Fauzia Khanum, Eduardo Louback, Federico Duperly, Colleen Jenkins, P. Kollmeyer, A. Emadi
{"title":"A Kalman Filter Based Battery State of Charge Estimation MATLAB Function","authors":"Fauzia Khanum, Eduardo Louback, Federico Duperly, Colleen Jenkins, P. Kollmeyer, A. Emadi","doi":"10.1109/ITEC51675.2021.9490163","DOIUrl":"https://doi.org/10.1109/ITEC51675.2021.9490163","url":null,"abstract":"This paper proposes a Kalman filter based state-of-charge (SOC) estimation MATLAB function using a second-order RC equivalent circuit model (ECM). The function requires the SOC-OCV (open circuit voltage) curve, internal resistance, and second-order RC ECM battery parameters. Users have an option to use an extended Kalman filter (EKF) or adaptive extended Kalman filter (AEKF) algorithms as well as temperature dependent battery data. An example of the function is illustrated using the LA92 driving cycle of a Turnigy battery performed at multiple temperature ranging from −10°C to 40°C.","PeriodicalId":339989,"journal":{"name":"2021 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"18 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":"125322428","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}
{"title":"Identifying Hopf Bifurcations of Networked Microgrids Induced by the Integration of EV Charging Stations","authors":"X. Jiang, Yan Li, Liang Du, Daning Huang","doi":"10.1109/ITEC51675.2021.9490159","DOIUrl":"https://doi.org/10.1109/ITEC51675.2021.9490159","url":null,"abstract":"A continuation method considering the dynamics of distributed energy resources (DERs) is presented to identify Hopf bifurcations in the networked microgrids induced by the integration of electrical vehicle (EV) charging stations. The dynamic model of networked microgrids is developed for bifurcation analysis. An adaptive predictor-corrector approach is presented for inclusively searching for equilibrium points in the space of bifurcation parameters. Extensive numerical results have demonstrated and validated the prediction of the subcritical Hopf bifurcation, based on which corresponding control strategies can be employed to stabilize the system when necessary. These features make the continuation method an effective tool for determining the system's critical operations and providing early warnings.","PeriodicalId":339989,"journal":{"name":"2021 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"59 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":"123761654","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}
{"title":"High Fidelity Rapid Modeling of Hybrid Rotor PM Machines using Equivalent Machine Model","authors":"Dheeraj Bobba, B. Sarlioglu","doi":"10.1109/ITEC51675.2021.9490181","DOIUrl":"https://doi.org/10.1109/ITEC51675.2021.9490181","url":null,"abstract":"Machines that use a combination of rotor types, i.e., hybrid rotor machines, have additional degrees of freedom with rotor combinations and are shown to produce a wide array of operating characteristics with minimal design changes. However, the axial asymmetric nature of the hybrid rotor PM machines requires 3D finite element analysis (FEA) based modeling approach, which is time-consuming and computationally expensive despite the use of rotational and axial symmetry to reduce model size. This article aims to develop a faster analysis method that combines 2D FEA models with an analytical equivalent machine model of the hybrid rotor PMSM. The proposed analysis method is compared with 3D FEA to verify the accuracy and will be shown to significantly reduce the computation time while maintaining high fidelity.","PeriodicalId":339989,"journal":{"name":"2021 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"402 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":"116659695","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}
{"title":"Reliability Analysis of Shore-to-Ship Fast Charging Systems","authors":"S. Karimi, M. Zadeh, J. Suul, Christoph A. Thieme","doi":"10.1109/ITEC51675.2021.9490146","DOIUrl":"https://doi.org/10.1109/ITEC51675.2021.9490146","url":null,"abstract":"This paper presents a reliability assessment of Shore-to-Ship Sharging (S2SC) systems with focus on the two most common topologies of ac and dc charging. In the proposed reliability model, the Markov chain and reliability block diagrams are used to establish multi-state models of the system. In this regard, the state of system is defined as the maximum transferable charging power into the onboard batteries from shore which can be comprimised by the failure of the individual compoents. As the results of Markov chain analysis, the probability of the operation states and Mean Time to The First Failure (MTTFF) are calculated. Further, to clearify the impact of the failure of the individual compoents on the charigng mission, an application-specific failure threshold is defined. Subsequently, two relibility indices, namely, Loss of Charging Expectation (LOCE) and Derated Charging Expectation (DCE) are introduced and computed using the calculated prbability tables and the defined failure threshold. The results from conducting such analysis for two case studies with ac and dc S2SC systems, shows how the studied dc charging system is more reliable than its ac counterpart.","PeriodicalId":339989,"journal":{"name":"2021 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"101 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":"128088469","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}
{"title":"Battery Voltage Prediction Using Neural Networks","authors":"Di Zhu, Jeffrey Campbell, Gyouho Cho","doi":"10.1109/ITEC51675.2021.9490081","DOIUrl":"https://doi.org/10.1109/ITEC51675.2021.9490081","url":null,"abstract":"The battery voltage prediction is critical to model predictive controls for the safe and efficient operation of battery systems. This paper presents a comprehensive study using a long-short-term-memory-based method to predict the battery voltage with past voltage and forecasted current and SOC information. Unlike prior art using many-to-one architecture, a many-to-many architecture was used with test data representing three temperatures. Battery-controller-accessible inputs were also selected. Further, the effectiveness of normalization for voltage prediction was investigated. The results show the temperature has no noticeable impact on the prediction accuracy. The lowest RMSE obtained from the 0 °C case is 0.0997. With having both inputs and output already on a similar scale, applying data normalization didn't provide any consistent accuracy improvement across the three selected temperatures.","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":"132944305","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}
Lode De Herdt, A. Shekhar, Yu-Yuan Yu, G. C. Mouli, Jianning Dong, P. Bauer
{"title":"Power Hardware-in-the-Loop Demonstrator for Electric Vehicle Charging in Distribution Grids","authors":"Lode De Herdt, A. Shekhar, Yu-Yuan Yu, G. C. Mouli, Jianning Dong, P. Bauer","doi":"10.1109/ITEC51675.2021.9490098","DOIUrl":"https://doi.org/10.1109/ITEC51675.2021.9490098","url":null,"abstract":"A simple and low-cost Power Hardware-in-the-Loop (PHIL) demonstrator is developed for the purpose of studying the impact of Electric Vehicle (EV) charging on low voltage distribution grids. An energy saving power circulating method with potential bi-directional function is proposed in this study as well. The distribution grid under test runs on a Digital Real Time Simulator (DRTS), and a controlled 3-phase voltage at one of the nodes is formed using a power amplifier. The practical setup consists of Electric Vehicle Supply Equipment (EVSE) and a system which emulates the charging behaviour of an EV, referred to as an EV emulator. These are integrated using a 15 kW back to back ac-dc converter based power router. Structure, performance and limitations of the test-bed components, communication protocols and signal processing are discussed.","PeriodicalId":339989,"journal":{"name":"2021 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"47 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":"116986814","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}
Jan Kleiner, Lorenz Lechermann, L. Komsiyska, G. Elger, C. Endisch
{"title":"Thermal Effects of Bad-Block-Management in an Intelligent Automotive Lithium-ion Battery Module based on lumped 3D Electro-Thermal Modeling","authors":"Jan Kleiner, Lorenz Lechermann, L. Komsiyska, G. Elger, C. Endisch","doi":"10.1109/ITEC51675.2021.9490059","DOIUrl":"https://doi.org/10.1109/ITEC51675.2021.9490059","url":null,"abstract":"In conventional battery systems, single weak cells are limiting the overall performance or are critical for the battery's safety. In intelligent battery systems, reconfiguration enables the individual handling of single cells in the system by Bad-Block-Management (BBM). Thereby, the thermal situation within the battery is changed by the combination of the thermal influence by weak cells and the reconfiguration procedures by BBM. For an optimal reconfiguration strategy, multiple aspects need to be considered such as the cell individual parameters, safety state and position. In this work, the thermal effects of various BBM scenarios under electric vehicle conditions are investigated on the example of an intelligent lithium-ion module made of 12 prismatic cells. A hardware prototype of an intelligent module with switchable cells is investigated experimentally to quantify the effects of reconfiguration and provide validation data for the model development. The model is based on electro-thermal coupling of a 3D lumped thermal model and an equivalent circuit model of the cell with electronics and reconfiguration functionality. The model is used to investigate the temperature distribution with weaks cells within the module and the effects of several associated BBM procedures.","PeriodicalId":339989,"journal":{"name":"2021 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"1 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":"117149436","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}
Kevin Malena, C. Link, Sven Mertin, Sandra Gausemeier, A. Trächtler
{"title":"Validation of an Online State Estimation Concept for Microscopic Traffic Simulations◆◆Research supported by the Ministry of Economy, Innovation, Digitalization and Energy of North Rhine-Westphalia, Germany.","authors":"Kevin Malena, C. Link, Sven Mertin, Sandra Gausemeier, A. Trächtler","doi":"10.1109/ITEC51675.2021.9490087","DOIUrl":"https://doi.org/10.1109/ITEC51675.2021.9490087","url":null,"abstract":"This paper deals with a novel method for the online fitting of a microscopic traffic simulation model to the current state of a real world traffic area. The traffic state estimation is based on limited data of different measurement sources and guarantees general accordance of reality and simulation in terms of multimodal road traffic counts and vehicle speeds. The research is embedded in the challenge of improving the traffic by controlling the traffic light systems (TLS) of the examined area. Therefore, the current traffic state and the predicted route choices of individual road users are the matter of interest. The concept is generally transferable to any road traffic system. To give an impression of the accuracy and potential of the approach, the validation and first application results are presented.","PeriodicalId":339989,"journal":{"name":"2021 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"70 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":"126772318","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}
C. S. Goli, M. Manjrekar, S. Essakiappan, P. Sahu, Nakul Shah
{"title":"Landscaping and Review of Traction Motors for Electric Vehicle Applications","authors":"C. S. Goli, M. Manjrekar, S. Essakiappan, P. Sahu, Nakul Shah","doi":"10.1109/ITEC51675.2021.9490129","DOIUrl":"https://doi.org/10.1109/ITEC51675.2021.9490129","url":null,"abstract":"With increasing penetration of electric vehicles, electric motor technologies have also seen rapid evolution. This paper reviews and provides a landscape of several topologies of traction motors employed in electrical vehicle traction applications. An emphasis has been made to showcase trends in volumetric power density and gravimetric power density of traction motors since they directly affect end product weight, packaging, and efficiency. A study and classification of motor topologies based on permanent magnet use, the location of the permanent magnets inside the motor, magnetic and reluctance components of torque, and design trends in rotor and stator have been discussed. Several key Original Equipment Manufacturers (OEM) products have been used in this analysis and thus, the paper provides a useful reference for understanding the product evolution and forecasting future trends.","PeriodicalId":339989,"journal":{"name":"2021 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"107 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":"124126331","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}
{"title":"Thermal Stress Oriented Dispatch Strategy for Paralleled Grid-Connected Converters in Electric Vehicle Charging Stations","authors":"Luocheng Wang, Linquan Bai, Tiefu Zhao","doi":"10.1109/ITEC51675.2021.9490172","DOIUrl":"https://doi.org/10.1109/ITEC51675.2021.9490172","url":null,"abstract":"The severe thermal stress is justified to be one major failure cause in power semiconductor devices. Most of the previous thermal stress reduction methods only scope on the local controller level for the individual converter. In the proposed method, a centralized system level strategy is designed to deal with the varying charging profiles in the electric vehicle charging station, where the proposed dispatch algorithm makes full use of the local control level thermal stress reduction methods, including the reactive power injection and the switching frequency variation, to adjust the power loss and reshape the thermal profiles for multiple grid-connected converters. The proposed thermal stress oriented dispatch (TSOD) strategy is described in this paper and its superior performance on the junction temperature profiles is validated through a real-time model-in-the-loop testing and a digital twin experimental prototype.","PeriodicalId":339989,"journal":{"name":"2021 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"42 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":"121552894","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}