Data-driven algorithms for predicting energy-efficient operating points in agricultural soil tillage

Sustainability is especially important in power-intensive tasks in the agricultural industry, and therefore an aspect with optimization potential. During adjustments of the operating speed, fuel consumption can vary. The prediction of the most efficient operating point for the tractor-implement combinations is challenging due to the complexity of the machinery and the varying interaction forces between soil and machine. Currently, human drivers are required to manually adjust the operating speed. This paper presents and compares two optimization algorithms for predicting the most energy-efficient operating speed based on real-time measurements of the system state. Field tests were conducted to evaluate the algorithms under varying soil types and operating conditions. The algorithms accurately determined advantageous operating points within the defined working quality boundaries, making them promising tools for increasing sustainability in the agricultural industry.