As various industrial fields electrified, the demands for high power capability and high-performance techniques for electric drive systems continue to increase. Several topologies of drive systems with state-of-the-art processors have been introduced and researched. In this context, this paper presents a comprehensive review on emerging techniques of power enhancement methods and intelligent drive techniques. In the conventional drive system fed by a voltage source inverter, the maximum output power of the motor drive systems is limited by the dc-link voltage. Primarily, the dc-link voltage has been increased either with voltage boosting or higher voltage batteries. However, topologies that enable higher voltage to be generated on the machine with the same dc-link voltage, such as a resonant or dual-inverter drive, have been introduced. This paper categorizes and reviews the power capability characteristics of different topologies. In the field of drive intelligence, many studies are being conducted through the improvement of digital signal processors (DSPs) and tools for data-driven modeling. These studies include intelligent control methods to improve real-time control performance and intelligent monitoring methods to ensure system stability. In more detail, the review section on drive intelligence covers i) the parameter mapping-based control method, ii) the machine learning-based control method, and iii) the data-driven system monitoring method.

Nissan developed LEAF as a mass-produced electric vehicle (EV) in 2010 and has been continuously improving it ever since. In 2016, Nissan also developed NOTE with e-POWER, a 100% motor-driven system, thus delivering excellent 100% motor-driven experience to customers. This paper describes the evolution of the motor and inverter the key components that support Nissan's 100% motor-driven system.

In this paper, a control method is proposed for a bidirectional isolated three-phase AC/DC Dual Active Bridge (DAB) converter based on a matrix converter (MC) that realizes a wide output voltage range. The proposed method achieves the reduction of excessive high frequency link currents and soft switching with online calculation by changing two modulation methods according to the input and output voltage ratio. Moreover, the proposed method realizes higher efficiency in the expanded output voltage range with reduced online calculation burden. The feasibility and validity of the proposed method are verified by experimental demonstration.

Concern about rainfall increase due to climate change and other factors is growing, inexpensive and easy-to-use rainfall forecasting methods are required. Therefore, this study developed a rainfall forecasting model using a neural network that uses readily available weather information such as cloud images, precipitation, and humidity. The proposed model achieved 89% accuracy for 24-hour-ahead classification, exceeding the 85% accuracy of the Japan Meteorological Agency (JMA). In addition, by focusing on the seasonality of weather and introducing time information into the forecast model, the stability of the forecast was improved. Finally, a rainfall forecast model was developed and simulated by applying AdaBelief to EfficientNetV2+Bi-LSTM. Consequently, the accuracy of both 2-hour and 24-hour-forecasts exceeded the forecast precision of the previous study and the JMA. In particular, the 24-hour-ahead rainfall forecast precision was improved by more than 10% compared to the previous research, indicating a significant improvement in precision.

Robust stable feedback (FB) controller design considering plant perturbation is crucial in industrial servo systems. However, because the controller parameter design generally requires expert skills and/or considerable labor for engineers, autonomous design technology would be promising. This study presents an efficient autonomous design method that optimizes the parameters of a cascade structure FB controller realizing robust stabilization. The proposed method improves the parameter optimization efficiency compared to that of a conventional method by identifying and eliminating inactive stability constraints. The effectiveness of the proposed method is evaluated through simulating of an example FB controller design for a laboratory galvanometer scanner.

A large-scale multiport converter based on the modular multilevel converter (MMC) architecture for charging electric vehicles (EVs) can reduce the volume and installation costs compared to those of conventional multiport converters. It has been pointed out that the multiport converter requires additional circulating current (intra-arm balancing current) to ensure both a balanced grid current and power distribution to the cells under large power unbalance among the cells in one arm. However, a control strategy of the intra-arm balancing current has not been discussed enough in the past. This paper proposes an online minimization control of the intra-arm balancing current. The proposed controller minimizes the intra-arm balancing current with capacitor voltage feedback and a PI controller. In addition, an adaptive observer is installed to adjust the controller gain, which realizes a fast response and stability under all loaded conditions. Experimental results verify that the proposed controller ensures a grid current with low total harmonic distortion of 3.1% and capacitor voltage balancing with minimum intra-arm balancing current exhibiting an error of 4.5% from the theoretical value under the largest power unbalance of 1p.u. among the cells.

Brushes enable the transfer of electrical current between stationary and moving conductors. Typical contacting components are a brush and commutator in direct-current machines and a brush and slip ring in alternating-current machines. In recent years, Ag-graphite brushes and noble-metal-coated slip rings have often been applied. However, there are many aspects concerning the sliding contact of these components that require clarification. This paper focuses on characteristics relating to the brush wear and contact voltage drop of Ag-graphite brushes when the Ag content is varied for a Au-plated slip ring. In this study, we conducted sliding tests, using Ag-graphite brushes (coated with Ag contents of 50, 60, 70, 80, and 90wt%) and a Au-coated slip ring. The results showed the effects of the interposing layer on the brush wear and drop in contact voltage. In particular, there were three distinct compositional zones, namely a zone where the effect of graphite was dominant (Ag content of the brush of 50wt%), a zone where both the graphite and Ag powder had influence (60-80wt%), and a zone where the effect of Ag powder was dominant (90wt%).

This study demonstrates that a proportional-integral (PI) controller in the constant DC-capacitor voltage control (CDCVC) block of a four-leg active power-line conditioner (APLC) in three-phase four-wire distribution feeders (TPFWDFs) accurately calculates the root-mean-square (RMS) value of the fundamental active currents in the feeder currents, using simulation and experimental results. The accuracy of the RMS value calculated by the PI controller in the CDCVC block is crucial because the reference signals for the source currents are calculated using the RMS value calculated in a previously proposed CDCVC-based strategy for the four-leg APLC in TPFWDFs. In this study, the previously proposed CDCVC-based strategy is modified by adding an algorithm for calculating the fundamental active currents in the feeder currents. The basic principle of the modified CDCVC-based strategy is discussed in detail and confirmed by digital computer simulations using a power electronics simulator (PSIM). A scaled-down experimental set-up is developed and examined. The simulation and experimental results demonstrate that the PI controller in the CDCVC block of the four-leg APLC accurately calculates the RMS value of the fundamental active currents in the load currents. Therefore, it is concluded that the previously proposed CDCVC-based strategy for a four-leg APLC is applicable to the four-leg APLCs in practical TPFWDFs.

The high-electromagnetic-interference (EMI)-noise area in a power circuit should be clarified when designing a low-EMI-noise power converter. For example, shielding of the power circuit prevents the EMI noise propagation to other circuits via near field couplings. It is important to know the high-EMI-noise area which should be shielded. The EMI noise distribution can be visualized by measuring the near-magnetic-field distribution above the power circuit. However, we cannot measure the near-magnetic-field distribution if there is not enough space for scanning a magnetic field probe between the power circuit and other circuits. Therefore, we propose to adopt a three-dimensional electromagnetic simulation for acquiring the near-magnetic-field distribution above a power circuit. In this paper, we study the validity of the frequency-domain noise-source model for the simulation of the near-magnetic field distribution. We evaluate the near-magnetic-field distribution maps for turn-on and turn-off of the transistor, respectively. The high-EMI-noise area differs depending on frequencies. The high-EMI-noise area for turn-on is different from that for turn-off. We have clarified that each high-EMI-noise area can be predicted by the simulation.

This paper presents a surrogate modeling technology and the application using the response surface methodology (RSM) for a half-wave rectified brushless synchronous motor (HRSM) for model-based design. HRSM adopts a field winding that is single-phase short-circuited through a diode, instead of a brush at the rotor. This brushless excitation facilitates the maintenance of the motor and variable field flux operation. However, creating a high accuracy motor model for model-based design using HRSM considering field current characteristics with the effects of the diode is difficult, and the problem of an unrealistic complex calculation for applications such as drive cycle simulations exists. To overcome these challenges, we propose a surrogate modeling technique for HRSM using RSM and finite element analysis. The objective of this study is achieve the fast and accurate simulation to predict the wide range and long-time driving conditions of HRSM, which is difficult to validate experimentally.

In this study, we focused on detecting seat belts of drivers from camera images of the front windshield area of cars. When the color of the seat belt differs from that of the clothing worn by the driver, the seat belt can be detected by focusing on edge and pixel value differences. This study created a template representing pixel value differences and applied template matching using a genetic algorithm to achieve higher detection rates than edge-based methods. To quantitatively evaluate the performance, we created a dataset consisting of 73 images and compared the performances of each method. Notably, the proposed method achieved higher detection rates than the other methods.

This study presents a method that displays selectively-blurred images to users wearing a VR Head Mount Display (HMD), for reducing their VR sickness while maintaining rich-presence they feel as much as possible. Our proposed method blurs displayed images selectively based on a specific length and direction of optical flow at each point in the image to not only reduce the VR sickness but also preserve the original rich-presence of the displayed images. The optical flow direction of each point is opposite to that of the whole image, such areas are not blurred in our proposed method. Our proposed method was verified via two types of experiments, the results proved that our method is effective appropriately for both VR sickness reduction and rich-presence preservation.

In recent years, applying SiC to switching devices of traction inverters has been attracting attention. By applying SiC devices, motors are able to increase the regenerative energy and reduce the power consumption by shortening powering time due to improved motor torque performance by driving motors with the larger current than the case of an Si-IGBT inverter. In this study, the trade-off relationships between increasing the loss of inverters and the effect of saving-energy are quantitatively studied by numerical simulations, assuming that SiC devices are applied for 1.5kV DC railway vehicle traction inverters.

The flux-modulating consequent pole motor (FCM) is a new type of variable-flux permanent magnet (PM) motor with a field winding on the stator. The magnetic poles of the rotor are consequent poles containing PM and iron poles. In this paper, the cross-coupling effects between d- and q-axes on the torque characteristics are analyzed for each MMF source when the permeability distribution in the FCM is frozen under each operating condition. Experimental results of a prototype machine are provided to justify the analysis. The results show that the cross-coupling effects between d- and q-axes can be reduced by appropriately designing the shape of the iron poles.

A bidirectional onboard DC/DC converter that can be used to rapidly charge an electric vehicle (EV) or feed EV battery power to a DC microgrid based on application requirements is proposed. This system concept is labeled as an onboard fast battery charging EV (cEV). Interestingly, owing to the presence of the inbuilt quick EV charger, external high power chargers are not required for fast charging applications. The proposed autonomous control strategy may also aid in DC grid voltage stabilization within the permissible range of 360V to 400V when power is being transferred from a PV to DC bus by controlling the DC/DC converter for PV and the DC multi power unit (DCMPU) independently. The DCMPU can also control both the power or DC bus voltage based on system requirements. Next, a droop-based control is implemented in the DCMPU to avoid mutual interference in the controllers. Detailed simulation studies are performed in MATLAB/Simulink to demonstrate the effectiveness of the proposed system. Overall, the proposed system helps maintain DC bus voltage fluctuations within a permissible range.