Transient Behavior Research Articles

Transient dynamic stress behavior analysis of the axial flow pump as turbine at part loads

To explore the structural dynamic characteristics of the impeller and shaft system of the axial flow pump as turbine, the variation law of impeller transient equivalent stress, deformation, and the impeller and shaft system mode are analyzed by the transient fluid-structure interaction method. Findings indicate that the equivalent stress is centralized at the blade root around the hub and tends to decrease as it moves towards the shroud. The maximum equivalent stress at 1.0Qbep and 1.1Qbep is 1.26 times and 2.0 times higher than that at 0.8Qbep. Blade deformation is significantly influenced by flow rate. The maximum deformation of the blade at 1.0Qbep and 1.1Qbep is 1.6 times and 3.6 times higher than that at 0.8Qbep. The impeller and shaft system with prestress in dry mode has an average natural frequency of the first 10 orders that is 16.7 Hz higher than without prestress. However, with the fluid adding mass and flow damping, the average natural frequency of the first 10 orders of the impeller and shaft system in wet mode is reduced by 278.08 Hz compared with dry mode. In fact, the impeller and shaft system of the axial flow pump as turbine is not prone to vibration.

Control of combustion distributions in compression-ignition engines using rate-constrained model predictive control with reference preview

To support the transition toward sustainable alternative fuels, advanced combustion control strategies can enable operation of compression-ignition engines with a wide range of fuels under challenging inlet conditions. This work presents a rate-constrained model predictive controller that uses state estimate feedback and integral tracking to control combustion phasing distributions by coordinating fuel injection timing with the power supplied to an electrically heated in-cylinder ignition assist device. The controller was validated in simulation using a statistical virtual engine that replicates both transient and steady-state stochastic combustion behavior. This virtual engine was tuned with data from experiments conducted at a low pressure-temperature inlet condition that induced highly variable combustion behavior akin to operating with a low cetane fuel. The controller achieves rapid tracking of combustion phasing step commands by supplying ignition assist power when needed to support fuel injection timing. All the while, it maintains closed-loop combustion variability at less than 6% higher than the open-loop system variability, and enforces ignition assist power range and rate constraints to reduce thermo-mechanical stress on the actuator. Furthermore, reference tracking is ensured even if combustion sensitivity to the ignition assist actuator deviates by as much as 83% from the controller’s internal model, without the need for retuning control parameters. Finally, the controller can coordinate actuators early and speed up tracking when a reference trajectory is previewed ahead of time, and its horizons can be tuned in a manner that maintains desirable control performance without compromising on computational tractability.

Analysis, Simulation, and Experiments of Dynamics and Control of a Hydrostatic Wind Turbine Under Partial Load

Abstract Kω2 control, also called torque control, is a popular method for maximizing wind turbine power. For hydrostatic wind turbines, torque control becomes pressure control with pc=K'ω2 because pressure is proportional to torque. Inverse Kω2 control is an alternative approach using rotor speed control with pc=(p/K')1/2. This work analyzes the dynamics of hydrostatic wind turbines using forward and inverse Kω2 control with P-, PD-, PI-, and PID-control for feedback. Dimensionless, linearized models are used. Analysis shows that the mechanical rotor dynamics are much slower than the hydrostatic transmission dynamics and that frictional and leakage losses are negligible. Linear perturbation of the nonlinear model reveals that the closed-loop control is not in Evan's form, so that closed-loop poles and zeros both vary with the loop gain. Pole and zero root locus analysis shows how systems responses change with controller gains. Both control approaches require derivative controller action to sufficiently dampen their responses; both are also fundamentally limited in speed of response by a slow stable pole regardless of controller loop gains. Nonlinear system simulation shows that both control approaches track the maximum power point with nearly identical transient behavior and have nearly identical power losses when using suboptimal values of the control law gain, K. Pressure control has a gain margin of infinity and a phase margin of 99.3 degrees, while speed control has a gain margin of 22.4 dB and a phase margin of 73.8 degrees showing that pressure control is more robust than speed control. Experiments using the power regenerative hydrostatic test stand at the University of Minnesota show that the control approaches have different transient responses but capture comparable power under steady and turbulent conditions.

Analysis of Transient Thermoacoustic Characteristics and Performance in Carbon Nanotube Sponge Underwater Transducers

Recent advancements in marine technology have highlighted the urgent need for enhanced underwater acoustic applications, from sonar detection to communication and noise cancellation, driving the pursuit of innovative transducer technologies. In this paper, a new underwater thermoacoustic (TA) transducer made from carbon nanotube (CNT) sponge is designed to achieve wide bandwidth, high energy conversion efficiency, simple structure, good transient response, and stable sound response, utilizing the TA effect through electro-thermal modulation. The transducer has potential application in underwater acoustic communication. An electro-thermal-acoustic coupled simulation for the open model, sandwich model, and encapsulated model is presented to analyze the transient behaviors of CNT sponge TA transducers in liquid environments. The effects of key design parameters on the acoustic performances of both systems are revealed. The results demonstrate that a short pulse excitation with a low duty cycle could greatly improve the heat dissipation of the encapsulated transducer, especially when the thermoacoustic response time becomes comparable to thermal relaxation time.

Real-time prediction of bottom-hole circulating temperature in geothermal wells using machine learning models

Drilling high-temperature geothermal wells presents technical and economic challenges. Real-time and precise estimation of bottom-hole circulating temperature (BHCT) during geothermal drilling is crucial for maximizing the working life of drill bits and temperature-limited bottom-hole assembly (BHA) components, thereby avoiding unplanned and unnecessary bit/BHA trips. This study introduces a novel machine learning (ML) model that accurately predicts BHCT in real time, enhancing proactive temperature management and mitigating thermally induced challenges during geothermal drilling operations.An integrated thermo-hydraulic model, validated using publicly available data from the Utah FORGE field, was used to generate a large dataset that simulates the transient BHCT under typical drilling conditions. This dataset was subsequently used to train and test the prediction capability of six ML models of the BHCT, including deep neural networks (DNN), support vector machines (SVR), random forests (RF), extreme gradient boosting regressor (XGBoost), ensemble (Stacked) algorithm, and long-short term memory (LSTM) networks. It was also used to generate an understanding of the non-linear relationship between the input features and the output variable (BHCT). Resultsdemonstrate the benefits of implementing the LSTM model for reliable prediction of the BHCT and capturing its full-scale transient behavior in geothermal wells. The LSTM model stands out for its excellent generalization capability, stability, and precision in real-time estimation of BHCT across various geothermal drilling conditions, including both stationary and dynamic scenarios. This is achieved without the high computational costs associated with complex numerical models, thus preventing temperature-related drilling problems. Among the other supervised ML models, the XGBoost model can still reliably simulate the BHCT with a mean absolute error (MAE) below 1 °C during geothermal drilling at constant drilling parameters, but will show overfitting when drilling parameters change.

High Temperature Solid Oxide Electrolyte Fuel Cell Formulation: Non-Steady State Utilization of Fuel and Oxidant

The formulation presented in this paper was developed with the objective of its application to investigate the transient behavior of a high temperature solid oxide fuel cell (SOFC); especially with respect to the non-steady state consumption of fuel and oxidant reactants. Specifically, the chemical species transient amounts, their mole fractions, and total pressures in the cell anode-side fuel- (hydrogen) and cathode-side oxidant- (oxygen of the air) chambers can be predicted under the isothermal condition at a fixed cell-current level. The developed formulation is also capable of predicting the transient mole fraction profiles of fuel (hydrogen) and oxidant (oxygen) in the cell porous anode and cathode, respectively; thus, providing insight into the reactant species' effective transport and their utilization, via electrochemical reactions, in the cell porous electrodes. The presented formulation can be adapted for any fuel and oxidant combinations in any high temperature SOFC.

A facile DNA coacervate platform for engineering wetting, engulfment, fusion and transient behavior.

Biomolecular coacervates are emerging models to understand biological systems and important building blocks for designer applications. DNA can be used to build up programmable coacervates, but often the processes and building blocks to make those are only available to specialists. Here, we report a simple approach for the formation of dynamic, multivalency-driven coacervates using long single-stranded DNA homopolymer in combination with a series of palindromic binders to serve as a synthetic coacervate droplet. We reveal details on how the length and sequence of the multivalent binders influence coacervate formation, how to introduce switching and autonomous behavior in reaction circuits, as well as how to engineer wetting, engulfment and fusion in multi-coacervate system. Our simple-to-use model DNA coacervates enhance the understanding of coacervate dynamics, fusion, phase transition mechanisms, and wetting behavior between coacervates, forming a solid foundation for the development of innovative synthetic and programmable coacervates for fundamental studies and applications.

Transient skin friction behavior associated with hemisphere-based vortex ring collisions

Global and local transient skin friction variations resulting from a large-eddy simulation study on ReΓ0=3000 vortex rings colliding with surface-mounted hemispheres of hemisphere-to-vortex-ring diameter-ratios of 0.5≤D/d≤2 are investigated here. Skin friction distribution changes due to the approaching primary vortex ring, formation of secondary/tertiary vortex rings, subsequent mutual interactions between various vortex ring structures, and azimuthal instabilities are clarified with a view to better establish their relationships when the relative hemisphere size varies. Results show that the primary vortex ring produces the highest skin friction levels when it is close to or collides with the hemisphere/flat wall. Additionally, entrainment of wavy secondary/tertiary vortex rings leads to them entangling around the primary vortex ring and resulting in segmented skin friction regions at later stages of the collision process, regardless of the diameter-ratio. Unlike smaller hemispheres, the largest D/d=2 hemisphere here restricts all skin friction changes along its surface with the flat wall unaffected. It is also revealed here that while the diameter-ratio governs the global skin friction distributions, how secondary/tertiary vortex rings interact with the primary vortex ring and how azimuthal instabilities manifest and evolve for all the various vortex rings confer strong influences on the breaking-up and dissipation of regions with high skin friction levels.

Full state observer-based pole placement controller for pulse width modulation switched mode voltage-controlled buck Converter

Switched mode DC-DC converters play an important role in today's renewable energy systems, electric Vehicles, consumer electrical appliances, and many more. While many researchers have designed controllers for DC-DC converters, achieving low implementation cost remains a significant hurdle. This paper proposes a cost-effective observer-based pole placement controller for a PWM voltage-controlled Buck converter with clear step by step design approach. The state space averaged model of the DC-DC power converter is used to design pole placement with integrator compensator and full state observer. Pole placement is employed to improve the transient and steady state behavior of Voltage reference tracking response and full state observer is applied to extract the inductor current with the aim of removing the actual current sensor. Design specifications are set to a settling time of less than 5 msec and an overshoot of less than 5 %. While designing Observer-Controller combination, the separation principle, designing the controller and observer independently, is utilized by placing the observer poles far to the left of the controller poles for the Observer to converge faster. The designed controller and observer is verified with simulation in MATLAB/SIMULINK software and design of developed controller and observer are realized using low-cost analog electronics circuit components The results shows that the proposed system's strength in tracking the reference output voltage even in the presence of input voltage disturbance and the mean value of inductor current is well extracted having only the output voltage and MOSFET gate signal.

Analyzing the Effects of Polymeric Dielectric Materials on Micro Capacitive Pressure Sensors: A Model Incorporating Displacement-Dependent Porosity

Recently, the extensive utilization of porous polymeric materials to amplify the sensitivity of capacitive devices is noticeable. The absence of an effective mathematical model for studying these devices has spurred the development of a comprehensive mathematical model in the current work. This model is formulated to analyze the static and dynamic behavior of systems incorporating a porous polymer dielectric material within the gap between flexible and fixed microplates. The derived nonlinear governing equations encompass the effects of electrostatic force, von-Karman nonlinear strains, and displacement-dependent porosity. Employing spatial decomposition, the resulting nonlinear algebraic equations and ordinary differential equations are leveraged to study the static and transient dynamic behavior, as well as the frequency response of the sensor using a learning approach. Two scenarios are investigated to assess the impact of various geometrical and physical parameters on sensor sensitivity one with a polymeric material and another without, each with distinct parameter values. The results reveal that the inclusion of a polymeric dielectric material increases electrostatic force but concurrently elevates the equivalent stiffness of the structure. The effectiveness of using a polymeric dielectric material is contingent upon the specific geometrical and physical properties of the sensor. Moreover, the obtained results in simplified cases are compared to existing numerical and experimental data, demonstrating a high degree of agreement. This work significantly contributes to advancing the understanding of sensors incorporating porous polymer dielectric materials and underscores their potential for enhanced sensitivity across diverse applications.

Transient dynamics of magneto-optic rotation with elliptically polarized light

In this paper, we analyze the transient behavior of nonlinear magneto-optical rotation in a 87Rb vapor cell. Our focus is on optimizing the optical rotation signal by identifying influential factors. We investigate the impact of cell temperature on alkali atom density and consider characteristics of the light field, such as polarization direction, frequency, intensity, and beam diameter. Low scanning magnetic field rates produce the usual absorption signal, whereas high rates show an asymmetric transient response with oscillatory decay. To further investigate this phenomenon, we evaluate signal amplitude and resonant peaks along the x-, y-, and z-axis directions. Notably, we establish a one-dimensional quadratic equation that describes the relationship between magnetic field scan rate and signal amplitude/peak value. Our findings facilitate the quick evaluation of cell performance, provide insights into the dynamics of ground-state coherence generation, and have potential applications in detecting transient spin coupling or monitoring magnetic fields.

A new analytically modified embedded discrete fracture model for pressure transient analysis in fluid flow

In the past few decades, multi-stage hydraulic fracturing has emerged as a crucial technology for the commercial development of unconventional oil and gas (UOG) resources. It is crucial to accurately and efficiently characterize transient fluid flow near fractures, which is a critical concern for many researchers. Discrete fracture models (DFMs) are primarily used to analyze the pressure transient behaviors of fluid flow in naturally fractured porous media. DFMs can accurately capture transient fluid flow near fractures, but they require a substantial number of grids to ensure computational accuracy, leading to higher computational costs. On the other hand, standard embedded discrete fracture models (EDFMs) based on pseudo-steady-state assumptions are computationally efficient, but they struggle to model the early transient fluid flow near fractures accurately. To address this limitation, we propose a new analytically modified EDFM (AEDFM) with structured Cartesian grids for analyzing the pressure transient behaviors of fluid flow in naturally fractured porous media.The transmissibility between the matrix and fractures is adjusted by multiplying it with a transient factor. In addition, we have validated the accuracy and efficiency of our proposed model through comparisons with results from analytical models and a standard well-testing software package. The results demonstrate the significance of our proposed model in accurately capturing transient fluid flow around fractures and reducing computational costs. In this work, we analyze the pressure transient behaviors of fluid flow using various parameter values and further evaluated the significance of the proposed modifications. The results indicate that AEDFM can effectively match the early nonlinear pressure drop near fractures compared to the standard EDFM. This work presents a powerful tool for the fast and accurate analysis of pressure transient behaviors of fluid flow in naturally fractured porous media.

Transient Performance Analysis of Centrifugal Left Ventricular Assist Devices Coupled With Windkessel Model: Large Eddy Simulations Study on Continuous and Pulsatile Flow Operation.

Computational fluid dynamics (CFD) simulations are widely used to develop and analyze blood-contacting medical devices such as left ventricular assist devices (LVADs). This work presents an analysis of the transient behavior of two centrifugal LVADs with different designs: HeartWare VAD and HeartMate3. A scale-resolving methodology is followed through Large Eddy Simulations, which allows for the visualization of turbulent structures. The three-dimensional (3D) LVAD models are coupled to a zero-dimensional (0D) 2-element Windkessel model, which accounts for the vascular resistance and compliance of the arterial system downstream of the device. Furthermore, both continuous- and pulsatile-flow operation modes are analyzed. For the pulsatile conditions, the artificial pulse of HeartMate3 is imposed, leading to a larger variation of performance variables in HeartWare VAD than in HeartMate3. Moreover, CFD results of pulsatile-flow simulations are compared to those obtained by accessing the quasi-steady maps of the pumps. The quasi-steady approach is a predictive tool used to provide a preliminary approximation of the pulsatile evolution of flow rate, pressure head, and power, by only imposing a speed pulse and vascular parameters. This preliminary quasi-steady solution can be useful for deciding the characteristics of the pulsatile speed law before running a transient CFD simulation, as the former entails a significant reduction in computational cost in comparison to the latter.

Extreme Homogeneous and Heterogeneous Multistability in a Novel 5D Memristor-Based Chaotic System with Hidden Attractors

This paper proposes a novel five-dimensional (5D) memristor-based chaotic system by introducing a flux-controlled memristor into a 3D chaotic system with two stable equilibrium points, and increases the dimensionality utilizing the state feedback control method. The newly proposed memristor-based chaotic system has line equilibrium points, so the corresponding attractor belongs to a hidden attractor. By using typical nonlinear analysis tools, the complicated dynamical behaviors of the new system are explored, which reveals many interesting phenomena, including extreme homogeneous and heterogeneous multistabilities, hidden transient state and state transition behavior, and offset-boosting control. Meanwhile, the unstable periodic orbits embedded in the hidden chaotic attractor were calculated by the variational method, and the corresponding pruning rules were summarized. Furthermore, the analog and DSP circuit implementation illustrates the flexibility of the proposed memristic system. Finally, the active synchronization of the memristor-based chaotic system was investigated, demonstrating the important engineering application values of the new system.

Analysis of interval type-2 fuzzy controller based interleaved sepic PFC converter for PQ enhancement in power solutions

The Power solutions have become indispensable for all the devices in recent years with an appropriate power conversion circuitries and control methods to ensure good dynamic response, improved stability, reliability and efficiency. The main intent of this article is to impart the designing of interval type-2 fuzzy logic controller (IT2FLC) based interleaved Sepic power factor correction (PFC) converter. This work also involves the careful design of the robust controller with enhanced precision and good power quality (PQ) performance at the AC mains. In addition, the development of IT2FLC based power solution improves the overall power conversion with stabilized output in the perspective of its quick rise time, less overshoot and fast settling time in comparison to other traditional controllers. Further, the uncertainties and issues associated with the conventional proportional integral (PI) and fuzzy logic controllers (FLCs) are handled effectively by the proposed IT2FLC controller. Moreover, this preferred converter is modeled with an internal parasitics and its performances are evaluated and compared with other conventional Zeigler Nicholas (ZN) tuned PI controller and FLC by dint of MATLAB/Simulink platform. Finally, the experimental test bench set up of 250 W, 48 V power circuitry is devised and the test outcomes confirm the excellent transient behavior and PQ performances of the modeled power solution.

Constrained Normalized Subband Adaptive Filter Algorithm and Its Performance Analysis

AbstractConstrained least mean square (CLMS) algorithm is the most popular constrained adaptive filtering algorithm due to its simple structure and easy implementation. However, its convergence slows down when the input signal is colored. To address this issue, this paper firstly introduces the normalized subband adaptive filter (NSAF) into the constrained filtering problem and derives a constrained NSAF (CNSAF) algorithm using the Lagrange multiplier method. Benefiting from the good decorrelation capability of the NSAF, the proposed CNSAF algorithm significantly improves the convergence performance of the CLMS algorithm under colored inputs. Then, the mean and mean-square stability of the CNSAF algorithm is analyzed, and the theoretical models to characterize the transient and steady-state mean square deviation (MSD) behaviors of the CNSAF algorithm are derived utilizing the Kronecker product property and vectorization method. Further to extend the CNSAF algorithm to the problem of sparse system identification, a sparse version of the CNSAF algorithm (S-CNSAF) is derived. Finally, the validity of the derived theoretical MSD prediction models and the superiority of the proposed algorithms are confirmed by extensive computer simulations on system identification with colored inputs.

Prediction of the Bubble Growth Behavior by Means of the Time-, Temperature-, Pressure- and Blowing Agent Concentration-Dependent Transient Elongational Viscosity Function of Polymers.

Bubble growth processes are highly complex processes, which are not only dependent on the foaming process parameters (temperature, pressure and blowing agent concentration) but also on the type and structure of the polymer used. Since the elongational viscosity at the bubble wall during bubble growth also depends on these influencing factors, the so-called transient elongational viscosity plays a key role in describing the gas bubble growth behavior in polymer melts. The model-based description of the transient elongational viscosity function is difficult due to its dependence on time, Hencky strain and strain rate. Therefore, representative viscosities or shear viscosity models are usually used in the literature to predict the bubble growth behavior. In this work, the transient equibiaxial elongational viscosity function at the bubble wall during bubble growth is described holistically for the first time. This is achieved by extending the so-called molecular stress function (MSF) model by superposition principles (temperature, pressure and blowing agent concentration) and by using the elongational deformation behavior (Hencky strain and strain rate) at the bubble wall during the initial, and thus viscosity-driven, bubble growth process. Therefore, transient uniaxial elongational viscosity measurements are performed and the non-linear MSF model parameters of the two investigated polymers PS (linear polymer chains) and PLA (long-chain branched polymer chains) are determined. By applying the superposition principles and by changing the strain mode parameter to the equibiaxial case in the MSF model, the transient equibiaxial viscosity master curve is obtained and used to describe the bubble growth process. The results show that the extended MSF model can fully predict the transient equibiaxial elongational viscosity function at the bubble wall during bubble growth processes. The bubble growth behavior over time can then be realistically described using the defined transient equibiaxial elongational viscosity function at the bubble wall. This is not possible, for example, with a representative viscosity and therefore clearly demonstrates the influence and importance of knowing the transient deformation behavior that prevails at the bubble wall during bubble growth processes.

Appearance of transient chaos and energy variability in Ueda oscillator driven by an amplitude‐modulated force

Transient chaos is a characteristic behavior observed in nonlinear systems, where trajectories within a specific region of phase space exhibit chaotic dynamics for a finite duration before transitioning to an external attractor. In many nonlinear systems, transient and chaotic behaviors are closely associated with variations in the system's energy. In this paper, we introduce the concept of an energy variable and establish its connection with the Melnikov integral. We explore the influence of energy variation in an amplitude‐modulated (AM) force‐driven Ueda oscillator through numerical simulations. Our investigation reveals the emergence of transient chaos, chaotic dynamics, and regular behaviors, underscoring the significant role played by the energy variable, denoted as , in the system. We employ various analytical tools, including phase diagrams, Poincaré maps, time series plots, and bifurcation diagrams, to characterize and visualize transient chaos, regular, and chaotic motions within the system.

Transient modeling of a solid oxide fuel cell using an efficient deep learning HY-CNN-NARX paradigm

Control and monitoring systems are crucial for ensuring optimal performance, efficiency, and longevity of Solid Oxide Fuel Cells (SOFC). Developing a model to accurately capture the transient behavior of the SOFC under dynamic operation is essential for these applications. As electrochemical, mass-transfer, and thermal equations are involved in SOFCs’ dynamic, physics-based approaches to capture all the complexity of SOFC systems are often too computationally expensive for real-time implementation. In this paper, an innovative multi-input neural network is developed to build an accurate model of SOFC that is computationally efficient. The proposed algorithm uses experimental data and is a modified nonlinear autoregressive exogenous (NARX) network. An optimal sequence of the most recent observations (output voltages) that characterize the SOFC dynamics is passed through stacked 1D convolutional layers (CNN) to extract latent spatial/temporal information. Then the output is concatenated with current and past exogenous inputs. The fusion of learned features, representing the internal dynamics and the effect of exogenous inputs, is then fed to a fully connected network for one-step ahead performance prediction. This hybrid structure, called HY-CNN-NARX, is capable of identifying the transient dynamics of the SOFCs by unrolling information from historical outputs and inputs within a feedforward framework. To evaluate the model performance, lab-scale tubular SOFCs are experimentally tested at 650–750 °C under various dynamic operations and initial conditions, and the transient and steady-state responses of the SOFC are collected. Once the model is validated using a wide operating range of data, the generalization and prediction performance of the proposed network is compared with a conventional NARX and a recurrent stacked Long short-term memory (LSTM) model. The comparative results demonstrate that the proposed HY-CNN-NARX model outperforms the NARX model on unseen data with an accuracy improvement of 59.2% for root mean square error and 53.7% for mean absolute percentage error. In addition, the prediction performance of the HY-CNN-NARX is comparable to its recurrent counterpart, the LSTM model, but with a 39.3% faster execution time.

Improvement of dynamic response and energy conversion ratio of a global type solenoid for high-speed valve by using an innovative magnet ring

The transient behavior and energy transmission of a global type solenoid for high-speed valve (HSV) depend upon the magnetic force acting on the sphere. Rapid responses are challenging to achieve because of the limited power supply energy, which makes it hard to optimize the magnetic force through its own structural characteristics for HSV. Aiming to obtain higher magnetic force without increasing the input electric power, an innovative magnet radial ring is presented and a relative evaluation of magnetic forces exerted on a global type solenoid for HSVs is conducted. A hollow-plunger-type magnet radial ring is engineered as a novel magnet ring form. The magnetic forces and transient action time of the conventional HSV and innovative HSV are evaluated by means of finite element method (FEM) analysis and demonstrated by verification of the experimental data. The assessment of the magnetic forces involves every solenoid with a diverse magnet ring shape with the variation of height and thickness. The suggested novel magnet ring successfully increases the magnetic force applied to the sphere by changing the internal magnetic connection structure and increasing the mechanical energy conversion ratio, according to a methodical comparison of the two HSVs' transient performances. Meanwhile the innovative magnet ring can reduce the strength of iron loss occurred in the magnetic field of HSV to realize the reduction of useless power loss. At the magnetization position at the attraction, the magnetic force is 17.35 N, while the magnetic ring increases the magnetic force to 28.84 N. Also, the maximum rising speed of the magnetic force is improved from 14945 N/ms to 38904 N/ms, and the transient action time is reduced from 3.74 ms to 1.30 ms. For the mechanical energy and iron loss energy in energy conversion occurred in solenoid, the mechanical energy ratio increases from 16.2 % (conventional valve) to 27.8 % (innovative valve) with height 26 mm and thickness 3.5 mm, while the iron loss energy ratio decreases from 40.7 % (conventional valve) to 31.8 % (innovative valve) synchronously.