This paper presents a novel Hall sensor–based methodology capable of simultaneously measuring rotary and translational positions for magnetic levitation systems and robotic joints. The sensing structure employs twelve low-cost Hall-effect sensors, arranged as four sets of three-phase sensors, to measure the radial magnetic flux generated by permanent magnets mounted on the moving part. By strategically placing the sensors in radial symmetry, differential information among the sensor sets is utilized to extract bothx–ytranslational displacements and the rotary angleθr. The proposed algorithm estimates positions using only simple addition and multiplication operations, with minimal signal filtering applied solely for noise suppression, resulting in nearly negligible phase delay. Using zero-sequence components derived from Clarke transformation, the method enables fast and accurate estimation of all three position components. The fabricated prototype achieves a rotary range of 0 to 2π and a translational range of ±3 mm along bothx- andy-axes, while maintaining a compact and low-cost configuration suitable for integrated multi-axis position sensing.

This article proposes a novel resonator structure for wireless power transfer (WPT) in autonomous vehicle seat applications. The proposed WPT system employs helical coils for both the transmitter and receiver (RX), achieving a high coupling coefficient exceeding 0.5 across a substantial RX movement range. To mitigate the complexity of the system due to RX movement, an$M$-uniform resonator with unequal turn spacing was developed using a genetic algorithm based on theoretical analysis. While the RX was moving, the proposed$M$-uniform resonator reduced the receiving-side voltage and current variations to 5.8% and 4.4%, respectively. This represents a significant improvement over the 34.1% and 37.0% observed in conventional coil designs with equal turn spacing. Additionally, the proposed system maintained a total system efficiency above 85% over the entire RX movement range, demonstrating its suitability for dynamic WPT applications without the need for RX position detection systems. In conclusion, the proposed resonator overcomes the tangling and reliability issues of traditional power cables, enabling flexible seat movement in future autonomous vehicles to optimize their interior space.

This paper presents a novel Hall sensor–based methodology capable of simultaneously measuring rotary and translational positions for magnetic levitation systems and robotic joints. The sensing structure employs twelve low-cost Hall-effect sensors, arranged as four sets of three-phase sensors, to measure the radial magnetic flux generated by permanent magnets mounted on the moving part. By strategically placing the sensors in radial symmetry, differential information among the sensor sets is utilized to extract bothx–ytranslational displacements and the rotary angleθr. The proposed algorithm estimates positions using only simple addition and multiplication operations, with minimal signal filtering applied solely for noise suppression, resulting in nearly negligible phase delay. Using zero-sequence components derived from Clarke transformation, the method enables fast and accurate estimation of all three position components. The fabricated prototype achieves a rotary range of 0 to 2π and a translational range of ±3 mm along bothx- andy-axes, while maintaining a compact and low-cost configuration suitable for integrated multi-axis position sensing.

This article proposes a novel resonator structure for wireless power transfer (WPT) in autonomous vehicle seat applications. The proposed WPT system employs helical coils for both the transmitter and receiver (RX), achieving a high coupling coefficient exceeding 0.5 across a substantial RX movement range. To mitigate the complexity of the system due to RX movement, an$M$-uniform resonator with unequal turn spacing was developed using a genetic algorithm based on theoretical analysis. While the RX was moving, the proposed$M$-uniform resonator reduced the receiving-side voltage and current variations to 5.8% and 4.4%, respectively. This represents a significant improvement over the 34.1% and 37.0% observed in conventional coil designs with equal turn spacing. Additionally, the proposed system maintained a total system efficiency above 85% over the entire RX movement range, demonstrating its suitability for dynamic WPT applications without the need for RX position detection systems. In conclusion, the proposed resonator overcomes the tangling and reliability issues of traditional power cables, enabling flexible seat movement in future autonomous vehicles to optimize their interior space.

Self-bearing machines do not contain physical bearings but magnetic bearings. Both rotor rotary and spatial positions displacement are required in these types of machines to control the rotor position while it is levitating. Self-bearing machines often use external sensors for x (horizontal) and y (vertical) spatial position measurement, which will result in additional cost, volume, complexity, and number of parts susceptible to failure. To overcome these issues, this paper proposes a xy-position estimation self-sensing technique based on both main- and cross-inductance variation. The proposed method estimates x and y position based on inductive saliency between two sets of three-phase coils. The proposed idea is applied on a combined winding self-bearing machine which does not require additional suspension force winding. No additional search coil placement for xy-position estimation is required. Therefore, the proposed algorithm can result in a compact size self-bearing machine that does not require external sensors for xy-position measurement and suspension force winding.

This study proposes a real-time methodology for estimating the energy efficiency of battery-powered motor drive systems under dynamic conditions. Instantaneous power estimation can be distorted by energy storage components-such as capacitors, inductors, and the moment of inertia-combined with position-dependent effects. To address this, physics-based models of each storage component are developed to compute energy flows at the component level, including the battery, inverter, and motor. The method further incorporates variations in driver input commands, enabling stable and accurate efficiency measurements even during transient operations. The proposed approach can also be extended to support component-level loss analysis and separation, fault diagnosis, and prognostics and health management (PHM) techniques.

Stepper motors are widely employed in equipment requiring indexing motion due to their simple control scheme and low cost compared to three-phase permanent-magnet (PM) servo machines. However, due to the inherent characteristics of stepper motor control in which step commands are applied, rapid movement toward a target position can cause overshoot, leading to a trade-off that increases the settling time. To address this issue, a field-oriented control (FOC) method has been proposed that drives a stepper motor in a manner similar to a synchronous machine. Nevertheless, since it employs outer loops for speed and position control, it cannot fully exploit the inherent advantage of stepper motors-namely, the ability to achieve position control without accumulated error using only a current controller, which enables a high control bandwidth. Therefore, this paper presents a motion control algorithm for hybrid stepper motors that utilizes active damping and state-feedback decoupling along with step current commands to enable fast and repetitive single-step angle positioning. These features make it particularly suitable for applications such as MLCC (Multi-Layer Ceramic Capacitor) inspection equipment, where camera-based inspection must be performed as quickly as possible through precise indexing motion.

We propose a method for rapid prototyping of a three-phase AC drive system for educational purposes. The proposed method allows college students to design and manufacture a drive system comprising three-phase inverters, a permanent-magnet (PM) machine, a controller, and sensors within a semester. The rapid prototyping process, which requires less than a day, enables efficient iteration and testing during the development process. In addition to addressing the electrical design considerations, this study also addresses the mechanical aspects of the drive system, including the use of coreless PM machines fabricated, using additive manufacturing technology, and the inverter manufacturing process, utilizing an auto-milling machine. Finally, we provide details of the rapid prototyping of closed-loop control, based on sensor feedback to regulate the rotating magnetic fields and output torque.

The efficient design optimization of electric machines for electric power steering (EPS) applications poses challenges in meeting demanding performance criteria, including high power density, efficiency, and low vibration. Traditional optimization approaches often fail to find a global solution or suffer from excessive computation time. In response to the limitations of traditional approaches, this paper introduces a novel methodology by incorporating a Gaussian process-based adaptive sampling technique into a surrogate-assisted optimization process using a metaheuristic algorithm. Validation on a 72-slot/8-pole interior permanent magnet (IPM) machine demonstrates the superiority of the proposed approach, showcasing improved exploitation–exploration balance, faster convergence, and enhanced repeatability compared to conventional optimization methods. The proposed design process is then applied to two surface PM (SPM) machine configurations with 9-slot/6-pole and 12-slot/10-pole combinations for EPS applications. The results indicate that the 12-slot/10-pole SPM design surpasses the alternative design in torque density, efficiency, cogging torque, torque ripple, and manufacturability.

The imbalance between the supply and demand of electricity is becoming expansive due to the increase in renewable energy penetration. Consequently, the time-varying electricity price is proposed as a tool to manage the mismatch. To cope with the electricity price difference across time and to extract the benefit to the limit, an energy storage system (ESS) can be a good tool to smooth out electricity usage. Nevertheless, ESS can be expensive due to the high installation cost and centrally managed system. In this paper, we propose a distributed ESS installed in each home appliance. Separately installed batteries can avoid sizeable initial investment costs. We calculated the benefit of the system that mainly stemmed from the electricity price difference and compared the benefits across various sizes of the battery system. In addition, the charging/discharging schedule depends on the power consumption profile and electricity price distribution. Decreasing battery prices and rising electricity price volatility can increase the system’s potential benefit.

The second-order generalized integrator based orthogonal signal generator (SOGI-OSG) is commonly used to produce direct and quadrature axis ( dq-axes) signals in stationary reference frame for single-phase systems. Fast and robust OSG with harmonic rejection capability is required for parallel operation of power generation systems. The frequency response function (FRF) of classical OSG does not show robustness towards DC offset and grid harmonic disturbances compared to the direct signal of SOGI. This paper presents OSGs based on nthorder bandpass filter with a phase shifter using a scaled Q factor as a design variable. The frequency and time-domain performance analysis will be performed based on the scaled Q factor to simplify the design process of the proposed OSGs. The -3dB frequency and settling step time will be matched in higher order OSGs selecting a scaled Q factor. The proposed method will show enhanced harmonic rejection ratio of an additional -20dB with increasing OSG order with tradeoff in computational burden.