This column will bring you the progress of the pre-competitive research being conducted at member universities that are part of the CCEFP network. This research will help give insight into the future direction of fluid power.
The Center for Compact and Efficient Fluid Power (CCEFP) holds a monthly forum, highlighting research, workforce, and special topic presentations.
CCEFP is a network of fluid-power-research laboratories, academic faculty, graduate and undergraduate students at nine universities. It is also a National Science Foundation Research Center. For more information on CCEFP, visit www.ccefp.org.
Since 2014, the National Fluid Power Association (NFPA) Foundation has supported and is helping to expand the pre-competitive fluid-power-research activities of the CCEFP, dramatically increasing the number of institutions and students impacted by its research program. For more on NFPA, visit www.nfpa.com/aboutnfpa/missionfocus.aspx.
Presented by: James Van de Ven, Associate Professor, University of Minnesota, and Eric Severson, Research Assistant, University of Wisconsin-Madison
Institutions: University of Minnesota and University of Wisconsin-Madison
PURPOSE
Electric systems are taking over a lot of jobs that hydraulic systems have traditionally held. Despite this, the force and power density of hydraulics really make it the premier choice for energy solutions. James Van de Ven asserts that if his team analyzes both systems, they can create a strategy that will allow industries to move between electrical systems and hydraulic systems in a more compact and efficient manner than today. Additionally, Van de Ven’s team sought to reduce the number of intermittent hydraulic loads in an attempt to reduce energy loss.
The primary application where the team feels their project’s success would benefit is the aerospace industry. Robotics could also use a new development in this area as Van de Ven is convinced electro-hydraulic systems are a long-neglected area of exploration for roboticists. Further in the future, the team is also convinced the push toward zero-emission vehicles creates an opportunity to develop a more efficient hydroelectric fuel cell.
PROGRESS
With the goal of creating the linear electromagnetic piston pump, Van de Ven plans to reduce the current five-step electric to hydraulic conversion process to a three-step conversion process. His team estimates that a system of six piston pumps will effectively minimize slow ripple and improve overall efficiency.
The team’s approach states that the fewer components in a conversion process will not only reduce the weight and volume, but will also improve the control bandwidth. By seamlessly integrating in both directions, they can also cool the electric motor and electric drive. This will lead to an increased power density. The team also decided to incorporate newly developed wide band gap MOSFETS which enables them to see a faster switching frequency and higher efficiency and power density in the pump.
NEXT STEPS
Although the project is in its infancy, the plan moving forward involves a two-year research strategy. In Year 1, the team will focus on model development and prototype design. The tasks include defining the design requirements, constructing the first-order models, increasing model details to inform that design, and selecting prototype parameters in order to optimize the design. In Year 2, the focus will shift to creating a laboratory benchtop prototype. The tasks required to make this a reality include fabricating a prototype machine, conducting experiment testing, and testing the hardware-in-the-loop.
As the project develops and new findings affect changes to the research strategy, Van de Ven asserts that the team will relay their progress to the fluid power research community on a regular basis. He also invites industry researchers and fluid power SMEs with expertise in “drive cycle” data for HST charge circuits in various applications to contact him at vandeven@umn.edu if they’d like to weigh in and share their thoughts on how his team can adjust their strategy to optimize their model.