Work State Estimation for Predictive Control of Self-Propelled Vehicles
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Self-propelled work vehicles, such as excavators and forestry machines, often operate inefficiently due to repetitive tasks requiring coordinated positioning of work tools and constant manual adjustment of engine speed, leading to fuel waste and operator fatigue.
Innovation Solution
A computer-implemented method for estimating the work state of self-propelled vehicles using onboard sensors to automate operations, such as engine speed control and work implement movements, based on detected parameters and operator commands, enabling predictive control signals to optimize vehicle performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If operators manually adjust engine speed continuously during field operations, then fuel efficiency can be optimized, but operator fatigue increases and productivity decreases due to repetitive adjustments
Solution Approach 1:
The system enables the work vehicle to automatically adjust its own engine speed based on sensor data and work state classification, eliminating the need for continuous manual operator intervention. The controller autonomously monitors sensor inputs, classifies work states, and adjusts engine parameters without operator involvement, allowing the vehicle to serve itself in optimizing fuel efficiency.
Solution Approach 2:
The patent replaces the manual mechanical adjustment system with an automated electronic control system. Sensors, processors, and controllers substitute for the operator's manual actions, using electronic signals and automated algorithms to adjust engine speed based on detected work conditions, thereby eliminating repetitive manual adjustments.
2Speed
If operators set engine speed dials to high idle settings during field operations, then the vehicle is ready for immediate response, but substantial fuel waste occurs due to unnecessarily high engine speeds
Solution Approach 1:
The system dynamically adjusts engine speed based on real-time work conditions rather than maintaining a static high idle setting. The controller continuously monitors sensor data and adapts engine parameters to match actual work demands, allowing the engine speed to vary flexibly between minimum and maximum settings according to the classified work state.
Solution Approach 2:
The patent changes the engine speed parameter dynamically based on work state classification. Instead of maintaining a constant high idle setting, the system adjusts engine speed parameters according to the detected work conditions, transitioning between different speed levels to match actual operational requirements and reduce unnecessary energy consumption.
3Productivity
If automated control systems are implemented to adjust engine speed and work implement positioning, then productivity increases and operator fatigue reduces, but system complexity increases
Solution Approach 1:
The controller serves multiple functions within a single integrated system: it processes sensor data, classifies work states, determines appropriate engine parameters, and controls work implement positioning. This multi-functional approach consolidates what could be separate complex systems into one unified controller, achieving automation benefits while limiting overall system complexity through functional integration.
Solution Approach 2:
The processor acts as an intermediary between the sensors and the control actuators. It receives raw sensor data, processes this information through work state classification algorithms, and generates appropriate control signals. This intermediary layer simplifies the overall system architecture by providing a centralized processing hub that coordinates between detection and control functions.
4Measurement precision
If onboard sensors continuously monitor work conditions to enable automated control, then work state detection accuracy improves, but energy consumption of the monitoring system increases
Solution Approach 1:
The sensor system continuously monitors work conditions without interruption to maintain accurate real-time detection of work states. This continuous monitoring ensures that the controller always has current information for optimal engine parameter adjustment and work implement control, maintaining measurement precision throughout operation while the system processes data efficiently to minimize energy overhead.
Data Source
AI summary
A self-propelled work vehicle is provided with work state estimation and associated control techniques. The work vehicle comprises ground engaging units, a work implement configured for controllably working terrain, and various onboard sensors. A controller is functionally linked to at least the one or more onboard sensors and configured to ascertain a first parameter or operation of the work vehicle, determine a work state of the work vehicle, based at least in part on respective input signals from one or more onboard sensors, and generate a control signal for controlling at least a second parameter or operation of the work vehicle, responsive to the ascertained first parameter or operation and the determined work state. The control signals may be provided for proactive adjustments to engine speed, movements of the work implement, movements of the work vehicle itself, etc.