Wheel Loader Power Mode Control via Load State Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
It is challenging to manually select an optimal power mode for a wheel loader based on changing work states, leading to inefficient fuel consumption and performance deterioration, as existing methods lack real-time detection and automatic control capabilities.
Innovation Solution
A method and system that utilize sensors to receive and analyze signals to determine the current work state of a wheel loader, employing machine learning algorithms, such as neural networks, to classify the load state into specific areas (light, medium, heavy, and acceleration/inclined-ground) and automatically control the engine or transmission accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If manual selection of power mode is used, then operator control flexibility is maintained, but fuel efficiency deteriorates and operating performance decreases due to inability to adapt to changing work states
Solution Approach 1:
The wheel loader system performs self-diagnosis and self-adjustment by automatically detecting work states through sensors and adjusting power mode without operator intervention. The control unit continuously monitors sensor signals representing work states and autonomously selects optimal power modes, enabling the system to serve itself in terms of power management.
Solution Approach 2:
The system implements closed-loop feedback by continuously monitoring sensor signals that represent work states and using this information to adjust power mode selections. The control unit receives real-time feedback from sensors about current operating conditions and automatically modifies power delivery accordingly, creating a dynamic adaptive control system.
2Productivity
If automatic control based on detected work states is implemented, then fuel efficiency improves, but system complexity increases due to additional sensors and control mechanisms
Solution Approach 1:
The control unit serves multiple functions: it processes sensor signals representing work states, determines current operating conditions, selects appropriate power modes, and controls power delivery. This multi-functional approach consolidates control logic into a single unit, reducing overall system complexity while maintaining advanced automatic control capabilities.
Solution Approach 2:
The system merges sensor signal processing, work state determination, and power mode control into an integrated control unit. By combining these previously separate functions into one unified system, the patent reduces the number of discrete components and simplifies the overall control architecture while achieving sophisticated automatic power management.
3Measurement precision
If real-time detection of work states is performed, then power mode adaptation accuracy improves, but measurement and detection difficulty increases
Solution Approach 1:
The patent segments the complex task of work state detection into distinct sensor signals, each representing specific aspects of operation. By dividing the monitoring function into multiple specialized sensors that detect different parameters, the system achieves comprehensive and accurate work state detection while simplifying the analysis of each individual signal.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
In a method of controlling a wheel loader, signals representing a state of work currently performed by the wheel loader, are received from sensors installed in the wheel loader. One or more signals are selected of the received signals, the one or more signals able to be used to determine whether or not to be within a respective one of a plurality of individual load areas, wherein the individual load areas are divided according to work load which consumes a power output of an engine during a series of work states performed by the wheel loader. Output values representing as to whether or not to be within the respective one of the plurality of individual load areas, are calculated by using the selected signal. The output values are analyzed to determine a current load state of the work currently performed by the wheel loader.