Digging efficiencies for a hydraulic excavator are highly dependent on an operator’s skills because the hydraulic cylinders should be driven simultaneously. If an operator has insufficient skill, the digging operation might not be efficient because of the stalling of the hydraulic cylinder. Incorrect operation may also cause accidents.
To address such problems, automatic digging and remote-control hydraulic excavators were recently studied by researchers from Doshisha University and Caterpillar Japan Ltd. with the ultimate goal of improving digging efficiency.
It was quickly determined that there was too little research to establish a definitive algorithm for digging-efficiency tests. The researchers set about proposing a high-performance digging algorithm, one that considered force feedback, to better estimate the effectiveness of digging operations.
Digging efficiency was defined as the soil volume derived by the applied energy to drive the bucket. The researchers developed a miniature digging test device and a digging simulation model by 2-D distinct element methods to evaluate the efficiency of digging according to the algorithm.
Two methods were used during the digging test. One method included digging in accordance with a preprogrammed tip trace. The other method drove a bucket to apply reaction-force feedback.
In the test device, one motor rotated the bucket while two others drove the container to vertical and horizontal directions, replicating hydraulic excavator operations. Force sensors were used to measure reaction forces acting on the container in both horizontal and vertical directions.
The measurement data from the sensors was filtered by a low-pass filter because of noise. The pure reaction force from just the soil to the bucket was calculated by subtracting the consumed force to move the soil container from the measured force during digging. Three tip traces were generated during the testing.
The value of the digging efficiency on Trace 1 was smaller than other traces because Trace 1 required more digging energy than the others. The maximum torque on Trace 1 was the largest among the three digging traces. Therefore, the digging energy grew, and the digging efficiency decreased on Trace 1; it was clarified quantitatively that digging efficiency depended on the digging trace.
The digging efficiency results of the three different tip traces and torque feedbacks were compared. The digging efficiency was drastically changed by the tip trace. Trace 2 digging efficiency was about two times better than Trace 1. On the other hand, feedback digging kept high digging efficiencies. However, that result was under a specific soil condition; it might be different under another condition. Moreover, an actual hydraulic excavator has a limitation of an applied torque for the digging by the hydraulic system, the engine-pump output power.
All cases for the applied torque feedback digging demonstrated the relatively higher digging efficiencies. In terms of the set threshold, the digging torque decreased when it exceeded the threshold. Digging torque repeated the increase and decrease around the threshold.
This feedback system helped to use the more effective applied torque around the appropriate output power for the digging. Therefore, the force feedback enabled the control of digging energy and improved digging efficiency. The results showed that applying the algorithm provided a clue to the improvement of digging efficiency.
Overall, the study showed that the miniature digging device with a real-time torque-feedback system could be established, and that tip trace significantly affected the digging efficiency. In the long run, the developed simulation and algorithm could enable development of hydraulic excavators that dig with better efficiency.
This article is based on SAE technical paper 2010-01-1923 by Takayuki Koizumi, Tatsuya Yoshida, and Nobutaka Tsujiuchi of Doshisha University; and Hiroaki Andou of Caterpillar Japan Ltd.