2022
DOI: 10.1177/09544070221133154
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Energy-efficient control of hydrostatic transmission of a front-end loader machine using machine learning algorithm and its sensitivity analysis

Abstract: This paper highlights development of 2-DOF and 3-DOF energy management controllers using a Machine Learning (ML) algorithm for closed-circuit hydrostatic transmission of Front-End Loader (FEL) machine. Objective of energy management controller, is to keep prime-mover, pump and hydro-motor in its efficient zone irrespective of variation of load-speed at drive end. Based on duty cycles of the transmission and sensitivity analysis of drive components, GPR algorithm shows better prediction (within 3%) of optimized… Show more

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Cited by 2 publications
(2 citation statements)
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“…Such failure and deformation significantly affect the productivity and work efficiency as well as the safety of workers [6,7]. Therefore, the front-end loader needs to be designed to have a safe structure and its safety must be verified through tests [8,9].…”
Section: Introductionmentioning
confidence: 99%
“…Such failure and deformation significantly affect the productivity and work efficiency as well as the safety of workers [6,7]. Therefore, the front-end loader needs to be designed to have a safe structure and its safety must be verified through tests [8,9].…”
Section: Introductionmentioning
confidence: 99%
“…With enormous amount of WLs are working in the world, it makes sense to diminish energy consumption of WLs. Literature are mainly studied on the energy-saving control methods that are widely applied to WLs include load-sensitive hydraulic system [2]- [4], hydrostatic drive technology [5], [6], engine energy-saving technology [7], [8], and hybrid power technology [9]- [11]. As the research and utilization of electrification becomes a trend in area of vehicles [12], the research of electric wheel loaders (EWL) has been paid more attention on.…”
Section: Introductionmentioning
confidence: 99%