Work Machine Control System for Energy Recovery Optimization
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Solution Overview
Problem
Hybrid electric wheel loaders face challenges in efficiently managing the state of charge of their energy storage systems during repeated work cycles, particularly in optimizing energy recovery and reducing fuel consumption across varying terrain and operational conditions.
Innovation Solution
A method and system for controlling power transfer to and from the energy storage means in a work machine, utilizing a predetermined control strategy adapted to the characteristics of the work cycle, which includes detecting operational parameters and using pre-available information such as topographical maps to optimize energy management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If a hybrid electric wheel loader uses an energy storage means during operation, then energy recovery is optimized and fuel consumption is reduced, but the control complexity of the power transfer system increases
Solution Approach 1:
The control system pre-determines a control strategy based on work cycle characteristics before operation begins. The system predicts energy requirements for different portions of the work cycle and pre-plans power transfer operations, allowing the energy storage means to be charged or discharged at optimal times without real-time complex decision-making, thus reducing control complexity while maintaining energy optimization benefits
Solution Approach 2:
The control strategy dynamically adjusts the state of charge of the energy storage means based on predicted energy requirements for different work cycle portions. The system flexibly manages power transfer between the power source and energy storage means according to varying operational demands, enabling optimal energy recovery and fuel consumption reduction while adapting to changing work conditions
2Productivity
If the control system predicts energy requirements based on work cycle characteristics, then energy management is optimized, but the system requires more sophisticated sensing and control capabilities
Solution Approach 1:
The system utilizes pre-available information about work cycle characteristics and topographical data to predict energy requirements before operation begins. By performing prediction and planning in advance rather than requiring complex real-time sensing and decision-making, the system achieves optimized energy management with reduced sophistication in sensing and control capabilities
Solution Approach 2:
The control system automatically manages energy transfer based on predetermined strategies without requiring complex external sensing or intervention. The system self-regulates power flow between the power source and energy storage means according to pre-determined work cycle characteristics, achieving efficient energy management through autonomous operation rather than sophisticated external control
Data Source
AI summary
A method is provided for controlling a work machine during operation in a repeated work cycle including controlling transfer of power to and from an energy storage arrangement in the work machine according to a predetermined control strategy, which is adapted for the characteristics of the work cycle.