2012 IEEE International Electric Vehicle Conference最新文献

{"title":"Electric vehicle charge planning using Economic Model Predictive Control","authors":"R. Halvgaard, N. K. Poulsen, H. Madsen, J. B. Jørgensen, F. Marra, D. E. M. Bondy","doi":"10.1109/IEVC.2012.6183173","DOIUrl":"https://doi.org/10.1109/IEVC.2012.6183173","url":null,"abstract":"Economic Model Predictive Control (MPC) is very well suited for controlling smart energy systems since electricity price and demand forecasts are easily integrated in the controller. Electric vehicles (EVs) are expected to play a large role in the future Smart Grid. They are expected to provide grid services, both for peak reduction and for ancillary services, by absorbing short term variations in the electricity production. In this paper the Economic MPC minimizes the cost of electricity consumption for a single EV. Simulations show savings of 50-60% of the electricity costs compared to uncontrolled charging from load shifting based on driving pattern predictions. The future energy system in Denmark will most likely be based on renewable energy sources e.g. wind and solar power. These green energy sources introduce stochastic fluctuations in the electricity production. Therefore, energy should be consumed as soon as it is produced to avoid the need for energy storage as this is expensive, limited and introduces efficiency losses. The Economic MPC for EVs described in this paper may contribute to facilitating transition to a fossil free energy system.","PeriodicalId":134818,"journal":{"name":"2012 IEEE International Electric Vehicle Conference","volume":"42 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":"127267183","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":"Trolleybuses in Smart Grids as effective strategy to reduce greenhouse emissions","authors":"A. Diez, I. C. Diez, J. A. Lopera, A. Bohórquez, E. Velandia, A. Albarracin, M. Restrepo","doi":"10.1109/IEVC.2012.6183213","DOIUrl":"https://doi.org/10.1109/IEVC.2012.6183213","url":null,"abstract":"This paper analyses the need of reintroduce electric transportation systems in countries that abandoned these modes and brings a methodology to assess the effectiveness of the electrification in terms of global warming mitigation. The potential interaction of grid connected vehicles and Smart Grids is presented among some ideas related to features that could be developed for massive transportation systems based on electric traction. As will be presented, Smart Grids could help to accelerate the electrification of transportation systems and the electrification could be used to accelerate the introduction of Smart grids. As reference cases in Colombia and Ecuador will be taken.","PeriodicalId":134818,"journal":{"name":"2012 IEEE International Electric Vehicle Conference","volume":"60 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":"127681722","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 model of Electric Vehicle charging station compatibles with Vehicle to Grid scenario","authors":"M. Singh, P. Kumar, I. Kar","doi":"10.1109/IEVC.2012.6183223","DOIUrl":"https://doi.org/10.1109/IEVC.2012.6183223","url":null,"abstract":"A large penetration of Electric Vehicles (EVs) will demand a huge infrastructure for power handling of the distribution network. In this paper, EVs charging station has been modelled which can fulfil different demands of the EV vehicles owners. The owner's demand can be to limit on the charging rate (Crate), or limit to the state of charge (SOC) or proper power management of the battery. A suitable fuzzy controller has been designed to control the Crate of the individual battery based on power available with the battery and the power required by the grid. An algorithm has been designed which can handle different situations like charging and discharging of EVs batteries based on the distribution node voltage. The algorithm updates the power requirement, if certain vehicles arrive or leave the charging station.","PeriodicalId":134818,"journal":{"name":"2012 IEEE International Electric Vehicle Conference","volume":"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":"129066061","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":"Intelligent sensorless ABS for regenerative brakes","authors":"A. Dadashnialehi, Z. Cao, A. Kapoor, A. Bab-Hadiashar","doi":"10.1109/IEVC.2012.6183169","DOIUrl":"https://doi.org/10.1109/IEVC.2012.6183169","url":null,"abstract":"The emergence of In-Wheel technology and the fact that an electric machine is embedded in each corner of an Electric Vehicle (EV) has profound effect on vehicle design. An electric motor is now available at each wheel and we show that the output of those motors can be used to eliminate the wheel speed sensor of a conventional ABS design. The paper analyses the transient behavior of the back EMF signal of the In-Wheel motor for a range of challenging braking scenarios using the wavelet technique. The analysis showed that the proposed method is capable of extracting important features related to changes in road conditions during the activation of ABS.","PeriodicalId":134818,"journal":{"name":"2012 IEEE International Electric Vehicle Conference","volume":"85 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":"122963604","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":"Use of conductive composite sensors for improved condition monitoring of Electric Vehicle motor insulation systems","authors":"K. Watkins, C. Wong","doi":"10.1109/IEVC.2012.6183295","DOIUrl":"https://doi.org/10.1109/IEVC.2012.6183295","url":null,"abstract":"Electric vehicle (EV) motors are subject to extreme and variable loads, resulting in degradation of winding insulation due to high temperatures. This paper describes research on a new conductive composite sensor, which utilizes insulation resin as the sensor element matrix. The sensor, embedded in the windings of EV motors, will provide remaining design life of the insulation based on actual vehicle operational and environmental conditions. Improved condition monitoring of the insulation systems of high performance EV motors will reduce in-use failures by identifying prematurely degraded insulation systems, and providing data for quality improvement programs.","PeriodicalId":134818,"journal":{"name":"2012 IEEE International Electric Vehicle Conference","volume":"66 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":"116792849","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 multicell battery system design for electric and plug-in hybrid electric vehicles","authors":"Taesic Kim, W. Qiao, Liyan Qu","doi":"10.1109/IEVC.2012.6183240","DOIUrl":"https://doi.org/10.1109/IEVC.2012.6183240","url":null,"abstract":"The performance of electric vehicles (EVs) and plug-in hybrid electric vehicle (PHEVs) strongly relies on their battery storage system, which consists of multiple battery cells connected in series and parallel. However, cell state variations are commonly present, which reduces the energy conversion efficiency of the battery system. Furthermore, in a large battery system the risk of catastrophic faults of cells increases because a large numbers of cells are used. To solve these problems, this paper proposes a novel power electronics-enabled, self-X, multicell battery system design. The proposed battery system can self-heal from failures or abnormal operations of single or multiple cells and self-balance from cell state variations. These features are achieved by a cell switching circuit and a high-performance battery management system (BMS). The proposed design is validated by simulation studies in MATLAB Simulink for a battery system containing five modules connected in series, where each module consists of 6×3 cylindrical lithium-ion cells. The proposed design is scalable to large battery systems for EV/PHEV applications.","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":"115522473","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":"Electrification of trucks and buses in an urban environment through continuous charging","authors":"N. Leemput, S. De Breucker, K. Engelen, J. Van Roy, F. Geth, J. Driesen","doi":"10.1109/IEVC.2012.6183159","DOIUrl":"https://doi.org/10.1109/IEVC.2012.6183159","url":null,"abstract":"This paper investigates the impact of electrification of trucks and buses in an urban environment. The vehicles are charged while driving on electrified roads (continuous charging), and battery powered on the non-electrified roads. A power management algorithm is proposed for driving on the electrified roads. Simulations covering a 24-hour time frame are performed for a selected urban area in Paris, France. The resulting peak power demand and energy consumption are calculated for a single road segment and for several adjacent road segments.","PeriodicalId":134818,"journal":{"name":"2012 IEEE International Electric Vehicle Conference","volume":"31 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":"114177779","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":"Optimal use of second life battery for peak load management and improving the life of the battery","authors":"A. Keeli, R. Sharma","doi":"10.1109/IEVC.2012.6183276","DOIUrl":"https://doi.org/10.1109/IEVC.2012.6183276","url":null,"abstract":"Impact of petroleum based vehicles on the environment, cost and availability of fuel has led to an increased interest in electric vehicle as a means of transportation. Battery is a major component in an electric vehicle. Economic viability of these vehicles depends on the availability of cost-effective batteries. Subsidies provided by the government will be instrumental in the initial success of electric vehicles. However, in the long run for the commercial success of electric vehicles the economics have to be self-sustained. Batteries used for transportation purpose cannot be used once the energy capacity reaches 70%-80%. The remaining capacity of the battery can still be utilized for secondary purpose like powering a building during peak load hours and reducing the carbon foot print. Owner of an electric vehicle would be benefited if a market for the used electric vehicle batteries is created. These batteries are called second life batteries. Commercial building peak load reduction is considered in this study. This work deals with using second life battery for peak load management and to analyze the cost effectiveness of the second life battery to be used for powering a commercial building. Battery is the main component in this study and increasing the life of the second life battery using Battery Life Estimator (BLE) is discussed. An optimal solution for incorporating peak load management, cost saving from the use of second life battery and lifetime of the second life battery is achieved using a rule-based control for the parameters.","PeriodicalId":134818,"journal":{"name":"2012 IEEE International Electric Vehicle Conference","volume":"41 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":"114775871","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":"Smartphone-based accurate range and energy efficient route selection for electric vehicle","authors":"R. Yaqub, Yu Cao","doi":"10.1109/IEVC.2012.6183293","DOIUrl":"https://doi.org/10.1109/IEVC.2012.6183293","url":null,"abstract":"Range anxiety - the fear of running out of battery power while on the road - is one of the major barriers to large scale adoption of Electric Vehicles (EVs). Range prediction solutions are available to address anxiety but most of them have limited functionalities. In this paper we propose a new, “Accurate Range” and “Energy-efficient Route” (ARER) selection mobile software solution which is based on smartphone platform. The proposed solution provides several attractive features. The first and prime feature is estimation of the most accurate driving range considering those real time factors that were never considered in the prior art such as geographical terrain of the driving route (Elevation and Depression), real time alert implemented on the road (i.e. the road flood clogged or blocked due to catastrophe - such information would be received through PLAN (Personal Localized Alerting Network), a new public safety system that FCC and FEMA are working on currently that will enable government officials to send emergency text alerts, such as tornados, floods, terrorisms, to specific affected geographic areas through cell towers in near future), Real Time Wind Speed (tailwind and headwind), real time weight in the EV (onboard Passengers and Cargo), and real time traffic (including not only on road vehicles, but also STOP signs, advisory road signs, and probability of encountering red traffic lights, etc.), comparing with available battery energy. The second key feature that leverages on the first one is proposing the alternate route(s) that may not be essentially shorter but the most energy efficient (e.g. the route with depression instead of elevation and at the same time not flood clogged or blocked, the route with favorable wind direction at that instant and location, the route with lesser traffic congestion, fewer stop signs and fewer red traffic light etc.). The third feature is to evaluate the service relevance and suggest the point of service; offering similar services, that fall on the most energy efficient route (e.g. if the EV Driver searched for Rite-Aid Pharmacy, the software may also suggest the WalGreens or Wall Mart, or Target, or Shoprite, because of service relevance/similar service offering and occurrence on the most energy efficient route from the EV Driver's current location). The fourth feature is that it keeps the history of the roads traversed and uses the log data for future optimization. Lastly the fifth feature is that it produces a visual 360-degree real time range display, and calculates the estimated energy cost of completing a chosen rout. The software to make prototype for the work is under development.","PeriodicalId":134818,"journal":{"name":"2012 IEEE International Electric Vehicle Conference","volume":"63 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":"125841532","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":"Electric vehicle charging facility planning in Shenzhen Power Supply Bureau Limited Company","authors":"Lili Zhao, Ming Xie, Jin Dong, Zhiyu Zheng, Xilin Wang","doi":"10.1109/IEVC.2012.6183185","DOIUrl":"https://doi.org/10.1109/IEVC.2012.6183185","url":null,"abstract":"Electric Vehicles (EV) are promoted world-wide as an effective approach to address gasoline consumption and transportation emission problems. In China, state-owned electric power companies are taking the lead in Electric Vehicle (EV) charging infrastructure area, in which the EV charging facility network construction is a key topic. This paper introduces a quantitative EV charging facility planning method. This method calculates EV charging demand distribution, and uses optimization techniques to calculate the optimal EV charging facility network. This method has been applied in Shenzhen Power Supply Bureau (PSB), which is a state-owned electric power company in China. By implementing this method, the costs and risk of Shenzhen PSB will be minimized and its charging facility management will be improved. Moreover, this work will play an exemplary role to peer companies and the public.","PeriodicalId":134818,"journal":{"name":"2012 IEEE International Electric Vehicle Conference","volume":"16 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":"126863324","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}