动力锂电池等效模型与实验平台搭建方法研究
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摘要
为清楚理解动力锂电池的内部结构和工作原理,选取搭建较为精确的等效模拟十分重要,它能更精确有效地获取各项内部参数。以动力锂电池为研究对象,分析其工作特性和原理,查阅资料做出最佳等效模拟电路,通过锂电池的充放电过程的HPPC实验研究,有效估算出SOC并得到所需各项参数,再由等效电路的计算方程得到等效参数。结论得出锂电池充放电过程中参数大致稳定,等效内阻均值为1.023 mΩ,标准差为0.218 6,极化电阻均值为0.304 4 mΩ,标准差为0.150 4。基于STM32、检测电路和LCD搭建的充放电系统,实现对锂电池电流和电压的检测以计算分析模拟电路内部参数。
For clear comprehension of the internal structure and operating principle of power lithium battery, it is important to establish a relatively accurate equivalent model, which can obtain the intrinsic parameters more precisely and availably. The characteristics and working principle of power lithium batteries were analyzed, and the optimal equivalent circuit was built by referring to the relative literature. Through HPPC experiment on the charge &discharge, SOC was estimated and the required parameters were collected. The equivalent parameters were also obtained by the equivalent circuit. It is concluded that the parameters during charge and discharge are approximately stable, the mean value of equivalent internal resistance is 1.023 mΩ, the standard deviation is 0.218 6, the polarization resistance is 0.304 4 mΩ and the standard deviation is 0.150 4. Based on STM32, detection circuit and LCD, the charge and discharge system was designed, which realizes the measure of currents and voltages of batteries for calculation and analysis of the internal data of artificial circuit.
For clear comprehension of the internal structure and operating principle of power lithium battery, it is important to establish a relatively accurate equivalent model, which can obtain the intrinsic parameters more precisely and availably. The characteristics and working principle of power lithium batteries were analyzed, and the optimal equivalent circuit was built by referring to the relative literature. Through HPPC experiment on the charge &discharge, SOC was estimated and the required parameters were collected. The equivalent parameters were also obtained by the equivalent circuit. It is concluded that the parameters during charge and discharge are approximately stable, the mean value of equivalent internal resistance is 1.023 mΩ, the standard deviation is 0.218 6, the polarization resistance is 0.304 4 mΩ and the standard deviation is 0.150 4. Based on STM32, detection circuit and LCD, the charge and discharge system was designed, which realizes the measure of currents and voltages of batteries for calculation and analysis of the internal data of artificial circuit.
引文
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[2]FARMANN A,WAAG W,MARONGIU A.Critical review of on-board capacity estimation techniques for lithium-ion batteries in electric and hybrid electric vehicles[J].J Power Sources,2015,281:114-130.
[3]何志超,杨耕,卢兰光.基于恒流外特性和SOC的电池直流内阻测试方法[J].清华大学学报,2015,55(5):532-537.
[4]黄泽波,王顺利,裴世杰,等.锂电池充电模块的设计与实验分析[J].电源世界,2017(1):34-42.
[5]BAGHDADI I,BRIAT O,GYAN P,et al.State of health assessment for lithium batteries based on voltage-time relaxation measure[J].Electrochimica Acta,2016,194(3):461-472.
[6]KIM T,WANG Y B,FANG H Z.Model-based condition monitoring for lithium-ion batteries[J].J Power Sources,2015,295:16-27.
[7]李起伟.防爆电动车锂电池管理系统设计[J].工矿自动化,2017(4):5-9.
[8]刘新天,孙张驰,何耀,等.基于环境变量建模的锂电池SOC估计方法[J].东南大学学报:自然科学版,2017(2):306-312.
[9]MATHEW M,KONG Q H,MCGRORY J,et al.Simulation of lithium ion battery replacement in a battery pack for application in electric vehicles[J].Journal of Power Sources,2017,349(5):94-104.
[10]WANG S L,SHANG LP,LI Z F.Lithium-ion battery security guaranteeing method study based on the state of charge estimationá???áá????á??áá?[J].Int J Electrochem Sc,2015,10(6):5130-5151.
[11]WANG S L,SHANG LP,LI Z F.Online dynamic equalization adjustment of high-power lithium-ion battery packs based on the state of balance estimation[J].Appl Energ,2016,166:44-58.
[12]王顺利,尚丽平,李占锋.基于滑动平均的锂电池关键参量检测方法研究[J].电子技术应用,2015,41(3):141-144.
[13]FIROUZ Y,TIMMERMANS J M,OMAR N,et al.Advanced lithium ion battery modeling and nonlinear analysis based on robust method in frequency domain:nonlinear characterization and non-parametric modeling[J].Energy,2016,106(7):602-617.
[14]杨思敏,申彩英,全奎松,等.电动汽车用锂电池模型研究[J].现代车用动力,2017(2):18-20.
[15]GUO Y F,ZHAO Z S,HUANG LM,et al.SOC estimation of lithium battery based on improved BP neural network[J].Energy Procedia,2017,105:4153-4158.
[16]徐建波.新型可监控锂电池串联监测管理模型设计和实现[J].电子技术与软件工程,2017(12):103.
[17]张智群.电动汽车用磷酸铁锂电池动态特性建模与仿真研究[D].西安:长安大学,2016.