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Research on SOC Estimation of Lithium Battery Based on Modified Strong Tracking Filter

Author: ZhangYuZuo
Tutor: ChengZe
School: Tianjin University
Course: Control Science and Engineering
Keywords: Electric vehicles Lithium battery SOC Strong Tracking FilterAlgorithm
CLC: TM912
Type: Master's thesis
Year: 2012
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Abstract


Due to the rise of global population and the increase of cars, energy-saving andenvironmental-protection problems have become particularly important. Electricvehicle has draw the whole world’s attention because of the advantages of low noise、energy-saving and zero emissions, thus the demand of advanced batteries and batteryenergy management is increasing rapidly. Since lithium batteries are high energydensity and non-pollution, they are widely used in energy storage device of electricvehicles. As one key technology of electric vehicle development, lithium batteries hasbecome the hot research issue, while the accurate estimation of battery SOC (state ofcharge) is the key in operation of lithium battery management system.In order to estimate SOC of lithium battery using related algorithms, it isessential to confirm the parameters of lithium battery model. Based on the researchand analysis of the existing model, it uses RC model as the battery model, measuresthe parameters through battery discharge experiment. The simulation results ofMATLAB prove that the measured model parameters are reliable and accurate. Also,this paper puts forward the modified strong tracking filter algorithm for lithium SOCestimation, combines strong tracking filter algorithm with the fuzzy control algorithmand adaptive filtering algorithm. The modified algorithm can effectively increase theestimation accuracy and enhance the adaptive and tracking performance of algorithm.Finally, based on the lithium battery of Tianjin Lishen Company, it hasconstructed an experimental platform and developed the high precision isolateddetection and switch selection circuit. FPGA is used as control chip to realize themodified strong tracking algorithm and display the SOC estimation results on theLCD screen. Hardware experiments verify that the modified algorithm is accurate andeffective.

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CLC: > Industrial Technology > Electrotechnical > Independent power supply technology (direct power) > Battery
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