Harvester Power Prediction for Auxiliary Subsystem Control
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Solution Overview
Problem
Agricultural harvesters face inefficiencies due to varying power requirements, leading to power deficits or excesses that affect performance and increase wear, particularly when operating auxiliary subsystems like material transfer systems.
Innovation Solution
A control system that utilizes in-situ data and predictive models to manage power distribution by generating control signals based on relationships between power characteristics and geographic-specific agricultural characteristics, such as topography, soil moisture, and vegetation indices, to optimize power usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the harvester operates auxiliary subsystems continuously, then productivity is improved, but power consumption increases causing power deficits
Solution Approach 1:
The control system predicts future power requirements of auxiliary subsystems based on geographic location data and field characteristic maps before the actual operation occurs. This allows the powerplant to be prepared in advance, adjusting its output to meet upcoming power demands and prevent power deficits during auxiliary subsystem operation.
Solution Approach 2:
The powerplant operating point is dynamically adjusted based on real-time geographic location and predicted power requirements. The system continuously modifies the power output to match the actual needs of auxiliary subsystems, transitioning between different operating states to optimize both productivity and energy efficiency.
2Power
If the powerplant operates at high power output, then power availability is improved, but wear on the powerplant increases
Solution Approach 1:
The system predicts future power requirements based on geographic location and field characteristics before auxiliary subsystems are activated. This allows the powerplant to operate at optimal power levels in advance, avoiding sudden high-power demands that would increase wear while ensuring power availability when needed.
Solution Approach 2:
The control system continuously monitors geographic location, compares it with field characteristic maps, and adjusts powerplant output accordingly. This feedback mechanism ensures the powerplant operates only at the necessary power level, minimizing wear while maintaining sufficient power availability for auxiliary subsystems when required.
3Use of energy by moving object
If the harvester adjusts operating parameters frequently, then power optimization is improved, but control system complexity increases
Solution Approach 1:
Power optimization is achieved through preliminary prediction of power requirements based on geographic location and pre-stored field characteristic maps. This approach allows the control system to determine optimal operating parameters in advance without requiring complex real-time adjustments, simplifying the control logic while maintaining power optimization.
Data Source
AI summary
An agricultural harvesting system includes a control system. The control system identifies a predictive value of a power characteristic based on a relationship between the power characteristic and a characteristic. The control system generates a control signal to control a controllable subsystem of a mobile agricultural harvesting machine based on the predictive value of the power characteristic.