Method for transmitting predictive information to a control device of a motor vehicle

Abstract

The invention relates to a method for transmitting predictive information to a control device of a motor vehicle and / or to a software module of the control device in order to determine an actuation command for at least one function of the motor vehicle by evaluating the transmitted predictive information. The method comprises the following steps: predicting the trend of a vehicle parameter of the motor vehicle for a preset time interval; determining at least one first extreme value of the predicted course, the first extreme value being located in a first partial time interval of the preset time interval starting from the current time point; determining at least one second extreme value of the predicted method, the second extreme value being located in a second partial time interval starting at the current time point, the second partial time interval being longer than the first partial time interval; and transmitting the determined at least one first extreme value and the determined at least one second extreme value as predictive information to the control device and / or the software module.

Description

Technical Field

[0001] The invention relates to a method for transmitting predictive information to a control device of a motor vehicle in order to determine, by means of the control device, an actuation command for at least one function of the motor vehicle by evaluating the transmitted predictive information. The invention also relates to a motor vehicle for carrying out such a method. Background Art

[0002] For example, a motor vehicle can have an algorithm located in a control device of the motor vehicle, which is designed as predictive information (i.e., for example, calculates and thereby predicts the expected future course of certain vehicle parameters). For example, this predictive information is used for intelligent control of the drive device of the motor vehicle so that the drive device can be operated in an energy-saving manner. For example, in a motor vehicle that can be driven at the front wheel axle and at the rear wheel axle by means of an electric motor, it can be preset that at least temporarily one of the electric motors used as secondary drives of the motor vehicle is not used in order to save energy. For example, it can be provided that when driving in a low load range at a constant speed, the secondary drive is disconnected and is connected again when the load range is about to increase. The control commands required for this purpose can be determined based on the predictive information (which, for example, describes the predicted wheel torque). By evaluating the predictive information, it is therefore possible to control the functions of the motor vehicle in a reasonable manner depending on the situation, for example, the function for disconnecting or connecting the secondary drive device in the motor vehicle to the two electric motors.

[0003] US2021 / 0316632 A1 shows a method for processing a preset computing task using a vehicle-based distributed computing system. The computing order is divided into different data packets, each of which includes computing data for a part of the computing order.

[0004] CN 106713512A shows an efficient data transmission method that can dynamically operate with the changing network bandwidth of the Internet of Things.

[0005] In the vehicle, predictive information and control commands for functions are usually determined in different modules and / or control units. Therefore, the vehicle-internal transmission of predictive information is necessary. However, this usually requires a high transmission power, since predictive information for a number of vehicle parameters must be determined and transmitted several times per second. Depending on the type of transmission, so-called aliasing phenomena may also occur, i.e. dynamic trends cannot be represented or determined correctly due to too low a sampling frequency. Summary of the invention

[0006] The object of the present invention is to provide a solution by means of which predictive information in a motor vehicle can be advantageously transmitted to a control device and / or a software module for determining an actuation command.

[0007] This object is achieved by the subject matter according to the invention.

[0008] A first aspect of the invention describes a method for transmitting predictive information to a control device of a motor vehicle and / or to a software module of the control device. This is achieved so that a control command for at least one function of the motor vehicle is determined by means of the control device or the software module by evaluating the transmitted predictive information. The control device is, for example, a control module or a control device in the motor vehicle, by means of which at least one component of the motor vehicle can be controlled. The software module is a component or a subunit of the control device. At least one controlled component is, for example, a drive device of the motor vehicle or a component associated with a drive device component. As at least one function, for example, if the motor vehicle has a main drive device and a secondary drive device (which are, for example, each configured as an electric motor and are associated with a corresponding wheel axle of the motor vehicle), a coupling or decoupling of the secondary drive device of the motor vehicle can be provided. For example, the main drive device is arranged at the rear axle of the motor vehicle and can drive the rear axle, while the secondary drive device is arranged at the front axle and can drive the front axle. In the low load range, it can be reasonable to decouple the secondary drive device (i.e., pause), for example, when driving with a constant speed in an area with a preset maximum speed. For example, the control command may relate to the disconnection or coupling of a secondary drive. For example, in order to couple a secondary drive again in good time (i.e., before it is needed), the control command is determined, in particular, based on predictive information. This enables proactive operation of the drive system. Alternatively or in addition to this, the function may relate, for example, to the start-stop control of the internal combustion engine of the motor vehicle when parking, the operation of the motor vehicle in a recuperation mode, or other functions for saving energy.

[0009] For example, the method according to the invention is performed with the aid of another control device of a motor vehicle, which is different from the control device for determining the control command. Thus, a first and a second control device can be distinguished. Alternatively or additionally to this, the method is performed with the aid of another software module of the control device of the motor vehicle. The software module can be included by the control device for determining the control command. In this case, the predictive information can be transmitted from the other software module to the software module of the control device that executes the determination of the control command. Therefore, the transmission of the predictive information is preferably carried out inside the vehicle. For example, the information transmission in the motor vehicle between the control devices of the motor vehicle is at least partially carried out with a cable, in particular by wire and / or without a cable, in particular wirelessly. Alternatively or additionally to this, if two different software modules or functions of a single control device are involved, the information transmission can be carried out inside the control device.

[0010] The method comprises predicting the course of a vehicle parameter of a motor vehicle for a preset time interval. For example, a specific vehicle parameter, such as a wheel torque, is predicted for a preset duration in the future. For example, the time interval is 1 second, 2 seconds or 3 seconds. Any time interval can be preset, which can be greater or less than the time interval mentioned, or between the time intervals mentioned. It is assumed that the time interval starts at a current time point and extends from this time point into the future. Known methods for predicting vehicle parameters of a motor vehicle can be used. Alternatively or in addition to the wheel torque, for example, wheel speed, speed, acceleration and / or other driving parameters can be predicted. Due to the predicted course, a number of individual values ​​that the vehicle parameter is expected to occupy within the time interval are calculated. Therefore, the course includes a plurality of individual values. For example, it can describe the predicted value for the vehicle parameter for all 10 milliseconds within the time interval. The individual predicted values ​​have a curve course, which is referred to here as the course of the vehicle parameter. Interpolation methods can be used to connect the individual predicted values ​​for the vehicle parameter (i.e., the vehicle parameter values) to each other. The interpolated values ​​then form the course.

[0011] The method comprises determining at least one first extreme value of the predicted trend. The first extreme value is located in a first partial time interval of a preset time interval starting at the current time point. The time interval, which is, for example, 2 seconds long in total, may include a first partial time interval, which is, for example, half a second long. The starting point of the partial time interval is the current time, so that it has the first half second of the time interval including two seconds. For example, the maximum value of a vehicle parameter may be determined as a first extreme value in the first partial time interval. This extreme value is a single value of the predicted trend and therefore a single value among the many values ​​included by the trend. Therefore, compared with the trend of the vehicle parameter, the first extreme value obviously requires less storage space and can be transmitted with less consumption.

[0012] In addition, at least one second extreme value of the predicted trend is determined, which second extreme value is located in a second partial time interval of the preset time interval starting at the current time point. The second partial time interval is longer than the first partial time interval. For example, the second partial time interval can be 1 second long. In this example, the two partial time intervals correspond to the first half second from the current time point. For example, the second extreme value can be the maximum value of the trend. Depending on the predicted trend, the first and second extreme values ​​can be the same or different. Therefore, at least two individual values ​​are determined from the predicted trend, one for each partial time interval. In addition to the two partial time intervals mentioned here as an example, alternative partial time intervals are also possible.

[0013] The corresponding determined extreme value comprises the value of the vehicle parameter and a time specification which specifies the time point in the time interval for which it is predicted. The extreme value thus describes a point along the predicted course. The corresponding extreme value can therefore alternatively be referred to as corresponding extreme value information describing the first or second extreme value.

[0014] The method comprises transmitting at least one first determined extreme value and at least one second determined extreme value as predictive information to a control device and / or a software module of the control device. Thus, at least two extreme values ​​constitute predictive information, which is provided to the control device and / or the software module so that the control device and / or the software module can determine a control command. Thus, the entire predicted course of the vehicle parameter is not provided, but only at least two extreme values. As a result, the amount of information to be transmitted is significantly reduced, wherein details about the predicted course are still present, based on which the control command can be reliably determined. Thus, the predictive information is advantageously transmitted to the control device and / or in the control device in the motor vehicle in order to determine the control command.

[0015] One embodiment provides that the control device and / or the software module receives at least one first extreme value and at least one second extreme value and checks whether at least one extreme value lies within a preset value range. This embodiment is therefore performed by a control device, which is used to determine the control command. For example, the preset value range can preset an upper or lower limit, from which or below which a specific function should be triggered. Therefore, the preset value range can include limit values ​​or threshold values, or alternatively be referred to as limit values ​​or threshold values. For example, extreme values ​​above or below the limit value or threshold value can then be evaluated as being within the preset value range. For example, in the case of wheel torque, the preset value range can be between greater than or equal to 80% and 100% of the maximum wheel torque. Alternative value ranges are possible.

[0016] If at least one of the extreme values ​​is within the predefined value range, an actuation command is determined and executed, according to which a function of the motor vehicle is activated. It is thus determined solely on the basis of the transmitted extreme values ​​and their evaluation whether a specific function of the motor vehicle should be activated. For example, if both transmitted extreme values ​​are within the predefined value range, this can lead, for example, to an automatic disconnection or coupling of a secondary drive. Thus, a rational actuation of a function of the motor vehicle is performed without requiring the entire predicted course of the vehicle parameter.

[0017] The control command can be determined in such a way that it is set for a predefined future time point in the time interval. Thus, for example, a control command can be determined for a time point in the future and its implementation can be prepared. Thus, the determination of the control command and its implementation can be carried out with a time delay.

[0018] Furthermore, one embodiment provides that a control command is determined and executed, according to which a function of the motor vehicle is activated, only when at least one first extreme value and at least one second extreme value are within a predefined value range and are not predicted for the same point in time. Thus, for example, it can be provided that two different extreme values ​​must be determined for two time intervals in order to assume that, for example, vehicle parameters within this value range are permanently present. Only then is the activation of the function actually carried out. This can be reasonable to take into account a trend in which, for example, only locally occurring extreme values ​​surrounded by lower or higher values ​​occur, so that activation of the function should only be carried out temporarily or should be inhibited.

[0019] In an additional embodiment, it is provided that at least one corresponding extreme value describes the maximum and / or minimum of the predicted trend. Preferably, each partial time interval determines two extreme values ​​(maximum and minimum). Alternatively or additionally to this, a distinction can be made between local and global extreme values. Thus, each partial time interval can determine and transmit multiple maxima (global value and at least one local value) and / or multiple minima (global value and at least one local value). It can also be preset that each maximum value and minimum value has its own value range preset, so that different operating strategies can be pursued depending on the transmitted extreme values. In addition, it is possible to obtain a detailed estimate of the trend of the vehicle parameter, because not only the maximum value (maximum) but also the minimum value (minimum) is known for each partial time interval. This improves the accuracy of the determination of the control command.

[0020] In another embodiment, if two extreme values ​​describe a maximum value for the same point in time, but describe a minimum value outside a predefined value range for different points in time, a control command is determined and implemented, according to which the function is not activated. Thus, for example, it can be the case that a maximum value occurs in the first partial time interval, which also constitutes the maximum value of the second partial time interval. After this maximum value, the predicted trend decreases again and again, so that two different minimum values ​​are determined for the partial time interval. In such a case, it can be reasonable to first not activate the function at all, because its activation condition may not be met for a long time. This can apply similarly to a common minimum value and different maximum values. This further refines the determination of the control command.

[0021] Generally, it is provided that if neither the maximum value nor the minimum value lies within a corresponding predefined value range, the function is not activated according to the determined control command (i.e., remains deactivated or paused, for example). For example, in this case, no change in the coupling state of the secondary drive occurs. Thus, a reset criterion can be predefined, which is met, for example, if the minimum value or the maximum value in each of the two partial time intervals lies outside a value range, in particular a corresponding value range.

[0022] Different actuation strategies are possible for the functions, which can be predefined on the basis of at least two extreme values ​​by determining corresponding actuation commands.

[0023] In one embodiment, it is provided that the trend of a vehicle parameter is predicted by applying a prediction criterion to at least one sensor information. The sensor information is acquired by means of a sensor device of a motor vehicle. The sensor device includes, for example, a sensor that describes the travel of the motor vehicle. For example, the sensor information can describe the operation of a gas pedal, the rotational movement of the wheels of the motor vehicle (wheel speed) and / or the steering angle. Alternatively or additionally to this, the sensor device can be an environmental sensor, such as a camera, a radar device, a laser device and / or an ultrasonic sensor. Then, the sensor information can describe at least a part of the environment of the motor vehicle. The environment may be arranged outside the vehicle and / or inside it. Preferably, the sensor device is configured to determine the position of the motor vehicle, for example, based on a global navigation satellite system (GNSS), such as a global positioning system (GPS), in particular. Then, the sensor information describes the position of the motor vehicle. Different on-board sensors can be included by the sensor device, and the trend of a vehicle parameter (for example, wheel torque) is predicted based on their data (ie, sensor information). For this purpose, the sensor device provides sensor information to a control device or a control module that predicts the trend. The provision can include transmission from the sensor device to the control device or to the control module. Alternatively or additionally thereto, the sensor device provides sensor information to a software module of the control device.

[0024] The prediction criterion should include at least one algorithm and / or rule, which, when executed, can infer the course of the vehicle parameter from the sensor information. For this purpose, multiple sensor information, in particular sensor information from different sensor devices, can be combined. This makes it clear how the predictive information can be reasonably determined.

[0025] Furthermore, one embodiment provides for determining and transmitting a reliability value for the corresponding extreme value. The reliability value describes the reliability of the prediction of the trend in the corresponding partial time interval. The reliability value indicates, for example, how reliable the predicted trend in the corresponding partial time interval is as a value between 0 and 1 or between 0% and 100%. Therefore, it is evaluated what kind of quality state the corresponding predicted trend and the extreme value determined thereby have. The reliability value can alternatively be referred to as a quality value or a credibility value. For example, the transmission of the reliability value enables different weightings of the individually transmitted extreme values ​​when determining the control command. Therefore, the control device and / or the software module take into account the transmitted reliability value when determining the control command.

[0026] For example, if the prediction for the second partial time interval is worse than the prediction for the first partial time interval because the corresponding reliability values ​​are lower or higher, it can be preset that only at least one first extreme value is taken into account when determining the control command, and at least one second extreme value is not taken into account. Therefore, in this example, only the extreme value is taken into account for determining the control command, which is the most reliable (i.e., it has, for example, the highest or lowest reliability value of the transmitted reliability values). Alternatively or in addition to this, a reliability limit value or a reliability value range can be preset, wherein only extreme values ​​are taken into account whose reliability values ​​are above or below the reliability limit value (according to the definition of the reliability limit value) or are located in the reliability value range. It is thus possible to first evaluate how reasonable it is to control the function of the motor vehicle based on the predictive information. For example, in the case of an insufficient reliability value, other methods for determining the control command (which do not require predictive information) can be used and / or the function can be suspended.

[0027] In an additional embodiment, the corresponding reliability value is determined by comparison. For example, vehicle parameters predicted for a past time interval that are at least temporarily stored are selected and compared with vehicle parameters actually measured within this time interval. Thus, for example, it is evaluated how reliable the trend of the predicted vehicle parameters is for the last 5 seconds that have passed, because for these past 5 seconds, for example, the actual trend measured is already known. Therefore, it is possible to retrospectively determine how reliable the prediction of the trend is, especially depending on the partial time interval, by comparing the predictive data with the data actually measured later. Thus, the accuracy and reliability of the prediction can be determined afterwards and, for example, can be assumed to remain unchanged and therefore continue to be valid for time intervals in the near future. The near future here means that the time interval between the comparison and the determination of the reliability value and the time interval of the predicted trend (for which the same reliability value should be assumed to remain) is close to a time of a few seconds or minutes, for example a maximum of 5 minutes.

[0028] Alternatively or additionally thereto, the reliability value can depend on the prediction criterion. For example, if the prediction criterion is based on a machine learning method (e.g., based on an artificial neural network), then, for example, the training quality of the prediction criterion and thus, for example, the training quality of the artificial intelligence model can be taken into account in order to indicate the reliability value. Thus, the reliability value can be fixedly preset depending on the prediction criterion used.

[0029] Alternatively or in addition thereto, the corresponding reliability value can be determined by evaluating the quantity and / or completeness of the sensor information. For example, if it is determined that there are dropouts in the acquisition of the sensor information, for example due to locally uncertain position information, the reliability value can be calculated based on this information. Dropouts can occur, for example, due to reception problems or other technical problems. For example, if there is only sporadic sensor information and therefore a small amount of sensor information for predicting the direction, this can also lead to a reduction in the reliability value compared to sensor information in which many and therefore more individual measured values ​​are available for each time interval.

[0030] Alternatively or additionally thereto, the respective reliability value may depend on the sensor device. For example, in the case of positioning a motor vehicle with the aid of GNSS data, the quality of the sensor device, in particular the number of visible satellites, may play a role. Depending on how good the quality of the respective sensor device and its information acquisition is, which may be position-dependent and / or time-dependent, the respective reliability value is calculated.

[0031] Therefore, many possibilities are possible for making a quality judgment and thus for determining a reliability value, so that this reliability value can be determined or predefined exactly.

[0032] In another embodiment, it is provided that the function of the motor vehicle relates to a drive device of the motor vehicle. The control command predetermines an operating strategy for the drive device. Preferably, the function thus relates to drive train control. Generally, the vehicle parameter can relate to a theoretical torque for the vehicle speed or the steering of the motor vehicle for the next few seconds. For example, efficiency and / or comfort advantages related to the drive of the motor vehicle can be achieved with the help of the control command.

[0033] For application situations or scenarios which may arise in the method and are not explicitly described here, it can be provided that according to the method an error message and / or a request for inputting user feedback and / or a standard setting and / or a predetermined initial state are set.

[0034] Another aspect of the invention relates to a motor vehicle. The motor vehicle is configured to carry out the method described above. For this purpose, the motor vehicle can have a control device. It can also have a further control device and / or a software module, wherein the control device or the software module carries out the prediction of the trend, the determination of the extreme value and the transmission of the determined extreme value. The motor vehicle is preferably designed as a car, in particular a passenger car or a truck, or as a passenger bus or a motorcycle.

[0035] The present invention also includes a corresponding control device. The control device may have a data processing device or a processor device, which is set up to perform the method according to the present invention. The processor device may include at least one microprocessor and / or at least one microcontroller and / or at least one FPGA (field programmable gate array) and / or at least one DSP (digital signal processor) for this purpose. As a microprocessor, in particular, a CPU (central processing unit), a GPU (graphics processing unit) or an NPU (neural processing unit) can be used respectively. In addition, the processor device may have a program code, which is set up to perform the method according to the present invention when implemented by the processor device. The program code can be stored in a data memory of the processor device. The processor device can be based on at least one circuit board and / or at least one SoC (system on chip), for example.

[0036] The invention also includes developments of the motor vehicle according to the invention which have the features which have already been described in conjunction with the exemplary embodiments of the method according to the invention. For this reason, the corresponding developments will not be described again here.

[0037] The invention also encompasses combinations of features of the described exemplary embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] An example of the present invention is described below. To this end:

[0039] Figure 1 A schematic diagram of a motor vehicle having a control device is shown;

[0040] Figure 2 A schematic diagram shows a signal flow diagram of a method for transmitting predictive information to a control device of a motor vehicle; and

[0041] Figure 3 The schematic diagram shows the Figure 2 Two embodiments of the method.

[0042] The examples explained below are preferred embodiments of the present invention. In the embodiments, the components described respectively constitute individual features of the present invention that should be considered independently of one another, which also improve the present invention independently of one another and should therefore also be considered as components of the present invention individually or in a combination different from the combination shown. In addition, the described embodiments can also be supplemented by other already described features of the present invention.

[0043] In the figures, functionally identical elements are respectively provided with the same reference symbols. DETAILED DESCRIPTION

[0044] Figure 1A motor vehicle 1 is shown having a control device 2. The control device 2 is designed to determine an actuation command 3 for at least one function 4 of the motor vehicle 1. The actuation command 3 relates, for example, to the activation, deactivation or suspension of the function 4. The function 4 of the motor vehicle 1 preferably relates to a drive device 5 of the motor vehicle 1. The actuation command 3 then specifies an operating strategy for the drive device 5.

[0045] The motor vehicle 1 has a further control device 6, which can alternatively be designed as a software module in the motor vehicle 1, for example, as a software module in the control device 2. The further control device 6 is designed to determine predictive information 7 and transmit it to the control device 2. For this purpose, for example, the further control device 6 can evaluate at least one sensor information 9, which is transmitted to the further control device by a sensor device 8 of the motor vehicle 1. The sensor device 8 of the motor vehicle 1 can acquire the sensor information 9. The sensor information 9 can be, for example, speed, steering angle, wheel speed, gas pedal actuation value and / or other driving-related parameters. Alternatively or in addition to this, the sensor information 9 can include camera data, radar data, lidar data and / or ultrasonic sensor data. In principle, the sensor device 8 can be any on-board sensor of the motor vehicle 1.

[0046] For example, the sensor information 9, the predictive information 7 and / or the control command 3 are transmitted via a wired communication connection in the motor vehicle 1. Alternatively or in addition thereto, the communication connection can be designed at least partially without a wire, in particular wirelessly.

[0047] Figure 2 The method steps of a method for transmitting predictive information 7 to a control device 2 of a motor vehicle 1 are shown. In method step S1, a course 10 of a vehicle parameter 11 of the motor vehicle 1 is predicted for a preset time interval 12. For example, the course 10 is determined by applying a prediction criterion 13 to at least one sensor information 9. For example, the course 10 of the wheel torque or another vehicle parameter 11 of the motor vehicle 1 is predicted. For example, the preset time interval 12 can be 2 or 3 seconds long from the current time point (t=0). In this case, an exemplary curve is drawn as the course 10, wherein in the diagram, the vehicle parameter 11 is plotted against the time t.

[0048] In method step S2, at least one first extreme value of the predicted course 10 is determined, which first extreme value is located in a first partial time interval 16 of the preset time interval 12, which begins at the current time point. In addition, at least one second extreme value is determined, which second extreme value is located in a second partial time interval 17 of the preset time interval 12, which begins at the current time point. The second partial time interval 17 is longer than the first partial time interval 16. For example, the first partial time interval 16 can be 0.5 seconds long, while the second partial time interval 17 can be 1 second long. In this case, each partial time interval 16, 17 determines a maximum value 14a, 15a and a minimum value 14b, 15b as extreme values. In this case, for example, the maximum values ​​14a, 15a coincide in two partial time intervals 16, 17, so that a common maximum value 14a, 15a is determined. In this case, the two minimum values ​​14b, 15b are different, so that each partial time interval 16, 17 determines a minimum value 14b, 15b, which is different from the corresponding other minimum values ​​14b, 15b. It may also be provided that a reliability value 20 , 21 is determined for the respective extreme value, which reliability value describes the reliability of the prediction of the course 10 in the respective partial time interval 16 , 17 .

[0049] The respective reliability values ​​20 , 21 can be determined by comparing vehicle parameters 11 predicted for past time interval 12 with vehicle parameters 12 measured in this time interval 12 and / or depending on prediction criteria 13 and / or by evaluating the quantity and / or completeness of sensor information 9 and / or depending on sensor device 8 .

[0050] In method step S3 , the at least one determined first extreme value and the at least one determined second extreme value are transmitted to the control device 2 as predictive information 7 .

[0051] In method step S4, it can then be provided that the control device 2 receives the extreme values ​​and checks whether they are within a predefined value range 18. In this case, a separate value range 18 can be predefined for each of the maximum values ​​14a, 15a and the minimum values ​​14b, 15b. If one of the extreme values ​​is within the predefined value range 18, a control command 3 can be determined, according to which a function 4 of the motor vehicle 1 is activated. This is done in method step S5. In method step S5, the determined control command 3 can also be implemented, that is, in this case, for example, a function 4 of the motor vehicle 1 is activated.

[0052] If it is determined in method step S4 that the extreme value lies outside the predefined value range 18 , then in method step S6 an actuation command 3 can be determined and executed, according to which the function 4 is not activated. For example, in this case it remains deactivated or paused.

[0053] Method steps S1 to S3 are performed here by means of a further control device 6. Method steps S4 to S6 are performed by means of the control device 2. Alternatively or in addition thereto, method steps S1 to S3 can be performed by means of a further software module of the control device 2, and method steps S4 to S6 can be performed by means of a software module of the control device 2 for determining the control command 3 (not shown here).

[0054] It can be provided that the corresponding transmitted reliability values ​​20, 21 are taken into account when determining the control command 3 and thus in method step S5 and optionally in method step S6. Thus, depending on how reliable the corresponding extreme value is, an adapted operating strategy for the drive device 5 can be selected by determining the corresponding control command 3.

[0055] exist Figure 3 , as case A, the situation is shown in which a separate maximum value 14a, 15a is determined for each of the two partial time intervals 16, 17, so that it can be assumed that maximum values ​​14a, 15a occur repeatedly within a predefined value range 18. It can be provided that a function 4 of the motor vehicle 1 is activated according to the control command 3 only when at least one extreme value and at least one second extreme value are within the predefined value range 18 and these extreme values ​​are not predicted for the same point in time.

[0056] As case B, the case is shown in which the two extreme values ​​describe maximum values ​​14a, 15a for the same point in time, but describe minimum values ​​14b, 15b for different points in time, which are also outside the predefined value range 18. In this case, a control command 3 is then determined and executed, according to which the function 4 is not activated. Additional or alternative operating strategies are possible.

[0057] Overall, the example shows a method for the efficient transmission and processing / utilization of predictive information 7 in a motor vehicle 1. Instead of a continuous data stream (curve 10) of a predicted physical variable, for example at time t+x seconds, and a further data stream at time t+y, t+n, etc., only the required minimum or maximum values ​​and the corresponding extreme values ​​in the corresponding previously defined prediction time periods (partial time intervals 16, 17) should be transmitted from the continuous prediction result (curve 10) to the receiver function (control device 2). The required transmission bandwidth and the required computing capacity are thereby reduced. In addition, aliasing of the predictive information 7 is thus excluded.

[0058] Furthermore, by using and taking into account two prediction time periods of different lengths and thus partial time intervals 16, 17, a simple and thus less intelligent hysteresis can be replaced by a logic that takes into account intelligent prediction data (predictive information 7). This allows a functional logic based on predicted vehicle behavior to be implemented that takes into account vehicle behavior more effectively. Thus, for example, it is not necessary to predetermine the hysteresis threshold as a limit value, in the case of which, for example, a lower value is required for switching off than for switching on, since this is not necessary due to the intelligent control based on extreme values.

[0059] The prediction of the course, the determination of the extreme values ​​and their transmission to the control device 2 are performed by means of a predictor or a prediction module in the motor vehicle 1. This predictor or prediction module is referred to here as a further control device 6. The receipt of the extreme values ​​and the determination and execution of the control command 3 are performed by means of the control device 2, which can alternatively be referred to as a control command module.

[0060] Reference numerals list

[0061] 1 Motor Vehicle

[0062] 2 Control device

[0063] 3 Control commands

[0064] 4 Functions

[0065] 5 Drive equipment

[0066] 6 Additional control devices

[0067] 7 Predictive Information

[0068] 8 Sensor devices

[0069] 9 Sensor information

[0070] 10 Trends

[0071] 11 Vehicle Parameters

[0072] 12 Time interval

[0073] 13 Prediction Criteria

[0074] 14a,15a maximum

[0075] 14b,15b maximum value

[0076] 16 Part 1 Time Interval

[0077] 17 Part 2 Time Interval

[0078] 18 Value range

[0079] 20 Reliability value

[0080] 21 Reliability value

[0081] S1 to S6 method steps

[0082] A, B situation

[0083] t time

Claims

1. A method for transmitting predictive information (7) to a control device (2) of a motor vehicle (1) and / or to a software module of the control device (2) in order to determine, by means of the control device (2) and / or the software module, an actuation command (3) for at least one function (4) of the motor vehicle (1) by evaluating the transmitted predictive information (7), wherein: The method comprises: - predicting (S1) the course (10) of a vehicle parameter (11) of the vehicle (1) for a predetermined time interval (12); - determining (S2) at least one first extreme value of the predicted trend (10), said at least one first extreme value being located in a first partial time interval (16) of the predetermined time interval (12) starting at the current time point; - determining (S2) at least one second extreme value of the predicted trend (10), said at least one second extreme value being located in a second partial time interval (17) of said predetermined time interval (12) starting at the current time point, wherein said second partial time interval (7) is longer than said first partial time interval (16); and - transmitting (S3) the at least one determined first extreme value and the at least one determined second extreme value as the predictive information (7) to the control device (2) and / or the software module.

2. The method according to claim 1, wherein: The control device (2) and / or the software module receives the at least one first extreme value and the at least one second extreme value and checks (S4) whether at least one of the extreme values ​​is within a predefined value range (18), wherein, if this is the case, a control command (3) is determined and executed (S5), according to which a function (4) of the motor vehicle (1) is enabled.

3. The method according to claim 2, wherein: The control command (3) is determined and executed only when the at least one first extreme value and the at least one second extreme value are within the predefined value range (18) and are not predicted for the same point in time, according to which the function (4) of the motor vehicle (1) is enabled.

4. A method according to any one of the preceding claims, wherein: The respective at least one extreme value describes a maximum value (14a, 15a) and / or a minimum value (14b, 15b) of the course (10).

5. The method according to claim 4, wherein: If the two extreme values ​​describe the maximum value (14a, 15a) at the same time, but describe the minimum value (14b, 15b) outside the predefined value range (18) at different times, an actuation command (3) is determined and executed, according to which the function (4) is not activated.

6. A method according to any one of the preceding claims, wherein: The course (10) of the vehicle parameter (11) is predicted by applying a prediction criterion (13) to at least one sensor information (9) acquired by means of a sensor device (8) of the motor vehicle (1).

7. A method according to any one of the preceding claims, wherein: A reliability value (20, 21) is determined and transmitted for the respective extreme value, which reliability value describes the reliability of the prediction of the course (10) in the respective partial time interval (12), wherein the control device (2) and / or the software module takes the transmitted reliability value (20) into account when determining the control command (3).

8. The method according to claims 6 and 7, wherein: Corresponding reliability value (20) - determined by comparing a vehicle parameter (11) predicted for a past time interval (12) with a vehicle parameter (11) measured during said time interval (12); and / or - depending on the prediction criteria (13); and / or - determined by evaluating the quantity and / or completeness of said sensor information (9); and / or -Depending on the sensor device (8).

9. A method according to any one of the preceding claims, wherein: The function (4) of the motor vehicle (1) relates to a drive device (5) of the motor vehicle (1), and the control command (3) specifies an operating strategy for the drive device (4).

10. A motor vehicle (1) which is designed to carry out the method according to any one of the preceding claims.

Images