Agricultural Vehicle Parameter Control With Cloud Model Updates

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Solution Overview

Problem

Existing agricultural machinery optimization systems require significant computing power and hardware resources for model updates, which are often underutilized due to the intermittent nature of agricultural operations, and are costly to maintain.

Innovation Solution

Outsource the adaptation of the machine parameter model to a cloud-based control unit, allowing the driver assistance system to initiate updates when operating data exceeds its primary range, leveraging the cloud's computing power to determine and send updated models for real-time optimization.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If model updates are performed locally on the tractor unit, then real-time optimization is achieved, but hardware complexity and computing power requirements increase significantly

Engineering Contradiction:
Improvereal-time optimization capabilityVSAvoidhardware requirements
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The patent extracts the complex model update computations from the local tractor unit and relocates them to a cloud-based server system. The driver assistance system on the tractor only maintains a basic model for real-time operations, while the cloud server handles sophisticated model updates using gathered operating data, thereby reducing local hardware complexity while preserving optimization capability

Inventive Principle:
Principle #2Taking out (Extraction)

Solution Approach 2:

The patent introduces a cloud server as an intermediary between the tractor unit and the model optimization process. The server receives operating data from multiple tractor-implement combinations, performs complex model updates, and sends updated models back to the vehicles. This intermediary handles the computational burden that would otherwise require expensive local hardware

Inventive Principle:
Principle #24Intermediary (Mediator)

2Speed

If hardware is sized for rapid model adjustments, then optimization speed is improved, but hardware remains idle for most of the time

Engineering Contradiction:
Improvemodel adjustment speedVSAvoidhardware idle time
Core Design Contradiction:
SpeedVSLoss of energy

Solution Approach 1:

The patent merges the computational resources of multiple tractor units into a shared cloud-based system. Instead of each tractor having dedicated hardware that sits idle, the cloud server consolidates computing power that serves multiple vehicles simultaneously. The server processes model updates for numerous tractor-implement combinations using aggregated operating data, maximizing resource utilization

Inventive Principle:
Principle #5Merging (Combining)

Solution Approach 2:

The cloud server provides universal model update services to multiple different tractor-implement combinations. A single server infrastructure supports various vehicle types, implement types, and operating conditions, making the hardware universally applicable rather than dedicated to a single vehicle's intermittent needs

Inventive Principle:
Principle #6Universality (Multi-functionality)

3Adaptability or versatility

If the model is updated frequently to cover broader operating ranges, then adaptability is improved, but computing power requirements increase

Engineering Contradiction:
Improveoperating range coverageVSAvoidcomputing power
Core Design Contradiction:
Adaptability or versatilityVSPower

Solution Approach 1:

The patent extracts computationally intensive model update operations from the local tractor system and places them on a cloud server with substantially greater computing power. This allows frequent and comprehensive model updates across broad operating ranges without burdening the tractor's limited onboard processing capabilities

Inventive Principle:
Principle #2Taking out (Extraction)

Solution Approach 2:

The system performs preliminary model updates in advance using cloud computing resources before the tractor needs the updated model for operation. The driver assistance system monitors operating conditions and triggers update requests when leaving the primary working area of the current model, allowing time for comprehensive cloud-based processing without real-time delays

Inventive Principle:
Principle #10Preliminary action

4Reliability

If local hardware is used for model updates, then real-time control is maintained, but system cost increases

Engineering Contradiction:
Improvereal-time control capabilityVSAvoidsystem cost
Core Design Contradiction:
ReliabilityVSEase of manufacture

Solution Approach 1:

The patent extracts expensive hardware requirements from the local tractor system and relocates them to a shared cloud infrastructure. The tractor unit only needs communication capabilities and basic processing for real-time control, while sophisticated model updates are performed remotely on cost-effective cloud servers that serve multiple vehicles

Inventive Principle:
Principle #2Taking out (Extraction)

Solution Approach 2:

The system uses communication networks to transmit model data and operating information between the tractor and cloud server. Rather than duplicating expensive processing hardware in each vehicle, the same cloud-based model update service is copied and accessed by multiple tractors through digital communication, significantly reducing per-vehicle system cost

Inventive Principle:
Principle #26Copying

Data Source

PatentEP4133927B1Method for optimizing the configuration of machine parameters of an agricultural vehicle combination
Publication Date: 2026.01.07 CLAAS TRACTOR
  • EP4133927B1 patent drawingFigure 1

AI summary

The invention relates to a method for optimizing the setting of machine parameters of an agricultural vehicle combination (4), wherein the vehicle combination (4) has a driver assistance system (5), wherein the driver assistance system (5) has a model for controlling and/or regulating the machine parameters of the vehicle combination (4), wherein the driver assistance system (5) determines settings of the machine parameters from the model as a function of operating data of the vehicle combination (4), wherein the model has a primary working range of the operating data, wherein the driver assistance system (5) triggers an update or recalculation of the model when the primary working range of the model is exceeded by operating data.It is proposed that the driver assistance system (5) initiates an update routine when the model leaves its primary working range, that the driver assistance system (5) sends at least part of the operating data to a cloud control unit (6) in the update routine, that the cloud control unit (6) determines an updated or newly determined model and update data for it based on the operating data, that the cloud control unit (6) sends the update data to the driver assistance system (5), and that the driver assistance system (5) determines machine parameter settings from the updated or new model depending on the operating data of the vehicle combination (4) and sets them on the vehicle combination (4) as part of the control and/or regulation of the machine parameters.