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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