{"title":"Combined Model Predictive Control Strategies to Improve the Reliability of IGBT Module in Doubly Fed Wind Power Converter","authors":"Yu Hu, Hui Li, Xiangiie Xie, Guisen Xia, Tian Yang, You Wu","doi":"10.1109/PRECEDE.2019.8753266","DOIUrl":"https://doi.org/10.1109/PRECEDE.2019.8753266","url":null,"abstract":"The reliability of the rotor side converter of doubly fed induction generator (DFIG) could be greatly degraded due to large junction temperature fluctuation and high power loss, a combined model predictive control strategy is proposed to reduce the junction temperature and switching loss. First, based on the structure of IGBT modules in DFIG wind power converter, the equivalent thermal network model is presented. Then, an improved maximum power point tracking control strategy, based on the power-speed outer control loop, is proposed by shortening the low frequency durations and increasing the speed gradient of the rotor side converter around synchronous speed. Furthermore, combined with the model predictive current control strategy, the switching loss of IGBT modules could be reduced. Finally, the dynamic performances of the junction temperature and power loss of IGBT modules are analyzed through the electrical-thermal model simulation and the equivalent experiment testing. Both simulation and experimental results show that the proposed control strategy could be effective to depress the IGBT junction temperature fluctuation and power loss.","PeriodicalId":227885,"journal":{"name":"2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116580551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sebastian Wendel, A. Geiger, E. Liegmann, David Arancibia, Esteban Durén, Thomas Kreppel, F. Rojas, Flaviu Popp-Nowak, M. Díaz, A. Dietz, R. Kennel, B. Wagner
{"title":"UltraZohm - a Powerful Real-Time Computation Platform for MPC and Multi-Level Inverters","authors":"Sebastian Wendel, A. Geiger, E. Liegmann, David Arancibia, Esteban Durén, Thomas Kreppel, F. Rojas, Flaviu Popp-Nowak, M. Díaz, A. Dietz, R. Kennel, B. Wagner","doi":"10.1109/PRECEDE.2019.8753306","DOIUrl":"https://doi.org/10.1109/PRECEDE.2019.8753306","url":null,"abstract":"This paper presents the hardware design, software architecture and workflow for rapid control prototyping intended for a wide-range of power electronics based systems. The proposed system is especially useful for computationally intensive algorithms and applications with high demands on the number of required measurements and gate signals. The focus is on a heterogeneous system architecture with minimized latency and jitter as well as a high signal integrity. The software architecture enables a simple, fast and performance driven implementation. A combination of carrier board and exchangeable interfacing adapter boards allows to control a wide range of power electronics applications and converters, i.e., starting with a single switching device, converters with one or several voltage levels and one or several phase legs, up to large modular multilevel converters for grid-tied connection or variable speed drives.","PeriodicalId":227885,"journal":{"name":"2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130336221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Robust Deadbeat Predictive Current Control for PMSM Drives Based on Single FPGA Implementaion","authors":"Zihao Chen, Chun Wu, Degang Zhong, Chen Qiang","doi":"10.1109/PRECEDE.2019.8753272","DOIUrl":"https://doi.org/10.1109/PRECEDE.2019.8753272","url":null,"abstract":"This paper proposes a robust deadbeat predictive current control (RPDCC) for permanent magnet synchronous motor (PMSM) drives. The parameter errors, model uncertainties and disturbances are treated as total disturbances and an adaptive observer is designed to estimate these total disturbances. The stability of this observer is analyzed by Lyapunov stability theory. Furthermore, this paper implements all control algorithms on single field programmable gate array (FPGA). Due to the parallel process and fast calculation ability of FPGA, the whole strategies can implemented during 1.31 us. The simulation and experimental results show the proposed RPDCC is robust against parameters variations, and can achieve fast dynamic performance and zero steady-state errors even with parameter errors.","PeriodicalId":227885,"journal":{"name":"2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125352577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xin Qi, R. Kennel, Xiaomin Zhou, Ke Zhou, Xianfeng Gong, Tao Feng
{"title":"Influence of leakage inductance on operation performances for predictive control low-switching frequency application","authors":"Xin Qi, R. Kennel, Xiaomin Zhou, Ke Zhou, Xianfeng Gong, Tao Feng","doi":"10.1109/PRECEDE.2019.8753188","DOIUrl":"https://doi.org/10.1109/PRECEDE.2019.8753188","url":null,"abstract":"To minimize current distortion and switching frequency with high dynamic, predictive control is excellent than other modulation methods. Leakage inductance is discussed as the key factor, which impacts the performance of predictive control. To study its influence, three induction machines, which have different rated voltage and different normalized parameters, serve as research objects. Current trajectories and waveforms of switching state are analyzed.","PeriodicalId":227885,"journal":{"name":"2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"58 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132531278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Adaptation of Predictive Acoustic Noise Control of IM Drive to Variable Operating Conditions","authors":"Michal Kroneisl, V. Šmídl, Z. Peroutka","doi":"10.1109/PRECEDE.2019.8753187","DOIUrl":"https://doi.org/10.1109/PRECEDE.2019.8753187","url":null,"abstract":"Finite control set MPC of IM drive is known to produce a spread spectrum of the stator currents. Spectrum of the acoustic noise also exhibits higher spread than that of the PWM which may be perceived as more pleasant sound by humans. Predictive acoustic noise control has been recently proposed using FCS-MPC with additive term maximizing spectrum flatness of the emitted acoustic noise. It has been shown that the acoustic noise generated by this control has better properties than the conventional random PWM. In this contribution, we study variability of the acoustic model with respect to operating conditions. We show that constant penalization factors are not optimal. We design a measure of performance of the acoustic noise controller and propose a scheduling mechanism for adjustment of the penalization coefficient to optimize this measure. Since we require noise measurements, the procedure is expected to be used during commissioning of the drive.","PeriodicalId":227885,"journal":{"name":"2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121654633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Simplified Model Predictive Control Method Used in Three-level Six-phase Invertor","authors":"Ling Feng, Y. Lv, Wensheng Song","doi":"10.1109/PRECEDE.2019.8753355","DOIUrl":"https://doi.org/10.1109/PRECEDE.2019.8753355","url":null,"abstract":"This paper presents a simplified model predictive control algorithm for three-level six-phase inverters. The simplified MPC algorithm not only achieves good output current tracking ability, but also eliminates the complex PI controller with three-level six-phase space vector pulse width modulation algorithm, which makes the control of the system simple and clear, so that it can be better applied to high-power and high-reliability applications.","PeriodicalId":227885,"journal":{"name":"2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125078624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Model Predictive Control of Modular Multilevel Converters with Independent Arm-Balancing Control","authors":"W. Tian, Xiaonan Gao, R. Kennel","doi":"10.1109/PRECEDE.2019.8753360","DOIUrl":"https://doi.org/10.1109/PRECEDE.2019.8753360","url":null,"abstract":"The model predictive control (MPC) for modular multilevel converter (MMC) has drawn attention among researchers in recent years due to its straightforward implementation, ability to control multiple objectives in a single cost functions, and excellent dynamics response. The AC-side current, circulating current and arm voltage are the three key control objectives for MMC. In most of the existing papers, the three objectives are direct added into a single cost function without considering the couplings within them. The circulating current and arm voltage depend on each other, so they are hard be controlled to the reference value at the same time in a single cost function. In this paper, a MPC of MMC with an independent arm-balancing control is proposed. The proposed strategy decouples the circulating current and arm voltage with an arm-balancing control. The performance of the proposed strategy for a 21-level MMC is evaluated based on the simulation studies.","PeriodicalId":227885,"journal":{"name":"2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123196837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Haotian Xie, Qing Chen, Ying Tang, R. Kennel, Fengxiang Wang, Anjun Xia, Zhenbin Zhang, José R. Rodríguez
{"title":"Sliding-Mode MRAS based Encoderless Predictive Torque Control for Induction Machine","authors":"Haotian Xie, Qing Chen, Ying Tang, R. Kennel, Fengxiang Wang, Anjun Xia, Zhenbin Zhang, José R. Rodríguez","doi":"10.1109/PRECEDE.2019.8753190","DOIUrl":"https://doi.org/10.1109/PRECEDE.2019.8753190","url":null,"abstract":"This paper presents a sliding-mode (SM) model reference adaptive system (MRAS) observer for predictive torque control (PTC) in the induction machine drives. The PTC scheme is one of the most promising control strategy for electrical drives. However, its performance is constrained due to the accuracy of parameter and speed estimation. The proposed SM MRAS is employed to estimate rotor speed for PTC. The dominant feature of the methodology is that the adjustable model is modified by a sliding manifold in accordance with the error signal. Compared with conventional MRAS, the proposed method is more robust and easily tuned. To enhance robustness of the PTC scheme to the parameter variation, the extended rotor resistance compensation is employed in the estimator. In this paper, the experimental results confirm that the proposed method achieves fast dynamic performance and strong robustness.","PeriodicalId":227885,"journal":{"name":"2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"426 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133305437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Mohebbi, D. Khaburi, S. Heshmatian, José R. Rodríguez, Cristian Garcia Peñailillo
{"title":"Predictive Control of Flux Angle for Induction Motors","authors":"M. Mohebbi, D. Khaburi, S. Heshmatian, José R. Rodríguez, Cristian Garcia Peñailillo","doi":"10.1109/PRECEDE.2019.8753320","DOIUrl":"https://doi.org/10.1109/PRECEDE.2019.8753320","url":null,"abstract":"Nowadays, induction motors are widely used in electrical drive systems. Vector control is one of the most utilized methods in these systems. This method has acceptable performance in heavy loading conditions and the rotor flux is the same as the nominal value. However, in light loading, using vector control method results in decreasing the efficiency. When the motor has light loading, there is no need for the nominal flux in order to provide the required torque. Motors are rarely used for operating with their nominal load and the loading is usually different from the nominal value. One of the reasons for this is the overdesign. In this paper, the efficiency of induction motor is improved, especially in light loading. This is accomplished by predictive control of the angle between stator current and rotor flux which is on the d-axis (flux angle). In the proposed method, for light loading condition (the range from no load to a certain value of boundary torque), the flux angle is controlled and kept to a constant value which depends on some of the machine parameters. For the loading range between the boundary torque and the nominal value, the flux angle is controlled but to a variable reference. The designed method can be easily implemented and significantly increases the induction motor efficiency in light loading.","PeriodicalId":227885,"journal":{"name":"2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131320431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Predictive current control for SynRM drives under low dc link voltage","authors":"Xin Yuan, Chengning Zhang, Shuo Zhang, Rui Wang, Xiaoguang Zhang","doi":"10.1109/PRECEDE.2019.8753201","DOIUrl":"https://doi.org/10.1109/PRECEDE.2019.8753201","url":null,"abstract":"Although it has an excellent steady performance, traditional proportion integration (PI) current control still needs PI parameters tuning, which is a time-consuming. In addition, because there are no permanent magnets in synchronous reluctance motor (SynRM) drives, the large stator inductance will affect the stator current variation, which actually limits the response of the current controller. This problem gets worse if dc link of an inverter is low. To deal with these problems, other current control strategies for SynRM will be introduced, namely deadbeat predictive current control (DPCC) and model predictive current control (MPCC). In addition, this paper analyzes the advantages and drawback about the PI current control and predictive control in SynRM drives. Simulation results are demonstrated to verify the effectiveness of the four control strategies.","PeriodicalId":227885,"journal":{"name":"2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131061123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}