Gyu Cheol Lim

In saliency-based sensorless control with switching frequency voltage injection, the accuracy of rotor position estimation is deteriorated by the injected voltage errors arising from pulsewidth modulation (PWM). To resolve this issue, current derivatives within an active voltage vector are employed for precise position estimation. Accurate measurement of current derivatives requires a sufficient active vector time, necessitating additional voltage injection in low-speed regions. Considering the increased losses from additional injection, this article proposes two types of voltage injection methods that ensure only the minimum active vector time without modifying the PWM scheme. In the proposed methods, the magnitude and direction of injected voltages are analytically determined by considering the angle between the injected and fundamental voltages. Consequently, the proposed injection methods reliably ensure the minimum active vector time regardless of the load conditions, thereby improving the position estimation accuracy. Experimental results under various operating conditions verify the effectiveness of the proposed methods.

This study introduces a data-driven approach for diagnosing faults in electric drive systems on embedded systems. The method is designed to diagnose current hall sensor offset, scale errors, and power switch open faults without the need for additional sensors or external computing resources. The proposed approach addresses three key points. Firstly, it identifies and suggests data types in electric drive systems that are rich in fault-related information. Additionally, it uses statistical analysis to propose an effective fusion method for the input data types to create a diagnostic model among the various candidates. Secondly, a down-sampling method utilizing average pooling is introduced to effectively sample data from the large volume of raw data processed by the digital signal processor (DSP), preserving essential information while reducing data size. Lastly, a diagnostic scheme employing a neural network-based classifier is proposed to accurately diagnose faults using the down-sampled data. The proposed method’s effectiveness, from sampling to diagnosis, is demonstrated through both analytical and statistical validation. Furthermore, real-time diagnostic results are presented using the TMS320F28379S DSP.

Recently, the battery voltage of electric vehicles (EVs) has almost doubled for faster charging. However, it is difficult to charge these EVs with existing low-voltage fast chargers. To solve this issue, boost charging topology using the motor drive system has been introduced and applied to commercial EVs. These motor-integrated chargers are controlled as three-phase interleaved boost converters. Since they use low-zero-sequence inductance for boosting, they could generate larger ripple currents and higher losses. This article analyzes the losses and finds a solution for increasing the charging efficiency and eliminating the torque to avoid rotation. Unlike the conventional method using the zero-sequence inductance, it considers the differential-mode inductance by two-phase conduction of the motor. This results in a significant reduction in current ripple, improving the efficiency. In addition, a position controller is proposed to suppress the rotation explicitly. The feasibility of this work is theoretically assessed, and the experimental results conducted in the reduced scale setup demonstrate the effectiveness of the proposed strategy.

Voltage source inverters (VSIs) are widely used in electric vehicle due to their high control performance and efficiency in electric motor drive systems. However, the output voltage of the inverter during switching instances generates bearing currents, leading to bearing damage. This article analyzes the relationship between bearing currents and bearing damage, and proposes a new method for reducing bearing currents. First, a precise bearing current measurement system using a current transformer is introduced. This system verifies the phenomenon of bearing damage caused by bearing currents at low speeds. Fourier transform analysis of audio signals from bearings is employed to confirm this phenomenon. Subsequently, a two-phase pulse-width modulation (PWM) method that considers the saliency of interior permanent magnet synchronous machines (IPMSMs) and a capacitive filter topology is presented. The proposed method is validated through experimental results in a commercial electric vehicle drive system. As a result, the bearing current is reduced by 91% compared to that of space vector PWM (SVPWM) method.

In capacitive power transfer systems, coupling variation inevitably occurs due to air gap variation and coupler misalignment. This paper presents a single-sided compensation network design method for capacitive power transfer systems considering coupling variation. The proposed method adopts a single-sided compensation network to reduce the volume and weight of the receiver side circuit. The proposed compensation network, within a preselected narrow operational frequency range, effectively transforms the variable load impedance into a single resistive point, resulting in constant output power and zero-phase angle operation under coupling variation. The proposed method employs the impedance matching network design based on a twoport network analysis. The validity of the proposed design method is confirmed with a simulation and a 1.2 kW small air gap capacitive power transfer system prototype. The experimental prototype system achieved a maximum efficiency of 91.2% under no misalignment and a minimum efficiency of 89.9% under a maximum 40% area displacement in coupling conductor plates, with a near-constant output power and zero-phase angle operation

Position sensorless drive with single current sensor (SD-SCS) is widely utilized in cost-effective applications. The drive performance of saliency-based SD-SCS can be easily deteriorated due to several reasons: inaccurate phase current reconstruction (PCR) and the interference in injected voltages for the PCR and position estimation. Here, this article proposes an enhanced sensorless control strategy employing six-vertex voltage injection for PCR and position estimation. First, the parameter dependency in position estimation is eliminated by using the current derivative measurements at six active vectors. In addition, by modifying the sequence of voltage vectors, the proposed pulsewidth modulation scheme reduces the current ripple caused by the injected voltages. Experimental results verify that the proposed method shows high accuracy of position estimation and significantly reduces the total harmonic distortion of the phase current in SD-SCS, making it comparable to that of a position-sensored drive.

The six-step operation is widely used with its advantages in voltage utilization increased by 10.27% without boost circuits. However, the six-step operation causes nonideal low-order harmonics in the currents due to the uneven ratio between the sampling frequency and the fundamental one. Moreover, transitioning between pulsewidth modulation and the six-step operation needs consideration of factors such as current shocks and parameter dependencies in voltage limit conditions. The proposed overmodulation method facilitates a seamless transition to the six-step operation while maintaining the closed-loop current regulator. Furthermore, the nonideal low-order current harmonics are eliminated through a variable time step control. The proposed method achieves a reduced number of switchings by utilizing edge voltage vectors. In addition, the current ripple is reduced by solving a minimization problem targeting the weighted total harmonic distortion of the phase voltage.

In vector-controlled drive systems, a position sensorless drive with a single current sensor (SD-SCS) is an attractive system due to the minimum number of sensors. However, when the saliency-based SD-SCS is applied, the position estimation accuracy is deteriorated due to the errors in the injected pulsewidth-modulated voltage and the reconstructed current. This article proposes a current-derivative-based sensorless control using a three active vector pulsewidth modulation (TAVPWM) to enhance the saliency-based SD-SCS. First, the TAVPWM scheme, which eliminates the current reconstruction dead zone in the low-modulation region, is adopted to improve the low-speed drive. Next, the derivatives of the phase currents are utilized and analyzed to minimize the position estimation error in the overall operating regions. Finally, the transition strategy with respect to the speed is proposed for the full-speed sensorless drive. Owing to the proposed method, the switching frequency increases up to 16 kHz and the audible noise is virtually eliminated in the saliency-based SD-SCS. Furthermore, the enhanced dynamic performance is verified by various experimental results.