Energy consumption evaluation of active tillage machines using dynamic modelling
Applied Sciences (Switzerland), ISSN: 2076-3417, Vol: 11, Issue: 14
2021
- 8Citations
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- 1Mentions
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
Soil tillage is a very energy-intensive operation. A general expectation is to reduce energy consumption and reduce soil compaction with as few turns and interventions as possible. Thus, more and more attention is being paid to the use of active tillage machines. The aim of the present work is to test a new approach to optimize PTO-driven tilling machine operations regarding energy consumption. A real, active tillage machine, the MSS-140 type spading machine, was investigated in the Matlab Simscape™ environment. The solid model of the spading machine was built using actual dimensions. The work done by a single spade is broken down into elementary processes. The acting forces on the implement, in each elementary process for different advancing speeds, were modelled and calculated. The model is suitable for illustrating the dynamics of loads and for calculating the mechanical work. The model was also tested in comparison with real fuel consumption. The consumed fuel quantity was measured and the energy requirement for the model calculated at three advancing speeds. A comparison between the measured and calculated energy consumption values was made: The calculated results are similar to the measured values; the mean difference is 9.91%, with a standard deviation 3.3%.
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