Duqiang Wu 1), Greg Schoenau 2),Richard Burton 2) and Doug Bitner 2)
1) Lead Engineer, Eaton Corp, Minneapolis
2)Department of Mechanical Engineering, University of Saskatchewan
57 Campus Drive, Saskatoon, Saskatchewan, Canada, S7N 5A9
A load sensing (LS) system is one in which the pump flow is regulated to keep the pressure drop across an orifice constant and independent of any variation in the load pressure. This ensures that the pressure loss across the orifice is kept to a minimum, thereby increasing efficiency. An LS regulator spool is used to sense the pressure drop across the orifice to control pump delivery. The spool can be underlapped, critically lapped or overlapped. As a trade-off between efficiency and dynamic response, the LS spool is usually critically lapped. This results in a nonlinear model that is sensitive to operating regions. In this paper, a review of published literature on LS systems is briefly summarized. An LS system model is developed and linearized. Procedures to solve these very complex equations are introduced. Because load sensing systems require pressure feedback, stability can often be an issue. Analysis of these systems to determine the steady state and dynamic performance is very difficult to do because of the dependency of the models on the operating point. Linearized models which reflect a methodology to account for changing operating conditions have been developed and have established three distinct regions of operation (labeled “Conditions I, II, and III”). This paper presents the experimental nature of these conditions and provides experimental evidence that the models so derived are valid over certain frequency ranges. The objective of this paper, then, was to establish confidence in the models by examining frequency response performance under these three distinct conditions. The results show that good agreement does exist between the models and their physical counterparts and establishes limitations thereof. This research can assist in the design or optimization of an LS system and help in the development of advanced control strategies for obtaining further efficiency within certain dynamic performance constraints.
Keywords: load sensing, stability, linearization, operating point, energy efficiency