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In this paper, a novel repetitive control scheme is presented and discussed, based on the so-called B-spline filters. These dynamic filters are able to generate a B-spline trajectory if they are fed with the sequence of control points defining the curve. Therefore, they are ideal tools for generating online reference signals with the prescribed level of smoothness for driving dynamic systems, possibly together with a feedforward compensator. In particular, a continuous zero phase error tracking controller (ZPETC) can be used for tracking control of nonminimum phase systems but because of its open-loop nature it cannot guarantee the robustness with respect to modeling errors and exogenous disturbances. For this reason, ZPETC and trajectory generator have been embedded in a repetitive control scheme that allows to nullify interpolation errors even in nonideal conditions, provided that the desired reference trajectory and the disturbances are periodic. This paper is based on the results presented in the conference paper [L. Biagiotti, F. Califano, and C. Melchiorri, “Repetitive control of non-minimum phase systems along b-spline trajectories,” in Proc. IEEE 55th Conf. Decis. Control, 2016, pp. 5496–5501.], where asymptotic stability of the overall control scheme has been proved mathematically, but extends such results with an experimental validation based on a nonminimum phase system. Different models of the same physical system have been identified and used in the implementation of this model-based control scheme, allowing a real evaluation of the relationship between control system performance and model accuracy. [ABSTRACT FROM AUTHOR]

Energy management strategy (EMS) is the key to the performance of fuel cell / battery hybrid system. At present, reinforcement learning (RL) has been introduced into this field and has gradually become the focus of research. However, traditional EMSs only take the energy consumption into consideration when optimizing the operation economy, and ignore the cost caused by power source degradations. It would cause the problem of poor operation economy regarding Total Cost of Ownership (TCO). On the other hand, most studied RL algorithms have the disadvantages of overestimation and improper way of restricting battery SOC, which would lead to relatively poor control performance as well. To solve these problems, this paper establishes a TCO model including energy consumption, equivalent energy consumption and degradation of power sources at first, then adopt the Double Q-learning RL algorithm with state constraint and variable action space to determine the optimal EMS. Finally, using hardware-in-the-loop platform, the feasibility, superiority and generalization of proposed EMS is proved by comparing with the optimal dynamic programming and traditional RL EMS and equivalent consumption minimum strategy (ECMS) under both training and unknown operating conditions. Results prove that the proposed strategy has high global optimality and excellent SOC control ability regardless of training or unknown conditions. [ABSTRACT FROM AUTHOR]

The evaluation of the state of transformer oil-immersed insulation based on the traditional methods becomes unreliable due to the nonuniform aging effect. To address this issue, a novel model for accessing the aging information of transformer oil-immersed insulation at the hotspot is proposed. In this article, frequency-domain spectroscopy (FDS) is selected as the carrier for characterizing the aging states of oil-immersed insulation. The multiobjective function for reversing the FDS of the hotspot is constructed based on the dielectric response equivalent circuit. Then, the nondominated sorting genetic algorithm with the multiconstraint scheme is proposed to solve the multiobjective function, by which the FDS data of the transformer hotspot region are acquired. The verification results indicate that the average standard deviation between the computed FDS of the hotspot region and the measured data is less than 0.26. The contribution of this article is in the exploration of the proposed model as a potential tool to extract the FDS data of the hotspot region. This will promote a more reliable aging evaluation of the transformer oil-immersed paper insulation at the hotspot. [ABSTRACT FROM AUTHOR]

In photovoltaic systems, common-mode voltage (CMV) generates leakage current, which shortens the insulation lifespan and causes safety problems. As for neutral-point-clamped (NPC) inverters, zero CMV PWM (ZCMV PWM) can be implemented to eliminate leakage current, but unable to balance neutral-point (NP) voltage in dc side. This article presents a novel modulation technique for NPC PV inverter. The strategy contains ZCMV PWM and another two modulation modes which keeps CMV constant in one switching period, so as to eliminate leakage current. In order to balance NP voltage, NP current is adjusted by selection of optimal modulation mode and the leakage current is still well eliminated during the process of balancing NP voltage. Compared with conventional ZCMV PWM, the proposed scheme can remove both leakage current and NP voltage deviation. The output performance and limitations of the proposed method are also introduced in the paper. Experiments are provided to verify the validity of the proposed method. [ABSTRACT FROM AUTHOR]

A novel analysis for a new type of variable reluctance resolvers (VR-Resolvers) with toroidal windings based on the magnetic equivalent circuit (MEC) method is presented in this work. Different cases including various windings configurations as well as different rotor structures are considered in order to investigate the performance of the resolver precisely. The position error of both healthy and eccentric resolvers are studied by a flexible MEC model. The effect of the eccentricity fault on the resolvers with different specifications is also evaluated to analyze the manufacturing tolerance due to the eccentric rotor for several cases. It is notable that the presented MEC provides the opportunity to adjust accuracy and model several structures in both healthy and faulty conditions by just a single model. Finally, the MEC results are confirmed by finite element method and experimental results to show the effectiveness of the proposed model. In general, development of a new VR-Resolver and analyzing its performance under different windings configurations and rotor structures by proposing a modified MEC approach are the paper novelties. [ABSTRACT FROM AUTHOR]

A phase-locked loop (PLL) is commonly used in grid-connected power converter for synchronization. A single input single output (SISO) linear model of PLL with the phase angle of the point of common coupling (PCC) voltage as input and the estimated phase angle as the output is generally used in the PLL analysis and design. However, an undesirable coupling between the magnitude and phase of the input voltage is present when a filtering stage is incorporated before the control loop, which a SISO model cannot capture, and could result in a significant disturbance in the PLL estimated phase during grid faults. This paper proposes a generalized multi-input multi-output (MIMO) linear model that captures the complete PLL dynamics during symmetrical faults for a PLL equipped with any prefilter. Furthermore, a compensation method that decouples the magnitude dynamics of the input voltage from the phase dynamics is proposed in this paper. The proposed compensation improves the PLL's phase tracking performance by ensuring that the prefiltered PLL acts only on the PCC voltage phase changes. A vital application of the proposed compensation method for PLL is during a grid fault case, wherein the converters are expected to contribute to the fault current, which requires an accurate measurement of the PCC voltage phase. The compensation method's effectiveness is demonstrated using power hardware in the loop simulation of a hardware voltage source converter interfaced to a distribution system simulated in real-time. [ABSTRACT FROM AUTHOR]

This paper proposes an intelligent modeling and optimization method to set up the smart energy hub model for the multiple energy system and optimize the operation of its associated energy hub model automatically. The core idea of the proposed method is to divide the complex energy hub model into several simple energy hub models. In this paper, the proposed computerized algorithm, which is applied to the smart energy hub model division, includes an energy loop intelligent searching method, a real nodes arrangement method, and a virtual nodes insertion method. One case study for the multiple energy system of a residential district in Guangzhou city is performed to validate the effectiveness of the proposed method. Compared with the traditional calculation method, the proposed method guarantees global optimal operation decision for the whole multiple energy system and the computational burden is significantly reduced. [ABSTRACT FROM AUTHOR]

The remaining useful life (RUL) of transformer insulation paper is largely determined by the winding hot-spot temperature (HST). Frequently the HST is not directly monitored and it is inferred from other measurements. However, measurement errors affect prediction models and if uncertain variables are not taken into account this can lead to incorrect maintenance decisions. Additionally, existing analytic models for HST calculation are not always accurate because they cannot generalize the properties of transformers operating in different contexts. In this context, this paper presents a novel transformer condition assessment approach integrating uncertainty modeling, data-driven forecasting models, and model-based experimental models to increase the prediction accuracy and handle uncertainty. The proposed approach quantifies the effect of measurement errors on transformer RUL predictions and confirms that temperature and load measurement errors affect the RUL estimation. Forecasting results show that the extreme gradient boosting (XGB) algorithm best captures the nonlinearities of the thermal model and improves the prediction accuracy among a number of forecasting approaches. Accordingly, the XGB model is integrated with experimental models in a particle filtering framework to improve thermal modeling and RUL prediction tasks. Models are tested and validated using a real dataset from a power transformer operating in a nuclear power plant. [ABSTRACT FROM AUTHOR]

The rising cost of production testing for a system-on-a-chip (SoC) is one of the crucial matters to chip makers, due to long test time and costly automated-test-equipment. This paper proposes a spectral leakage-driven built-in self-test (BIST) scheme to precisely predict the nonlinearity of mixed-signal circuits in the loopback mode, thereby accomplishing cost-effectiveness (compared to previous BIST-based works). A digitally synthesized single-tone sinusoidal stimulus used for conventional harmonic testing is incoherently sampled by a device under test (DUT). The DUT output signal exhibits the correlation between the DUT harmonics and the spectral leakage introduced by the incoherent sampling. The DUT output signal is then fed to another DUT through a loopback path, so that the harmonics of a pair of DUTs are correlated with the spectral leakage on the loopback response; the magnitude of the spectral leakage is considered as a weighting factor on the harmonic magnitude of those DUTs. The correlation is quantitatively modeled as characteristic equations in , and postprocessing predicts the harmonics of the two individual DUTs, by simultaneously solving the characteristic equations using on-chip DSP core available in an SoC. Simulation and hardware measurements validated that this paper can be practically used for production testing by showing less than 0.3 and 0.6 dB of the prediction errors, respectively. [ABSTRACT FROM AUTHOR]

In this letter (Zhu et al. 2011), an adaptive sliding mode controller is proposed for attitude stabilization of spacecraft under inertia uncertainty, external disturbances, and actuator constraints. Some comments on this issue are made here to point out a serious mistake and the untenable main result in the paper. A correction is proposed. [ABSTRACT FROM AUTHOR]

Presents a state variable model for the drying section of a paper-making machine. Linearization and design of the model; What the solution for the model yielded; Specification of boundary conditions; Comparison of the obtained results with dynamic model results; What the study concluded.

Short-term household electricity load forecasting is important for utility companies to ensure reliable power supplies. Traditional methods for load forecasting relied on historical records from one single data source and have limitations with insufficient or missing data. Recently, an emerging family of machine learning algorithms, multitask learning (MTL), has been developed and has the potential for load forecasting. By MTL, the electricity consumption data from multiple communities can be fused to improve forecasting accuracy. However, appropriate modeling of the relatedness to enable the between-community knowledge transfer remains a challenge. This paper proposes an improved MTL algorithm for a Bayesian spatiotemporal Gaussian process model (BSGP) to characterize the relatedness among the different residential communities. It hypothesizes on the similar impacts of environmental and traffic conditions on electricity consumption in improving short-term load forecasting. Furthermore, this paper proposes a low-ranked dirty model along with an iterative algorithm to improve the learning of model parameters under an MTL framework. This paper uses a real-world case study from two residential communities in Tallahassee, Fl, USA, to demonstrate the method effectiveness. The proposed method significantly outperforms state-of-the-art forecasting methods and effectively captures the relatedness to provide between-community knowledge transfer compared with other MTL methods. [ABSTRACT FROM AUTHOR]

This paper proposes an analytical model for the prediction of air gap magnetic field distribution for axial flux permanent magnet (AFPM) machine with various types of misalignments. The AFPM machine geometry is first transformed to a polar representation. Consequently, the subdomain model based on current sheet technique is developed. Then the stator coordinate system is chosen as reference coordinate to consider both static/dynamic angular and axis misalignments. The back electromagnetic forces and cogging torque are obtained accordingly based on Maxwell's equations. The results show that the proposed approach agrees with the finite-element method. The model is further validated by experiments under healthy, dynamic angular and axis misalignment conditions, which can validate the proposed approach. It turns out that the proposed approach can predict the performance of AFPM machines with types of misalignment quickly and effectively, which is greatly significant for further fault detection. [ABSTRACT FROM AUTHOR]

DC shipboard power systems have been considered as a promising solution for stricter environmental regulations on ships due to their main benefits in fuel savings with variable speed engines and easy integration of energy storage systems. In order to employ the dc solution in the shipboard power systems, the dc power systems have to be protected from a system fault with protection selectivity to minimize impacts of the fault or to avoid other undesirable situations in the system. For low-voltage dc shipboard power systems, a three-level protection has been proposed: 1) fast action (first)—bus separation by solid-state dc bus-tie switch; 2) medium action (second)—feeder protection by high-speed fuse; and 3) slow action (third)—generator–rectifier fault controls. This paper proposes a new method by means of additional bus capacitance added in main dc buses to help reliable operation of the three-level protection. The principle of the proposed method is introduced and the sizing of the additional bus capacitance is addressed in this paper. With the modeling of the dc shipboard power systems, the analyses of voltage drops for the bus separation failure and fault clearing time for the feeder protection are carried out to verify the proposed method. The results show that the proposed method not only mitigates the voltage drop for the bus separation failure, but also achieves the selectivity and the sensitivity for the feeder protection. [ABSTRACT FROM AUTHOR]

Modularization design has been widely used to reduce the detent force of permanent magnet linear synchronous motor (PMLSM). For modular PMLSM, ideally, unit motors are independent of each other and the detent force of the whole motor is the sum of that for unit motors; thus, the whole motor's detent force can be suppressed by adjusting the phase difference among the unit motors’ detent forces. But actually, there is coupling effect between adjacent unit motors, which has adverse effect on the detent force suppression. The coupling effect changes the magnetic field distribution, which is often neglected in current research. Hence, this paper carries out the research on magnetic field analysis and flux barrier design for modular PMLSM considering the coupling effect: the influence of the coupling effect on the air gap magnetic field is clarified through magnetic field analysis; the coupling force is isolated by finite element analysis, and then the effects of key parameters are discussed; the whole motor's detent force model considering the coupling effect is established, and an optimal design method of adjusting the flux barrier length is presented to suppress the detent force. Finally, a prototype is made to test the detent force characteristics with different flux barrier lengths, which verifies the research theory in this paper. The research results in this paper can provide guidance and reference for the design of modular PMLSMs. [ABSTRACT FROM AUTHOR]

In multiphase ac power systems, e.g., aircraft electric power systems (EPS), the proximity effect between the feeder cables can be severe and complex due to the tightly wired cable bundles. Simulation software is widely used to analyze such effects in order to guarantee proper system operation, but it is highly time consuming and requires extensive computational resources. Accordingly, this paper proposes an analytical calculation method for estimating the ac resistance of closely bundled power cables, namely multiconductor cables. Simulation and experimental tests are performed to validate the effectiveness and accuracy of the method, showing that the algorithm developed in this paper is easy to implement with a minimum accuracy of 92% in all the tests. It allows online estimation of cable resistances, which can be beneficial for advanced system monitoring and management to enhance safety and reduce losses. Aircraft EPS and cables are used as the example in this paper, while the proposed method is also applicable for other applications, such as shipboard EPS, renewable energy parks, or microgrids where multiconductor cables are used. [ABSTRACT FROM AUTHOR]

Finite set model predictive torque control (FCSMPTC) of induction machines has received widespread attention in recent years due to its fast dynamic response, intuitive concept, and ability to handle nonlinear constraints. However, FCSMPTC essentially belongs to the open-loop control paradigm, and unmatched parameters inevitably cause electromagnetic torque tracking error. In addition, the outer loop (i.e., the speed loop) based on a proportional-integral (PI) regulator cannot achieve optimal control between speed dynamic response and torque tracking error compensation. The traditional control paradigm is abbreviated as PI-MPTC. In order to solve the aforementioned problem, this paper proposes active disturbance-rejection-based model predictive torque control (ADR-MPTC). First, the influence mechanism of mismatched parameters on torque prediction error in PI-MPTC is studied, and then the performance of a traditional PI regulator used to compensate for torque prediction error is analyzed. Second, this paper introduces several parts of the proposed ADR-MPTC, including the design of the torque prediction error observer, nonlinear prediction error compensation strategies, an enhanced predictive torque control, and a simplified full-order flux observer. Finally, PI-MPTC and ADR-MPTC are studied experimentally. The experimental results show that compared with PI-MPTC, ADR-MPTC performs better in dynamic and steady states, and has stronger robustness. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of how to estimate the remaining useful life (RUL) for partially observed linear stochastic degrading systems with survival measurements. The motivation of this paper arises from two engineering facts—the measured degradation signals are taken from a survival degradation path and the degradation progression of the system is inevitably affected by multisource variability. To do so, we first revisit the linear degradation modeling framework driven by the Wiener process to account for the above two facts, and a new state-space model with non-Gaussian state transitions is constructed based on the constraint of survival measurements. Then, the particle filtering algorithm is applied to real-time estimate the non-Gaussian degradation state and random-effect parameter from measurements. Furthermore, we derive the probabilistic distribution of the RUL which can be real-time updated based on the available measurements. To apply the presented method, a two-stage estimation procedure based on particle expectation maximization algorithm is presented to determine and update the model parameters. The novelty of the presented method is to exclude the probability of failure before the current monitoring time and account for both impacts of the multisource variability and surviving degradation path on the RUL estimation. Finally, we demonstrate the proposed approach by a case study on gyros in the inertial platform. [ABSTRACT FROM AUTHOR]

A converter monitoring unit (CMU) that monitors the power modules of the converter in a multimegawatt test wind turbine is presented in this paper. A method of calculating the virtual temperature ($T_{v}$) of the power semiconductors is laid out. Contrary to previous work, the method enables $T_{v}$ characterization of the semiconductors by means of sampled data during normal operation of the converter, without the need for special calibration routines. The dynamic operation of the wind turbine and the large amount of data sampled in the CMU enables a statistical approach to generate reference data for $T_{v}$ calculations. The method was tested on machine side converter diodes of the test turbine, based on samples of collector-emitter voltage ($vce_{\text{on}}$) and current ($i_{c}$). Other temperature sensitive electrical parameters may also be used as input to the method. The CMU has been operating for more than a year in the test turbine, showing consistent data throughout the whole period. While the monitoring method and results are based on measurements on a single test turbine, the paper also link these to converter failure data from a large fleet of operating turbines. [ABSTRACT FROM AUTHOR]

Battery safety is one of the most crucial issues in the utilization of lithium-ion batteries (LiBs) for all-climate electric vehicles. Short circuit, overcharge, and overheat are three common field failures of LiBs. In this paper, online fault diagnosis for external short circuit (ESC) of LiB packs is investigated. The experiments are carried out to obtain and compare ESC characteristics of 18650-type NMC battery pack and single cell. Based on the analysis of experimental results, a two-step equivalent circuit model is established to describe the ESC process and an online model-based scheme is proposed to diagnose ESC faults of battery packs. The proposed scheme is evaluated by experimental data. The results show that it can effectively diagnose ESC faults in 3.5 s after their occurrences with the terminal voltage error less than 25 mV. The proposed scheme has shown great generalization ability. ESC faults of battery packs under different number of cells connected in series and unavailable current information can also be diagnosed at the terminal voltage error less than 48 and 60 mV, respectively. [ABSTRACT FROM AUTHOR]

In this paper, automated omnidirectional touch probe (ODTP) including adaptive tuning of the complex contour curve with optimal interpolation and motion planning based on a hybrid multiaxis robot (HMAR) with dual drive gantry-type machine (DDGM) are presented. It is called an “omnidirectional” because the 6-degrees of freedom ODTP in tool center point mode can always maintain normal direction towards the object contour curve. The new optimal solutions of the interpolation and motion planning are provided to tackle the small segments issues for a complex curvature object. We present an algorithm to maintain maximum acceleration, so that it generates smooth and efficient three-dimensional reverse object in a higher order complex contour trajectory composed of piecewise small segments. As a result, the constant moving speed is very important to certain applications, such as gluing, welding, and laser cutting, to preserve quality processing. The utilization of object symmetry, extension, and synthesis properties to simplify the process of performing reverse engineering is described. These methods reduce the time required for the touch probe to detect the points. The experimental implementation to demonstrate the success of this paper with video clip are presented. [ABSTRACT FROM AUTHOR]

In recent years, there has been an increasing interest in hand movements in various application fields. However, the human hand is too dexterous and only has limited space. Developing a proper method to monitor and capture hand motion is meaningful. Conventionally, an optical measurement method is widely used to capture hand gestures. Nevertheless, this method is costly and has the problem of line-of-sight shielding. In this paper, a sensor fusion algorithm is proposed to calculate a more accurate result by calculating acceleration, magnetic field strength, and angular speed from the inertial measurement unit (IMU). The core concept of this algorithm is based on the idea of feedback control. To validate the performance, the active rotary platform is set up to compare the measured results to the references directly. Most of the error results are less than 3°, and the standard deviations are less than 1°. The measurement results ensure the feasibility of the inertial measurement method with the sensor fusion algorithm proposed in this paper. [ABSTRACT FROM AUTHOR]

Active flow control by means of plasma actuators has potential advantages over conventional strategies, e.g., mechanical or hydraulic components may be replaced by lightweight, compact, fast response plasma actuators. In this paper, several designs of dielectric barrier discharge (DBD) plasma actuators are presented for aerospace applications and the focus is on the associated feedback control implementation. The interdisciplinary nature of aerodynamic feedback control with plasma, however, makes direct experimental demonstrating an outstanding challenge. Here, we propose a realistic experimental control implementation afforded by commercial off-the-shelf electric products and the major achievement is the detailed instruction (in both electricity and aerodynamics) and the successful demonstration of the closed-loop design in controlling the dominant modes from a cylinder flow setup. The essence of our approach is to drive DBD plasma actuations by a downstream sensor and excite aerodynamic velocity perturbations, which are further amplified on the shear flow from the cylinder, leading to airflow structures, such as vortex roll-up and randomization, which are measured by the downstream sensor to complete the whole loop. We benchmark our control approach by comparing to the predicted dominant frequencies of the controlled flow system, which can be achieved by the Barkhausen stability criterion after establishing the corresponding transfer function of the whole flow control system. Overall, this paper shall assist a host of new applications in aerospace applications in the near future. [ABSTRACT FROM AUTHOR]

This paper proposes a new force estimation approach based on the dither periodic component elimination (DPCE) Kalman filter and the disturbance observer (DOB) for realization of a fine sensorless force control system under the existence of static friction. A dither signal is inserted to the desired reference signal to eliminate the effect of static friction of a ball-screw system. The DOB estimates the periodical torque caused by dither signal. The DPCE Kalman filter uses the periodical torque for the estimation of the high-order torque responses to achieve the torque estimation with the elimination of periodic component. The problem of noise in the force sensation and the effect of static friction are reduced effectively by using the DPCE Kalman filter. Therefore, the bandwidth of the force sensing is increased and the wide band DOB is achieved. As a result, this paper has accomplished the fine sensorless force control realization. The force control experiments of a ball-screw system are carried out to verify the validity and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper proposes and experimentally evaluates a method, which is able to measure the refrigeration capacity of compressors in extremely short times. Traditionally, the measurement of this parameter is done using specialized and expensive test rigs and can take up to 4.5 h for the measurement of a single compressor. To overcome this long measurement time, it is proposed to use a simpler measuring system, in which, instead of measuring the refrigeration capacity directly, the rate of pressure rise imposed by the compressor to a cylinder with fixed volume is measured. This paper shows that both variables have a high correlation factor when the test and compressor conditions are taken into account. As the correlation among the variables is nonlinear, it is not possible to use simple mathematical correlation functions, so neural networks are used for that purpose. By using the proposed method, the refrigeration capacity of a compressor can be determined in less than 7 s, which is approximately 0.05% of the time required by traditional methods. To guarantee the metrological reliability of the results presented by the proposed neural model, this paper proposes a novel approach based on the Monte Carlo and the bootstrap methods. [ABSTRACT FROM AUTHOR]

In this paper, a three-dimensional (3-D) motion tracking method is proposed for binocular microscopic vision system to precisely record the motion trajectories of millimeter size objects in the Cartesian space. Primarily two fundamental problems are solved. The first problem arises from the limited depth of field (DOF) of microscope. Considering the motion of the objects, the existing autofocusing methods requiring sequential images either in focus or defocus are not workable. Therefore, a one-shot prior autofocusing approach is desired, which needs to take the motion tendency of objects into account. Besides, the autofocusing process always lags behind the motion of objects, and there inevitably will be prediction deviation on the motion tendency of objects. This leads to the second problem to estimate the 3-D motion states from defocused images. In this paper, we first explain the defocusing process from the perspective of S-Transform, based on which the Bayesian inference inspired method to estimate the depth from defocus from one single image is derived thereafter. Afterwards, a motion states, including both the position and velocity, estimation approach is developed within the Kalman filter framework. The above two aspects mutually supply the necessary information for each other to be functional to accurately realize the DOF tracking and motion tracking of moving objects. Experiments were well-designed to validate the effectiveness of the proposed method, and experiments result showed a tracking precision of 3 μm was achieved. [ABSTRACT FROM AUTHOR]

By combining radio-frequency identification (RFID) and paper-microfluidics technologies, a low-cost first-of-its-kind platform for comprehensive liquid sensing, i.e., the “smart test strip,” is presented, which enables portable wireless real-time liquid sensing with handhold devices (e.g., cell phones), and integration of various multifunctional electrical and chemical sensors, for numerous Lab-on-Chip applications, including manufacturing control, environmental monitoring, and point-of-care medical diagnostics. The fabrication of RFID tags and two types of microfluidics are accomplished by a single inkjet-printing process in a cost-effective environmental-friendly additive manufacturing approach, which makes possible the production of disposable, lightweight, and flexible sensing platforms. Taking advantage of the proposed smart test strips platforms, we demonstrate two proof-of-concept high-performance electrical sensors based on interdigitated electrode topologies: a resistivity-based sensor with a 1782 $\Omega$/( $\Omega$*m) sensitivity; nevertheless, the proposed permittivity-based sensor with a 15%/$\epsilon _r$ sensitivity, but the proposed integrated wireless platform, can facilitate the integration of even more chemical and electrical sensors. In addition, two on-strip antenna prototypes have been designed, optimized, and tested to work at 2.4 GHz and 13.56 MHz, respectively. Furthermore, the wireless interrogation of a complete proof-of-concept smart test strip is presented, which shows an excellent sensing resolution of 1.33 $\Omega$ over the range of 0–1371 $\Omega$. [ABSTRACT FROM PUBLISHER]

DC microgrid has attracted more and more attention due to its unique characteristics, but the development of a dc microgrid is also facing some challenges, such as interruption and isolation of short-circuit fault currents. Therefore, the dc circuit breaker plays an important role in ensuring the normal work of a dc microgrid. In this paper, a novel bidirectional dc solid-state circuit breaker is proposed to realize the bidirectional flow of energy, which ensures the higher operating efficiency of the dc microgrid. Compared with other solid-state circuit breakers, the proposed novel topology has simpler structure, common ground, and fewer components. First, this paper makes a detailed analysis of the different working stages of the circuit when the fault occurs in combination with simulation results of the circuit topology. Then, the standard of selecting the components through the calculation and analysis of the circuit is given in this paper. Finally, the performance of the novel bidirectional solid-state circuit breaker is verified by experiments. [ABSTRACT FROM AUTHOR]

The development of the dc microgrid system on-board has promoted the development of the dc circuit breaker, but short circuit fault may cause serious damage to the system. Many problems exist in the traditional dc circuit breaker such as long periods of fault interruption, complex circuit structure, existing arc, low reliability, and low anti-interference. Aiming to solve these problems, a novel solid-state dc circuit breaker is proposed in this paper. First, this paper analyzes the working principle and process of the circuit in detail according to the results of the simulation based on Saber. Second, this paper gives the criteria on how to choose the parameters of the components correctly in the circuit. The concept of the maximum fault resistance according to the minimum fault current is also introduced. Moreover, this paper analyzes the influence of the minimum fault ramp rate on the circuit performance. Finally, experimental results verify that the performance of this novel solid-state circuit breaker agree with the theoretical analysis. [ABSTRACT FROM AUTHOR]

Development of smart grid technologies has created a promising atmosphere for smart cities and energy trading markets. Especially, traditional electricity consumers evolve into prosumers who produce as well as consume electricity in modern power electric systems. In this evolution, the electric power industry has tried to introduce the notion of local energy markets for prosumers. In the local energy market, prosumers purchase electricity from distributed energy generators or the other prosumers with surplus electricity via a local power exchange center. For this purpose, this paper proposes joint geometric clustering and truthful auction schemes in the local energy markets. The proposed clustering scheme is designed for distribution fairness of the distributed energy generator for serving prosumers, where the scheme is inspired by expectation and maximization based unsupervised learning. Moreover, this paper proposes an auction mechanism for truthful electricity trading in a local energy market. In order to guarantee truthful electricity trading, the proposed auction mechanism is constructed based on the Vickrey–Clarke–Groves auction, which was proven to guarantee truthful operations. The Hungarian method is also considered in addition to the auction. The simulation results for the auction verify that the utilities of local market energy entities are maximized when the prosumers are truthful. [ABSTRACT FROM AUTHOR]

The railway power conditioner-based energy storage system (RPC-based ESS) is a promising technology to improve the regenerative braking energy (RBE) utilization and power quality of ac direct-fed (25 kV) and AT-fed (2 × 25 kV) railway power systems. However, despite its benefits from the technical perspective, economic viability must be concerned in industrial applications. The capacity is one of the critical issues affecting ESS performance in technical and economic aspects. Therefore, this paper presents a comprehensive approach to designing the capacity for the RPC-based ESS by considering multiple objectives, including the RBE utilization rate, power quality standard, and net lifetime benefit. The proposed approach develops a technical-economic model for the RPC-based ESS based on variables such as the system capacity for RBE utilization and power quality improvement, lifetime cost, and electric charge-based benefits. Moreover, the master-slave control strategy is employed to control the RPC-based ESS to implement the capacity design objectives. Finally, the correctness and effectiveness of the proposed method are validated by sufficient tests based on field load data of a Chinese traction substation. [ABSTRACT FROM AUTHOR]

The hybrid dc circuit breaker (HDCCB) is one of the most promising solutions for the dc interruption. But the power electronics-based load commutation switch (LCS) in the main current path causes the high on-state loss and cost, which inhibits the application of the HDCCB. In this paper, a novel hybrid dc circuit breaker is proposed, in which the vacuum interrupter with the external transverse magnetic field (ETMF) is designed to improve the arc voltage and thus enhance the current commutation to power electronics. The ETMF-based vacuum interrupter achieves the fast current commutation instead of the LCS, which realizes the low on-state loss and cost while preserving the short commutation and interruption time. The arc voltage characteristic with ETMF is analyzed, and the influence of the different factors on the commutation time and di/dt before current zero are investigated in detail. Based on the calculation results, a 10 kV dc breaker prototype based on the proposed topology is developed with the breaking current of 15.5 kA. Finally, the application of the proposed scheme in HVdc grids is discussed. [ABSTRACT FROM AUTHOR]

The flux-switching permanent magnet (FSPM) machine has aroused wide interest recently due to high-power density, favorable PM cooling capability, and essentially sinusoidal electromotive-force (EMF) waveform per phase. Previously, the phase back-EMF generation mechanism of FSPM machines is exposed from a flux-switching perspective, however, which is rethought from the viewpoint of air-gap modulation magnetic field in Part I as in this article, and electromagnetic torque generation mechanism of FSPM machines will be reported in Part II as another sister paper. With the aid of magnetic field modulation theory, the air-gap PM magnetic field and back-EMF of the FSPM machine are modeled based on modulation and winding functions. Their characteristics are analyzed in detail and consequently, principles concerning FSPM machines on arbitrary stator-slot/ rotor-pole combinations can be obtained, including the basic feature of FSPM machines, the principle and necessary conditions for the back-EMF generation, the fundamental reason of sinusoidal back-EMF waveform, and the contributions of modulation harmonics to phase back-EMF. Finally, experimental verification on a 12s/10p prototyped machine is conducted. [ABSTRACT FROM AUTHOR]

The design rules of winding configurations and stator-pole/rotor-tooth (SP/RT) number combinations of doubly-fed flux-switching permanent magnet (DF-FSPM) machines are investigated in this paper based on coil electromotive force (EMF) vectors. The relationships between the components of stator and rotor coil-EMF vector diagrams are unveiled at first, including the numbers of stator and rotor phases, and the numbers of stator and rotor spokes. Then, the SP/RT number combinations are derived considering feasible stator/rotor phase number combinations and different winding configurations. The SP/RT number combinations are optimized considering the winding factors, magnetic field harmonics, unbalanced magnetic forces and machine diameter. It is shown that both of the stator and rotor pitch factors increase when the SP and RT numbers get closer. Furthermore, the influence of winding configurations and SP/RT number combinations on electromagnetic performances of DF-FSPM machines are analyzed by finite-element method. Finally, the analysis results are validated by experiment. [ABSTRACT FROM AUTHOR]

Based on the back electromotive force generation principle in part I of the series papers, the electromagnetic torque generation mechanism of flux-switching permanent magnet (FSPM) machines is rethought in this article as part II from the perspective of air-gap modulation magnetic field. By magnetic field modulation theory, the air-gap armature magnetic field due to winding currents is modeled. Considering the unipolarity of the stator core, a novel concept of ‘fictitious modulation reluctance (FMR) rotor’ for FSPM machines is proposed. Then, by combining with the air-gap permanent magnet (PM) field and the FMR rotor, generation mechanisms of harmonic PM torque and reluctance torque are investigated. The requirements for FSPM machines to produce a stable electromagnetic torque are determined, i.e., |mPw ± vPr| = Ppm, mrvMfm ≠0, and ωe = Prωr. Besides, the harmonics operation states and harmonic torque characteristics of FSPM machines are analyzed and calculated based on the Maxwell stress tensor method. Further, the average torque versus current density predicted by finite element is validated by testing on an exampled 12s/10p FSPM one. [ABSTRACT FROM AUTHOR]

The fabrication of piezoelectric ZnO-based micro-electro-mechanical systems (MEMS) acoustic sensor has been reported. The sensor structure consists of a piezoelectric ZnO film deposited between two Al electrodes on a thin silicon diaphragm. A microtunnel is fabricated in the sensor structure using novel approach. This microtunnel is used to protect the diaphragm and determine the lower cut-off frequency of device. The approach presented in this paper completely removed a serious problem of microtunnel blockages during fabrication of sensors. In the developed process, the acoustic sensor fabricated using silicon-on-insulator and the Pyrex glass wafers are diced separately with same chip dimensions. Finally, both Pyrex glass and acoustic sensor chips are fitted in a jig for alignment and then anodically bonded. In reference to microtunnel blockages, the yield of the present technique is obtained as almost 100%. Also, the technique will serve as a cost-effective alternative to the present practice. The developed technique can also be used in manufacturing of similar devices where the microtunnels or microchannels are required in device structure. The technological development is supported by extensive atomic force microscopy (AFM), field emission scanning electron microscopy, Raman spectroscopy, and X-ray diffraction studies of ZnO film; glass-to-silicon bond strength measurement; resonance frequency measurement by laser doppler vibrometer; response characterization of the fabricated sensor, and scanning electron microscopy of microtunnel mouth to demonstrate the feasibility and yield of the process. [ABSTRACT FROM AUTHOR]

Conventional ultrasound probes have inherent limitations in some application scenarios. Because of their fixed shapes and sizes, they can hardly pass through small orifices to examine the target closely. With the recent development of microelectromechanical systems and flexible electronic technologies, collapsible and self-assembling devices are being considered as a potential approach to address this problem. This article presents an innovative transformable ultrasonic transducer (TUT), which can transform between a one-dimensional (1-D) linear array and a 2-D planar array with the ability of switching between different functions including 2-D/3-D imaging and high-intensity focused ultrasound beamforming. The transforming process is accomplished with a specially designed flexible printed circuit board inspired by a paper-folding mechanism. The electrical and acoustic properties of the developed transducer along with the acoustic field distribution in its different forms have been characterized. The 2-D/3-D imaging performances of the TUT have been also evaluated under 1-D and 2-D configurations, respectively. In addition, the performance of a focused concave transforming mode has been also discussed. The evaluation results suggest that TUT can maintain its performance under different structures with precise transforming control. The TUT device has the potential to considerably expand the applications of industrial and clinical ultrasound. [ABSTRACT FROM AUTHOR]

Metallized film capacitor (MFC) selection is a key step to ensure the safe and reliable operation of high-capacity power electronic equipment. However, as a crucial factor leading to overstress failure, the changing of stress tolerance boundary caused by parameter drift and insulation deterioration has not been fully considered in capacitor design. Therefore, the establishment method of MFC lifecycle safe operation area (SOA) is proposed innovatively in this article, which characterize the shrinking of safe operating boundaries caused by electrothermal coupling and capacitor aging during long-term operation. First, the failure mechanisms and electrothermal coupling of MFC are discussed and the modeling process of initial SOA is proposed based on the datasheet and dc withstand voltage experiments. In addition, considering the increase of the hot-spot temperature and the decrease of breakdown strength due to equivalent series resistance parameter drift and dielectric insulation degradation in the whole lifecycle, the shrinking of MFC operation boundary is characterized and the modeling process of lifecycle SOA is proposed based on aging model and lifetime tests. Finally, taking an MMC system as example, the MFC selection based on practical operating condition and lifecycle SOA is performed to verify the validity of the method. [ABSTRACT FROM AUTHOR]

The mechanical parameters, including the Coulomb and viscous friction coefficients together with the moment of inertia, are of great interest for the performance optimization and condition evaluation of surface-mounted permanent magnet synchronous motor (SPMSM) drives. This article contributes a speed-controller-independent mechanical parameter identification scheme using open-loop speed response due to signal injection, which has not been reported in existing works. It is designed based on the premise that the viscous friction torque is disproportional to the rotor speed, which is a new progress toward estimating the mechanical parameters with high precision. Moreover, as a practical full-participation-type solution, this scheme involves a new electrical parameter estimation technique based on differential algebra to assist in identifying the mechanical parameters. This auxiliary technique attains the current-controller-free estimation of the electrical parameters with the inverter nonlinearity eliminated, thereby addressing the current controller self-commissioning and serving to acquire the accurate electromagnetic torque. The experimental evaluations on two prototype SPMSM drive systems validate the feasibility of this suggested scheme. [ABSTRACT FROM AUTHOR]

The concept of energy Internet (EI) is very promising due to its ability to integrate distributed generators and storage devices. Energy routers (ERs) enable highly efficient, reliable, and flexible power system operation. To dynamically control and optimize energy flow in EI, an extensive communication is required. Considering the diversity of generators and ERs, it is crucial that such communication is achieved in a standardized and interoperable way. In this paper, an improved energy routing algorithm and its impact in EI operation are demonstrated. Furthermore, a full communication solution is developed for ERs and their interaction with grid operator. This paper proposes an International Electrotechnical Commission (IEC) 61850 communication-based power routing algorithm in microgrids. Optimal selection of source and routing path is achieved according to the proposed algorithm and communicated to the ERs via IEC 61850 based communication. The effectiveness of the proposed IEC 61850 communication-based routing algorithm is verified on network emulation platform comprising of IEC 61850 emulator tools and network simulator tool. [ABSTRACT FROM AUTHOR]

The classification of distinct problems of insulators in the distribution networks is a task that requires operator's experience. The applications of techniques to automate the inspection of electrical systems with the objective of detecting faults in insulators have shown to be reasonable alternatives to improve reliability in power grid. In this paper, based on the development of an experimental setup, signals are acquired considering three distinct faults in insulators. In this case, 13.8 kV (rms) is applied in drilled, contaminated, and good insulators considering an ultrasound detector connected to a computer. In the sequence, a multiclass classification method is proposed considering the ensemble of classifiers. The method considers the association of five distinct techniques, Bottom-Up segmentation, wavelet energy coefficient, principal component analysis, and particle swarm optimization associated with ensemble extreme learning machine (EN-ELM). Named optimized ensemble extreme learning machine, the present approach outperforms the original EN-ELM method. Finally, results show significant increase in robustness and faster training procedure when compared to classical approaches. [ABSTRACT FROM AUTHOR]

Robust and accurate control of a flapping-wing aerial vehicle (FWAV) system is a challenging problem due to the existence of backlash-like hysteresis nonlinearity. This paper proposes uncertainty and disturbance estimator (UDE)-based control with output feedback for FWAV systems. The approach enables the acquisition of the approximate plant model with only a partial knowledge of system parameters. For the design of the controller, only the bandwidth information of the unknown plant model is needed, which is available through the UDE filter. The stability analysis of the closed-loop system with the UDE-based controller is presented. It is shown that the proposed control scheme can ensure the boundedness of the control signals. A number of numerical simulations are carried out to demonstrate the satisfactory trajectory tracking performance of the proposed method. [ABSTRACT FROM AUTHOR]

The transverse dynamic force microscope (TDFM) and its shear force sensing principle permit true noncontact force detection in contrast to typical atomic force microscopes. The two TDFM measurement signals for the cantilever allow, in principle, two different scanning modes of which, in particular, the second presented here permits a full-scale noncontact scan. Previous research work mainly focused on developing the sensing mechanism, whereas this paper investigates the vertical axis dynamics for advanced robust closed-loop control. This paper presents a new TDFM digital control solution, built on field-programmable gate array equipment running at high implementation frequencies. The integrated control system allows the implementation of online customizable controllers, and raster scans in two modes at very high detection bandwidth and nanoprecision. Robust control algorithms are designed, implemented, and practically assessed. The two realized scanning modes are experimentally evaluated by imaging nanospheres with known dimensions in wet conditions. [ABSTRACT FROM AUTHOR]

This paper proposes and investigates a novel near-optimal finite-control-set model predictive control (NOP-MPC) algorithm to control the grid-connected, pulsewidth-modulator-driven voltage source converters with LCL filters. Exploiting the convex and elliptical paraboloid properties of the cost error, NOP-MPC adopts a systematic iterative algorithm within each control cycle to progressively synthesize finite sets of virtual voltage vectors (VVs) for the control optimization stage. The synthesis has the inherent features of respecting the converter voltage limits and converging the sets of VV candidates toward the global optimal point. The fixed-switching-frequency feature of NOP-MPC is expected to ease the LCL filter design. Effects of computational delay, pulsewidth modulation delay, and deadtime are considered and compensated successfully. A two-vector-variable cost function is used to actively damp the inherent LC resonance through an adjustable, weighting-factor-based damping level. This paper is substantiated by theoretical consideration, simulation and experimental results, parameter sensitivity study, and a comparative study with the standard finite-control-set model predictive control that uses only actual VVs. [ABSTRACT FROM AUTHOR]

Smart buildings form an integral part of the smart grid that lowers electricity cost. This objective can be achieved by using suitable enhanced algorithms and techniques. The motivation of this paper is the request for an economical decision-making system from a commercial company in Singapore. This paper presents an economical building management system (EBMS) concept inspired by the building management system and machine learning. EBMS improves the decision-making process through rule-based algorithm within the system. Machine learning algorithm is included as part of EBMS to enhance the computational calculation for the electricity distribution. It includes the function of self-making decision for purchasing electricity based on forecasting system for electricity price or real-time electricity price data when facility managers are not present. EBMS uses multiagent system to communicate, interact, and negotiate with multiple agents for energy supply and demand in the building. Simulation studies have shown the potential of EBMS concept to provide a cost reduction solution up to 61.42% savings for smart buildings. Better electricity purchasing contract option can be decided based on the forecasting system for building power consumption. [ABSTRACT FROM AUTHOR]

In this paper, the modular consequent-pole (MCP) rotor is adopted in the fractional-slot interior permanent magnet (IPM) machine to utilize the strong flux-focusing effect and reduce the leakage flux. Hence, the torque density and utilization ratio of permanent magnet (PM) material can be improved. However, the unacceptable unbalanced magnetic force (UMF) may arise due to asymmetric airgap flux density produced by consequent-pole topology. Thus, a pole-shaping method based on three-sectional arcs is proposed to suppress it. Due to the relatively complex rotor structure, the multiobjective optimization combined finite-element method with genetic algorithm is performed in this paper. Furthermore, the electromagnetic performance of the IPM machine with MCP rotor (namely IPM-MCP machine), including the open-circuit airgap flux density, phase back EMF, torque, PM utilization ratio, efficiency, flux-weakening capability and UMF, are compared with the conventional surface-mounted PM (SPM), IPM, and consequent-pole IPM (IPM-CP) machines. It is demonstrated that the IPM-MCP machine obtains the largest output torque in these machines. Meanwhile, the IPM-MCP and IPM-CP machines respectively have >30% and >20% higher PM utilization ratio than the conventional SPM and IPM machines while they obtain similar torque ripple and efficiency. Moreover, the IPM-MCP machine can obtain much lower UMF than the IPM-CP machine due to the effective suppression of asymmetric airgap flux density. Finally, a 12-slot/10-pole IPM-MCP machine is fabricated to verify the analyses. [ABSTRACT FROM AUTHOR]

The ability to monitor the quality of the metal forming process as well as the machine's condition is of significant importance in modern industrial processes. In the case where a physical device (i.e., sensor) cannot be deployed due to the characteristics of the system, models that rely on the estimation of both the applied force and the dynamic behavior of the machine (i.e., system) are adopted. The development of such models and the corresponding algorithms used to estimate the above-mentioned quantities has attracted the interest of the community. The main contribution of this paper is the estimation of a servo press force by employing a novel dual particle filter based algorithm, achieving a maximum relative error in the force estimation of 3.6%. Moreover, to address real-time performance requirements, this paper proposes a field programmable gate array based accelerator that improves the sampling rate by a factor of 200 compared to a processor-based solution, thus enabling the deployment of the system in many realistic scenarios. [ABSTRACT FROM AUTHOR]

This paper aims to propose a new Vernier reluctance machine (VRM), which integrates the advantages of a robust rotor structure, good torque density, and flexible flux control ability. The key is to establish the excitation field with both stator slot permanent magnets (PMs) and zero-sequence current. Two excitation sources have different pole pair numbers but share a parallel magnetic circuit and contribute to superimposed torque in this machine. Meanwhile, a flexible flux control can be achieved by regulating zero-sequence current, and little demagnetization risk exists for slot PMs during flux control. In this paper, the machine configuration and operation principle are introduced, along with its integrated ac and dc drive method. Electromagnetic performance of this new machine is evaluated by finite-element analysis. Leading design parameters are determined and optimized considering optimal injection ratio of zero-sequence current. A prototype is fabricated, and relevant experiment results demonstrate the feasibility of the proposed solution. [ABSTRACT FROM AUTHOR]

In order to improve the performance of interior permanent magnet synchronous machine (IPMSM) based on space voltage vector modulation schemes, this paper presents a highly accurate online method to find the proper maximum-torque-per-ampere (MTPA) angles. This algorithm fully considers the nonlinear characteristics of the d-axis inductance, q-axis inductance, and permanent magnetic flux together. Additionally, the influences of temperature are taken into account. In this paper, the proposed method injects a small virtual angle signal into the current angle mathematically to track the stator current reference angle that is close to real MTPA points. Moreover, following a theoretical analysis method, the error of the virtual signal injection method is analyzed. Then, based on the results of error analysis, this paper proposes a compensation strategy that can significantly reduce the current angle error between the tracking point and real MTPA point. At last, various experiments on an IPMSM test bench verify the proposed control technique and overall performance. [ABSTRACT FROM AUTHOR]

In most multiobjective optimization problems of electrical machines, the weighted function method is used to convert them into single-objective optimization problems. This paper applies a kind of new multiobjective evolutionary algorithms (MOEAs), called adaptive multiobjective black hole (AMOBH) algorithms, to achieve effective multiobjective optimization of a tubular coreless linear permanent magnet synchronous motor (LPMSM). To reduce the computation cost of the MOEAs, a one-layer analytical model (AM) is presented for the tubular coreless LPMSM in this paper. The accuracy of the simplified one-layer AM is verified by comparisons with multilayer AM and finite element analysis (FEA) under different structure parameters. It is found that the simplified AM has good accuracy and can decrease the computation cost significantly. AMOBH algorithm is subsequently introduced. The optimal Pareto front with regard to thrust, copper loss, and permanent magnet volume are analyzed, and more diversified optimization results are provided. The final Pareto solution can be selected directly by practical physical values according to the application requirements. Finally, a prototype is fabricated for the selected design; its experimental results are provided and compared with those of the FEA results. [ABSTRACT FROM AUTHOR]