Hydraulic Actuator Research Articles

Development of a pressure-, velocity-, and acceleration-dependent phenomenological friction model using experimental data of sliding tests between 11 polymers and stainless steel

This paper experimentally investigates the frictional behavior between stainless steel and 11 polymers. Particularly, the dependence of the friction coefficient on the sliding velocity, pressure, and acceleration is quantified. The novelty of this work lies in quantifying the acceleration-dependent nature of friction, correlating it to the well-documented Stick-Slip effect. The experimental setup consisted of two parallel stiff steel beams, one above the other, with a separation of 95 mm, and steel surfaces welded at the inner sides for sliding the polymers. Cylindrical polymer pads were placed between the stainless-steel surfaces and connected to a dynamic actuator to apply the displacement protocol. The protocol consisted of consecutive nominally constant-velocity ramp cycles covering velocities from 1 mm/s to 300 mm/s (with 20 mm/s increments). An additional vertical force was applied with a hydraulic actuator to reach nominal pressures in the polymers between 5 and 80 MPa. The results showed that the friction coefficient depends on the velocity, pressure, and acceleration of the motion, and a phenomenological model on these three variables is proposed. The velocity dependence can be represented through a logarithmic relationship, while the pressure dependence is through an exponential decay relationship. The acceleration dependence was represented through a linear relationship, which could capture the stick-slip effect. Overall, this work contributes to a better understanding of friction for seismic isolation systems. Since friction is the main source of energy dissipation in such structures, the proposed model will allow a higher accuracy in predicting variables of interest during the dynamic analyses of seismically isolated structures with frictional systems.

Adaptive sliding mode control with disturbance estimation for hydraulic actuator systems and application to rock drilling jumbo

For achieving high-performance control of hydraulic actuator systems, an adaptive sliding mode control with disturbance estimation algorithm is proposed and successfully applied to the hydraulic actuator systems of rock drilling jumbo. A switching extended state observer for hydraulic actuator systems is proposed, which combines the advantages of the linear extended state observer and the nonlinear extended state observer to estimate system disturbances more efficiently. The designed parameter adaptive law provides adaptivity to the system parameters, while the disturbance estimation algorithm can online estimate the unknown disturbances, such integration can enhance the adaptability and robustness of the sliding mode control algorithm. Rigorous simulation tests and practical application experiments are conducted to evaluate the performance of the proposed controller. The reliability of the designed parameter adaptive law and switching extended state observer is validated in detail in simulation studies. In the application experiments of rock drill jumbo, the results indicate the proposed controller is superior to sliding mode control with disturbance estimation and PID control. The average error of the developed controller is reduced by 58 %, 54 %, and 56 % compared to the sliding mode control with disturbance estimation controller, and 82 %, 78 %, and 79 % compared to the PID controller in tracking the low-frequency, high-frequency, and superimposed sinusoidal signals, respectively. Moreover, both the convergence of the uncertain parameters and the estimation of the unknown disturbances in the experiments are satisfactory. These experimental results adequately demonstrate the practical application value of the proposed controller.

The Optimization and Control of the Engagement Pressure for a Helicopter Dry Clutch

The engagement quality of a helicopter dry clutch has a significant impact on the service life and overall flight performance of the helicopter. The engagement oil pressure is an important factor affecting the clutch engagement quality. Firstly, a nonlinear input–output dynamic model for the dry clutch is developed to investigate the optimization and control of dry clutch engagement pressure in this paper. Secondly, to efficiently obtain the optimal pressure curve, an optimal method combining the developed dynamic model with the state feedback gain of a linear quadratic optimization regulator (LQR) solver is proposed. Thirdly, considering that hydraulic actuators may struggle with tracking certain pressure curves, a hydraulic actuator for accurately tracking pressure curves based on fuzzy PID is proposed. The simulation results indicate that the developed hydraulic actuator exhibits an excellent tracking performance. Moreover, compared with linear and segmented pressure curves, the optimal pressure curve derived from the proposed method significantly reduces jerk, friction work, and engagement duration, resulting in improved helicopter dry clutch engagement quality.

Fluidic Multichambered Actuator and Multiaxis Intrinsic Force Sensing.

Soft robots have morphological characteristics that make them preferred candidates, over their traditionally rigid counterparts, for executing physical interaction tasks with the environment. Therefore, equipping them with force sensing is essential for ensuring safety, enhancing their controllability, and adding autonomy. At the same time, it is necessary to preserve their inherent flexibility when integrating sensory units. Soft-fluidic actuators (SFAs) with hydraulic actuation address some of the challenges posed by the compressibility of pneumatic actuation while maintaining system compliance. This research further investigates the feasibility of utilizing the incompressible actuation fluid as the means of actuation and of multiaxial sensing. We have developed a hyperelastic model for the actuation pressure, acting as a baseline pressure. Any disparities from the baseline have been mapped to external forces, using the principle of pressure-based fluidic soft sensor. Computed tomography imaging has been used to examine inner deformation and validate the analytically derived actuation-pressure model. The induced stresses within the SFA are examined using COMSOL simulations, contributing to the development of a calibration algorithm, which accounts for geometric and cross-sectional nonlinearities and maps pressure variations with tip forces. Two force types (concentrated and distributed) acting on our SFA under different configurations are examined, using two experimental setups described as "Point Load" and "Distributed Force." The force sensing algorithm achieves high accuracy with a maximum absolute error of 0.32N for forces with a magnitude of up to 6N.

Design and testing of a high power piezo pump for hydraulic actuation

Traditional valve-controlled hydraulic cylinders are usually very inefficient due to power loss through the control valve. An efficient alternative architecture is to distribute power electrically rather than hydraulically to a group of cylinders and drive each cylinder via individual servomotor-driven pumps. This arrangement is called electrohydrostatic actuation. Such actuators are currently available for power ratings of several hundred watts or greater, but not in the sub-100 W range. This paper details the design, simulation and testing of a piezopump which is intended to address this gap. The motivation is for aerospace applications, and in particular accessory actuators used in the landing gear system. The 10–100 W range is a high-power output for a piezopump, and to achieve this a novel design using disc-style reed valves was developed to allow pumping frequencies above 1 kHz. These high frequencies necessitated the development of custom power electronics capable of delivering 950 V peak-peak sine wave excitation to a largely capacitive load. Experimental results show that the piezopump is capable of delivering over 30 W of hydraulic power, and at no-load can deliver up to 2 L/min of flow at 1250 Hz. Future development includes a transition to multi-cylinder pumps, and improved reed-valve modelling to improve the accuracy of simulated performance.

Full-scale hybrid fire test in real-time with multiple degree of freedom

To experimentally assess the fire resistance of civil structures, testing whole structures is very costly but the standard tests on individual structural elements can sometimes be too simplistic, regarding their boundary conditions. Hybrid fire testing offers a promising solution to these limitations, but performing such tests is technically challenging and few full-scale tests have been conducted. Current approaches rely on high-performance sensors and actuator systems, as well as assumptions about the stiffness of the tested element. This paper presents the detailed methodology and results of a full-scale, real-time test with 3 degrees of freedom on a concrete beam. The use of an adaptive controller allowed for maintaining stability and achieving reasonable precision despite the use of relatively low-precision sensors, regular hydraulic actuators, and no assumptions about the tested element’s stiffness. The comparison with the same element tested using a standard fire resistance test demonstrates the usefulness of this technique in achieving a more accurate representation of the performance of the tested element in realistic conditions.

A Comparative study of pseudoinverse and damped least squares approaches in inverse kinematics for a 5-DOF hydraulic arm

Abstract This paper presents a comparative study of two iterative methods for solving the inverse kinematics problem on a hydraulically actuated 5-DOF arm with non-standard geometries. The work aims to determine the joint angles required to achieve a desired end effector position and orientation, which indicates a specific displacement of the hydraulic actuators. A simulation model is used with the Pseudoinverse and damped least squares methods. The results show that using the model with both methods can be utilized to solve the inverse kinematics problem. The damped Least Squares method exhibits higher accuracy and robustness to singularities than the Pseudoinverse method, however, the Pseudoinverse method is more computationally efficient and can give results close to the damped least squares method but with some modifications. The paper concludes with implications of the findings and recommendations for future research, particularly in the application of these methods to real-world hydraulically actuated robotic systems.

Soft crawling caterpillar driven by electrohydrodynamic pumps

AbstractSoft crawling robots are usually driven by bulky and complex external pneumatic or hydraulic actuators. In this work, we proposed a miniaturized soft crawling caterpillar based on electrohydrodynamic (EHD) pumps. The caterpillar was mainly composed of a flexible EHD pump for providing the driving force, an artificial muscle for performing the crawling, a fluid reservoir, and several stabilizers and auxiliary feet. To achieve better crawling performances for our caterpillar, the flow rate and pressure of the EHD pump were improved by using a curved electrode design. The electrode gap, electrode overlap length, channel height, electrode thickness, and electrode pair number of the EHD pump were further optimized for better performance. Compared with the EHD pumps with conventional straight electrodes, our EHD pump showed a 50% enhancement in driving pressure and a 60% increase in flow rate. The bending capability of the artificial muscles was also characterized, showing a maximum bending angle of over 50°. Then, the crawling ability of the soft crawling caterpillar is also tested. Finally, our caterpillar owns the advantages of simple fabrication, low‐cost, fast movement speed, and small footprint, which has robust and wide potential for practical use, especially over various terrains.

A robot-assisted tracheal intubation system based on a soft actuator?

Tracheal intubation is the gold standard of airway protection and constitutes a pivotal life-saving technique frequently employed in emergency medical interventions. Hence, in this paper, a system is designed to execute tracheal intubation tasks automatically, offering a safer and more efficient solution, thereby alleviating the burden on physicians. The system comprises a tracheal tube with a bendable front end, a drive system, and a tip endoscope. The soft actuator provides two degrees of freedom for precise orientation. It is fabricated with varying-hardness silicone and reinforced with fibers and spiral steel wire for flexibility and safety. The hydraulic actuation system and tube feeding mechanism enable controlled bending and delivery. Object detection of key anatomical features guides the robotic arm and soft actuator. The control strategy involves visual servo control for coordinated robotic arm and soft actuator movements, ensuring accurate and safe tracheal intubation. The kinematics of the soft actuator were established using a constant curvature model, allowing simulation of its workspace. Through experiments, the actuator is capable of 90° bending as well as 20° deflection on the left and right sides. The maximum insertion force of the tube is 2N. Autonomous tracheal intubation experiments on a training manikin were successful in all 10 trials, with an average insertion time of 45.6s. Experimental validation on the manikin demonstrated that the robot tracheal intubation system based on a soft actuator was able to perform safe, stable, and automated tracheal intubation. In summary, this paper proposed a safe and automated robot-assisted tracheal intubation system based on a soft actuator, showing considerable potential for clinical applications.

Fully 3D-Printed Miniature Soft Hydraulic Actuators with Shape Memory Effect for Morphing and Manipulation.

Miniature shape-morphing soft actuators driven by external stimuli and fluidic pressure hold great promise in morphing matter and small-scale soft robotics. However, it remains challenging to achieve both rich shape morphing and shape locking in a fast and controlled way due to the limitations of actuation reversibility and fabrication. Here, fully 3D-printed, sub-millimeter thin-plate-like miniature soft hydraulic actuators with shape memory effect (SME) for programable fast shape morphing and shape locking, are reported. It combines commercial high-resolution multi-material 3D printing of stiff shape memory polymers (SMPs) and soft elastomers and direct printing of microfluidic channels and 2D/3D channel networks embedded in elastomers in a single print run. Leveraging spatial patterning of hybrid compositions and expansion heterogeneity of microfluidic channel networks for versatile hydraulically actuated shape morphing, including circular, wavy, helical, saddle, and warping shapes with various curvatures, are demonstrated. The morphed shapes can be temporarily locked and recover to their original planar forms repeatedly by activating SME of the SMPs. Utilizing the fast shape morphing and locking in the miniature actuators, their potential applications in non-invasive manipulation of small-scale objects and fragile living organisms, multimodal entanglement grasping, and energy-saving manipulators, are demonstrated.

Design of Variable Valve Timing and Electronic Control for Honda R18A

Abstract: This paper explores the Variable Valve Timing and Lift Electronic Control (VTEC) system developed by Honda, focusing on its mechanisms, design methodology, and impact on engine performance. VTEC optimizes engine efficiency and power by switching between cam profiles suited for low-RPM stability and high-RPM power output, controlled by the engine's computer based on operational conditions. We examine the intricate workings of the VTEC system, detailing its hydraulic actuation and the resulting enhancements in torque and horsepower. Our study centers on the Honda R18A engine, targeting increased maximum RPM and power output. Using theoretical analysis validated through Ricardo Wave software and MATLAB simulations, we determine optimal valve lift and timing to achieve the desired performance. Additionally, the research addresses the geometric parameters influencing airflow through the valves, providing a comprehensive understanding of the VTEC system's contribution to engine efficiency and driving experience. This investigation not only underscores the technological advancements in variable valve timing but also presents practical insights for automotive engineering applications.

Experimental assessment of stainless-steel wire mesh (SSWM) strengthened wet precast beam-column connections

Connections are important elements of precast structures as they introduce discontinuity between the elements affecting strength and stiffness. In the present study, locally available SSWM 40 × 32 is explored as a strengthening material for precast beam column connections. Experiments are conducted on test specimens to evaluate their performance under monotonic vertical loading applied using hydraulic actuator. Various wet precast connections with different location of connections and detailing of beam column reinforcement are considered for this investigation. Two novel SSWM configurations like enclosure of junction with box shape strip and diagonal strips of SSWM are used for strengthening of precast beam column connections. Experimental study is conducted on twelve test specimens to measure their performance in terms of ultimate load capacity, displacement profile, ductility, failure pattern and energy dissipation. SSWM strengthened specimens show 8–43 % improvement in load carrying capacity along with better ductility and energy dissipation. For the precast connections at junction, box shape SSWM strip configuration is recommended while for the connection at the face of column, diagonal strip configuration of SSWM is recommended. Overall, SSWM can be effectively used for strengthening of precast connections.

Adaptive neural tracking control for flexible joint robot including hydraulic actuator dynamics with disturbance observer

AbstractIn this paper, a disturbance observer‐based adaptive neural backstepping integral sliding mode control (BISMC) is developed for a flexible joint robot (FJR) with the integration of an adjustable stiffness rotary actuator (ASRA). This system suffers from unknown system dynamics, external disturbance, and the influence of variable stiffness, which is a challenge for achieving precision tracking performance. Considering the lumped disturbances in FJR generated by the hydraulic system and the stiffness modulation of the ASRA, we investigate the structural dynamics nonlinear model of the FJR system, including hydraulic actuator dynamics. While other linear control strategies are applied for the FJR, the proposed controller uses BISMC, neural networks (NN), and nonlinear disturbance observers to deal with the disadvantages mentioned above. Radial basis function neural networks (RBFNN) are designed to tackle unknown nonlinear functions, and the disturbance observers are introduced to compensate for the influence of the variable stiffness, disturbance, and the approximation error caused by NN. Simulations and experiments are independently implemented to demonstrate the effectiveness and feasibility of the proposed controller. Results exhibit that the integral absolute error‐index is reduced by 20.4% when the proposed method is deployed for the experiment with a multistep trajectory.

Conditional adaptive time series compensation and control design for multi-axial real-time hybrid simulation

The structural performance of critical infrastructure during extreme events requires testing to understand the complex dynamics. Shake table testing of buildings to evaluate structural integrity is expensive and requires special facilities that can allow for the construction of large-scale test specimens. An attractive alternative is a cyber-physical testing technique known as Real-Time Hybrid Simulation (RTHS), where a large-scale structure is decomposed into physical and numerical substructures. A transfer system creates the interface between physical and numerical substructures. The challenge occurs when using multiple actuators connected with a coupler (i.e., transfer system) to create translation and rotation at the interface. Tracking control strategies aim to reduce time delay errors to create the desired displacements that account for the complex dynamics. This paper proposes two adaptive control methodologies for multi-axial real-time hybrid simulations that improve capabilities for a higher degree of coupling, boundary, complexity, and noise reduction. One control method integrates the feedback proportional derivative integrator (PID) control with a conditional adaptive time series (CATS) compensation and inverse decoupler. The second proposed control method is based on a coupled Model Predictive Control (MPC) with the CATS compensation. The performance of the proposed methods is evaluated using the virtual multi-axial benchmark control problem consisting of a steel frame as the experimental substructure. The transfer system consists of a coupler that connects two hydraulic actuators generating the translation and rotation acting at the joint. Through sensitivity analysis, parameters were tuned for the decoupler components, CATS compensation, and the control design for PID, LQG, and MPC. Comparative results among different control methods are evaluated based on performance criteria, including critical factors such as reduction in the time delay of bothactuators. The research findings in this paper improve the tracking control systems for the multi-axial RTHS of building structures subjected to earthquake loading. It provides insight into the robustness of the proposed tracking control methods in addressing uncertainty and improves the understanding of multiple output controllers that could be used in future cyber-physical testing of civil infrastructure subjected to natural hazards.

Solar Tracking Methods: A Comprehensive Survey

Abstract: In the pursuit of maximizing solar energy utilization, solar tracking systems have emerged as indispensable tools for enhancing the efficiency of photovoltaic (PV) systems. This comprehensive survey delves into the multifaceted landscape of solar tracking methods, elucidating the diverse techniques and strategies employed in optimizing solar panel orientation relative to the sun's position Solar tracking systems are classified into two primary categories: single-axis and dual-axis tracking. Single-axis tracking systems adjust solar panels along one axis, typically the azimuth axis, while dual-axis tracking systems dynamically alter both azimuth and elevation angles to accurately follow the sun's apparent motion across the sky.Within the realm of solar tracking, passive and active tracking methods are explored. Passive tracking mechanisms rely on natural phenomena such as gravity or thermal expansion to adjust panel orientation, whereas active tracking systems employ mechanical, electrical, or hydraulic actuators driven by motors or other means to actively adjust panel angles based on real-time tracking algorithms.A pivotal aspect of solar tracking systems is the selection and implementation of tracking algorithms. Various algorithms, including sun position algorithms, maximum power point tracking (MPPT) algorithms, and predictive algorithms, are analyzed for their effectiveness in accurately predicting and optimizing solar panel orientation.Furthermore, this survey scrutinizes the role of sensor technologies in solar tracking, encompassing GPS-based tracking, light-intensity-based tracking, weather-based tracking utilizing meteorological sensors, and horizon tracking techniques. These sensor-based methodologies offer different advantages and trade-offs in terms of accuracy, cost, and reliability. To provide a comprehensive understanding, comparative analyses are conducted, evaluating the efficiency, cost-effectiveness, and energy yield of different tracking methods. These comparative assessments offer valuable insights into the performance characteristics and suitability of various tracking methodologies across diverse applications and environmental conditions.In conclusion, this survey serves as an invaluable resource for researchers, engineers, and policymakers involved in the design, development, and optimization of solar tracking systems for renewable energy applications. By synthesizing the latest advancements and comparative analyses, this survey facilitates informed decision-making and fosters the advancement of sustainable solar energy technologies.

SSFLNet: A Novel Fault Diagnosis Method for Double Shield TBM Tool System.

In tunnel boring projects, wear and tear in the tooling system can have significant consequences, such as decreased boring efficiency, heightened maintenance costs, and potential safety hazards. In this paper, a fault diagnosis method for TBM tooling systems based on SAV-SVDD failure location (SSFL) is proposed. The aim of this method is to detect faults caused by disk cutter wear during the boring process, which diminishes the boring efficiency and is challenging to detect during construction. This paper uses SolidWorks to create a complete three-dimensional model of the TBM hydraulic thrust system and tool system. Then, dynamic simulations are performed with Adams. This helps us understand how the load on the propulsion hydraulic cylinder changes as the TBM tunneling tool wears to different degrees during construction. The hydraulic propulsion system was modeled and simulated using AMESIM software. Utilizing the load on the hydraulic propulsion cylinder as an input signal, pressure signals from the two chambers of the hydraulic cylinder and the system's flow signal were acquired. This enabled an in-depth exploration of the correlation between these acquired signals and the extent of the tooling system failure. Following this analysis, a collection of normal sample data and sample data representing different degrees of disk cutter abrasions was amassed for further study. Next, an SSFL network model for locating the failure area of the cutter was established. Fault sample data were used as the input, and the accuracy of the fault diagnosis model was tested. The test results show that the performance of the SSFL network model is better than that of the SAE-SVM and SVDD network models. The SSFL model achieves 90% accuracy in determining the failure area of the cutter head. The model effectively identifies the failure regions, enabling timely tool replacement to avoid decreased boring efficiency under wear conditions. The experimental findings validate the feasibility of this approach.

An Improved Zero-Flowrate Switching Control Method to Reduce Switching Losses in a Hydraulic Actuator

Hydraulic switching actuators are high-efficiency, fast response, and low-cost solutions for hydraulic control systems. One of the challenging problems is throttling losses during valve transitions. Previously, the authors proposed a zero-flowrate switching method to reduce the throttling energy loss of the switching valve, where a hydraulic resonator is applied to make the flowrates through the lines approaching zero before the valves are switched off. The major challenge of this approach is fast switching valves whose transition times are less than 2 ms. In this paper, an improved zero-flowrate switching method is presented. It utilizes the capacity with independent inlet/outlet ports to regulate flowrates through the lines. Models of capacity applied in a simple line with different pressure signals are developed to explore characteristics of the capacity, based on which a complete actuation system is developed. In the complete model, resistance and inductance are optimized to achieve the desired flowrate response. The improved zero-flowrate switching method reduces throttling energy losses by 99.945% compared to a hard switching system. The simulation results demonstrated that the improved zero-flowrate switching method performs as expected in the design condition. A capacity with proper volume is able to regulate flowrates through all the lines to zero, with the help of appropriate resistance and inductance. Compared to the previous zero-flowrate switching method, the novel strategy allows slower switching valves applied in hydraulic actuation systems and achieves better efficiency performance. This research paves a new avenue for reducing throttling energy losses and improves system efficiency in hydraulic switching actuators, as well as most of the hydraulic switch-mode circuits.

Dynamic Modeling and Simulation of a Discrete Incremental Hydraulic Positioning System Controlled by Binary Valves

This article presents the conceptual design, operation principle, dynamic modeling, and simulation results of a discrete incremental hydraulic positioning system (DIHPS) intended for use in high-precision, heavy-load industrial automation solutions. An original solution for precise incremental step positioning using DIHPS is proposed, comprising an n-step linear double-acting hydraulic actuator (HA) with a double rod, cylinder sleeve with outflow gaps, binary valves (BVs) bleed-off into the tank, and fixed throttle valves (TRVs) at the inlets of the actuator chambers. The discrete incremental shift of the HA is determined by controlling the opening and closing of the individual BVs, and the step shift of the HA piston stops at the opening location of the BV. A dynamic model of incremental step shift for DIHPS is developed, considering the behavior and relationships of its individual elements. A dynamic model of HA with and without a hydropneumatic accumulator (HPA) is presented. HPA has been shown to effectively dampen piston vibrations and pressure peaks at the HA stop position. The design assumptions, dynamic models, and discrete incremental positioning of the DIHPS are verified by simulation tests and assessed with quantitative indicators. Innovative DIHPSs have significant practical potential in the discrete incremental positioning of heavy loads.

Adaptive Online Neural Predictive Control of Hydraulic Actuator Using FPGA Acceleration

Hydraulic actuators have recently been widely used in control systems as efficient output devices. However, high-precision control of hydraulic actuators in industrial applications remains challenging due to the conflict between controllers' complexity, especially in theoretical modeling, and their generalization abilities, including adaptability to parametric uncertainties and versatility for various working conditions. To address this issue, we propose an adaptive online neural predictive control (AONPC) scheme, which is capable of handling unmodeled nonlinearities and uncertainties with a simple structure and low demand for system modeling. Specifically, an artificial neural network (ANN) is responsible for data-driven system identification and predictive control, while upper confidence bound (UCB) algorithm is introduced for hyperparameter self-adaptation. The ANN structure and the iteration number for solving the optimization problem are determined through a simulation study. Then, to complete the whole control loop within a short and fixed tracking interval, the proposed controller is implemented on a field programmable gate array (FPGA), which can effectively improve the tracking precision. Finally, extensive experimental results on a realistic hydraulic actuator device demonstrate the superiority of the proposed controller.

Dynamic performance prediction and experimental analysis of wet clutch actuator considering thermal flow characteristics

The hydraulic actuator system (HAS) for wet clutches in heavy-duty vehicle transmissions is required to have a fast response and high precision in the pressure regulation procedure. Conventional pressure control valves for HAS are almost slide spool structures, which perform a large flow force at a high flow rate. An open-center spool structure is designed and developed in this paper, which is a combination of a traditional slide spool and a valve sleeve. It has an orifice-groove combination throttling orifice, which can take into account the large through-flow capacity and small flow force. Firstly, to deeply understand the mechanism of pressure variation in the clutch chamber, a high-fidelity dynamic characteristic mathematical model of HAS considering the oil temperature is proposed. Secondly, the functional relationship between the oil temperature on the medium physical property parameters and the orifice thermal flow parameters in the model is deduced in detail. An experimental bench to measure the pressure valve dynamic performance and actuator pressure regulation characteristics in a wide temperature domain is then designed and implemented to validate the accuracy of the simulation model. Finally, the mechanisms of oil temperature and system pressure on pressure impact and pressure response are quantitatively analyzed in association with a supervised learning algorithm. The feasible domains of the two adjustable variables are also explored. This study provides a new perspective on dynamic control and energy saving of HAS pressure valves and a new method for the prediction of HAS performance under complicated operating conditions.