Research on the degradation mechanism and model of lithium-ion battery in
48V "micro-hybrid" system
The battery capacity of the 48V "light hybrid" system is low, so it usually
works at a larger rate, which is very detrimental to the cycle life of the power
battery. Recently, Zifan Liu (first author) and Simona Onori (corresponding
author) of Clemson University in the United States studied the cycle life of
NCM18650 batteries in the 48V "light hybrid" system operating mode, and used a
single particle (SP) model to A modeling study of capacity fading was
conducted.
The battery used by Zifan Liu in the experiment is Sony's VTC4 NCM18650
battery with a capacity of 2Ah, a maximum continuous discharge current of 32A,
and a maximum continuous charging current of 12A. The detailed information of
the battery is as shown in the table above. The test system simulates 48V "light
hybrid" "The usage scenarios of the system were carried out, and the smooth
driving low-speed cycle mode CLS and the intense driving high-speed cycle mode
AHS were simulated (as shown in Figures a and b below). The experimental
processes were conducted at 23°C and 45°C through temperature control equipment.
The experiment The battery arrangement is shown in the table below.
The relationship between the reversible capacity loss of batteries cycled
under different regimes, charging capacity and cycle time is shown in Figures a
and b below. From the figure, it can be seen that whether the abscissa is time
or capacity, the battery under the CLS23 regime has a lifespan of 3 months. No
significant degradation occurred in the cycles, and the battery cycled under the
AHS45 and NC45 regimes had the most serious degradation, followed by the CLS45
regime, then AHS23, and the slowest decay was CLS23. From the results, we can It
is not difficult to see that temperature has the greatest impact on the
degradation of lithium-ion batteries, followed by the discharge current when the
battery is working.
Zifan Li used the single particle model SP to simulate the degradation
characteristics of lithium-ion batteries under several cycle systems. In this
model, a single particle replaced the lithium-ion battery electrode, and the
kinetic characteristics of a single particle represented the behavior of the
entire electrode. Dynamic characteristics (as shown in the figure below), but
the single-particle model generally assumes that the electrolyte is stable on
the particle surface and does not have decomposition problems. This assumption
is true when the current density is small (<1C), but when the current density
When it is larger, we need to take the decomposition of the electrolyte into
consideration, which is the enhanced single-particle model.
According to Fick's law, the Li concentration inside the particle can be
calculated by the following formula, where C is the Li concentration inside the
particle and D is the diffusion coefficient of Li in the solid phase. This
formula contains two boundary conditions, as shown in the following equations 2
and 3, where equation 2 indicates that Li diffuses from the center of the
particle to the surface of the particle, and equation 3 indicates that the
diffusion rate of Li at the particle interface is the same as the current
density.
According to the diffusion characteristics of Li in the solid phase, we can
assume that the concentration distribution of Li inside the particles conforms
to the characteristics of a parabola. Therefore, we can assume that the
concentration of Li inside the particles conforms to the following equation 5.
If we substitute equation 5 into equation 1, we can get Equation 6. If Equation
5 is substituted into Equation 3, we can convert the current density at the
interface into Equation 7.
After the model is determined, it is necessary to determine the parameters
in the model. There are a total of 14 parameters that need to be determined in
the model. The parameter determination process can be divided into two steps.
First, the model is fitted according to the cycle data of the battery to reduce
the model The error between the actual data and the optimal value of the
parameters is initially obtained; the second step is to set the parameters that
have nothing to do with the life decline of the lithium-ion battery as
constants, and then use the MCMC method to further analyze the parameters that
are related to the life of the lithium-ion battery. parameters are
optimized.
Based on the above model, Zifan Liu simulated the life decay
characteristics of two batteries, cell5# and cell7#, which were cycled at
different temperatures. The root mean square error of the simulation data was
less than 0.03V, indicating that the model can restore the model very well. The
degradation characteristics of lithium-ion batteries in different modes were
analyzed. The parameter Ap represents the equivalent active area of the positive
electrode. The Ap value dropped significantly under both cycle systems,
indicating that the positive electrode was stable under both cycle systems. A
loss of active material has occurred. The parameter SoCn, 100, is the SoC state
of the negative electrode at the beginning of discharge. It decreased
significantly under both cycle conditions, indicating that the battery
experienced loss of active Li and SEI film growth in both cases.
The figure below shows the regression relationship curve between the
reversible capacity loss of the battery and the two parameters we improved
above. From the figure, there is a significant correlation between the SoCn,100
parameter and the reversible capacity loss of the battery. The R2 value reaches
0.9981, indicating that two There is a strong correlation between the variables,
while the correlation between the loss of active material at the positive
electrode and the loss of the battery's reversible capacity is weak (R2 value is
only 0.6757), which indicates that the SEI film growth of the negative electrode
and the loss of active Li are responsible for the battery's reversible capacity.
The main factor causing reversible capacity loss, while the loss of positive
active material is a secondary factor causing reversible capacity loss in
batteries.
Zifan Li experimentally verified the battery degradation characteristics of
the 48V "light hybrid" system, and modeled and analyzed the battery degradation
through a single-particle model. Combining battery test data and MCMC data
optimization methods, the lithium-ion battery in the " The life decay
characteristics of the "light hybrid" system were simulated. The simulation
results show that among the 14 model parameters, SoCn, 100 and Ap have a clear
correlation with the reversible capacity loss of lithium-ion batteries,
indicating that The SEI film growth of the negative electrode and the loss of
active Li are the main factors leading to the reversible capacity loss of the
battery, followed by the loss of the positive electrode active material.
ZifanLi's work provides a new research method for us to study the life decay
characteristics of lithium-ion batteries in 48V "light hybrid" systems.
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