Electric Vibration Research Articles

Design of tuned mass damper for the electric reactor based on finite element method

AbstractThe reliable operation of the electric reactor is critical for ensuring energy transmission in the power system. Vibration is an important influencing factor. This study focused on the vibration response characteristics of the electric reactor during the operation process. The vibration at the measuring points on four side surfaces and the top of the oil tank is measured and analysed by applying the rated voltage at the rated frequency on the reactor. The frequency corresponding to the maximum vibration amplitude at the measuring point between the reinforced iron on the side surface of the reactor is determined. The tuned mass damper (TMD) is designed and the material is prepared. The specific frequency tuning mechanism is designed to suppress the reactor's vibration. The damper's optimal structural size is determined based on finite element method according to modal analysis results. According to the simulation results, the designed TMD can provide an inertia force at the target frequency for the controlled structure along the opposite direction, significantly reducing the electric reactor's vibration amplitude and effectively suppressing the vibration at a single frequency. In addition, static analysis and model strength checks are also conducted to ensure the damper's stability and safety in actual applications.

Electric Vehicle Battery Technologies: Chemistry, Architectures, Safety, and Management Systems

Electric and hybrid vehicles have become widespread in large cities due to the desire for environmentally friendly technologies, reduction of greenhouse gas emissions and fuel, and economic advantages over gasoline and diesel vehicles. In electric vehicles, overheating, vibration, or mechanical damage due to collision with an object or another vehicle can lead to the failure of lithium-ion batteries up to thermal runaway and fire. Therefore, the development of battery safety control systems is one of the most important factors contributing to the large-scale electrification of public and private transport. This review examines the design features of the location and management of the battery pack to achieve maximum safety and operational efficiency when using an electric vehicle. The power characteristics and life-cycles of various types of lithium-ion batteries depending on the chemical nature of their electrodes are considered, using the example of commercial vehicles’—Tesla, Nissan Leaf, Porsche Taycan, Zeekr, and Chevrolet Volt—strategic technologies for the placement and packaging of batteries, and battery cooling and monitoring systems (State of Health and State of Charge) are also discussed. In conclusion, the current challenges in the field are summarized and promising research directions are proposed.

Whistle, whine and modal implications due to the electromechanical coupling of an electric powertrain

Electric (e-) powertrain Noise, Vibration and Harshness (NVH) shows tonal behaviour due to the electromagnetic (EM) forces in the e-motor (leading to whistling noise) and the gear meshing (leading to whining noise). Tonal excitations activate different system modes as the motor speed changes, amplifying whistling and whining. Accurate prediction of resonance speeds and aggressive NVH is essential. Due to EM interactions, the e-motor exhibits EM torsional stiffness, affecting the system dynamics. Past studies considered EM stiffness in torsional vibration lumped parameter models, mostly neglecting flexible components (i.e. powertrain housing). In this work, the EM stiffness is calculated using the Frequency Response Function method and is included for the first time in the modal analysis of a three-dimensional e-powertrain model. This enables e-powertrain electromechanical coupling analysis during the design phase, considering the housing three-dimensional flexibility, a key NVH contributor. Conducting modal analysis with the EM stiffness shows effects on the system natural frequencies, along with the mode shapes at different frequency ranges and operating speeds, establishing an accurate design method to describe the e-powertrain dynamics and provide clearer insight on the NVH physics.

Electrodynamic analysis of a sinusoidal antenna for small wave sizes

Background. The work is aimed at developing and researching rigorous methods for calculating thin-wire structures with a complex generatrix shape, having small wave sizes, as well as studying the physical processes occurring in them. A special case of such structures is a sinusoidal antenna operating in a standing current wave mode. Aim. In progress the solution of internal and external problems of electrodynamics is carried out for a sinusoidal antenna of small wave sizes located above an infinitely extended ideal reflector. The currents on the elements of the structure are calculated, its input resistance and radiation characteristics are determined. Methods. The research is based on a strict electrodynamic approach, within the framework of which, for the specified structure in the thin-wire approximation, an integral representation of the electromagnetic field is formed, which, when considered on the surface of conductors together with boundary conditions, is reduced to a system of Fredholm integral equations of the second kind, written relative to unknown current distributions on conductors (internal task). Results. A mathematical model of the radiating structure is proposed, determined: the input resistance of the structure and the basic characteristics of its radiation. It is shown that the operating range of a sinusoidal antenna in the standing wave mode is determined by the quality factor of the input impedance resonances; An increase in the width of the sinusoidal conductor leads to a decrease in the resonant frequencies of the input resistance with a simultaneous increase in the quality factor of the resonances. Conclusion. From a practical point of view, the use of the considered structure allows significantly reduce the dimensions in comparison with a thin electric vibrator, however in this case, the operating range will be correspondingly narrowed, which is determined, due to the weak dependence of the radiation characteristics on frequency, by the quality factor of the resonances. The current distribution on the generatrix of the structure can be considered as a «projection» standing surface wave localized in the plane of a sinusoidal conductor, and resulting from the superposition of forward and backward surface (slow) waves propagating at a speed significantly lower than the speed of light. To further clarify the physics of the processes occurring in the structure, one should use spectral analysis of current functions and study the distributions of the electromagnetic field in the near zone of the structure.

Examining the “unearthly archives”: Spiritualism, Psychical Research, and Psychometric Material Culture in the US and Britain

Abstract This article examines the intersection of material culture and the occult by exploring the practice of psychometry, drawing parallels between this esoteric mode of object interpretation and more conventional approaches. Coined by physician Joseph Rodes Buchanan in the 1840s, psychometry—meaning “soul or mind measurement”—is the ability of “sensitive” individuals, often women, to read an object’s electrical vibration and glean information about its history, as well as that of its owner, living or deceased. Adopted by spiritualists and psychical researchers in the United States and Britain, psychometry mediated between humans and objects, and humans and their own mortality, in the decades spanning the turn of the twentieth century. Drawing on material culture studies, consumer studies, and histories of spiritualism and psychical research, I contextualize and compare firsthand accounts of psychometric readings with more traditional approaches to object-based inquiry to contend that psychometry is a mode of affective design historical practice, a speculative design history that relies on senses other than vision, and knowledge more intuitive than rational.

A novel multi-excitation transient vibration framework for coupling three- and one-dimensional pumped storage hydropower shafting systems

In vibration models of shafting systems, the hydraulic excitation is difficult to characterize due to the complex and changeable hydraulic factors. Thus, hydropower units are not well understood in terms of their dynamics and stability control under transient processes. A hydraulic–mechanical–electric multi-excitation transient vibration calculation framework is developed for analyzing the relationship between shafting vibration and internal flow regimes. First, the boundary data from penstocks, tailraces, and hydro-turbine are interacted with using one-dimensional and three-dimensional (1D–3D) coupling; Second, user-defined function secondary development is applied to achieve two-stage guide vane closure and the runner's variable speed rotation; Third, based on the computational fluid dynamics results, a multi-excitation vibration model is established to analyze shafting system characteristics. There is less than 1.2% error between the algorithm and the field test in terms of speed peak values. Under braking or reverse pumping modes, various vortice clusters are generated in the blade channel as well as the cascade, blocking the flow passage and leading to the runner's unbalanced force. Three sudden increases in vibration amplitudes of the shafting system have occurred in the radial direction under load rejection, each corresponded to the runner's stall rotations. The change trend in axial vibration amplitudes, however, is closely related to the change in axial hydraulic thrust. Furthermore, in braking and reverse pumping conditions, the axis trajectory is more complex under the action of multiple coupling factors than when only hydraulic factors are considered.

Investigation of experimental parameters in the electric field and mechanical vibration integrated AFM-based nanopatterning on PEDOT

Atomic force microscope (AFM)-based nanomanufacturing offers an affordable and easily deployable method for fabricating high-resolution nanopatterns. This study employs a comprehensive design of experiment (DOE) approach to investigate the effects of various parameters, such as voltage, speed, and vibration axis, on the width and depth of lithography patterns using electrical field and vibration-assisted lithography on PEDOT: PSS films. The DOE explores the effect of voltage and speed on the process of electrical field and vibration-assisted AFM-based nanopatterning in two vibration trajectories: a circular trajectory employing X and Y axis vibration and a reciprocating trajectory employing Y axis vibration. The results indicate that using circular XY-vibration with a low stiffness contact probe and optimized speed and voltage factors results in higher depth and width of the lithography patterns compared to Y-vibration alone at the same parameters as expected. In both cases, pattern width was dominantly controlled by the voltage. Regarding depth, in XY-vibration, the speed of the tip is the most significant factor, while for Y-vibration, voltage plays the most significant role. It is noteworthy that there is a minimum threshold of speed that can produce a pattern; for example, the high-speed level that produced patterns in the circular trajectory (XY-vibration) did not produce patterns in reciprocating motion (Y-vibration). In conclusion, the study demonstrates the significant impact of voltage, speed, and axis on the width and depth of the lithography patterns. These findings can be instrumental in developing and understanding AFM-based high-resolution nanofabrication techniques.

Energy Harvesting Technologies in Electric Vehicles and Applications in Sustainable Agricultural Transportation: A Review

The increasing challenges of energy depletion, environmental pollution, climate change, and agricultural transportation costs demand innovative solutions. Electric vehicles (EVs) offer a promising solution towards mitigating these issues through renewable energy sources. However, limited driving range remains a crucial barrier to their widespread adoption, particularly in environmentally friendly agricultural transportation. This review paper comprehensively analyzes energy harvesting technologies in electric vehicles and their application in agricultural transportation. The focus is on their potential to improve driving range and address the specific needs of farmers in terms of maximizing their income. Very few review articles have been published on maximum number of possibilities of harvesting energies in electric vehicles, application in agricultural transportation and future prospects for improvement. Existing and current literature was systematically reviewed on various energy harvesting techniques applicable to EVs, including solar energy harvesting, regenerative braking, aerodynamic (wind) energy recovery, and vibration energy harvesting through suspension systems which are all renewable energy sources. Their advantages, working principle, limitations, and recent advancements were critically discussed. All explored energy harvesting methods show the ability to extend EV driving range. However, solar energy and wind or aerodynamic energy harvesting in EVs are theoretically possible but still under research for practical applications due to lots of limitations. Regenerative braking and vibration energy harvesting show the most promising current applications. The Electrical or electromagnetic vibration energy harvesters produce better results over mechanical (hydraulic and pneumatic harvesters). When optimization is employed, better results were achieved. Research on the application of artificial intelligence based computer algorithms to optimize and produce the best amount of harvested energy in EVs will play a significant contribution in the adoption of EVs for sustainable agricultural transportation.

Maximization of entropy production during vibration in a suspension based on graphite and silicone oil.

The electrical conductivity of a suspension of graphite and silicone oil in the presence of a small electric potential difference and vibration (40÷50Hz) is considered. The concentration of the suspension was selected near the percolation threshold. It has been found that such a nonequilibrium system evolves to increase its dissipation power, and low-energy vibrations accelerate, and high-energy ones hinder this process. Since the dissipation power of the considered system is proportional to entropy production, the results obtained are consistent with the so-called maximum entropy production principle (MEPP). This is the first experimental confirmation of MEPP in the case of a nonequilibrium process with continuous transformations under conditions for the emergence of alternative variants for the development. The possibility of choice among alternatives in a complex system is a fundamental point in the experimental discussion of MEPP, and it was previously underestimated.

Low frequency vibration monitoring of wind turbine tower based on optical fiber sensor and its potential for internet of things

Among all renewable energy sources, wind energy is a cost-effective alternative energy source. The majority of wind turbines are built in harsh environments due to their power generation characteristics, which is one of the prime reasons resulting in frequent failures of wind turbine. Among various failures, the vibration of wind turbine tower cannot be ignored because it is a precursor of the failure of the wind turbine. The electrical vibration sensors have the problems of power supply and electromagnetic interference for the condition assessment of wind turbine tower. A vibration sensor based on optical Fabry-Perot (F-P) interference principle with high sensitivity is designed, fabricated and characterized to further meet the requirements of vibration detection of wind turbine tower. The mechanical simulation model of the diaphragm and optical vibration platform is constructed to verify the sensing characteristic of the F-P optical fiber vibration sensor (OFVS). The experiment results indicate a resonant frequency of the F-P OFVS of 223 Hz, an output sensitivity of 122.22 mV/m·s−2 at 10 Hz, and a horizontal output of less than 6 %. In addition, the designed F-P OFVS possesses the superiorities of compact structure, passive and excellent anti-electromagnetic interference, and has a wide application prospect in the vibration detection of the wind turbine tower.

Dynamic characteristics analysis and vibration control of coupled bending-torsional system for axial flow hydraulic generating set

Aiming at the vibration problems of shaft system for axial flow hydraulic generating sets caused by complex excitations, the coupled bending-torsional dynamic equations of rotor-runner system are established considering multi-effect including hydraulic, mechanical, electrical and other external vibration sources. Whether taking the torsional degree of freedom into account, the stability and disparate destabilization laws of system periodic solutions are analyzed using the shooting method combined with Floquet theory. On this basis, the influence of coupling bending-torsional effect on system dynamic behaviors is discussed through bifurcation diagrams, Poincaré maps, trajectories, time domains and frequency spectrums. Furthermore, in order to alleviate the unsteady vibration of rotor as well as runner, the magnetorheological fluid damper is introduced into the shaft system, and numerical simulations are performed on models of coupled bending-torsional systems with or without the magnetorheological fluid damper. The analyses indicate that the interaction between bending and torsional vibration of the shaft system will expand the chaotic sustained range for rotor. Meanwhile, the amplitude of the rotor-runner system is magnified owing to the torsional vibration, which leads to local rubbing faults of the system under specific operating conditions, while the intervention of the magnetorheological fluid damper can significantly suppress the nonlinear motion of rotor and runner, reduce the amplitude of system vibration, so as to avoid the occurrence of friction defects effectively. The above research results can provide conducive references for fault diagnosis, optimized design, and vibration control of axial flow hydraulic generating sets.

Investigation of noise characteristics of electric vibrator utilizing acoustic camera and transfer path analysis

Abstract Mechanical equipment operation frequently results in noise generation, which can raise concerns regarding quality and safety. This study focuses on electric vibrators, essential electromechanical systems, with the goal of identifying the source and transfer path of noise. To achieve this objective, an acoustic camera positioning analysis was performed to approximate the distribution and characteristics of the noise. Building upon this foundation, a thorough evaluation of the transfer path and noise contribution was conducted. Subsequently, targeted noise suppression methods were implemented based on the properties of the noise. Primary noise sources were observed to be classified into wind turbulence and mechanical vibration based on operating conditions. Time-frequency analysis revealed the presence of low-frequency signals (around 50 Hz) and intermediate-frequency signals (around the resonant frequency), corresponding to wind-induced and mechanical response noise, respectively. Leveraging the characteristics of the noise and its transfer path, passive methods (Sound-absorbing rubber and Soundproof cotton) and active method (FxLMS algorithm) were employed. The findings of this study contribute to a better understanding of noise mechanisms and provide insights for noise emission strategies.

Optimization of electromagnetic layout for E-machine in electric vehicles: Achieving high performance, efficiency and NVH

The development of electric vehicles (EVs) presents the challenge of optimising electric machines to enhance efficiency, compactness, noise, vibration, harshness (NVH), and affordability, while reducing the dependence on heavy rare-earth materials to reduce the CO2 footprint of electric powertrains. This paper introduces a comprehensive optimization approach for the electromagnetic design of permanent magnet synchronous machines (PMSMs), employing a combination of Design of Experiment (DoE) and Robust Neural Networks (RNN). The optimization framework is utilised to comprehensively address the multiple objectives of an electric machine, including efficiency, noise, vibration, harshness (NVH), and cost. The integration of Artificial Intelligence (AI)-driven modelling has resulted in significant performance improvements, achieving up to 96% total efficiency over the entire load cycle with substantial NVH reductions of up to 20 dB, while reducing the magnet rare earth materials by 35% compared to the baseline. Furthermore, this methodology reduces the simulation time by up to 90%, demonstrating the potential of combining neural network optimization with conventional finite element simulation techniques. The validation of the AI-driven optimization approach with the measurement of the baseline and optimised electric machines for efficiency and vibration is demonstrated for correlation.

On the Applicability Boundaries of the Pocklington and Gallen Equations in Modelling of Electric Vibrators

On the Applicability Boundaries of the Pocklington and Gallen Equations in Modelling of Electric Vibrators

Improving of pure electric vehicle sound and vibration comfort using a multi-task learning with task-dependent weighting method

The improvement of pure electric vehicle (PEV) vibro-acoustical comfort quality has currently taken precedence in development. The acoustic and vibration characteristics of PEVs exhibiting a wide frequency distribution and encompassing numerous objectives, thereby presenting challenges in its predicting and optimizing. Traditional simulation and experimental methods, though capable of simultaneous analysis of noise and vibration information, grapple with intricate modeling and reduced efficiency. This paper proposes a solution through a multi-task learning approach with homoscedastic uncertainty interpretation as task-dependent weighting (TDW), effectively balancing losses across distinct regression tasks. This method rectifies biased predictions among tasks, ensuring accurate interior vibro-acoustical comfort prediction across diverse features and frequency distributions. Furthermore, a fusion method, integrating TDW-based multi-task learning with a vibro-acoustical comfort knowledge graph (VACKG), is introduced. The proposed method is validated through PEV noise and vibration prediction and optimization, demonstrating its accuracy and robustness in enhancing interior vibro-acoustical comfort in real vehicular experiments.

Vertical dynamics analysis and multi-objective optimization of electric vehicle considering the integrated powertrain system

Integrated powertrain system, mainly composed of driving motor and reducer, is one of the excitation sources to electric vehicle vibration but is limited in coupling with the vertical vehicle dynamic in the existing research, which restricts the reliability of dynamics investigation of vehicle and integrated powertrain system. This work proposes a novel vertical dynamic model of the electric vehicle considering the integrated powertrain system, enabling the way to access the coupled vibration among the chassis, unsprung mass, and integrated powertrain system. The road irregularity, unbalanced magnetic pull, and gear mesh excitation are developed and are further applied to the novel vehicle dynamic model with ten degrees of freedom (DOFs). Then, the dynamic response between the novel model and traditional one is compared. Further, the effects of the stiffness and damping of suspension and mounting on the vibration of chassis and integrated powertrain system are explored by numerical calculation. Finally, a multi-objective optimization model is proposed and is driven by the dragonfly algorithm to minimize the vibration of chassis and integrated powertrain system. The research results shown that there will be present the new complex dynamic characteristics with considering the excitation from the integrated powertrain system. The suspension and mounting parameters have the nonlinear effects on the vehicle vibration. And the system vibration can be globally optimized with the optimization algorithm.

An inerter-integrated wave energy converter for vibration mitigation of offshore floating buoys and its experimental validation

This paper presents an inerter-integrated wave energy converter (WEC) for vibration mitigation of offshore floating structures. The proposed WEC complies a floating buoy and an upper structure placed over the floating buoy connected by a spring and a ball screw with a rotational mass, which converts linear motion to rotational one, and the ball screw is connected to a rotating generator. As the two bodies move separately, the inertial force proportional to the relative acceleration of the two bodies called inerter is produced. This mechanism, similar to passive vibration reduction systems in automobiles and civil structures, not only produces electric power but also mitigates the vibration induced by the wave disturbances acting on the floating buoy. In this research, its analytical model was developed based on the two-degree-of-freedom dynamic model and the circuit equation of the generator. Numerical studies considering only the heave direction showed that the proposed WEC can achieve electric power generation and vibration mitigation of the upper structure at the same time. Moreover, to verify the efficacy experimentally, a small-scaled prototype was designed, and wave flume testing was conducted, which demonstrated a response reduction of more than 40% compared to the device without the proposed mechanism.

An Extremely Close Vibration Frequency Signal Recognition Using Deep Neural Networks

This study proposes the utilization of an optical fiber vibration sensor for detecting the superposition of extremely close frequencies in vibration signals. Integration of deep neural networks (DNN) proves to be meaningful and efficient, eliminating the need for signal analysis methods involving complex mathematical calculations and longer computation times. Simulation results of the proposed model demonstrate the remarkable capability to accurately distinguish frequencies below 1 Hz. This underscores the effectiveness of the proposed image-based vibration signal recognition system embedded in DNN as a streamlined yet highly accurate method for vibration signal detection, applicable across various vibration sensors. Both simulation and experimental evaluations substantiate the practical applicability of this integrated approach, thereby enhancing electric motor vibration monitoring techniques.

Pre-analytical stability of the CEA, CYFRA 21.1, NSE, CA125 and HE4 tumor markers.

For lung cancer, circulating tumor markers (TM) are available to guide clinical treatment decisions. To ensure adequate accuracy, pre-analytical instabilities need to be known and addressed in the pre-analytical laboratory protocols. This study investigates the pre-analytical stability of CA125, CEA, CYFRA 21.1, HE4 and NSE for the following pre-analytical variables and procedures; i) whole blood stability, ii) serum freeze-thaw cycles, iii) electric vibration mixing and iv) serum storage at different temperatures. Left-over patient samples were used and for every investigated variable six patient samples were used and analysed in duplicate. Acceptance criteria were based on analytical performance specifications based on biological variation and significant differences with baseline. Whole blood was stable for at least 6 hours for all TM except for NSE. Two freeze-thaw cycles were acceptable for all TM except CYFRA 21.1. Electric vibration mixing was allowed for all TM except for CYFRA 21.1. Serum stability at 4°C was 7 days for CEA, CA125, CYFRA 21.1 and HE4 and 4 hours for NSE. Critical pre-analytical processing step conditions were identified that, if not taken into account, will result in reporting of erroneous TM results.

Research progress in spasmodic torticollis rehabilitation treatment.

Spasmodic torticollis (ST) is a focal dystonia that affects adults, causing limited muscle control and impacting daily activities and quality of life. The etiology and curative methods for ST remain unclear. Botulinum toxin is widely used as a first-line treatment, but long-term usage can result in reduced tolerance and adverse effects. Rehabilitation therapy, with its minimal side effects and low potential for harm, holds significant clinical value. This article explores the effectiveness of adjunctive therapies, including exercise therapy, transcranial magnetic stimulation, shockwave therapy, neuromuscular electrical stimulation, vibration therapy, electromyographic biofeedback, and acupuncture, in the treatment of ST. The aim is to provide clinicians with additional treatment options and to discuss the efficacy of rehabilitation therapy for ST.