Arnold Hießl, Rudolf Scheidl,
"Methodical Loss Reduction in Load Sensing Systems based on Measurements"
: Proceedings of the Bath/ASME Symposium on Fluid Power and Motion Control FPMC2016, 2016
Original Titel:
Methodical Loss Reduction in Load Sensing Systems based on Measurements
Sprache des Titels:
Englisch
Original Buchtitel:
Proceedings of the Bath/ASME Symposium on Fluid Power and Motion Control FPMC2016
Original Kurzfassung:
Energy efficiency improvements are forced by steadily increasing general performance and cost saving requirements, and for mobile machines mostly by stricter governmental emission laws. Such improvements can be realized by new system architectures, like hybrids or energy recovery systems, but also by optimizing existing systems. This publication discusses the reduction of systematic losses for an existing hydraulic Load Sensing System (LSS) used in mobile working machines, especially in compact excavators. Energy losses in a LSS are proportionaltothe pressure difference between pump and actuator in each section. These systematic losses are investigated and can be reduced by actuator adaptation or by splitting non-correlating sections.Energy losses along the hydraulic circuit, such as pump losses hydraulic line losses and actuator losses, which are affected by these adaptations indirectly, are neglected.
The investigations are founded on measurements of a 5 ton compact excavator and their systematic evaluation. The actuator adaptation can be realised by changing the excavator?s geometry and/or hydraulic specifications (cylinder areas, displacement volume). The focus of this paper is limited to the hydraulic domain. Mathematical models and operation scenarios verified by measurements were taken as the basis to find optimum system parameterconfigurations by mathematical optimization, employing evolutionary algorithm. This included also different groupings of LSS circuits. Boom, stick, bucket and swing were taken into account and results are shown for a one, two and three pump LSS. Considering the introduced methods an effective way for reducing systematic losses up to 40% is shown in this exemplary case.