Adjustable Inertia Research Articles

Nonlinear modeling of ball screw-type inertial container suspension

Abstract In order to better reduce the influence of spring-loaded mass inertia on vehicle suspension performance and make it better adapt to road excitation, this paper proposes a ball screw inertial container suspension configuration with adjustable inertia coefficient. By adjusting the mass of the flywheel part of the passive ball screw inertial container in the radial direction, the rotating radius is changed under the action of centrifugal force, and then the rotating inertia is changed, so that the rotating inertia of the flywheel can be adjusted with the rotating speed of the flywheel itself to achieve the adjustable inertia coefficient. Considering the nonlinear influence of the ball screw inertial container suspension system, a two-freedom nonlinear dynamic model of 1/4 vehicle is established. The model is simulated and analyzed. The results show that, compared with the passive and fixed inertia coefficient ball screw inertial container suspension, the adjustable inertia coefficient is improved by 45%, 11%, and 37%, respectively, compared with the fixed inertia coefficient inertial container suspension. The ball screw inertial container active suspension can effectively suppress the vibration impact of vehicles under road excitation.

An Adaptive Virtual Inertial Control Strategy for DC Distribution Networks

The DC distribution network is a low-inertia system, which is very sensitive to load disturbance, system failure, and other factors. By adding virtual capacitance to the converter connected to the power supply, the virtual inertia of the DC power grid can be improved. Firstly, this paper proposes a strategy for adjusting virtual capacitance based on the voltage change rate to achieve adaptive control of virtual inertia, which enables the converter to quickly absorb or release energy during power fluctuations. Secondly, the adaptivity of the strategy is improved and the main control parameters in the proposed control method are qualitatively analyzed. Finally, the four-terminal photovoltaic storage DC distribution network system is constructed. Through Simulink, the adaptive virtual inertia control is incorporated on the battery side to simulate and validate the effectiveness of the strategy and the rationality of parameter analysis. The results show that this method can provide flexible and adjustable inertia support for DC grids and improve the voltage stability of DC grids.

Multi-Objective Optimal Design of a Cable-Driven Parallel Robot Based on an Adaptive Adjustment Inertia Weight Particle Swarm Optimization Algorithm

Abstract Cable-driven parallel robots (CDPRs) have been widely used in engineering fields because of their significant advantages including high load-bearing capacity, large workspace, and low inertia. However, the impact of convergence speed and solution accuracy of optimization approaches on optimal performances can become a key issue when it comes to the optimal design of CDPR applied to large storage space. An adaptive adjustment inertia weight particle swarm optimization (AAIWPSO) algorithm is proposed for the multi-objective optimal design of CDPR. The kinematic and static models of CDPR are established based on the principle of virtual work. Subsequently, two performance indices including workspace and dexterity are derived. A multi-objective optimization model is established based on performance indices. The AAIWPSO algorithm introduces an adaptive adjustment inertia weight to improve the convergence efficiency and accuracy of traditional particle swarm optimization (PSO) algorithm. Numerical examples demonstrate that final convergence values of the objective function by the AAIWPSO algorithm can almost be 14∼20% and 19∼40% higher than those by the PSO algorithm and genetic algorithm (GA) for the optimal design of CDPR with different configurations and masses of end-effectors, respectively.

The Sleepiness of International Students in Online Chinese Classroom: An Experimental Study Based on Hybrid Technology of Facial Feature Point Distribution Model

The study presented in this article is a ground-breaking investigation into the quick advancement of intelligent online language instruction based on wireless communication networks, learner physiological and psychological alterations;to predict and prompt learners’ sleepiness, a hybrid technology of facial feature point distribution model is applied to the process of online learning of Chinese for international students. This technology aids teachers in timely monitoring and discovering learners’ levels of sleepiness in the process of online learning and adjusting it, ensuring effective teacher-student interaction and the accomplishment of learning objectives in the classroom. The following specific designs are carried out in order to increase the contribution of teaching and training samples to the classification effect: (1) To train the neural network classifier and ensure more stable and accurate recognition results, the system employs the particle swarm optimization approach with adaptive parameter adjustment; (2) A simulated annealing technique is suggested to address the premature convergence flaw of the conventional particle swarm optimization algorithm, and an adjustable inertia weight factor is created to enhance the optimization capability of particle swarm optimization; (3) A PSO-SVM based facial expression recognition system based on multi-scale wavelet transform theory and support vector regression machine is created in order to further enhance the network’s generalization capability. The simulation findings demonstrate some improvement in the convergence of the two widely used face recognition techniques. Additionally, this study provides a principal component analysis approach based on DCT coefficient singular decomposition and a texture feature selection method based on LDA model in an effort to apply wavelet analysis theory to face recognition. Highlights A system for predicting and prompting learners’ sleepiness in online foreign language classroom teaching is constructed In the case of being unable to actively integrate into online classroom teaching, learners are prone to lack of concentration, sleepiness, even anxiety, irritability and facial muscle twitching Eye fatigue identified at a distance of 0.3–1.5 m from ordinary cameras is relatively easy to identify The appearance of a large proportion of tired students in the online classroom suggests that teachers should adjust the teaching design scheme The reasons leading to the burnout of online learners are very complex, and it still needs interdisciplinary in-depth research

Grid-Forming Inverter Enabled Virtual Power Plants With Inertia Support Capability

Modern energy systems are experiencing the transition towards renewable-powered ones. Some conventional thermal units based on synchronous machines are gradually decommissioned and replaced by power electronics interfaced renewables. Thus, the lack of natural inertia and governor damping, which are the features of synchronous machines, raises significant concern about system frequency stability, including the faster rate of change and lower nadir point of frequency. Meanwhile, with the rapid development of communication and Internet of Things technologies, distributed energy resources can be aggregated as a virtual power plant to help balance real-time electricity demand and supply. However, the capability of utilizing the whole virtual power plant to provide adjustable inertia support has not been explored yet. In this paper, we propose a framework of the synchronous virtual power plant based on grid-forming inverter interfaced distributed energy resources. By coordinating the parameter settings of grid-forming inverters, the virtual power plant provides inertia support. Also, we design an online learning-based parameter settings method that makes the inertia of the virtual power plant adjustable. A case study in IEEE 34 nodes system illustrates the effectiveness of the proposed method.

PV-Supercapacitor Cascaded Topology for Primary Frequency Responses and Dynamic Inertia Emulation

Owing to rapid increase in PV penetration without inherent inertia, there has been an unremitting deterioration of the effective inertia of the existing power systems. This may pose a serious threat to the stability of power systems during disturbances if not taken care of. Hence, the problem of how to emulate Synthetic Inertia (SI) in PV Systems (PVS) to retain their frequency stability demands attention. Super Capacitor (SC)-based storage become an attractive option over the other energy storage types because of its high-power density, burst power handling capability, faster response and longer life cycle. Considering this, the authors here propose a novel PV-SC Cascaded Topology (PSCT) as a cost-effective approach to emulate SI by integrating a low voltage SC to a high voltage grid-connected PVS. The proposed PSCT helps in operating the SC as a voltage source rather than a current source. Thus, it eliminates the high gain requirements of the SC interfacing converters. The aim is to target two main frequency response services, i.e., Primary Frequency Response (PFR) and Synthetic Inertial Response (SIR), using a novel common control scheme, but without affecting any other energy intensive services. The authors introduced a Droop-Inspired (DI) method with an adjustable inertia constant to emulate dynamic inertia so that a wider range of Rate of Change of Frequency (RoCoF) values can be serviced with a limited storage. A very streamlined analysis was also carried out for sizing of the SC stage based on a simple Three-Point Linearization (TPL) technique and DI technique with a limited knowledge of the disturbance parameters. The whole system was initially validated in a MATLAB Simulink environment and later confirmed with the OPAL-RT Real-Time Simulator. The investigated response was subject to variation in terms of control parameters, changes in solar irradiance, grid frequency variation, etc.

Modelling and control of a semi-active dual-chamber hydro-pneumatic inerter-based suspension system

This study develops a new type of semi-active dual-chamber hydro-pneumatic inerter-based suspension (SADHPIS) based on the ‘inerter–spring–damping’ vibration isolation system and semi-active control. The mathematical model of SADHPIS is linearised to match the nonlinear SADHPIS system with a linear control strategy, and the equivalent parameters are calculated. A linear–quadratic–Gaussian (LQG) controller that matches the nonlinear characteristics of the SADHPIS system is designed. Furthermore, the performance of a quarter-vehicle model with SADHPIS is analysed and compared with that with normal semi-active hydro-pneumatic suspension (SAHPS). Simulation results show that the performance of SADHPIS is better than that of SAHPS, indicating that ride comfort and handle stability are improved greatly in SADHPIS. A prototype is also developed, and a comparative bench test is conducted to verify the accuracy of the simulations. SADHPIS can realise adjustable inertia with a small space and low energy consumption. This work provides new insights for research on variable inertia, promotes the matching of inerters and hydro-pneumatic suspension systems and further proves the practical application value of hydro-pneumatic inerter-based suspension.

Research on the Damping Device with Adjustable Inertia and Damping

In this paper, a new type of composite structure is proposed based on the original semi-active suspension of magnetorheological shock absorber and automobile suspension with inertia container, and the structure is analysed theoretically. The proposed new composite device is composed of a hydraulic cylinder, a magnetorheological damper and a hydraulic motor. The magnetorheological damper is compounded in the hydraulic cylinder and connected to the hydraulic motor through a hydraulic pipeline. The magnetorheological damper has the function of adjusting the damping, and the hydraulic motor achieves the purpose of adjusting the inertia by changing the mass. In order to analyse the device, the mechanical characteristics of magnetorheological valve and hydraulic motor are modelled and analysed. A quarter-vehicle suspension simulation analysis was performed on the overall operating characteristics of the system. The analysis results showed that the compound device has good variable damping inertia capacity characteristics, which is of great significance for improving the semi-active control suspension system.

Adjustable inertia implemented by bidirectional power converter in hybrid AC/DC microgrid

Hybrid AC/DC microgrid is regarded as a low inertia system due to the extensive integration of renewable energy sources. Thus, the AC bus frequency and DC bus voltage are easily damaged when a step change or random fluctuation appears, which threatens the system power quality. Focusing on this problem, this study proposes an adjustable inertia implementing method for the two-stage bidirectional power converter (BPC) to enhance the dynamic performance of the hybrid power system. Concretely, the first stage of the BPC is controlled as a virtual synchronous generator to support the AC subgrid and plays the role of imitating the inertia frequency response in the AC bus. The second stage controls the built-in capacitor of the BPC to implement adjustable inertia for the DC subgrid and improves the DC bus voltage response. Besides, the terminal voltage of the built-in capacitor will be restricted to ensure the normal operation of the BPC. The small-signal analysis of the hybrid system is provided to illustrate the stability of the proposed control method. Finally, the experimental results based on the real-time hardware-in-loop platform demonstrate the effectiveness of the proposed method.

Shield Tunneling Parameter Matching Model and UI Interface

In order to improve the accuracy of shield tunneling parameter matching under the limited data, the matching model based on support vector machine (SVM) and exponential adjustment inertia weight immune particle swarm optimization (EAIW‐IPSO) is proposed. The nonlinear relationship model between the tunneling parameters and the ground settlement is constructed by SVM and trained with the actual engineering sample data. Based on the trained model, EAIW‐IPSO is used to optimize the tunneling parameters. At the same time, UI interface was developed based on the tunneling parameter matching model. The matching model based on BP neural network and PSO algorithm is compared in simulation experiments and engineering case. It is verified that the matching model based on SVM and EAIW‐IPSO still maintains great accuracy and stability as the number of samples continues to decrease. The paper provides a better solution for the matching of tunneling parameters in actual engineering.

Inertia Characteristic of DFIG-Based WT Under Transient Control and its Impact on the First-Swing Stability of SGs

The first-swing stability of synchronous generators (SGs) has a close relationship with synchronizing ability of the grid and inertia characteristic of all the generators. This paper studies inertia characteristic of doubly fed induction generator (DFIG) based wind turbine (WT) under transient control to analyze its impact on the first-swing stability of SGs. First, an analytic model of DFIG-based WT following the concept of motion equation is developed to describe and explain its inertia characteristic. The foundation is the definition of internal voltage of DFIG. Based on the model, an important conclusion is drawn that DFIG-based WT under transient control during grid fault has adjustable inertia characteristic that has a clear link with control parameters. Then, the impacts of transient control parameter of DFIG-based WT on the first-swing stability of SGs are studied through numerical simulation. Finally, the impact mechanism of transient control of DFIG-based WT on the first-swing stability of SGs is clearly explained by physical concept of inertia characteristic and synchronizing force.

A Novel Data Classification Method and its Application in IRIS Flower Shape

IRIS flower data is a class of multi variable data set, which is widely applied in data classification. This paper aims at the parameter optimization problem of least squares support vector machine (LS-SVM) in data classification, an improved particle swarm optimization(IMPSO) algorithm is introduced into the LS-SVM model for improving the learning performance and generalization ability of LS-SVM model. A new data classification method based on IMPSO algorithm and LS-SVM (IMPSO-LS-SVM) model is proposed. First, the numbers of current iteration and population are added into the control strategy of adaptive adjustment inertia weight in order to improve the performance of inertia weight of PSO algorithm. Then the IMPSO algorithm is used to search the optimal combination values of the parameters of kernel function for obtaining the IMPSO-LS-SVM. Finally, the training samples are used to comprehensively train the IMPSO-LS-SVM, and the best large-scale data classification model is constructed. The IRIS flower data is used to validate the effectiveness of the IMPSO-LS-SVM model. The result indicates that the IMPSO algorithm can effectively search the optimal combination values of the parameters, and the proposed data classification model has better generalization performance, faster training speed and higher classification precision.

An Adjustable Inertia Balance Support for High-Speed Scanning Probe Microscope

An adjustable inertia balance support is proposed to counterbalance the inertial force from the actuators for high performance scanning probe microscope. The adjusting method is based on voltage proportion control. In contrast with traditional method that adding or removing mass, it is very convenient to adjust to minimize the inertial force transmitted to the supporting base. It may have a promising application on the current inertia balance support structure, which is used in some high-speed scanning probe microscope. What is more, it has a very good compatibility with current structure.

Nominal shocks in monopolistically competitive markets: An experiment

A market experiment examines the capacity of price and information frictions to explain real responses to nominal price shocks. Results indicate that both price and information frictions impede the response to a nominal shock, as predicted by the standard dynamic adjustment models. Observed adjustment delays, however, far exceed predicted levels. Results of a pair of subsequent treatments indicate that a combination of announcing the shock privately to all sellers (rather than publicly) and a failure of many sellers to best respond to their expectations explains the observed adjustment inertia.

Design and Dynamic Analysis of an Adjustable Inertia Absorber for Semiactive Structural Vibration Attenuation

A new class of adaptive tuned vibration absorber, a variable effective inertia absorber, is presented to impart optimum vibration absorption. The tuning scheme has two facets: spectral analysis of the excitation and a concurrent in situ tuning of the absorber. The spectral analysis reveals the frequency content of the excitation. The online tuning uses the frequency content of the excitation to reposition a moving mass and change the damping coefficient of a variable rate damper for optimal (broadband) or tonal vibration suppression. The nonlinear differential equations of motion are linearized and then utilized to develop the online tonal and the broadband tuning of the variable effective inertia absorber. A case study is presented to demonstrate the novelty of the concept. The results show that the retuned absorber delivers considerable vibration suppression improvement over the detuned one.

Old habits die hard

In the economic literature the reasons for recession during the transformation of a planned into a market economy are still debated. The following article sets the arguments in this debate against an interpretation of the stylised facts of the transformation process in Central Eastern Europe that is centred around the legacy of soft budget constraints for state owned enterprises. It is shown that deficient bankruptcy enforcement and a perverse incentive structure at the firm level can account for adjustment inertia in emerging market economies.

Sluggish quantity adjustment in a non‐clearing market—a disequilibrium econometric application to the loan market

AbstractThe paper argues that the estimated speed of price adjustment in a disequilibrium econometric model is likely to be biased if allowance is not made for quantity adjustment inertia on both sides of the market. Furthermore, if the model estimated is static rather than dynamic then, in certain circumstances, an excess demand regime may be mistaken for one of excess supply and vice‐versa. In an empirical application to the loan market for the clearing banks in Ireland we can claim to have obtained some support for this belief.