Agricultural work machine with driver assistance system

Abstract

The invention relates to an agricultural machine (1) comprising a driver assistance system (45) which is designed and configured to automatically monitor and adjust working parameters (44, 50a..i) and quality parameters (49, 49a) of the agricultural machine (1), wherein a process model (47) comprising characteristic curve fields (48) is assigned to the driver assistance system (45) and the optimization method (65) implemented by the driver assistance system (45) is designed as a characteristic curve control (69) and the optimization method (65) generates optimized working parameters (44, 50a..i) as a control variable (51) and the driver assistance system (45) adjusts the working parameters (44, 50a..i) depending on the optimized working parameters (44, 50a..i).i) the quality parameters (49,49a) of the agricultural machinery (1) are determined, wherein the process model (47) is designed as a dynamic nonlinear process model (59) in such a way that the dynamic nonlinear process model (59) comprises a static process model component (60) and a dynamic process model component (61), wherein at least the manipulated variables (51) in the static process model component (60) undergo an optimization step (52) and in the dynamic process model component (61) undergo a control loop structure (62).

Description

[0001] The invention relates to an agricultural work machine comprising a driver assistance system according to the preamble of claim 1.

[0002] Driver assistance systems that optimize the operation of agricultural machinery, particularly harvesters, and thereby largely relieve the operator of monitoring and adjustment tasks, are already comprehensively described in the prior art. DE 10 2010 017 687 A1 discloses a driver assistance system that determines optimized setting parameters for the working components of an agricultural harvester using a map-based approach. The method disclosed here approximates optimized working parameters in an iterative process. Such systems are well suited for quickly determining optimized working parameters of the harvester under more or less homogeneous harvesting conditions.In rapidly changing harvesting conditions, such methods have the disadvantage that, due to the inertia of the optimization process, a certain settling-in process must be completed until the harvesting machine is operating at an optimized point again.

[0003] Prior art has already recognized that the quality of the used map has a significant influence on the respective optimization result. For example, EP 2 687 922 A2 proposed selectively targeting specific operating points of the map located outside the current operating range in order to keep the map updated across a large portion of the overall map. This has the particular effect of adjusting the mathematical relationships governing the map in such a way as to accelerate the determination of optimized operating parameters. However, a disadvantage of such methods is the additional effort required for the targeted control of operating points outside the current operating range.

[0004] To enable a map used for optimizing the operating parameters of an agricultural machine, particularly a combine harvester, to quickly determine optimized operating parameters, it is also known from the prior art according to EP 4 154 699 A1 to assign a so-called control curve to a map. This control curve summarizes the optimal operating points over a large area of ​​the map, and the assistance system controls the parameter optimization process along this optimal curve. This has the particular advantage that the optimal operating points are reached more quickly using this map-based optimization. The disadvantage remains that there is some inertia in the system's response to abrupt changes in harvesting conditions, as the optimization system must first steer towards the new optimal operating point aligned with the control curve.

[0005] It is therefore an object of the invention to avoid the described disadvantages of the prior art and in particular to create a driver assistance system that adapts quickly to the real harvesting conditions and in particular reacts quickly to abrupt changes in the harvesting conditions.

[0006] This problem is solved according to the invention by an agricultural machine having the characterizing features of claim 1.

[0007] By incorporating a driver assistance system into the agricultural machinery, which is designed and configured to automatically monitor and adjust the working and quality parameters of the agricultural machinery, wherein a process model comprising characteristic curve fields is assigned to the driver assistance system, such that the optimization procedure implemented by the driver assistance system is designed as a characteristic curve control, and the optimization procedure generates optimized working parameters as a manipulated variable, and the driver assistance system determines the quality parameters of the agricultural machinery as a function of the optimized working parameters, and the process model is designed as a dynamic nonlinear process model in such a way that the dynamic nonlinear process model comprises a static process model component and a dynamic process model component,where at least the control variables in the static process model component undergo an optimization step and in the dynamic process model component a control loop structure, it is ensured that the driver assistance system can quickly adapt the optimization of the working parameters to changing process conditions and abruptly changing harvesting conditions.

[0008] In an advantageous embodiment of the invention, the characteristic map control defined by the process model is configured and configured to specify the operating parameters of the agricultural machinery and limit values ​​for the control loop structure. A self-adjusting controller is assigned to the control loop structure, and this self-adjusting controller is provided and configured to monitor the quality parameters of the process. This has the particular effect of ensuring that the agricultural machinery is always operated at an optimal operating point.

[0009] In a further advantageous embodiment of the invention, the optimization step and the control loop structure form an optimization method which is provided and configured to operate the process model in a model adaptation step in such a way that the dynamic nonlinear process model component is provided and configured to determine the stationary model component of the process from the monitoring of the quality parameters and using a parameter estimation method, wherein the one or more manipulated variables comprising the optimized working parameters and the one or more quality parameters dependent on the respective manipulated variable form input variables of the optimization method.This has the particular effect of limiting process optimization to the essential parameters, so that the required computing power can be reduced to a level that allows the application of the optimization method in an ongoing harvesting operation.

[0010] In an advantageous embodiment of the invention, by determining optimized control variables from the control variables derived from the process model and specified quality parameters in the optimization step, it is first ensured that the working parameters describing the real process are adequately taken into account in the entire optimization process.

[0011] Several effects are achieved by defining the control loop structure encompassing the self-adjusting controller, using as input variables the manipulated variables optimized in the optimization step, the predefined quality parameters, and the quality parameters determined as a function of the optimized manipulated variables, and by further designing and configuring the self-adjusting controller to derive optimized manipulated variables from a comparison of the predefined quality parameters with the determined quality parameters and to transfer these to the process and the model adaptation step of the dynamic model adaptation. On the one hand, it becomes easy to detect when abrupt changes in harvesting conditions have occurred, which the usual map-based control cannot adequately respond to.Furthermore, it is ensured that the optimized parameters determined by the control loop structure are also fed into the stored process model, so that it is gradually adapted to describe the changed conditions of the process with sufficient accuracy.

[0012] In this context, it is advantageous if the determined quality parameter is also passed as an input to the model adaptation step, so that the changed process conditions can be taken into account with sufficient accuracy during the model adaptation.

[0013] The driver assistance system can optimize the operation of the agricultural machine quickly enough if the driver assistance system is set up in an advantageous further training to automatically adjust the optimized control variables on the working elements of the agricultural machine.

[0014] In an advantageous embodiment of the invention, a rapid improvement in the operation of the agricultural machinery under abruptly changing harvesting conditions is achieved by providing and configuring the control loop structure to effect a dynamic adjustment of the process before the stored process model has been updated.

[0015] A particularly efficient optimization of the working method of the agricultural machine results in a further advantageous design when the nonlinear dynamic process model describes the relationship between the working parameters of a working element and the quality parameters.

[0016] In an advantageous embodiment of the invention, a mathematically simple verification of the quality parameter describing the current operation of the agricultural machine is achieved by structuring the limit values ​​assigned to the quality parameters in such a way that it is determined in one test step whether the achieved quality parameter is still within the limit value defined for the quality parameter or not, wherein the control loop structure is activated if the limit value is exceeded and the activation of the control loop structure is then omitted or terminated if the limit value is not or no longer exceeded.

[0017] In a further advantageous embodiment, the control loop structure remains activated until the optimized operating parameters derived from the nonlinear dynamic model meet the process quality criteria. This ensures that the agricultural machinery's operation, in accordance with the selected harvesting strategy, is maintained even while the process model is being adapted to the actual process conditions.

[0018] In an advantageous embodiment of the invention, a particularly efficient process model-based control of the operation of an agricultural machine is achieved when the working elements of the agricultural machine are combined into process unit automation units, and one or more working elements together with the driver assistance system form a process unit automation unit, wherein process models describing the respective process unit automation unit are stored in a storage unit assigned to the driver assistance system, and the computing unit is provided and configured to operate the process unit automation unit using the stored process models, and the process unit automation unit is configured to optimize the working parameters of the working element(s) and to specify the optimized working parameters to the respective working element.In this context, it is advantageous if the agricultural machine is designed as a combine harvester and the process unit is designed at least as a threshing machine and / or as a separating machine and / or as a cleaning machine, and each of these process unit machines is assigned a process model.

[0019] To optimize computing power and shorten optimization time, a further advantageous embodiment provides that at least the threshing machine and the separating machine are assigned a common process model, preferably the threshing machine, the separating machine, and the cleaning machine. This has the particular effect of significantly reducing the required computing power by decreasing the number of characteristic-map-based models to be used.

[0020] In a further advantageous embodiment of the invention, the dynamic nonlinear process model, preferably the dynamic process model component, is designed as a self-learning process model, and the parameter estimation method is preferably based on a so-called LMN-FIR model (Local Model Networks with Local Finite Impulse Response Models). These models have already proven their worth and can be readily integrated into optimization routines; in particular, they are well adaptable to crop conditions and different types of agricultural machinery in an agricultural context.

[0021] The complex processes occurring in an agricultural machine designed as a combine harvester can be represented particularly efficiently using a process model and translated into a correspondingly efficient optimization of the combine harvester's operation if, in an advantageous embodiment of the invention, the optimization method is integrated into the driver assistance system assigned to the agricultural machine, wherein the respective process model is stored in a storage unit of the driver assistance system assigned to the control unit that houses the computing unit, such that the computing unit is provided and configured to operate the optimization method using the stored process model, and the driver assistance system is further configured a.) to determine the working parameters and associated control variables using suitable sensor systems and to transfer them to the optimization process b.) the optimization procedure adapts the nonlinear dynamic process model in a model adaptation step and then derives the static process model component. c.) The optimized working parameters are then determined using the derived static process model component and the quality parameters that can be specified by the operator of the agricultural machinery. d.) The determined optimized working parameters are passed to the control loop structure, and optimized working parameters are determined based on the passed working parameters and the passed quality parameters. e.) The optimized working parameters are then set on the working elements of the agricultural machinery and the resulting quality criteria of process P are determined. f.) The determined quality parameters are then compared with the predefined quality parameters in a test step depending on a limit value, whereby if the limit value is exceeded the control loop structure is activated and the activation of the control loop structure is then omitted or terminated if the limit value is not or no longer exceeded. g.) and, with the control loop structure activated, the operating parameters determined by the control loop structure are specified to the respective working element.

[0022] Further advantageous embodiments are the subject of further dependent claims and are described below with reference to exemplary embodiments illustrated in several figures. These show: Fig. 1 A schematic view of the agricultural machine with driver assistance system according to the invention Fig. 2 Details of a process model-based optimization of working parameters of agricultural machinery known from the state of the art Fig. 3 Details of the process model-based optimization of working parameters of the agricultural machinery according to the invention Fig. 4 a embodiment variant of the process model-based optimization of working parameters of the agricultural machinery according to the invention Fig. 3.

[0023] The in Fig. Figure 1, schematically depicted as a combine harvester 2, incorporates a grain header 3 in its front section, which is connected to the inclined conveyor 4 of the combine harvester 2 in a manner known per se. The crop flow 5 passing through the inclined conveyor 4 is transferred in the upper, rear section of the inclined conveyor 4 to the threshing elements 7 of the combine harvester 2, which are at least partially enclosed at the bottom by a so-called threshing concave 6. A deflecting drum 8 downstream of the threshing elements 7 redirects the crop flow 5 exiting them in the rear section so that it is transferred directly to a separating device 10 designed as a separator rotor assembly 9. It is within the scope of the invention that the separating device 10 can also be designed as a straw walker, which is known per se and therefore not shown.It is also within the scope of the invention that the separating device can be designed with one or two rotors, or that the threshing elements 7 and the separating device 10 are combined into a single- or double-rotor axial flow threshing and separating device. In the separating device 10, the crop flow 5 is conveyed in such a way that freely moving grains 11 contained in the crop flow 5 are separated in the lower region of the separating device 10. Both the grains 11 separated at the threshing concave 6 and in the separating device 10 are fed via the return floor 12 and feed floor 13 to a cleaning device 17 consisting of several sieve levels 14, 15 and a blower 16. The cleaned grain flow 18 is finally transferred to a grain tank 20 by means of elevators 19.

[0024] In the rear section of the separating device 10, a shredding device 23, designed as a straw chopper 22 and enclosed in a funnel-shaped housing 21, is assigned to it in the illustrated embodiment. The straw 24 exiting the separating device 10 in the rear section is fed to the straw chopper 22 from above. (Not shown) the straw 24 can also be redirected after the separating device 10 so that it is deposited directly onto the ground 25 in a swath. At the outlet of the straw chopper 22, the material stream consisting of the shredded straw 24 and the non-grain components separated in the cleaning device 17 is transferred to a material distribution device 26, which discharges the residual material stream 27 in such a way that it is spread across the ground 25.In the embodiment shown here, the residual material stream 28 separated in the cleaning unit 17 is discharged into the straw chopper 22 by means of a so-called chaff spreader 29 and ultimately conveyed from the combine harvester 12 as a common residual material stream 27 by means of the crop distribution unit 26. In the following, the grain cutter 3, the inclined conveyor 4, the threshing units 7 and the associated threshing concave 6, the separating unit 10, the cleaning unit 17, the elevators 18, the grain tank 20, the straw chopper 22, the crop distribution unit 26, and the chaff spreader 29 are referred to as working elements 30 of the agricultural machine 1.

[0025] Furthermore, the agricultural machine 1 has a vehicle cab 31 in which at least one control and regulating device 33, equipped with a display unit 32, is arranged. This device allows a multitude of processes P, which will be described in more detail later, to be controlled automatically or initiated by the operator 34 of the agricultural machine 1. The control and regulating device 33 communicates with a multitude of sensor systems 36 via a so-called bus system 35 in a manner known per se. Details regarding the structure of the sensor systems 36 are described in detail in DE 101 47 733, the contents of which are hereby incorporated in their entirety into the disclosure of this patent application. Therefore, the structure of the sensor systems 26 will not be described again below.

[0026] Furthermore, it shows Fig. Figure 1 shows a schematic representation of the display unit 32 of the control and regulating device 33 and the computing unit 37 associated with and coupled to the display unit 32. The computing unit 37 is designed to process, in addition to the information 38 generated by the sensor systems 36, external information 39 and information 40 stored in the computing unit 37 itself, such as expert knowledge, into a variety of output signals 41. The output signals 41 are designed to include at least display control signals 42 and working element control signals 43, the former determining the contents of the display unit 32 and the latter causing changes to the various working parameters 44 of the working elements 30 of the agricultural machine 1, with arrow 44 symbolically representing the threshing drum speed.The control and regulating device 33 with its associated display unit 32 and computing unit 37 are part of the driver assistance system 45 according to the invention, which will be described in more detail below.

[0027] According to the invention, a process optimization module 46 is assigned to the driver assistance system 45, wherein the process optimization module 46 is preferably part of the computing unit 37. One or more process models 47 are assigned to the process optimization module 46, which describe the processes P taking place in the agricultural machine 1, which will be described in more detail below. The single or multiple process models 47 are described by characteristic curve fields 48, wherein the relationship between quality parameters 49 and operating parameters 50a..i of the agricultural machine 1 is defined in each characteristic curve field 48.

[0028] The processes P described by the respective process model 47 can be, for example, the threshing process, the separation process, or the cleaning process of the harvested crop 5, to name just a few examples. The quality parameters can be, for example, the quality parameters "threshing loss," "broken grain percentage," "separation loss," "cleaning loss," "threshing load," and "fuel consumption," which are known per se and therefore not described in detail here. The operating parameters 50a..i of the agricultural machinery include, on the one hand, parameters related to the crop flow 5, such as the crop throughput, the layer height of the crop flow 5 detected in the agricultural machinery, and / or the moisture content of the crop flow 5. On the other hand, the operating parameters 50a..i parameters relating to the working elements 30 of the agricultural machine, such as the aforementioned threshing drum speed 44 and / or the speed of the blower 16 associated with the cleaning device 17, to name just two examples. This in . Fig. 1 The example shown for a characteristic map 48 describing a process model 47 could, for example, describe the quality parameter 49 “separation loss” as a function of the working parameters threshing drum speed 44, 50a and the layer height 50i related to the crop flow 5.

[0029] With such a structure of an agricultural machine 1 designed as a combine harvester 2, comprising the described driver assistance system 45, which is designed and configured to automatically monitor and adjust the working parameters 44, 50a..i and the quality parameters 49 of the combine harvester 2, a driver assistance system 45 is created that supports the operator 34 of the combine harvester 2 in operating the combine harvester 2. This is made possible because a process model 47 comprising characteristic curve fields 48 is assigned to the driver assistance system 45, and the process model 47 defines the respective quality parameter 49 as a function of control variables 51, here the working parameters 50a..i, and the driver assistance system 50 is configured, in a manner to be described in more detail, to determine optimized working parameters 50a..i of the agricultural machine 1 as a function of the respective process model 47.

[0030] To better understand the invention, in Fig. 2. First, general aspects of the driver assistance system 45, known from the prior art, are described in detail. In an optimization step 52, the driver assistance system 45 optimizes the working parameters 44, 50a..i of the agricultural machine 1, designed as a combine harvester 2. The optimization of the working parameters 44, 55a..i depends on a preselected harvesting process strategy 53 that determines the optimization step 52. The harvesting process strategy 53 is generally specified by the operator 34 and, in the simplest case, defines the quality parameters 49 to be achieved, such as maximum permissible grain losses or a certain grain purity 11, to name just two examples of quality criteria 49. The optimized working parameters 44, 55a..i determined in the optimization step 52...The parameters are then transferred to process P and automatically set at the respective working elements 30 of the combine harvester 2, for example, an optimized rotational speed 44 of a threshing drum assigned to the threshing elements 7. The driver assistance system 45 then determines the quality criteria 49a resulting from an adjustment of the working parameters 44, 55a..i.

[0031] Both the optimized operating parameters 44, 50a..i and the determined quality parameters 49a are transmitted to the process optimization module 46 in a model adaptation step 54. Depending on the transmitted parameters 44, 50a..i, 49a, the process model 47 is adapted in a known manner if the stored process model 47 no longer adequately describes the actual process P. The model adaptation step 54, known from the prior art, is designed as a so-called stationary model adaptation 55. In a data preprocessing step 56, quasi-stationary states are first determined for the manipulated variables 51 and the determined quality parameters 49a. The values ​​corresponding to the quasi-stationary state for the manipulated variables 51 and the determined quality parameters 49a are then transferred to the process optimization module 46 for adaptation of the process model 47.This tracking of the process model 47 to the actual process P, known from the prior art, is referred to below as inert model adaptation 55, since a certain settling time is always required until the stored process model 47 is adapted to the actual process P. If conditions describing process P change abruptly and / or only briefly, such as the crop throughput or the moisture content of the crop stream 5, this control structure suffers from the disadvantage that it cannot react sufficiently well to the changing conditions of process P, which ultimately leads to the quality criteria 49 specified by the selected harvesting process strategy 53 not being adequately met. This is where the invention comes in.

[0032] Fig. Figure 3 now shows details of the driver assistance system 45 according to the invention with the process optimization module 46 associated with it, in which the process model 47 and the characteristic curve fields 48 associated with the process model 47 are stored, wherein the process model 47 describes the relationship between working parameters 50a..i of a working element 30, the control variables 51, and the quality parameters 49, so that the optimization procedure (65) to be implemented by the driver assistance system (45) and which will be explained in more detail below is designed as a characteristic map control (69).

[0033] The process model 47 is assigned a model adaptation step 57, which, according to the invention and to be explained in more detail below, is designed as a dynamic model adaptation 58, such that the underlying process model 47 is designed according to the invention as a nonlinear dynamic process model 59, wherein the nonlinear dynamic process model 59 is composed of a static process model component 60 and a dynamic process model component 61. Analogous to the underlying process model 47, the nonlinear dynamic process model 59 also represents the relationship between the operating parameters 50a..i of a working element 30, the manipulated variables 51, and the quality parameters 49.

[0034] The characteristic map control 69 is set up and configured to specify the working parameters 44, 50a..i of the agricultural machinery 1 and limit values ​​66 to be described in more detail for the control loop structure 62, wherein a self-adjusting controller 63 is assigned to the control loop structure 62 and the self-adjusting controller 63 is provided and configured to monitor the quality parameters 49, 49a of the process.

[0035] In the static process model component 60, optimized control variables 51', the working parameters 44, 50a..i, are first determined in an optimization step 52 from the quality criteria 49 assigned to the selected harvesting process strategy 53 and the control variables 51 derived from the process model 47.

[0036] The dynamic process model component 61 comprises a control loop structure 62, including a self-adjusting controller 63. Input variables E of the self-adjusting controller 63 are initially the optimized manipulated variables 51', the optimized operating parameters 44, 50a..i, and the quality parameters 49 defined in the selected harvesting process strategy 53. Furthermore, the quality parameters 49a achieved in process P by applying the optimized operating parameters 44, 50a..i also constitute input variables E of the self-adjusting controller 63. Additionally, the manipulated variables 51 determined in the model adaptation step 57 are passed to the self-adjusting controller 63 as further input variables E. In the self-adjusting controller 63, the defined quality parameters 49 are compared with the achieved quality parameters 49a.If the defined quality parameter 49 and the respective achieved quality parameter 49a deviate from each other, dynamically adjusted working parameters 64a..i are generated, taking into account the respective stored process model 47, and automatically set at the respective working elements 30 in the agricultural machine 1, designed as a combine harvester 2, which describes the process P. At the same time, these dynamically adjusted working parameters 64a..i are also passed to the model adaptation step 57.

[0037] By designing the process model 47 as a dynamic nonlinear process model 59 in such a way that the dynamic nonlinear process model 59 comprises a static process model component 60 and a dynamic process model component 61, wherein at least the manipulated variables 51 undergo an optimization step 52 in the static process model component 60 and a control loop structure 62 in the dynamic process model component 61, it is ensured that the driver assistance system 45, and here specifically the optimization of the working parameters 50a..i, adapts quickly to the real harvesting conditions, the process P, and in particular reacts quickly to abrupt changes in the harvesting conditions.In this way, the optimization step 52 and the control loop structure 62 form an optimization procedure 65, which is designed and set up to adapt the process model 47, 59 in a model adaptation step 57 in such a way that the dynamic nonlinear process model component 61 is provided and set up to determine the stationary process model component (60) of the process (P) from the monitoring of the quality parameters 49, 49a and using a parameter estimation procedure 70, wherein the one or more manipulated variables 51 and the one or more quality parameters 49a dependent on the respective manipulated variable 51 form the input variables of the optimization procedure 65 in the model adaptation step 57.

[0038] The nonlinear dynamic process model 59, preferably the dynamic process model component 61, can in a preferred embodiment be designed as a self-learning process model and the parameter estimation method 70 can preferably be formed by an LMN-FIR model (Local Model Networks with local Finite Impulse Response Models).

[0039] The described control loop structure 62 is designed to dynamically adapt process P until the stored process model 47, 59 has been updated to match process P. This updating of the stored process model 47, 59 is achieved by passing the dynamic operating parameters 64a..i generated by the self-adjusting controller 63 and the determined quality parameters 49a as input variables E to the model adaptation step 57, which performs the dynamic model adaptation 58. In this way, the stored model 47 is gradually adapted to the conditions of process P.To ensure that the control loop structure 62 only dynamically adjusts process P when the achieved quality parameters 49a no longer correspond to the quality parameters 49 defined in the selected harvesting process strategy 53, limit values ​​66 are assigned to the quality parameters 49 and 49a. In a test step 67, it is first determined whether the achieved quality parameter 49a is still within the limit value 66 applicable to quality parameter 49. If the determined quality parameter 49a exceeds the defined limit value 66, the control loop structure 62 is activated. Conversely, the control loop structure 62 does not intervene in process P if the limit value 66 is not exceeded. This also ensures that the control loop structure 62 remains activated until the optimized operating parameters 50a derived from the nonlinear dynamic process model 59 are reached.i meet the quality criteria 49 of process P.

[0040] In order for the described optimization method 65 to be used efficiently, it is provided, as described, that the optimization method 65 is integrated into the driver assistance system 45 assigned to the agricultural work machine 1, wherein the respective process model 47, 59 is stored in one of the storage units 68 of the driver assistance system 45 assigned to the control and regulation unit 33 that accommodates the computing unit 37, so that the computing unit 37 is designed and configured to operate the optimization method 65 using the stored process model 47, 58. The driver assistance system 45 is configured, as described, by means of suitable sensor systems 36 ( Fig. 1) to determine and provide the working parameters 44, 50a..i and associated control variables 51.

[0041] The driver assistance system 45, which implements the optimization procedure 65, is thus designed such that the map control 69 derives the operating parameters 44, 50a..i and the quality criteria 49, 49a from the static process model component 60 of the process P describing the machine behavior, as well as from the user specifications, the predefinable harvesting process strategies 53, and the technical limits of the agricultural machine 1 by means of optimization. The operation of the agricultural machine 1, designed as a combine harvester 2, is controlled by monitoring the quality parameters 49, 49a by means of the control loop structure 62 according to the invention, to which the self-adjusting controller 63 is assigned.Furthermore, the control loop structure 62 enables the adaptation of the stored process model 47, 58, whereby the described nonlinear dynamic model component 61 of the quality parameters 49, 49a is determined by applying a parameter estimation method 70 and from this the process model 47 of the steady-state machine behavior is determined.

[0042] The characteristic map control 69 thus performs two tasks, namely the direct specification of the working parameters 44, 50a..i of the working elements 30 and the specification of the limit values ​​66 of the control loop structure 62, wherein the self-adjusting controller 63 assigned to the control loop structure 62 monitors the quality parameters 49, 49a, wherein the control loop structure 62 can be designed such that the self-adjusting controller is either a so-called standard controller for maintaining a setpoint or a limit load controller, which activates when the limit value 66 is exceeded and deactivates again after falling below the limit value 66.

[0043] Thus, the optimization method according to the invention is designed such that it, on the one hand, implements adaptive feedforward control 71 of the process P and, on the other hand, enables dynamic monitoring and control of the quality parameters 49, 49a. This means that the basic setting of the operating parameters 44, 50a..i is derived from the static process model component, and compliance with the specified quality parameters 49, 49a is ensured by the control loop structure 62, so that the resulting control structure is designed as adaptive control with feedforward control.

[0044] A simple implementation of this procedure can be achieved by first determining the optimized working parameters 44, 50a..i using the derived static process model component 60 and the quality parameters 49 specified by the operator 34 of the agricultural machine 1. The optimized working parameters 44, 50a..i determined in this way are then transferred to the control loop structure 62 in order to determine optimized working parameters 64a..i based on the transferred working parameters 44, 50a..i and the transferred quality parameters 49. The optimized working parameters 64a..i are then set on the working elements 30 of the agricultural machine 1 and the resulting quality criteria 49a of process P are determined.In the next step, the determined quality parameters 49a are compared with the predefined quality parameters 49 in a test step 67 depending on a limit value 66. If the limit value 66 is exceeded, the control loop structure 62 is activated. The activation of the control loop structure 62 is either omitted or terminated if the limit value 66 is not exceeded or is no longer exceeded. If the control loop structure 62 is activated, the operating parameters 64a..i determined by the control loop structure 62 are assigned to the respective working element 30.

[0045] Fig. Section 4 now describes in more detail the application of the described dynamic process model 59 in an agricultural machine 1 designed as a combine harvester 2. It is known from the prior art that the driver assistance system 45 operates a so-called automated control system for the agricultural machine 1. In this context, it is known that the threshing elements 7, the associated threshing concave 6, and the deflecting drum 8 are combined to form a so-called threshing unit 80. It is also known to design the separating device 10 as a so-called separating unit 81. Furthermore, so-called cleaning units 82 are described in the prior art, which essentially consist of the working elements 30 of a cleaning unit 17 and include at least the blower 16 and the sieve levels 14, 15.

[0046] The process unit automatons 83 mentioned here, namely the threshing unit 680, the separating unit 781 and the cleaning unit 782, share the basic structure of an automatic system, namely that the driver assistance system 45 with its associated control and regulating device 33 and the associated computing unit 37 and storage unit 68 is designed to autonomously determine individual working parameters 44, 50a..i of the respective working elements 30 and to specify them to the respective working element 30, whereby the basis for determining the respective working parameters 44, 50a..i is the described user-side selection of harvesting process strategies 53.The driver assistance system 45 is designed such that process models 47, 59 describing the respective process unit 83 are stored in the storage unit 68 of the driver assistance system 45 and the computing unit 37 is set up to use the stored process models 47, 59 to control the process unit 83 according to . Fig.3 to operate, wherein the respective process unit 83 is configured to optimize the operating parameters 44, 50a..i of the working element(s) 30 and to specify the optimized operating parameters 50a..i, 64a..i to the respective working element 30. As already described, the process model 47 is designed as a dynamic nonlinear process model 59. In a first embodiment relating to the process unit 83, the process unit threshing unit 80, separating unit 81 and cleaning unit 82 are each assigned a separate dynamic process model 59a..c and associated optimization procedure 65a..c, so that the operation of each process unit 83 can be optimized independently of the operation of the other process unit 83.In another embodiment, the threshing unit 80 and the separating unit 81 can be combined into a single separating unit 85, in which case a single dynamic process model 59d and associated optimization method 65d are assigned to the single separating unit 85. This optimization method optimizes the operation of the threshing elements 7 and the associated working elements 30 (threshing concave 6 and deflecting drum 8), as well as the separating device 10. It would also be conceivable that a single process model (47) and associated optimization method (65) are assigned to the threshing unit (80), the separating unit (81), and the cleaning unit (82). Reference symbol list: 1 Agricultural work machine 2 combine harvesters 3 Grain cutter 4 inclined conveyors 5 Harvested crop flow 6 threshing baskets 7 threshing organ 8 Deflection drum 9 Separator rotor arrangement 10 Separating device 11 grains 12 Return floor 13 Feed tray 14 Sieve level 15 sieve level 16 blowers 17 Cleaning equipment 18 grain stream 19 Elevator 20 grain tank 21 funnel-shaped housing 22 straw choppers 23 Shredding device 24 straw 25 floor 26 Goods distribution device 27 Residual material flow 28 Residual material flow 29 chaff spreaders 30 Working organ 31 Vehicle cabin 32 Display unit 33 Control and regulating device 34 operators 35 bus system 36 sensor system 37 computing units 38 Internal Information 39 External Information 40 Information 41 Output signal 42 Display signal 43 Working organ signal 44 operating parameters 45 Driver assistance systems 46 Process optimization module 47 Process model 48 characteristic curve field 49.49a Quality parameters 50a..i Operating parameters 51 Control variable 51' optimized control variable 52 Optimization step 53 Harvesting process strategy 54 Model adaptation step 55 stationary model adaptation 56 Data preprocessing step 57 Model adaptation step 58 dynamic model adaptation 59 dynamic process model 60 static process model component 61 dynamic process model component 62 Control loop structure 63 self-adjusting controller 64a..i dynamic operating parameter 65 Optimization methods 66 Limit value 67 Test step 68 storage units 69 Map control 70 parameter estimation methods 71 adaptive feedforward control 80 threshing machine 81 Separator 82 Cleaning machine 83 Process unit automatic 84 85 common separator E Input size P Process QUOTES INCLUDED IN THE DESCRIPTION

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

[0000] DE 10 2010 017 687 A1

[0002] EP 2 687 922 A2

[0003] EP 4 154 699 A1

[0004] DE 101 47 733

[0025]

Claims

[1] Agricultural work machine (1) comprising a driver assistance system (45) which is provided and set up to automatically monitor and adjust working parameters (44, 50a..i) and quality parameters (49, 49a) of the agricultural work machine (1), wherein a process model (47) comprising characteristic curve fields (48) is assigned to the driver assistance system (45), so that the optimization method (65) implemented by the driver assistance system (45) is designed as a characteristic field control (69) and the optimization method (65) generates optimized working parameters (44, 50a..i) as a manipulated variable (51), and the driver assistance system (45) determines the quality parameters (49, 49a) of the agricultural work machine (1) depending on the optimized working parameters (44, 50a..i). characterized bythat the process model (47) is designed as a dynamic non-linear process model (59) in such a way that the dynamic non-linear process model (59) comprises a static process model part (60) and a dynamic process model part (61), wherein at least the manipulated variables (51) in the static process model part (60) pass through an optimization step (52) and in the dynamic process model part (61) pass through a control loop structure (62). [2] Agricultural work machine (1) comprising a driver assistance system (45) according to claim 1, characterized bythat the characteristic map control (69) defined by the process model (47) is set up and designed to predetermine the working parameters (44, 50a..i) of the agricultural working machine (1) and limit values (66) for the control loop structure (62), wherein a self-adjusting controller (63) is assigned to the control loop structure (62) and the self-adjusting controller (63) is provided and set up to monitor the quality parameters (49, 49a) of the process. [3] Agricultural work machine (1) comprising a driver assistance system (45) according to claim 1, characterized byin that the optimization step (52) and the control loop structure (62) form an optimization method (65) which is provided and set up to adapt the process model (47, 59) in a model adaptation step (57) in such a way that the dynamic non-linear process model component (61) is provided and set up to determine the stationary model component (60) of the process (P) from the monitoring of the quality parameters (49, 49a) and using a parameter estimation method (70), wherein the one or more manipulated variables (51, 51') comprising the optimized working parameters (44, 55a..i, 64a..i) and the one or more quality parameters (49, 49a) dependent on the respective manipulated variable (51, 51') form the input variables (E) of the optimization method (65). [4] Agricultural working machine (1) comprising a driver assistance system (45) according to one of the preceding claims, characterized bythat in the optimization step (52) optimized manipulated variables (51') are determined from the manipulated variables (51) derived from the process model (47) and predetermined quality parameters (49). [5] Agricultural working machine (1) comprising a driver assistance system (45) according to one of the preceding claims, characterized bythat the control loop structure (62) comprising the self-adjusting controller (63) comprises as input variables (E) the manipulated variables (51, 51') optimized in the optimization step (52), the predetermined quality parameters (49) and the quality parameters (49a) determined as a function of the optimized manipulated variables (51, 51'), and that the self-adjusting controller (63) is further provided and set up to derive optimized manipulated variables (51', 64a..i) from a comparison of the predetermined quality parameters (49) with the determined quality parameters (49a) and to transfer them to the process (P) and the model adaptation step (57) of the dynamic model adaptation (58). [6] Agricultural work machine (1) comprising a driver assistance system (45) according to claim 5, characterized by that the determined quality parameter (49a) is passed as input variable (E) to the model adaptation step (57). [7] Agricultural working machine (1) comprising a driver assistance system (45) according to one of the preceding claims, characterized by that the driver assistance system (45) is designed to automatically adjust the optimized control variables (51) to the working elements (30) of the agricultural working machine (1). [8] Agricultural working machine (1) comprising a driver assistance system (45) according to one of the preceding claims, characterized by that the control loop structure (62) is provided and configured to effect a dynamic adaptation of the process (P) before the stored process model (47) has been adjusted to the process (P). [9] Agricultural working machine (1) comprising a driver assistance system (45) according to one of the preceding claims, characterized bythat the non-linear dynamic process model (59) describes the relationship between working parameters (44, 50a..i) of a working organ (30) and the quality parameters (49,49a). [10] Agricultural working machine (1) comprising a characteristic map control according to claim 1 and 2, characterized by that the limit values (66) assigned to the quality parameters (49, 49a) are structured in such a way that in a test step (67) it is determined whether the achieved quality parameter (49a) is still within the limit value (66) defined for the quality parameter (49) or not, wherein when the limit value (66) is exceeded the control loop structure (62) is activated and the activation of the control loop structure (62) is then omitted or terminated when the limit value (66) is not or is no longer exceeded. [11] Agricultural working machine (1) comprising a driver assistance system (45) according to one of the preceding claims, characterized bythat the control loop structure (62) remains activated until the optimized working parameters (44, 50a..i) derived from the non-linear dynamic model meet the quality criteria of the process (P). [12] Agricultural working machine (1) comprising a driver assistance system (45) according to one of the preceding claims, characterized byin that the working elements (30) of the agricultural working machine (1) are combined to form process unit automatons (83) and one or more working elements (30) together with the driver assistance system (45) form a process unit automaton (83), wherein process models (47) describing the respective process unit automaton (83) are stored in a memory unit (68) assigned to the driver assistance system (45), and the computing unit (37) is provided and configured to operate the process unit automaton (83) by means of the stored process models (47), and the process unit automaton (83) is configured to optimize working parameters (44, 50a..i) of the working element(s) (30) and to specify the optimized working parameters (44, 50a..i) to the respective working element (30). [13] Agricultural working machine (1) comprising a characteristic map control according to claim 12, characterized bythat the process unit automatic device (83) is designed at least as a threshing machine (80) and / or as a separating machine (81) and / or as a cleaning machine (82) and each of these process unit automatic devices (83) is assigned a process model (47). [14] Agricultural working machine (1) comprising a characteristic map control according to claim 13, characterized by that at least the threshing machine (80) and the separating machine (81) are assigned a common process model (47), preferably the threshing machine (80) and the separating machine (81) and the cleaning machine (82) are assigned a common process model (47). [15] Agricultural working machine (1) comprising a driver assistance system (45) according to claim 3, characterized bythat the dynamic non-linear process model (59), preferably the dynamic process model part (61) is designed as a self-learning process model (47) and the parameter estimation method (70) is preferably formed by an LMN-FIR model (Local Model Networks with local Finite Impulse Response Models). [16] Agricultural working machine (1) comprising a driver assistance system (45) according to one of the preceding claims, characterized bythat the optimization method (65) is integrated into the driver assistance system (45) assigned to the agricultural work machine (1), wherein the respective process model (47, 59) is stored in a memory unit (68) of the driver assistance system (45) assigned to the control and regulating device (33) accommodating the computing unit (37), so that the computing unit (37) is provided and configured to operate the optimization method (65) by means of the stored process model (47, 59) and the driver assistance system (45) is further configured a.) to determine the working parameters (44, 50a..i) and associated manipulated variables (51) by means of suitable sensor systems (36) and to transfer them to the optimization process (65) b.) the optimization method (65) adapts the non-linear dynamic process model (59) in a model adaptation step (57) and then derives the static process model part (60) c.) the optimized working parameters (44, 50a..i) are then determined by means of the derived static process model component (60) and the quality parameters (49) that can be specified by the operator (34) of the agricultural working machine (1) d.) the determined optimized working parameters (44, 50a..i) are transferred to the control loop structure (62) in order to determine optimized working parameters (44, 64a..i) on the basis of the transferred working parameters (44, 50a..i) and the transferred quality parameters (49) e.) the optimized working parameters (44, 64a..i) are then set on the working elements (30) of the agricultural working machine (1) and the resulting quality criteria (49a) of the process (P) are determined f.) the determined quality parameters (49a) are then compared with the predefined quality parameters (49) in a test step (67) as a function of a limit value (66), wherein the control loop structure (62) is activated when the limit value (66) is exceeded and the activation of the control loop structure (62) is then omitted or terminated when the limit value (66) is not or is no longer exceeded. g.) when the control loop structure (62) is activated, the working parameters (44, 64a..i) determined by the control loop structure (62) are specified to the respective working element (30).

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