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  11. Optimization Of Traction Power Conservation And Energy Efficiency In Agricultural Mobile Robots Using The Tecs Algorithm

Optimization of traction power conservation and energy efficiency in agricultural mobile robots using the TECS algorithm

Yavuz Bahadır Koca1, Barış Gökçe2, Yılmaz Aslan3

  • 1Electrical Engineering Department, Faculty of Engineering, Afyon Kocatepe University, Afyonkarahisar, Turkey. ybkoca@gmail.com.

Scientific Reports
|September 25, 2025

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View abstract on PubMed

Summary
This summary is machine-generated.

This study introduces the Tillage and Energy Control System (TECS) for optimizing agricultural robot traction and energy use. TECS adapts to soil conditions by monitoring wheel slip rate for efficient tillage operations.

Area of Science:

  • Agricultural Robotics
  • Control Systems Engineering
  • Soil Mechanics

Background:

  • Efficient energy utilization and traction control are critical for autonomous agricultural machinery.
  • Variable soil conditions pose significant challenges to maintaining optimal performance in tillage operations.
  • Existing control systems often lack adaptability to dynamic environmental factors encountered during fieldwork.

Purpose of the Study:

  • To develop and validate a novel control algorithm, the Tillage and Energy Control System (TECS), for optimizing traction power and energy efficiency in agricultural robots.
  • To enhance the adaptability of control systems to changing tillage conditions, including soil variations and obstacles.
  • To improve the performance of agrobot robots through intelligent traction management.

Main Methods:

Keywords:
Agricultural mobile robotControlEmbedded systemsOptimization

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  • Developed a Tillage and Energy Control System (TECS) algorithm focusing on traction power conservation and energy efficiency.
  • Utilized experimental data on traction-terrain interaction across diverse soil conditions to derive optimal traction models.
  • Implemented and compared traditional PID controllers with a Fuzzy Inference System for optimal traction control.
  • Integrated real-time monitoring of slip rate and traction changes as key control inputs for agrobot robots.

Main Results:

  • The proposed TECS algorithm demonstrated adaptability to varying tillage conditions by optimizing vehicle speed based on slip rate.
  • Optimal traction models were established as a function of traction ratios for maximum traction and energy efficiency.
  • The developed traction controller successfully compensated for soil spectrum changes, stone impacts, and system noise.
  • Experimental verification on a four-wheel skid steer robot prototype confirmed the effectiveness of the TECS control strategy.

Conclusions:

  • The Tillage and Energy Control System (TECS) offers an effective solution for optimizing traction and energy management in agricultural robots.
  • TECS enhances operational efficiency and robustness by adapting to dynamic soil conditions and potential disturbances.
  • The study validates the practical applicability of the proposed control algorithm in real-world agricultural robotic applications.
Robot operating system