车用锂离子动力电池电化学模型修正方法
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摘要
针对锂离子动力电池伪二维(P2D)电化学模型在高倍率放电工况下精度降低的问题,提出基于平均电极模型的修正方法。分析锂离子动力电池电化学平均电极模型灵敏性参数-固相扩散系数与颗粒粒径对模型的影响,基于恒压-恒流充电容量比方法建立电流与固相扩散系数的耦合关系;通过充放电测试获取锂离子动力电池电极颗粒的粒径分布特征,将其归纳为最大粒径、中粒径和最小粒径三种不同粒径颗粒的权重系数,构建了变固相扩散系数三粒子电池电化学模型。搭建了面向单体电池的多倍率放电试验和电池组的NEDC循环工况试验平台,对比分析结果表明,相比传统的P2D电化学模型,提出的变参数模型精度提高了80%,输出电压平均误差不超过0.02 V、最大偏差在0.05 V左右,验证了变参数修正模型的有效性和准确性,为锂离子动力电池管理系统状态估计与控制提供了理论支撑。
Aim to improve the accuracy of P2D model under the condition of high discharge rate, a modified method based on the average electrode model is proposed. The effects of sensitivity parameters-solid phase diffusion coefficient and particle size on the average electrode model are analyzed. Based on the Ratio of Potentio-charge capacity to Galvano-charge capacity(RPG), the coupling relationship between current and solid phase diffusion coefficient is established. The particle size distribution characteristics of electrode particles of li-ion power battery are obtained by charging and discharging tests and concluded as the weight coefficients according to the maximum particle size, medium particle size and minimum particle size. Then, a three-particle electrochemical model with variable solid phase diffusion coefficient is given. Meanwhile, the multi-power discharge test for single battery and the NEDC cycle test platform for battery pack are carried out. Compared with the traditional P2D electrochemical model, the accuracy of the proposed variable parameter model is increased by 80%, the error of average output voltage is no more than 0.02 V, and the maximum deviation is about 0.05 V. The experiment verifies the validity and accuracy of the variable parameter model, which provides theoretical support for the state estimation and control of the Li-ion power battery management system.
Aim to improve the accuracy of P2D model under the condition of high discharge rate, a modified method based on the average electrode model is proposed. The effects of sensitivity parameters-solid phase diffusion coefficient and particle size on the average electrode model are analyzed. Based on the Ratio of Potentio-charge capacity to Galvano-charge capacity(RPG), the coupling relationship between current and solid phase diffusion coefficient is established. The particle size distribution characteristics of electrode particles of li-ion power battery are obtained by charging and discharging tests and concluded as the weight coefficients according to the maximum particle size, medium particle size and minimum particle size. Then, a three-particle electrochemical model with variable solid phase diffusion coefficient is given. Meanwhile, the multi-power discharge test for single battery and the NEDC cycle test platform for battery pack are carried out. Compared with the traditional P2D electrochemical model, the accuracy of the proposed variable parameter model is increased by 80%, the error of average output voltage is no more than 0.02 V, and the maximum deviation is about 0.05 V. The experiment verifies the validity and accuracy of the variable parameter model, which provides theoretical support for the state estimation and control of the Li-ion power battery management system.
引文
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[3]林成涛,仇斌,陈全世.电流输入电动汽车电池等效电路模型的比较[J].机械工程学报,2005,41(12):76-81.LI Chentao,QIU Bin,CHEN Quanshi.Comparison of current input equivalent circuit models of electrical vehicle battery[J].Chinese Journal of Mechanical Engineering,2005,41(12):76-81.
[4]戴海峰,孙泽昌,魏学哲.利用双卡尔曼滤波算法估计电动汽车用锂离子动力电池的内部状态[J].机械工程学报,2009,45(6):95-101.DAI Haifeng,SUN Zechang,WEI Xuezhe.Estimation of internal states of power lithium-ion batteries used on electric vehicles by dual extended Kalman filter[J].Journal of Mechanical Engineering,2009,45(6):95-101.
[5]胡晓松,唐小林.电动车辆锂离子动力电池建模方法综述[J].机械工程学报,2017,53(16):20-31.HU Xiaosong,TANG Xiaoling.Review of modeling techniques for lithium-ion traction batteries in electric vehicles[J].Journal of Mechanical Engineering,2017,53(16):20-31.
[6]徐兴,王位,陈龙.基于GA的车用锂离子电池电化学模型参数辨识[J].汽车工程,2017,39(7):813-821.XU Xing,WANG Wei,CHEN Long.Parameter identification of electrochemical model for vehicular lithium ion battery based on genetic algorithm[J].Automotive Engineering,2017,39(7):813-821.
[7]DOYLE M,FULLER T F,NEWMAN J S.Modeling of galvanostatic charge and discharge of the lithium/polymer/insertion cell[J].Journal of the Electrochemical Society,1993,140(6):1526-1533.
[8]DOMENICO D D,STEFANOPOULOU A,FIENGO G.Lithium-ion battery state of charge and critical surface charge estimation using an electrochemical model-based extended kalman filter[J].Journal of Dynamic Systems Measurement&Control,2010,132(6):768-778.
[9]XU X,WANG W,CHEN L.Order reduction of lithium-ion battery model based on solid state diffusion dynamics via large scale systems theory[J].Journal of the Electrochemical Society,2016,163(7):A1429-A1441.
[10]LI J F,WANG L X,LYU C,PECHT M.State of charge estimation based on a simplified electrochemical model for a single LiCoO2 battery and battery pack[J].Energy,2017,133:572-583.
[11]ARORA P,DOYLE M,GOZDZ A S,et al.Comparison between computer simulations and experimental data for high-rate discharges of plastic lithium-ion batteries[J].Journal of Power Sources,2000,88(2):219-231.
[12]马克华.锂离子电池参数获取及变参数模型[D].哈尔滨:哈尔滨工业大学,2014.MA Kehua.Parameter acquistion and variable parameters model for lithium-ion battery[D].Harbin:Harbin Institute of Technology,2014.
[13]唐新村,何莉萍.恒压-恒流充电容量比值法测定石墨电极中的锂离子扩散系数[J].物理化学学报,2002,18(8):705-709.TANG Xincun,HE Lipin.Determination of solid diffusion coefficient of insertion-host electrode materials based on capacity parameter[J].Acta Physico-Chimica Sinica,2002,18(8):705-709.
[14]CHATURVEDI N A,KLEIN R,CHRISTENSEN J,et al.Algorithms for advanced battery-management systems[J].IEEE Control Systems,2010,30(3):49-68.
[15]WANG C Y,GU W B,LIAW B Y.Micro-macroscopic coupled modeling of batteries and fuel cells.Part I:model development[J].Journal of the Electrochemical Society,1998,145(10):3407-3417.