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This paper presents a hybrid power supply system for robot actuators that has multiple voltage buses and hybrid energy storage including a supercapacitor. The proposed system utilizes a multi-tasking control scheme to reduce the component count. To improve the system response of mobile robots, a supercapacitor is employed in the proposed architecture along with a battery. The proposed circuit offers two higher voltage buses than the main battery voltage in order to employ higher voltage actuators with a lower current for a higher power density. To manage the DC buses and the supercapacitor’s bidirectional power flow, three switching devices are used in the proposed structure, reducing a switching device and an inductor. A control structure using a mixed switching strategy has been developed to regulate the higher-voltage buses and the supercapacitor’s power flow simultaneously. The proposed control and circuit structure are validated by hardware experiments.

A series arc produces both light and heat, which results in a risk of fire. Hence, its prompt detection is very important. The series arc has different frequency characteristics depending on the operating conditions of the inverter and the line impedance. As a result, it is difficult to detect with conventional methods that use specific frequency bands. In this study, series arcs generated by three-phase pulse-width-modulated and three-phase model-predictive-control inverter loads, operating under various conditions, were detected using a deep-learning algorithm. To detect a series arc fault, the frequency characteristics were analyzed using all the frequency bands of a fast Fourier transform (FFT) result. To use all the frequency bands, a deep neural network (DNN), which is a deep-learning algorithm, was used. DNNs can learn quickly from large amounts of data and model complex nonlinear relationships. The DNN model proposed in this paper was designed to use all the frequency bands, and three cases were tested by changing the current magnitude and switching frequency. The arc current detection accuracy was calculated for three test cases and the obtained results were analyzed in detail based on the percentages of true/false and mean absolute error metrics. The analysis confirmed that the arc current was accurately detected, which validates the suitability of the DNN for series arc detection.

Various studies on arc detection methods are described. Series AC arc is detected based on the characteristics extracted from arc voltage, frequency, and time domain of the current. Methods of arc detection using artificial intelligence have been studied previously. In the present study, the performance of multiple methods is analyzed by comparing different input parameters and artificial neural networks. In addition to the input parameters presented in the literature, the performance is compared and analyzed using the following parameters: zero-crossing period, frequency average, instantaneous frequency, entropy, combination of fast Fourier transform (FFT) and maximum slip difference, and combination of FFT and frequency average. These parameters and different neural networks are studied in the bounded and unbounded case, and the performance is compared. For different combinations of neural networks and input parameters, another research question is to identify the input parameters to be used if the number of training data is limited. Moreover, this study investigates the change in detection rate depending on the number of training samples. As a result, the minimum dataset size required to obtain the final detection rate is identified.

This paper presents a computational reduction algorithm for applying model predictive control to a three-level four-leg converter. An optimal switching state is selected by only considering 7 voltage vectors located near the reference voltage vector, rather than using 81 voltage vectors in every sampling period, as in the conventional method. The sector, prism, and tetrahedron are sequentially selected using the position of the reference voltage vector. In addition, the seven voltage vectors selected in advance are the vectors constituting the selected tetrahedron. Thus, the proposed method reduces the computational cost and provides an improved model predictive control that does not affect the performance. The proposed method comprises an experimental setup of the proposed three-level four-leg converter to compare its performance with that of the conventional method.

Owing to the low number of submodules (SMs) in modular multilevel converters (MMCs), especially in medium-voltage applications, the output current and voltage generated by conventional nearest-level control (NLC) methods contain evident distortions. Previously, various hybrid and level-increased NLC methods have been proposed to improve the output voltage quality, but such measures wither increased the complexity or did not regulate all the control objectives simultaneously. To further enhance the output performances of MMCs containing low numbers of SMs, an improved predictive NLC (I-PNLC) method combining NLC and model predictive control (MPC) is proposed, where the output and circulating currents are regulated with the corresponding predicted references, and the output voltage is controlled by the added voltage correction. The proposed I-PNLC not only reduces the output current and voltage total harmonic distortion (THD) considerably but also avoids additional complexity in the control system design. The results of simulations and an experiment are presented to verify the proposed approach, in addition to a comparison of the evaluations of conventional NLC methods.

The wide variety of arc faults induced by different load types renders residential series arc fault detection complicated and challenging. Series dc arc faults could cause fire accidents and adversely affect power systems if not promptly detected. However, in practical power systems, they are difficult to detect because of a low arc current, absence of a zero-crossing period, and various abnormal behavior based on different types of power loads and controllers. In particular, conventional protection fuses may not be activated when they occur. Undetected arc faults could cause false operation of power systems and potentially lead to damage to property and human casualties. Therefore, it is imperative to develop a detection system for series arc faults in DC systems for the reliable and efficient operation of such systems. In this study, several typical loads, especially nonlinear and complex loads such as power electronic loads, were chosen and analyzed, and five time-domain parameters of the current—average value, median value, variance value, RMS value, and distance of the maximum and minimum values—were chosen for arc fault detection. Various machine learning algorithms were used for arc fault detection and their detection accuracies were compared.

Nearest-level control (NLC) is a popular technique used in modular multilevel converters (MMCs) with a large number of submodules (SMs) owing to the NLC's flexibility and ease of implementation. However, in medium-voltage applications, MMCs contain a relatively low number of SMs, and the drawbacks of the NLC methods emerge, wherein the poor quality of output voltages and currents result in high total harmonic distortion, large ripples in SM capacitor voltages, and unsuppressed circulating currents. Several NLC methods have been proposed to handle these problems, but they do not satisfy all the control objectives simultaneously. This paper proposed a modified NLC capable of enhancing the output quality of MMCs with low number of SMs without deteriorating the control objectives. Unlike previously reported NLC methods, instead of directly calculating the numbers of SMs from the upper and lower arm voltage references, the difference and total number of SMs are obtained from the output voltage reference and circulating current control, respectively. Hence, the numbers of SMs in the upper and lower arms are acquired by simply solving a system of first-order two-variable equations. The simulated and experimental results for a single-phase MMC system were used to verify the appropriateness and effectiveness of the proposed modified NLC method.

48 V electric system architecture has been recently introduced to accommodate an increasing number of electric components in mild hybrid electric vehicles. In this study, two additional DC buses are added for electric machines including 36 and 24 V AC- and DC-motor/actuator loads, in a 48/12 V power supply system. This structure can yield significant benefits, especially for electrified vehicles that have more electric machines and actuators. A single-inductor multi-output structure is employed, with a control strategy that produces linear transfer functions and is less sensitive to load variation, to accommodate multiple-bus motor/actuator drives. The proposed structure and control strategy can offer options for selecting proper bus voltages, optimising the electric machine's power density. Both simulations and experiments have been performed to verify the system structure and control schemes using 36 and 24 V electric machines connected to the additional dual-output buses on top of the existing 12/48 V bus structure.

This paper presents switch fault detection and compensation control schemes for a modified dc-dc converter that relocates a diode location. The proposed fault detection and compensation control schemes are applicable to various energy generation systems that include energy storage. A fault detection index has been introduced to detect an open switch fault in the modified converter structure, and a compensation control method based on a mixed switching strategy has been developed. The fault-tolerant control method along with the detection scheme can make a system return to work even under a switch fault. The proposed schemes have been tested and verified both by the simulations and by experiments using a TMS320F28335 DSP. The results will significantly improve the reliability of alternative energy generation systems against open switch faults.

This paper proposes a novel input power factor control method based on a concept of virtual capacitors to provide unity input power factor for three-phase matrix rectifiers. The proposed algorithm introduces, at the input terminal of the matrix rectifier, an imaginary input capacitor generated by modifying a reference vector of the space vector modulation method. The virtual input capacitor, which is fictitiously built in parallel with an input LC filter, successfully compensates for the leading power factor of the LC filter of the matrix rectifier. Thus, the proposed method yields a unity power factor operation despite the presence of the LC filter of the three-phase matrix rectifier. In addition, under a condition when the unity power factor operation cannot be realized, the proposed algorithm adjusts a virtual capacitance to obtain a maximum achievable power factor operation. Because the proposed technique yields the input power factor control by introducing the virtual capacitor and adjusting a reference space vector, the proposed algorithm can be easily incorporated with conventional space vector modulation algorithms for the three-phase matrix rectifiers. Thus, the proposed method can control input power factor without employing proportional-integral controllers used in conventional power factor control methods for the matrix rectifiers, leading to simple control structure and straightforward tuning process for power factor control.

High modularity, easy scalability, and superior harmonic performance, comprising the topology with the most potential for medium- to high-voltage high-power applications, are representative features of a modular multilevel converter (MMC). Each application of a MMC requires a proper scheme such that it conforms to control objectives such as correct submodule capacitor voltage balancing control and the suppression of circulating current. Over the past few years, various studies have been presented that meet the MMC requirements through both classical control-based pulse-width modulation and model predictive control, although some drawbacks exist for both control concepts. The dynamic performance of the classical control methods with proportional-integral or proportional-resonant controllers is unsatisfactory, and the requirement of proportional-integral parameters tuning procedure makes converter operation performance depends on proportional-integral parameters adjustment. Meanwhile, model predictive control performance depends significantly on the mathematical model of a system, and weighting factor selection is tedious. In this paper, we propose an improved phase-shifted carrier pulse-width modulation method and capacitor voltage balancing control that inherits the merits from both classical control and model predictive control. Meanwhile, the proposed control method eliminates the requirement of the tedious proportional-integral parameters tuning procedure and improves the dynamic performance compared with the conventional phase-shifted carrier pulse-width modulation-based proportional-integral controller method. Simulations and experiments were conducted to demonstrate the proposed method's properness.

This paper proposes a direct power control (DPC) method with a minimum reactive power reference for ac-to-dc matrix rectifiers using space vector modulation. Based on the calculated active and reactive power reference values, the developed DPC algorithm directly controls both the active and reactive power components of the source by operating the three-phase matrix rectifiers, thereby obtaining the sinusoidal input currents and output dc voltage/current of the rectifier. The proposed DPC method instantaneously determines a source reactive power reference command to achieve a unity input power factor or maximum achievable power factor on given input and output conditions, because ac-to-dc matrix rectifiers cannot always attain a unity power factor due to the existence of the input capacitors. In addition, the developed algorithm calculates the minimum reactive power reference without using any circuit parameters. Thus, the proposed algorithm is free from any inevitable parameter uncertainty, resulting in a more robust and accurate power factor control for the rectifier. Based on the minimum reactive power reference, the proposed algorithm enables matrix rectifiers to operate at an input power factor that can be maximally obtained at all times. The effectiveness of the proposed method was verified by the simulations and experiments.

When single-phase three-level neutral-point-clamped (NPC) converters operate, there are two main control objectives that need to be met for correct operation. First, the ac source current must be controlled to be sinusoidal. Second, the dc capacitor voltages must be balanced. In original model predictive control (MPC) methods for NPC converters, an optimization process involving an empirical weighting factor design is required to meet both of these objectives simultaneously. This study proposes an MPC approach developed for single-phase three-level NPC converters to meet these objectives using a single reference voltage consisting of a difference-mode term and a common-mode term in each phase. The difference-mode term and the common-mode term are responsible for sinusoidal ac source current synthesis and dc capacitor voltage balancing, respectively. Then, a single cost function compares the adjusted reference voltage with possible voltage candidates to select an optimal switching state, resulting in the smallest cost function value. Different from the conventional MPC method, the proposed approach avoids the selection of weighting factors and the attendance of various control objectives. Thanks to the deterministic approach, the proposed MPC method is straightforward to implement and maintain fast transient performance while guaranteeing the control objectives. Finally, the effectiveness and feasibility of the proposed approach for single-phase three-level NPC are verified through comprehensive experimental results.

Capacitors are critical components of power converter systems as they influence the cost, size, performance, and scale of such systems. However, capacitors exhibit the highest degeneration and breakdown rates among all power converter components due to their wear-out failures and short lifespans. Therefore, condition monitoring is a vital process to estimate the health status of capacitors and to provide predictive maintenance for ensuring stability in the operation of power converter systems. The equivalent series resistance (ESR) and the capacitance of the capacitor are two widely used parameters for evaluating the health status of capacitors. Unlike the ESR, the capacitance of a capacitor is suitable for the health monitoring of various types of capacitors; therefore, it is more preferable for large-scale systems. This paper presents an overview of previous research addressing this aspect of capacitors and provides a better understanding of the capacitance monitoring of capacitors utilized in power converter systems.

In order to apply the model predictive control to the power converter, a study on the calculation amount reduction algorithm was performed in various topologies such as 2-level, 3-level, multi-level converter. Similarly, in order to apply the model predictive control to the 3-level 4-leg converter, it is necessary to study the calculation amount reduction algorithm. In this paper, instead of considering 81 candidate voltage vectors for every sampling period as in the conventional model predictive control, the optimal switching state is selected considering only 7 candidate voltage vectors located near the reference voltage vector. The sector, prism, and tetrahedron are selected sequentially by using the position of the reference voltage vector, and the preselected 7 candidate voltage vectors are the vectors constituting the tetrahedron. The proposed method represents an improved model predictive control which reduces the amount of computation and does not affect performance. This method constructs the 3-level 4-leg NPC inverter simulation and experimental setup to compare the performance with the conventional method.

Model predictive control (MPC) for modular multilevel converter (MMC) systems has drawn attention among researchers in recent years due to its straightforward implementation, ability to control multiple objectives in a single cost function, and excellent dynamic response. Even though MPC seems promising for the MMC, it suffers from an excessive increase in computational complexity when the number of submodules (SMs) per arm ( N ) is increased. The computational load can be reduced by decoupling the SM capacitor voltage control from the cost function and balancing them in an external voltage sorting algorithm. In this paper, a further reduction of computations in the MPC is achieved by the preselection of control options that can satisfy the control objectives in the next sampling time. The preselection algorithm generates a greatly reduced number of control options to be computed by a straightforward MPC loop at each sampling time. In addition, the MPC together with the preselection algorithm can generate $2N+ 1$ output voltage levels in the MMC while maintaining a low $dv/ dt$ in the output voltage and suppressing the circulating currents in MMCs with considerable number of SMs. The steady-state and dynamic performance of the MMC operating with the proposed method is verified by simulation and experimental results.

Active front-end rectifiers are tasked with generating high-quality, low-distortion sinusoidal line currents in the presence of adverse circuit conditions. When suitable control methods are applied to such rectifiers, significant performance improvements can be realized, especially under abnormal utility conditions. Although several control methods based on model predictive control platforms have been recently developed, there is a lack of comparative studies of these methods in the literature. In this paper, the details and theoretical background of four model predictive control methods, namely, current control, virtual flux control, direct power control, and virtual flux direct power control, are presented. Then, the performance of these methods was compared by the way of experiments to determine the respective quality of the line current under various conditions, such as unbalanced input voltages, input voltage distortion, uncertainty in the parameters, and dc voltage fluctuation. In summary, based on the results of the experiments, the virtual flux control scheme was found to be distinctly superior to the other three schemes for distorted and unbalanced line voltages.

Demand for modular multilevel converters (MMCs) has been steadily increasing for utilization in medium- to high-power applications because of qualities such as high modularity, easy scalability, and superior harmonic performance. Furthermore, there has been a growing trend toward utilizing model predictive control for MMCs due to its simplicity, good dynamic response, and ease of multi-objective control. However, the rise in computational load leads to a great drawback when increasing the number of submodules (SMs). This paper presents an approach to reducing the computational load and using on-state SMs and circulating currents, by preselecting the number of SMs inserted in the upper and lower arms. This approach is based on using the number of on-state SMs and the circulating current, to compute the number of SMs inserted in the upper and lower arms, which is evaluated in the next sampling instant. This facilitates a significant reduction in the number of control options and the computational load. A sorting algorithm is used to retain the balancing capacitor voltages in each SM, while the cost function guarantees the regulation of the ac-side currents, arm voltages, and MMC circulating currents. Simulation and experiment results validate the performance of the proposed approach.

A predictive direct power control (PDPC) technique to decrease switching loss by injecting offset voltage is proposed for three-phase voltage source converters. The active and reactive power elements of the converter are directly controlled by using three-phase future converter input voltages, which are modified for lowering switching losses by injecting a future offset voltage. Switching operations, generated by the developed PDPC algorithm with modified converter voltage, stop switching operation in one of the converter phases exposed to the highest input current. The non-switching period and the non-switching phase in the proposed technique is automatically adjusted by the reactive power reference, which leads to high efficiency, irrespective of varying input power factor angle condition. The proposed algorithm chooses one optimal voltage vector enabling future active and reactive power to approach closest to the future power references and prohibiting switching of one converter phase conducting the highest current at each step. Therefore, the developed technique can directly control power components and increase converter efficiency, which is proven by simulation and experimental verification.

This paper proposes a model predictive virtual flux control (MPVFC) method that can mitigate the degradation of the total harmonic distortion of rectifier input currents experienced by active front-end (AFE) rectifiers when input voltages are distorted by harmonics. The proposed method utilizes a cost function based on virtual fluxes, which are robust to input voltage distortions, to control the rectifiers. For the calculation of the proposed cost function which consists of a predictive value of the rectifier virtual flux and a reference of the rectifier virtual flux, the dynamics of AFE rectifiers and the definition of the integration in the discrete time domain are used. Also, the phase of the reference current which is needed when calculating the reference of the rectifier virtual flux is obtained by the input virtual flux. The proposed MPVFC method shows better input current waveforms with lower total harmonic distortion than those obtained with the conventional model predictive control method under input voltage distortion conditions, which was proved via simulations and experiments.

In a current source rectifier such as a matrix rectifier, input voltage and current cannot be in phase unless an additional input power factor control technique is implemented. This paper proposes such a technique for a matrix rectifier using power-based space vector modulation (SVM). In the proposed method, the modulation index and phase required in order to apply the SVM are calculated based on the active and reactive power of the rectifier for intuitive power factor control. The active power that the rectifier should generate for the regulation of the output inductor current is obtained by the PI (proportional-integral) controller. The reactive power, which is supplied by the rectifier for adjustment of the power factor, is assigned differently depending on the output condition: for the output condition capable of unity power factor, it is set to a negative value of reactive power of the input capacitor, and when the unity power factor is not achievable, it is set with the maximum reactive power the rectifier can generate under the given condition to attain the maximum possible input power factor. It is determined whether the given condition is the light load condition by comparing the absolute value of the reactive power supplied by the input capacitor with the maximum rectifier reactive power that can be produced under the given condition. The SVM based on the active and reactive power of the rectifier in this technique allows the input power factor control to be intuitive and simple. The performance and feasibility of the technique were proved by simulation and experimentation.

A switching losses reduction technique for the model predictive control (MPC) algorithm, which uses double-vector in the three-phase rectifier, is presented. The proposed method controls the output voltage of the rectifier by using reference rectifier input voltages with the offset voltage injection to reduce the switching losses. One leg with the largest source current among the three legs in the rectifier is clamped to either the positive or negative output voltage in the proposed method. The proposed method calculates the offset voltage on the basis of the future rectifier input voltages obtained by the reference rectifier input voltage, output voltage, and the source currents in every sampling period, so the clamping region in the leg conducting the largest input current is optimally varied depending on the reference rectifier input voltages and the source currents. Therefore, the proposed method can reduce the switching losses of the rectifier regardless of the different source power factor angle. Due to the effects of clamped legs, the quality of the input current waveform inevitably deteriorated. Thus, in the proposed method, double vectors were utilized to avoid degradation of current qualities and achieved compromised performance by reducing switching losses and keeping the current waveform quality. A performance comparison between the conventional method and the proposed method was made to show performance differences. Additionally, the simulation and experiment were conducted to verify the effectiveness of the proposed method.

Six-phase Interior Permanent Magnet Synchronous Machine(IPMSM) is adopted for lower torque ripple, reduced phase current, and higher fault tolerance. For the high tolerant operation such as traction systems, six-phase machine enables converting to three-phase operation and lower torque ripple than five-phase is generated when one phase is in open fault state. In this paper, six-phase machine was analyzed to identify the variation of generated torque, copper loss and iron loss in three-phase operation. And also, the comparison with the results of normal six-phase operation is represented to verify trade-off.

The sorting algorithm is the most widely accepted capacitor voltage balancing strategy for a modular multilevel converter. This strategy offers to keep the balance among submodule capacitor voltages under all of the modular multilevel converter working conditions. However, this method generates unnecessary switching transitions in submodules, which results in high switching frequency and switching loss, and uneven distribution of switching transitions and switching loss among submodules (SMs). In this paper, a simplified switching loss balancing control strategy was proposed in order to handle these issues. The proposed approach adjusted the submodule selection process of the sorting algorithm by taking into consideration the number of switching transitions in addition to the capacitor voltages. Even distribution of switching transitions and switching loss was achieved, and the average switching loss was reduced at the cost of slightly increasing the capacitor voltage fluctuations. The effectiveness of the proposed approach was verified through both simulation and experimental results.

Even though classical control based pulse-width modulation has a superior steady state performance and stable switching state, it suffers from some drawbacks. The dynamic performance of the classical control methods with proportional-integral or proportional-resonant controllers is unsatisfactory and the requirement of proportional-integral parameters tuning procedure makes designing the controller more complex. In this paper, we propose a novel phase-shifted carrier pulse-width modulation method and capacitor voltage balancing control aimed at medium-voltage applications. The proposed control method eliminates the requirement of the tedious proportional-integral parameters tuning procedure and improves the dynamic performance compared to the conventional phase-shifted carrier pulse-width modulation-based proportional-integral controller method. Simulations were conducted to demonstrate the proposed method's properness.

In single-phase three-level neutral point (NPC) converters, two major objectives are to generate sinusoidal source current and to balance two dc capacitor voltages. This paper proposes a model predictive control (MPC) method for the NPC converters to accomplish these multi-objectives using single reference voltage with offset voltage injection, without using a weighting factor in a cost function. The proposed MPC method determines a modified reference voltage signal which simply adds a reference voltage and an offset voltage, where a reference voltage deals with sinusoidal source current synthesis and an offset voltage accomplishes capacitor voltage balancing. By comparing the modified reference voltage with all possible voltage candidates producible in the single-phase three-level NPC converter, an optimal state to the dc voltage balance as well as the sinusoidal source current control with unity power factor is selected at every step. As a result, the proposed method is free from multi-objective optimization issue and empirical approaches to select a proper weighting factor accompanied by conventional MPC methods for the NPC converters. Therefore, the proposed method is easy to implement based on a deterministic approach for the capacitor voltage balance as well as the sinusoidal source current control, whereas fast dynamic performance is guaranteed.

In this paper, the model predictive current control (MPCC) method using two vectors has been proposed to control output currents of three-phase voltage source inverters (VSIs) with small current errors and current ripples. Also, the proposed method can reduce switching losses by applying the vector pre-selection technique to the MPCC for the VSI. The VSI generates seven voltage vectors to control the output currents, but the proposed method uses four available voltage vectors with one switch, which are classified by the vector pre-selection method clamping one leg and conducting the largest output current among the three legs to reduce the switching losses. In the proposed method, selecting two future voltage vectors among the four voltage vectors and dividing them in a future sampling period are determined by an optimization process. The proposed method results in the lower total loss, better total harmonic distortion (THD), and smaller current errors than the conventional method with half the sampling period of the proposed method due to the optimal process. Simulation and experimental results of the three-phase VSIs are presented in order to verify the effectiveness of the proposed method.

Active front end (AFE) rectifier has been widely used for making high quality, little distorted sinusoidal input currents in several conditions. If appropriate control schemes are applied to AFE rectifier, respectable high performance is able to be realized. In this paper, the explanation of MP-VFC method was exhibited, and the performance comparisons of the four control methods which are MP-VFC (Virtual Flux Control), MP-CC (Current Control), MP-DPC (Direct Power Control), and MP-VFDPC (Virtual Flux Direct Power Control), were proceeded under several conditions, which are input voltage unbalance, input voltage distorted by fifth and seventh harmonic components. In summary, on the basis of the results of the experiments, the MP-VFC method shows excellent performance compared to the other three methods for input voltage distortion and unbalance.

This paper proposes the power factor control algorithm of current source rectifier using the virtual inductance in the space vector modulation. In the proposed method, the phase difference between the input voltage and the input current is removed by the virtual inductor parallel to the input capacitor, which make the impedance of the input capacitor-side infinite. To find the virtual inductance, the capacitance of the input capacitor and the angular frequency of the input voltage is utilized. By additionally making the current in the virtual inductor from the rectifier, the effect of the virtual inductor which make the impedance of the input capacitor-side infinite can be implemented. The additional current is calculated by integration of the input voltage and the virtual inductance. The proposed method has advantages of yielding input unity power factor without input current sensing. Simulation and experiments verify the effectiveness of the proposed power factor control method.

This paper proposes a highly efficient single-phase three-level neutral point clamped (NPC) converter operated by a model predictive control (MPC) method with reduced commutations of switches. The proposed method only allows switching states with none or a single commutation at the next step as candidates for future switching states for the MPC method. Because the proposed method preselects switching states with reduced commutations when selecting an optimal state at a future step, the proposed method can reduce the number of switchings and the corresponding switching losses. Although the proposed method slightly increases the peak-to-peak variations of the two dc capacitor voltages, the developed method does not deteriorate the input current quality and input power factor despite the reduced number of switching numbers and losses. Thus, the proposed method can reduce the number of switching losses and lead to high efficiency, in comparison with the conventional MPC method.

Model predictive control has become a tremendously popular control method for power converters, notably a modular multilevel converter, owing to the ability to control various objectives at once with a particular cost function and prominent dynamic performance. However, the high number of submodules in cascaded control means that the model predictive control for the modular multilevel converter suffers from a computational burden. Several approaches focused on reducing the computational burden based on limiting the number of possible switching states (possible choices) to be evaluated at each sampling instant. The dynamic performance of the modular multilevel converter is degraded in a transient state, despite the reduced computational burden. This paper presents an improved indirect model predictive control method to reduce the computational burden and enhance the dynamic performance. The proposed approach considers the steady-state and transient state individually and applies a different range of choices for each specific case. The range of choices during the steady-state is limited in order to reduce the computational burden without deteriorating the output quality, whereas the number of choices will be increased during the transient state to guarantee dynamic performance. The results that were obtained by implementing an experiment on a laboratory setup of a single-phase modular multilevel converter are presented in order to verify the proposed approach&rsquo, s effectiveness. From the experimental setup, the computational time in the proposed approach was reduced by about 75% when compared with the conventional indirect model predictive control, whereas keeping fast dynamic performance.

According to the change of traction system from combustion engine to electric motor for electric vehicles, the compressor in air conditioner needs to be replaced to the separated system. This paper compares the performance of distributed and concentrated wound interior permanent magnet synchronous motor (IPMSM) for compressor. Each IPMSM model is analyzed by 2D FEA for cogging torque, output torque and back-EMF. Furthermore, the analysis of torque ripple characteristics, loss calculation and saliency ratio are performed.

A model predictive current control method is proposed to reduce switching losses in an AC-DC matrix converter. In the proposed control strategy, several vectors are selected from among all possible switching vectors for a given location of the input current reference. The switching vector that minimizes the cost function is applied to the converter in the next sampling period. The principle of the proposed method involves clamping the selected switches to stop performing the switching operation to minimize the number of switchings in every sampling cycle. The total efficiency of the AC-DC matrix converter under the proposed strategy is 91.2% whereas that of the conventional strategy is 89.7%. In addition, unity-power-factor operation is guaranteed and smooth and sinusoidal waveforms are achieved. Finally, simulation and experimental results are demonstrated to confirm the validity of the proposed control strategy.

This paper proposes an approach to improve the computational burden of Model Predictive Control (MPC) method by preselecting insertion indexes. This approach is based on utilizing number of on-state submodules (SMs), neighboring output voltage levels and circulating current to calculate the insertion indexes which are evaluated in the next sampling instant. This allows to reduce significantly number of control options and the computational burden. By using a sorting algorithm, which retains balance of capacitor voltages while a cost function ensures the regulation of the output current, arm voltages, and MMC circulating currents. Performance of the proposed approach is verified by experimental results.

In multilevel cascaded H-bridge (CHB) inverters, the number of voltage vectors generated by the inverter quickly increases with increasing voltage level. However, because the sampling period is short, it is difficult to consider all the vectors as the voltage level increases. This paper proposes a model predictive control algorithm with reduced computational complexity and fast dynamic response for CHB inverters. The proposed method presents a robust approach to interpret a next step as a steady or transient state by comparing an optimal voltage vector at a present step and a reference voltage vector at the next step. During steady state, only an optimal vector at a present step and its adjacent vectors are considered as a candidate-vector subset. On the other hand, this paper defines a new candidate vector subset for the transient state, which consists of more vectors than those in the subset used for the steady state for fast dynamic speed; however, the vectors are less than all the possible vectors generated by the CHB inverter, for calculation simplicity. In conclusion, the proposed method can reduce the computational complexity without significantly deteriorating the dynamic responses.

This paper proposes a novel method to reduce switching losses on the basis of a model-predictive direct power control (MPDPC) method for ac-dc active rectifiers. The main idea is to preselect voltage vectors to decrease switching losses at the next sampling period, and then select one optimum voltage vector among only the preselected voltage vectors to perform direct power control (DPC). The proposed vector preselection scheme enables a predefined cost function to consider only four vectors to control the real and the reactive power at every sampling period. The proposed MPDPC method using only the four preselected vectors stops switching operation of one leg exposed to the largest input current at every sampling period. On the basis of the preselected vectors at each sampling period, the proposed method can effectively reduce the switching losses, as well as accurately perform power control of the active rectifier.

Powertrain of an electric vehicle (EV) is a compound system with an electrical sub-system, such as batteries, inverters, and electrical motors, as well as a mechanical sub-system, including transmissions, differential, and wheels. Since the electrical systems directly affect the vehicle driving performance and dynamics of an EV, integrated modeling considering both the mechanical and electrical systems is essential to assess ultimate kinetic and dynamic characteristics of an EV in terms of input electrical quantities. In this paper, an entire analytic model for the powertrain of EVs is developed to describe EV dynamics with respect to electrical signals, in consideration of both mechanical and electrical systems. Theoretical models based on mathematical expressions, combining the mechanical power system and the electrical power systems, are derived for predicting the final vehicle driving performance as a function of electrical quantities. In addition, a Matlab model of an EV is developed to verify the derived mathematical analysis model. Based on the theoretical model of the powertrain, a variety of relationships between electrical quantities and vehicle dynamics, such as velocity, acceleration, and forces of the EVs, are finally investigated and analyzed.

In this paper, the virtual space vector modulation for the AC&ndash, DC (alternating current&ndash, direct current) matrix converters is proposed to reduce the DC current ripples in the whole modulation index range. In the proposed method, each virtual vector is synthesized by the two nearest original active vectors. To synthesize the current reference vector, two virtual vectors and one zero vector are used in every switching period. The main principle of the proposed method is to reduce the dwelling period of the largest active current vector in each sector. In addition, the optimized switching patterns are proposed to further reduce the DC current ripples at both high- and low-power operation. Finally, simulation and experimental results are illustrated to validate the effectiveness of the proposed strategy.

In this paper, a comprehensive double-vector approach is proposed to alleviate the common-mode voltage of voltage-source inverters based on a model predictive control scheme. Only six active vectors are selected to alleviate the common-mode voltage. Furthermore, one sampling period must be split to apply two non-zero vectors, which can generate currents with small current ripples and errors, despite not using zero vectors. The developed algorithm regards in full all 36 possible cases combined by two non-zero active vectors when selecting two vectors and splitting them into one sampling period. Thus, an optimal future set of two non-zero active vectors and optimal durations of two non-zero active vectors to produce the smallest current errors between the real currents and the reference in future load current trajectories were selected from 36 entire sets. This was done to minimize the cost function defined at the time when it varies from the first vector to the second vector and at the next sampling instant. Thus, the proposed algorithm can control the output currents with a fast transient response and reduce output-current ripples and errors, as well as alleviate the common-mode voltage to &plusmn, V d c / 6 .

A cost-effective and high-efficiency driver is proposed for plasma display panels (PDPs) by eliminating switching devices with high current ratings. The proposed driver is based on a neutral -point clamped inverter structure, and the path switches can be eliminated without reducing the flexibility in designing driving waveforms. Moreover, the LC resonant operation during the sustain period can be constructed with only unidirectional diodes in aid of the switching scan IC devices. Thus, the proposed driver can produce a PDP driving waveform with no path switches as well as no resonant switches. Since the path switches and the resonant switches are practically implemented with several semiconductor devices in parallel due to high gas-discharge and capacitor displacement current, the proposed driver can considerably simplify the overall driver with fewer semiconductor devices. Additionally, high conduction losses from the path switches and the resonant switches with high current loading can be eliminated in the proposed driver, leading to higher efficiency. The developed driver also places the clamping diodes to recover the inductive energy trapped in the resonant inductors due to the inevitable diode reverse-recovery phenomena.

In this paper, design and performance analysis of robust and inexpensive permanent magnet-assisted synchronous reluctance generators (PMa-SynRG) for tactical and commercial generator sets is studied. More specifically, the optimal design approach is investigated for minimizing volume and maximizing performance for the portable generator. In order to find optimized PMa-SynRG, stator winding configurations and rotor structures are analyzed using the lumped parameter model (LPM). After comparisons of stator windings and rotor structure by LPM, the selected stator winding and rotor structure are optimized using a differential evolution strategy (DES). Finally, output performances are verified by finite element analysis (FEA) and experimental tests. This design process is developed for the optimized design of PMa-SynRG to achieve minimum magnet and machine volume as well as maximum efficiency simultaneously.

A plasma display panel (PDP) driver with dissymmetric energy transfer speed is designed to obtain fast voltage transition during the up-commutation period and improved efficiency during the down-commutation period. The proposed driver configures the sustain circuit and the resonant circuit in such a way that the resonant network is energized by the sustain voltage level and the half sustain voltage level in charging and discharging the panel capacitor, respectively. The energy transferred into the panel from the power supply is twice as fast as the conventional Weber-type driver biased by half sustain voltage level, for improved image quality and display resolution. The proposed driver, on the other hand, recovers the panel energy using the resonant circuit with the half sustain voltage and increased inductance, leading to enhanced energy recovery. Moreover, the proposed driver is supplied from half of required sustain voltage level. As a result, the proposed driver can be designed by devices with reduced voltage rating compared with the conventional Weber-type driver. Therefore, the PDP driver presented in this paper can feature faster sustain voltage transition, higher brightness, uniform images, low-voltage power supply, low-voltage-rating switching devices, and high efficiency.

A low-cost driving system for plasma display panels (PDPs) is proposed from standpoints of the entire driver. The proposed driving system is developed with no path switches, based on the series connection of the ramp-generating switches with the sustain circuit. In addition, the proposed driver is arranged in such a way that the scan integrated circuits (ICs) can be utilized with switching operation during sustain periods. The operation of the switching scan ICs results in a simplified sustain circuit with low-cost and low-voltage-rating circuit components. Since the proposed driver is designed by circuit devices with low voltage rating, it can take advantages of semiconductor devices with reduced conduction and switching losses as well as cost effectiveness. Furthermore, the developed driving system requires no power supply assigned to the bias circuit, and parts of the sustain circuit can be used for the bias circuit as well. As a result, the PDP driving system presented in this paper can feature low-cost structure, reduced number of switching devices, smaller size, and high efficiency.

This paper presents a new approach to analyze the stator inter-turn fault of a brushless dc motor. It is essential to analyze the behavior of the machine under internal faults and design appropriate protection systems to avoid expensive failures that might occur to the machine in the near future. The winding functions and inductance change of stator windings under internal faults are explained in detail, and the informative simulation results, based on the winding function theory, are provided to analyze a current's abnormalities and torque pulsation under turn-to-turn faults. To verify the proposed analysis, the stator current, back-electromotive force, and resultant torque waveforms for both healthy and faulty machines are presented, utilizing both the finite-element method (FEM) and computer simulation based on dynamic equations. Finally, experimental results present the actual behavior under the stator faults. The detailed simulation and experimental results will be the guideline for early detection of internal failures in brushless dc motors.

This paper proposes a model predictive current control (MPCC) method utilizing two output voltages with variable application durations in one sampling period, to control output currents of single-phase voltage source inverters (VSIs). In the proposed method, application durations of the two voltages as well as selection of two output voltages used in the future sampling period are determined by an optimization process, to minimize current error inside the future sampling period and to eliminate current error at the end of the future sampling instant.

A multilevel power-converter topology based on two types of current-source inverters (CSIs) has been proposed for large induction motor drives. The topology utilizes the combination of the load-commutated inverter (LCI) using thyristors and the CSI using gate turn-off thyristors (GTOs). As a result, the multilevel-inverter operation takes advantage of a soft switching of the LCI and hard switching of the CSI. The output capacitor is required to generate the leading power factor for load commutation of the LCI. It is shown that the proposed multilevel operation contributes to the leading-power-factor generation by providing the effective phase shift. Thus, the leading power factor required for the load commutation of the LCI is obtained with significantly smaller capacitors at the inverter's output terminals. As a result, the proposed approach can employ the LCI and utilize its soft-switching operation, yielding a cost-effective solution compared with the conventional multilevel CSI using two GTO CSIs. The switching losses are curtailed due to the natural commutation of the LCI and the six-step operation of the GTO CSI. Therefore, the proposed multilevel inverter can both increase the output power level and decrease the output capacitor size for LCI. The simulation and experimental results have been shown to verify the feasibility of the proposed multilevel topology and its operation

A thyristor-based current-source inverter (CSI) is proposed, employing a standalone voltage-source inverter (VSI) with a small power rating. The VSI, as an external circuit of the CSI, performs three tasks: 1) turning off of thyristors; 2) transfer of reactive load energy; and 3) clamping peak voltages across the load and thyristors. In comparison with conventional thyristor-based CSIs requiring large ac commutation capacitors as well as individual energy recovery and voltage clamping circuits, the proposed CSI system can replace all the complicated auxiliary circuits and bulky ac capacitors with the small VSI. Furthermore, the proposed CSI ensures simple and easy control of the commutation process due to the simple switching operation of the VSI. The VSI operates only during the commutation periods of the load currents and stops working in the noncommutation periods. Thus, the VSI with small power rating can be used for the proposed CSI system. The feasibility of the proposed CSI system is verified by simulation and experimental results

A hybrid converter system employing a combination of a load-commutated inverter (LCI), a dc-dc buck converter, and a voltage-source inverter (VSI) is proposed for the large induction motor drives. The VSI ensures the safe commutation of the LCI with active commutation angle control over all speed regions. By replacing capacitor banks and a forced dc-commutation circuit, this system can eliminate all drawbacks related to these circuits in the conventional LCI-based induction motor drives. Sinusoidal motor current and voltage waveforms are achieved with the VSI providing the reactive and harmonic power to the motor, resulting in high-performance drives. The buck converter enables both the VSI and the LCI to be fed from the single-diode rectifier. As a result, the dc-link inductor size can be reduced and the LCI is operated without the controlled rectifier. In addition, faster dynamic response can be obtained through the VSI and the buck converter operation. Finally, the buck converter performs the dc-link current control to ensure minimum VSI rating. The feasibility of the proposed hybrid circuit for the high-power drive systems is verified by computer simulation for a 500-hp induction motor. Experimental results are also included for a 1-hp induction motor laboratory setup controlled by the proposed hybrid system.