Design and Experimental Analysis of a Medium-Frequency Transformer for Solid-State Transformer Applications M. Leibl, G. Ortiz, J. W. Kolar

IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN POWER ELECTRONICS, VOL. 5, NO. 1, MARCH 2017 

Design and Experimental Analysis of a Medium-Frequency Transformer for Solid-State Transformer Applications Michael Leibl, Member, IEEE, Gabriel Ortiz, Member, IEEE, and Johann W. Kolar, Fellow, IEEE 

 Abstract— Within a solid-state transformer, the isolated dc–dc converter and in particular its medium-frequency transformer are one of the critical components, as it provides the required isolation between primary and secondary sides and the voltage conversion typically necessary for the operation of the system. A comprehensive optimization procedure is required to find a transformer design that maximizes power density and efficiency within the available degrees of freedom while complying with material limits, such as temperature, flux density, and dielectric strength as well as outer dimension limits. This paper presents an optimization routine and its underlying loss and thermal models, which are used to design a 166 kW/20 kHz transformer prototype achieving 99.4% efficiency at a power density of 44 kW/dm3. Extensive measurements are performed on the constructed prototype in order to measure core and winding losses and to investigate the current distribution within the litz wire and the flux sharing between the cores.

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Fast Charging, State of Charge Estimation, and Remaining Useful Life Prediction of Lithium-Ion Battery for Smart Battery Management System = 스마트 배터리 관리 시스템을 위한 리튬 이온 배터리의 급속충전, 충전 상태 및 잔여 수명 예측

 

Dissertation for the degree of Doctor of Philosophy Fast Charging, State of Charge Estimation, and Remaining Useful Life Prediction of Lithium-Ion Battery for Smart Battery Management System]

 BY Muhammad Umair Ali-February 2020

 Department of Electrical and Computer Engineering The Graduate School Pusan National University 

 ABSTRACT 

Due to the escalation in environmental pollution and energy prices, electric vehicles (EVs) have widely explored in the past few years. Battery electric vehicles (BEVs), plug-in hybrid electric vehicles (PHEVs), and fuel cell electric vehicles (FCEVs) are the different variants of EVs. These EVs consist of energy storage and the motor system as the auxiliary or primary energy source (FCEVs and PHEVs) or the sole energy source (BEVs). The lithium-ion (Li-ion) batteries are preferred as an energy storage system because of its longlife cycle, reliability, high energy density, low toxicity, low self-discharge rate, high power density, and high efficiency. In EVs, a smart battery management system (BMS) is one of the essential components; it not only measures the states of battery accurately but also ensures safe charging/discharging operation and prolongs the battery life. The issues of accurate estimation of the state of charge (SOC), remaining useful life prediction (RUL), and reduction in charging time of the Li-ion battery is still a bottleneck for the commercialization of EVs because the Li-ion battery is a highly time-variant, non-linear, and complex electrochemical system. In this dissertation, a novel fuzzy logic and temperature feedback-based method, Lagrange multiplier approach, and partial discharge data (PDD) based support vector machine (SVM) model are presented for reduction of the charging time, SOC estimation, and RUL prediction of the Li-ion battery, respectively. This dissertation comprises of four studies, each of which constitutes a step towards a smarter BMS for EV applications. The first study proposes an efficient, real-time, fastcharging methodology of Li-ion batteries. Fuzzy logic was adopted to drive the charging current trajectory for series-connected Li-ion batteries. The voltage and temperature of the cells were fed to the controller to find the optimal charge current value within the safe temperature limit. A temperature control unit was also implemented to evade the effects of fast charging on the aging mechanism. The proposed method of charging also protects the battery from overvoltage and overheating. Extensive testing and comprehensive analysis were conducted to examine the proposed charging scheme. The results show that the proposed charging strategy favors a full battery recharging in 9.76% less time than the conventional constant-current–constant-voltage (CC/CV) method. The methodology charges the battery at a 99.26% SOC without significant degradation. The entire scheme was implemented in real-time, using Arduino interfaced with MATLABTM Simulink. This decrease in charging time assists in the fast charging of cell phones and notebooks and the large-scale deployment of EVs. The second work presents a new online data-driven battery model identification method, where the battery parameters are updated using the Lagrange multiplier method. A battery model with unknown battery parameters was formulated in such a way that the terminal voltage at an instant time step is a linear combination of the voltages and load current. A cost function was defined to determine the optimal values of the unknown parameters with different data points measured experimentally. The constraints were added in the modified cost function using the Lagrange multiplier method, and the optimal value of the update vector was determined using the gradient approach. An adaptive open-circuit voltage (OCV) and SOC estimator was designed for the Li-ion battery. The experimental results showed that the proposed estimator is highly accurate and robust. The proposed method effectively tracks the time-varying parameters of a battery with high accuracy. During the SOC estimation, the maximum noted error was 1.28%. The convergence speed of the proposed method was only 81 s with a deliberate 100% initial error. Owing to the high accuracy and robustness, the proposed method can be used in the design of a smarter BMS for real-time applications. In the third work, the sensitivity analysis is performed for the first and second-order RC autoregressive exogenous (ARX) battery model to check the influence of voltage and current transducer measurement uncertainty. The sensitivity analysis is performed under the following conditions: Current sensor precision of ±5 mA, ±50 mA, ±100 mA, and ±500 mA and voltage sensor precision of ±1 mV, ±2.5 mV, ±5 mV, and ±10mV. The comparative analysis of both models under the perturbed environment has been carried out. The effects of the sensor’s sensitivity on the different battery structures and complexity are also analyzed. Results show that the voltage and current sensor sensitivity has a significant influence on SOC estimation. This research outcome assists the researcher in selecting the optimal value of sensor accuracy to accurately estimate the SOC of the Li-ion battery for a smarter BMS. In the last work, a novel partial discharge data (PDD) based support vector machine (SVM) model is proposed for RUL prediction. The proposed algorithm extracts the critical features from the voltage and temperature of PDD to train the SVM models. The classification and regression attributes of SVM are utilized to classify and predict accurate RUL. The different ranges of PDD were analyzed to find the optimal range for training the SVM model. The SVM model trained with optimal PDD features classifies the RUL into six different classes for gross estimation, and the support vector regression is used to estimate the accurate value of the last class. The classification and predictive performance of SVM model trained using the full discharge data and PDD are compared. Results show that the SVM classification and regression model trained with PDD features can accurately predict the RUL with low storage pressure on BMS. The PDD-based SVM model can be utilized for online RUL estimation in Li-ion battery BMS.

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전기버스 급속충전기의 PI-IP 혼합 제어기를 이용한 AC/DC 컨버터 DC-Link 전압 제어에 관한 연구 = A Study on AC/DC Converter DC-Link Voltage Control Using PI-IP Hybrid Controller of EV Bus Fast Charger

 

전기버스 급속충전기의 PI-IP 혼합 제어기를 이용한 AC/DC 컨버터 DC-Link 전압 제어에 관한 연구 = A Study on AC/DC Converter DC-Link Voltage Control Using PI-IP Hybrid Controller of EV Bus Fast Charger 

A Study on AC/DC Converter DC-Link Voltage Control Using PI-IP Hybrid Controller of EV Bus Fast Charger BY Gyu-Nam Yang 

Department of Electrical Engineering Graduate School, Chonnam National University

 (Supervised by Professor Sung-Jun Park) 

 (Abstract) 

The supply of electric vehicles (xEVs) in the transport sector is increasing in response to the global demand for reducing carbon dioxide emissions. However, due to the gradual slow dissemination, the emission is rather difficult, increasing every year. The reasons for this include a relatively high price compared to an internal combustion engine vehicle, limiting the driving range on a single charge, and insufficient charging station. In such a situation where the spread is slow, the method of preferentially eco-friendly public transportation, which has a higher usage rate than passenger cars, is being accepted. In particular, EV buses, which account for a large portion of public transportation, are rapidly spreading. Accordingly, there is a growing demand for the introduction of a large-capacity fast charger that can charge a battery of several hundred kW within 30 minutes. In general, the structure of a fast charger consists of an AC/DC converter and a 2-stage of an isolated DC/DC converter. AC/DC converter converts system 3-phase AC power to DC power and improves power factor. The isolated DC/DC converter uses the rectified DC output to control the voltage and current required by the EV bus battery to directly charge the battery. AC/DC converters have several topologies. Among them, the fast charger for charging is a 3-level converter, and the Vienna Rectifier has many advantages. However, the Vienna Rectifier is a unidirectional converter and it is difficult to control during no-load or light-load operation. In particular, there is a disadvantage in that it is unstable during initial operation and when the battery is fully charged. Several methods have been proposed to solve this problem. Burst mode control [1,2], which is a representative method, has a problem in that it adversely affects the performance of the secondary-side converter and the battery being charged due to the large DC-Link voltage ripple. As another method, a control method with a hysteresis loop was reviewed [3], However, the problem of induced high inrush current is not effectively improved.[4] Therefore, in this paper, hardware configuration and voltage control method for stable control of Vienna Rectifier are presented. Vienna Rectifier is a unidirectional converter characteristic, but there is instability of control under light load conditions. Accordingly, we propose a hardware configuration that can reduce losses by using it as a system power source instead of a conventional dummy resistor. In addition, the existing PI controller has a large transient state due to its quick response when a sudden load change occurs, and the recovery of the steady state may be delayed in the Vienna Rectifier. To solve this problem, In order to secure reliability in the entire load section, we propose a voltage control method that determines the setting parameters of the PI-IP hybrid controller using the load current. The proposed method proved the validity of the hardware configuration and control algorithm of Vienna Rectifier presented through PSIM simulations and experiments.

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Telyakovsky S.A. Coleção de problemas de teoria das funções de uma variável real

 

Design and evaluation of automotive power module : 650V GaN E-HEMT with meandered interconnection and integrated motor-inverter power module---GaN E-HEMT 소자용 인터커넥션과 자동차용 모터-인버터 통합구조 파워모듈의 설계 및 평가

Design and evaluation of automotive power module : 650V GaN E-HEMT with meandered interconnection and integrated motor-inverter power module By Jihwan Seong

 A thesis submitted to the graduate school of Hanyang University for the degree of Doctor of philosophy Department School of Hanyang university 

ABSTRACT 

 With increasing demand in automotive fuel efficiency and ever-strengthening global carbon dioxide emission regulations, electrification has become an indispensable trend. Especially in the automobile industry, miniaturization and performance are other major challenges, and they should be considered with electrification as goals in the equipment design stage. Because of the challenges, a tailored design and evaluation process is necessary for power modules that perform high-level power conversion for motor driving. This dissertation attempts to present the design and evaluation of power modules used in electrified vehicles. The dissertation starts with the configuration of a power module and a description of each module component. A power module includes power devices and packaging components. Among the power devices, wide bandgap (WBG) devices have recently been widely used in power modules, and their characteristics are described. In addition, the roles of packaging components and their design considerations are presented. Because the power module treats electric power, electrical verification is important. Electrical verification methods based on the finite element method (FEM) and circuit simulation tools are introduced. The aforementioned design and evaluation methods are applied to the proposed models of two applications. First, a new interconnection design is proposed. The interconnection is specially designed for the GaN E-mode High-electron-mobility Transistor (E-HEMT). The design process for the proposed interconnection is presented in detail, and a parametric study is conducted considering major design variables, to achieve minimum parasitic inductance and thermal resistance objectives. The expected advantages of the optimal interconnection design, as obtained from the parametric study, are described. To verify these expected advantages, various simulations and experiments are conducted. A prototype of the proposed interconnection is fabricated and experimentally evaluated. Secondly, the inverter power module is designed and analyzed to be applied in the motor-inverter integrated structure of the electric compressor and starter-generator components used in 48-V mild hybrid vehicle system. An improved power module design is proposed, and it demonstrates all of the electrical and thermal performances required in the integrated structure. The performances are evaluated by conducting electrical/thermal simulations and experiments. As a result, the superiority of the proposed interconnection for GaN E-HEMTs and the improved power module considering the integrated structure was demonstrated, and their evaluation processes were validated based on the similarity between the simulation and experimental results.

LINK: 

http://www.riss.kr/search/detail/DetailView.do?p_mat_type=be54d9b8bc7cdb09&control_no=6224a1e85e0d3ab0ffe0bdc3ef48d419&keyword=INVERTER%20GaN