A control system for an autonomous electric agricultural vehicle

Abstract

A control system (1000), and method, for controlling an electric autonomous agricultural vehicle (110) comprising a battery (120) for powering of the vehicle (110), and an agricultural tool (130) connected to the vehicle (110) for processing an agricultural field. The control system (100) comprises a battery management system (140), a control unit (150) configured to control at least one vehicle propulsion property of the vehicle (110), and at least one tool operation property of the tool (130). The control system (1000) further comprises a processor (160) communicationally connected to the battery management system (140) and the control unit (150), wherein the processor (160) is configured to, based on conditions, provide instructions (162) to the control unit (150) for the control of at, least one of, the at least one vehicle propulsion property of the vehicle (110), and the at least one tool operation property of the tool (130).

Description

[0001] A CONTROL SYSTEM FOR AN AUTONOMOUS ELECTRIC AGRICULTURAL VEHICLE

[0002] TECHNICAL FIELD

[0003] The present invention relates to electric autonomous agricultural vehicles, in particular systems for controlling electric autonomous vehicles.

[0004] BACKGROUND

[0005] Agriculture is becoming ever more technologically advanced with remotely operated or even fully autonomous agricultural vehicles becoming available on the market. Such vehicles bring with them new challenges and opportunities for the operations of agriculture.

[0006] Particularly for electric autonomous vehicles, an effective use of the energy of the battery, and the recharging of the same, is of utmost importance and constitutes completely new critical elements of agricultural process chain.

[0007] Hence there is a need for new technology for integrating these new elements into the agricultural process chain whilst facilitating an effective use of the energy of the battery of electric autonomous agricultural vehicles.

[0008] SUMMARY

[0009] The invention is set out in the appended claims. This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description.

[0010] It is an object of the present invention to provide a control system for controlling the operations of an electrical autonomous agricultural vehicle, which control system facilitates both an efficient use of the energy of the battery and, enabling forecastable battery replacements operations for agricultural vehicles having replaceable batteries.

[0011] According to a first aspect, there is provided a control system for an electric autonomous agricultural vehicle comprising a battery for powering of the vehicle, and an agricultural tool connected to the vehicle for processing an agricultural field. The control system comprises a battery management system configured to monitor a power output and a remaining energy of the battery. The control system further comprises a control unit configured to control, at least one of, at least one vehicle propulsion property associated with a propulsion of the vehicle, and at least one tool operation property associated with an operation of any agricultural tool connected to the vehicle for processing an agricultural field.

[0012] A processor is communicationally connected to the battery management system and the control unit, wherein the processor is configured to, iteratively, obtain input data. The input data comprises data representing, at least one of, the power output and the remaining energy of the battery, the at least one vehicle propulsion property, the at least one tool operation property, a defined area of the agricultural field to be processed, and a defined time for completion of the processing of the field. The processor is further configured to compute from said input data at, least one of, a process time estimate for the processing of the defined area to be processed as a function of the obtained at least one vehicle propulsion property and the obtained defined area of the agricultural field to be processed, a required energy estimate for the processing of the defined area to be processed as a function of the obtained power output of the battery and the computed process time estimate, and a remaining process time based on a current time and the obtained defined time for completion.

[0013] Provided that, at least one of, a first condition that a difference between the computed required energy estimate and remaining energy of the battery differs from a targeted remaining energy of the battery by an amount which exceeds a threshold, and a second condition, that the computed process time estimate differs from said remaining process time by an amount which exceeds a threshold, is fulfilled, the processor is further configured to provide instructions to the control unit for the control of, at least one of, the at least one vehicle propulsion property, and the at least one tool operation property.

[0014] Accordingly, there is provided a control system that allows an autonomous electrical agricultural vehicle to autonomously adjust a combination of vehicle propulsion properties and tool operation properties, depending on environmental factors, to meet a requirement set on the agricultural processing of the defined area. The requirement may be to process the entire defined area using a targeted amount of energy of the battery while maximizing the agricultural processing performed by the tool. Expressed differently, the requirement may be to process the entire defined area using an amount of energy corresponding to the battery having a targeted amount of energy remaining upon completion of the processing of the defined area, all the while maximizing the agricultural processing performed by the tool. Alternatively, the requirement may be to process a defined area in a defined amount of time, all the while, maximizing the agricultural processing performed by the tool. The requirement may further be a combination of the two-above requirements, requiring the processing of a defined area using a target amount of the energy of the battery within a defined amount of time while maximizing the agricultural processing of the tool.

[0015] Maximizing the agricultural processing of the tool is the common demeanor in each of the above requirements. The adjustment made to the vehicle propulsion properties and / or the tool operation properties by the control system to meet any of the above requirements may be motivated by varying environmental factors of the processed field. By the meaning of environmental factors according to the above, it is here meant factors which would affect an energy requirement, i.e., a consumption of energy form the battery, for the processing of an area of a field. For example, the energy requirement for the tilling operation of an area of a field is very much dependent on the soil type of that specific field. Similarly, the energy requirement for the tilling operation of the same area of the same field is further dependent on the water contents of the soil at the time of tilling, i.e., soil condition. Hence, the control system according to the first aspect allows for an adaptability of the vehicle propulsion properties and / or tool operation properties, to variations in required energy resulting from environmental factors. This in turn allows the agricultural vehicle to process the whole of a defined area whilst fulfilling any of the above requirements.

[0016] By the meaning of maximizing the processing performed by the tool, it is here meant that an amount of an agricultural process is maximized. For example, if the tool is a cultivator, the maximizing of the processing performed by the cultivator could be a maximized depth of the cultivating. Hence, the amount of the agricultural process which is maximized is dependent on the type of tool which is connected to the autonomous agricultural vehicle. In the context of the present invention, the term maximized should not be interpreted as setting the here exemplified cultivator to its deepest setting. Instead, it should be interpreted as setting the at least one tool operation property to have the highest processing output corresponding to an energy and / or time requirement which, in combination with any other energy requirement of the vehicle, facilitates any of the above requirements set on the agricultural processing of the defined area.

[0017] The adaptability to variations in the required energy for the processing of a defined area of a field is achieved by tuning vehicle propulsion properties and / or tool operation properties. Vehicle propulsion properties pertain to the maneuvering and / or the movement of the autonomous agricultural vehicle. For example, the vehicle propulsion property(ies) may comprise e.g., vehicle speed, wheel slip, and / or path overlap. By the meaning of path overlap, it is here meant a factor describing an autonomously derived, or predetermined path of the vehicle for processing the defined area of the field, which factor describes the amount of overlap between a current position of the tool and a previous position of the tool. For example, a path overlap of 50%, will result in a path of the vehicle in which the connected tool will have ha 50% overlap with previously process soil. Similarly, a path overlap of 0% will result in a path of the vehicle in which the connected tool will have ha no overlap with previously process soil. Typically, overlap of the tool with previously processed soil is avoided as it is associated with a reduced energy efficiency for the processing of the field. Accordingly, a path overlap close to 0% is most commonly used. However, for some specific agricultural process, path overlapping exceeding 0% may be used. It is recognized by the skilled person that each of the above vehicle propulsion properties influences either a required power output from the battery, the time for processing the defined area, or both. For example, a reduced vehicle speed may result in a reduced power output from the battery and an increased process time. However, despite the increase in process time, the reduction in the power output may be significant enough to render an overall reduced required energy for the processing of the defined area of the field. Typically, for a human operated agricultural vehicle, a too long processing time of a field is undesirable due to for example the fatigue of the operator. However, for autonomous agricultural vehicles, there is no human operator, thus a long processing time for the processing of a defined area of the field need not be undesirable should it be associated with a reduced required energy. Further to the increase of the associated processing time by reducing vehicle speed, it should also be contemplated that the resulting increase of the process time enables adjustments of tool operation properties corresponding to a reduced energy requirement since a tool will have more time to process the field provided the reduced vehicle speed. Hence, a similar processing of the field may be achieved using less energy from the battery.

[0018] The tool operation properties primarily affect the power output from the battery, and the amount of agricultural processing of the field achieved. By the meaning of tool operation properties, it is here meant properties pertinent to the operation of the tool, such as a soil working depth, a tool engagement level, a variable tool width, a tool working speed, and / or a power supplied to the tool. The skilled person realizes that the power supplied to the tool may be electrical power supplied to the tool, or mechanical power derived from an electric of hydraulic motor integrated into the autonomous electrical vehicle.

[0019] The adjustment to each of the vehicle propulsion properties, and the tool operation properties, for the purpose of facilitating a requirement on the processing of a defined area of a field, may be performed via instructions provided by a processor. The processor may be communicationally connected to, and configured to provides instruction to, a control unit which is configured to control at least one vehicle propulsion properties and / or at least one tool operation property.

[0020] The control of the at least one vehicle propulsion property, and the at least one tool operation property, may be based on a respective predetermined property operational range. In other words, the control of the each of the vehicle propulsion property(ies), and each of the tool operation property(ies) may be limited to a respective predetermined operational range. For example, the vehicle speed may be limited to an operation range being defined by a predetermined maximum speed and a predetermined minimum speed. Similarly, a tool operation property corresponding to the depth of tilling of a tillage tool may be limited to an operational range defined by a predetermined maximum depth and a predetermined minimum depth.

[0021] Each of the at least one vehicle propulsion property and / or each of the at least one tool operation property may have a common control unit configured for their control. Each of the at least one vehicle propulsion property and / or each of the at least one tool operation property may alternatively have a respective control unit configured for their control, in which case, each control unit may be communicationally connected to the processor. It may further be contemplated that several properties may share a common control unit for their control.

[0022] The control unit(s) is (are) configured to provide the processor with data representing the vehicle propulsion properties, and / or tool operation properties.

[0023] The processor may further be communicationally connected to a battery management system configured to monitor a power output and a remaining energy of the battery of the electric autonomous agricultural vehicle. The battery management system may be configured to provide the processor with data representing a power output and a remaining energy of the battery.

[0024] The processor is configured to iteratively obtain input data representing at least one of, the power output and the remaining energy of the battery, at least one vehicle propulsion property, and / or at least one tool operation property. By the meaning of the term iteratively, it is here meant that the processor is configured to obtain data at several instance during the processing of the defined area of the field, wherein the obtained data corresponds to the power output, the remaining energy of the battery, the at least one vehicle propulsion property, and / or at least one tool operation property, at the time of obtaining the data.

[0025] The processor is further configured to obtain processing requirement data comprising information pertinent to the requirement set on the processing of the defined area of the field. The requirement data may be uploaded to the autonomous agricultural vehicle at the beginning of operations. Alternatively, the requirement data may be obtained by the processor from a remote server or cloud infrastructure. The requirement data may be obtained once at the beginning of the agricultural processing. Alternatively, the requirement data may be obtained iteratively during the course of the agricultural processing wherein the obtained requirement data corresponds to the requirements at the time of obtaining the data. Accordingly, a remote operator may at any time change the requirement information to change the behavior of the autonomous agricultural vehicle.

[0026] The requirement data may comprise data representing a defined area of the agricultural field which is to be agriculturally processed. The defined area may be the whole area of an agricultural field. Alternatively, the defined area may constitute only a part of an agricultural field, or a sum of two or more agricultural fields. The requirement information may further comprise a defined time for the completion of the agricultural process. The defined time for completion of the agricultural process may be a future point in time including a specified time and / or a date, alternatively the defined time may be an amount of time. The defined time may be determined by a remote operator or determined based on data obtained from a remote battery charging unit as will be described later.

[0027] The requirement information may further comprise a minimum remaining energy of the battery upon completion of the agricultural processing of a defined area of an agricultural field to be processed.

[0028] As the agricultural processing proceeds in time, the skilled person realizes that the defined area to be processed, i.e., the remaining area, of the initially defined area, to be processed, decreases. Accordingly, the processor may further be configured to iteratively obtain and / or compute a defined area to be processed which corresponds to a remaining area of the agricultural field to be processed at the time of obtaining and / or computing the defined area. The processor may further be configured to iteratively compute a process time estimate for the processing of the agricultural field. The processing time estimate may be computed as a function of the obtained at least one vehicle propulsion property e.g., vehicle speed and / or path overlap, and the obtained defined area of the agricultural field to be processed.

[0029] The defined area of the agricultural field to be processed, from which the process time is computed may be an area defined by a remote operator.

[0030] The processor may further be configured to iteratively compute a required energy estimate for the processing of the defined area, i.e., the remaining area to be processed. The required energy estimate may be calculated as a function of the obtained at least one power output of the battery and the computed process time estimate.

[0031] The processor may further be configured to iteratively compute a remaining process time based on a current time and the obtained defined time for completion.

[0032] The processor may be configured to iteratively provide the control unit with instructions for the control of at least one of the vehicle propulsion properties, and / or at least one of the tool operation properties, provided the fist condition that a difference between the computed required energy estimate and the remaining energy of the battery differs from a targeted remaining energy of the battery by an amount which exceeds a threshold. The target remaining energy of the battery may be defined by a remote operator.

[0033] The instructions provided by the processor to the control unit for the control, may be based on a predicted required energy, for the processing of the defined area of the agricultural field to be processed, associated with the control. The predicted required energy is a predicted future energy requirement which may be different from the computed energy requirement estimate. The predicted required energy is associated with the control of vehicle propulsion properties and / or the tool operation properties as changes to these properties, due to the control, affects the energy requirement for the processing of the field.

[0034] The predicted required energy associated with the control may correspond to the amount of energy, of the remaining energy of the battery, which exceeds a targeted remaining energy of the battery. For example, if the targeted remaining energy of the battery is set to zero, the predicted required energy for the processing will correspond to the amount of energy of the remaining energy of the battery which exceeds zero, i.e., the whole amount of the remaining energy of the battery. Hence, upon completion of the processing of the defined area, the remaining energy of the battery would be an amount of zero. Similarly, if the targeted remaining energy of the battery is instead set to, for example, 20 kWh, the predicted required energy for the processing would correspond to the remaining energy of battery which exceeds 20 kWh. Accordingly, upon completion of the processing of the defined area, the battery would have a remaining amount of energy being 20 kWh.

[0035] Since the iteratively provided instructions to the control unit for the control may, due to adaptations to environmental conditions, result in changes to the process time estimate, the processor may be configured to transmit any changes to the process time estimate to the remote server or cloud infra structure. Thereby a remote operator is kept aware of changes to the process time estimate. The changes to the process time estimate may further be transmitted, optionally via a remote server or cloud infrastructure, to a remote charging station as will be described later.

[0036] Provided the condition that a difference between the computed required energy estimate and remaining energy of the battery differs from a targeted remaining energy of the battery by an amount which exceeds a threshold, and provided the condition that that the computed required energy estimate is less than the amount of the energy of the remaining energy of the battery which exceeds the targeted remaining energy of the battery, the processor may be configured to perform a prioritization of instructions to the control unit for the control of the at least one tool operation property. In this case the instructions may be based on a predicted required energy for the processing of the defined area to be processed, associated with the control of the at least one tool operation property, which associated predicted required energy corresponds to the amount of the energy of the remaining energy of the battery which exceeds the targeted remaining energy of the battery. Accordingly, if the processor determines that there is a too low predicted required energy for the processing of the determined area of the field, the processor may issue instructions to the control unit for the control to increase the required energy by increasing the processing of a tool, thereby maximizing the agricultural processing performed by the tool.

[0037] The processor may further be configured to iteratively provide the control unit with instructions for the control of at least one of the vehicle propulsion properties, and / or at least one of the tool operation properties, provided the condition that the computed process time estimate differs from said remaining process time by an amount which exceeds a threshold. Typically, this condition can only be met provided that the processor has obtained a defined time for completion of the processing. Provided that the above condition is met, the processor may be configured to perform a prioritization of instructions, overruling any other prioritizations, to the control unit for the control of the at least one vehicle propulsion property, based on a predicted process time for the processing of the defined area to be processed associated with the control of the at least one vehicle propulsion property, which associated predicted process time corresponds to the remaining process time. The predicted process time according to the above is a future process time which may be different from the computed process time estimate. The predicted process time is associated with the control of vehicle propulsion properties as changes to these properties via the control at least affects the time for the processing.

[0038] Accordingly, provided that a defined time for completion of the processing has been obtained by the processor, the prioritization of the instructions provided by the processor allows the defined time for completion of the processing of the defined area to be kept without considering the remaining energy of the battery. However, provided such prioritized instructions, a required energy estimate may be obtained which facilitates the condition that a difference between the computed required energy estimate and remaining energy of the battery differs from a targeted remaining energy of the battery by an amount which exceeds a threshold. In such situations, the processor may be further configured to provide the control unit with instructions to the control unit for the control of the at least one tool operation property, based on a predicted required energy, for the processing of the defined area to be processed, associated with the control of the at least one tool operation property, which associated predicted required energy corresponds to the amount of the energy of the remaining energy of the battery which exceeds a targeted remaining energy of the battery.

[0039] Regardless of which conditions are fulfilled, the processor is configured to cancel any prioritization of instructions to the control unit for the control, if the controlled property has reached an end of its operational property range according to the obtained input data. The operational range may be prescribed by a remote operator. For example, it may be prescribed that the operational range of the soil working depth of a tillage tool is with in the range of a maximum depth and a minimum depth. Similarly, the vehicle speed can be prescribed to an operational range being within a minimum and a maximum speed.

[0040] Further to what has already been described, the control system may further comprise a memory, and the processor may be configured to iteratively store iteration data comprising at least one of, the iteratively obtained input data, the iteratively computed process time estimate, the iteratively computed required energy estimate, and the iteratively provided instructions, in said memory. The processor may further be configured to provided instructions to the control unit for the control, further based on the iteratively stored iteration data.

[0041] The control system may further comprise a machine learning element, and wherein the instructions provided by the processor, to the control unit, is further based on an input from the machine learning element. The input from the machine learning element may be derived from at least one of the iteratively obtained input data, and the iteratively stored iteration data.

[0042] By way of example, the machine learning element may be configured to, based on the stored data, and / or on the obtained input data, derive a suitable combination of the at least on vehicle propulsion property and / or at least one tool operation property. One non-limiting example where this would be applicable, is when an agricultural field having an inclination is being processed. Imagine the typical meander-like path followed by agricultural vehicles on such an inclined field. This type of path could result in an intermittent up-hill, down-hill processing of the field wherein the up-hill processing is associated with a larger power output from the battery. A machine learning element would be able to recognize this repetitiveness of processing conditions and therefor aid the processor in deriving suitable instructions to the control unit.

[0043] The control system according to the above may further comprise a remote charging unit, communicationally coupled with the processor and configured to control a charging of a remote battery, and to transmit data representative of a charging status of the remote battery to the processor.

[0044] The remote battery is typically an intended replacement battery for the autonomous agricultural vehicle.

[0045] The data representing the charging status of the remote battery may comprise a rate of charging of the remote battery, a stored energy in the remote battery, a time remaining until a full charge is achieved. The time remaining time until a full charge is achieved is dependent on the charging rate of the remote battery. The charging rate of the remote battery may be dependent on fluctuations in the power grid to which the charging unit is connected. The power grid may be comprised of a local power grid or and / or a public power grid. The local power grid may comprise a plurality of different power generating elements such as solar panels and / or wind turbines. A high output from the power generating elements may be associated with a faster charging rate of the battery and vice versa. Similarly, variations in energy prices in the main power grid may also be associated with the rate of charging the battery, wherein high energy prices may be associated with a slow or no charging of the battery. Accordingly, the charging unit is configured to control the charging rate of the battery based on the power generation in the local power grid, and energy prices in the main power grid. Ultimately, the control of the charge rate by the charging unit determines the time remaining until a full charge is achieved.

[0046] Since a battery replacement operation can be performed in the field where the autonomous agricultural is operating, it is beneficial to coordinate the processing time for the processing of a defined area to be processed, and the charging rate of the charging of the remote battery. Accordingly, the defined time for completion for the processing of the defined area to be processed obtained by the processor of the control system may be determined based on data representing a charging status of the remote battery. In particularly, the defined time for completion of the processing of defined area to be processed obtained by the processor may be determined based on data representing a time until a full charge of the remote battery is achieved. The charging unit may further be configured to, disregard factors pertaining to the output from the power generating elements power production or energy costs. Instead, the charging unit may control the charging rate of the remote battery based on an obtained computed process time estimate. This ensures that the remote battery is fully charged once the agricultural vehicle has completed the processing of the defined area of the agricultural field to be processed.

[0047] According to a second aspect of the invention, there is provided an electric autonomous agricultural vehicle comprising, a battery for powering of the vehicle, an agricultural tool connected to the vehicle for processing an agricultural field, and a control system according the first aspect of the invention.

[0048] The features, functions and benefits of the autonomous agricultural vehicle comprising a control system according to the meaning of the second aspect corresponds to the features, functions, and benefits of the control system according to the first aspect and will thus not be repeated. According to a third aspect, there is provided a method for controlling an electric autonomous agricultural vehicle comprising a battery for powering of the vehicle, and an agricultural tool connected to the vehicle for processing an agricultural field, the method comprising: monitoring, a power output and a remaining energy of the battery, and controlling, at least one vehicle propulsion property associated with a propulsion of the vehicle, and at least one tool operation property associated with an operation of any agricultural tool connected to the vehicle for processing an agricultural field.

[0049] The method further comprises obtaining, iteratively, input data, comprising, at least one of the power output and the remaining energy of the battery, the at least one vehicle propulsion property, the at least one tool operation property, and a defined area of the agricultural field to be processed, and a defined time for completion of the processing of the field, and iteratively computing, from said input data, at least one of, a process time estimate for the processing of the defined area to be processed as a function of the obtained at least one vehicle propulsion property and the obtained defined area of the agricultural field to be processed, and a required energy estimate for the processing of the defined area to be processed as a function of the obtained at least one power output of the battery and the computed process time estimate, and a remaining process time based on a current time and the obtained used defined time for completion.

[0050] The method further comprises, provided that at least one of, a first condition, that a difference between the computed required energy estimate and remaining energy of the battery differs from a targeted remaining energy of the battery by an amount which exceeds a threshold, and a second condition, that the computed process time estimate differs from said remaining process time by an amount which exceeds a threshold, is fulfilled, providing instructions, to the control unit for the control of, at least one of, the at least one vehicle propulsion property, and the at least one tool operation property.

[0051] The features, functions, and benefits of the method according to the meaning of the third aspect corresponds to the features, functions, and benefits of the control system according to the first aspect and will thus not be repeated.

[0052] BRIEF DESCRIPTION OF THE DRAWINGS

[0053] The invention will be described in detail with reference to the schematic drawings.

[0054] Fig. 1: Illustrates, highly schematically, an example embodiment of the control system.

[0055] Fig. 2: Illustrates, highly schematically, a further example embodiment of the control system comprising a machine learning element. Fig. 3: Illustrates, highly schematically, a further example embodiment of the control system comprising a charging unit.

[0056] DETAILED DESCRIPTION

[0057] For an improved understanding of the technology, the main elements of the control system will be discussed below with reference to Fig. 1.

[0058] Fig. 1 shows an example control system 100 for an electric autonomous agricultural vehicle 110 comprising a battery 120 for powering of the vehicle 110, and an agricultural tool 130 connected to the vehicle 110 for processing an agricultural field. The control system 100 comprises a battery management system 140 configured to monitor a power output and a remaining energy of the battery 120. The control system 100 further comprises at least one control unit 150 configured to control, at least one of, at least one vehicle propulsion property associated with a propulsion of the vehicle 110, and at least one tool operation property associated with an operation of any agricultural tool 130 connected to the vehicle 110 for processing an agricultural field. In the present example, one common control unit 150 is shown.

[0059] A processor 160 is communicationally connected to the battery management system 140 and the control unit 150, wherein the processor 160 is configured to, iteratively, obtain input data.

[0060] The obtained input data comprises data representing, at least one of, the power output 141 of the battery 120, the remaining energy 142 of the battery 120, the at least one vehicle propulsion property 151 of the vehicle 110, the at least one tool operation property 152 of the tool 130. The processor 160 may further be configured to obtain processing requirement data comprising information pertinent to the requirement set on the processing of the agricultural field. The requirement data may be uploaded to the control system 100 at the beginning of processing operation. Alternatively, the requirement data may be obtained by the processor 160 from a remote server or cloud infrastructure 200. The requirement data may be obtained once at the beginning of the agricultural processing. Alternatively, the requirement data may be obtained iteratively during the course of the agricultural processing wherein the obtained requirement data corresponds to the requirements the at the time of obtaining the data. Accordingly, a remote operator 300 may at any time change the requirement information to change the behavior of the autonomous agricultural vehicle. The requirement data may comprise data representing a defined area 201 of the agricultural field which is to be agriculturally processed. The requirement information may further comprise a defined time 202 for the completion of the agricultural process. The defined time 202 for completion of the agricultural process may be a future point in time including a specified time and / or a date, alternatively the defined time 202 may be an amount of time. The requirement information may further comprise a target remaining energy 203 of the battery 120 after completion of the processing of the defined area 201.

[0061] The processor 160 may further be configured to iteratively compute from said input data, a process time estimate A, for the processing of the defined area 201 to be processed as a function of the obtained data being representative of the at least one vehicle propulsion property 151 of the vehicle 110 and the obtained defined area 201 of the agricultural field to be processed.

[0062] The processor may be configured to iteratively compute a required energy estimate B, for the processing of the defined area 201 to be processed as a function of the obtained at least one power output 141 of the battery 120 and the computed process time estimate A.

[0063] The processor may also be configured to iteratively compute a remaining process time C, based on a current time and the obtained defined time for completion 202.

[0064] Provided that, at least one of, a first condition that a difference between the computed required energy estimate B, and remaining energy 142 of the battery 120 differs from a target remaining energy 203 of the battery 120 by an amount which exceeds a threshold, and a second condition, that the computed process time estimate A, differs from said remaining process time C by an amount which exceeds a threshold, is fulfilled, the processor 160 may be configured to provide instructions 162 to the control unit 150 for the control of, at least one of, the at least one vehicle propulsion property of the vehicle 110, and the at least one tool operation property of the tool 130.

[0065] The instructions 162 provided by the processor 160 to the control unit 150 for the control, may be based on a predicted required energy, for the processing of the defined area 201 be processed, associated with the control. The predicted required energy associated with the control may correspond to the amount of the energy, of the remaining energy 142 of the battery 120, which exceeds the target remaining energy 203 of the battery 120.

[0066] Provided the first condition, and provided the condition that that the computed required energy estimate B, is less than the amount of the energy, of the remaining energy 142 of the battery 120, which exceeds the targeted remaining energy of the battery 203, the processor 160 may be configured to perform a prioritization of the instructions 162 to the control unit 150 for the control of the at least one tool operation property of the tool 130, based on a predicted required energy for the processing of the defined area 201 to be processed, associated with the control of the at least one tool operation property, which associated predicted required energy corresponds to the amount of energy, of the remaining energy 142 of the battery 120, which exceeds the targeted remaining energy 203 of the battery 120. Accordingly, if the processor 160 determines that there is a too low predicted required energy for the processing of the determined area 201 of the field, the processor 160 will issue instructions 162 to the control unit 150 to increase the required energy B, by increasing the processing of the tool 130, thereby maximizing the agricultural processing performed by the tool.

[0067] The processor 160 may further be configured to iteratively provide the control unit 150 with instructions 162 for the control of at least one of the vehicle propulsion properties of the vehicle 110, and / or at least one of the tool operation properties of the tool 130, provided the fulfillment of the second condition. Typically, the second condition can only be fulfilled provided that the processor 160 has obtained a defined time 202 for completion of the processing of the defined area 201. Provided that the this condition is met, the processor 160 may be configured to perform a prioritization of instructions 162, overruling any other prioritizations, to the control unit 150 for the control of the at least one vehicle propulsion property of the vehicle 110, based on a predicted process time for the processing of the defined area 201 to be processed associated with the control of the at least one vehicle propulsion property, which associated predicted process time corresponds to the remaining process time C. In the case that, the prioritized instructions 162 provided to the control unit 150 for the control of the at least on vehicle propulsion property of the vehicle 110 corresponds to a required energy estimate which facilitates the first condition, the processor 160 may be further configured to provide the control unit 150 with instructions 162 for the control of the at least one tool operation property of the tool 130. The instruction 162 may be based on a predicted required energy, for the processing of the defined area 201 to be processed, associated with the control of the at least one tool operation property, which associated predicted required energy corresponds to the amount of energy of the remaining energy 142 of the battery 120 which exceeds a targeted remaining energy 203 of the battery 120.

[0068] The control system 100 shown in Fig. 1 enables an autonomous electrical agricultural vehicle 110 to autonomously adjust a combination of vehicle propulsion properties and tool operation properties, depending on environmental factors, to meet a requirement set on the agricultural processing of the defined area 201. The requirement may be to process the whole of a defined area 201 while leaving a target amount of energy 203 remaining in the battery 120, and maximizing the agricultural processing performed by the tool 130. Alternatively, the requirement may be to process a defined area 201 in a defined amount of time 202, all the while, maximizing the agricultural processing performed by the tool 130. The requirement may further be a combination of the two-above requirements, requiring the processing of a defined area 201 within a defined amount of time 202 while leaving a target amount of the energy 203 remaining in the battery 120.

[0069] The iteratively provided instructions 162 to the control unit 150 for the control may results in changes to the process time estimate A. Hence, in the present example, the processor 160 is configured to transmit 163 any changes to the process time estimate A, to the remote server or cloud infrastructure 200. The changes to the process time estimate A, may further be transmitted 164 to a remote operator 300.

[0070] Regardless of which conditions are fulfilled, the processor 160 is configured to cancel any prioritization of instructions 162 to the control unit 150 for the control, if the controlled property has reached an end of its operational property range according to the obtained input data 151,152. The operational range may be prescribed by a remote operator 300.

[0071] Now turning to Fig. 2, an example embodiment for the control system 100 is shown. In the present example each of the at least one vehicle propulsion property of the vehicle 110, and the at least one tool operation properties of the tool 100, have a respective control unit 150a, 150b, configured for their control. Each control unit 150a, 150b may be communicationally connected to the processor 160. The processor 160 may be configured obtain data representing at least one vehicle propulsion property 151 from the control unit 150a which is configured for the control of the at least on vehicle propulsion property of the vehicle 110. Similarly, the processor 160 may be configured obtain data representing at least one tool operation property 152 from the control unit 150b which is configured for the control of the at least on vehicle propulsion property of the tool 130. Correspondingly, the processor 160 is configured to provide each of the control units 150a, 150b with instructions 162a, 162b.

[0072] The example embodiment shown in Fig. 2 further comprises a memory 170, and the processor 160 is configured to iteratively store iteration data 165 comprising at least one of, the iteratively obtained input data 141, 142, 151, 152 the iteratively computed process time estimate A, the iteratively computed required energy estimate B, and the iteratively provided instructions 162, in said memory 170. The processor 160 may further be configured to provided instructions 162 to the control unit 150 for the control, further based on the iteratively stored iteration data 165.

[0073] The control system in Fig. 2 further comprises a machine learning element 180, and the instructions 162 provided by the processor 160 may be further based on an input 181 from the machine learning element 180 wherein the input 181 may be derived from at least one of the iteratively obtained input data 141, 142, 151, 152, and the iteratively stored iteration data 165. The machine learning element 180 may be configured to, based on the iteratively stored data 165, and / or the obtained input data 141, 142, 151, 152, derive a suitable combination of the at least on vehicle propulsion property and / or at least one tool operation property.

[0074] Now turning to Fig. 3, showing the control system 100 according to Fig. 1 further comprise a remote charging unit 400, communicationally coupled with the processor 600 and configured to control a charging of a remote battery 410. The remote battery 410 is typically an intended replacement battery for the autonomous agricultural vehicle 110.

[0075] The charging unit 400 may further be configured to transmit data representative of a charging status of the remote battery 410 to the processor 160.

[0076] The data representing the charging status of the remote battery 410 may comprise a rate of charging 401 of the remote battery 410, a stored energy 402 in the remote battery 410, and / or a time remaining 403 until a full charge is achieved. The time remaining 403 until a full charge is achieved is dependent on the charging rate 401 of the remote battery 410. The charging rate 401 of the remote battery 410 may be dependent on fluctuations in the power grid 500 to which the charging unit

[0077] 400 is connected. The power grid 500 may be comprised of a local power grid 510 and / or a public power grid 520. The local power grid 510 may comprise a plurality of different power generating elements 511 such as solar panels and wind turbines. A high output from the power generating elements 511 may be associated with a fast charge rate 401 of the battery 410 and vice versa. Similarly, variations in energy prices in the main power grid 520 may also be associated with the rate of charging

[0078] 401 of the battery 410, wherein high energy prices may be associated with a slow or no charging of the battery 410. Accordingly, the charging unit 400 is configured to control the charging rate 401 of the battery 410 based on the power generation of power generating element 511 in the local power grid 510, and energy prices in the main power grid 520. Ultimately, the control of the charge rate 401 by the charging unit 400 determines the time 403 remaining until a full charge is achieved.

[0079] Since a battery replacement operation can be performed in the field where the autonomous agricultural vehicle 110 is operating, it is beneficial to coordinate the time of replacing the battery 120 with the processing time for the processing of a defined area 201 to be processed. Accordingly, the defined time 202 for completion for the processing of the defined area 201 to be processed may be determined based on data 401, 402, 403 representing a charging status of the remote battery 410. In particularly, the defined time 202 for completion of the processing of defined area 201 to be processed be determined based on data representing a time 403 until a full charge is achieved. The charging unit 400 may further be configured to, disregard factors pertaining to the output from the power generating elements 511 and / or energy prices. Instead, the charging unit 400 may be configured to control the charging rate 401 of the remote battery 410 based on an obtained computed process time estimate A, or a remaining process time C. Thereby ensuring that the remote battery 410 is fully charged once the agricultural vehicle 110 has completed the processing of the defined area 201 of the agricultural field to be processed.

Claims

CLAIMS1. A control system (100) for an electric autonomous agricultural vehicle (110) comprising a battery (120) for powering of the vehicle (110), and an agricultural tool (130) connected to the vehicle (110) for processing an agricultural field, the control system (100) comprising a battery management system (140) configured to monitor a power output and a remaining energy of the battery (120), a control unit (150) configured to control, at least one vehicle propulsion property associated with a propulsion of the vehicle (110), and at least one tool operation property associated with an operation of any agricultural tool (130) connected to the vehicle (110) for processing an agricultural field, a processor (160) communicationally connected to the battery management system (140) and the control unit (150), wherein the processor (160) is configured to, iteratively, obtain input data, comprising data representing at least one of the power output (141), and the remaining energy (142) of the battery (120), the at least one vehicle propulsion property (151), the at least one tool operation property (152), a defined area of the agricultural field to be processed (201), and a defined time (202) for completion of the processing of the agricultural field, compute from said input data (141, 142, 151, 152, 201, 202) at least one of a process time estimate (A) for the processing of the defined area (201) to be processed as a function of the obtained at least one vehicle propulsion property (151) and the obtained defined area (201) of the agricultural field to be processed, a required energy estimate (B) for the processing of the defined area (201) to be processed as a function of the obtained at least one power output (141) of the battery (120) and the computed process time estimate (A), and a remaining process time (C) based on a current time and the obtained defined time (202) for completion, provided that at least one of, a first condition, that a difference between the computed required energy estimate (B) and remaining energy of the battery (142) differs from atargeted remaining energy of the battery (203) by an amount which exceeds a threshold, and a second condition, that the computed process time estimate (A) differs from said remaining process time (C) by an amount which exceeds a threshold, is fulfilled, the processor (160) is further configured to provide instructions (162) to the control unit (150) for the control of at least one of the at least one vehicle propulsion property of the vehicle (110), and the at least one tool operation property of the tool (130).

2. The control system (100) according to claim 1, wherein, if the first condition is fulfilled, the instructions (162) provided by the processor (160) to the control unit (150) for the control, is based on a predicted required energy, for the processing of the defined area (201) of the agricultural field to be processed, associated with the control, which associated predicted required energy corresponds to the amount of the energy, of the remaining energy (142) of the battery (120), which exceeds the targeted remaining energy (203) of the battery (120).

3. The control system (100) according to claim 1 or 2 , wherein, if the first condition is fulfilled, and provided the condition that that the computed required energy estimate (B) is less than the amount of the energy, of the remaining energy (142) of the battery (120), which exceeds the targeted remaining energy (203) of the battery (120), the processor (160) is configured to perform a prioritization of instructions (162) to the control unit (150) for the control of the at least one tool operation property, based on a predicted required energy for the processing of the defined area (201) to be processed, associated with the control of the at least one tool operation property, which associated predicted required energy corresponds to the amount of energy of the remaining energy (142) of the battery (120) which exceeds the targeted remaining energy (203) of the battery (120).

4. The control system (100) according to any of the previous claims, wherein, if the second condition is fulfilled, the processor (160) is configured to perform a prioritization of instructions (162), overruling any other prioritizations (162), to the control unit (150) for the control of the at least one vehicle propulsion property, based on a predicted process time, for the processing of the defined area (201) to be processed, associated with the control of the at least one vehicle propulsion property, which associated predicted process time corresponds to the remaining process time (C).

5. The control system (100) according to any of the previous claims, wherein the control of the at least one vehicle propulsion property, and the at least one tool operation property, is based on a respective predetermined property operational range.

6. The control system (100) according to claims 5, wherein the processor (160) is configured to cancel any prioritization of instructions (162) to the control unit (150) for the control, if the controlled property has reached an end of its operational property range according to the obtained input data.

7. The control system (100) according to any of the previous claims, wherein the at least one vehicle propulsion property includes one of a speed of the vehicle, a wheel slip of the vehicle, and a path overlapping of the vehicle, wherein the at least one tool operation property includes one of a soil working depth, a tool engagement level, a tool working width, a tool working speed, and a power supplied to the tool.

8. The control system (100) according to any of the previous claims, wherein the defined area (201) of the agricultural field to be processed, from which the process time (C) is computed, is an area defined by a remote operator.

9. The control system (100) according to any of the previous claims, wherein the control system (100) comprises a memory (170), and wherein the processor (160) is configured to iteratively store iteration data (165) comprising at least one of the iteratively obtained input data (151, 152,141, 142), the iteratively computed process time estimate (A), the iteratively computed required energy (B) , and the iteratively provided instructions (162), in said memory (170), and wherein, the processor (160) is configured to provided instructions (162) to the control unit (150) for the control, further based on the iteratively stored iteration data (165).2110. The control system (100) according to claim 9, wherein the control system (100) comprises a machine learning element (180), and wherein the instructions (162) provided by the processor (160) is based on an input (181) from the machine learning element (180) derived from at least one of, the iteratively obtained input data (181), and the iteratively stored iteration data (165).

11. The control system (100) according to any of the previous claims, further comprising, a remote charging unit (400), communicationally coupled with the processor (160) and configured to control a charging of a remote battery (140), and transmit data representative of a charging status of the remote battery (410) to the processor (160).

12. The control system (100) according to claim 11, wherein the charging unit (400) is further configured to control the charging of the remote battery (410) based on the computed process time estimate (A).

13. The control system (100) according to any of the previous claims, wherein the defined time (202) is determined by at least one of, a defined time (202) defined by a remote operator (300), and data representative of the charging status of the battery (410).

14. An electric autonomous agricultural vehicle (110), comprising, a battery (120) for powering of the vehicle (110), an agricultural tool (130) connected to the vehicle (110) for processing an agricultural field, and a control system (100) according to any one of the preceding claims.

15. A method for controlling an electric autonomous agricultural vehicle (110) comprising a battery (120) for powering of the vehicle (110), and an agricultural tool (130) connected to the vehicle (110) for processing an agricultural field, the method comprising monitoring a power output (141) and a remaining energy (142) of the battery (120), controlling at least one vehicle propulsion property associated with a propulsion of the vehicle (110), and22 at least one tool operation property associated with an operation of any agricultural tool (130) connected to the vehicle (110) for processing an agricultural field, iteratively, obtaining input data (151, 152, 141, 142), comprising at least one of the power output (141) and the remaining energy (142) of the battery (120), the at least one vehicle propulsion property (151), the at least one tool operation property (152), a defined area (201) of the agricultural field to be processed, and a defined time (202) for completion of the processing of the agricultural field, computing from said input data (151, 152, 141, 142) at least one of a process time estimate (A) for the processing of the defined area (201) to be processed as a function of the obtained at least one vehicle propulsion property (151) and the obtained defined area (201) of the agricultural field to be processed, and a required energy estimate (B) for the processing of the defined area (201) to be processed as a function of the obtained at least one power output (141) of the battery (120) and the computed process time estimate (A), and a remaining process time (C) based on a current time and the obtained used defined time (202) for completion, provided that at least one of, a first condition, that a difference between the computed required energy estimate (B) and remaining energy (142) of the battery (120) differs from a targeted remaining energy (203) of the battery (120) by an amount which exceeds a threshold, and a second condition, that the computed process time estimate (A) differs from said remaining process time (C) by an amount which exceeds a threshold, is fulfilled, providing instructions (162) to the control unit for the control of at least one of the at least one vehicle propulsion property, and the at least one tool operation property.

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