Payload Estimation Using Power Source Parameters
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Solution Overview
Problem
Existing payload estimation systems for work machines, such as dump trucks, are costly to install and maintain due to the need for additional sensors, and often rely on inaccurate methods like multiplying haul counts with rated load capacities, which do not account for actual payload deviations.
Innovation Solution
A payload estimation system that includes a power source, payload carrier, actuator, and controller, which uses existing machine parameters like speed, torque, and fuel consumption to estimate payload weight by comparing them with a pre-determined dataset, eliminating the need for additional sensors and providing accurate payload counter functionality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If additional sensors are installed to measure payload weight directly, then measurement precision is improved, but device complexity and installation cost increase
Solution Approach 1:
The power source performs payload measurement functions while serving its primary purpose of providing mechanical power. The controller monitors parameters the power source naturally generates during operation (speed, torque, fuel consumption) and uses these self-generated data streams to estimate payload weight, eliminating the need for separate measurement devices
Solution Approach 2:
The power source and its control system are made multi-functional by enabling them to perform both their primary function (providing power) and a secondary function (payload measurement). The existing controller that manages power source operation is extended to also collect and process operational parameters for payload estimation, making a single system serve multiple purposes
2Device complexity
If payload estimation uses simple methods like multiplying haul counts with rated load capacities, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The estimation approach transitions from using a single static parameter (rated load capacity multiplied by haul count) to using multiple dynamic parameters (speed, torque, fuel consumption) that change with actual operating conditions. This allows the system to adapt to variations in payload weight, terrain, and machine performance over time
Solution Approach 2:
The system incorporates feedback by continuously monitoring power source parameters during operation and comparing them against expected values for different payload weights. The controller adjusts estimates based on actual measured deviations from expected operational patterns, improving accuracy over static estimation methods
3Device complexity
If existing machine parameters are used for payload estimation, then device complexity and cost are reduced, but measurement precision may be compromised
Solution Approach 1:
The patent replaces direct mechanical measurement systems (sensors, scales, load cells) with a computational approach using electrical/control system data. Instead of physically measuring weight through mechanical means, the system substitutes mathematical modeling and parameter analysis of power source operation to estimate payload weight
Data Source
AI summary
A payload estimation system for a work machine is provided. The system includes a power source, a payload carrier, an actuator and a controller. The payload carrier is configured to contain a payload of material. The actuator is configured to effectuate movement of the payload carrier. The controller is configured to control an operation of the actuator. The controller is also configured to receive one or more parameters associated with the power source of the work machine, during an operation of the payload carrier. Further, the controller is configured to compare the one or more parameters with a pre-determined dataset to estimate a weight of the payload on the work machine.