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Research On Bidirectional Active Equalization Of Lithium-ion Battery Pack

Posted on:2021-02-25Degree:MasterType:Thesis
Country:ChinaCandidate:C LiFull Text:PDF
GTID:2392330602980287Subject:Master of Engineering
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Lithium-ion power battery pack is one of the core components of electric vehicles.As a source of power,it consists of hundreds or hundreds of single cells connected in series or parallel.Lithium-ion batteries connected in series will have inconsistent differences in capacity,voltage,and internal resistance due to the effects of manufacturing,loading environment,and use process.This imbalance seriously affects the power,safety and life of power batteries.The maximum usable capacity of a lithium-ion battery pack is determined by the single battery with the smallest remaining capacity,so it also limits the remaining mileage of the electric vehicle.In order to solve the problem of imbalance among single cells,balanced management has become one of the key technologies of battery management systems.In this paper,the bidirectional flyback transformer equalization circuit is studied based on the minimum heat generation from the aspects of equilibrium rate and equilibrium efficiency,which makes the battery pack work more safely and steadily Reference value.Its main content is divided into the following parts:(1)Construction of battery equivalent circuit model and estimation of battery state of charge(SOC).This paper first establishes a second-order RC equivalent circuit model of the battery.Because the battery parameters have different changes at different charge and discharge rates,different temperatures,and different SOC states,the battery rebound voltage data is collected in the charge and discharge experiments.The hysteresis characteristics are identified offline using the least squares fitting method for battery model parameters at different charge and discharge rates and different SOC states.The identified model parameters are applied to the second-order RC equivalent circuit model of the battery.The battery model and the extended Kalman filter-error back propagation network joint algorithm model are built in MATLAB/Simulink.The estimated SOC value has a small error from the theoretical value.The accuracy of the algorithm is verified.(2)Research on the working principle and balancing control strategy of the flyback bidirectional transformer balancing circuit.The basic working principle of the flyback bidirectional transformer equalization circuit is analyzed,and the working process of the flyback bidirectional transformer equalization circuit is theoretically introduced.Then build the balanced circuit model in MATLAB/Simulink,using the battery SOC as the balanced variable,and start from the balanced time and the balanced system efficiency,and compare their respective advantages.(3)On the premise of taking into account the balance rate and balance efficiency,a fuzzy logic balance control strategy was developed.Since the equalization time and the efficiency of the equalization system cannot be expressed in the working state of the equalization circuit at the same time,this paper proposes a fuzzy logic equalization that takes the difference between the maximum and minimum values of the individual SOC in the battery pack and the average value of the SOC of the battery pack as the input and the balance current as the output Control strategy,perform simulation analysis.(4)Verify the real-time performance of the equilibrium control strategy based on the PXI real-time computing system.Configure and compile the NI Veristand input and output interface for the battery model and the equalization circuit model in Matlab/Simulink;set up the equalization control strategy and compile under the MotoHawk workspace;establish the NI Veristand project file to match the input and output of the model and hardware Interface;After the completion of the entire hardware-in-the-loop test platform,Verify the real-time performance of the equilibrium control strategy in the fuzzy logic balance control strategy in the PXI system.
Keywords/Search Tags:SOC estimation, flyback bidirectional transformer, balance control strategy, Hardware-in-the-loop test
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