System for parameterizing a motor vehicle operating strategy

Abstract

System (20) for parameterizing a motor vehicle operating strategy, the system (20) comprising - a human-machine interface (21) and - a processor unit (22), wherein - the human-machine interface (21) is configured to output a user interface (26) visible to a user of the human-machine interface (21), - the user interface (26) displays a polygon (24), the corners (27, 28, 29) of which are each assigned a category of an operating strategy (Sport, Eco, Comfort) for a motor vehicle (1), the operating strategies (Sport, Eco, Comfort) being maximally pronounced in the corners (27, 28, 29), - a plurality of operating strategy points (30, 31, 32, 34) are arranged within the polygon (24), wherein the operating strategy points (30, 31, 32, 34) are each assigned an operating strategy which corresponds to a mixed form of the different operating strategies (Sport, Eco, Comfort), - the human-machine interface (21) is designed to allow the user to select at least one operating strategy point (30) located within the polygon (24), - the processor unit (22) is configured to determine several parameters (35.1, 36.1) for controlling the motor vehicle (1) based on a selected operating strategy point (30), - first parameters (35.1) are stored in a first parameter level (35) which is not visible to the user and is hidden by the polygon (24) displayed by the user interface (26), - second parameters (36.1) are stored in a second parameter level (36) which is not visible to the user and which is hidden by the polygon (24) displayed by the user interface (26) and by the first parameter level (25), and - the operating strategy points (30) are each arranged vertically above the first parameters (35.1) and second parameters (36.1) assigned to them.

Description

The invention relates to a system for parameterizing a motor vehicle operating strategy.In known controls of an operating strategy of a vehicle, fixed parameterizations are typically predefined, which allow little individualization. The driving behavior of the vehicle is classified into categories such as "comfort", "economy", and "sport", for example. Characteristic maps are usually varied here, which provide for a dynamic acceleration (provided the category "sport") or a different steering ratio, for example. The adjustment possibilities and the number of adjustable parameters are limited in this case. Research themes in the field of operating strategy of a vehicle are currently directed to predictive regulations, which comprise in particular a system for model-based predictive regulation. In such a system, a parameterizable cost function is typically minimized. The complex systems usually used in this case result in a large amount of possible parameterizations which have to be controlled.The post-published document DE 10 2022 111 537 A1 teaches weighting factors in a quality function and the selection of optimization goals. In this case, the weighting factors are translated into corresponding parameter settings if the trajectory planning is heuristic and rule-based.An object of the present invention can be seen in reducing the complexity in the selection of parameters of an operating strategy for a motor vehicle and simplifying the parameterization for a user of the motor vehicle. The object is achieved by the subject matters of the independent claims. Advantageous embodiments are the subject matter of the dependent claims, the following description and the figures.According to the present invention, an interface architecture for parameterization is proposed, in particular for parameterizing an MPC system for a motor vehicle. In a driver-vehicle interface or a control of the operating strategy of the motor vehicle, a multidimensional characteristic diagram is incorporated. Categories or operating strategies for the motor vehicle are applied at the corners of the characteristic map, for example "comfort", "eco" and "sport". In particular, by moving a cursor, a user or a driver of the motor vehicle can set the preference for a desired system behavior. Behind the cursor is a data record of the parameterization, as a result of which the parameterization of the model-based predictive control, for example, is varied. According to the number of categories, the number of vertices varies. The interface architecture according to the invention enables a great simplification of the parameterization and individualization of complex software systems, in particular in the case of an MPC algorithm in the vehicle application.In this sense, the invention provides a system for parameterizing an operating strategy for a motor vehicle. The motor vehicle is in particular a vehicle which is driven by an engine, for example an automobile (e.g. a passenger car with a weight of less than 3.5 t), motorcycle, motor scooter, moped, bicycle, e-bike or pedelec (acronym for Pedal Electric Cycle), bus or truck (e.g. with a weight of more than 3.5 t), or else a rail vehicle, a ship, an aircraft such as helicopter or aircraft. The invention can also be used in small, lightweight electric motor vehicles of micromobility, these motor vehicles being used in particular in urban traffic and for the first and last mile in rural space. The first and last mile can be understood to mean all routes and paths which are located in the first and last link of a mobility chain. This is, for example, the path from home to station or the route from station to station. In other words, the invention can be used in all fields of transport, such as automotives, aviations, nautics, astronautics, etc. The motor vehicle may belong to a fleet of vehicles, for example. The motor vehicle may be controlled by a driver, possibly assisted by a driver assistance system. However, the motor vehicle can also be controlled remotely and / or (partially) autonomously, for example.The system according to the invention comprises a human-machine interface and a processor unit, wherein the human-machine interface is configured to output a user interface visible to a user of the human-machine interface. The user interface represents a polygon, the corners of which are each assigned a category of an operating strategy for a motor vehicle, wherein the operating strategies are each maximally pronounced in the corners. A plurality of operating strategy points are arranged within the polygon, wherein the operating strategy points are each assigned an operating strategy which corresponds to a mixed form of the different operating strategies. The man-machine interface is configured to allow the user to select at least one operating strategy point lying within the polygon. The processor unit is configured to define a plurality of parameters for controlling the motor vehicle based on a selected operating strategy point. This determination of the parameters is effected in particular fully automatically by the processor unit without the user having to influence or being able to influence it.In one specific embodiment, the motor vehicle is controlled by means of a model-based predictive control, the processor unit being set up to define a plurality of parameters of the model-based predictive control for controlling the motor vehicle on the basis of the selected operating strategy point. A first parameter can be, for example, a maximum permissible transverse acceleration of the motor vehicle. A second parameter can be, for example, an energy value which must be provided, for example, by a battery of the motor vehicle in order to move the motor vehicle along a selected optimized trajectory within a prediction horizon of a model-based predictive control. A third parameter can be, for example, a period of time within which the motor vehicle is intended to cover the selected optimized trajectory. The above-mentioned parameters and their number are to be understood merely as examples. The number of parameters or parameter levels can be defined in particular by a number of parameters of the motor vehicle to be set. Expressed mathematically, the number of different parameters or parameter planes can be described by an element of the natural numbers N.According to a further embodiment, it is provided that the processor unit is configured to adapt a cost function and / or a secondary condition of the model-based predictive control as a function of the defined parameters. For example, the motor vehicle can travel along a trajectory that has been optimized and selected by the model-based predictive control. An energy term may be included in a cost function of the model-based predictive control, which describes the energy required to be provided in order for the motor vehicle to be able to follow the trajectory within the prediction horizon. The trajectory can be, for example, a speed trajectory according to which waypoints and / or points in time which lie within the prediction horizon are assigned speed values of the motor vehicle. If, for example, a more environmentally friendly trajectory corresponding to the category or operating strategy "ECO" is now to be generated, the required energy can be defined as a parameter on the basis of the selected operating strategy point by the relevance of the energy term of the cost function being increased. However, this would greatly intervene in the planned trajectory and should not be adjustable by inexperienced end consumers. For example, an application team of an automobile manufacturer would be the suitable user. An application that would be to be adjusted by the end user would be to select the operating strategy point in terms of ride comfort.If, alternatively or additionally, for one of the parameters, for example, the maximum permissible transverse acceleration that the motor vehicle may have within the planned trajectory is selected, then it would be advantageous from the standpoint of comfort to reduce the transverse acceleration. Thus, an assignment close to the comfort category would be expedient with this. The transverse acceleration in turn could in this case be, in particular, a parameterizable boundary condition. It would likewise be conceivable to include this parameter in the configuration, so that the parameter in the cost function influences the solution as a factor. For example, the described transverse acceleration could also be included in a term of the cost function, but does not have to be included. This is part of the definition of the model and the use of model-based predictive control.In particular, according to one specific embodiment, it is provided that the operating strategy approaches the maximum characteristic of the respective operating strategy as the distance between the operating strategy points and one of the corners decreases. The closer the user moves a cursor within the user surface in the direction of one of the corners of the polygon, for example, the more the characteristic of the respective operating strategy can be characteristic. If, for example, a sporting operating strategy is assigned to one of the corners of the polygon and the user moves the cursor within the polygon in the direction of this corner, then he thus increases the sporting character of the operating strategy.By moving the cursor within the polygon, the driver can set the preference of the desired system behavior. Behind the cursor is a data record of the parameterization, as a result of which the parameterization of the model-based predictive control can be varied. In the application of model-based predictive control, many parameters are to be set which cannot be reliably set without incumbent technical knowledge. It should also be noted that not all combinations of parameters are settable. This can lead to poor or dangerous driving behavior, such as strong jerks in starting situations or tight rearing and immediately following deceleration. This can be ruled out from the outset by defining the parameter planes in the background. In this sense, in a further embodiment, a plurality of parameters for controlling the motor vehicle are respectively assigned to the operating strategy points, wherein the man-machine interface is configured to allow the user to select an operating strategy point lying within the polygon in such a way that parameters assigned to the selected operating strategy point are selected together when selecting the operating strategy point. The processor unit is configured to define, for the control of the motor vehicle, those parameters which are assigned to the selected operating strategy point.In one embodiment, an interaction interface, which otherwise consists of many individual parameter interfaces, is reduced to a substantial area. The actual parameters, the forwarding of which is not necessarily desired, are defined in the background according to the input of an application person or driver. Figuratively, the different parameters can be visualized in different planes that are not visibly arranged for the user below the polygon of the user interface. The possible parameters in the different planes are dependent on the selected model of the model predictive control and the selected categories which are located at the corners of the surface of the polygon. In this sense, it is provided according to the present invention that first parameters are stored in a first parameter plane (background plane) that is not visible to the user and is concealed by the polygon displayed by the user interface. Second parameters are furthermore stored in a second parameter plane (background plane) which is not visible to the user and is concealed by the polygon displayed by the user interface and by the first background plane, wherein the operating strategy points are each arranged perpendicularly above the first parameters and second parameters assigned to them.The user can move the cursor discretely to points of intersection of lines, for example, depending on his interaction request, in order to select a desired operating strategy point. In this sense, according to one embodiment, it is provided that a plurality of lines are arranged within the polygon, wherein the lines intersect at nodes which represent operating strategy points. The human-machine interface is configured to allow the user to select the operating strategy points represented by the nodes.Another option is to interpolate between the nearest parameter values once the cursor is in space between lines, for example. In this sense, according to a further embodiment, it is provided that the man-machine interface is configured to allow the user to select an operating strategy point lying between the nodes, wherein the processor unit is configured to define the parameters for controlling the motor vehicle by the processor unit interpolating between operating strategy points which are represented by those closest nodes which have the smallest distance from the selected operating strategy point.In a simple example, which covers nevertheless a particularly large number of different operating strategy points, a triangle is selected as a polygon, wherein a first corner of the triangle is assigned a sport operating strategy in its maximum form, a second corner of the triangle is assigned an efficient operating strategy in its maximum form, and a third corner of the triangle is assigned a comfortable operating strategy in its maximum form. The dimensionality of the characteristic map is not regulated, however, and can be adapted. For example, a quadrangle may be selected based on four categories, or generally a polygon corresponding to the number of categories.The system according to the invention can likewise be integrated into other automated driving function approaches which are not based on an MPC structure but rather on an AI such as, for example, a neural network. A prerequisite for this is the presence of a set of parameters. Alternatively or additionally to the above-described model-based predictive control, the motor vehicle can therefore be controlled by means of a cruise control system or by means of a cruise control system or by means of an AI-based control system (AI stands here for artificial intelligence), wherein the processor unit is configured to define a plurality of parameters of the cruise control system or of the AI-based control system on the basis of the selected operating strategy point for controlling the motor vehicle.A further application case consists in the simulation of the application of a motor vehicle manufacturer (original equipment manufacturer, abbreviated to: OEM). By further combinations of possible corner points, for example, an adaptive cruise control (ACC) would be settable. The application effort would thus be greatly simplified.The human-machine interface can be installed in a fixed manner in the motor vehicle or integrated into a mobile terminal which can be used by the user of the human-machine interface both inside the motor vehicle and outside the motor vehicle for parameterizing the motor vehicle operating strategy. Alternatively or additionally, the processor unit can either be fixedly installed in the motor vehicle or integrated into a mobile terminal which can be used by the user of the human-machine interface both inside the motor vehicle and outside the motor vehicle for parameterizing the motor vehicle operating strategy.Exemplary embodiments of the invention are explained in more detail below with reference to the schematic drawing, wherein identical or similar elements are provided with the same reference numerals. This shows FIG. 1 shows a schematic illustration of a vehicle having a parameter system, which in particular comprises a human-machine interface having a touchscreen, FIG. 2 shows a schematic view of the touchscreen with a user interface which outputs a polygon for selecting operating strategy points for a user, FIG. 3 shows details of the polygon according to FIG. 2 with parameter planes arranged behind the polygon, which are not visible to the user, FIG. 4 shows details of a first parameter plane, and FIG. 5 shows details of a second parameter plane.FIG. 1 shows a vehicle 1. in the exemplary embodiment shown, the vehicle 1 is a motor vehicle, for example a passenger car. In the exemplary embodiment shown, the vehicle 1 comprises an MPC system 2 for model-based predictive regulation of the motor vehicle 1. the motor vehicle 1 furthermore comprises a driver assistance system 16 having a processor unit 18 and having a communication interface 19.In the exemplary embodiment shown, the MPC system 2 comprises a processor unit 3, a memory unit 4, a communication interface 5 and a detection unit 6 for detecting the relevant environmental data and status data of the motor vehicle 1. the motor vehicle 1 furthermore comprises a drive train 7, which for example comprises an electric machine 8, which can be operated as a motor and as a generator, a battery 9 and a transmission 10. The electric machine 8 can drive wheels 28 of the motor vehicle 1 via the transmission 10 in the motor mode, which for example can have a constant transmission ratio. The electrical energy required for this purpose can be provided by the battery 9. The battery 9 can be charged by the electric machine 8 when the electric machine 8 is operated in the generator mode (recuperation). The battery 9 can optionally also be charged at an external charging station. The drive train of the motor vehicle 1 can likewise optionally have an internal combustion engine 17 which, alternatively or additionally to the electric machine 8, can drive the motor vehicle 1. The engine 17 may also drive the electric machine 8 to charge the battery 9.A computer program product 11 is stored on the storage unit 4. The computer program product 11 can be executed on the processor unit 3, for which purpose the processor unit 3 and the memory unit 4 are connected to one another by means of the communication interface 5. When the computer program product 11 is executed on the processor unit 3, it instructs the processor unit 3 to fulfil the functions described in connection with the drawing or to execute method steps.The computer program product 11 contains an MPC algorithm 13. the MPC algorithm 13 in turn contains a longitudinal dynamics model 14 of the motor vehicle 1. furthermore, the MPC algorithm 13 contains a cost function 15 to be minimized. the processor unit 3 executes the MPC algorithm 13 and in the process determines trajectories of the motor vehicle 1 on the basis of the longitudinal dynamics model 14, so that the cost function 15 is minimized.As the output of the optimization by the MPC algorithm 13, for example, an optimum rotational speed and an optimum torque of the electric machine 8 for discretized points in the preview horizon of the model-based predictive control can result. For this purpose, the processor unit 3 can determine an input variable for the electric machine 8, so that the optimum rotational speed and the optimum torque are established. The processor unit 3 can control the electric machine 8 on the basis of the determined input variable. Alternatively, however, this can also be effected, for example, by the driver assistance system 16.The detection unit 6 can measure current state variables of the first motor vehicle 1, record corresponding data and supply them to the MPC algorithm 13. Furthermore, route data from an electronic map for a forecast horizon or prediction horizon (e.g. 400 m) in front of the motor vehicle 1 can be updated or updated in particular cyclically. The route data may include, for example, slope information, curve information, and speed limit information. Furthermore, for example, a curve curvature can be incorporated into the model-based predictive control. In addition, the first motor vehicle 1 can be located by means of the detection unit 6, in particular by means of a signal generated by a GNSS sensor 12 for precise localization on the electronic map. The processor unit 3 can access information of the mentioned elements, for example via the communication interface 5. This information can be incorporated, for example, into the longitudinal dynamics model 14 of the motor vehicle 1, in particular as input values, restrictions or secondary conditions.The motor vehicle 1 further comprises a parameter system 20 for parameterizing an operating strategy of the motor vehicle 1. the parameter system 20 comprises in particular a human-machine interface 21 and a processor unit 22. Alternatively, two or three of these processor units 3, 18, 22 can also be combined in one or two processor units in order to save components.In the exemplary embodiment shown, the human-machine interface 21 has a touchscreen 23, which is arranged together with the rest of the human-machine interface 21 within the motor vehicle 1, so that a user, not shown, or driver of the motor vehicle 1 can select an operating strategy point of the motor vehicle 1 via the touchscreen 23, which is explained in more detail below. The parameter system 20 forms an interface architecture for parameterizing the MPC system 2 of the motor vehicle 1. a multidimensional characteristic diagram is incorporated in the human-machine interface 21, said multidimensional characteristic diagram being represented by FIGS. 2 to 5 in the form of a polygon, a triangle 24 in the exemplary embodiment shown. categories or operating strategies for the motor vehicle 1 are plotted at the corners of the characteristic diagram / triangle 24, "comfort", "eco" and "sport" in the exemplary embodiment shown. In particular, by moving a cursor 25, the user or driver of the motor vehicle 1 can set the preference for a desired system behavior. Behind the cursor 25 is a data record of the parameterization, whereby the parameterization of the model-based predictive control is varied. According to the number of categories, the number of vertices varies. The interface architecture 20 enables a great simplification of the parameterization and individualization of complex software systems, in particular in the case of an MPC algorithm 13 in the vehicle application.The human-machine interface 21 outputs a user interface 26 visible to the user of the human-machine interface 21. The polygon is represented by the user interface 26 in the form of the triangle 24. A sports operating strategy "sport" is assigned to a first corner 27 of the triangle 24 in its maximum form. An efficient operating strategy "Eco" is assigned to a second corner 28 of the triangle 24 in its maximum form. A third corner 29 of the triangle 24 is assigned a comfortable operating strategy "comfort" in its maximum form. The sport operating strategy "sport" is maximally pronounced in the first corner 27, the efficient operating strategy "eco" in the second corner 28, and the comfortable operating strategy "comfort" in the third corner 29.FIG. 3 shows that multiple operating strategy points are arranged within triangle 24. By way of example, four operating strategy points 30, 31, 32 and 34 in FIG. 3 are provided with a reference sign. The operating strategy points 30, 31, 32 and 34 are each assigned an operating strategy which corresponds to a mixed form of the different operating strategies "sport", "eco" and "comfort". By means of the touchscreen 23 of the human-machine interface 21, the user can select one of the operating strategy points 30, 31, 32 and 34 lying within the triangle. The processor unit 22 determines a plurality of parameters for controlling the motor vehicle 1 based on the selected operating strategy point 30 or 31 or 32 or 34, which is discussed in more detail further below.The user can move the cursor 25 on the touch screen 23 discretely on nodes of intersecting lines 33 depending on his interaction request in order to select a desired operating strategy point. One of these lines is exemplarily provided with a reference sign 33 in FIG. 3. Three of the exemplary operating strategy points 30, 31, 32 are arranged at nodes, i.e. where two of the lines 33 intersect. In the embodiment shown by FIG. 3, the lines are parallel to the sides of triangle 24, but this is not mandatory. Another option is to interpolate between the nearest parameter values once the cursor 25 is in space between lines 33, for example. Thus, the user can select an operating strategy point 34 lying between the nodes 30, 31, 32 on the touchscreen 23. The processor unit 22 determines the parameters for controlling the motor vehicle 1 in that the processor unit 22 interpolates between the operating strategy points 30, 32 which have the smallest distance from the selected operating strategy point 34 and are located on the nodes 30, 32.The operating strategy approaches the maximum expression of the respective operating strategy sport, eco or comfort as the distance between the operating strategy points 30, 31, 32, 34 decreases. The closer the user moves the cursor 25 within the user area 26 in the direction of one of the corners 27, 28, 29 of the triangle 24, the more pronounced is the characteristic of the respective operating strategy sport, eco or comfort. If the user moves the cursor 25 within the triangle 24 in the direction of the lower left corner 27, for example, then he thus increases the sporting character of the operating strategy.The processor unit 22 determines a plurality of parameters of the model-based predictive control for controlling the motor vehicle 1 on the basis of the selected operating strategy point 30, 31, 32 or 34. A first parameter can be, for example, a maximum permissible transverse acceleration of the motor vehicle 1. A second parameter can be, for example, an energy value which must be provided, for example, by the battery 9 of the motor vehicle 1 in order to move the motor vehicle 1 along a selected optimized trajectory within a prediction horizon of the model-based predictive control.The processor unit 22 can adjust the cost function 15 and / or a secondary condition of the MPC algorithm 13 as a function of the defined parameters. For example, the motor vehicle 1 can travel along a trajectory that has been optimized and selected by executing the MPC algorithm 13 by means of the processor unit 3. The cost function 15 of the MPC algorithm 13 can contain an energy term which describes the energy required to be provided in order for the motor vehicle 1 to be able to follow the trajectory within the prediction horizon. The trajectory can be, for example, a speed trajectory according to which waypoints and / or points in time which lie within the prediction horizon are assigned speed values of the motor vehicle 1. If, for example, a more environmentally friendly trajectory corresponding to the category or operating strategy "Eco" is now to be generated, the required energy can be defined as a parameter on the basis of the operating strategy point 31 shown at the furthest top in FIG. 3 by the relevance of the energy term of the cost function 15 being increased.If, alternatively or additionally, for one of the parameters, for example, the maximum permissible transverse acceleration that the motor vehicle 1 may have within the planned trajectory is selected, then it would be advantageous from the standpoint of comfort to reduce the transverse acceleration. Thus, a selection of the operating strategy point 30 arranged furthest to the left in FIG. 3 would be expedient. The transverse acceleration in turn could in this case be, in particular, a parameterizable boundary condition. It would likewise be conceivable to include this parameter in the configuration, so that the parameter in the cost function 15 influences the solution as a factor. For example, the described transverse acceleration could also be included in a term of the cost function 15, but does not have to be included.By moving cursor 25 within triangle 24, the driver may set the preference of the desired system behavior. Behind the cursor 25 is a data record of the parameterization, as a result of which the parameterization of the model-based predictive control can be varied. In the application of model-based predictive control, many parameters are to be set which cannot be reliably set without incumbent technical knowledge. It should also be noted that not all combinations of parameters are settable. This can lead to poor or dangerous driving behavior, such as strong jerks in starting situations or tight rearing and immediately following deceleration.By defining the parameter planes 35, 36 shown in FIGS. 3 to 5 in the background, this can be ruled out from the outset. For example, a first parameter 35.1 (value "1.5", FIG. 4 ) of a first parameter level 35 and a second parameter 36.1 (value "1", FIG. 5 ) of a second parameter level 36 are assigned to the operating strategy point 30. The operating strategy point 30 is shown on the leftmost side in FIG. 3 and lies on the node point formed by the intersection of the lowermost horizontal line 33.1 and the leftmost line 33.2. FIGS. 2 and 3 show that the user interface, which otherwise typically consists of many individual parameter interfaces, is reduced to an essential area, namely to the triangle 24 described above. The actual parameters, for example the two parameters 35.1 and 36.1, the transfer of which is not necessarily desired, are defined in the background in the two parameter planes 35, 36 according to the input of a user.The different parameters 35.1, 36.1 are thus arranged in different parameter planes 35, 36, which are not arranged visually for the user below the triangle 24 of the user interface 26. The first parameters can be, for example, the maximum transverse acceleration that can be realized on the solution trajectory, whereas the second parameters can describe, purely by way of example, the permitted electrical energy to be drawn from the battery 9.The operating strategy points 30, 31, 32, 34 within the triangle 24 are each assigned a first parameter and a second parameter for the control of the motor vehicle. The user can select an operating strategy point lying within the triangle 24, for example the operating point 30 shown on the leftmost side in FIG. 3, by means of the touchscreen 23 by moving the cursor 25. The processor unit 22 determines for the control of the motor vehicle 1 those parameters 35.1, 36.1 which are assigned to the selected operating strategy point 30. For example, the first parameter 35.1 (transverse acceleration) can be stored in the first parameter plane 35 that is not visible to the user and is concealed by the triangle 24 displayed by the user interface 26. The second parameter 36.1 (electrical energy) can furthermore be stored in the second parameter plane 36, which is not visible to the user and is concealed by the triangle displayed by the user interface 26 and by the first parameter plane 35. Conclusions can be drawn between the two parameters 35.1 and 36.1. The operating strategy point 30 is arranged here vertically above the first parameter 35.1 and vertically above the second parameter 36.1. For this purpose, the two parameter planes 35, 36 can also have lines 37, 38 which each run identically to the lines 33 within the triangle 24 of the user interface 26.As an alternative to the model-based predictive control shown, the motor vehicle can also be controlled by means of a cruise control system or an AI-based control system, wherein the processor unit is then configured to define a plurality of parameters of the cruise control system or of the AI-based control system on the basis of the selected operating strategy point 30 for controlling the motor vehicle 1.Reference numerals denote reference numeralsComfort-comfort operating strategy Eco Efficient / economic operating strategy Sport operating strategy 1 Vehicle 2 MPC system 3 Processor unit 4 Memory unit 5 Communication interface 6 Detection unit 7 Drive train 8 Electric machine 9 Battery 10 Transmission 11 Computer program product 12 GNSS sensor 13 MPC algorithm 14 Longitudinal dynamics model 15 Cost function 16 Driver assistance system 17 Internal combustion engine 18 Processor unit of the driver assistance system 19 Communication interface of the driver assistance system 20 System for parameterizing an operating strategy 21 Human machine interface 22 Processor unit 23 Touchscreen 24 Characteristic map (polygon) 25 Cursor 26 User interface 27 First corner 28 Second corner 29 Third corner 30 Operating strategy point 31 Operating strategy point 32 Operating strategy point 33 Line within the polygon 33.1 Horizontal line 33.2 Left line 34 Operating strategy point 35 Level of first parameter 36 Level of second parameter 37 Line within the first parameter level 38 Line within the second parameter level

Claims

System (20) for parameterizing a motor vehicle operating strategy, the system (20) comprising - a human-machine interface (21) and - a processor unit (22), wherein - the human-machine interface (21) is configured to output a user interface (26) visible to a user of the human-machine interface (21), - a polygon (24) is represented by the user interface (26), the corners (27, 28, 29) of which polygon in each case a category of an operating strategy (sport, eco, comfort) for a motor vehicle (1) is assigned, wherein the operating strategies (sport, eco, comfort) are in each case maximally defined in the corners (27, 28, 29), - a plurality of operating strategy points (30, 31, 32, 34) are arranged within the polygon (24), wherein the operating strategy points (30, 31, 32, 34) are arranged within the polygon (24), 34), each operating strategy corresponding to a mixed form of the different operating strategies (sport, eco, comfort), - the man-machine interface (21) is configured to allow the user to select at least one operating strategy point (30) lying within the polygon (24), - the processor unit (22) is configured to define a plurality of parameters (35.1, 36.1) for controlling the motor vehicle (1) based on a selected operating strategy point (30), - first parameters (35.1) are stored in a first parameter plane (35) not visible to the user, which is concealed by the polygon (24) displayed by the user interface (26), - second parameters (36.1) are stored in a second parameter plane (36) not visible to the user, which is concealed by the polygon (24) displayed by the user interface (26) and by the first parameter plane (25), and - the operating strategy points (30) are each arranged vertically above the first parameters (35.1) and second parameters (36.1) assigned to them.The system (20) according to claim 1, wherein - the motor vehicle (1) is controlled by means of a model-based predictive control, and - the processor unit (22) is configured to define a plurality of parameters (35.1, 36.1) of the model-based predictive control for controlling the motor vehicle (1) based on the selected operating strategy point (30).The system (20) according to claim 2, wherein the processor unit (22) is configured to adapt - a cost function (15) and / or - a constraint of the model-based predictive control depending on the defined parameters (35.1, 36.1).The system (20) according to any one of the preceding claims, wherein the operating strategy approaches the maximum characteristic of the respective operating strategy as the distance of the operating strategy points (30, 31, 32, 34) from one of the corners (27, 28, 29) decreases.The system (20) according to any one of the preceding claims, wherein - a plurality of parameters (35.1, 36.1) for controlling the motor vehicle (1) are respectively assigned to the operating strategy points (30), - the human-machine interface (21) is configured to allow the user to select an operating strategy point (30) lying within the polygon (24) in such a way that parameters (35.1, 36.1) assigned to the selected operating strategy point (30) are jointly selected when selecting the operating strategy point (30), and - the processor unit (22) is configured to determine those parameters (35.1, 36.1) assigned to the selected operating strategy point (30) for controlling the motor vehicle (1).The system (20) according to any of the preceding claims, wherein - a plurality of lines (33, 33.1, 33.2) are arranged within the polygon (24), - the lines (33, 33.1, 33.2) intersect at nodes (30, 31, 32), - the nodes (30, 31, 32) represent the operating strategy points, and - the man-machine interface (21) is configured to allow the user to select the operating strategy points represented by the nodes (30, 31, 32).The system (20) according to claim 6, wherein - the man-machine interface (21) is configured to allow the user to select an operating strategy point (34) located between the nodes (30, 31, 32), and - the processor unit (22) is configured to set the parameters for controlling the motor vehicle (1) by the processor unit (22) interpolating between operating strategy points represented by those closest nodes (30, 32) that have the smallest distance from the selected operating strategy point (34).The system (20) according to any one of the preceding claims, wherein - the polygon is a triangle (24), - a first corner (27) of the triangle (24) is assigned a sport operating strategy (sport) in its maximum expression, - a second corner (28) of the triangle (24) is assigned an efficient operating strategy (Eco) in its maximum expression, and - a third corner (29) of the triangle (24) is assigned a comfortable operating strategy (comfort) in its maximum expression.The system (20) according to any one of the preceding claims, wherein - the motor vehicle (1) is controlled by means of a cruise control system or an AI-based control system, - the processor unit (22) is configured to define a plurality of parameters of the cruise control system or of the AI-based control system based on the selected operating strategy point (30) for controlling the motor vehicle (1).

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