Research on Energy-Saving Control Strategy of Loader Based on Intelligent Identification of Working Stages
Publication: Journal of Construction Engineering and Management
Volume 150, Issue 7
Abstract
An energy-saving control strategy for wheel loaders is proposed in this paper to address the issue of high energy consumption during their operation. The strategy is based on the intelligent identification of working stages, allowing for staged power matching and resulting in reduced energy consumption. Each work stage of the loader is identified by matching it to the main pump pressure waveform and actuator pilot pressure waveform. Using a sliding time window method, pressure waveforms from each working stage are subjected to feature extraction. A bidirectional long short-term memory neural network (BILSTM) algorithm is then used to establish an intelligent recognition model. Based on work stage identification, an energy-saving control strategy based on power matching is proposed for the shoveling stage of the loader, and the Grey Wolf optimization (GWO)-PID algorithm is utilized for control parameter tuning. Finally, the effectiveness of the energy-saving control strategy based on work stage identification is verified through experiments. The research results indicate that the BILSTM recognition model outperforms other models with a recognition accuracy of 96.1%. The optimal time window width is 0.6 s, and the proposed energy-saving control strategy achieves a fuel-saving rate of 6.81%. This method provides feasibility for reducing energy consumption in construction machinery and achieving energy-saving and carbon-reduction goals.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The work was supported by the National Key Research and Development Program of China (2020YFB1709903).
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Information & Authors
Information
Published In
Journal of Construction Engineering and Management
Volume 150 • Issue 7 • July 2024
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Nov 22, 2023
Accepted: Feb 23, 2024
Published online: May 13, 2024
Published in print: Jul 1, 2024
Discussion open until: Oct 13, 2024
ASCE Technical Topics:
- Algorithms
- Continuum mechanics
- Design (by type)
- Dynamic loads
- Dynamics (solid mechanics)
- Energy consumption
- Energy efficiency
- Energy engineering
- Engineering fundamentals
- Engineering mechanics
- Load factors
- Mathematics
- Model accuracy
- Models (by type)
- Solid mechanics
- Structural design
- Structural dynamics
- Structural engineering
- Structural systems
- Vehicle loads
- Windows
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