Co-simulation Model Research Articles

Research on the Optimization of the PID Control Method for an EOD Robotic Manipulator Using the PSO Algorithm for BP Neural Networks

Large-scale explosive ordnance disposal (EOD) robotic manipulators can replace manual EOD tasks, offering higher efficiency and better safety. This study focuses on the control strategies and response speeds of EOD robotic manipulators. Using Adams to establish the dynamic model of an EOD robotic manipulator and constructing a hydraulic system model in AMEsim, a co-simulation model is integrated. This study proposes a PID control strategy optimized by the particle swarm optimization (PSO) algorithm for a backpropagation (BP) neural network and simulates the system’s step response for analysis. To address the vibration issues arising during the manipulator’s motion, B-spline curves are used for trajectory optimization to reduce vibrations. The PSO algorithm optimizes the connection weight matrix of the BP neural network, solving the potential problem of local minima during the training process of the BP neural network, thereby enhancing the global search capability, learning efficiency, and network performance. Simulation results indicate that compared to traditional BP+PID control, genetic algorithm (GA)+PID control, and whale optimization algorithm (WOA)-BP+PID control, the PSO-BP+PID algorithm control rapidly tunes the PID control parameters Kp, Ki, and Kd. Under the same step function conditions, the overshoot is only 1.37%, significantly lower than other methods, and the settling time is only 14 s. After stabilization, there is almost no error, demonstrating faster response speed, higher control accuracy, and stronger robustness. This research has theoretical value and reference significance for the control methods and improvements in EOD robotic manipulators.

Design and Testing of a 2-DOF Adaptive Profiling Header for Forage Harvesters

The existing forage harvester header cannot automatically adjust the height and inclination during operation, resulting in uneven stubble height of forage, which, in turn, affects the efficiency of harvesting and the quality of forage regeneration. To address this issue, this study conducted the design and experimentation of a 2-degrees-of-freedom (DOF) profiling header. Firstly, this study designed an adaptive profiling header with 2-DOF adjustment, which was realized by the height adjustment mechanism and the tilt angle adjustment mechanism. The relationship model between the profiling device and the attitude of the header was established so that the header can acquire ground undulation in real time through the angle sensor of the profiling device. In order to verify the rationality of the header design, a co-simulation model of ADAMS and MATLAB/Simulink was built, and the header attitude control system was designed based on the fuzzy PID algorithm. The co-simulation results show that the header height (H) is always kept around 150 mm during the forwarding process of the harvester, with a maximum error of 5.8 mm, and the average relative error (REH) and root mean square error (RMSEH) were 1.4% and 2.6 mm, respectively, and the maximum error of the tilt angle (γ) of the header is 0.53° and the RMSEγ is 0.22°, which indicates that the header profiling mechanism can accurately reflect the undulation of the terrain and the header attitude control system has good robustness. Finally, the test platform was built and tested in a grassland. The test results show that the average height of the header is 149.8 mm, the maximum error is 7.5 mm, and the REH and RMSEH are 3.4% and 5.3 mm, respectively. The average error of the header inclination is 0.34°, and the maximum error is 0.57°. The test results indicate that the header can realize the adaptive adjustment of height and inclination, and the control system has high precision, stability and reliability, meeting the demand of automatic regulation of header attitude of a forage harvester.

Improved high temperature energy storage density and efficiency of polyimide nanocomposites via hindering charge and molecular motions

Electric vehicles and renewable energy consumption have huge demands for high-performance polymer dielectric capacitors. However, the resistivity and breakdown strength of existing polymer dielectrics deteriorate significantly at high temperatures, reducing the energy storage density and charge-discharge efficiency of capacitors below service requirements. The charge transport and molecular chain motion characteristics in linear polymers determine their conductivity, breakdown, and energy storage properties, but the quantitative relationship between them is not clear. An in-situ polymerization method was used to prepare polyimide/Al2O3 nanocomposites (PI/Al2O3 PNCs). Experimental results show that the resistivity, breakdown strength, energy storage density, and charge-discharge efficiency of PNCs increase initially and then decrease with increasing doping content, peaking at 3 wt%. The discharged energy density of PI/Al2O3-3 wt% PNCs at 180°C is 207.52 % higher than pure PI. A conductance-breakdown-energy storage co-simulation model based on charge transport and molecular chain displacement was used to simulate the voltage-current, breakdown, and energy storage characteristics of PNCs. The simulation results are consistent with the experiments. Comparative studies between simulation and experiments show that the independent interface zone between nanofillers and PI hinders charge transport and molecular chain movement, reducing electric field distortion and molecular chain spacing, thereby improving high-temperature breakdown and energy storage performance of PNCs.

Research on the traction characteristic evaluation of urban rail vehicles based on entropy weight TOPSIS

This paper aims to investigate the influence of different speed at the end of the constant power section of the traction characteristic curve (TCC) on the vehicle dynamic performance and evaluate the TCC. A dynamics co-simulation model is developed in SIMPACK and MATLAB for dynamic analysis of the urban rail vehicle (URV) under different traction characteristics. Then it is used to investigate how acceleration distance and vehicle dynamic performance varies with the speed at the end of the constant power section of the TCC under different starting torques. Moreover, the entropy weight TOPSIS method which is widely used to solve the multi-objective decision-making problem is chosen to evaluate the traction characteristics based on various dynamic performance indexes over 25 test sections and acceleration distance. The results show that under traction conditions, the starting torque has effects on the lateral and vertical accelerations of car body, lateral and vertical wheel-rail contact forces, derailment coefficient and wheel unloading factor. The higher the torque, the greater the value of each index, that means the poorer the vehicle ride characteristics and running safety. For a given starting torque, the dynamic performance indexes increase with the increase of the speed at the end of the constant power section from 50 km/h to 80 km/h during the vehicle speed-up process. The maximum growth rate of the lateral and vertical accelerations of car body, lateral and vertical wheel-rail contact forces are 17%, 8%, 8% and 2%, respectively, when the speed at the end of the constant power section increases from 50 km/h to 80 km/h. Last, the comprehensive evaluation of traction characteristics using entropy-weight TOPSIS method reveals when the starting torque is 800 [Formula: see text], 1000 [Formula: see text], 1200 [Formula: see text] and 1400 [Formula: see text], the corresponding optimal speed at the end of the constant power section is 80 km/h, 80 km/h, 70 km/h and 50 km/h, respectively. The result of the study can provide theoretical support for traction characteristic design and traction control for URVs.

A Steady-Pressure Control Method for Emulsion Pump Station Based on Online Updating of Optimal Flow Rate

In order to solve the problem of unstable fluid supply pressure and serious impact caused by the complicated and changeable working condition of a fully mechanized mining face in coal mines and the sluggish response of the fluid supply system to the fluid demand for the hydraulic support, a control method based on online updating generalized regression neural network (GRNN) was proposed. Firstly, the simulated hydraulic support test platform and co-simulation model were built. Secondly, The optimal flow dataset of steady-pressure fluid supply under different working conditions is calculated by simulation. Furthermore, the GRNN prediction model was established by using dataset and online updating learning technology to predict the optimal fluid supply flow according to environmental parameters. Finally, the optimal flow control method of online updating GRNN was established, and numerical research and experimental verification were also carried out in different working conditions. The results indicated that the proposed control method could track the working conditions of the working face in real time and adjusted the fluid supply flow of the emulsion pump station adaptively, which effectively alleviated the pressure fluctuation and pressure shock, and the system pressure was more stable, meeting the demand of steady-pressure fluid supply on the working face.

Sideband Vibro-Acoustics Suppression and Numerical Prediction of Permanent Magnet Synchronous Motor Based on Markov Chain Random Carrier Frequency Modulation

This paper presents a Markov chain random carrier frequency modulation (MRCFM) technique for suppressing sideband vibro-acoustic responses caused by discontinuous pulse-width modulation (DPWM) in permanent magnet synchronous motors (PMSMs) for new energy vehicles. Firstly, the spectral and order distributions of the sideband current harmonics and radial electromagnetic forces introduced by DPWM are characterized and identified. Then, the principle and implementation method of three-state Markov chain random number generation are proposed, and particle swarm optimization (PSO) algorithm is chosen to quickly find the key parameters of transition probability and random gain. A Simulink and JMAG multi-physics field co-simulation model is built to simulate and predict the suppression effect of the MRCFM method on the sideband vibro-acoustic response. Finally, a 12-slot-10-pole PMSM test platform is built for experimental testing. The results show that the sideband current harmonics and vibro-acoustic response are effectively suppressed after the optimization of Markov chain algorithm. The constructed multi-physics field co-simulation model can accurately predict the amplitude characteristics of the sideband current harmonics and vibro-acoustic response.

Research on Multi-Mode Control of Electro-Hydraulic Variable Displacement Pump Driven by Servo Motor

The electro-hydraulic power source with an electro-hydraulic variable pump driven by a servo motor is suitable for electrified construction machinery. To achieve better energy efficiency in different working conditions, the multi-mode control scheme was proposed for the electro-hydraulic power source. The control scheme includes pressure control, flow control, and torque control modes. The switching rule among the three control modes was formulated based on the minimum pump pressure. The fuzzy PID controller was designed, and a composite flow regulation strategy was formulated, including the load-sensitive adaptive displacement regulation and servo motor variable speed regulation. The AMESim-Simulink co-simulation model of multi-mode control was established. The test platform was built, and the experimental study was carried out. The results indicate that the fuzzy PID control has a shorter response time and a more stable control effect compared with PID control. Additionally, the composite flow regulation strategy improves the flow regulation range by 36% and reduces the flow overshoot by 20% compared with the load-sensitive adaptive displacement regulation. As the main control valve received an opening step signal, the full flow regulation (7~81 L/min) of the power source took approximately 0.5 s to rise and 0.2 s to fall. The relative error of pressure difference for the main control valve was 0.63%. When receiving the pressure and torque step signal, the pump pressure and pump input torque both took approximately 0.45 s to rise and 0.2 s to fall. The relative errors of pump pressure and torque control were 0.2% and 0.16%, respectively. In the multi-mode control, the electro-hydraulic power source could switch smoothly between flow control mode, pressure control mode, and torque control mode. These results provide a reference for the multi-mode control of an electro-hydraulic power source with an electro-hydraulic variable pump driven by a servo motor.

Development of a steady state electrothermal cosimulation model of SiC power modules

Silicon carbide power modules are suitable for high temperature, high voltage and high frequency applications. High operating temperature and high power density bring enormous challenges in chip parallel connection and junction temperature predicting. In this work, a steady state electrothermal cosimulation model is established based on Matlab electrical model and ANSYS thermal analysis model. An experimental study is conducted using a customized single die SiC module. The experimental and numerical results exhibit great agreement, with deviation consistently below 4 %. Then, comprehensive research is conducted to investigate the electrothermal performance of several dies in parallel configuration. The findings unequivocally validate the efficacy of the proposed model in accurately capturing the intricate electrical and thermal characteristics. The proposed numerical model offers a reliable and accurate electrothermal modeling approach for SiC power modules.

A Co-Simulation Model Integrating a Musculoskeletal Human Model with Exoskeleton and Power Tool Model

Working at and above head height with a power tool represents a common activity in craft and assembly applications. To assist and protect the user from overload and injuries in these situations, the development and use of application-specific support systems, such as exoskeletons and power tools, have greatly increased in recent years. Thus, the integration of aspects of the user-centered product development of support systems in the early phases of product development process has high potentials. A common approach to integrate the user early in the product development process is the use of musculoskeletal human models, which allow the evaluation of effects on the human body. This could also be applicable in the mentioned use case to enable the evaluation of the interactions for the user. Therefore, a co-simulation model for virtual modelling and simulating human–machine interactions is presented. The co-simulation model is made up of a musculoskeletal human model and the models of the technical systems (exoskeleton and power tool). By applying the co-simulation model, the impact of technical systems on the human body can be taken into account to derive design alternatives for the technical system due to the requirements of the user. The paper describes the design of the co-simulation model and particularly, the interaction of the submodels. The evaluation of the co-simulation model is carried out with the help of a subject study for the selected use case working at and above head height. The results show plausible results for the muscle loads considering the support by an exoskeleton. Furthermore, the comparison of simulated results to measured muscle activations via surface electromyography shows a good agreement. Thus, the co-simulation model passes the test for functionality and seems to be applicable for the derivation of design alternatives of technical systems regarding the user needs. In future, the co-simulation model will be further validated with a higher number of subjects and to implement design alterations in the technical systems.

Comparing the Complexity and Efficiency of Composable Modeling Techniques for Multi-Scale and Multi-Domain Complex System Modeling and Simulation Applications: A Probabilistic Analysis

Modeling and simulation of complex systems frequently requires capturing probabilistic dynamics across multiple scales and/or multiple domains. Cyber–physical, cyber–social, socio–technical, and cyber–physical–social systems are common examples. Modeling and simulating such systems via a single, all-encompassing model is often infeasible, and thus composable modeling techniques are sought. Co-simulation and closure modeling are two prevalent composable modeling techniques that divide a multi-scale/multi-domain system into sub-systems, use smaller component models to capture each sub-system, and coordinate data transfer between component models. While the two techniques have similar goals, differences in their methods lead to differences in the complexity and computational efficiency of a simulation model built using one technique or the other. This paper presents a probabilistic analysis of the complexity and computational efficiency of these two composable modeling techniques for multi-scale/multi-domain complex system modeling and simulation applications. The aim is twofold: to promote awareness of these two composable modeling approaches and to facilitate complex system model design by identifying circumstances that are amenable to either approach.

A Co-Simulation Model for the Operating Mechanism of a High-Voltage Circuit Breaker

A Co-Simulation Model for the Operating Mechanism of a High-Voltage Circuit Breaker

Modelling and characteristics analysis of an electro-hydraulic proportional valve with a discrete pilot stage for underwater hydraulic manipulators

As the harshness of the underwater operating environment and complexity of underwater tasks gradually increase, underwater hydraulic manipulators with high reliability and precision attract more research attention. To improve the reliability and dynamic performance of the traditional electro-hydraulic proportional valve (EHPV) used in the underwater hydraulic manipulator, an improved electro-hydraulic proportional valve with a discrete pilot stage (DEHPV) is proposed. In the pilot stage, two 2-position 3-way normally open high speed switching valves (HSVs) are used, and the initial oil spring stiffness in the control chamber is large enough to maintain the dynamic performance of the DEHPV. First, the working principle and configuration of the DEHPV are both given, and the coupled electric-magnetic-mechanical-fluid model of the DEHPV is presented. Moreover, a dual-valve hybrid pulse width modulation (DVHPWM) control strategy is proposed to improve the position tracking accuracy of the DEHPV. Furthermore, a co-simulation model of the DEHPV considering the multi-field coupling law is established to study the dynamic characteristics. Extensive experiments are carried out to verify the effectiveness of the proposed structure as well as its good dynamic performance and control accuracy.

Research on Three-Closed-Loop ADRC Position Compensation Strategy Based on Winch-Type Heave Compensation System with a Secondary Component

To mitigate the interference of waves on an offshore operation ship, heave compensation systems find widespread application. The performance of heave compensation systems significantly influences the efficiency and safety of maritime operations. This study established a mathematical model for a winch-based active heave compensation system. It introduced a three-loop active disturbance rejection control (ADRC) strategy that encompasses piston position control, winch speed control, and load-displacement control to enable the real-time estimation and compensation of system disturbances, thereby enhancing the performance of the heave compensation system. To assess the effectiveness of this control strategy, this study employed Matlab/Simulink and AMESim to construct a co-simulation model and conducted a comparative analysis with traditional proportional integral derivative (PID) control systems. The research findings indicate that the three-loop ADRC position control strategy consistently delivered superior compensation performance across various operational scenarios.

Research on a Pressure Control Method for a Liquid Supply System Based on Online Updating of a Radial Basis Function Neural Network

In order to solve the problem of frequent pressure fluctuations caused by fluid quantity variation in hydraulic support liquid supply systems and the pressure response lag caused by long-distance pipelines, an online updated radial basis function neural network (RBF neural network) control method was proposed for the long-distance liquid supply system. Based on the analysis of the measured pressure fluctuations of the mining face and the process of the stable pressure liquid supply system, the influencing factors of the stable pressure liquid supply flow demand were obtained. The flow set of the stable pressure liquid supply system was established and fitted in the SimulationX–Simulink co-simulation model and the online correction was carried out by using the characteristics of the repeated action of the hydraulic support. Finally, the online updating RBF neural network regulator was established to realize the pressure regulator control of the pumping station, and the experimental platform was set up for verification. The results show that this method can effectively reduce the pressure fluctuations caused by the change in the flow demand of the mining face, and can adjust the flow rate of the mining face, reduce the pressure impact, and improve the efficiency of the machine.

A control strategy for improving the accuracy of lateral tracking of autonomous vehicles

Lateral tracking is a fundamental technology for autonomous vehicles, particularly in narrow and complex scenes such as parking lots and alleys, where precise control is critical. To enhance the efficacy and precision of the traditional Pure Pursuit algorithm (PP) in the lateral tracking of low-speed autonomous vehicles, this study proposes a continuous adaptive piecewise fitting method based on the cubic Bézier curve to smooth the reference path, followed by a search for the look-ahead point based on the geometric relationship between the vehicle and the reference path. An improved search algorithm based on vehicle speed and road curvature is used to identify the look-ahead point. In case of significant changes in the reference path curvature, the initially obtained look-ahead point is modified. The proposed Improve Pure Pursuit Method (IPP) is then used to calculate the steering angle of the front wheel. To validate the proposed method, the Carsim/Simulink co-simulation model and the autonomous vehicle platform are established. The simulation and real-vehicle tests demonstrate that compared with the pure pursuit algorithm based on Vehicle speed control (VPP) and Fuzzy Logic control pure Pursuit (FPP), IPP performs better in complex low-speed lateral tracking scenes. It reduces the issue of cutting corners when the vehicle enters a corner and enhances lateral tracking accuracy.

Stability control of high-speed bogies using an adaptive vibration absorber

In this paper an active bogie stability scheme combining a dynamic vibration absorber (DVA) and an actuator is proposed for high-speed trains, and a control strategy is presented by transforming the actuating force into a virtual part of hybrid DVA whose characteristic frequency and damping can be adjusted. Firstly, a simplified model of the lateral bogie dynamics is established for control system design, and the optimal value of the characteristic frequency and damping of the hybrid DVA are theoretically investigated from the perspective of bogie stability. Then the strategy of active stability is introduced by using the idea of adaptive vibration absorber, and a method for auto-tuning the optimal value of the DVA suspension is proposed. To realize this auto-tuning strategy a method to detect the bogie instability and its frequency is presented. At last, the feasibility of the adaptive vibration absorber is verified by comparing it to a passive one using a co-simulation model of a railway vehicle, and the effect of time delay in the control system on bogie stability is also analyzed.

Research on Energy Efficiency Characteristics of Mining Shovel Hoisting and Slewing System Driven by Hydraulic-Electric Hybrid System

Mining shovel is a crucial piece of equipment for high-efficiency production in open-pit mining and stands as one of the largest energy consumption sources in mining. However, substantial energy waste occurs during the descent of the hoisting system or the deceleration of the slewing platform. To reduce the energy loss, an innovative hydraulic-electric hybrid drive system is proposed, in which a hydraulic pump/motor connected with an accumulator is added to assist the electric motor to drive the hoisting system or slewing platform, recycling kinetic and potential energy. The utilization of the kinetic and potential energy reduces the energy loss and installed power of the mining shovel. Meanwhile, the reliability of the mining shovel pure electric drive system also can be increased. In this paper, the hydraulic-electric hybrid driving principle is introduced, a small-scale testbed is set up to verify the feasibility of the system, and a co-simulation model of the proposed system is established to clarify the system operation and energy characteristics. The test and simulation results show that, by adopting the proposed system, compared with the traditional purely electric driving system, the peak power and energy consumption of the hoisting electric motor are reduced by 36.7% and 29.7%, respectively. Similarly, the slewing electric motor experiences a significant decrease in peak power by 86.9% and a reduction in energy consumption by 59.4%. The proposed system expands the application area of the hydraulic electric hybrid drive system and provides a reference for its application in oversized and super heavy equipment.

Study on the vibration reduction characteristics of shock absorber throttle orifice in tractor suspension

The hydraulic shock absorber of a certain tractor suspension system is analyzed to determine the influence of the cross-sectional area ratio of the throttling holes of the restoration valve and the compression valve on the vibration damping performance of the whole vehicle, using a new method of machine-hydraulic co-simulation. First, the AMESim model of the hydraulic shock absorber is established, and the Kriging model is used to approximate the parameters of the AMESim hydraulic shock absorber model; the multi-island genetic algorithm and the gradient descent algorithm are used to obtain the three scenarios in which the cross-sectional area ratios of the throttle orifices of the same equivalent damping coefficients are greater than, equal to, or less than one. Then, a co-simulation model of 1/4 vehicle Recurdyn/AMESim and a co-simulation model of the whole vehicle with 162 degrees of freedom were established. The result show that, compared with the traditional method, this machine-hydraulic co-simulation method improves the calculation accuracy, calculation speed, and co-simulation model parameter accuracy. For low-speed conditions, when the throttle orifice area ratio equals 0.32, the minimum vehicle body center acceleration (root mean square value equal to 1.78 m/s2) is achieved. For high-speed driving conditions, when the throttle orifice area ratio is approximately 3.1, the minimum vehicle body center acceleration (root mean square value equal to 3.52 m/s2) is achieved.

Braking Intention Identification Strategy of Electric Loader Based on Fuzzy Control

As a widely-used construction machinery, the electric loader has the potential to recover braking energy due to its large mass and frequent starts and stops. Identifying braking intention accurately is the foundation of braking energy recovery. The typical braking condition of an electric loader is analyzed; the braking intention is divided into sliding brake, mild braking, moderate braking, and emergency braking. A large number of braking data were collected under different braking intentions, which are used as the basis for fuzzy control variable partitioning, fuzzy controller parameter setting and fuzzy control rule formulation. The control strategies of deceleration intention identification based on accelerator pedal, braking intention identification based on brake pedal and sliding brake intention identification are proposed in this paper, respectively. This paper takes the hydraulic brake pressure as a feedback parameter, even if there is hysteresis or failure based on the intention of pedal identification, the system can still provide sufficient braking strength to ensure the braking safety. The AMESim(R12)-Matlab/Simulink co-simulation model and prototype are built to verify the feasibility of the control strategy under different braking intention identification. The results show that the braking strength under stronger braking intention can satisfy the braking demand whether at a speed of 2 m/s or 12 m/s, which ensures the safety of emergency braking, and the electric loader can provide stable braking strength under different braking intention and different speed. This has good braking stability.

Transient research on distribution networks incorporating superconducting cables utilizing field–circuit coupling method

High temperature superconducting (HTS) cable represents a promising solution for fulfilling the power demands of cities with large loads and high density. However, due to their connection to the distribution network, HTS cables are vulnerable to fault currents exceeding ten times their rated current, which poses a serious threat to both the safety of the cable and the operation of the grid. Considering the highly nonlinear nature of superconducting conductivity, this study develops a field–circuit coupling model to investigate the transient characteristics of distribution networks incorporating superconducting cables (DNSC). Firstly, a finite element model based on the two-dimensional H formulation was built to calculate the electrical and thermal parameters of the HTS cable. Subsequently, an equivalent circuit model of the distribution network was employed to estimate the short-circuit currents. Communicating via a co-simulation server, the superconducting cable current and distribution network impedance were updated in each step. Further, based on an actual DNSC system in Shenzhen, China, the highest quenching temperature of the cable and the maximum fault current of busbars were assessed. Finally, by integrating current limiters into the system, the withstand capability of the cable and busbars was determined, which indicates that the improved protection configuration can effectively suppress fault currents and ensure safe operation. Successfully applied to an actual distribution network, the co-simulation model utilizing the field–circuit coupling method addresses the challenges of solving highly nonlinear and time-varying systems, enabling transient analysis and protection research for the integration of superconducting devices into the conventional grid.