When the lithium-ion power battery is working, whether the vehicle is in a driving state or a parking state, the battery system will cause a series of electrochemical reactions to cause capacity attenuation. When the remaining discharge capacity of the battery system is less than 80% of the rated capacity, it is considered end of life. The life state of the lithium-ion power battery system directly affects the performance of the vehicle, and the length of the life is also an important content that designers and customers care about. This chapter first introduces the commonly used SOC estimation methods for power batteries, establishes a lithium-ion power battery model, fits the life curve of the battery system according to the cycle life test data, and estimates the life of the power battery, which is the rational use of the on-board battery system and prolongs the use of the battery system. Longevity provides an important basis.
1.1 Commonly used state-of-charge estimation methods
What is the method of estimating the SOC of lithium-ion power battery?
The measurement of the state of charge of lithium-ion power batteries can be divided into two categories: based on the measurement of battery internal parameters (active material parameters or electrolyte) or external parameters (voltage, current, temperature), and its characteristics are shown in Figure 3-1. . Since the real-time detection of battery internal parameters is not operational after the battery leaves the factory, this section mainly focuses on the measurement of external parameters such as battery voltage, current, and temperature. It is also because of the complex electrochemical characteristics of the battery itself and many factors that affect the estimation of the battery. The estimation of the battery state of charge is always the difficulty and focus of battery management and electric vehicle applications.
At present, SOC estimation methods are mostly used in open circuit voltage method and Ah integral method. In recent years, researchers have successively developed some new power battery SOC estimation methods, such as neural network method, Kalman filter method, impedance spectroscopy and other smarter algorithms. These methods are usually used in the literature of Power County) The basic method and its advantages and disadvantages of the more commonly used food in pediatrics are briefly introduced.
1.1.1 Open circuit voltage method
The electromotive force of the power battery is not much different from its open circuit voltage in value. The open circuit voltage method can be used to
Short-term measurement, it is closely related to the electrolyte concentration, and can be directly used for the measurement of the state of charge SOC:
Formula Figure 1-1 State-of-charge SOC measurement
In the formula, Ua represents the open circuit voltage value when the battery is fully charged; Ub represents the open circuit voltage value when the battery is fully discharged. This method is effective in the initial and final stages of battery charging. The disadvantage is that the over-potential may cause the battery to be overcharged for 5h or longer to ensure that its terminal voltage reaches a steady state, and then the true open circuit voltage value can be obtained. This shortcoming causes certain difficulties in the actual measurement, and it is not easy to accurately determine the resting time of the battery. Therefore, this method is suitable for the parking state of electric vehicles. Figure 3-2 is a graph of the relationship between open circuit voltage OCV and battery SOC.
Figure 1-2 OCV and SOC relationship curve
It can be found from Figure 1-2 that the relationship curve between open circuit voltage OCV and battery SOC is basically linear. In the initial stage of battery discharge, the battery SOC changes steeply with the voltage drop, and almost shows a complete linear relationship in the middle of the discharge, while the battery SOC value tends to be relatively flat at the end of the discharge.
1.1.2 Neural Network Method
Since the power battery of electric vehicles is a highly nonlinear system, it is difficult to establish an accurate mathematical model for its use parameters. The neural network has the basic properties of non-linearity, and can give corresponding output to the input layer data through training, so it fits the characteristics of the battery and can dynamically simulate its charging and discharging, and predict the SOC value. The estimation of battery SOC usually uses a three-layer typical neural network. The number of neurons in the middle layer depends on the complexity and analysis accuracy of the research problem. The input and output layer neurons are usually linear functions, and the number is determined In the actual situation of the network. To estimate the state of charge of the battery, the commonly used input variables are the current battery temperature, internal resistance, voltage, accumulated discharge capacity, current, and historical charge and discharge data or changes in related parameters. Whether the choice of input parameter types and the choice of training samples for each parameter is reasonable is closely related to the accuracy of the network model construction and the estimated amount of calculation.
Neural network can be used in various types of batteries, and its application in power battery estimation shows certain advantages, and it is also a current research hotspot. The main disadvantage is that the estimated output is greatly affected by the training method and training data.
1.1.3 Kalman filter method
The essence of the Kalman filter method is a method to make the best estimation of the system state. When applied to the estimation of the power battery SOC algorithm, the power battery is regarded as a system, and the battery S0C is the internal state of the system. By establishing the corresponding power battery SOC estimation model, the recursive algorithm is used to achieve the minimum variance. Excellent estimate.
The Kalman filter method is suitable for all kinds of batteries. The estimation accuracy is high. It can correct the initial error of the battery estimation. It also has a certain inhibitory effect on the interference noise. It is very suitable for the estimation of the SOC battery of electric vehicles with severe current fluctuations. The disadvantage is that the algorithm requires a lot of data to be processed, the algorithm is complex, and the calculation speed of software and hardware is high.
1.1.4 Ah integration method
This is a method of measuring the discharge capacity or ampere-hours, and it is a relatively simple and commonly used method to determine the state of charge of the battery. If the initial state of the power battery during operation is SOC0, then the state of charge estimation formula of the battery during charging and discharging is shown in formula (1-3)
Formula Figure 1-3 The state of charge of the battery during charging and discharging
Among them, CN represents the rated capacity of the battery; Ⅰ represents the working current of the battery.
However, the above ampere-hour method does not consider the battery’s charge and discharge efficiency, self-discharge, etc., and the current integration is usually used to correct this deviation. The Ah measurement method mainly has the following problems:
(1) Measurement offset: including difficulty in obtaining the initial state SOCO accurately and inaccurate measurement of current.
Before using the ampere-hour integration method, the initial state of charge value of the battery must be determined. The OCV-SOC experimental relationship table is usually used to calculate S0C0. However, for the working power battery, the battery does not have enough standing time. The initial voltage value detected at this moment and the electromotive force of the battery have a certain error, and the resulting SOC0 is also inaccurate, leading to subsequent battery S0C estimation It’s not accurate enough. When the power battery of an electric vehicle is working, the temperature of the battery will constantly change, and the working current will also fluctuate sharply. Therefore, the current measurement will be inaccurate, which will lead to battery estimation errors. With the increase of time, the integral value of the current will be larger and larger, and the error will be larger.
(2) The estimation of the charge and discharge efficiency is wrong. The self-discharge speed and aging characteristics of the battery during use have not been accurately considered. In this regard, a large number of experiments must be done in advance to establish the empirical formula of the charge and discharge efficiency of this type of battery. At the same time, after the battery has been running for a period of time, the ampere-hour model needs to be modified according to the battery’s usage.
In general, the Ah measurement method has a wide range of applications and is also a relatively simple and reliable method for estimating battery SOC. It usually needs to be combined with the open circuit voltage method.
1.1.5 Internal resistance method
The internal resistance of the battery is divided into DC internal resistance and AC internal resistance. In a period of time, the DC internal resistance of the power battery is expressed as the ratio of the change of the terminal voltage and the current. In practical applications, when the power battery is charged and discharged, the open circuit voltage value and the load voltage value are measured, and the two values are made the difference, and the difference is compared with the current to get the battery’s DC internal resistance. According to the inherent characteristics of lead-acid batteries, in the later stage of battery discharge, the DC internal resistance changes significantly, which is suitable for battery estimation.
The AC internal resistance of the battery is a complex variable and needs to be measured with an instrument. The AC impedance of the power battery is easily affected by external factors, and at the same time, researchers have not yet reached a conclusion about the application of its measurement, so it is rarely used in real vehicles.
Comparing the two internal resistance methods, the AC internal resistance is not practical, and the estimation of the DC internal resistance is easily affected by the time period: if only a short-term estimation is performed, the polarization internal resistance of the battery will not be detected; otherwise, the estimated time If it is too long, the internal resistance will be more complicated. Therefore, the internal resistance method of battery estimation is only applicable to the later stage of battery discharge.