2021 IEEE Transportation Electrification Conference & Expo (ITEC)最新文献_第6页

Effect of Rotor Geometry on Rotor Air Cooling of a Ventilated Axial-Flux Permanent Magnet Machine 转子几何形状对通风轴向磁通永磁电机转子风冷的影响

2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490086

Islam Zaher, R. Rodriguez, Ehab Sayed, A. Callegaro, Mikhail Goykhman, A. Emadi

{"title":"Effect of Rotor Geometry on Rotor Air Cooling of a Ventilated Axial-Flux Permanent Magnet Machine","authors":"Islam Zaher, R. Rodriguez, Ehab Sayed, A. Callegaro, Mikhail Goykhman, A. Emadi","doi":"10.1109/ITEC51675.2021.9490086","DOIUrl":"https://doi.org/10.1109/ITEC51675.2021.9490086","url":null,"abstract":"High heat losses are generated in the rotors of Axial-flux Permanent Magnet (AFPM) machines due to their high power density. Therefore, they require intensive cooling to maintain safe continuous and peak power operation. For ventilated-type machines, air cooling is the predominant cooling method that keeps the rotor magnets temperature below critical limits. Integration of air-cooling features such as protruding magnets, rotor vents, and rotor integrated fan blades into machines has been widely investigated. These features improve the overall cooling of the machine and eliminate the reliance on external cooling devices. This study investigates different rotor geometries, including either a single or a combination of the mentioned features, and assesses their thermal performance and cooling efficiency considering associated windage losses. From the simulated cases, it was found that rotors with geometrical features that allow though-flow ventilation to directly cool the magnets are more efficient compared to others that rely on indirect cooling.","PeriodicalId":339989,"journal":{"name":"2021 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"76 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":"125161264","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

A Look-up Table-based Model Predictive Torque Control of Switched Reluctance Motor Drives with Improved Prediction 基于查找表的改进预测开关磁阻电机驱动转矩预测控制

2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490078

Diego F. Valencia, Rasul Tarvirdilu-Asl, C. Garcia, José Raúl Rodríguez Rodríguez, A. Emadi

引用次数: 1

A Novel Three Phase Oak Ridge DC / AC Converter for Wireless Grid Tied Applications 一种新型的用于无线并网应用的三相Oak Ridge DC / AC变换器

2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490101

Erdem Asa, O. Onar, V. Galigekere, Rong, Zeng, G. Su, B. Ozpineci

引用次数: 3

Design and Modeling of Auxiliary Misalignment Detection Coils for Dynamic Wireless Electric Vehicle Charging Systems 动态无线电动汽车充电系统辅助不对中检测线圈的设计与建模

2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490124

Youssef Louca, Eiman ElGhanam, Mohamed S. Hassan, A. Osman

{"title":"Design and Modeling of Auxiliary Misalignment Detection Coils for Dynamic Wireless Electric Vehicle Charging Systems","authors":"Youssef Louca, Eiman ElGhanam, Mohamed S. Hassan, A. Osman","doi":"10.1109/ITEC51675.2021.9490124","DOIUrl":"https://doi.org/10.1109/ITEC51675.2021.9490124","url":null,"abstract":"Due to the inherent misalignment variations in dynamic wireless electric vehicle (EV) charging systems, it is essential to implement effective misalignment detection and correction techniques to maximize the amount of energy received by the EV. A misalignment detection system consists of detector coils or sensors, and the corresponding detection circuitry. In this work, the design details of the auxiliary misalignment detection coils are presented. In particular, the paper investigates the effect of the number of turns of the auxiliary coils, their turn-to-turn spacing, and their positions relative to the edges of the secondary coil, on their lateral misalignment detection capability. Based on the conducted simulations, it is observed that increasing the number of turns as well as the turn-to-turn spacing of the auxiliary coils both significantly improve their misalignment detection capability by improving the resultant mutual inductance variations with lateral misalignments. Also, the optimal position of the auxiliary coils is determined to be 200 mm from both edges of the secondary coil.","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":"134240633","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

Propulsion Assisting Roads for Driving Range Extension of Electric Vehicles 助力电动汽车续驶里程的道路推进

2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490182

V. Kuptsov, P. Fajri, Md. Rasheduzzaman, M. Shadmand

引用次数: 0

Integration of Electric Vehicle Load and Charging Infrastructure in Distribution Network 配电网中电动汽车负荷与充电基础设施的集成

2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490169

Vivienne Hui Fan, K. Meng, Zhaoyang Dong

{"title":"Integration of Electric Vehicle Load and Charging Infrastructure in Distribution Network","authors":"Vivienne Hui Fan, K. Meng, Zhaoyang Dong","doi":"10.1109/ITEC51675.2021.9490169","DOIUrl":"https://doi.org/10.1109/ITEC51675.2021.9490169","url":null,"abstract":"While road electrification offers economic and environmental advantages, the non-conventional load due to electric vehicles usage and charging patterns pose challenges to distribution systems. The strategic design of charging infrastructure is becoming an essential element to facilitate power system planning and decision-making process. This paper presents a probabilistic method to derive charging patterns and estimate the electric vehicle demand profiles under uncertainty and variability. We apply a Gaussian copula to capture correlations between the key multivariates. We investigate the optimal location and size of charging stations based on queueing theory and intercepted traffic flow model. We examine the impact of the charging demand occurred in residential and public area on distribution expansion investment and incremental operational cost. The feasibility of the approach is tested on an interconnected distribution grid and transportation system. The case studies show that a careful probabilistic analysis of the randomness intrinsic to the charging behavior is of great importance to define and implement an integrated power and transportation system design.","PeriodicalId":339989,"journal":{"name":"2021 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"36 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":"134361226","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

Reluctance Mesh-Based Modeling of Switched Reluctance Machines 基于磁阻网格的开关磁阻电机建模

2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490134

Gayan Watthewaduge, Ehab Sayed, A. Emadi, B. Bilgin

引用次数: 1

Accurate Surface Temperature Estimation of Lithium-Ion Batteries Using Feedforward and Recurrent Artificial Neural Networks 基于前馈和循环神经网络的锂离子电池表面温度精确估计

2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490043

Mina Naguib, P. Kollmeyer, Carlos Vidal, A. Emadi

{"title":"Accurate Surface Temperature Estimation of Lithium-Ion Batteries Using Feedforward and Recurrent Artificial Neural Networks","authors":"Mina Naguib, P. Kollmeyer, Carlos Vidal, A. Emadi","doi":"10.1109/ITEC51675.2021.9490043","DOIUrl":"https://doi.org/10.1109/ITEC51675.2021.9490043","url":null,"abstract":"Lithium-ion batteries are an essential component in electric vehicles. A robust battery management system (BMS) must be able to estimate the battery states including state of charge (SOC), state of health (SOH), and, ideally, battery temperature as well. The cells in the pack may experience significant temperature differences during operation, and this would typically be monitored by a multitude of temperature sensors. A surface temperature estimation model can be used to reduce the number of sensors necessary for a pack, which has the side benefit of reducing cost and potentially increasing reliability. In this paper, two data-driven models are proposed to estimate the surface temperature of Li-ion batteries. The first model is based on a feed-forward neural network (FNN), while the second model is based on a recurrent neural network (RNN) with long short-term memory (LSTM). These models are trained and tested using cylindrical cell drive cycle data at a range of temperatures. The LSTM model is shown to be capable of estimating temperature with no more than a few degrees Celsius of error, even for challenging low temperature and varying temperature conditions.","PeriodicalId":339989,"journal":{"name":"2021 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"252 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":"134415425","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

A Hybrid Time-Efficient Modeling Approach for Acoustic Noise Prediction in SRMs 一种混合时间效率建模方法用于srm的噪声预测

2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490075

Ziyan Zhang, Zichao Jin, Chengxiu Chen, Selin Yaman, M. Krishnamurthy

引用次数: 0

Peukert's Law for Lithium-ion Capacitors With Constant Power Loads 恒功率负载下锂离子电容器的Peukert定律

2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490096

Hengzhao Yang

引用次数: 1