Work Vehicle Transmission Prognostics for Torque-Based Wear Prediction
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Solution Overview
Problem
Existing work vehicle powertrains with multi-mode continuously variable transmissions lack effective monitoring and prognostics systems to assess component wear and maintenance needs, leading to inefficient operation and potential breakdowns.
Innovation Solution
A prognostics system is integrated into the powertrain, utilizing a processor and memory architecture to monitor components associated with the output shaft or transmission, generating usage values based on commanded torque and aggregating them to provide prognostics values for maintenance and replacement decisions, while operating in various modes that combine engine and continuously variable power sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a prognostics system is integrated to monitor and predict component wear, then component lifespan and operational efficiency are improved, but device complexity increases
Solution Approach 1:
The prognostics controller is integrated with the existing transmission control functionality, allowing a single controller to perform both transmission control and prognostics monitoring. This multi-functional approach enables component wear prediction without adding separate dedicated hardware systems, thus improving reliability while minimizing the increase in device complexity.
Solution Approach 2:
The prognostics system utilizes data already generated by the powertrain operation (torque commands, operational parameters) to automatically assess component wear and generate maintenance recommendations. The system serves itself by using existing operational data without requiring external monitoring equipment, thereby extending component lifespan through intelligent analysis rather than physical modifications.
2Productivity
If real-time monitoring and prognostics data collection is implemented, then maintenance efficiency is improved, but loss of information increases due to the complexity of data management
Solution Approach 1:
The prognostics controller continuously receives operational data from the powertrain, processes this information to assess component wear, and generates feedback in the form of maintenance recommendations and usage values. This closed-loop feedback system ensures that data is not only collected but actively utilized to improve maintenance timing and accuracy, enhancing maintenance efficiency while maintaining data integrity through systematic processing.
Solution Approach 2:
The system performs preliminary assessment of component wear by continuously analyzing operational data and generating prognostics values before actual component failure occurs. This advance prediction capability allows maintenance to be scheduled proactively based on predicted component conditions rather than reactively after failure, improving maintenance efficiency while organizing data in a structured manner that prevents information loss.
3Measurement precision
If usage values are generated and aggregated for each component, then measurement precision of component wear is improved, but device complexity increases due to additional monitoring requirements
Solution Approach 1:
The system replaces physical wear measurement mechanisms with computational analysis of operational parameters. Instead of using sensors to physically measure component wear, the prognostics controller calculates usage values by analyzing torque commands and operational data, then aggregates these values to predict wear. This substitution of mechanical measurement with computational assessment improves measurement precision while avoiding the complexity of additional physical monitoring hardware.
Data Source
AI summary
A work vehicle includes an engine; at least one continuously variable power source (CVP) configured to operate according to a commanded torque; an output shaft; a transmission positioned operatively between the output shaft and the engine and the CVP such that the output shaft selectively receives power from one or both of the engine and the at least one CVP; and a prognostics system configured to monitor a respective component associated with at least one of the output shaft or the transmission. The prognostics system includes a prognostics controller having a processor and memory architecture, configured to: receive input data, including the commanded torque; generate a usage value for the respective component for a time period as a function of the commanded torque; aggregate the usage value with previous usage values to generate a prognostics value over a life of the respective component; and store the prognostics value.