Energy Efficiency Improvement of Heavy-Load Mobile Hydraulic Manipulator with Electronically Tunable Operating Modes

The conventional hydraulic drive system for a heavy-load mobile manipulator is usually operated under single mode, such that both inlet/outlet and potential energy losses are large to lower the energy efficiency. In this paper, a novel electro-hydraulic drive system is presented to improve energy efficiency. Extended control degrees of freedom are obtained utilizing the independent metering valve and electronic controlled pump. Then, multiple operating modes are carried out pertaining to the cylinder, valve, and pump. To achieve both optimal energy efficiency and precise motion tracking, both multi-mode switching and multi-variable controller are designed to accommodate with time-varying and uncertain load characteristics. As a consequence, the inlet, outlet, and potential energy losses can be decreased simultaneously. The experimental validation is conducted by using a three-joint manipulator in a 2 t excavator. A duty cycle of movement including all three actuators and covering full load quadrants is used to evaluate the efficiency improvement. Compared with the conventional load sensing system, the proposed multi-mode switching system using the pump pressure with valve meter-in control mode yields a 25.8% energy-saving ratio. Furthermore, the pump flow with valve mete-out control mode yields a 35.3% energy-saving ratio. Using this combined control mode, higher efficiency can be obtained due to the minimum inlet losses, but faster dynamic response together with higher overshoot will appear. It is proved that the energy efficiency is improved, while the motion tracking performance is not degraded by introducing the multi-mode switching

High-Precision and Modular Decomposition Control for Large Hydraulic Manipulators

It is difficult to achieve a high-precision motion control in hydraulic manipulators due to their structural redundancy, strong coupling of closed-chain structures, and flow–pressure coupling. In this paper, a high-precision motion control method for hydraulic manipulators is proposed based on the traditional virtual decomposition control (VDC). The method proposed avoids an excessive virtual decomposition of the hydraulic manipulator and requires fewer model parameters than the traditional VDC. Further, the control precision improved by combining an adaptive real-time update of the inertial parameters. Compared with MBC, the proposed control method improved the motion accuracy of the hydraulic manipulator by more than 40% and 20% under elliptical and triangular trajectories. The simulation results showed that the proposed control method reduced the maximum position errors in Cartesian space by 90.4%, 86.8%, 23.6%, and 44.3% compared with PID and model-based control (MBC) in the absence of disturbances. The maximum position error in Cartesian space was reduced by 76.5% compared with that of MBC in a simulation with external disturbances. It can be seen from all the simulation results that with the proposed control method, the position error of the manipulator was less than 50 mm. The proposed control method effectively improved the motion precision of the examined hydraulic manipulator

Real-Time Anti-Saturation Flow Optimization Algorithm of the Redundant Hydraulic Manipulator

As a typical single-pump multi-actuator system, the hydraulic manipulator faces the flow saturation problem when moving at a high speed to track a desired trajectory. To overcome this problem, this paper proposes a real-time anti-saturation flow optimization algorithm based on the gradient projection method. By projecting the gradient of the demand flow in the null space of the task Jacobians, this algorithm can reduce the flow demand while enforcing a global volumetric flow limit in real time. The model of a 7-degree-of-freedom (DOF) hydraulic redundant manipulator was established to carry out theoretical derivation and algorithm design. Then, the experimental verification was completed on the real manipulator platform. Experimental results show that this algorithm reduces average demand flow by 9.85% and average power consumption by 310.3 W under no saturation condition. When flow saturation occurs, the algorithm can increase the average endpoint velocity by 7.52% and reduce the maximum directional error by 71.73% with an average calculation time step of 3 ms. The average trajectory position error can also be reduced by 42.59% compared with the anti-saturation algorithm. Therefore, the proposed algorithm can achieve real-time optimization to reduce flow consumption and achieve anti-saturation in practical applications of redundant hydraulic manipulator

Real-Time Anti-Saturation Flow Optimization Algorithm of the Redundant Hydraulic Manipulator

As a typical single-pump multi-actuator system, the hydraulic manipulator faces the flow saturation problem when moving at a high speed to track a desired trajectory. To overcome this problem, this paper proposes a real-time anti-saturation flow optimization algorithm based on the gradient projection method. By projecting the gradient of the demand flow in the null space of the task Jacobians, this algorithm can reduce the flow demand while enforcing a global volumetric flow limit in real time. The model of a 7-degree-of-freedom (DOF) hydraulic redundant manipulator was established to carry out theoretical derivation and algorithm design. Then, the experimental verification was completed on the real manipulator platform. Experimental results show that this algorithm reduces average demand flow by 9.85% and average power consumption by 310.3 W under no saturation condition. When flow saturation occurs, the algorithm can increase the average endpoint velocity by 7.52% and reduce the maximum directional error by 71.73% with an average calculation time step of 3 ms. The average trajectory position error can also be reduced by 42.59% compared with the anti-saturation algorithm. Therefore, the proposed algorithm can achieve real-time optimization to reduce flow consumption and achieve anti-saturation in practical applications of redundant hydraulic manipulator

Soft computing-based predictive modeling of flexible electrohydrodynamic pumps

Flexible electrohydrodynamic (EHD) pumps have been developed and applied in many fields due to no transmission structure, no wear, easy manipulation, and no noise. Physical simulation is often used to predict the output performance of flexible EHD pumps. However, this method neglects fluid–solid interaction and energy loss caused by flexible materials, which are both difficult to calculate when the flexible pumps deform. Therefore, this study proposes a flexible pump output performance prediction using machine learning algorithms. We used three different types of machine learning: random forest regression, ridge regression, and neural network to predict the critical parameters (pressure, flow rate, and power) of the flexible EHD pump. Voltage, angle, gap, overlap, and channel height are selected as five input data of the neural network. In addition, we optimized essential parameters in the three networks. Finally, we adopt the best predictive model and evaluate the significance of five input parameters to the output performance of the flexible EHD pumps. Among the three methods, the MLP model has exceptionally high accuracy in predicting pressure and flow. Our work is beneficial for the design process of fluid sources in flexible soft actuators and soft hydraulic sources in microfluidic chips

3D Printing for Energy-Saving: Evidence from Hydraulic Manifolds Design

With the compact circuit layout and small size, hydraulic manifolds sometimes cause high pressure loss. The purpose of this paper is to investigate the pressure loss under different circumstances with various geometry features and present solutions to reduce pressure loss. The pressure loss performance is evaluated by both experimental and numerical methods. Verified by the experiments, the numerical simulations are qualified to depict the correct trend of the pressure drop. After the basic analysis of traditional passages, three novel forms are proposed, which are very hard to be manufactured by a common method. Furthermore, the geometrical features are selected optimally by means of full factorial experiments to balance the pressure loss and space requirement. Moreover, taking advantage of 3D printing, it is possible to build the passages in novel forms which are beyond the capacity of conventional manufacturing. Results show that the pressure loss can be reduced considerably by adopting a smooth transition, where the reduction can reach up to 50%