T. Huria, Massimo Ceraolo, Javier Gazzarri, Robyn A. Jackey
{"title":"High fidelity electrical model with thermal dependence for characterization and simulation of high power lithium battery cells","authors":"T. Huria, Massimo Ceraolo, Javier Gazzarri, Robyn A. Jackey","doi":"10.1109/IEVC.2012.6183271","DOIUrl":"https://doi.org/10.1109/IEVC.2012.6183271","url":null,"abstract":"The growing need for accurate simulation of advanced lithium cells for powertrain electrification demands fast and accurate modeling schemes. Additionally, battery models must account for thermal effects because of the paramount importance of temperature in kinetic and transport phenomena of electrochemical systems. This paper presents an effective method for developing a multi-temperature lithium cell simulation model with thermal dependence. An equivalent circuit model with one voltage source, one series resistor, and a single RC block was able to account for the discharge dynamics observed in the experiment. A parameter estimation numerical scheme using pulse current discharge tests on high power lithium (LiNi-CoMnO2 cathode and graphite-based anode) cells under different operating conditions revealed dependences of the equivalent circuit elements on state of charge, average current, and temperature. The process is useful for creating a high fidelity model capable of predicting electrical current/voltage performance and estimating run-time state of charge. The model was validated for a lithium cell with an independent drive cycle showing voltage accuracy within 2%. The model was also used to simulate thermal buildup for a constant current discharge scenario.","PeriodicalId":134818,"journal":{"name":"2012 IEEE International Electric Vehicle Conference","volume":"41 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114123795","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":"Sensitivity analysis on frequency characteristics of a fuel cell-electrical double layer capacitor hybrid power source system","authors":"N. Katayama, K. Tanaka, S. Kogoshi","doi":"10.1109/IEVC.2012.6183269","DOIUrl":"https://doi.org/10.1109/IEVC.2012.6183269","url":null,"abstract":"Polymer electrolyte membrane fuel cells (PEMFCs) attract much attention as next generation energy sources. To prolong durability of PEMFCs, which is one of the present challenges, we have developed a fuel cell-electrical double layer capacitor hybrid power source system to maintain the fuel cell current to a constant value, and investigated dynamic response with investigating relationship between load current changing and fuel cell current disturbance in our previous studies. In the present study sensitivity of circuit parameters on the frequency characteristics, which indicate dynamic response of the proposed FC-EDLC hybrid power system with developed multi-port bidirectional DC-DC converter has been analyzed by using numerical simulation. The model circuit parameters are set based on actual circuit's parameters. We chose electric capacitance and ESR of EDLCs and inductance of the EDLC port of the converter as parameters for analysis. The range of the electric capacitance of the EDLCs is from 1.12 mF to 56.0 F, the ESR of the EDLCs is from 70 mΩ to 1750 mΩ, and the inductance of the EDLC port is from 12.5 μH to 1250 μH. The simulation result yield the following conclusion: excessive electric capacitance of the EDLCs give no influence on the frequency characteristic, whereas decreasing electrical capacitance of the EDLCs leads to lower response speed of the power source system; reducing the ESR makes the response of the power source system better at the lower frequency than near 100 Hz, but when the ESR is 70 mΩ the stability of the system could become worse; the inductance of the EDLC port mainly affect the characteristic in the frequency range from 100 Hz to 1 kHz.","PeriodicalId":134818,"journal":{"name":"2012 IEEE International Electric Vehicle Conference","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114218045","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":"Finding minimum-cost paths for electric vehicles","authors":"Timothy M. Sweda, D. Klabjan","doi":"10.1109/IEVC.2012.6183286","DOIUrl":"https://doi.org/10.1109/IEVC.2012.6183286","url":null,"abstract":"Modern route-guidance software for conventional gasoline-powered vehicles does not consider refueling since gasoline stations are ubiquitous and convenient in terms of both accessibility and use. The same technology is insufficient for electric vehicles (EVs), however, as charging stations are much more scarce and a suggested route may be infeasible given an EV's initial charge level. Recharging decisions may also have significant impacts on the total travel time and longevity of the battery, which can be costly to replace, so they must be considered when planning EV routes. In this paper, the problem of finding a minimum-cost path for an EV when the vehicle must recharge along the way is modeled as a dynamic program. It is proven that the optimal control and state space are discrete under mild assumptions, and two different solution methods are presented.","PeriodicalId":134818,"journal":{"name":"2012 IEEE International Electric Vehicle Conference","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114372459","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":"Supervisory control of Plug-in Hybrid Electric Vehicle with hybrid dynamical system","authors":"H. Banvait, Jianghai Hu, Yaobin Chen","doi":"10.1109/IEVC.2012.6183215","DOIUrl":"https://doi.org/10.1109/IEVC.2012.6183215","url":null,"abstract":"In this paper, a supervisory control of Plug-in Hybrid Electric Vehicles (PHEVs) using hybrid dynamical systems theory is presented. In hybrid dynamical systems, the state trajectories are described by both differential equations and discrete transitions. A PHEV has different operating modes which are modelled in the hybrid dynamical systems framework, simulated and analyzed. Furthermore, a constrained optimization problem to minimize energy used by PHEV is formulated. Finally, dynamic programming is used to minimize energy consumption. The obtained results are studied to evaluate the performance of supervisory control and hybrid dynamical system.","PeriodicalId":134818,"journal":{"name":"2012 IEEE International Electric Vehicle Conference","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114990496","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":"Quality of service in Plug-in Electric Vehicle charging infrastructure","authors":"M. Erol-Kantarci, J. Sarker, Hussein T. Mouftah","doi":"10.1109/IEVC.2012.6183227","DOIUrl":"https://doi.org/10.1109/IEVC.2012.6183227","url":null,"abstract":"Electrification of transportation is offering reduced vehicle emissions and operating costs in addition to increased energy-independence. Electric cars are anticipated to be adopted as passenger vehicles and in commercial fleets in the near future. Plug-in Hybrid Electric Vehicles (PHEVs) can drive on battery up to few hundred miles with the current battery technologies. Depleting PHEV batteries are charged from the power grid either with a Level 1 or Level 2 charger where the latter delivers more power than the former. Despite the advantages of PHEVs, charging several PHEVs simultaneously from the same distribution system may cause local outages due to transformer overloading. Thus, PHEV charging infrastructure calls for admission control schemes that operate on the smart grid. It is also essential to provide service differentiation to increase consumer satisfaction. In this paper, we propose a Quality of Service (QoS)-aware admission control scheme for the PHEV charging infrastructure. Our scheme operates on the Energy Management System (EMS) of the smart grid distribution system. The proposed approach relies on a wireless communication network that delivers the demands of PHEVs to the EMS and delivers the admission decisions of EMS to PHEVs. In our admission control scheme, PHEV owners who are willing to pay more can charge faster than the “best-effort” users similar to the Internet traffic service differentiation mechanisms. We provide mathematical analysis and simulation results for the proposed scheme. We show that high priority PHEVs are supplied with higher power rating, hence they are able to charge faster than low priority PHEVs.","PeriodicalId":134818,"journal":{"name":"2012 IEEE International Electric Vehicle Conference","volume":"196 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132226399","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":"An approach to develop location-based efficiency systems without real test drives","authors":"T. Ganslmeier, M. Kellner, B. Bruegge","doi":"10.1109/IEVC.2012.6183278","DOIUrl":"https://doi.org/10.1109/IEVC.2012.6183278","url":null,"abstract":"The development of intelligent vehicle systems based on non-deterministic input signals of the environment, have a dramatically increased complexity. Real test drives are no longer adequate to cover all test-cases, due to costs and complexity. One way to meet this challenge is a simulated test drive. In this case the driver, the environment and the vehicle are described within simulation models. Scenarios can be reproduced exactly. Tests can be executed automatically. Based on realistic road networks, realistic positioning data can be simulated. This allows development and testing of location-based systems. Especially for electric vehicles location-based systems are of great importance. We developed a simulation framework which represents the three domains (vehicle, driver and environment) within a closed-loop simulation. Using the framework we are able to execute simulated test-drives. In order to confirm the significance of the simulated test drive for the development, we validate the quality of the simulation results with data recorded on an electric vehicle fleet test. The architecture enables to reproduce a real test drive within a closed loop simulation.","PeriodicalId":134818,"journal":{"name":"2012 IEEE International Electric Vehicle Conference","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128287464","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":"A Simulated System of Battery-Management-System to test Electric Vehicles Charger","authors":"Xiangwu Yan, Wei Li, Jiancheng Gu, Xiangning Xiao","doi":"10.1109/IEVC.2012.6183197","DOIUrl":"https://doi.org/10.1109/IEVC.2012.6183197","url":null,"abstract":"This paper presents the implementation of a Simulated System of Battery-Management-System (SS-BMS) based on a computer with CAN communication interface to test the Electric Vehicles (EV) Charger. The SS-BMS includes the mathematical models to simulate the electrical and thermal properties of power battery, provides users with defining a variety of mode to simulate different charging circumstances and real-time information, such as single voltage, single temperature and state of charge (SOC) estimation by taking real-time charging current into account. With the SS-BMS, it is able to make the testing process more controllable and the results more reliable.","PeriodicalId":134818,"journal":{"name":"2012 IEEE International Electric Vehicle Conference","volume":"200 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133878742","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":"Inductive power transfer for electric vehicles: Potential benefits for the distribution grid","authors":"S. Mohagheghi, B. Parkhideh, S. Bhattacharya","doi":"10.1109/IEVC.2012.6183266","DOIUrl":"https://doi.org/10.1109/IEVC.2012.6183266","url":null,"abstract":"It is believed that the latest advances in battery and converter technology, along with government mandates on energy independence and resilience, will pave the way for higher deployment of electric vehicles in the transportation fleet. These vehicles, when equipped with bidirectional energy transfer capabilities, can function as mobile energy resources and be utilized in a vehicle-to-grid (V2G) scheme to temporarily inject energy back into the power grid. The forecasted increase in the number of these vehicles can turn them into a considerable energy resource to be used by the utilities as ancillary services or even for long-term integration with the grid. The energy injection into the power system by electric vehicles has been investigated in the literature for charging stations or single residential charging devices. The need for the vehicle to be stationary during the transfer, and the possible drive and/or change in the driving route in order to go the station are some of the hurdles that may lead to inconvenience and hence lower V2G participation by the vehicle drivers. Moreover, the need for an electrical connection between the vehicle and the station makes implementing remote supervisory control schemes difficult, if not impractical. However, with the advent of inductive charging systems for contactless transfer of energy, new horizons have been opened for seamless integration of these resources of energy into the distribution grid. This paper focuses on the applications of inductive power transfer systems for V2G purposes in the modern distribution grid. It will be shown here that such a scheme could potentially allow for supervisory control and management of the mobile energy resources with the ultimate goal of improving the reliability and security of the power grid without the need for capacity expansion.","PeriodicalId":134818,"journal":{"name":"2012 IEEE International Electric Vehicle Conference","volume":"43 8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127126570","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":"Driving pattern identification for EV range estimation","authors":"Hai Yu, F. Tseng, R. McGee","doi":"10.1109/IEVC.2012.6183207","DOIUrl":"https://doi.org/10.1109/IEVC.2012.6183207","url":null,"abstract":"This paper presents a driving pattern recognition method based on trip segment clustering. Driving patterns categorize various driving behaviors that contain certain energy demand property in common. It can be applied to various applications including intelligent transportation, emission estimation, passive/active safety controls and energy management controls. In this paper, pattern features are first identified from high impact factors from static and quasi-static environmental and traffic information. A feature based trip/route partitioning algorithm is then developed based on data clustering methods. The driving patterns are finally recognized by synthesizing all partitioned feature zones along the trip/route where each partitioned road section is distinguished by an attribute of feature combination that will result in a distinctive drive energy demand property. The driving pattern recognition is a critical technology especially in solving problems like range estimation and energy consumption preplanning for the plug-in capable electrified vehicles.","PeriodicalId":134818,"journal":{"name":"2012 IEEE International Electric Vehicle Conference","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129105683","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":"Distributed self organising Electric Vehicle charge controller system: Peak power demand and grid load reduction with adaptive EV charging stations","authors":"U. Reiner, C. Elsinger, T. Leibfried","doi":"10.1109/IEVC.2012.6183277","DOIUrl":"https://doi.org/10.1109/IEVC.2012.6183277","url":null,"abstract":"Previous Simulations showed that non-controlled Electric Vehicle (EV) charging can cause critical grid situations such as voltage sag and line overloads. Today's EV charging stations mostly support uncontrolled charging; hereby the charging process is not adapted to the grid situation which could avoid grid stress or outages. As the increasing rollout of EVs is expected in the near future, grid capacity surveillance and control systems are required. Following the function of a distributed charging system is described which is able to cope with the named grid challenges.","PeriodicalId":134818,"journal":{"name":"2012 IEEE International Electric Vehicle Conference","volume":"189 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124319023","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}