Modification Method of Electrochemical Model for Vehicular Lithium-ion Power Battery

doi:10.3901/JME.2019.12.128

Abstract

Abstract: 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.

Key words: average electrode models, electric vehicle, li-ion batteries, modification method, variable parameters

CLC Number:

TM911

XU Xing, XU Qiling, WANG Feng, YANG Shichun, ZHOU Zhiguang. Modification Method of Electrochemical Model for Vehicular Lithium-ion Power Battery[J]. Journal of Mechanical Engineering, 2019, 55(12): 128-136.

References

[1] SUN Yong,MA Zilin,TANG Gongyou,et al. Estimation method of state-of-charge for lithium-ion battery used in hybrid electric vehicles based on variable structure extended Kalman filter[J]. Chinese Journal of Mechanical Engineering,2016,29(4):717-726.
[2] 戴海峰,魏学哲,孙泽昌. 基于扩展卡尔曼滤波算法的燃料电池车用锂离子动力电池荷电状态估计[J]. 机械工程学报,2007,43(2):92-95. DAI Haifeng,WEI Xuezhe,SUN Zechang. Estimate state of charge of power lithium-ion batteries used on fuel cell hybrid vehicle with method based on extended Kalman filtering[J]. Journal of Mechanical Engineering,2007,43(2):92-95.
[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.