摘要
为了便于终端用户更容易获取到电芯内部相关的电化学参数数据,本文通过逆向拆解的方法结合电化学-热耦合模型,采用有限元仿真分析和电化学参数优化试验的方式,验证了所获取参数的精确性,并通过参数辨识的方式考虑了Bruggman系数,反应速率常数和固相扩散系数对动力电池充放电性能和温度的影响。研究结果表明:逆向拆解法可以精确地获取电池的动力学参数和热力学参数,对标锂电池的电压、温度误差范围在3%左右;Bruggman系数影响放电中后期的电压,增大数值增加极化,随着Bruggman系数的不断增大电池温度呈现减小趋势;反应速率常数影响全范围内的电压变化,温度随着反应速率常数的增大出现减小的状况,增大反应速率常数减小极化;固相扩散系数影响低SOC范围内的电压,增大数值减小极化。
This study integrates the electrochemical thermal coupling model with the reverse disassembly method to facilitate easier access for end-users to electrochemical parameter data about the battery cell's interior.It employs finite element simulation analysis and electrochemical parameter optimization experiments to validate the accuracy of the obtained parameters.Furthermore,it examines the impact of the Bruggman coefficient,reaction rate constant,and solid-phase diffusion coefficient on the charging and discharging performance and the temperature of power batteries.The findings reveal that the reverse disassembly method effectively captures the dynamic and thermodynamic battery parameters,with an error margin of approximately 3%for voltage and temperature in standard lithium batteries.Notably,the Bruggeman coefficient influences voltage,particularly in the middle and later stages of discharge,wherein an increase in its value amplifies polarization.Moreover,as the Bruggeman coefficient rises,battery temperature demonstrates a decreasing trend.The reaction rate constant affects voltage across the entire discharge range,inversely correlating with temperature;higher reaction rate constants correspond to reduced polarization.Similarly,the solid-phase diffusion coefficient influences voltage within the low state-of-charge(SOC)range,with higher values diminishing polarization.
作者
陶正德
张志超
郭昌梁
TAO Zhengde;ZHANG Zhichao;GUO Changliang(Tianmu lake Insitute of Advanced Energy Storage Technologies,Liyang 213300,Jiangsu,China)
出处
《储能科学与技术》
CAS
CSCD
北大核心
2024年第6期2022-2029,共8页
Energy Storage Science and Technology
基金
国家重点研发计划(2022YFB2502200)。
关键词
电化学-热耦合模型
逆向拆解
精度验证
参数辨识
electrochemical thermal coupling model
reverse disassembly
accuracy verification
parameter identification
