Full-SiC Integrated Power Module Based on Planar Packaging Technology for High Efficiency Power Converters in Aircraft Applications O. Raab, M. Guacci, A. Griffo, K. Kriegel, M. Heller, J. Wang, D. Bortis, M. Schulz, J. W. Kolar

 

Proceedings of the 11th International Conference on Integrated Power Electronics Systems (CIPS 2020), Berlin, Germany, March 24-26, 2020 

Full-SiC Integrated Power Module Based on Planar Packaging Technology for High Efficiency Power Converters in Aircraft Applications O. Raab, M. Guacci, A. Griffo, K. Kriegel, M. Heller, J. Wang, D. Bortis, M. Schulz, J. W. Kolar 

Full-SiC Integrated Power Module based on Planar Packaging Technology for High Efficiency Power Converters in Aircraft Applications Oliver Raaba , Mattia Guaccib , Antonio Griffoc , Kai Kriegela , Morris Hellerb , Jiabin Wangc , Dominik Bortisb , Martin Schulza , and Johann W. Kolarb aSiemens AG, Corporate Technology, Munich, Germany bPower Electronic Systems Laboratory, ETH Zurich, Zurich, Switzerland cDepartment of Electronic and Electrical Engineering, The University of Sheffield, Sheffield, UK 

Abstract

 Compact, light-weight, efficient and reliable power converters are fundamental for the future of More Electrical Aircraft (MEA). Core elements supporting the electrification of the aerospace industry are power modules (PMs) employing exclusively SiC MOSFETs. In order to fully exploit the high switching speeds enabled by SiC, and to address the challenges arising from the parallelization of power devices, novel PM concepts must be investigated. In this paper, highly symmetrical layouts, low inductance planar interconnection technologies, and integrated buffer capacitors are explored to realize a high efficiency, fast-switching, and reliable full-SiC PM for MEA applications. A comprehensive assessment of a number of performance metrics against state-of-the-art full-SiC PMs demonstrates the benefits of the proposed design approach and manufacturing technologies. Moreover, by integrating temperature and current sensors, intelligent functions, which are crucial for the safe application of power electronics in MEA, are added to the developed PM. In this context, the use of MOSFETs’ Temperature Sensitive Electrical Parameters for online junction temperature estimation is demonstrated, allowing for non-invasive, i.e. without the need for dedicated sensors, thermal monitoring. Additionally, a highly compact gate driver, reducing the overall system volume and complexity, is designed and integrated in the housing of the PM. Finally, switching waveforms are measured during operation of the PM at 500V and 200A, proving the performance improvement enabled by the low inductance layout, the integrated snubber, and the gate driver.

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The MEGACube 166kW/20kHz Medium-Frequency Transformer

 

The MEGACube 166kW/20kHz Medium-Frequency Transformer 

ABSTRACT 

High power DC-DC conversion constitutes the key enabling technology for the implementation of solid-statetransformers. Within these high-power DC-DC converters, the Medium Frequency (MF) transformer is one of the main components, as its task is to provide the primary to secondary isolation and the step-up ratio between the different voltage levels. Several options for the construction of this MF transformer have been reported with different considered core materials, winding arrangements, isolation concepts and thermal management, whereby the main realizations will be revised in this paper. Thereafter, the details of a 166kW/20kHz MF transformer will be presented together with the designed test-bench utilized for the continuous testing of the transformer.

ORIGINAL LINK IN WEB:https://www.pes-publications.ee.ethz.ch/uploads/tx_ethpublications/01_MegaCube_Trafo_Digest_APEC2013.pdf

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.

ORIGINAL LINK:

 http://www.riss.kr/search/detail/DetailView.do?p_mat_type=be54d9b8bc7cdb09&control_no=34f4c539629b2d90ffe0bdc3ef48d419&keyword=charging%20battery

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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