2023 IEEE Transportation Electrification Conference & Expo (ITEC)最新文献_第3页

An EV Integrated Bidirectional DC Fast Charger based on a Dual Wound Synchronous Machine 基于双绕组同步电机的电动汽车集成双向直流快速充电器

2023 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2023-06-21 DOI: 10.1109/ITEC55900.2023.10186963

S. S. Ghumman, P. Lehn

引用次数: 0

Experimental Study of Magnetic Field Effect on Multi-Rotor Drones Operation in Autonomous Power Line Inspection 多旋翼无人机自主巡检中磁场效应的实验研究

2023 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2023-06-21 DOI: 10.1109/ITEC55900.2023.10187002

Shervin Salehi Rad, R. Kheirollahi, Shuyan Zhao, Amr Mostafa, Zilong Zheng, Yao Wang, Hua Zhang, Gary Friedman, F. Lu

{"title":"Experimental Study of Magnetic Field Effect on Multi-Rotor Drones Operation in Autonomous Power Line Inspection","authors":"Shervin Salehi Rad, R. Kheirollahi, Shuyan Zhao, Amr Mostafa, Zilong Zheng, Yao Wang, Hua Zhang, Gary Friedman, F. Lu","doi":"10.1109/ITEC55900.2023.10187002","DOIUrl":"https://doi.org/10.1109/ITEC55900.2023.10187002","url":null,"abstract":"This digest studies the effects of the magnetic field on multi-rotor drones (MR-drones) used for alternating current (AC) transmission line inspections. Although MR-drones are used for fast and accurate monitoring of the powerlines, there are many difficulties to deliver this task. In this digest, a DJI MA VIC Pro2 MR-drone is employed to study the effects of changing magnetic fields on the drone's built-in magnetometer sensors. The DJI MR-drone is tested under two different levels of magnetic field strength. For this purpose, two sets of experiments are conducted including a solenoid with 350 turns and a large coil with 49 turns. The amplitude of the sinusoidal current injected into the solenoid is about 30 A, where the corresponding magnetic field strength is 1800 µT from a 10 cm distance. Also, the amplitude of the sinusoidal current that is inj ected into the larger coil is 63.34 A, with a magnetic field strength of 2500 µT from a 10 cm distance. The DJI MR data that is recorded by magnetometer sensors are analyzed.","PeriodicalId":234784,"journal":{"name":"2023 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116986479","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

Intelligent Multi-Vehicle DC/DC Charging using an Active Response Management (ARM) 基于主动响应管理(ARM)的智能多车DC/DC充电

2023 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2023-06-21 DOI: 10.1109/ITEC55900.2023.10187028

Michéle Weisbach, H. Fechtner, U. Spaeth, A. Popp, B. Schmuelling

引用次数: 0

Single Stage Cascaded H-bridge Topology Based Power Electronic Traction Transformer 基于单级级联h桥拓扑的电力电子牵引变压器

2023 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2023-06-21 DOI: 10.1109/ITEC55900.2023.10187088

Adnan Farooq Khan, S. Nag, Bhim Singh

{"title":"Single Stage Cascaded H-bridge Topology Based Power Electronic Traction Transformer","authors":"Adnan Farooq Khan, S. Nag, Bhim Singh","doi":"10.1109/ITEC55900.2023.10187088","DOIUrl":"https://doi.org/10.1109/ITEC55900.2023.10187088","url":null,"abstract":"Power electronic transformer (PET) technology shows great promise for medium to high power conversion systems especially in traction systems. Conventional power electronic traction transformer or solid-state transformer (PETT/SST) for railway traction application has two stage operation: ac-dc that is performed by hard switched active front end (AFE) based on cascaded H-bridges (CHBs) followed by isolated dc-dc converter and a three-phase inverter connecting to the traction motor. This paper presents a novel multilevel architecture that employs a single-stage conversion topology for every module, combining the AC-DC and DC-DC stages into a unified single-stage architecture. The modules are connected in series at the input to form a multilevel topology. The converter is controlled using sine pulse width modulation (SPWM) and phase shift control, which enables the topology to operate at unity power factor (UPF) on the grid side, with bidirectional power flow. The proposed single-stage topology results in a reduction of the switch count in each module, which enhances reliability. Additionally, all switches operate using zero voltage switching (ZVS). The paper outlines the operating principle and analysis of the single-stage module, which forms the basis of the proposed topology. Additionally, the converter is designed for a 4.5 kW rating and the operation of the converter is validated through simulation.","PeriodicalId":234784,"journal":{"name":"2023 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123942617","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

Hybrid Neural Sliding Mode Observer for Speed-Sensor less Control of Induction Motor 异步电机无速度传感器控制的混合神经滑模观测器

2023 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2023-06-21 DOI: 10.1109/ITEC55900.2023.10187090

M. Babaie, M. A. Khoshhava, M. Abarzadeh, H. Mosaddegh, Simon Caron, K. Al-haddad

{"title":"Hybrid Neural Sliding Mode Observer for Speed-Sensor less Control of Induction Motor","authors":"M. Babaie, M. A. Khoshhava, M. Abarzadeh, H. Mosaddegh, Simon Caron, K. Al-haddad","doi":"10.1109/ITEC55900.2023.10187090","DOIUrl":"https://doi.org/10.1109/ITEC55900.2023.10187090","url":null,"abstract":"The state of the art demonstrates that Sliding Mode-based Observers (SMO) can effectively meet the speed-sensorless control requirements of induction machines. Even so, parametric uncertainties adversely affect the switching operation of the SMO and intensify the chattering, which appears as variable frequency noises in the observed speed. The chattering stimulates the ignored high-frequency dynamics of the system and leads to poor control performance and instability of the drive system under dynamic conditions. Concerning this issue, an appropriate filtering strategy is required to filter out the chattering in the SMO-based sensorless control of induction machines. However, filtering limits the bandwidth of the speed observer and weakens the dynamic performance of the controller and drive. To address this issue, a novel hybrid Neural Sliding Mode Observer (NSMO) is proposed and developed in this paper. In the NSMO, an artificial neural network is effectively trained to estimate a chattering-free speed signal based on the stator currents, reference speed, and observed rotor flux. In addition, the proposed NSMO is not sensitive to the motor parameters variation, thanks to the model-free structure of the ANN-based speed observer. In the end, the simulation results of various dynamic and comparative test scenarios performed by MATLAB verify the superiority of the proposed technique over an SMO technique.","PeriodicalId":234784,"journal":{"name":"2023 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124834573","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

Heating-cooperative Charging of Lithium-ion Batteries at Low Temperatures 低温下锂离子电池的加热协同充电

2023 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2023-06-21 DOI: 10.1109/ITEC55900.2023.10187065

Xiangfeng Meng, Xin Xu, Zhongbao Wei

引用次数: 0

Machine Learning-based Energy Consumption models for Battery Electric Trucks 基于机器学习的纯电动卡车能耗模型

2023 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2023-06-21 DOI: 10.1109/ITEC55900.2023.10187000

Emmanuel Hidalgo Gonzalez, Jacqueline Garrido, M. Barth, K. Boriboonsomsin

{"title":"Machine Learning-based Energy Consumption models for Battery Electric Trucks","authors":"Emmanuel Hidalgo Gonzalez, Jacqueline Garrido, M. Barth, K. Boriboonsomsin","doi":"10.1109/ITEC55900.2023.10187000","DOIUrl":"https://doi.org/10.1109/ITEC55900.2023.10187000","url":null,"abstract":"Efforts to transition the heavy-duty vehicle sector from conventional diesel trucks to battery electric trucks (BETs) have generated vast interest in understanding the energy demand of heavy-duty BETs. Microscopic models are commonly used for modeling vehicle energy consumption during powertrain design and evaluation as they are very accurate. However, these models involve a number of input parameters and require high-resolution data for many of those inputs (e.g., second-by-second speed, acceleration, and road grade profiles). This level of input data may not be readily available, for example, when modeling energy consumption of multiple vehicles or for a large number of drive cycles. Mesoscopic models offer a practical alternative as the inputs needed, such as average traffic speed and road grade on a link-by-link basis, can be obtained more easily. This paper presents the development of mesoscopic energy consumption models for BETs using both real-world and microscopically simulated BET energy consumption datasets. A machine learning technique called random forest (RF) regressor was applied to the datasets to fit models. The results show that the RF regressor outperforms the classical linear regressor as evidenced by the resulting models having higher R2 values. When applied to the simulated dataset, the RF regressor can capture the behaviors of BET energy consumption well, where the R2 values of the resulting models are 0.86-0.89. When applied to the real-world dataset, the R2 values of the resulting models are only 0.50-0.52 as a large portion of the variance in the real-world dataset (e.g., cargo weight) is not captured.","PeriodicalId":234784,"journal":{"name":"2023 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127350351","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

Design Considerations of DC/DC Regulator for High-Power Dynamic Wireless Charging Systems 大功率动态无线充电系统中DC/DC稳压器的设计考虑

2023 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2023-06-21 DOI: 10.1109/ITEC55900.2023.10186894

Lingxiao Xue, G. Su, V. Galigekere, O. Onar, Mostak Mohammad

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Anomaly Detection for Connected and Automated Vehicles: Accident Analysis 联网和自动驾驶车辆的异常检测:事故分析

2023 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2023-06-21 DOI: 10.1109/ITEC55900.2023.10187080

Mansi Girdhar, Junho Hong, Yongsik You, T. Song

{"title":"Anomaly Detection for Connected and Automated Vehicles: Accident Analysis","authors":"Mansi Girdhar, Junho Hong, Yongsik You, T. Song","doi":"10.1109/ITEC55900.2023.10187080","DOIUrl":"https://doi.org/10.1109/ITEC55900.2023.10187080","url":null,"abstract":"Smart mobility is a key component of smart cities, and the switch from traditional automotive systems to connected and automated vehicles (CAVs) is recognized as one of the evolving technologies on urban roads. Although the current autonomous vehicle (AV) mobility environment may be geared toward infrastructure and road users, it cannot facilitate the adoption of CAV in the future due to the presence of different modules that are nested in the cyberspace. Furthermore, the ability to make accurate decisions in real-time is essential for the success of autonomous systems. However, cyberattacks on these entities might skew the decision-making processes, which can result in complex CAV mishaps. Furthermore, the method utilized by the police to conduct accident investigations cannot be used to identify road accidents brought on by cyberattacks. Therefore, this paper proposes a 5Ws & 1H-based investigation approach to deal with cyberattack-related accidents. Also, a stochastic anomaly detection system is proposed to identify the abnormal activities of the automated driving system (ADS) functions during a crash analysis. Further, two case studies are shown to validate the results of the proposed algorithms.","PeriodicalId":234784,"journal":{"name":"2023 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125524869","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

Complex Vector Current Regulation Strategy for a High-Speed Doubly Salient Machine with Stator PMs 高速双凸极定子永磁电机的复杂矢量电流调节策略

2023 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2023-06-21 DOI: 10.1109/ITEC55900.2023.10186990

C. S. Goli, S. Essakiappan, D. Ionel, J. Gafford, M. Manjrekar

{"title":"Complex Vector Current Regulation Strategy for a High-Speed Doubly Salient Machine with Stator PMs","authors":"C. S. Goli, S. Essakiappan, D. Ionel, J. Gafford, M. Manjrekar","doi":"10.1109/ITEC55900.2023.10186990","DOIUrl":"https://doi.org/10.1109/ITEC55900.2023.10186990","url":null,"abstract":"A complex vector current (CVC) regulation strategy for a high-power density doubly-salient special machine with 12 modular concentrated coils and 12 PMs in the stator and 10 pole protrusions in the rotor is presented in this digest. The special machine has been designed to operate at a rated torque of 41Nm at a base speed of 5000RPM. A plant model of the special machine has been developed using FEA software. The phase flux linkage and inductance have substantial variations with the rotor position and therefore variations and possible errors are expected for the estimation of d-q inductances. Classical current regulation strategy in synchronous reference frame with or without decoupling is not capable of stable operation if uncertainty in the estimation of d-q inductances has been considered to determine proportional and integral constants of the controller. Thus, considering a wide range of uncertainty in the estimation of d-q inductances, the CVC regulation strategy has been employed for this special machine. A comparative analysis of classical and CVC regulation strategies has been presented in this digest for both maximum torque per ampere and field weakening control regimes to regulate the torque or speed over a wide range for electric vehicle traction applications. A detailed stability analysis reveals that the CVC regulation strategy is more robust compared to the classical proportional integral current regulation strategy in synchronous reference frame with decoupling. The performance of these two current regulation strategies has been validated by simulations in continuous domain and verified by employing controller hardware in the loop (CHIL).","PeriodicalId":234784,"journal":{"name":"2023 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123351045","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