2021 IEEE Transportation Electrification Conference & Expo (ITEC)最新文献_第3页

Comparison of Model Predictive Control strategies on PMSM based Electric Power Steering system 基于永磁同步电机的电动助力转向系统模型预测控制策略比较

2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490048

Chang Zhang, Jian Shi

引用次数: 0

Analyzing Power Quality Implications of High Level Charging Rates of Electric Vehicle Within Distribution Networks 配电网内电动汽车高充电率对电能质量的影响分析

2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490166

A. Soofi, Reza Bayani, Saeed D. Manshadi

引用次数: 7

Acoustic Noise and Vibration of an Interior Permanent Magnet Traction Motor: PWM Effect 内置式永磁牵引电机的噪声与振动:PWM效应

2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490156

Nathan Emery, Yawei Wang, D. Al-Ani, B. Bilgin

引用次数: 3

Comparative economic analysis between LTO and C-ion energy storage system for electric vehicles ultra-fast charger buffering application LTO与c离子储能系统在电动汽车超快充电器缓冲应用中的经济性比较分析

2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490173

N. Sockeel, J. Gafford, M. Manjrekar, M. Mazzola

{"title":"Comparative economic analysis between LTO and C-ion energy storage system for electric vehicles ultra-fast charger buffering application","authors":"N. Sockeel, J. Gafford, M. Manjrekar, M. Mazzola","doi":"10.1109/ITEC51675.2021.9490173","DOIUrl":"https://doi.org/10.1109/ITEC51675.2021.9490173","url":null,"abstract":"Due to the growth of the electric vehicle (EV) market and the extension of EVs battery range, the demand for ultra-fast charging is expected to increase. However, ultra-fast charging causes extreme high peak load demand, going beyond the capabilities of current electric utility infrastructure in many location. A high power energy storage system has the ability to off-set such infrastructure power limitations. On top of providing the energy of an EV battery and peak load demands, the decisive metrics for such system are cost of ownership and longevity. The main contribution of this article is to update a previous developed approach to evaluate the economic plausibility of an energy storage system (ESS) solution for EVs ultra-fast charger buffering application. This approach considers the calendar and cycling aging of the energy storage system, the overall efficiency, OPEX, and CAPEX of the ultra-fast charger, but also the purchasing price of the grid electricity. Furthermore, this approach is used to compare the highest longevity lithium battery technology solution, named LTO, to a new super capacitor solution contender, named C-ion. The findings of this study show that both LTO and C-ion technology may represent a cheaper alternative than refueling a gasoline car.","PeriodicalId":339989,"journal":{"name":"2021 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"16 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":"121405695","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 Robust Non-Permanent Magnet Five-Phase Synchronous Reluctance Traction Motor 鲁棒非永磁五相同步磁阻牵引电机

2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490116

Zhiwei Zhang

引用次数: 1

Dual Functional Power Management System for an Energy Storage in Light Fuel-Cell Hybrid Electric Vehicles 轻型燃料电池混合动力汽车储能双功能电源管理系统

2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490183

Taehyung Kim

{"title":"Dual Functional Power Management System for an Energy Storage in Light Fuel-Cell Hybrid Electric Vehicles","authors":"Taehyung Kim","doi":"10.1109/ITEC51675.2021.9490183","DOIUrl":"https://doi.org/10.1109/ITEC51675.2021.9490183","url":null,"abstract":"This paper presents a new dual functional control system for an energy storage in a light fuel-cell electric vehicle such as a small motor cycle and an electric cart. The proposed control system manages charging and discharging of an energy storage and regulate two bus voltages at the same time to minimize the number of circuit elements in the system. Since a fuel-cell voltage varies based on the load, a boost converter needs to be employed in the proposed system to provide a 48V DC power to a traction inverter for this light vehicle application. An additional voltage bus which can be higher or lower than the input fuel cell voltage is added for other electric loads. The new dual functional controller is employed for this system to control two different output voltages and manage a battery at the same time. Through the effort of the dual functional control system, one switching element and one inductor can be removed while keeping the same functionality. The proposed dual-functional control strategy and the converter structure are explained in detail first. Then, the feasibility of the converter is verified by experiments.","PeriodicalId":339989,"journal":{"name":"2021 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"29 2 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":"126090465","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

System-Level Modeling and Virtual Testing of Fuel Cell Vehicle Mobypost Using Energetic Macroscopic Representation 基于能量宏观表征的燃料电池车桥系统级建模与虚拟测试

2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490044

Hao Bai, Chen Liu, D. Chrenko, A. Ravey, F. Gao

引用次数: 1

Fast Charging Li-Ion Battery Capacity Fade Prognostic Modeling Using Correlated Parameters' Decomposition and Recurrent Wavelet Neural Network 基于相关参数分解和循环小波神经网络的快充锂离子电池容量衰减预测建模

2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490177

Asadullah Khalid, A. Sarwat

{"title":"Fast Charging Li-Ion Battery Capacity Fade Prognostic Modeling Using Correlated Parameters' Decomposition and Recurrent Wavelet Neural Network","authors":"Asadullah Khalid, A. Sarwat","doi":"10.1109/ITEC51675.2021.9490177","DOIUrl":"https://doi.org/10.1109/ITEC51675.2021.9490177","url":null,"abstract":"Continuous cycling of Lithium-Ion (Li-ion) batteries, as required by applications, degrades their resulting capacities over time. This degradation is generally negligible in the early charge/discharge cycles. An increase in charging/discharging rates (C-rate) applied on a continuous cycling battery reduces its charging time, thereby resulting in a fast charging battery, however, this also escalates the degradation. This degradation can be studied from the resultant decrease in charging/discharging capacities, also termed as capacity fade. To analyze capacity fade, an approach using reference C-rate based charging/discharging capacity analysis is proposed for a time-limited degradation analysis. Further, a step-ahead forecasting approach is proposed for all the charging/discharging capacities' correlated original, and corresponding deviation parameters, to present time-ahead modeling of all the impacted parameters. A combinatorial empirical mode decomposition (EMD)-recurrent wavelet neural network (RWNN) model is proposed as the step-ahead forecasting approach for the correlated parameters. Finally, a comparison of error values between the proposed EMD-RWNN model is performed with combinatorial EMD-wavelet neural network (WNN), standalone WNN and RWNN models to effectively analyze the resulting superior performance of the recurrent nature of the proposed model by forecasting every decomposition.","PeriodicalId":339989,"journal":{"name":"2021 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"60 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":"132131073","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

Battery Voltage Prediction Using Neural Networks 基于神经网络的电池电压预测

2021 IEEE Transportation Electrification Conference & Expo (ITEC) Pub Date : 2021-06-21 DOI: 10.1109/ITEC51675.2021.9490081

Di Zhu, Jeffrey Campbell, Gyouho Cho

引用次数: 1

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