Stable Operating Points Research Articles

Evaluating the thermal stability of an interior permanent magnet synchronous machine through iterative multi‐physics simulation

AbstractThis paper investigates the thermal operating capability of an interior permanent magnet synchronous machine. An iterative workflow is presented, combining electromagnetic modeling, control, power‐loss modeling, and thermal modeling to identify maximum thermal stable operating points. Special attention is given to the critical temperatures of winding and permanent magnets. A nonlinear reduced order model based on finite element method model was used to simulate the system, including an inverter model with space vector pulse width modulation in combination with field‐oriented control. Furthermore, an advanced iron core loss model and thermal lumped parameter model were employed. The presented approach allows for evaluating losses and their impact on steady‐state temperatures. The obtained results highlight the significant influence of space vector pulse width modulation on iron core losses and the importance of considering both advanced power‐loss models and adequate thermal models when analyzing the machine's thermal state. This research emphasizes the concept of a thermally stable envelope, providing a comprehensive understanding of the thermal boundaries under various operating conditions.

Analysis and Prediction of the Stability Limit for Centrifugal Compressors with Vaneless Diffusers

A numerical study was conducted to identify the mechanisms involved in the destabilisation of centrifugal compressors with vaneless diffusers. A stability analysis—carried out on the rotating and fixed parts of the studied machines—showed that the vaneless diffuser is a limiting component at a low mass flow rate. It was demonstrated that the reorganisation of stall patterns into recirculation in the inducer stabilises the impellers’ flow fields. As the destabilisation of vaneless diffusers has been a recurrent topic in the literature, many models have shown that it is the inlet-flow angle that drives the loss of stability. Models from the literature have estimated critical angle values using the geometry of the diffuser. Thus, for a given stage, expressing the diffuser inlet-flow angle as a function of the mass flow rate allows one to estimate its stability limit. However, this law needs to be calibrated to consider each compressor’s geometrical and aerodynamic specificities. This calibration can be achieved through single-passage steady simulations performed at stable operating points with high mass flow rates. With this methodology, a designer can estimate the stability limit of a centrifugal compressor with a vaneless diffuser from single-passage RANS calculations.

Operating point control method for the Mach-Zehnder modulator in a phase-shift laser range finder

An operating point control method is proposed for the Mach-Zehnder modulator (MZM) based on a dual-cascaded MZM structure. Unlike traditional methods with dither signals, the proposed method is advantageous because the components monitored in the control process are not masked by the spectrum noise floor and the drift direction is clearly determined at the quadrature point, thus imparting greater control stability. Additionally, the proposed control method is suitable for phase-shift laser range finders (PSLRFs). Compared with traditional methods, experimental results reveal that the proposed method increases the operating point stability of MZM from ±0.59° to ±0.36° within 2 h, resulting in better ranging stability than 17 μm in 1 min and 39 μm in 1 h in a PSLRF with a 200 MHz modulation frequency.

On the Origin of “Rotating Instabilities”—Stability and Frequency Studies of Channel Flows

Abstract A group of unsteady flow phenomena in turbomachinery is often referred to as “rotating instabilities.” They occur at flow conditions with very asymmetric velocity profiles, as found downstream of blade rows in axial compressors with large rotor tip clearance in stable operating points close to compressor stall or off-design operating points in steam turbines. In the present work, it is shown that such instabilities do not depend on the blading but also occur in blading-free flow channels. The theoretical proof is carried out with the tools and computational programs of spatial stability theory and Reynolds number dependent jumps in the transverse wavelengths at characteristic perturbation frequencies of the present asymmetric turbulent channel flow are discovered. Experimental investigations in a straight flow channel confirm the calculated frequency field and other characteristics of the perturbations. In agreement to theoretical results, a very asymmetric velocity profile across the channel height was found to trigger disturbances within a limited range of frequencies and not bound to the existence of blading. The notion of rotating instability is misleading in the characterization of this disturbance.

Experiment-based analysis of dynamic characteristic of the ejector for the hydrogen recirculation system of the PEM fuel cell using active periodic pressure excitation

The ejector-driven hydrogen recirculation system plays an important role in enhancing efficiency of the PEM fuel cell. It's necessary to have deep knowledge of dynamic characteristic of the ejector for optimizing system state, but until now related research is not adequate. In this paper, dynamic characteristic of the ejector for the hydrogen recirculation system of the PEM fuel cell is studied using active periodic pressure excitation. Test plant is set up and active periodic pressure excitation with small amplitude is superimposed on steady pressure at the ejector primary flow inlet. Experiment result shows that in frequency domain, amplitude ratio of dynamic pressure at primary flow inlet to the dynamic delta-pressure, equal to pressure at mixing outlet minus that at backflow inlet, is independent of excitation frequency for each steady operating point. In the complex coordinate, vector of dynamic pressure at primary flow inlet is in parallel with that of dynamic delta-pressure, for all frequencies and for all stable operating points. Furthermore, amplitude ratio of dynamic pressure at primary flow inlet to dynamic delta-pressure exhibits linearity with entrainment ratio of the ejector for all stable operating points. Experiment on the 120 kW fuel cell system validates the same dynamic characteristic.

Stabilization of methane–hydrogen flames inside a divergent porous media reactor

The energy transition process triggered by the threat of climate change has created the need for cleaner heat generating systems. Using blends of hydrocarbons with increasing presence of green fuels, such as green hydrogen, has been proposed as an initial step of this process. The present study aims to investigate methane–hydrogen flames stabilized inside a divergent inert porous media burner. Experimentally, four stable operating points were found for the considered burner with a hydrogen presence between 0% and 30% in the fuel mixture at a constant thermal output of 2 kW. Temperatures are presented for each condition, noticing a decreasing trend as hydrogen presence was increased, since the equivalence ratio was gradually reduced to achieve stabilization. CO and NOx emissions were below 15 ppm for all studied cases. A 2-dimensional numerical model incorporating the GRI-Mech 3.0 mechanism was developed and validated against experimental data.The model revealed that the stabilized flame front is observed as a straight line that runs parallel to the radial coordinate. This line exhibits a slight curvature close to the burner wall, which is caused by heat losses and the influence of the divergent geometry. Solid surface temperature was not constant due to the reduced convective heat exchange with flue gases in the periphery of the burner. To reduce this issue a lower expansion angle is proposed as an alternative. In addition, changes in the chemical kinetics due to H2 addition were also evaluated. As results, a general trend towards reaction shifting was found with a 56% of the reactions being strongly promoted by H2 presence, which is associated with an increase in radical concentration in the flame front due to H2 decomposition.

MOSFET-Based RF Switch With Active Biasing

A biasing method for a stacked field-effect transistor (FET)-based radio-frequency (RF) switch is proposed. The advantage of the method over conventional passive resistive biasing is the ability to sustain a desirable operating point under the peak RF excitation conditions achieved by compensating the excessive leakage current of FETs in the stack. Operating point stabilization results in improved RF voltage-handling capabilities of the OFF-state switch. A single-pole double-throw (SPDT) hardware demonstrator implemented in a dedicated 130-nm bulk-CMOS RF switch technology shows an increase in breakdown voltage by 10% for a 35-V voltage-handling class switch device. The improvement is achieved at the expense of increased peak current consumption and no penalty in the RF performance of the switch.

DC operating points of Mott neuristor circuits

In 1960 Hewitt Crane conceptualized neuristors as electronic logic networks that could mimic action potential generation by biological neurons. In 2012 Mott memristors were presented as nano-scale electronic devices for physically constructing neuristor networks. Both the original Mott memristor model and the simplified model presented in 2020 are stiff nonlinear first-order ordinary differential equations (ODEs) that describe the voltage controlled threshold switching and current controlled negative differential resistance, attributed to a Mott insulator-to-metal phase transition. By design, a Mott neuristor contains two identical Mott memristors plus linear resistors and capacitors (no inductors), which enables alternating threshold switching by the memristors to generate periodic (AC) output voltage spikes in response to a DC current or voltage input. This paper presents a steady-state analysis of dynamic neuristor models, including four-, five-, and six-state variables (each of which is a system of first-order ODEs involving the states) based on the original phenomenological model of the Mott memristor. Specifically, it reveals the unique stable operating points that occur for applied currents or voltages below the amounts needed to induce resistive switching. These DC operating points represent the physically meaningful “OFF” states for the circuit when the neuristor does not output voltage spikes. Jacques Hadamard's mathematical criteria for a well-posed physical model (existence, uniqueness, continuity, stability) motivated the search for these DC operating points (OFF states), which are needed for efficiently initializing neuristor models before conducting dynamic neuristor simulations. The key result of our analysis is the neuristor steady-state eq. (29) which is useful for understanding neuristor OFF states as well as the role of negative-differential resistance (NDR) in the operation of the Mott memristor model and neuristor circuits. In addition to the steady-state analysis, three numerical examples of dynamic neuristor circuit operation are also given and MATLAB code for the dynamic four-state model is available for interested readers.

CD and PMD Effect on Cyclostationarity-Based Timing Recovery for Optical Coherent Receivers

Timing recovery is critical for synchronizing the clocks at the transmitting and receiving ends of a digital coherent communication system. The core of timing recovery is to determine reliably the current sampling error of the local digitizer so that the timing circuit may lock to a stable operation point. Conventional timing phase detectors need to adapt to the optical fiber channel so that the common effects of this channel, such as chromatic dispersion (CD) and polarization mode dispersion (PMD), on the timing phase extraction must be understood. Here we exploit the cyclostationarity of the optical signal and derive a model for studying the CD and PMD effect. We prove that the CD-adjusted cyclic correlation matrix contains full information about timing and PMD, and the determinant of the matrix is a timing phase detector immune to both CD and PMD. We also obtain other results such as a completely PMD-independent CD estimator, etc. Our analysis is supported by both simulations and experiments over a field implemented optical cable.

Online estimation of controlled islanding time intervals using dynamic state trajectories through cascading failures from WAMS data

• Use the wide area measurement system to evaluate the system dynamic stability. • A new concept of estimating islanding time. • Proposing an islanding identification time (IIT) index based on the system dynamic behaviors. • Presenting an adaptive concept of IIT scheme with respect to fault severity. • Presenting an online and non-model-based index through real-time evaluations. • Online evaluation of Unstable Equilibrium Point (UEP) to estimate the stability margin of each created island. Islanding strategy is the last controlling action performed through different phases. In this case, fast and secure estimation of the islanding identification time (IIT) are two emergency parameters which play important roles on wide area stability. Due to nonlinear behaviors of the power system generators through severe faults, determining the best islanding scenario remains as an important challenge. By using wide area measuring system (WAMS) technology, an online and adaptive concept of IIT scheme is presented in this paper. To do this, at each time window, considering a set of proper IITs, the best islanding times are estimated. In this case, considering each islanding scenario, based on concept of Unstable Equilibrium Point (UEP) through online evaluations, the synchronism and stability margin of each created island is evaluated. By this way, the corresponding synchronous generators (GSs) are separated though a set of secure islanded subsystems which are operated within different stable operating points. In the case of estimating unstable islanding cases, by rescheduling GSs islanding scenarios through real-time evaluations, the most proper IITs are estimated and performed. Simulation results indicate the effectiveness of provided scheme for online estimation of proper islanding times through different wide area instability scenarios.

TEMPERATURE CONTROL FOR A CONTINUOUSLY STIRRED REACTOR

The objective of this article is to model, by using a system of ordinary differential equations, the behavior of a reaction in a continuously stirred tank, a model that is highly presented in the industry in general and in particular in the pharmaceutical industry. Through the non-linear study of the response, pollutant concentration and temperature inside the reactor, we intend to determine the stable operating points for both the non-linear model and the linear model. The implementation of a proportional integral derivative controller will allow us to make the error signal null in a stable state in a closed loop with the respective gains for the proportional, integral, and derivative actions; said control is necessary and useful to be able to respond effectively and in a short time to the needs of the applications described, otherwise the dynamic system could not be used as a representation of the applied systems since time and control restrictions are strictly necessary. Keywords: Control, Nonlinear Dynamics, Steady State Error, Continuously Stirred Reactor, Controller Robustness DOI： https://doi.org/10.35741/issn.0258-2724.58.1.59

Research on Robust Model Predictive Control Strategy of Wind Turbines to Reduce Wind Power Fluctuation

• Establish a robust model predictive control (RMPC) strategy for wind turbines based on wind speed uncertainty. • The error model of the nominal system and actual system is constructed and Lyapunov stability is used to prove that the error system tends to be stable. • Simulation analysis of the influence of RMPC strategy on wind turbine operation at different stable operating points. In the process of wind power generation, the random fluctuation of wind speed affects the smooth operation of the wind turbine and the stability of the output power of the wind turbine. Aiming at the influence of wind speed random fluctuation on the stable operation of wind turbines, this paper regards wind speed random fluctuation as bounded disturbance and adopts Robust Model Predictive Control (RMPC) strategy to divide the actual wind power system with wind speed disturbance into two parts: undisturbed nominal system and perturbed parts. As for the mismatch between the actual wind power system and the nominal system, the state of the actual wind power system is limited to a constant set by a certain feedback control law. The feedback control law and robust invariant set are then solved off-line via linear matrix inequalities (LMI). The 5MW wind turbine model developed by Nrel is used to simulate the feasibility of the algorithm on the MATLAB platform. RMPC control strategy can achieve the control goals of maximum wind energy capture at low wind speed and constant power operation at high wind speed. RMPC can effectively reduce the influence of wind speed uncertainty on stable operation of wind turbines, reduce output power fluctuation and improve power generation quality.

Prosumer-Centric Self-Sustained Smart Grid Systems

Modern smart grid systems exploit a two-way interaction paradigm between the utility and the electricity user and promote the role of prosumer, as a new user type, able to generate and sell energy, or consume energy. Within such a setting, the prosumers and their interactions with the microgrid system become of high significance for its efficient operation. In this article, to model the corresponding interactions, we introduce a labor economics-based framework by exploiting the principles of contract theory, that jointly achieves the satisfaction of the various interacting system entities, i.e., the microgrid operator (MGO) and the prosumers. The MGO offers personalized rewards to the sellers and buyers, to incentivize them to sell and purchase energy, respectively. To provide a stable and efficient operation point, while aiming at jointly satisfying the profit and requirements of the involved competing parties, optimal personalized contracts, i.e., rewards and amount of sold/purchased energy, are determined, by formulating and solving contract-theoretic optimization problems between the MGO and the sellers or buyers. The analysis is provided for both cases of complete and incomplete information availability regarding the prosumers’ types. Detailed numerical results are presented to demonstrate the operation characteristics of the proposed framework under diverse scenarios.

Optical Fiber Sensor with Stable Operating Point for AC Magnetic Field Measurement

A novel alternating current (AC) magnetic field sensor that has a stable operating point and is insensitive to ambient temperature fluctuations is presented. The sensor is based on a high attenuation fiber Bragg grating (HAFBG) attached to a magnetostrictive rod. A stable operating point is achieved by regulating a heating laser based on a feedback algorithm that compensates the temperature fluctuations of the surrounding environment. Experimental results show that the sensor responds well to dynamic magnetic fields and is able to ensure a stable operating point in the range of at least 15 °C in an ambient temperature disturbance test. The ease of fabrication and excellent performance suggest that the proposed fiber sensor is suitable for practical AC magnetic field sensing applications, such as health monitoring of transformers and fault diagnosis of induction motors.

Research on attitude control strategy of unmanned helicopter based on hybrid particle swarm optimization algorithm

For the unmanned helicopter attitude control problem, an optimal control strategy based on hybrid particle swarm optimization (PSO) algorithm has been proposed. Firstly, a coupled dynamics model of the system has been established based on the structural characteristics of the unmanned helicopter system; secondly, a gain scheduling control method has been adopted to select multiple system stable operating points with real-time error as the scheduling variable, and a gain scheduling attitude controller has been designed; further, the inertia weights and learning factors are dynamically adjusted on the basis of the traditional PSO algorithm, and a hybrid PSO algorithm has been proposed for unmanned helicopter attitude control; finally, the improved controller has been compared and verified by the semi-physical. The experimental results show that the improved algorithm improves the attitude control effect and anti-interference capability of the unmanned helicopter, resulting in a reduction of the adjustment time by about 3.8s and the maximum steady-state amplitude by about 0.154°.

A highly energy-efficient milling of Inconel 718 via modulated short electric arc machining

An excellent and advanced manufacturing method named modulated short electric arc machining (M-SEAM) was proposed in this study to solve the problems of low machining efficiency and high specific energy consumption (SEC) for difficult-to-machine materials in the traditional electric discharge machining (EDM) and electric arc machining (EAM) process.The discharge channel is established by the collision between the electrode and the workpiece. The arc spreads and moves as the electrode rotates. Moreover, the energy balance equation of the modulated arc was established, which revealed that the volt-ampere characteristic is resistive when the frequency of pulse voltage tends to infinity in the steady state, the arc had a large relative thermal inertia, and two stable operating points were analyzed. M-SEAM processing was performed using graphite and Inconel 718 as electrode and workpiece materials, respectively. The results showed a maximum MRR of 49,020 mm3/min, and the relative electrode wear rate (REWR) and SEC were limited to 0.92% and 50.21 kJ/cm3, respectively. The peak current was 1940 A, and the maximum discharge time for a single arc was 328.56 ms.

Games in Normal and Satisfaction Form for Efficient Transmission Power Allocation Under Dual 5G Wireless Multiple Access Paradigm

In this paper, to exploit the challenges and potential offered by the simultaneous use of non-orthogonal multiple access (NOMA) and orthogonal frequency division multiple access (OFDMA) transmission options in future 5G wireless systems, we aim at the proper modeling and transformation of the uplink power allocation problem. In particular, in this setting, each user has two degrees of freedom in the decision making process, namely its overall transmission power level, and the corresponding power investment to the OFDMA and/or NOMA based transmissions. The resulting multi-variable power allocation problem is treated and solved under three different perspectives, namely: 1) Games in Normal Form and Nash Equilibrium (NE); 2) Optimization techniques targeting system social welfare through a centralized optimal solution; and 3) Games in Satisfaction Form and Efficient Satisfaction Equilibrium (ESE). Based on these approaches, different solutions and stable operation points are identified and their properties are analyzed. An in depth evaluation and comparison of the various obtained outcomes is achieved, via modeling and simulations. The focus is placed on the impact and the interplay of the NOMA specific features, including the potential over-exploitation of the available bandwidth, the fairness in accessing it, and the interference treatment. It is also shown that, using the satisfaction form games for the users to converge to the ESE, provides an efficient and promising user-centric modeling approach to the power allocation problem, as the system adapts to the users’ application needs, while at the same time eliminates a significant amount of interference.

Thermodynamic modelling and real-time control strategies of solar micro gas turbine system with thermochemical energy storage

Distributed solar gas turbine systems with thermal energy storage are expected to overcome the intermittence and instability of solar irradiance and produce reliable and flexible electricity for remote districts and islands. Here, a mathematical model is developed for a 10 kWe solar micro gas turbine (MGT) system with thermochemical energy storage (TCES) to study the system thermodynamic characteristics at real-world direct normal irradiation (DNI) variations. Real-time control strategies aiming for stable operation and set point tracing are proposed and implemented in transient simulations to analyze the control effect against both short- and long-term DNI disturbances based on system dynamics. Results show that, by regulating the output power, rotational speed (N) is kept constant, and system responses are smoothened (e.g., less than 5.8% fluctuation of the mass flow rate). Power regulation also enables a constant turbine outlet temperature (TOT) and the optimal overall performance (e.g., output power and total efficiency exceeding 14 kWe and 14%, respectively). By combining power and bypass regulations, N and TOT can simultaneously remain constant while outputting a stable power of 12.6 kWe ±5% under 750–820 W/m2, with a sharp drop to 500 W/m2. For favorable weather, N-TOT simultaneous control can guarantee the high and stable system performance. If massive clouds appear, constant TOT operation is more advantageous during peak load demand for larger electricity generation, while constant N operation is preferable during low power demand for smoother turbine operation.Furthermore, the addition of TCES smoothens the performance variation and prolongs the generation duration. TCES also allows constant TOT operation to store up to 32% more energy than constant N and output 18–28 kWh more energy during daytime operation, thanks to the higher operating temperature. Overall, the proposed real-time control methods reduce the dependency on fossil fuel combustion and contribute to the stable, safe, and efficient operation of a distributed high-percentage-solar-share MGT system.

Multidisciplinary Design Optimization for Performance Improvement of an Axial Flow Fan Using Free-Form Deformation

Abstract This paper describes a multidisciplinary design optimization for performance improvement of an electric-ducted fan rotor using free-form deformation (FFD) and data mining techniques. A practical partitioning approach for FFD parameterization was applied in combination with engineering design parameters to optimize the fan rotor. Regression analysis was used to initially determine an approximation function for the blade static stress and subsequently integrated into a fully coupled iterative loop to optimize the blade considering two operating points. Two optimization solutions for 10 and 12 blades were performed. Percentage improvements in the efficiency of 1.05% and 1.32% were realized for 10 and 12 blades, respectively, at near peak efficiency flowrate. Also, blade static stress was reduced by percentages of 5.49% and 12.37% for 10 and 12 blades compared with the baseline. Data mining results revealed key design variable sensitivities where blade twist, sweep, chord, and hub thickness distribution were found to be the most influential for 12 blades while for 10 blades, blade lean, sweep and chord at the midspan and tip. The optimized blades were found to have a significant increase in chord from midspan to tip mimicking a wide chord fan blade particularly for 10 blades. Analysis of the flow field revealed that the axial velocity from 0.4 to 0.8 spanwise length increased significantly for the optimum blades due to the increase in blade twist and chord length at all stable operating points. However, the leakage trajectory relative to the blade chord was observed to be larger and interacted with the trailing edge wake flow downstream for the optimum blades at near-stall conditions. Furthermore, the increase in chord length and the thinning of the blade close to the trailing edge from 0.4 to 0.8 span reduced the suction-side blade loading and static stress.

Stability Regions of Vehicle Lateral Dynamics: Estimation and Analysis

Abstract A new method is proposed to estimate and analyze the vehicle lateral stability region, which provides a direct and intuitive demonstration for the safety and stability control of ground vehicles. Based on a four-wheel vehicle model and a nonlinear two-dimensional (2D) analytical LuGre tire model, a local linearization method is applied to estimate the vehicle lateral stability regions by analyzing the vehicle stability at each operation point on a phase plane, which includes but not limited to the equilibrium points. As the collections of all the locally stable operation points, the estimated stability regions are conservative because both vehicle and tire stability are simultaneously considered, which are especially important for characterizing the stability features of highly/fully automated ground vehicles (AGV). The obtained lateral stability regions can be well explained by the vehicle characteristics of oversteering and understeering in the context of vehicle handling stability. The impacts of vehicle lateral load transfer, longitudinal velocity, tire-road friction coefficient, and steering angle on the estimated stability regions are presented and discussed. To validate the correctness of the estimated stability regions, a case study by matlab/simulink and CarSim® co-simulation is presented and discussed.