Active power optimization control of speed closed-loop engine for energy saving in hydraulic excavator

ABSTRACT

Most hydraulic excavators use passive power control to adjust the engine speed according to the load torque to achieve power matching, which has very limited effectiveness in energy saving. In this paper, an active power optimization control of speed closed-loop engine is proposed to improve its tracking performance for the dynamic energy-saving operating points. The inertia movement of the engine during variable speed control is analyzed to determine the kinetic energy requirements for different start and end operating points. An RBF-based neural network controller is designed based on power optimization to actively compensate the strong hysteresis of the engine speed relative to the optimal torque. The simulation and the experimental results show that the proposed control method has a much faster response for the energy-saving operating points, which reduces the energy consumption by 9.28% and 5.56% without adding any energy storage devices to the hydraulic excavator.

KEYWORDS:

• Energy conservation
• power matching
• hydraulic excavator
• active power optimization control
• inertia moment compensation

Disclosure statement

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

Additional information

Funding

We gratefully acknowledge the support by the National Key Research and Development Program of China through [Grant No. 2020YFB1709903] and the National Natural Science Foundation of China through [Grant No. 51975082].

Notes on contributors

Weiqi Sun

Weiqi Sun, is a doctor at the school of mechanical engineering, Dalian University of Technology. He is studying on measurement and control technology.

Yong Sang

Yong Sang, is a professor at the school of mechanical engineering, Dalian University of Technology. He received his M.S. degree in Mechatronics from Shandong University in 2004 and the PhD in Mechatronics from Beijing University of Aeronautics and Astronautics in 2007. He worked in the department of mechanical engineering as a postdoctoral researcher, University of Minnesota from Aug. 2012 to Dec. 2013. He is studying on advanced testing technique, hydraulic transmission and control.

Guoshuai Li

Guoshuai Li, is a graduate student at the school of mechanical engineering, Dalian University of Technology. He is studying on measurement and control technology.

Weiwei Liu

Weiwei Liu, received the PhD degree in mechanical engineering from Northeastern University, Shenyang, P.R. China, in 2009. He is currently an associate professor of mechanical engineering with Dalian University of Technology, Dalian, P.R. China. His research interests include intelligent manufacturing, green manufacturing, laser additive manufacturing. computer vision, and intelligent control.

Guofeng Li

Guofeng Li, is the head of Power Electronics, Machines and Electromagnetic Theory Group of Dalian University of Technology, P.R. China. He received the B.S. in Physics from Harbin Normal University in 1990, the M.S in Nuclear Physics form Northeast Normal University in 1993, and the Ph.D. degree in Chemical Engineering from the Dalian University of Technology in 2000. His research interests include numerical computation of electromagnetic equations, fault analysis and condition monitoring of electric machines, and power electronics.

Fuhai Duan

Fuhai Duan, is a professor at the school of mechanical engineering, Dalian University of Technology. He received his M.S. degree in vehicle guidance, navigation and control technology in 1996 and the PhD in 1999 from Northwestern Polytechnical University. He is studying on embedded computer testing technique, virtual instrument technology and precision control of servo motor.