Nonlinear Characteristics Of System Research Articles

Modeling and Nonlinear Dynamic Characteristics Analysis of Fault Bearing Time-Varying Stiffness-Flexible Rotor Coupling System

There is a complex dynamic interaction between the aero-engine bearing and the rotor, and the resulting time-varying system parameters have an impact on the nonlinear dynamic characteristics of the rolling bearing-flexible rotor system. In this study, the interaction between the time-varying stiffness of the rolling bearing and the transient response of the flexible rotor is considered. The Newmark-β integral method is used to solve the dynamic equation, and the relationship between the time-varying characteristics of bearing stiffness and load and the dynamic characteristics of the rotor is studied. The relationship between bearing stiffness and vibration strength is analyzed, and the influence of damage size on the time domain signal energy of the disc is analyzed. The results show that the model established in this paper can accurately reflect the dynamic interaction between the bearing and the rotor. With the extension of the bearing damage, the dynamic stiffness of the bearing attenuates, the intensity of the excitation force increases, and the vibration is transmitted to the disc, which affects the motion stability and vibration response of the disc.

Optimal scheduling of zero-carbon park considering variational characteristics of hydrogen energy storage systems

Zero-carbon parks have broad prospects in carbon neutralization. As an energy hub, hydrogen energy storage plays an important role in zero-carbon parks. However, the nonlinear characteristics of hydrogen energy storage systems (HESSs) have a significant impact on the system economy. Therefore, considering the variable working condition characteristics of HESSs, a hybrid operation method is proposed for HESS, to support the efficient and economic operation of zero-carbon parks, by analyzing the operating principle of a zero-carbon park with HESS, the system structure framework and variable condition linearization model of the equipment in HESS are established. Moreover, considering the energy output characteristics of hydrogen energy storage equipment under variable working conditions, a multimodule hybrid operation strategy is proposed for electrolytic and fuel cells, effectively meeting the thermoelectric load demand of zero- carbon parks in different scenarios. Finally, the economy of the proposed hybrid operation strategy was verified in typical scenarios, using a zero-carbon park embedded with a HESS.

Research on Energy-Saving Control Strategies for Single-Effect Absorption Refrigeration Systems

The automatic control device is a critical component of absorption refrigeration systems. Its functional enhancement can reduce operating costs, improve energy efficiency, and ensure long-term stable unit operation. Given that absorption refrigeration systems operate under various dynamic conditions, the rational design of control strategies is particularly important. This study analyzes the influence of changes in the cooling water and heat source water flow rates on the outlet temperature of chilled water in the unit based on the open-loop response characteristics of absorption refrigeration systems. It proposes a dual-loop energy-saving control strategy for single-effect hot water lithium bromide absorption refrigeration systems based on the setpoint comprehensive optimization algorithm. Considering the multiple variables, strong coupling, large inertia, long time delay, and nonlinear characteristics of absorption refrigeration systems, as well as the difficulties in modeling these systems, this study applies a model-free adaptive control algorithm to the system’s control. It derives both SISO and MIMO model-free control algorithms with time-delay components. Through simulations comparing MFAC, improved MFAC, and traditional PID control, the dual-loop energy-saving control strategy is demonstrated to effectively reduce system heat consumption by approximately 20%, decrease power consumption by about 10%, and enhance the system’s SCOP by approximately 19.3%.

Vibration Friction Investigation on the NCS of Joints of the CNC Machine Tools Considering Friction Factor

Machine tool vibrations play a significant role in hindering productivity during machining. The growing vibrations accelerate tool wear and chipping, cause a poor wave surface finish, and may damage the spindle bearing. Some research showed that tribological properties such as friction factors can have obvious influences on the topography of rough surfaces and the nonlinear dynamic characteristics of machine tool systems. Therefore, studying the vibration friction dynamic characteristics on the normal contact stiffness (NCS) of joints of CNC machine tools is absolutely necessary for improving the machining accuracy and precision of the whole system. The study results of NCS of joints of the CNC and the friction coefficient are discussed in this paper. The model of NCS based on fractal parameters was obtained. The models of deformations of the rough surfaces and contact surfaces were deduced. The results showed that the NCS based on the calculation method considering the elastic–plastic deformation of the asperity is much higher in precision than the methods considering only elastic or plastic deformation separately. The observations this paper described suggest that in the CNC machine tools system, higher D and G and higher friction coefficients lead to higher normal contact stresses (NCSs).

Nonlinear vibration characteristics of rotor-bearing system with disc-shaft insufficient interference and flexible coupling misalignment fault

Abstract For the traditional rotor system, the looseness fault caused by disc-shaft insufficient interference is always ignored. Aimed at the disc-shaft looseness caused by insufficient interference, a novel dynamic model of rotor-bearing system in the presence of coupling misalignment is established in this paper to make an investigation on the fault characteristics of disc-shaft looseness fault. Due to the nonlinearity of contact model between disc-shaft, the iterative solving of kinetic equations can be obtained by the combination of Newmark-β and Newton-Raphson methods. The vibration characteristics of the rotor-bearing system with and without the disc-shaft looseness caused by insufficient interference are compared and analyzed. The comparison results show that the slight collision between disc-shaft can be caused in the disc-shaft early looseness fault, and the beat vibration of system is appeared when the disc-shaft looseness become severe. Considering the effect of coupling misalignment, the vibration responses of system under different coupling misalignment are further discussed and parallel misalignment is proved to have a significant effect on the disc-shaft looseness. It is expected that the research results provide a useful reference for the identification and diagnosis of the looseness fault caused by disc-shaft insufficient interference.

Experimental study of nonlinear vibration characteristics of a two-rotor turbofan engine system with an intershaft support

Experimental study of nonlinear vibration characteristics of a two-rotor turbofan engine system with an intershaft support

Nonlinear Adaptive Control Design for Quadrotor UAV Transportation System

In response to the non-linear and underactuated characteristics of quadrotor UAV suspension transportation system, this paper proposes a novel control strategy aimed at achieving precise position control, attitude control, and anti-swing capabilities. Firstly, a dynamical model required for controller design is established through the Newton-Euler method. In the controller design process, the paper employs the energy method and barrier Lyapunov function to design a double-closed-loop nonlinear controller. This controller is capable of not only accurately controlling the position and attitude angles of the quadrotor UAV suspension transportation system but also effectively suppressing the swing of the payload. Building on this, considering the elastic deformation of the lifting cable, and by analyzing the forces in the Newton-Euler equations, this paper proposes an adaptive control design for the case where the length of the cable connecting the UAV and the payload is unknown. To validate the effectiveness of the proposed control scheme, comparative experiments were conducted in the MATLAB simulation environment, and the results indicate that the method proposed in this paper exhibits superior control performance compared to traditional controllers.

A Nonlinear Active Disturbance Rejection Feedback Control Method for Proton Exchange Membrane Fuel Cell Air Supply Subsystems

The control strategy of the gas supply subsystem is very important to ensure the performance and stability of the fuel cell system. However, due to the inherent nonlinear characteristics of the fuel cell gas supply subsystem, the traditional control strategy is mainly based on proportional integral (PI) control, which has the disadvantages of large limitation, large error, limited immunity, and inconsistent control performance, which seriously affects its effectiveness. In order to overcome these challenges, this paper proposes an optimal control method for air supply subsystems based on nonlinear active disturbance rejection control (ADRC). Firstly, a seven-order fuel cell system model is established, and then, the nonlinear ADRC and traditional PI control strategies are compared and analyzed. Finally, the two strategies are simulated and compared. The validation results indicate that the integral absolute error (IAE) measure of PI control is 0.502, the integral square error (ISE) measure is 0.1382, and the total variation (TV) measure is 399.1248. Compared with the PI control, the IAE and ISE indexes of ADRC were reduced by 61.31% and 58.03%, respectively. ADRC is superior to PI control strategy in all aspects and realizes the efficient adjustment of the system under different working conditions. ADRC is more suitable for the nonlinear characteristics of the gas supply system and is more suitable for the oxygen excess ratio (OER).

Mode decomposition of core dynamics transients using higher-order DMD method

Accurately predicting three-dimensional power distribution within a reactor core during reactivity transients is crucial for optimizing reactor operational control. This paper proposes a higher-order dynamic mode decomposition (DMD) method for analyzing highly nonlinear dynamic systems in nuclear reactors. Through analysis of the 3-D LWR Core Transient Benchmark (3DLWRCT) with rod ejection accident, traditional DMD reconstruction techniques were found inadequate in accurately capturing the system’s dynamic evolution using the given simulation data, primarily due to the nonlinear features and local high-order characteristics of the reactor system. In contrast, the HODMD approach demonstrated its effectiveness in predicting future variations in the core’s state. These findings establish the feasibility of employing the HODMD method for transient analysis of core dynamics, leading to promising prospects for dynamic analysis in nuclear energy systems. Future research directions for improving the reconstructive accuracy of HODMD include capturing nonlinear characteristics, automating parameter selection, enabling multi-scale analysis, enhancing anomaly detection capabilities, and providing a broader context for analysis.

Research on Multi-Mode Variable Parameter Intelligent Shift Control Method of Loader Based on RBF Network

The loader is one of the most widely used pieces of engineering machinery in the world for soil transportation, loading and unloading materials, and low-intensity shovel digging operations in harsh and complex operating conditions; it requires very frequent shifting and has other challenging characteristics. In order to realize automatic frequent shifting, we need to better design the shifting rules in the shifting process, improve the shifting quality and working efficiency, and solve the key engineering problems of energy saving and high efficiency in the shifting process of loaders. In this paper, a 7-ton wheel loader is taken as the research object, the loader shoveling process of the four operating modes is analyzed, and a multi-mode variable parameter shift law is designed. Aiming at the complicated and nonlinear characteristics of the power transmission system of the loader, an intelligent shift control method based on an RBF neural network is proposed. Finally, the simulation test and the clutch shift oil pressure test are carried out. From the test results, the clutch test oil pressure curve obviously shows a four-stage upward trend during shifting, and the buffering effect is obvious. The designed multi-mode variable-parameter intelligent shift law of the loader is reasonable and feasible, and the shift recognition rate reaches 97.92%, which provides theoretical support for the realization of intelligent automatic speed change control of the loader, and it certainly has engineering value.

A subspace parameter identification method for nonlinear structures under oversampling conditions

In engineering practice, sampling frequencies much higher than the Nyquist frequency are often used to obtain accurate measurements of the dynamic characteristics of nonlinear systems. However, it may lead to oversampling when using the nonlinear subspace identification method (NSIM). This study proposes a subspace parameter identification method to address the identification of nonlinear structures under oversampling conditions. The proposed method first employs the prediction error method (PEM) to estimate the linear part of the state space model. In noisy environments, the PEM can achieve more accurate results than the NSIM by minimizing an error criterion function. The initial values fed into the PEM are obtained by the stochastic subspace identification method. The nonlinear part of the state space model is estimated by solving a linear regression equation. The proposed method effectively reduces the impact of high sampling frequencies on identification accuracy by combining data with different sampling frequencies to construct the linear regression equation. Among them, the low sampling frequency data is obtained by downsampling the high sampling frequency measurement data. The proposed method effectively reduces the effect of high sampling frequencies and environmental noise on identification accuracy by accurately estimating both the linear and nonlinear parts of the state space model. The identification accuracy of the proposed method is numerically verified by a chain-type structure with five degrees of freedom and a cantilever beam structure. Additionally, experimental verification is carried out on a two degrees of freedom floor structure with local nonlinearities. The results show that the proposed method achieves high identification accuracy in oversampling conditions and noisy environments.

An Improved Embedded based PID Controller for Boosting Operation in Solar Energy-Battery Systems

The proposed work introduces an improved PID controller for boosting operation in solar energy-battery systems, leveraging model-based controller (MBC) techniques. In general, boost converters are crucial for managing and optimizing power flow in renewable energy systems. While PID controllers are commonly used in boosting applications due to their simplicity, they often face challenges in adapting to the dynamic and nonlinear characteristics of solar energy systems. This can result in suboptimal performance and efficiency. Hence, a model-based controller with manual tuning is proposed to improve the stability and efficiency by systematically tuning controller gain parameters based on its system model. Extensive simulation studies conducted using MATLAB/Simulink shows that the proposed controller outperforms the conventional PID controller under various operating conditions, such as fluctuations in solar irradiance and changes in battery state of charge. Further, the experimental tests conducted on a prototype setup validates the feasibility and ability of the model-based controller to accurately regulate the solar panel output and efficiently charge the battery, which leads to enhanced performance. This work offers a promising solution for enhancing energy conversion efficiency and facilitates the effective integration of renewable energy sources into the power grid.

Nonlinear dynamic characteristics of mechatronics integrated planetary gears considering wear and temperature effects

The electromechanical planetary gear system has high work efficiency and long service life, but factors such as heat, wear, and electrical signals can affect the transmission performance of electromechanical planetary gears. This article comprehensively considers factors such as temperature, tooth surface wear, lubrication, current and voltage, damping ratio, etc. Based on the principle of thermal deformation, Archard wear model, and equivalent circuit principle, a dynamic model of electromechanical planetary gears is established. The existing literature has not comprehensively analyzed the effects of temperature, wear, and electrical signal changes on the nonlinear characteristics of electromechanical planetary gear systems. The results show that when the motor current is between 7 A and 18 A and the voltage is lower than the rated voltage, the system is in a stable state; as the temperature rises, the system tends to stabilize; the gear wear exceeds 30 μm, and the bifurcation characteristics of the system are more pronounced.

Offset-Free Koopman Model Predictive Control of Thermal Comfort Regulation for a Variable Refrigerant Flow-Dedicated Outdoor Air System-Combined System

Abstract Variable refrigerant flow (VRF) system has been an appealing solution of air conditioning for residential and commercial buildings, due to its flexibility and cost effectiveness, while lack of ventilation capability is a major drawback. Incorporation of dedicated outdoor air system (DOAS) is a typical practice. However, good coordination between DOAS and VRF is critical for achieving desired thermal comfort is challenging due to the possible complexity of mixed sensible and latent heat exchanges. In this paper, to handle the nonlinear dynamic characteristics of VRF-DOAS system, we propose an offset-free Koopman model predictive control (MPC) strategy for thermal comfort regulation, in which the MPC design is computationally more efficient due to the convex problem formulation and the use of reduced-order Koopman models, and the offset-free MPC structure enhances the robustness to model uncertainties and unmeasured disturbances. A control-oriented model is obtained by hybridizing the first-principle and data-driven modeling approach. The proposed controls strategy is evaluated with a Modelica simulation model of a VRF-DOAS system. A Dymola-Python cosimulation platform is developed via the functional mockup interface (FMI), for which the MPC algorithms are implemented in Python. Simulation results show significantly better performance of the offset-free Koopman MPC in thermal comfort regulation.

Improved deep learning based state of charge estimation of lithium ion battery for electrified transportation

The increasing interests and recent advancements in artificial intelligence and machine learning have significantly accelerated the development of novel techniques for the state estimation of batteries in the battery management systems (BMS) of electrified vehicles. To ensure the safe and reliable operation of an electric vehicle, it is essential to determine the state of charge (SOC) among the battery's numerous states. Deep learning models have been effective for SOC estimation due to the nonlinear and time-varying characteristics of a battery management system. This article seeks to describe an SOC estimator design method using deep neural network (DNN) models, particularly non-recurrent and recurrent neural networks, owing to their excellent computational intelligence and capacity for self-learning. A thorough investigation has been conducted at various temperatures, and the model is trained on data received from the cell during discharging processes like the urban dynamometer driving schedule (UDDS). Finally, the accuracy of the models is compared based on various performance indices. From the results, it has been concluded that the DNN models acquire a Mean Absolute Error (MAE) of less than 1 % and a Root Mean Square Error (RMSE) of close to 1 % when validated over various datasets at temperatures of 10 °C, 25 °C, and 40 °C.

A heavy-haul train longitudinal-vertical coupled dynamics model and its dynamic behaviour under emergency braking

The heavy-haul train dynamic performance under emergency braking is complex and directly affects the reliability and running safety. To reveal the heavy-haul train dynamic behaviour in emergency braking process on the long downhill segments, a comprehensive heavy-haul train longitudinal-vertical coupled dynamics model (HTLVDM) that considers the air braking system and coupler draft gear system is established in this paper. HTLVDM considers the components of the locomotive and wagon, such as the wheelset, bogie frame, and car body. The coupler force model considers the nonlinear hysteresis characteristic of the coupler draft gear system. The braking delay time and pressure variation of the brake cylinders are taken into the air braking model. In addition, the validity of HTLVDM is verified by published data. Based on the real-world data of the Shuozhou-Huanghua Line and the established model, the HTLVDM's dynamic responses are analysed through numerical simulations. The results indicate that both the brake forces and coupler forces have a significant effect on the wheel-rail dynamic interactions and the dynamic response of the car body in the heavy-haul train.

Novel techniques to analyze dynamical properties of quantum chaos with peculiar evidence of hybrid systems confinement

Recent results demonstrate the dynamical peculiarities of the quantum chaos within the hybrid systems by chaotic parameters and probe the pattern formation under the influence of condensation. The complex dynamic behavior of the considered systems was determined with numerical simulation and presented an efficient technique that studied fractional systems comprising chaos-coherence fractions. The findings divulge the peculiar association between the coherence structure and the correlations at finite relative momenta. Thus the present study helps to explore the partially chaos hybrid systems in order to stimulate the experimental applications of nonlinear phenomena. The coherent-chaotic parameters can be measured by examining the chaos peculiarities that possess explicit relations with the condensations to demonstrate the environs of the physical systems. We investigate the influence of the multiplicities, chaos, momentum and temperature of the nonlinear system on the coherent-chaotic normalized correlations. The chaotic parameters are suppressed considerably with the coherence fraction and it appears numerically zero at maximum condensation and one at ideal chaos emissions. We procure that the meaningful parameters decrease significantly with the multiplicity of the nonlinear systems and increase with the momentum in the specified regimes. The identical multiplicity leads to contemplating the coherence and thus the normalized chaotic parameters within its spectacular influences exhibit significance worth contemplating in earnest. The findings underscore the significance of cogitating correlations in deciphering the nonlinear system characteristics and bestowing extraordinary perceptiveness into the convoluted essence of complex systems. The contemplated methodology can be applied to evaluating and analyzing the nonlinear systems and such an innovative approach computes the problems of celestial mechanics, heartbeats and chemical reactions in engineering and medical fields.

Application of Fuzzy Control and Neural Network Control in the Commercial Development of Sustainable Energy System

Sustainable energy systems (SESs) occupy a prominent position in the modern global energy landscape. The purpose of this study is to explore the application of fuzzy control and neural network control in photovoltaic systems to improve the power generation efficiency and stability of the system. By establishing the mathematical model of a photovoltaic system, the nonlinear and uncertain characteristics of photovoltaic system are considered. Fuzzy control and neural network control are used to control the system, and their performance is verified by experiments. The experimental results show that under the conditions of low light and moderate temperature, the fuzzy neural network control achieves a 3.33% improvement in power generation efficiency compared with the single control strategy. Meanwhile, the system can still maintain relatively stable operation under different environmental conditions under this comprehensive control. This shows that fuzzy neural network control has significant advantages in improving power generation efficiency and provides beneficial technical support and guidance for the commercial development of SESs.

Research on axial nonlinear vibration characteristics of ball screw feed system considering segmented restoring force

Taking the ball screw feed system as the research object, the two degree of freedom axial dynamic model of the system is constructed firstly. Based on Hertz contact theory, when the ball screw pair adopts variable lead self-preloading to eliminate the assembly clearance between the ball and raceway, considering the nonlinear segmented axial elastic recovery force generated by the uneven contact deformation between the ball and raceway under the action of external excitation force, further derive the nonlinear dynamic equation group of the system. Next, the fourth-order Runge-Kutta method was used to numerically solve the equation system, obtaining the system’s two and three-dimensional phase diagrams, Poincaré sections, time-domain waveform diagrams, frequency spectra, and bifurcation diagrams. Then, the effects of damping constant, initial contact angle between ball and raceway in ball screw pairs, and number of balls on the system’s response characteristics were analyzed, and the influence of external excitation forces on system stability was further studied. Finally, it was verified through experiments that the axial vibration of the system is indeed nonlinear vibration, providing a theoretical basis for the study of the dynamic characteristics of the ball screw feed system.

Nonlinear dynamics analysis of electromechanical planetary gear systems with temperature effects considered

PurposeThe electromechanical planetary transmission system has the advantages of high transmission power and fast running speed, which is one of the important development directions in the future. However, during the operation of the electromechanical planetary transmission system, friction and other factors will lead to an increase in gear temperature and thermal deformation, which will affect the transmission performance of the system, and it is of great significance to study the influence of the temperature effect on the nonlinear dynamics of the electromechanical planetary system.Design/methodology/approachThe effects of temperature change, motor speed, time-varying meshing stiffness, meshing damping ratio and error amplitude on the nonlinear dynamic characteristics of electromechanical planetary systems are studied by using bifurcation diagrams, time-domain diagrams, phase diagrams, Poincaré cross-sectional diagrams, spectra, etc.FindingsThe results show that when the temperature rise is less than 70 °C, the system will exhibit chaotic motion. When the motor speed is greater than 900r/min, the system enters a chaotic state. The changes in time-varying meshing stiffness, meshing damping ratio, and error amplitude will also make the system exhibit abundant bifurcation characteristics.Originality/valueBased on the principle of thermal deformation, taking into account the temperature effect and nonlinear parameters, including time-varying meshing stiffness and tooth side clearance as well as comprehensive errors, a dynamic model of the electromechanical planetary gear system was established.