in software or hardware, or in a mixed form of software and hardware, for example in a controller.

[0021] The approaches presented herein further provide a controller configured to perform, activate or cause to be performed the steps of the method variations presented herein in a corresponding device.

[0022] The controller may be an electrical device with at least one computing unit for processing signals or data, at least one memory unit for storing signals or data, and at least one interface and / or communication interface for reading or outputting data embedded in a communication protocol. The computing unit may be, for example, a signal processor, a so-called system ASIC or a microcontroller for processing sensor signals and outputting data signals depending on the sensor signals. The memory unit may be, for example, a flash memory, an EPROM or a magnetic memory unit. The interface may be formed as a sensor interface for reading sensor signals from the sensor and / or as an actuator interface for outputting data and / or control signals to the actuator. The communication interface may be formed for reading or outputting data wirelessly and / or wired. The interface may be, for example, a software module next to other software modules on a microcontroller.

[0023] Also advantageous is a computer program product or computer program with a program code, which may be stored on a machine-readable carrier or a storage medium such as a semiconductor memory, a hard disk memory or an optical memory, in particular when the program product or program is executed on a computer or device, and which is used to perform, to bring into execution and / or to initiate the steps of the method according to one of the above-described embodiments.

[0024] It should be noted that some of the possible features and advantages of the present invention are described herein with respect to different embodiments, and those skilled in the art will recognize that the features of the controller and method can be appropriately combined, adapted, or exchanged to obtain other embodiments of the present invention. Several embodiments of the present invention will now be described with reference to the accompanying drawings, but neither the drawings nor the description should be construed as limiting the present invention. [Brief description of the drawings]

[0025] [Figure 1] 1 is a diagram of a vehicle with a controller according to one embodiment. [Diagram 2] FIG. 11 is a diagram showing the progression of a slip state. [Diagram 3] 1 is a diagram illustrating the principle of a traction control system according to an embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0026] The figures are only schematic and not to scale. Identical references represent elements of the same or identical function.

[0027] 1 illustrates a vehicle 100 with a controller 102 according to one embodiment. The controller 102 is configured to control slip at the wheels 104 of the vehicle 100. In particular, the controller 102 is configured to control drive slip at the driven wheels 104 of the vehicle 100. The controller 102 can also be used to control braking slip at the driven wheels 104 and non-driven wheels of the vehicle 100. The controller 102 is coupled to a braking system 106 of the vehicle 100 acting on the wheels 104. Similarly, the controller 102 is coupled to a drive system 108 of the vehicle 100 acting on the driven wheels 104.

[0028] The controller 102 reads the slip condition 110 for each wheel 104 or for each axle. The slip condition 110 is used in the controller to read from a matrix 112 at least one parameter 114 for an action 116 to be taken if the slip condition 110 is outside a target slip range 118 of the matrix 112. To determine if the slip condition 110 is outside the target slip range 118, the data field 120 of the matrix 112 assigned to the slip condition 110 is determined, and if the data field 120 is outside the target slip range 118, the parameter 114 is read from the data field 120. If the data field 120 assigned to the slip condition 110 is within the target slip range 118, then the data field 120 is not read since the slip condition 110 should not have changed.

[0029] To implement the action 116, the parameters 114 are used to generate control signals 122 for the braking system 106 and / or the drive system 108. If the wheel 104 for which the slip condition 110 is observed currently has excessive slip, the action 116 reduces the torque acting on that wheel 104, with the parameters 114 setting how much the torque is reduced.

[0030] If the braking torque is excessive, the action 116 can be to reduce the braking pressure supplied by the brake system 106 to the wheels 104, the parameters 114 then indicating by how much the braking pressure should be reduced. Alternatively or complementary, the action 116 by the drive system 108 can be to generate or increase a drive torque at the wheels 104 or axles which counteracts the braking torque, the parameters 114 then indicating by how much the drive torque should be increased.

[0031] If the braking torque is too low, then action 116 may be to increase the braking pressure supplied to the wheels 104 from the braking system 106, with parameter 114 indicating how much the braking pressure should be increased.

[0032] If the drive torque is excessive, the action 116 can be to reduce the power output from the drive system 108 to the wheels 104 or axles, with the parameters 114 then indicating how much the drive torque should be reduced. Alternatively or complementary, the action 116 can be to generate a braking torque at the wheels 104 that counteracts the drive torque, with the parameters 114 then indicating how much the braking torque should be increased.

[0033] If the drive torque is too low, then action 116 can be to increase the power output from drive system 108 to the wheels 104 or axles, with parameter 114 representing how much the drive torque should be increased.

[0034] Following the action 116, the slip condition 110 of the wheels 104 is read anew and, if the slip condition 110 is still outside the target slip range 118, the corresponding parameters 114 for the next action 116 are retrieved from the matrix 112. The next action 116 is initiated by new control signals 122 for the braking system 106 and / or the drive system 108.

[0035] In one embodiment, when subsequently reading the slip state 110, the success of the previously implemented actions 116 is checked, in particular whether the parameters 114 have led to the desired improvement of the slip state 110. If the improvement is too small, the previously used parameters 114 and / or actions 116 are modified, whereby the modification of the parameters 114 can be made depending on the difference of the slip state 110 from the desired slip state in the target slip range 118.

[0036] In one embodiment, the slip state 110 is two-dimensional and is composed of a relative wheel 104 velocity value 124 and a relative wheel 104 acceleration value 126 .

[0037] In one embodiment, the relative speed value 124 represents the difference between a wheel speed value 128 of the wheel 104 and a reference speed value 130 of the vehicle 100. The wheel speed value 128 is sensed by a wheel speed sensor 132 of the vehicle 100 at the wheel 104. The reference speed value 130 is continually updated by a state evaluator 134 of the vehicle 100.

[0038] In one embodiment, the relative speed value 124 represents the difference between a left wheel speed value 128a of the left wheel 104a of the axle and a right wheel speed value 128b of the right wheel 104b of the axle.

[0039] In one embodiment, different data fields 120 are assigned different actions 116. The action 116 to be performed and the associated parameters 114 are then read from the matrix 112 depending on the slip state 110 read.

[0040] FIG. 2 shows the time course of a slip state 110. The slip state 110 is two-dimensional and is shown in two time-correlated graphs, one above the other. Both graphs plot time t in seconds on the horizontal axis. The upper graph plots velocity in m / s on the vertical axis. The lower graph plots acceleration in m / s on the vertical axis. 2 In the upper graph, the course of the wheel speed values ​​128a, 128b is shown. In the lower graph, the course of the relative acceleration value 126 is shown.

[0041] At the beginning of the curve, the vehicle is traveling at a constant speed. Then the vehicle accelerates and the right wheel speed 128b increases with a constant gradient. The left wheel loses road grip and starts to spin. The left wheel speed value 128a increases with a much greater gradient than the right wheel speed value 128b. The difference between the left wheel speed value 128a and the right wheel speed value 128b is the relative speed value 124. The relative speed value 124 increases sharply after the left wheel loses road grip. This sharp increase is also shown in the curve of the relative acceleration value 126, since the relative acceleration value 126 is the derivative of the relative speed value 124 with respect to time t. With the loss of road grip, the relative acceleration value 126 also increases sharply from zero. At the first turning point of the curve of the relative speed value 124, the curve of the relative acceleration value 126 has a maximum value. The maximum value of the curve of the relative speed value 124 is reached when the left wheel speed value 128a also reaches a maximum value. At this maximum value, the curve of the relative acceleration value 126 has a zero crossing. After the zero crossing, the curve of the relative acceleration value 126 has a minimum value at a second turning point of the curve of the relative velocity value 124.

[0042] The instant t1 is entered before the curve of the relative velocity value 124 reaches the first turning point, so that the curve of the relative acceleration value 126 has not yet reached its maximum value at the instant t1.

[0043] Fig. 3 shows a principle diagram of a traction control system according to an embodiment. The traction control system can be implemented, for example, in a controller as shown in Fig. 1. The two-dimensional slip states 110 at time t1 in Fig. 2 are highlighted in a matrix 112. Data fields 120 of the matrix 112 are assigned to all the different slip states 110. From left to right, the data fields 120 are assigned to increasing relative velocity values ​​124. From bottom to top, the data fields 120 are assigned to increasing relative acceleration values ​​126. A target slip range 118 is likewise shown in the matrix 112. The target slip range 118 here comprises three data fields 120 of the matrix.

[0044] Eight matrix subranges 300, 302, 304, 306, 308, 310, 312, 314 are illustrated within matrix 112 in addition to the target slip range 118. In the first matrix subrange 300, data field 120 is assigned a greater relative velocity value 124 than data field 120 of target slip range 118 and a greater relative acceleration value 126 than data field 120 of target slip range 118. In the second matrix subrange 302, data field 120 is assigned a greater relative velocity value 124 than data field 120 of target slip range 118 and the same relative acceleration value 126 as data field 120 of target slip range 118. In the third matrix subrange 304, the data field 120 is assigned a relative velocity value 124 greater than the data field 120 in the target slip range 118 and a relative acceleration value 126 less than the data field 120 in the target slip range 118. In the fourth matrix subrange 306, the data field 120 is assigned a relative velocity value 124 equal to the data field 120 in the target slip range 118 and a relative acceleration value 126 less than the data field 120 in the target slip range 118. In the fifth matrix subrange 308, the data field 120 is assigned a relative velocity value 124 less than the data field 120 in the target slip range 118 and a relative acceleration value 126 less than the data field 120 in the target slip range 118. In the sixth matrix subrange 310 In the seventh matrix subrange, the data field 120 is assigned a relative velocity value 124 that is less than the data field 120 of the target slip range 118, and a relative acceleration value 126 that is the same as the data field 120 of the target slip range 118. 312 8, data field 120 is assigned to relative velocity values ​​124 less than data field 120 of target slip range 118 and relative acceleration values ​​126 greater than data field 120 of target slip range 118. 314, data field 120 is assigned the same relative velocity value 124 as data field 120 of target slip range 118 and a greater relative acceleration value 126 than data field 120 of target slip range 118 .

[0045] The data field 120 assigned to the slip condition 110 at time t1 is within the first matrix subrange 300. The desired slip condition is within the target slip range 118. The eight matrix subranges 300, 302, 304, 306, 308, 310, 312, 314 represent the static portion 316 of the traction control system presented herein.

[0046] The changes in slip conditions 110 from maneuver to maneuver can be described by logic and represent the dynamic portion 318 of the traction control system presented herein.

[0047] The static portion 316 and the dynamic portion 318 are used to determine a basic action type 320. The basic action type 320 and other influence quantities 322 are used to determine a functional action type or action 116. The action 116 may have three states 324, 326, 328. The first state 324 is to accelerate. The second state 326 is to decelerate. The third state 328 is to stop.

[0048] The action 116 and the static part 316 are used to read one parameter 114 from the matrix 112 which belongs to the respective state 324, 326, 328 of the action 116. The action 116 and the parameter 114 are used in an actuator controller 330 to generate a control signal 122 for the braking system and / or the drive system.

[0049] In one embodiment, the results of the activation are evaluated by a learning algorithm 332 and correction coefficients 334 are generated for the parameters 114 filed in the data field 120, thereby optimizing the traction control system fully automatically.

[0050] The possible embodiments and configurations of the contact points presented herein will now be restated.

[0051] We present a traction control system based on state actions.

[0052] The Traction Control System (TCS) is a functional block of the ESP system. The main function of the Traction Control System is to ensure that the wheels do not spin when the vehicle is launched longitudinally, thus meeting the vehicle requirements regarding stability, steerability and traction.

[0053] Conventional traction control systems have a powertrain physics modeling size dependency and a speed reference dependency, where the speed reference is an estimate from an external function. The controller of a conventional traction control system provides a target value setting that is converted into an actuator adjustment.

[0054] Conventional traction control systems are complex systems that require nearly two years of effort to fully understand the system. Conventional traction control systems are rich in variants (>50 variants in one project) and therefore have high application costs with project times of one to two years. Conventional traction control systems require evaluation of the drive torque acting on the wheels and a speed reference as accurate as possible.

[0055] Conventional systems essentially consider the drive torque acting on the axles and wheels in the physical unit Newton-meter (Nm). This torque is modeled on the basis of a powertrain model using quantities such as prime mover speed and wheel speed. In the case of tuning a conventional traction control system, an optimal drive slip is calculated, which provides an ideal torque target setting for the prime mover or an ideal brake torque setting for the brake system. The brake torque setting is then converted back into brake pressure. If the drive torque estimation does not work correctly, for example in a suboptimal application for the respective vehicle model, or if the speed-based external function is not precise, performance or accuracy will be reduced as soon as possible.

[0056] When applying the conventional system, there are nearly 500 adjustment parameters that directly or indirectly affect the system. In order to apply the function properly, it is necessary to deepen the cooperation between the parameters and the system, which requires a large time cost.

[0057] In conventional systems, all the know-how built into the system is almost entirely specific to the traction control system. It is not easy for a function developer, software developer or calibration engineer trained for conventional traction control systems to help with other functions (e.g. ABS or VDC).

[0058] In the presented approach, the description of the system using physical and quantitative model size is no longer so important. In the presented approach, precise activation actions are sufficient. The presented approach describes an intuitive system with low application cost and a small number of variants.

[0059] As long as the traction control system's activation actions function correctly, there is no performance loss. Based on the state-action principle, the "state" is purely measurement-technically based on the sensors, and the "action" acts directly on the respective actuator, prime mover or brake system.

[0060] The controller parameters of the traction control system presented here are scaling values ​​that affect the actuators, the prime mover and the brake system explicitly with respect to absolute values ​​and / or implicitly with respect to delta values. These parameter values ​​are learned fully automatically by means of a learning algorithm, by starting a very general operation of the traction control system according to a predefined operation catalogue. This allows a direct relationship of the parameter values ​​to the "state", i.e. to the wheel and axle behavior of the vehicle, to remain. This allows the calibration engineer to additionally make individual additional adaptations in a relatively clear or intuitive manner.

[0061] The approach presented here describes an intuitive system. The controller is "thought" anew. It does not attempt to describe the highly complex reality of vehicle, tire and environment modeling and manage it with control technology. Rather, it assumes from the outset that one cannot and does not wish to describe highly complex systems. The approach is limited to sensor measurements and control elements or actuators. Everything in between is a general intellectual approach.

[0062] In the presented approach, knowledge of the definition of "state" and of the basic control objectives of the traction control system are sufficient for understanding the system. No special know-how is needed to apply the traction control function, since the software structure embodies this know-how in a general way in the main functions and does not require further modifications or adaptations. This also means that the understanding of the software and functions of the traction control system can be easily transferred to other functions, such as ABS or VDC.

[0063] In the state-action principle presented here, a "state" describes a state where an action is performed based on a change in state of that state, and an "action" describes the direct influence on actuators, i.e. on the prime mover and / or braking system.

[0064] The possible "states" and target ranges are filed in a table. On the X-axis of the table, the speed slip of one wheel or one axle is plotted. On the Y-axis of the table, the acceleration of this wheel or this axle is plotted.

[0065] The signal flow of the presented approach is now explained. Information about speed and acceleration is read by the wheel speed sensors and processed in the signal processor. The processed signals are used to determine the "state", which involves detecting the statics and dynamics of the "state". The action type is determined via the internal logic, e.g. to boost or reduce torque. The actuator size is set based on the action type. The resulting actuator setting progression is characteristic of the state-action principle.

[0066] In the approach presented here, the learning algorithm runs during the application, updating the parameter table: if the action was good, no changes are made; if the action was bad, parameter changes are made.

[0067] The learning algorithm is continuously disabled, reading parameters from a table and setting the actuators. Alternatively, continuous learning is also possible.

[0068] The wheels or axles are adjusted so that the system keeps the state within the control objectives, in the so-called target zone, which allows the desired slip and the desired acceleration to be adjusted, thus achieving optimal traction independent of the speed criteria.

[0069] The speed slip represents the difference between the speed of the wheel (or axle) containing the crack and a reference speed.

[0070] As a reference speed, the same reference speed as in conventional systems can be used. The reference speed is an external function of the Vehicle State Estimation (VSE). Alternatively, however, an inherent (simple) reference logic may be implemented, since a quantitative description is no longer important for the state-action principle. In the case of the presented approach, the reference speed is important especially for the correct start-up action of the traction control case. The presented approach can be called “slip-free”, since a very precise speed reference is not needed as in the case of the prior art.

[0071] Finally, it is to be pointed out that words such as "comprise" and "include" do not exclude other elements or steps, and words such as "a" do not exclude a plurality. Reference signs in the claims are not to be regarded as limitations. [Explanation of symbols]

[0072] 100 vehicles 102 Controller 104 Wheels 104a left wheel 104b Right wheel 106 Brake system (actuator) 108 Drive system (actuator) 110 Slip condition 112 Matrix 114 Parameters 116 Action 118 Target slip range 120 Data Fields 124 Relative Velocity Value 126 Relative Acceleration Value 128a Wheel speed value of the left wheel 128b Wheel speed value of the right wheel 300,302,304,306,308,310,312,314 Matrix Subranges 334 Correction factor

Claims

1. A method for controlling slip of at least one wheel (104) of a vehicle (100), comprising, when a slip state (110) of said wheel (104) is outside a target slip range (118) of a matrix (112), using said slip state (110) to read from said matrix (112) at least one parameter (114) of an action (116) to be performed, determining a data field (120) of said matrix (112) assigned to said slip state (110) for reading said at least one parameter (114) from said data field (120) and activating at least one actuator (106, 108) of said vehicle (100) using said parameter (114) to perform said action (116); further selecting the action to be initiated (116) using the slip state (110); Different actions (116) are filed in the data field (120) of the matrix (112), and the action (116) to be activated is read from the data field (120) assigned to the slip state (110), determining a row range for the slip condition (110) in the matrix (112) by comparing a first value of a value pair characterizing the slip condition (110) with a row value range of the target slip range (118), determining an upper row range if the first value is greater than the row value range, determining a middle row range if the first value is within the row value range, and determining a lower row range if the first value is less than the row value range; determining a column range for the slip condition (110) in the matrix (112) by comparing a second value of the value pair with a column value range of the target slip range (118), and determining a second value determining a right column range if the second value is greater than the column value range, determining a middle column range if the second value is within the column value range, and determining a left column range if the second value is less than the column value range, the determined row range and the determined column range characterizing one of eight possible matrix subranges (300, 302, 304, 306, 308, 310, 312, 314) of the matrix (118) around the target slip range (118), and selecting the action (116) to be initiated using the characterized matrix subrange (300, 302, 304, 306, 308, 310, 312, 314). method.

2. 2. The method of claim 1, further comprising forming a value pair for said slip condition (110) consisting of a relative velocity value (124) of said wheels (104) and a relative acceleration value (126) of said wheels (104).

3. 3. The method of claim 2, wherein the relative acceleration value (126) is determined using a progression of the relative velocity value (124).

4. 4. The method according to claim 2 or 3, wherein the relative velocity value (124) is determined using a wheel speed value (128a) of the wheel (104a) and another wheel speed value (128b) of another wheel (104b) provided on the axle of the wheel (104a).

5. 5. The method according to claim 1, further comprising detecting a deviation of a next slip condition (110) sensed in time after performing the action (116) from the target slip range (118) and using this deviation to determine a correction factor (334) for the parameter (114) and filing it in the data field (120).

6. A controller (102) configured to implement, execute and / or activate the method according to any one of claims 1 to 5 in a corresponding device.

7. A program for executing the method according to any one of claims 1 to 5.

8. A computer-readable storage medium storing the program according to claim 7.

Images