What is the power lithium ion battery SOC estimation method?

　　Author ：Iflowpower – Portable Power Station Supplier

Since the development of battery technology, it has been used to estimate the SOC's approach. There are only traditional current integral, battery internal resistance, discharge experiment, open circuit voltage method, load voltage method, and more innovative Kalman filtering method. Fuzzy logical theory and neural network law, etc.

, various estimated methods have their own advantages and disadvantages, and the following is a brief analysis of commonly used SOC methods: (1) Current integral method is also called safety metering method, It is currently one of the more common SOC estimation methods in the category of the battery management system, and the essence is based on battery charging or discharge, by accumulating the amount of electricity that is filled or released to estimate the SOC of the battery while at the same time according to the discharge rate and battery temperature. A certain compensation for the estimated SOC. If the SOC value of the battery in the initial state of the battery is SOCT0, then the remaining capacity SOC after T always is: q, q is the battery rated capacity, N is charge and discharge efficiency, also called coulomb efficiency, its value The battery charge and discharge rate is determined, I is the current of T.

Compared to other SOC estimation methods, current integration method is relatively simple and reliable, and can dynamically estimate the SOC value of the battery, which is widely used. However, there are also two limitations: one, the current integral method should obtain the initial SOC value of the battery in advance, and accurately collect the current flowing into or out of the battery to make the estimation error be as small as possible; two, which The way is only the external characteristics of the battery. As the SOC estimation, it is ignored that the battery's self-discharge ratio, the degree of aging, and the charge and discharge ratio on the battery SOC.

Long-term use can also cause the measurement error to continue to accumulate Zhang Da, so to introduce related Correction correction factor. (2) Discharge Experiment Method The discharge test method is to continue the constant current discharge of the target battery until the cutoff voltage of the battery, multiply the time used by this discharge process by the size value of the discharge current, that is, the remaining capacity of the battery. This method generally uses this method as a calibration method for battery SOC or in the later maintenance of the battery, which does not understand the battery SOC value, relatively simple, reliable, and the result is also more accurate, and the different kinds of batteries All effectively.

However, there are two deficiencies in the discharge experiment method: First, the experimental process of this approach takes a lot of time; second, when using this approach, the target battery should be removed from the electric vehicle, so the approach cannot be used to calculate Power lithium ion battery in working state. (3) Open circuit voltage method is indirectly fitted with a correspondence between the battery SOC in accordance with the change relationship between the open circuit voltage of the battery and the internal lithium ion concentration of the battery. When the actual operation is performed, the battery is perfiltrated by the fixed discharge ratio (generally 1c) to discharge until the discharge is stopped, and the discharge process obtains the relationship curve between OCV and SOC according to the discharge process.

When the battery is in the actual working state, it can be based on the voltage value at both ends of the battery, and the current battery SOC is obtained by finding the OCV-SOC relational table. Although this approach is effective for various batteries, there is also its own defect: First, the target battery is not allowed to stand more than 1 h before measuring the OCV, thereby displacing the internal electrolyte of the battery to obtain a stable end voltage; second, the battery is at different temperatures Or during different life, although the open circuit is the same, the actually SOC may differ, and the measurement results of the measurement of this method are not guaranteed. Therefore, the open circuit voltage method is the same as the discharge experiment, and does not apply to the running battery SOC estimation.

(4) Kalman filtering method KALMAN filtering method is a new type of optimized self-regression data filtered in the "New Achievements of Linear Filtering and Forecasting Theory" in the 1960s. algorithm. The essence of the algorithm is that the state of the complex dynamic system can be optimized for the state of the complex dynamic system according to the principle of the least hometown.

Non-linear dynamic systems will be linear into a state space model of the system in the Kalman filtering method. When the system is based on the estimation value of the current time, the system variable is updated, and the prediction is followed. Error correction mode, eliminating the deviation and interference of the system random.

When the SOC of the dynamic lithium ion battery is estimated using the Kalman filtering method, the battery is converted into a state space model in the form of a power system, and the SOC becomes a state variable inside the model. The established system is a linear discrete system. Since the Kalman filtering method can not only correct the system initial error, it can effectively suppress system noise, so there is a significant use value in the SOC estimation of electric vehicle power lithium-ion batteries in operation conditions.

However, the method also exists two-point defects: 1. Kalman filtering method estimates the accuracy of the SOC depends to a large extent on the accuracy of the battery model, and the working characteristics itself is highly non-linearly powered lithium-ion battery, in Kalman filtering method. After linearization, it is inevitable that there is no error, and if the model is established is not accurate enough, its estimation is not necessarily reliable; two, the algorithm involved in this approach is very complicated, the calculation amount is very large, the calculation cycle is longer, And demanding hardware performance requirements.

(5) Neural network method neural network method is analog human brain and its neuron used to solve the new type of algorithm for non-linear systems, and there is no need to study the internal structure of the battery, and simply extract a large number of working characteristics from the target battery in advance. Enter the SOC value of the run from the output sample and enter it into the system established by using this Member. This method is relatively simple in later periods, that is, it is necessary to take the error of the battery model after linearization in the Kalman filtering method, but also obtain the dynamic parameters of the battery in real time.

However, the previous period of the neural network method is relatively large, to extract a large number and comprehensive target sample data to train the system, the way the training data and training in the training data will be largely affecting the estimation accuracy of SOC. In addition, under the complex use of battery temperature, self-discharge ratio and battery aging, the same set of batteries is estimated to estimate the SOC value of the same set of batteries, and the accuracy will also be big discount. Therefore, this approach is not much in the SOC estimation of the power lithium-ion battery.