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2021 IEEE Transportation Electrification Conference & Expo (ITEC)最新文献

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Fully Decentralized Energy Management Strategy Based on Model Predictive Control in a Modular Fuel Cell Vehicle 基于模型预测控制的模块化燃料电池汽车全分散能量管理策略
2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490041
A. Soltani, L. Boulon, Xiaosong Hu
{"title":"Fully Decentralized Energy Management Strategy Based on Model Predictive Control in a Modular Fuel Cell Vehicle","authors":"A. Soltani, L. Boulon, Xiaosong Hu","doi":"10.1109/ITEC51675.2021.9490041","DOIUrl":"https://doi.org/10.1109/ITEC51675.2021.9490041","url":null,"abstract":"Power allocation strategy (PAS) plays an essential role in fuel cell vehicles (FCVs). Current studies mainly focus on centralized PASs (C-PASs) without adequately providing flexibility (plug & play) and robustness. In this regard, a decentralized PAS (D-PAS) based on prediction is proposed for a modular FCV powertrain. The performance of this suggested approach is analyzed for various driving scenarios. Based on the numerical results, the proposed D-PAS provides superior performance compared to the centralized ones.","PeriodicalId":339989,"journal":{"name":"2021 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123653793","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
Small Signal Analysis and Control of Single-Phase Bridgeless Cuk-based PFC Converter for On-Board EV Charger 车载充电器单相无桥PFC变换器的小信号分析与控制
2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490141
Sukanya Dutta, S. Gangavarapu, Venkata R. Vakacharla, A. Rathore, V. Khadkikar, H. Zeineldin
{"title":"Small Signal Analysis and Control of Single-Phase Bridgeless Cuk-based PFC Converter for On-Board EV Charger","authors":"Sukanya Dutta, S. Gangavarapu, Venkata R. Vakacharla, A. Rathore, V. Khadkikar, H. Zeineldin","doi":"10.1109/ITEC51675.2021.9490141","DOIUrl":"https://doi.org/10.1109/ITEC51675.2021.9490141","url":null,"abstract":"This work presents detailed small-signal-modeling and closed-loop controller design of novel Cuk-based PFC converter for on-board EV charger. Since the converter is designed to operate in discontinuous conduction mode (DCM) for attaining power factor correction (PFC) naturally on the input side. Thus, only the output voltage sensing is required as the input voltage and current sensing is not necessary. Thereby, making the operation of the converter less-costly, reliable, and intensifying the robustness towards higher frequency noise. The control strategy is straightforward requiring one control loop and sensor. This article describes the complete derivation of control-to-output transfer function along with optimal selection of control parameters. Finally, to validate the controller design, simulation and hardware results are provided.","PeriodicalId":339989,"journal":{"name":"2021 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123757262","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
Quasi-Dynamic Electromagnetic Field Safety Analysis and Mitigation for High-Power Dynamic Wireless Charging of Electric Vehicles 电动汽车大功率动态无线充电准动态电磁场安全性分析与缓解
2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490192
Bo Zhang, R. Carlson, V. Galigekere, O. Onar, Mostak Mohammad, Charles C. Dickerson, L. Walker
{"title":"Quasi-Dynamic Electromagnetic Field Safety Analysis and Mitigation for High-Power Dynamic Wireless Charging of Electric Vehicles","authors":"Bo Zhang, R. Carlson, V. Galigekere, O. Onar, Mostak Mohammad, Charles C. Dickerson, L. Walker","doi":"10.1109/ITEC51675.2021.9490192","DOIUrl":"https://doi.org/10.1109/ITEC51675.2021.9490192","url":null,"abstract":"Dynamic wireless charging of electric vehicles (EV) is an emerging charging technology to enable non-contact wireless charging while the vehicle is moving. Compared to stationary wireless charging, in-motion wireless charging involves dynamic processes in which an EV is passing over the charging pads (transmitters). This in-motion process makes the dynamic electromagnetic (EM) environment more complicated, and EM safety needs to be ensured under all circumstances. This is due to the fact that the entire vehicle body may be exposed to magnetic fields while the vehicle moves over the energized transmitter. This paper investigates several typical charging scenarios when EVs approach, pass over, and move away from the charging pads. Quasi-dynamic models, which are preliminarily verified by coils' inductance measurements, are developed to analyze the dynamic process. Based on the quasi-dynamic analysis, shielding solutions are also studied to ensure EM safety for the dynamic wireless charging processes.","PeriodicalId":339989,"journal":{"name":"2021 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126149607","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: 3
Small Signal Modeling and Control of Resonant Switched Capacitor Converter 谐振开关电容变换器的小信号建模与控制
2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490057
Yan Liu, Xiaofeng Yang, Chengzhang Yan, Qian Chen, S. Igarashi, T. Takaku
{"title":"Small Signal Modeling and Control of Resonant Switched Capacitor Converter","authors":"Yan Liu, Xiaofeng Yang, Chengzhang Yan, Qian Chen, S. Igarashi, T. Takaku","doi":"10.1109/ITEC51675.2021.9490057","DOIUrl":"https://doi.org/10.1109/ITEC51675.2021.9490057","url":null,"abstract":"Featured with low switching loss, resonant switched capacitor converter (RSCC) has attracted more attention in recent years. However, as the key basis for controller design, the small signal model of RSCC is rarely studied. This paper firstly introduces the operation principle of RSCC under phase shift control. Then the small signal model of RSCC is studied based on the extended describing function (EDF) method. With the small signal model, the controller is designed to improve the RSCC dynamic performance. Finally, the simulation and experimental results verify the correctness of the small signal model and the effectiveness of the controller designed in this paper.","PeriodicalId":339989,"journal":{"name":"2021 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129638369","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
Double Q-learning-based Energy Management Strategy for Overall Energy Consumption Optimization of Fuel Cell/Battery Vehicle 基于双q学习的燃料电池/电池汽车整体能耗优化能源管理策略
2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490114
Xiang Meng, Qi Li, Guorui Zhang, Xiaofeng Wang, Wei-rong Chen
{"title":"Double Q-learning-based Energy Management Strategy for Overall Energy Consumption Optimization of Fuel Cell/Battery Vehicle","authors":"Xiang Meng, Qi Li, Guorui Zhang, Xiaofeng Wang, Wei-rong Chen","doi":"10.1109/ITEC51675.2021.9490114","DOIUrl":"https://doi.org/10.1109/ITEC51675.2021.9490114","url":null,"abstract":"Nowadays, most energy management strategies (EMSs) of hybrid systems are developed based on optimization theories. However, the EMS with global optimization capabilities often relies on prior knowledge of operation condition, which is often difficult in practice. Furthermore, with the increasing promotion of machine learning technology, reinforcement learning has been introduced into the research field of hybrid system EMS. Algorithms such as Q-learning and Deep Q Network have been extensively studied. However, the above algorithms have inherent defects of overestimation problem, which will lead to the problems of instability and poor performance. In order to overcome the above problems and save the overall energy consumptions, this paper proposes to adopt Double Q-learning algorithm to design the EMS of a fuel cell hybrid system. Through simulation experiments, the effectiveness of the proposed strategy is verified.","PeriodicalId":339989,"journal":{"name":"2021 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"37 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130592565","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: 5
Modeling of Traction Batteries for Rail Applications Using Artificial Neural Networks 基于人工神经网络的轨道牵引蓄电池建模
2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490180
René Bauer, S. Reimann, P. Gratzfeld
{"title":"Modeling of Traction Batteries for Rail Applications Using Artificial Neural Networks","authors":"René Bauer, S. Reimann, P. Gratzfeld","doi":"10.1109/ITEC51675.2021.9490180","DOIUrl":"https://doi.org/10.1109/ITEC51675.2021.9490180","url":null,"abstract":"The development of novel operational strategies for battery electric trains requires a vehicle model including the traction battery. This paper proposes a method to generate accurate traction battery models on system level for application in a simulation model of battery electric multiple units. Artificial neural networks are used to identify the coherences within real system data from a traction battery used in an electric bus. Two approaches are examined to estimate the terminal voltage: a feedforward neural network and a long short-term memory network. Model generation is followed by a comparison with an existing physics-based battery model in order to prove the increase of accuracy.","PeriodicalId":339989,"journal":{"name":"2021 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130160718","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
A Review of Virtual-Flux Model Predictive Control and Receding Horizon Estimation in Motor Drives 电机驱动中虚拟磁链模型预测控制和后退水平估计的研究进展
2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490153
Michael Eull, M. Preindl
{"title":"A Review of Virtual-Flux Model Predictive Control and Receding Horizon Estimation in Motor Drives","authors":"Michael Eull, M. Preindl","doi":"10.1109/ITEC51675.2021.9490153","DOIUrl":"https://doi.org/10.1109/ITEC51675.2021.9490153","url":null,"abstract":"Model predictive control and receding horizon estimation are advanced control and estimation techniques for next-generation high performance motor drives. These methods benefit from low noise and accurate system models, which are challenging to realize with parameter-based motor models. The idea of virtual-flux, where the machine is modelled with flux instead of current, has been seen as a solution, as the parameters and their nonlinearities can be captured by a function that maps measured current onto the corresponding flux it generates. In this way, all system information can be encoded in a single static function, simplifying the stability and robustness analyses, as well as online computational requirements. Furthermore, virtual-flux modelling allows for many electric machines and even the electric grid to be described in a similar way. This review condenses the results in literature into a uniform virtual-flux framework and explores the applications and potential of model predictive control and receding horizon estimation. The combination of these concepts is shown to strongly benefit their respective problems, ranging from finite control set and convex control set MPC, full and reduced phase current sensor set flux estimation, and position and speed co-estimation.","PeriodicalId":339989,"journal":{"name":"2021 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122427647","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
Programmable and Reconfigurable Cyber-Physical Networked Microgrids through Software-Defined Networking 通过软件定义网络的可编程和可重构网络-物理网络微电网
2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490123
Yan Li, Liang Du
{"title":"Programmable and Reconfigurable Cyber-Physical Networked Microgrids through Software-Defined Networking","authors":"Yan Li, Liang Du","doi":"10.1109/ITEC51675.2021.9490123","DOIUrl":"https://doi.org/10.1109/ITEC51675.2021.9490123","url":null,"abstract":"Networked microgrids provide promising solutions to modernize the electric power grids. To promote the physical networked microgrids' operations, Software-Defined Networking (SDN) technology is used to establish a programmable communication network for the physical system. By using OpenFlow protocol, SDN separates the data plane from its control plane, which makes it easy to flexibly program the cyber-layer when necessary. Based on SDN, the cyber-physical system's formation, partition, and reconfiguration are introduced. Extensive tests verify the effectiveness of SDN technology in enabling programmable and reconfigurable networked microgrids system. The test results also offer an insight into enhancing the resilience of networked microgrids by reconfiguring the system using SDN.","PeriodicalId":339989,"journal":{"name":"2021 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"214 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122428126","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: 4
An Accurate Online Parameter Estimation Technique for Inductive Electric Vehicle Charging Systems 感应式电动汽车充电系统参数在线准确估计技术
2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490175
H. Jafari, Temitayo O. Olowu, M. Moghaddami, A. Sarwat
{"title":"An Accurate Online Parameter Estimation Technique for Inductive Electric Vehicle Charging Systems","authors":"H. Jafari, Temitayo O. Olowu, M. Moghaddami, A. Sarwat","doi":"10.1109/ITEC51675.2021.9490175","DOIUrl":"https://doi.org/10.1109/ITEC51675.2021.9490175","url":null,"abstract":"An accurate online parameter estimation method for inductive power transfer (IPT) systems is introduced. Using the proposed parameter estimation method both magnetic coupling factor and battery charging current can be estimated simultaneously. This method is specifically suitable for inductive electric vehicle (EV) charging systems in which the battery charging load dynamically varies during the charging process. The proposed method only requires measurements from the primary side and thereby eliminates the need for data communication between the transmitter and receiver. The technique is based on the use of resonance frequency tracking controllers that continuously match the switching frequency the resonance frequency of the IPT system. Detailed analytical formulations for the derivation of magnetic coupling factor and battery charging current and voltage are presented. Theoretical analysis, simulation models and experimental validations of the proposed parameter estimation method are presented. The results show that the proposed method can accurately estimate the magnetic coupling factor and battery charging current in real-time. The experimental results confirm that the proposed method can be easily implemented in any IPT system.","PeriodicalId":339989,"journal":{"name":"2021 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"4 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120903817","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
Correlation study between features of a geographic location and Electric Vehicle Uptake 地理位置特征与电动汽车使用的相关性研究
2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490076
S. Shom, K. James, M. Alahmad
{"title":"Correlation study between features of a geographic location and Electric Vehicle Uptake","authors":"S. Shom, K. James, M. Alahmad","doi":"10.1109/ITEC51675.2021.9490076","DOIUrl":"https://doi.org/10.1109/ITEC51675.2021.9490076","url":null,"abstract":"There are many socio-economic and travel-related factors of a given region that will impact the local adoption of Battery Electric Vehicles (BEVs). In this paper, eleven states are considered to study BEV uptake, and a total of 242 features are used to characterize each zip code. The results are analyzed to determine the degree of correlation between zip code features and BEV uptake. Preliminary results show several features well-correlated with BEV uptake, in particular individuals or households with high income in a single-dwelling unit and owning more than one vehicle.","PeriodicalId":339989,"journal":{"name":"2021 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"R-30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126631387","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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