2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)最新文献

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Model Predictive Control for a Multisource Inverter in Electrical Vehicle Applications 电动汽车中多源逆变器的模型预测控制
M. Hosseinzadeh, Maryam Sarebanzadeh, C. Garcia, Fengxiang Wang, José Raúl Rodríguez Rodríguez
{"title":"Model Predictive Control for a Multisource Inverter in Electrical Vehicle Applications","authors":"M. Hosseinzadeh, Maryam Sarebanzadeh, C. Garcia, Fengxiang Wang, José Raúl Rodríguez Rodríguez","doi":"10.1109/PRECEDE51386.2021.9680875","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9680875","url":null,"abstract":"The classical voltage source inverter (VSI) is a suitable topology for electrical vehicles (EVs) due to low cost, high power density, and simple control. However, VSI indicates some restrictions due to the wide range of electrical machine performance and high power demand requirements. Recently, one concept called multisource inverter (MSI) has been introduced, which uses two independent DC sources to respond to different ranges of electrical vehicle speed. In this research, a model predictive control (MPC) is applied to the MSI that drives a permanent magnet synchronous machine (PMSM). The simulation results show that the proposed MPC to drive EVs that use MSI as a traction inverter possesses good advantages such as quick performance without any distortion in speed signal and also MPC uses a good transition to reach high voltage levels to respond to the high speeds of EV.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123205177","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}
引用次数: 1
A New Time Sequence for Predictive Current Control in PMSM Drives 一种用于永磁同步电机预测电流控制的新时间序列
Zhang Huixuan, Fan Tao, Guo Jing, Liu Zhongyong
{"title":"A New Time Sequence for Predictive Current Control in PMSM Drives","authors":"Zhang Huixuan, Fan Tao, Guo Jing, Liu Zhongyong","doi":"10.1109/PRECEDE51386.2021.9680965","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9680965","url":null,"abstract":"Conventional deadbeat predictive current control is a powerful control strategy for electric drive because of the advantages of fast dynamic response and easy implementation. In this paper, an improved deadbeat control algorithm for PMSM is employed based on timing optimization. The current controller calculates the current instruction piecewise, then generates the compensation value of the voltage command, thus eliminating the one-beat delay of the current instruction. Simulation and experimental results both show that the improved current prediction algorithm can effectively improve the dynamic performance of the current loop, and the steady-state behavior will not be influenced.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122551948","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}
引用次数: 1
Distributed Model Predictive Control for Multi-port DC-DC Converter Wind-Solar Complementary System 多端口DC-DC变换器风光互补系统的分布式模型预测控制
Yu Chen, Yi Zhang, Yang Liu
{"title":"Distributed Model Predictive Control for Multi-port DC-DC Converter Wind-Solar Complementary System","authors":"Yu Chen, Yi Zhang, Yang Liu","doi":"10.1109/PRECEDE51386.2021.9681014","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9681014","url":null,"abstract":"For the large-scale and geographically dispersed wind-solar complementary system, the information communication between each sub-system is lacking, and the problem of synchronous optimization is not far apart. The strategy of distributed model predictive control is proposed to optimize and adjust the system power balance and voltage stability throughout the entire wind-solar complementary system. Aiming at the problem of power flow of wind, photovoltaic, and battery sub-system through multiple single-port bidirectional DC-DC converters, it is proposed to apply the multi-port bidirectional DC-DC converter to the wind-solar complementary system, thereby reducing the number of DC-DC converters and the cost. The experimental research proves that the proposed distributed model predictive control strategy is applied to the multi-port DC-DC converter type wind-solar complementary system. Comparing with the traditional control method, its optimization rate is high and the safe and reliable operation of the system is guaranteed.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128868823","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}
引用次数: 2
FPGA-Based Double Vectors Model Predictive Torque Control for PMSM Drives Using Maximized Parallel Implement Architecture 基于fpga的永磁同步电机双矢量模型预测转矩控制
Taoming Wang, Guangzhao Luo, Donghua Wu, Yi Wang, Chunqiang Liu, Zhe Chen
{"title":"FPGA-Based Double Vectors Model Predictive Torque Control for PMSM Drives Using Maximized Parallel Implement Architecture","authors":"Taoming Wang, Guangzhao Luo, Donghua Wu, Yi Wang, Chunqiang Liu, Zhe Chen","doi":"10.1109/PRECEDE51386.2021.9680995","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9680995","url":null,"abstract":"To reduce the computation time of double vectors model predictive torque control (DV-MPTC), the maximized parallel architecture implemented in field programmable gate array (FPGA) for the surface-mounted permanent magnet synchronous motor (SPMSM) is proposed. Double vectors, which include an active vector and a zero vector, are used during one control period to reduce steady-state current ripples. In conventional implement architecture, predictive controller and speed controller are a cascaded form. By adjusting the execution sequence of one-step compensation module and candidate vector module in the cascaded predictive controller, the maximized parallel architecture is designed. Furthermore, the parallel architecture may have the problem of disordered parameter update sequence due to the different execution steps. To ensure the orderly execution of the maximized parallel architecture, a logic trigger mechanism is designed and applied in the parallel architecture. Experimental results illustrate the effectiveness of the proposed parallel implement architecture.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125347982","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}
引用次数: 1
Weightless Model Predictive Torque Control of Induction Motor with Simplified Candidate Voltage Vectors Set 基于简化候选电压矢量集的异步电动机失重模型预测转矩控制
Yao-hua Li, Guixin Chen, Zikun Liu, Xiaoyu Wang, Dongmei Liu, Chao Ren
{"title":"Weightless Model Predictive Torque Control of Induction Motor with Simplified Candidate Voltage Vectors Set","authors":"Yao-hua Li, Guixin Chen, Zikun Liu, Xiaoyu Wang, Dongmei Liu, Chao Ren","doi":"10.1109/PRECEDE51386.2021.9680974","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9680974","url":null,"abstract":"In order to reduce the torque ripple, flux ripple and calculation burden of the conventional model predictive torque control (MPTC) of induction motors (IM), and avoid the design of weight coefficients, a weightless MPTC method with simplified voltage vectors (VVs) based on deadbeat (DB) is proposed. The duty cycle of the VVs is calculated through DB method, and then the MPTC link is performed after VVs are corrected to select the optimal VV. Based on the DB-MPTC, the symmetrical distribution of the duty cycle with the VVs is used to reduce the number of non-zero VVs traversed by half. Secondly, the cost function in the algorithm only contains the flux term, and has almost no effect on the control performance, thus eliminating the weight coefficient and further simplifying the MPTC model. Finally, the influence of extending VVs on DB-MPTC is briefly studied. The experimental results prove that through the method, the torque ripple is improved by 64.92%, flux ripple is improved by 52.24%, current total harmonic distortion (THD) is optimized from 12.68% to 5.60%, the design of weight coefficient can be effectively avoided, and the calculation burden is also reduced by 48.61%, so the control and real-time performance is improved.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130157969","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}
引用次数: 0
Research on Secondary Ripple Suppression of Single-phase Rectifier based on CRH3 基于CRH3的单相整流器二次纹波抑制研究
Zi Liu, Hongjin Zhang, Pengcheng Han, Xiaoqiong He
{"title":"Research on Secondary Ripple Suppression of Single-phase Rectifier based on CRH3","authors":"Zi Liu, Hongjin Zhang, Pengcheng Han, Xiaoqiong He","doi":"10.1109/PRECEDE51386.2021.9680972","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9680972","url":null,"abstract":"The single-phase rectifier in traction drive system has the problem of secondary voltage ripple at the dc side, while the LC passive filter device used at present can effectively suppress the secondary voltage ripple at the dc side, but the required parameters are very large, which greatly reduce the power density of the converter. Therefore, this paper deeply analyzes the energy flow of traction drive system, deduces the voltage expression of the intermediate dc capacitance, analyzes the influence of the secondary ripple of dc voltage on the current at the rectifier network side according to the working characteristics of the rectifier, and finally researches the active secondary filtering method at the rectifier dc side.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130169538","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}
引用次数: 0
Robust Model Predictive Current Control Method for Grid-Connected Converter Based on Weighted Strategy 基于加权策略的并网变流器鲁棒模型预测电流控制方法
Yanyan Li, Zhiye Xu, Leilei Guo, Nan Jin, Pengfei Gao, Wei Wang
{"title":"Robust Model Predictive Current Control Method for Grid-Connected Converter Based on Weighted Strategy","authors":"Yanyan Li, Zhiye Xu, Leilei Guo, Nan Jin, Pengfei Gao, Wei Wang","doi":"10.1109/PRECEDE51386.2021.9681047","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9681047","url":null,"abstract":"This paper presents a current model predictive control (CMPC) method for two-level grid-connected converters. As known, model predictive control (MPC) strategy is a model-based control method. However, the temperature rise and current change will lead to the change of the inductors, resistance of the circuit. Thus, when the parameter in the prediction model is inconsistent with the one in actual circuit, the current accuracy of the conventional CMPC method will be reduced obviously. So, in this paper, to improve the parameter robustness of the CMPC method and improve the grid-connected quality further. A new weighted CMPC strategy is creatively proposed. Through detailed theoretical analysis, the principle of the proposed method to reduce the influence of parameter errors is revealed. Finally, the effectiveness and feasibility of the proposed method are verified by simulation.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126321368","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}
引用次数: 0
State Analysis of Distributed Power System Considering the Randomness of PV Generation 考虑光伏发电随机性的分布式电力系统状态分析
Diao Shoubin, Li Xinpeng, Caoxin, Li Jian, Du Peixin, Wang Qingyan
{"title":"State Analysis of Distributed Power System Considering the Randomness of PV Generation","authors":"Diao Shoubin, Li Xinpeng, Caoxin, Li Jian, Du Peixin, Wang Qingyan","doi":"10.1109/PRECEDE51386.2021.9681036","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9681036","url":null,"abstract":"As the awareness of environmental protection increases, renewable energy generation, represented by photovoltaic power generation, is rapidly connected to the distribution network, changing the operating state and increasing uncertainty of state. Effective analysis of the system uncertainty is an important tool for system planning and optimization, based on which this paper investigates the state of the distribution system considering PV access. This paper first analyzes the impact mechanism of PV access on voltage, network loss and then studies the system state based on the uncertainty power flow analysis method considering the randomness of PV output, and finally analyzes the uncertain impact of PV access on the system state based on the improved IEEE 33 bus system.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"166 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126224535","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}
引用次数: 0
Improved Model Predictive Robust Current Control for Permanent Magnet Synchronous Hub Motor 永磁同步轮毂电机的改进模型预测鲁棒电流控制
Teng Li, Xiaodong Sun
{"title":"Improved Model Predictive Robust Current Control for Permanent Magnet Synchronous Hub Motor","authors":"Teng Li, Xiaodong Sun","doi":"10.1109/PRECEDE51386.2021.9680898","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9680898","url":null,"abstract":"Model predictive control is a model-based method for permanent magnet synchronous hub motors (PMSHM). The inconsistency between the real operating parameters and the motor actual value will reduce the performance of the control method. Therefore, this paper proposes an improved robust model predictive current control (MPCC), which uses an incremental model to remove the effects of flux linkage changes. The cost function includes the previously selected predicted current value and the previously measured value to improve forecasting accuracy and reduce the impact of changes in inductance. Meanwhile, the steady-state performance of model predictive control is improved by synthesizing virtual vectors. Finally, experiments prove the method can improve robustness and have good steady-state performance.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133514118","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}
引用次数: 0
Zero Sequence Voltage Control of Open-End Winding Induction Motor by a Model-Free Predictive Control 基于无模型预测控制的开放式绕组异步电动机零序电压控制
M. Mousavi, S. Davari, Alireza Ja’afari, C. Garcia, Fengxiang Wang, José Raúl Rodríguez Rodríguez
{"title":"Zero Sequence Voltage Control of Open-End Winding Induction Motor by a Model-Free Predictive Control","authors":"M. Mousavi, S. Davari, Alireza Ja’afari, C. Garcia, Fengxiang Wang, José Raúl Rodríguez Rodríguez","doi":"10.1109/PRECEDE51386.2021.9681011","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9681011","url":null,"abstract":"Supplying the open-end winding induction motor (OEWIM) with two typical voltage source inverters is an efficient mechanism to achieve a multi-level voltage on the stator. The asymmetric switching states of these two inverters generate a zero-sequence voltage (ZSV). The ZSV must be controlled in a way to prevent the production of zero-sequence current (ZSC) in the motor windings. This paper presents a finite-set model-free predictive control (FS-MFPC) to eliminate the ZSC. The proposed FS-MFPC utilizes an ultra-local model, which is independent of the system parameters. So, the robustness of the control scheme is improved against the uncertainties of the OEWIM. The ultra-local model of the proposed FS-MFPC is constructed by an extended state observer (ESO), which estimates the unknown function of the system. To avoid the complexity of applying ZSV in the modulation techniques, the proposed scheme is implemented in the finite-set predictive voltage control approach. The simulation results confirm that the proposed ZSV control has a good steady-state and dynamic performance.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"63 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131251552","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}
引用次数: 1
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