Power management for multi-actuator mobile machines with displacement controlled hydraulic actuators

Economic and environmental factors provide the motivation for a continuing trend toward more energy efficient fluid power systems in construction and agricultural machinery. One of the energy-efficient alternatives to today\u27s valve-controlled hydraulic systems is displacement controlled (DC) actuation, in which hydraulic cylinders and motors are controlled directly by variable displacement pumps. The primary contribution of this thesis is a novel method for optimizing the operation of mobile machines with multiple DC actuators. The proposed power management method improves fuel economy by adjusting the operating points of the hydraulic pumps and diesel engine. The instantaneous rate of fuel consumption is minimized based on operator commands and detailed maps of pump and engine efficiency, including hydraulic energy recovery. Tradeoffs between dynamic response and steady-state efficiency are also considered. In order to facilitate real-time operation, the multi-actuator optimization problem is reduced to a one-dimensional minimization problem without compromising the solution. In support of the new power management method, nonlinear models are derived for variable displacement pumps and DC linear and rotary actuators. A sliding mode control law is proposed for robustly controlling pump displacement in spite of uncertain control pressure and swash plate moment. DC actuators operate in two modes, depending on the direction of the load. While actuating inertial loads, DC actuators can experience a limit cycle behavior with repeated switching between modes. Stability characteristics are analyzed. Stability can be assured by design (increasing damping or static load) or by feedback control. Robust control of pumps and actuators is demonstrated by simulation and experiment. A prototype 5-ton compact excavator was developed as part of the research. The DC excavator was fully instrumented for measuring energy efficiency and fuel consumption. The proposed power management algorithm reduced measured fuel consumption for a load-positioning duty cycle by 56% compared to the same system without optimization. Fuel measurements for a truck loading cycle yielded a 69% improvement in fuel efficiency (soil loaded per fuel consumed) compared to a conventional mini excavator