The Plug-in Hybrid Electric Vehicle As Generator And Load .

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x̂ (9)k Ak 1 .x̂ k 1 Bk 1 .uk 1Current influences need more tests to be determined. Howeverthe higher or lower influence may depend on the battery Pk Ak 1 .Pk 1.ATk 1 Q(10)technology. "1 0#

Fig. 17.Evolution of voltage on a 4A discharge with 4A parameters,simulation using a Kalman filterFig. 16.Evolution of voltage on a 4A discharge with 2A parameters,simulationMeasurement update equationsKk Pk .CkT .[Ck .Pk .CkT R] 1(11) x̂ k x̂k Kk .[zk Ck .x̂k Dk .uk ](12)Fig. 18. Evolution of state of charge in a 4A discherge, simulation using aKalman filterPk [I Kk .Ck ].Pk (13)The matrixes according to the proposed model are thefollowing: Ak "1 0 0[1 ](14) t Z (15) Voc (soc) (16)Bk Ck tCDk 1 .RDk 1#Cn tCD soc 1 Dk Rseriesk(17)The results of the simulation are presented on the nextfigures 17, 18.The initial SOC was set to 200% which converges fast to90%. The covariance and variances of noise and errors are setempirically.VII. C ONCLUSIONSAND FURTHER STUDIESThe implementation and the study of the V2G technologyrequires good battery models, those which can represent thebattery behaviour in stationary and dynamic regime.The proposed model is intuitive, incorporares several characteristics from different electrical circuit approaches andallows the representation of all kind of battery.However, the model parameters extraction is a hard task.The state of charge is a utmost caracteristic that need estimation. The parameters varies with the working point ofthe battery (SOC, current) differently for the several batterytechnologies.In addiction, this work leads to the conclusion that the mainparameters involved in battery modeling are Rseries ,RD ) andthe function Voc (SOC), which represents the fast dynamics.The Kalman filter is for sure a good solution to be appliedin the batteries scenario, that allows a good match betweenexperimental and model results.

R EFERENCES[1] Chan, C.C. , The state of the art of electric and hybrid vehicles, IEEE,vol. 90, pp.247-275, 2002.[2] www.generalmotors.com[3] Kempton, W. and Steven Letendre, Electric Vehicles as a New Source ofPower for Electric Utilities, Transportation Research 2(3): 157-175.[4] Kempton, W. and J. Tomie, Vehicle to Grid Fundamentals: CalculatingCapacity and Net Revenue, J. Power Sources Volume 144, Issue 1, 1 June2005, Pages 268-279.[5] Kempton, W. and J. Tomie, Vehicle to Grid Implementation: from stabilizing the grid to supporting large-scale renewable energy, J. PowerSources Volume 144, Issue 1, 1 June 2005, Pages 280-294.[6] P. Denholm , W. Short, An Evaluation of Utility System Impacts and Benefits of Optimally Dispatched Plug-In Hybrid Electric Vehicles, NationalRenewable Energy Laboratory ,Technical Report, NREL/TP-620-40293,October 2006.[7] Kempton, W. , J. Tomie, Using fleets of electric-drive vehicles for gridsupport, Journal of Power Sources , 2007.[8] Kempton, W. , Toru Kubo, Electric-drive vehicles for peak power inJapan, Energy Police, vol 28, 2000, Pages 9-18.[9] http://www.greencarcongress.com/v2g/index.html[10] http://www.acpropulsion.com/[11] Linen, David and Redy Thomas The handbook of the batteries, ThirdEdition, Macgraw Hill[12] Pesaran, Ahmad Battery Choices and Potential Requirements for Plug-InHybrids, National Renewable Energy Laboratory[13] www.A123systems.com[14] www.altairnano.com[15] Ravishankar Rao, Sarma Vrudhula, Daler N. Rakhmatov, Battery modeling for energy-aware system design, IEEE ,vol. 36, pp.77-87, 2003.[16] Gregory L. Plett, Extended Kalman filtering for battery managementsystems of LiPB-based HEV battery packs Part 1. Background, Journalof Power Sources 134 (1),pp. 252-261, 2004.[17] Gregory L. Plett, Extended Kalman filtering for battery managementsystems of LiPB-based HEV battery packs Part 2. Modeling and identification, Journal of Power Sources 134 (2) ,pp. 262-276, 2004.[18] Gregory L. Plett, Extended Kalman filtering for battery managementsystems of LiPB-based HEV battery packs Part 3. State and parameterestimation, Journal of Power Sources 134 (3) ,pp. 277-292, 2004.[19] By S.Buller, M.Thele, R.W. De Doncker ,E. Karden, Impedance-Basedsimulation models, of supercapacitors and lithium-ion batteries for powerelectronic applications, IEEE transactions on industry apllications ,vol.41, no. 3, may-june 2005.[20] Jaemoon Lee, Oanyong Nam, B.H. Cho,Li-ion battery SOC estimationmethod based on the reduced order extended Kalman filtering, Journal ofPower Sources vol. 174 ,pp. 9-15, 2007.[21] Ziyad M. Salameh, Margaret A. Casacca, William A. Lynch A mathematical model for Lead-Acid Batteries, IEEE Transactions on EnergyConversion, vol. 7, no.1 , March 1992.[22] Lijun Gao, Shengyi Liu, Roger A. Dougal, Dynamic Lithium-Ion batterymodel for system simulation, IEEE transactions on components andpackaging technologies vol. 25, no.3, September 2002.[23] Min Chen, Gabriel A. Rincon-Mora, Accurate Electrical battery modelcapable of predicting runtime and I-V performance, IEEE transactionson energy conversion vol. 21, no. 2, June 2006.[24] Suleiman Abu-Sharkh, Dennis Doerffel, Rapid test and non-linear modelcharacterisation of solid state lithium-ion batteries, Journal of PowerSources vol. 130, pp. 266-274, 2004.[25] Bernhard Schweighofer, Klaus M. Raab and Gerog Brasseur, Modelingof High Power Automotive Batteries by the use of an automated testsystem, IEEE transactions on instrumentation and measur

the possibility of bidirectional power flow on the electric motor. (a) Series (b) Parallel (c) Series-parallel (d) Complex Fig. 1. Four common architectures of Hybrid Electric Vehicles [1] The function and power of the electric motor defines the class. Micro, vehicle

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