METHOD AND CONTROL DEVICE FOR CONTROLLING THE SLIP OF AT LEAST ONE WHEEL OF A VEHICLE

Description

Field of the invention

[0001] The invention relates to a method for controlling a slip of at least one wheel of a vehicle and a corresponding control unit. State of the art

[0002] When a vehicle wheel rolls on a surface, slippage occurs between the wheel and the surface when a force is transmitted to the surface in one direction of rolling, against the direction of rolling and / or perpendicular to the direction of rolling. Slip can be expressed in the direction of rolling or against the direction of rolling as the ratio of the wheel's rotational speed to the wheel's actual speed of movement. Up to a certain slip value, the transferable force increases. If this value is exceeded, the transferable force decreases and the wheel begins to slip. In the direction of rolling, slipping can be described as spinning. In the opposite direction of rolling, slipping can be described as locking.

[0003] To prevent wheel spin, the vehicle may be equipped with a traction control system. Traction control models physical relationships within the vehicle and limits the drive torque at the wheel before the wheel begins to slip. Traction control can control a vehicle braking system and / or a vehicle drive system to limit the drive torque.

[0004] In order to apply the traction control system to the vehicle, the traction control parameters are set by an application engineer in a complex optimization process.

[0005] US 6,542,806 B1 describes a method for controlling the traction of a ground vehicle.

[0006] DE 10 2013 205 320 A1 describes a traction control device for a motorcycle. Disclosure of the invention

[0007] Against this background, the approach presented here provides a method for controlling the slip of at least one wheel of a vehicle and a corresponding control unit, as well as a corresponding computer program product and a machine-readable storage medium according to the independent claims. Advantageous further developments and improvements of the approach presented here emerge from the description and are described in the dependent claims. Advantages of the invention

[0008] Embodiments of the present invention can advantageously enable the reduction of computational effort during an intervention of a vehicle's traction control system. Thus, the traction control system can respond with a short reaction time.

[0009] A method for controlling the slip of at least one wheel of a vehicle is proposed, wherein at least one parameter of an action to be carried out is read out from a matrix using a slip state (state) of the wheel if the slip state lies outside a target slip range of the matrix, wherein a data field of the matrix assigned to the slip state is determined for reading and the at least one parameter is read out from the data field, wherein at least one actuator of the vehicle is controlled using the parameter to carry out the action, wherein a value pair is formed for the slip state from a relative speed value of the wheel and a relative acceleration value of the wheel, wherein the relative speed value represents a difference in speed between the wheel and a surface.

[0010] Ideas for embodiments of the present invention may be considered, among other things, to be based on the thoughts and findings described below.

[0011] A slip condition can describe a current state of slip at a wheel of a vehicle. The slip condition can be detected at the wheel using at least one sensor. The slip condition can also be determined for an axle of the vehicle. The slip condition can then be detected by at least one sensor per wheel of the axle. Sensor signals from the sensors can be combined to determine the slip condition.

[0012] A matrix can be a table. The matrix can have a plurality of data fields. A data field can contain one or more parameters. A coordinate of a data field in the matrix can be assigned to a numerical value of the slip state. A parameter can be a scaling value or a scaling factor. An action to be performed can be stored in the data field. An actuator can be a vehicle's braking system. The actuator can also be a vehicle's drive system. The braking system can be controlled for each individual wheel. The drive system can usually be controlled for each individual axle or, if possible, for each individual wheel. To control the actuator, the parameter can be converted into a control signal or modulated onto the control signal. A target slip range can be a sub-range of the matrix. The target slip range can comprise multiple data fields in the matrix.In the target slip area, the data fields can be empty.

[0013] For the slip condition, a value pair can be formed from a relative wheel speed value and a relative wheel acceleration value. Numerical values ​​of the value pair can correspond to the coordinate of the selected data field. A relative speed value can represent a wheel slip speed. The slip speed can be a differential speed between the wheel and the ground. A relative acceleration value can represent a wheel slip acceleration. The slip acceleration can be a change in the slip speed. The slip speed and the slip acceleration can be determined by sensors and a reference speed of the vehicle. The reference speed can be available as a value in the vehicle.

[0014] The relative acceleration value can be determined using a curve of the wheel's relative speed value. The slip acceleration can be a gradient of the curve. The slip acceleration can be derived from the slip speed. This derivation requires only one sensor on the wheel.

[0015] The relative speed value can be determined using a wheel speed value of the wheel and another wheel speed value of another wheel on an axle of the wheel. A wheel speed value can represent a wheel speed of the wheel. The wheel speed can be detected by a simple and reliable sensor on the wheel. For example, a wheel speed sensor on the wheel can be used to detect the wheel speed. The slip speed can be a speed difference between the wheel speed and the wheel speed of the other wheel on the axle.

[0016] The action to be controlled can be selected based on the slip state. In particular, the action to be controlled can depend on a momentary change in the slip state. Different actions may be required to bring the slip state into the target slip range. For example, the wheel can be accelerated when locking. This can be achieved, for example, by increasing the drive torque or reducing the braking torque. Conversely, when spinning, the drive torque can be reduced or the braking torque increased.

[0017] If the current slip state is static, a different action may be required than if the current slip state changes dynamically.

[0018] Different actions can be stored in the data fields of the matrix. The action to be controlled can be read from the data field assigned to the slip state. At a transition from one slip state to another, adjacent data fields can be assigned to different actions.

[0019] A first value of a pair of values ​​characterizing the slippage state can be compared with a row value range of the target slippage range to determine a row range of the slippage state in the matrix. An upper row range can be determined if the first value is greater than the row value range. A middle row range can be determined if the first value lies within the row value range. A lower row range can be determined if the first value is less than the row value range.

[0020] A second value of the pair can be compared to a column range of the target slack range to determine a column range of the slack state in the matrix. A right column range can be determined if the second value is greater than the column range. A middle column range can be determined if the second value is within the column range. A left column range can be determined if the second value is less than the column range.

[0021] The specific row range and the specific column range can identify one of eight possible matrix sub-ranges of the matrix surrounding the target range. The action to be controlled can be selected using the identified matrix sub-range. The different matrix sub-ranges can be assigned to different slack state ranges. Transitions between different stored actions can be arranged at transitions between matrix sub-ranges.

[0022] A deviation of a subsequent slip state detected after the execution of the action from the target slip range can be determined.

[0023] Using the deviation, a correction factor can be determined for the parameter. The correction factor can be stored in the data field. If an action is carried out with at least one of the parameters stored in the data field, the subsequently recorded slip state should reach the target slip range or change in the right direction. If the slip state does not reach the target slip range or changes in the wrong direction, the parameter may be unsuitable for this vehicle. A correction factor can change the parameter so that at least an improvement can be achieved in a subsequent cycle. If a deterioration is achieved in the subsequent cycle, the sign of the correction factor can be changed. Correction factors can be used to optimize the traction control system fully automatically.

[0024] The method can be implemented, for example, in software or hardware or in a mixed form of software and hardware, for example in a control unit.

[0025] The approach presented here further provides a control device which is designed to carry out, control or implement the steps of a variant of the method presented here in corresponding devices.

[0026] The control unit can 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 a communication interface for reading in or outputting data embedded in a communication protocol. The computing unit can 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 can be, for example, a flash memory, an EPROM, or a magnetic storage unit. The interface can be designed as a sensor interface for reading in the sensor signals from a sensor and / or as an actuator interface for outputting the data signals and / or control signals to an actuator.The communication interface can be configured to read or output data wirelessly and / or via a wired connection. The interfaces can also be software modules, which are present, for example, on a microcontroller alongside other software modules.

[0027] Also advantageous is a computer program product or computer program with program code that can be stored on a machine-readable carrier or storage medium such as a semiconductor memory, a hard disk memory or an optical memory and is used to carry out, implement and / or control the steps of the method according to one of the embodiments described above, in particular when the program product or program is executed on a computer or a device.

[0028] It should be noted that some of the possible features and advantages of the invention are described herein with reference to different embodiments. A person skilled in the art will recognize that the features of the control device and the method can be combined, adapted, or interchanged as appropriate to achieve further embodiments of the invention. Short description of the drawing

[0029] Embodiments of the invention are described below with reference to the accompanying drawings, wherein neither the drawings nor the description are to be interpreted as limiting the invention. Fig. 1 shows a representation of a vehicle with a control unit according to an embodiment; Fig. 2 shows a representation of a slip state progression; and Fig. 3 shows a schematic diagram of a traction control system according to an embodiment.

[0030] The figure is merely schematic and not to scale. Like reference numerals denote like or equivalent features. Embodiments of the invention

[0031] Fig. 1 shows a representation of a vehicle 100 with a control unit 102 according to an exemplary embodiment. The control unit 102 is designed to regulate slip at wheels 104 of the vehicle 100. The control unit 102 is designed, in particular, to regulate traction slip at driven wheels 104 of the vehicle 100. The control unit 102 can also be used to regulate brake slip at the driven wheels 104 and non-driven wheels of the vehicle 100. The control unit 102 is connected to a braking system 106 of the vehicle 100 acting on the wheels 104. The control unit 102 is also connected to a drive system 108 of the vehicle 100 acting on the driven wheels 104.

[0032] The control unit 102 reads in a slip state 110 per wheel 104 or per axle. Using the slip state 110, at least one parameter 114 of an action 116 to be performed is read from a matrix 112 in the control unit if the slip state 110 lies outside a target slip range 118 of the matrix 112. To determine whether the slip state 110 lies outside the target slip range 118, a data field 120 of the matrix 112 associated with the slip state 110 is determined, and the parameter 114 is read from the data field 120 if the data field 120 lies outside the target slip range 118. If the data field 120 assigned to the slip state 110 lies within the target slip range 118, the data field 120 is not read out because the slip state 110 should then not change.

[0033] To execute action 116, a control signal 122 for the braking system 106 and / or the drive system 108 is generated using parameter 114. If the wheel 104, whose slip state 110 is being considered, currently has excessive slip, action 116 reduces the torque acting on the wheel 104. Parameter 114 specifies by how much the torque is reduced.

[0034] If the braking torque is too high, the braking pressure applied by the braking system 106 to the wheel 104 can be reduced as action 116. Parameter 114 represents the amount by which the braking pressure is reduced. Alternatively or additionally, the drive system 108 can generate or increase a drive torque at the wheel 104 or the axle that counteracts the braking torque. Parameter 114 represents the amount by which the drive torque is increased.

[0035] If the braking torque is too small, the braking pressure applied by the braking system 106 to the wheel 104 can be increased as action 116. Parameter 114 represents the amount by which the braking pressure is increased.

[0036] If the drive torque is too high, the power delivered by the drive system 108 to the wheel 104 or the axle can be reduced as action 116. Parameter 114 represents the amount by which the drive torque should be reduced. Alternatively or additionally, the braking system 106 can generate a braking torque at the wheel 104 that counteracts the drive torque. Parameter 114 represents the amount by which the braking torque is increased.

[0037] If the drive torque is too low, the power delivered by the drive system 108 to the wheel 104 or the axle can be increased as action 116. Parameter 114 represents the amount by which the drive torque is increased.

[0038] The slip state 110 of the wheel 104 is subsequently read in again after the action 116, and a corresponding parameter 114 for a subsequent action 116 is read from the matrix 112 if the slip state 110 continues to be outside the target slip range 118. The subsequent action 116 is controlled by a new control signal 122 for the braking system 106 and / or the drive system 108.

[0039] In one embodiment, the success of the previously executed action 116 is checked when the slip state 110 is subsequently read in again.

[0040] In particular, it is checked whether parameter 114 has led to a desired improvement in slip state 110. If the improvement is too small, the previously used parameter 114 and / or action 116 are changed. The change in parameter 114 can be made depending on a difference between slip state 110 and desired slip states of the target slip range 118.

[0041] In one embodiment, the slip state 110 is two-dimensional and is composed of a relative speed value 124 of the wheel 104 and a relative acceleration value 126 of the wheel 104.

[0042] In one embodiment, the relative speed value 124 represents a 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 detected at the wheel 104 by a wheel speed sensor 132 of the vehicle 100. The reference speed value 130 is continuously updated by a state estimator 134 of the vehicle 100.

[0043] In one embodiment, the relative speed value 124 represents a 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.

[0044] In one embodiment, different actions 116 are assigned to different data fields 120. The action 116 to be executed and the associated parameter 114 are read from the matrix 112 depending on the read slip state 110.

[0045] Fig. 2 shows a representation of a temporal progression of a slip state 110. The slip state 110 is two-dimensional and is shown in two temporally correlated diagrams superimposed on each other. Both diagrams have the time t plotted in seconds on the abscissa. The upper diagram has a speed in m / s plotted on the ordinate. The lower diagram has an acceleration in m / s 2< plotted on the ordinate. The upper diagram shows progressions of wheel speed values ​​128a, 128b. The lower diagram shows a progression of a relative acceleration value 126.

[0046] At the beginning of the curves, the vehicle is traveling at a constant speed. Then the vehicle accelerates, and the right wheel speed 128b increases at a constant gradient. The left wheel loses traction and begins to spin. The left wheel speed value 128a increases at a significantly greater gradient than the right wheel speed value 128b. A 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 rapidly after the left wheel loses traction. This rapid increase is also reflected 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 traction, the relative acceleration value 126 also increases rapidly from zero.At a first inflection point of the curve of the relative speed value 124, the curve of the relative acceleration value 126 has a maximum. A maximum of the curve of the relative speed value 124 is reached when the left wheel speed value 128a also reaches a maximum. At the maximum, 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 at a second inflection point of the curve of the relative speed value 124.

[0047] A time t1 is entered before reaching the first inflection point of the curve of the relative velocity value 124. Thus, the curve of the relative acceleration value 126 has not yet reached its maximum at time t1.

[0048] Fig. 3 shows a schematic diagram of a traction control system according to an exemplary embodiment. The traction control system can, for example, be implemented in a control unit as shown in Fig. 1 A two-dimensional slip state 110 at time t1 from Fig. 2 is highlighted in the matrix 112. The data fields 120 of the matrix 112 are all assigned to 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. The target slip range 118 is also shown in the matrix 112. The target slip range 118 here comprises three data fields 120 of the matrix.

[0049] In addition to the target slip range 118, eight matrix sub-ranges 300, 302, 304, 306, 308, 310, 312, 314 are shown in the matrix 112. In the first matrix sub-area 300, the data fields 120 are assigned to greater relative speed values ​​124 and greater relative acceleration values ​​126 than the data fields 120 in the target slip range 118. In the second matrix sub-area 302, the data fields 120 are assigned to greater relative speed values ​​124 and the same relative acceleration values ​​126 than the data fields 120 in the target slip range 118. In the third matrix sub-area 304, the data fields 120 are assigned to greater relative speed values ​​124 and smaller relative acceleration values ​​126 than the data fields 120 in the target slip range 118. In the fourth matrix sub-area 306, the data fields 120 are assigned the same relative speed values ​​124 and smaller relative acceleration values ​​126 than the data fields 120 in the target slip range 118.In the fifth matrix sub-area 308, the data fields 120 are assigned to smaller relative speed values ​​124 and smaller relative acceleration values ​​126 than the data fields 120 in the target slip range 118. In the sixth matrix sub-area 300, the data fields 120 are assigned to smaller relative speed values ​​124 and the same relative acceleration values ​​126 than the data fields 120 in the target slip range 118. In the seventh matrix sub-area 300, the data fields 120 are assigned to smaller relative speed values ​​124 and larger relative acceleration values ​​126 than the data fields 120 in the target slip range 118. In the eighth matrix sub-area 300, the data fields 120 are assigned to the same relative speed values ​​124 and larger relative acceleration values ​​126 than the data fields 120 in the target slip range 118.

[0050] The data field 120 assigned to the slip state 110 at time t1 is located in the first matrix sub-area 300. The desired slip states are located in the target slip range 118. The eight matrix sub-areas 300, 302, 304, 306, 308, 310, 312, 314 represent a static part 316 of the traction control system presented here.

[0051] Changes in the slip state 110 from run to run can be described by logic and represent a dynamic part 318 of the traction control presented here.

[0052] Using the static part 316 and the dynamic part 318, a basic action type 320 is determined. Using the basic action type 320 and additional influencing variables 322, a functional action type, or action 116, is determined. Action 116 can have three states 324, 326, and 328. The first state 324 is acceleration. The second state 326 is deceleration. The third state 328 is stop.

[0053] Using action 116 and static part 316, a parameter 114 is read from the matrix 112 associated with the respective state 324, 326, 328 of action 116. Action 116 and parameter 114 are used in an actuator control unit 330 to generate a control signal 122 for the braking system and / or the drive system.

[0054] In one embodiment, a result of the control is evaluated in a learning algorithm 332 and correction factors 334 are created for the parameters 114 stored in the data fields 120 in order to optimize the traction control fully automatically.

[0055] In the following, possible embodiments and configurations of the contact points presented here are described again in other words.

[0056] A state-action based traction control system is presented.

[0057] The Traction Control System (TCS) is a functional component of an ESP system. A core function of the Traction Control System is to prevent the wheels from spinning during a vehicle's longitudinal acceleration, thus meeting vehicle requirements regarding stability, steerability, and traction.

[0058] Conventional traction control is dependent on physical modeling variables of the powertrain and a speed reference. The speed reference is an estimate from an external function. The controller of conventional traction control provides setpoint specifications, which are converted into actuator control variables.

[0059] Conventional traction control is a complex system and requires approximately two years of effort to fully understand the system. Due to the large number of variants (>50 variants in a single project), conventional traction control requires a high level of application effort, with project durations of one to two years. Conventional traction control requires an estimate of the drive torque acting on the wheels and a speed reference as accurate as possible.

[0060] In the conventional system, the effective drive torque at the axles and wheels, expressed in newton meters (Nm), is used as the basis. This torque is modeled on the basis of a powertrain model using variables such as engine speed and wheel speeds. In the control case of conventional traction control, optimal traction slips are calculated, which provide ideal torque setpoints for the engine or braking torque specifications for the braking system. The braking torque specifications are then transformed back into brake pressure. If, for example, the drive torque estimation does not function correctly due to a suboptimal application for the respective vehicle variant or the external speed reference function is inaccurate, the performance or accuracy decreases.

[0061] When applying a conventional system, there are approximately 500 adjustment parameters that directly or indirectly influence the system. Understanding the interplay between parameters and the system is necessary to apply the function correctly. This requires a significant amount of time.

[0062] In the conventional system, all the know-how built into the system is almost exclusively specific to traction control. A function developer, software developer, or application engineer trained in conventional traction control cannot simply substitute for another function (e.g., ABS or VDC).

[0063] In the approach presented here, describing the system using physical-quantitative model variables is no longer so central. With the approach presented here, correct triggering is sufficient. The approach presented here describes an intuitive system with little application effort and a small number of variants.

[0064] As long as the traction control triggering works correctly, there is no loss of performance. Due to the state-action principle, the "state" is purely based on sensors, and the "action" acts directly on the respective actuators of the engine or braking system.

[0065] The controller parameters of the traction control system presented here are scaling values ​​that influence the engine and braking system actuators explicitly via absolute values ​​and / or implicitly via delta values. Using learning algorithms, these parameter values ​​are learned fully automatically by executing the most common traction control maneuvers according to a predefined maneuver catalog. This creates a direct relationship between the parameter values ​​and the "state," i.e., the wheel and axle behavior of the vehicle. This allows the application engineer to subsequently perform individual recalibration in a relatively straightforward and intuitive manner.

[0066] The approach presented here describes an intuitive system. The controller is "reimagined." There is no attempt to describe and control a highly complex reality by modeling the vehicle, the tires, and the environment. Rather, the premise is set from the outset that the highly complex system is neither able nor desired to be described. The approach is limited to the measured variables of sensors and the actuators. Everything in between is a generic approach.

[0067] With the approach presented here, understanding the system requires knowledge of the definition of the "state" and the basic control objective of the traction control system. No special expertise is required to apply the traction control function, as the software structure incorporates this expertise generically in the functional core and requires no further modification or adaptation. This also means that an understanding of the software and the function of the traction control system can be easily transferred to other functions such as ABS or VDC.

[0068] In the state-action principle presented here, a "state" describes a condition, based on which an action is executed based on a change in the state. The "action" describes a direct influence on the actuator, i.e., the motor and / or the braking system.

[0069] The possible "states" and the target range are stored in a table. The x-axis of the table shows the speed slip of a wheel or axle. The y-axis of the table shows the acceleration of the wheel or axle.

[0070] The following describes a signal flow of the approach presented here. Information about speed and acceleration is read from a wheel speed sensor and processed in a signal processing system. The "state" is determined based on the processed signals. The statics and dynamics of the "state" are determined. An action type, such as a pressure buildup or a torque reduction, is determined via internal logic. The actuator variables are set based on the action type. The resulting actuator control curves are characteristic of the state-action principle.

[0071] In the approach presented here, the learning algorithm is activated during the application. Parameter tables are updated. If an action was good, no change is made. If the action was bad, the parameters are varied.

[0072] The learning algorithm is deactivated in series. The parameter is read from the table and the actuator is set. Alternatively, learning in series is also possible.

[0073] The wheel or axle is controlled so that the system maintains its state within a control target, the so-called target zone. This allows the desired slip and acceleration to be set. This allows optimal traction to be achieved regardless of the speed reference.

[0074] The speed slip represents a difference between the speed of the wheel (or axle) that is breaking away and the reference speed.

[0075] The same reference speed as in the conventional system can be used as the reference speed. The reference speed is an external function of a vehicle state estimation (VSE). Alternatively, however, a separate (simple) reference logic can be implemented, since the quantitative description is no longer the focus for the state-action principle. In the approach presented here, the reference speed is primarily relevant for the correct triggering of a traction control event. The approach presented here can be described as "slip-free" because it does not require such an accurate speed reference as in the state-of-the-art.

[0076] Finally, it should be noted that terms such as "comprising," "having," etc., do not exclude other elements or steps, and terms such as "a" or "an" do not exclude a plurality. Reference signs in the claims are not to be considered limiting.

Claims

1. Method for controlling slip of at least one wheel (104) of a vehicle (100), wherein at least one parameter (114) of an action (116) to be performed is read from a matrix (112) using a slip state (110) of the wheel (104) if the slip state (110) is outside a target slip area (118) of the matrix (112), wherein, for reading, a data field (120) of the matrix (112) that is assigned to the slip state (110) is determined and the at least one parameter (114) is read from the data field (120), wherein, in order to perform the action (116), at least one actuator (106, 108) of the vehicle (100) is controlled using the parameter (114), characterized in that, for the slip state (110), a pair of values is formed from a relative speed value (124) of the wheel (104) and a relative acceleration value (126) of the wheel (104), wherein the relative speed value (124) represents a differential speed between the wheel (104) and a substrate.

2. Method according to Claim 1, in which the relative acceleration value (126) is determined using a progression of the relative speed value (124).

3. Method according to one of the preceding claims, in which the relative speed value (124) is determined using a wheel speed value (128a) of the wheel (104a) and a further wheel speed value (128b) of a further wheel (104b) on an axle of the wheel (104a).

4. Method according to one of the preceding claims, in which the action (116) to be controlled is furthermore selected using the slip state (110).

5. Method according to Claim 4, in which different actions (116) are stored in the data fields (120) of the matrix (112) and the action (116) to be controlled is read from the data field (120) assigned to the slip state (110).

6. Method according to one of Claims 4 to 5, in which a first value of a pair of values characterizing the slip state (110) is compared with a row value range of the target slip area (118) in order to determine a row area of the slip state (110) in the matrix (112), wherein an upper row area is determined if the first value is greater than the row value range, a middle row area is determined if the first value is within the row value range, and a lower row area is determined if the first value is less than the row value range, wherein a second value of the pair of values is compared with a column value range of the target slip area (118) in order to determine a column area of the slip state (110) in the matrix (112), wherein a right-hand column area is determined if the second value is greater than the column value range, a middle column area is determined if the second value is within the column value range, and a lefthand column area is determined if the second value is less than the column value range, where the determined row area and the determined column area indicate one of eight possible matrix subareas (300, 302, 304, 306, 308, 310, 312, 314) of the matrix (118) around the target slip area (118), wherein the action (116) to be controlled is selected using the indicated matrix subarea (300, 302, 304, 306, 308, 310, 312, 314).

7. Method according to one of the preceding claims, in which a deviation of a subsequent slip state (110) detected after the execution of the action (116) from the target slip area (118) is determined, wherein a correction factor (334) for the parameter (114) is determined using the deviation and is stored in the data field (120).

8. Control unit (102) which is designed to carry out, implement and / or control the method according to one of the preceding claims in corresponding devices.

9. Computer program product which is configured to instruct a processor to carry out, implement and / or control the method according to one of Claims 1 to 7 when executing the computer program product.

10. Machine-readable storage medium, on which the computer program product according to Claim 9 is stored.