With the development of electric vehicles, battery management systems (BMS)
have also been widely used. In order to give full play to the power performance
of the battery system, improve the safety of its use, prevent the battery from
overcharging and over-discharging, extend the service life of the battery,
optimize driving and improve the performance of electric vehicles, the BMS
system must monitor the battery's state of charge That is, SOC (State-Of-Charge)
for accurate estimation.
1 Introduction
In order to cope with the energy crisis and slow down global climate
warming, many countries have begun to pay attention to energy conservation and
emission reduction and the development of a low-carbon economy. Because electric
vehicles are driven by electricity and can reduce carbon dioxide emissions or
even achieve zero emissions, they have attracted attention from various
countries and developed rapidly. However, battery costs are still high, and the
performance and price of power batteries are the main "bottlenecks" in the
development of electric vehicles. Lithium iron phosphate batteries have become
an ideal power source for electric vehicles because of their long life, good
safety performance, and low cost.
With the development of electric vehicles, battery management systems (BMS)
have also been widely used. In order to give full play to the power performance
of the battery system, improve the safety of its use, prevent the battery from
overcharging and over-discharging, extend the service life of the battery,
optimize driving and improve the performance of electric vehicles, the BMS
system must monitor the battery's state of charge That is, SOC (State-Of-Charge)
for accurate estimation. SOC is an important parameter used to describe the
charge and discharge capacity of a battery during use.
2. Raising the question
The SOC of the battery is related to many factors (such as temperature,
charge and discharge status at the previous moment, polarization effect, battery
life, etc.), and has strong nonlinearity, which brings great difficulties to
real-time online estimation of SOC.
At present, battery SOC estimation strategies mainly include: open circuit
voltage method, ampere-hour measurement method, artificial neural network
method, Kalman filter method, etc.
The basic principle of the open circuit voltage method is to allow the
battery to rest sufficiently to restore the battery terminal voltage to the open
circuit voltage. The resting time is generally more than 1 hour and is not
suitable for real-time online detection of electric vehicles. Figure 1 compares
the relationship between the open circuit voltage (OCV) and SOC of lithium
manganate batteries and lithium iron phosphate batteries. The OCV curve of
LiFePO4 batteries is relatively flat, so it is difficult to estimate its SOC
simply by using the open circuit voltage method.
Figure 1 OCV-SOC curves of lithium manganate and lithium iron phosphate
Currently, most of the practical methods for estimating SOC online in real
time use the ampere-hour measurement method. Since there are errors in
ampere-hour measurement, the cumulative error will become larger and larger as
the usage time increases. Therefore, this method is used alone to estimate the
SOC of the battery. It doesn't achieve very good results. In actual use, most of
them are used in combination with the open circuit voltage method, but the flat
OCV-SOC curve of LiFePO4 has little significance in correcting the ampere-hour
measurement. Therefore, some scholars use the characteristics of the larger
polarization voltage of the battery in the later stages of charge and discharge
to correct the SOC. For LiFePO4 batteries, when the polarization voltage
increases significantly, the battery SOC is approximately above 90%. The
relationship between the battery's state of charge and charging current can be
divided into three stages: the first stage, low-end SOC (such as SOC <10%),
the internal resistance of the battery is large, and the battery is not suitable
for high-current charging and discharging; the second stage Segment, the middle
segment of the battery's SOC (such as 10%90% ), in order to prevent
lithium deposition and over-discharge, the acceptable charge and discharge
current of the battery decreases. Fundamentally, in order to prevent the battery
from having a bad impact on battery life when it is in extreme working
conditions, the battery should be controlled not to work at both ends of the
SOC. Therefore, this article does not recommend using the characteristic of
higher polarization voltage when the battery is at both ends of the SOC to
correct the SOC.
The data required by the artificial neural network method and Kalman
filtering method are mainly based on changes in battery voltage to obtain
satisfactory results, so they cannot meet the accuracy requirements of LiFePO4
batteries for SOC.
This article takes the mass-produced LiFePO4 batteries used in pure
electric vehicles as the research object, analyzes the characteristics of
LiFePO4 batteries, and proposes an accurate method to correct the SOC of LiFePO4
batteries based on the existing SOC estimation analysis.
3. ΔQ/ΔV method
In the electrochemical measurement method, when analyzing the relationship
between the chemical reaction rate inside the battery and the electrode
potential, a commonly used method is the linear potential sweep method
(potentialsweep) to control the electrode potential to change at a constant
speed, that is, to measure the current passing through the electrode at the same
time.
This method is also often called voltammetry in electrochemistry. The rate
of linear scan has a great influence on the shape and value of the polarization
curve of the electrode. When there is an electrochemical reaction in the battery
during charge and discharge, the faster the scan rate, the greater the
polarization voltage of the electrode. Only when the scan rate is slow enough
When, a stable volt-ampere characteristic curve can be obtained. At this time,
the curve mainly reflects the relationship between the electrochemical reaction
rate inside the battery and the electrode potential. The volt-ampere curve
reflects important characteristic information of the battery, but in actual
engineering applications, real-time measurement of the volt-ampere curve is
basically not carried out.
The main reason is that there is no linear potential scanning condition
during the charging and discharging process of the battery, making it impossible
to directly obtain the volt-ampere curve of the battery.
The constant current-constant voltage (CC-CV) charging method is currently
a commonly used battery charging method. The potential always changes at a
constant rate during the potential scan. The electrochemical reaction rate
changes with the change of the potential. The battery changes over a period of
time. The amount of electricity Q charged and discharged with current i within
(t1-t2) is:
By measuring the voltage and current of the battery online, the voltage is
constantly changed in the direction of charge and discharge, a set of voltages
ΔV is obtained at equal intervals, and the current is integrated over the time
interval of each ΔV to obtain a set of ΔQ, based on the ΔQ that can be measured
online The /ΔV curve can reflect the charge and discharge capacity of the
battery at different electrode potential points. Figure 2 shows the ΔQ/ΔV curve
of a 20Ah LiFePO4 battery under 1/20C constant current charging.
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