Compact, backdrivable, and efficient design of linear electro-hydrostatic actuator module

Abstract

An electro-hydrostatic actuator (EHA) has high backdrivability and is suitable for robots that interact with the environment, including human. However, the challenging problem in its mechanical design is that it is difficult to achieve compact size and high power transmission efficiency, compared with standard gear reducers. To tackle this problem, this study presents the design method by macro- and micro-scale designs. A linear-type EHA consists of a cylinder and a hydraulic pump. The former includes cylinder parameters that are dominant in the total size, and the latter includes gap width in the gear pump that is important for reducing power loss. We propose the hierarchical design to determine these parameters. In the macro-scale design, we determine the cylinder radius and differential pressure to maximize the efficiency-to-volume ratio. Based on the result of the macro-scale design, the micro-scale design determines the width of internal gaps to minimize the power loss in the gear pump. We derive mathematical formulations for the designs and develop the EHA by utilizing modular design and 3D printing. Moreover, we evaluate the fundamental properties of the developed EHA module, focusing on its power transmission efficiency and backdrivability.

GRAPHICAL ABSTRACT

Keywords:

• Electro-hydrostatic actuator
• hydraulic actuators
• efficiency

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Saint-Gobain Performance Plastics., ‘OmniSeal${}^{\circledR }$Product: Spring-Energized Seals,’ https://www.seals.saint-gobain.com/products/omniseal-spring-energized-seals.

2 ISO 3290-1:2014, Rolling bearings – Balls – Dimensions and tolerances.

3 JIS B 8265:2017, Construction of pressure vessel-General principles.

Additional information

Funding

This work was supported by the joint research of the University of Tokyo and Nachi-Fujikoshi CORP. titled “Development of an Electro-Hydrostatic Driven Robot System (High-Pressure Drive System/Hand /Manipulator)”.

Notes on contributors

Mitsuo Komagata

Mitsuo Komagata is Project Assistant Professor, Department of Mechano-informatics, University of Tokyo. He received his B.Eng., M.Eng., and Ph.D degrees in Mechano-Informatics from the University of Tokyo in 2014, 2016, and 2020, respectively. He was Project Researcher at the University of Tokyo (2020). His research interests include actuations and mechanical design. He is a member of IEEE, JSME, and RSJ.

Ko Yamamoto

Ko Yamamoto received the Ph.D. degree in mechano-informatics from the University of Tokyo, Tokyo, Japan, in 2009. He is an Associate Professor with the Department of Mechano-informatics, University of Tokyo. He was a Postdoctoral Research Fellow with the Tokyo Institute of Technology in 2009–2012, and an Assistant Professor with Nagoya University in 2012–2014. He joined the University of Tokyo as an Assistant Professor in 2014, and was a Project Lecturer with the Department of Mechanical Engineering in 2016-2017. He was also a Visiting Researcher with Stanford University, Stanford, CA, USA, in 2012. His research interests include mechanical design, dynamics computation and motion control of humanoid robots and soft robots, biomechanical analysis based on human musculo-skeletal model, and modeling and control of swarm robots and pedestrian crowds. Dr. Yamamoto is a Member of the Japan Society of Mechanical Engineers, the Robotics Society of Japan and IEEE.

Yoshihiko Nakamura

Yoshihiko Nakamura is Senior Researcher with Corporate Sponsored Research Program ‘Human Motion Data Science’, Research into Artifacts Center for Engineering, Graduate School of Engineering, University of Tokyo. He received Ph.d in 1985 from Kyoto University and held faculty positions in Kyoto University, University of California Santa Barbara and University of Tokyo. His fields of research started from redundancy of robot manipulators and kinodynamics of large DOF robot systems, and include humanoid robotics, cognitive robotics, neuro-musculo-skeletal human model, and their computational algorithms. He is a recipient of King-Sun Fu Memorial Best Transactions Paper Award, IEEE Transaction of Robotics and Automation in 2001 and 2002, JSME Medal for Distinguished Engineers in 2019, Pioneer Award of IEEE-RAS in 2021, and Tateisi Prize Achievement Award in 2022. Dr. Nakamura is Foreign Member of Academy of Engineering Science of Serbia, TUM Distinguished Affiliated Professor of Technische Universität München, Fellow of JSME, RSJ, and World Academy of Art and Science, Life Fellow of IEEE, and Professor Emeritus of University of Tokyo.