Pressure Control Algorithm Research Articles

Fusing crowdsourced data to an adaptive wireless traffic signal control system architecture

In this study, a novel wireless adaptive traffic signal control System architecture is proposed, in which crowdsourced data is integrated to detect the traffic state on each approach of an intersection. Under the wireless architecture, the green signal timing is calculated using a travel time-based Max Pressure control algorithm, which is performed on a single-board computer (SBC, RPi 4). The resulting green timings are sent from SBC to the master controller (ESP32) over serial UART and then to the slave (ESP32) wirelessly using ESP-NOW; slave ESP32 is placed on each approach of the intersection. It integrates a fail-safe mechanism to avoid any vehicular conflicts. The proposed system architecture also embeds a crowdsourced data-based pre-emption of intersections for efficient movement of emergency vehicles. The efficacy of the proposed system is compared using a simulation tool with real-world data. With respect to actuated and Max Pressure based on traffic flow, the proposed algorithm reduces the total delay by 54.8% and 22.96%, respectively. Further, the total queue dissipation time decreases by 8.32% and 5.45%, respectively. It outperforms the actuated signal control as well as Max Pressure based on traffic flows. The capability of transforming existing traffic signal controllers into wireless adaptive traffic signal control systems makes it a very affordable and scalable solution.

A Review of One-Box Electro-Hydraulic Braking System: Architecture, Control, and Application

With the development of automobile electrification and intelligence, new requirements have been put forward for automotive braking technologies. Under this background, the One-box EHB (Electro-Hydraulic Braking system) brake-by-wire technology has emerged, which combines the electric booster and wheel-cylinder control module into one box and can realize vehicle stability and comfort functions such as service brake, pedal feel simulation, brake decoupling, failure backup, active braking, and wheel-cylinder pressure control. This article reviews the current research of key technologies of One-box EHB, including system architecture design and applications under high-level autonomous driving, master cylinder pressure control algorithm design, wheel-cylinder pressure control algorithm design, and electro-hydraulic composite braking control algorithm design. Finally, this article summarizes the current research status of One-box EHB key technologies and puts forward suggestions for future research directions.

Finite element simulations and experimental investigations on formability of magnesium alloys in superplastic forming

The paper presents the formability aspects of magnesium alloy (AZ31B) sheets into regular and intricate shapes during Super Plastic Forming (SPF). Finite Element (FE) simulations are performed at specific strain rates within the superplastic temperature range. The formability of 1 mm sheet into conical, cylindrical, box and groove shaped dies are simulated. The simulated Pressure-Time (P-T) curve is given as pressure control algorithm to form the shapes experimentally. Thickness strains of the experimentally formed components validated with simulation results are found to be in close agreement with each other. It is demonstrated by the analysis that regular shapes posses uniform thickness distribution throughout the profile. The components with complex intricate shapes recorded unevenness in thinning behavior. The unevenness in thinning is influenced by the Grain Boundary Sliding (GBS) and diffusion kinetics. GBS is well controlled by optimum P-T algorithm to produce sharp intricate shapes with uniform thickness.

Combined extreme learning machine and max pressure algorithms for traffic signal control

Nowadays, rush-hour traffic congestion problems persist in most major cities around the world, resulting in increased pollution, noise, and stress for citizens. Therefore, an optimal traffic light strategy is needed. For this purpose, several models have been proposed. However, these models often overlook the non-stationarity of traffic, which occurs due to changing traffic conditions over time. Additionally, these models are steady-state process models, leading to a decrease in their predictive power over time. To address these issues, this paper proposes the combination of two algorithms: a passive Extreme Learning Machine with periodic mini-batch learning (PB-ELM) for predicting traffic flow and the Max Pressure control algorithm (MPA) for signal control. In the first step, the passive periodic Extreme Learning Machine (PB-ELM) adjusts quickly and regularly based on new data, overcoming traffic non-stationarity and improving long-term performance. In the second step, the MPA is preferred for signal control due to its simplicity and speed. The PB-ELM-MPA model is a combination of predictive algorithms that takes the current road network conditions as input and predicts the flow of vehicles at intersections. The model utilizes learned characteristics of the source and destination roads to estimate the number of vehicles in each movement. The PB-ELM outputs serve as the starting point for the max-pressure algorithm, which reduces congestion by considering only the vehicles on road segments closest to the intersection and selecting the highest pressure at each time interval. The proposed PB-ELM-MPA model is evaluated on an isolated intersection simulated with the SUMO micro-simulator, demonstrating a significant improvement in avoiding traffic jams. The total staying time of all vehicles present at the intersection is reduced by 65% compared to the fixed configuration of traffic lights. Additionally, CO2 emissions and fuel consumption are reduced by approximately 34% compared to the classic MPA and Deep Q-Network approaches.

Study on the control mode of proton membrane fuel cell system

In the era of energy shortage, proton membrane fuel cell using hydrogen as energy source has attracted great attention because of its advantages of zero emission and high energy conversion efficiency. Hydrogen supply system is an important part of fuel cell system. Efficient hydrogen supply system can improve hydrogen utilization rate and relieve anode flooding and hydrogen hunger with optimal exhaust drainage time. At the same time, the pressure difference between cathode and anode must be maintained within a certain range when proton membrane fuel cells are running. Reasonable pressure control algorithm can improve the safety and stability of proton membrane fuel cells. In this paper, based on the model of the total fuel cell system, the anodic fuzzy PID pressure control algorithm and the cathode fuzzy PID pressure following control algorithm for proton membrane fuel cells are designed, and the effectiveness of the fuel cell pressure control algorithm is studied through simulation analysis.

(Invited) Key Aspects in Enabling Lithium Metal Batteries

Lithium metal batteries hold the promise for next generation rechargeable batteries. The recent breakthroughs in electrolyte formation, pressure control algorithm and quantitative characterization tools have made this promise closer to reality. In this talk, I will provide an overview of those recent breakthroughs and share a few new perspectives on the surprisingly challenging issues in enabling rechargeable lithium metal batteries.

Monitoring, Control System Development, and Experimental Validation for a Novel Extrapulmonary Respiratory Support Setup

This article presents a novel mechatronic setup intended for providing respiratory support to patients suffering from pulmonary failure. The setup relies upon the circulation of an oxygenated perfluorocarbon (PFC) through the abdominal cavity. Such circulation provides a potential pathway for the transport of oxygen to the bloodstream. However, the viability of this technology for <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{CO}_2$</tex-math></inline-formula> clearance has not been established. Moreover, there is a lack of experimental data enabling the modeling and identification of the underlying dynamics of this technology. To address these gaps, we develop a flexible experimental perfusion setup capable of monitoring and controlling key variables, such as perfusate flowrate, temperature, pressure, and oxygenation. One important scientific objective of this setup is to enable the measurement of the impact of abdominal PFC perfusion on <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{CO}_2$</tex-math></inline-formula> clearance. The article 1) summarizes the design of this setup; 2) highlights the degree to which its data acquisition system enables the collection and cross-correlation of both perfusion-related and physiological variables; and 3) discusses the development of flow, pressure, and temperature control algorithms for the setup. Experiments with large animals (swine) show that perfusion can potentially affect both <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{O}_2$</tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{CO}_2$</tex-math></inline-formula> dynamics, and that the setup succeeds in recording key data needed for modeling these dynamics.

Combined dynamic operation of PEM fuel cell and continuous dehydrogenation of perhydro-dibenzyltoluene

Hydrogen storage in liquid organic hydrogen carriers (LOHC) such as the substance system dibenzyltoluene/perhydro-dibenzyltoluene (H0/H18-DBT) offers a promising alternative to conventional methods. In this contribution, we describe the successful demonstration of the dynamic combined operation of a continuously operated LOHC reactor and a PEM (polymer exchange membrane) fuel cell. The fuel cell was operated stable with fluctuating hydrogen release from dehydrogenation of H18-DBT over a total period of 4.5 h, reaching electrical stack powers of 6.6 kW. The contamination with hydrocarbons contained in the hydrogen after activated carbon filtering did not result in any detectable impairment or degradation of the fuel cell. The proposed pressure control algorithm based on a proportional integral (PI) controller proved to be a robust and easy-to-implement approach to enable the dynamic combined operation of LOHC dehydrogenation and PEM fuel cell.

Large-Scale Molecular Dynamics Simulations Reveal New Insights Into the Phase Transition Mechanisms in MIL-53(Al)

Soft porous crystals have the ability to undergo large structural transformations upon exposure to external stimuli while maintaining their long-range structural order, and the size of the crystal plays an important role in this flexible behavior. Computational modeling has the potential to unravel mechanistic details of these phase transitions, provided that the models are representative for experimental crystal sizes and allow for spatially disordered phenomena to occur. Here, we take a major step forward and enable simulations of metal-organic frameworks containing more than a million atoms. This is achieved by exploiting the massive parallelism of state-of-the-art GPUs using the OpenMM software package, for which we developed a new pressure control algorithm that allows for fully anisotropic unit cell fluctuations. As a proof of concept, we study the transition mechanism in MIL-53(Al) under various external pressures. In the lower pressure regime, a layer-by-layer mechanism is observed, while at higher pressures, the transition is initiated at discrete nucleation points and temporarily induces various domains in both the open and closed pore phases. The presented workflow opens the possibility to deduce transition mechanism diagrams for soft porous crystals in terms of the crystal size and the strength of the external stimulus.

Research on Pressure Control Algorithm of Regenerative Braking System for Highly Automated Driving Vehicles

Conclusive evidence has demonstrated the critical importance of highly automated driving systems and regenerative braking systems in improving driving safety and economy. However, the traditional regenerative braking system cannot be applied to highly automated driving vehicles. Therefore, this paper proposes a fully decoupled regenerative braking system for highly automated driving vehicles, which has two working modes: conventional braking and redundant braking. Aimed at the above two working modes, this paper respectively proposes the pressure control algorithm, based on P-V characteristics, and the pressure control algorithm, based on the overflow characteristics of the solenoid valve. AMESim is utilized as the simulation platform, and then is co-simulated with MATLAB/Simulink, which is embedded with the control algorithm. The simulation results show the feasibility and effectiveness of the regenerative braking system and the pressure control algorithm.

The Control System of a Robot Bed for Caring Pressure Ulcer

The medical bed developed in this study is an electrically driven segmental keyboard. First describe the instrument of the segmental bed specially designed for pressure ulcer prevention, then the motor control system and pressure ulcer prevention operation of the bed. The main factor of pressure ulcer generation is displayed as body pressure x time, and when the keyboard falls, the body pressure becomes zero, and the pressure becomes higher than the threshold even if the body pressure is above the threshold, the pressure control algorithm has been developed. Therefore, using the proposed pressure control method, it has no particular ulcer occurred theoretically.

Bi-objective optimisation based tuning of pressure control algorithms for water distribution networks

With the application to water industry of the Industry 4.0 approach (i.e. the Water 4.0 approach), Real Time Control is gaining attention as a strategic tool for the management of Water Distribution Networks. Moreover, this approach favours the installation of a wired communication infrastructure, which guarantees new standards in communication between sensors, actuators and control units. This work focuses on the particular task of service pressure regulation, obtained by means of a closed-loop control based on Pressure Control Valves and frequency domain control algorithms. While the topics of the identification of proper control structures, and the analysis of their stability and robustness properties were covered in previous works, this paper is aimed at improving the design phase of such algorithms by formulating the regulator tuning problem as a bi-objective optimisation one. Its solution leads to a Pareto front that captures the typical design trade-off between regulation performances and control effort and robustness, and helps the designer selecting the favoured tunings to be tested on the plant. Simulations performed on a detailed model of two different WDNs highlight the benefits of the approach and the reliability of the obtained tunings.

Pressure Estimation and Pressure Control of Hydraulic Control Unit in Electric-Wheel Vehicle

In order to improve the braking performance and safety performance of electric vehicles driven by a hub motor, the cylinder pressure estimation and pressure control of its hydraulic braking system are studied. In this paper, a mathematical model is established for the solenoid valve, a key component of the hydraulic actuator, and the hydraulic and electrical characteristics of the solenoid valve are studied. A state equation is established for the solenoid valve, and the square root volume Kalman filter (SRCKF) algorithm is used to estimate the solenoid valve spool position. The brake fluid flow and brake wheel cylinder pressure are calculated based on the spool position. Finally, a solenoid valve spool position control algorithm based on sliding mode variable structure algorithm is designed, and the brake pressure in the brake wheel cylinder is controlled by adjusting the spool position. Matlab/Simulink-AMESim software simulation and hardware-in-the-loop were used to verify the algorithm. Simulation results show that the brake cylinder pressure can be estimated accurately, and the pressure control algorithm can accurately follow the control target value.

Pressure Control Algorithm Based on Adaptive Fuzzy PID with Compensation Correction for the Tractor Electronic Hydraulic Hitch

In order to realize the pressure control of the tractor electronic hydraulic hitch in the fields, the pressure control algorithm is essential. In this study, combining the kinematics model with the dynamic model of ploughing and the hydraulic system model, an adaptive fuzzy PID controller is proposed to adjust the real-time data of the PID parameters for the pressure control of the tractor electronic hydraulic hitch. The feasibility of the proposed controller was verified by simulation. Next, a pressure control experimental with the real vehicle experiment platform was carried out under three control algorithms of the traditional PID, the traditional PID with compensation correction and the adaptive fuzzy PID with compensation correction in verifying the pressure control effect of the tractor in different controllers. When the system was stable, the experimental results showed that the input was 1.5 MPa step signal with response time in the traditional PID controller of 2.5 s, fluctuation range of 0.5 MPa. However, the response time in the adaptive fuzzy PID with compensation correction was 1.5 s, fluctuation range of 0.3 MPa. The responding time was 40% lower, and the pressure fluctuation range was reduced by 40%. In conclusion, the proposed algorithm successfully realized the pressure control of the tractor. The proposed adaptive fuzzy PID with compensation correction in this paper has a better dynamic performance.

Torque Coordination Control of an Electro-Hydraulic Composite Brake System During Mode Switching Based on Braking Intention

The electro-hydraulic composite braking system of a pure electric vehicle can select different braking modes according to braking conditions. However, the differences in dynamic response characteristics between the motor braking system (MBS) and hydraulic braking system (HBS) cause total braking torque to fluctuate significantly during mode switching, resulting in jerking of the vehicle and affecting ride comfort. In this paper, torque coordination control during mode switching is studied for a four-wheel-drive pure electric vehicle with a dual motor. After the dynamic analysis of braking, a braking force distribution control strategy is developed based on the I-curve, and the boundary conditions of mode switching are determined. A novel combined pressure control algorithm, which contains a PID (proportional-integral-derivative) and fuzzy controller, is used to control the brake pressure of each wheel cylinder, to realize precise control of the hydraulic brake torque. Then, a novel torque coordination control strategy is proposed based on brake pedal stroke and its change rate, to modify the target hydraulic braking torque and reflect the driver’s braking intention. Meanwhile, motor braking torque is used to compensate for the insufficient braking torque caused by HBS, so as to realize a smooth transition between the braking modes. Simulation results show that the proposed coordination control strategy can effectively reduce torque fluctuation and vehicle jerk during mode switching.

Effects of various operating conditions on the performance of a CO2 air conditioning system for trains

This paper aims to investigate the effects of different operating parameters on the performance of a transcritical CO2 air conditioning system for trains. Similar designs of automotive CO2 air conditioning system are used in the train system such as internal heat exchanger (IHX) to improve the system efficiency. Experimental results are presented for the performance characteristics of the CO2 train air conditioning system with two independent circuits under different test conditions such as different refrigerant charge amount, compressor working frequency, indoor air volume flow rate and outdoor chamber temperature. Two different operating modes of the two circuits are also included in this research. For mode I while only one circuit is working, the test results show that the maximum cooling capacity and coefficient of performance (COP) is 24.3 kW and 2.7, during 55 Hz and 40 Hz compressor working frequency conditions respectively. Also, the cooling capacity and COP reach the minimum, 16.2 kW and 1.5, when the outdoor chamber temperature is 45 °C. For mode II while both two circuits are working, the results show that the cooling capacity and COP are 42.0 kW and 2.4, respectively. The system performance error between the test and numerical modeling which directs the design of the system is within ±5%. Furthermore, an optimum high pressure control algorithm for the transcritical CO2 cycle of the train AC system is also presented.

Prediction of superplastic forming of 7475 aluminium alloy sheets

Superplastic forming is mainly used in the aeronautic and astronautic domains and to fabricate the complex shape parts with the materials hard to process. The numerical simulation is used to predict the superplastic forming process due to the difficulty to predict a forming pressure by a traditional trial and error method. In the article, the superplastic behaviour of a 7475 aluminium alloy has been investigated. Uniaxial tensile tests over a wide range of temperatures and strain rates have been performed. An Arrhenius-type model using strain compensation has been identified. A failure criterion based on the evolution of fracture work is also proposed. This material model has been implemented by user subroutine in numerical simulations (ABAQUS) to predict the ability of the material to form a complex revolution part by superplastic forming. A pressure control algorithm has been developed to minimize the pressure instability and decrease the simulation CPU time. The numerical results, in terms of thickness evolution in the formed component and location of damage-risk zones, have finally been compared to experimental results after the realization of some bulging experiments using the generated pressure cycle.

A Novel Pneumatic Brake Pressure Control Algorithm for Regenerative Braking System of Electric Commercial Trucks

Since the control of brake pressure has a significant impact on regenerative braking performance of electric vehicles, a novel combined brake pressure control algorithm based on two high-speed on-off valves is developed to improve the precision and timeliness of pressure tracking for the regenerative braking system of electric commercial trucks in this paper. First, a comprehensive mathematical model of the valve control system is built up which is composed of several sub-models and verified by experiments. Second, a PID controller with pulse width modulation (PWM) and a fuzzy controller with cooperative PWM are separately adopted in the proposed combined control algorithm to substitute for the traditional PWM approach. Moreover, through the numerical simulation studies, better control performance is obtained in MATLAB/Simulink on the basis of the built models. Finally, the experimental tests under various typical braking pressure input signals are carried out to verify the simulation results. The comparison between the simulation and experimental results fully demonstrates that the proposed control algorithm is feasible and the dynamic performance of this combined valve control algorithm is considerably improved compared with the conventional PID control algorithm.

An Improved Model Combining Evolutionary Algorithm and Neural Networks for PV Maximum Power Point Tracking

Aiming at the large error of the traditional constant control method in predicting the maximum power of solar UAV, this paper proposed an improved mind evolutionary algorithm combined with BP neural network (BPNN), in which the improved mind evolutionary algorithm optimizes the BPNN. The optimized model is used to predict the voltage at the maximum power of the panel in the UAV. The constant voltage parameter based on the conventional constant pressure control algorithm is replaced by this value. At the same time, a new control simulation model of constant voltage solar panel maximum power tracking based on the improved mind evolution algorithm optimize BPNN was built. At last, the algorithm was simulated and validated in the MATLAB/Simulink environment. The simulation results show that this algorithm is better than simply using BPNN and genetic algorithm optimize BPNN stability and higher accuracy.

Development of Wheel Pressure Control Algorithm for Electronic Stability Control (ESC) System of Commercial Trucks.

This paper presents a wheel cylinder pressure control algorithm for application to the vehicle electronic stability control (ESC) systems for commercial trucks. An ESC system is an active system that improves the driving stability by distributing the appropriate braking pressure to each wheel, which is an essential system for safe driving. It is important that the ESC system, through proper braking pressure supply, delivers the correct pressure under control. However, to reduce the cost involved, commercial trucks use a solenoid valve of the on/off-type, rather than a proportional valve that has good pressure control capability. The performance of a proposed wheel pressure control system based on an on/off solenoid valve control was verified by means of experiments conducted using the wheel pressure control algorithm presented in this paper.