Battery SOC estimation and calibration method, terminal and multi-battery energy storage system

Abstract

The invention discloses a battery SOC (state of charge) estimation and calibration method, a terminal and a multi-battery energy storage system, a battery comprises a plurality of groups of same battery modules, and a function curve of a corresponding relation between open-circuit voltage and a state of charge SOC of the battery modules at each temperature is constructed; calculating the SOC operation lower limit and the SOC operation upper limit of each battery module at the corresponding operation temperature based on the function curve; estimating the SOC value of each battery module through an unscented Kalman filtering algorithm, and calculating the SOC value of the battery; and controlling the battery and each battery module to respectively work between the corresponding SOC operation lower limit and the SOC operation upper limit, and if the battery module reaches the preset calibration condition, calibrating the SOC of the battery module, thereby realizing accurate estimation of the battery SOC in the irregular charging and discharging energy storage system, reducing the difficulty in obtaining the calibration point, and improving the accuracy of the calibration point. And the SOC calibration frequency and accuracy of the battery are improved.

Description

Technical Field

[0001] The present invention relates to the field of lithium battery technology, and in particular to a battery SOC estimation and calibration method, a terminal and a multi-battery energy storage system. Background Art

[0002] In lithium-ion battery energy storage systems, accurate SOC estimation is crucial to optimizing battery management, improving system performance, and ensuring operational safety. It can optimize charging and discharging strategies, reduce energy loss, ensure stable operation of the power system, extend battery life, prevent safety accidents, and enhance user confidence. It is also the basis for other state estimations.

[0003] In the prior art, the ampere-hour integration method (AHI) is a commonly used SOC estimation method, but it is an open-loop estimation, which cannot quickly correct the initial error and will accumulate measurement system errors. The actual capacity of the battery is affected by environmental factors such as temperature, so the integral model needs to be constantly corrected, and frequent and regular calibration points are required; the open circuit voltage method can be used to estimate SOC in certain regular operating scenarios, but its OCV value varies little within the specific SOC range of certain batteries, the measurement resolution is insufficient, and OCV data is difficult to obtain during the continuous charging and discharging of the battery; the Kalman filter method makes the estimated value close to the true value through a closed loop, but the time-varying parameters of the battery make the battery a nonlinear system. The basic Kalman filter cannot handle nonlinear systems, and a linearization method needs to be used. Therefore, no matter which of the above methods is used, there are problems that need to be solved when applied to energy storage systems:

[0004] (1) Ampere-hour integration method: In irregular charging and discharging scenarios such as industrial and commercial energy storage and power energy storage, errors are easily accumulated and cannot be calibrated for a long time, resulting in large deviations.

[0005] (2) SOC estimation precision: The battery-level SOC estimation is usually performed by the master controller, which is not precise enough. In a multi-battery powered energy storage system, due to differences in working conditions, when the parallel batteries are charged and discharged at the same power, the SOC of each battery is different, which affects the total capacity of the system.

[0006] (3) Calibration point acquisition: The general SOC estimation method can only be calibrated at the critical point of full charge or full discharge. In scenarios where the battery needs to work in a certain range and is frequently charged and discharged, the calibration point is not easy to obtain, which increases special working conditions and human intervention, affecting the utilization efficiency of the energy storage system.

[0007] (4) Power distribution method: The method of evenly distributing power in the system will aggravate the inherent consistency of the battery and reduce the available capacity of the battery.

[0008] (5) Balancing problem: Generally, energy storage batteries are balanced at the cell level, which results in low power and low efficiency. Active balancing is costly and complex to control.

[0009] (6) Problem of OCV value change: For example, if the OCV value of an LFP cell changes slightly within a certain SOC range, it is difficult to effectively distinguish the changes by sampling, which makes it difficult to estimate the SOC in this range. Summary of the invention

[0010] The technical problem to be solved by the present invention is to provide a method, terminal and multi-battery energy storage system for estimating and calibrating battery SOC, so as to accurately estimate the battery SOC in an energy storage system with irregular charging and discharging, reduce the difficulty of obtaining calibration points, and improve the frequency and accuracy of battery SOC calibration.

[0011] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0012] A method for estimating and calibrating battery SOC, wherein the battery comprises a plurality of identical battery modules, comprising the steps of:

[0013] S1. constructing a function curve of the corresponding relationship between the open circuit voltage and the state of charge SOC of the battery module at each temperature;

[0014] S2. Calculating the SOC lower limit and the SOC upper limit of each battery module at the corresponding operating temperature based on the function curve;

[0015] S3, estimating the SOC value of each battery module by using an unscented Kalman filter algorithm, and calculating the SOC value of the battery;

[0016] S4, controlling the battery and each of the battery modules to operate between the corresponding SOC lower limit and SOC upper limit, and if the battery module reaches a preset calibration condition, calibrating the SOC of the battery module.

[0017] In order to solve the above technical problems, another technical solution adopted by the present invention is:

[0018] A battery SOC estimation and calibration terminal comprises a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps in the above-mentioned battery SOC estimation and calibration method are implemented.

[0019] In order to solve the above technical problems, another technical solution adopted by the present invention is:

[0020] A multi-battery energy storage system, comprising a plurality of identical batteries, a plurality of bidirectional DC / DC converters, a plurality of bidirectional AC / DC converters, a plurality of energy storage control units, a DC bus and an AC bus;

[0021] Each battery is connected to the DC bus or the AC bus through the bidirectional DC / DC converter or the bidirectional AC / DC converter;

[0022] Each battery includes a battery controller and a plurality of battery modules, the battery controller communicates with the energy storage control unit, and the energy storage control unit communicates with the bidirectional DC / DC converter or the bidirectional AC / DC converter;

[0023] The multi-battery energy storage system implements the steps in the above-mentioned method for estimating and calibrating battery SOC.

[0024] The beneficial effects of the present invention are as follows: a method, terminal and multi-battery energy storage system for estimating and calibrating the battery SOC of the present invention construct a function curve of the corresponding relationship between the open-circuit voltage of the battery module and the state of charge SOC at various temperatures to replace the cell curve, thereby improving the resolution of the corresponding voltage and facilitating the calibration and judgment of the open-circuit voltage; the SOC calibration point is obtained based on the function curve, and the influence of temperature is combined to dynamically adjust the battery operation range and calibration range, which is conducive to full utilization of the battery and improving the SOC calibration frequency; the SOC is estimated by using the unscented Kalman filter method in units of modules, and the SOC of the battery is calculated accordingly, so that the battery SOC estimation is more accurate and the influence of conditions such as reaction temperature can be reflected, and the SOC estimation value can be corrected in real time in combination with battery parameters, thereby improving the estimation accuracy and the available capacity of the battery, and can be applicable to nonlinear systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A flowchart of a method for estimating and calibrating battery SOC according to an embodiment of the present invention;

[0026] Figure 2 A specific flow chart of a method for estimating and calibrating battery SOC according to an embodiment of the present invention;

[0027] Figure 3 A schematic diagram of a fitting function curve of a method for estimating and calibrating battery SOC according to an embodiment of the present invention;

[0028] Figure 4 A schematic diagram of a method for calculating the upper and lower limits of SOC operation in a method for estimating and calibrating battery SOC according to an embodiment of the present invention;

[0029] Figure 5 A first-order equivalent circuit diagram of a battery module of a method for estimating and calibrating battery SOC according to an embodiment of the present invention;

[0030] Figure 6 A schematic diagram of an SOC estimation process and a UKF algorithm of a method for estimating and calibrating a battery SOC according to an embodiment of the present invention;

[0031] Figure 7 A structural diagram of a terminal for battery SOC estimation and calibration according to an embodiment of the present invention;

[0032] Figure 8 A structural diagram of a multi-battery energy storage system according to an embodiment of the present invention;

[0033] Description of labels:

[0034] 1. A battery SOC estimation and calibration terminal; 2. A processor; 3. A memory. DETAILED DESCRIPTION

[0035] In order to explain the technical content, achieved objectives and effects of the present invention in detail, the following is an explanation in combination with the implementation modes and the accompanying drawings.

[0036] Please refer to Figure 1 and Figure 2 A method for estimating and calibrating battery SOC, wherein the battery comprises a plurality of identical battery modules, comprising the steps of:

[0037] S1. constructing a function curve of the corresponding relationship between the open circuit voltage and the state of charge SOC of the battery module at each temperature;

[0038] S2. Calculating the SOC lower limit and the SOC upper limit of each battery module at the corresponding operating temperature based on the function curve;

[0039] S3, estimating the SOC value of each battery module by using an unscented Kalman filter algorithm, and calculating the SOC value of the battery;

[0040] S4, controlling the battery and each of the battery modules to operate between the corresponding SOC lower limit and SOC upper limit, and if the battery module reaches a preset calibration condition, calibrating the SOC of the battery module.

[0041] From the above description, it can be seen that the beneficial effects of the present invention are: constructing a function curve of the corresponding relationship between the open circuit voltage of the battery module and the state of charge SOC at various temperatures to replace the battery cell curve, thereby improving the resolution of the corresponding voltage and facilitating the calibration and judgment of the open circuit voltage; obtaining the SOC calibration point based on the function curve, combining the influence of temperature, so that the battery operating range and the calibration range are dynamically adjusted, which is conducive to the full utilization of the battery and improving the SOC calibration frequency; using the unscented Kalman filter method to estimate the SOC in units of modules, and calculating the SOC of the battery based on this, so that the battery SOC estimation is more accurate and the influence of reaction temperature and other conditions can be reflected, and the SOC estimation value can be corrected in real time in combination with the battery parameters, thereby improving the estimation accuracy and the available capacity of the battery, and can be applicable to nonlinear systems.

[0042] Further, step S1 includes the steps of:

[0043] S11, taking a first preset number of temperature points, and taking a second preset number of state of charge SOC points at each temperature point, and performing discharge and charge tests on the battery module at the same rest time, respectively, to obtain the discharge and charge open circuit voltages corresponding to each SOC point of the battery module at different temperature points, wherein the discharge open circuit voltage is:

[0044] V OCV =[V OCV_T1 ,...,V OCV_Tk ] T ;

[0045] in:

[0046] V ocv_Ti =[V Ti_SOC1 ,V Ti_SOC2 ,...,V Ti_SOCn ],i∈(1,k);

[0047] V Ti_SOCn is the open circuit voltage at the nth SOC point at the ith temperature point under the discharge test condition;

[0048] The charging open circuit voltage is:

[0049] V′ OCV =[V′ OCV_T1 ,...,V′ OCV_Tk ] T ;

[0050] in:

[0051] V′ ocv_Ti =[V' Ti_SOC1 ,V′ Ti_SOC2 ,...,V′ Ti_SOCn ,];

[0052] V′ Ti_SOCn is the open circuit voltage at the nth SOC point at the ith temperature point under the charging test condition;

[0053] S12, calculating a three-dimensional data set of the static open circuit voltage of the battery module at the first preset number of temperature points, wherein the calculation formula of the static open circuit voltage is:

[0054] U OCV =(V OCV +V′ OCV ) / 2;

[0055] S13, performing high-order polynomial fitting on the three-dimensional data set of the static open-circuit voltage to obtain a fitting function U at the first preset number of temperature points OCV_Ti =fTi (SOC).

[0056] From the above description, it can be seen that by performing discharge and charging tests at multiple temperature points and multiple SOC points at each temperature point, the open circuit voltage data of the battery module is obtained, and a three-dimensional data set is constructed to intuitively present the relationship between voltage, temperature and SOC. The fitting function is then obtained through high-order polynomial fitting, which provides a rich and accurate data foundation for a comprehensive and in-depth understanding of the battery module performance. The relationship expression is simplified by the fitting function, which is convenient for the subsequent prediction of voltage under untested conditions, evaluation of battery performance, estimation of remaining power and precise control of battery modules in the battery management system.

[0057] Further, step S2 includes the steps of:

[0058] S21, obtaining the operating temperature of any battery module in the battery, performing temperature interpolation between the two function curves that are closest to the operating temperature in the function curve, and obtaining the open circuit voltage U of any module at the operating temperature. OCV data;

[0059] S22, selecting a step length ΔSOC based on the SOC calculation resolution to form a point set SOC_x, and calculating the open circuit voltage U at each discrete point of the calculation point set OCV The value of constitutes the point set U OCV _x;

[0060] S23, calculating the point set U according to the point set SOC_x OCV The difference between any two adjacent values ​​in _x, where the difference between any two adjacent values ​​is calculated as:

[0061] E(j)=U OCV_x (j)-U OCV_x (j-1),j∈(1,p);

[0062] Where p is the number of discrete points in SOC_x obtained by evenly dividing the SOC value range [0,100] according to the step size ΔSOC;

[0063] When the difference satisfies a preset condition, the SOC lower limit and the SOC upper limit of the battery module are obtained, and the corresponding open circuit voltage lower limit reference value and the open circuit voltage upper limit reference value are obtained;

[0064] S24, repeating steps S21 to S23 until the SOC operating lower limit, the SOC operating upper limit, the open circuit voltage lower limit reference value, and the open circuit voltage upper limit reference value of all battery modules at the corresponding operating temperature are obtained.

[0065] From the above description, we can know that U is obtained by interpolating the operating temperature of the battery module. OCVData is selected, and the step size is determined to calculate the set of calculation points and calculate U OCV Value. The SOC operating limit and the reference voltage are determined according to the difference between adjacent values, and the operation is repeated to obtain all the relevant parameters of the module, which is beneficial to adapting to the working conditions of the battery module in different temperature environments, improving the adaptability of the entire SOC estimation and management system to the actual operating conditions, and comprehensively obtaining the module parameters to realize the optimal management of the battery system.

[0066] Further, in step S23, when the difference satisfies the preset condition, the SOC operating lower limit and the SOC operating upper limit of the battery module are obtained, and the corresponding reference value of the lower limit of the open-circuit voltage and the reference value of the upper limit of the open-circuit voltage are obtained. Specifically:

[0067] When E(j) < ε and E(j) < E(j - 1), the point SOC_x(j) in the point set SOC_x is the SOC operating lower limit of the battery module, corresponding to U OCV _x in the point set U OCV _x(j) is the reference value of the lower limit of the open-circuit voltage of the battery module;

[0068] When E(j) > ε and E(j) > E(j - 1), the point SOC_x(j) in the point set SOC_x is the SOC operating upper limit of the battery module, corresponding to U OCV _x in the point set U OCV _x(j) is the reference value of the upper limit of the open-circuit voltage of the battery module.

[0069] As can be seen from the above description, the SOC operating lower limit and upper limit are defined based on the characteristics of the open-circuit voltage changing with SOC obtained by actual measurement, making the determined SOC operating lower limit and upper limit more in line with the true performance of the battery module, avoiding overcharging and over-discharging of the battery from affecting its lifespan, and providing an accurate judgment basis for subsequent battery management operations to ensure the stable operation of the system.

[0070] Further, step S4 includes the steps of:

[0071] S41. Obtain the SOC operating lower limit and the SOC operating upper limit of all battery modules in the battery and construct a data set. Use the highest value of the SOC operating lower limit in the data set as the SOC operating lower limit of the battery, and use the lowest value of the SOC operating upper limit in the data set as the SOC operating lower limit of the battery;

[0072] S42. Control the battery to work within the SOC operating lower limit and the SOC operating upper limit of the battery, and control the SOC of each battery module in the battery to work within the SOC operating lower limit and the SOC operating upper limit of each battery module respectively;

[0073] S43, calculating the equivalent open circuit voltage of the battery module, and if the current equivalent open circuit voltage is equal to the lower limit reference value of the open circuit voltage of the battery module, calibrating the SOC of the battery module to the SOC operation lower limit of the battery module;

[0074] If the current equivalent open circuit voltage is equal to the open circuit voltage upper limit reference value of the battery module, calibrating the SOC of the battery module to the SOC operating upper limit of the battery module;

[0075] The calculation formula of the equivalent open circuit voltage is:

[0076] W OCV_h =e h -I h R0;

[0077] Among them, W OCV_h is the equivalent open circuit voltage, e h is the voltage of the hth module, I h is the current of the hth module, the charging direction is positive and the discharging direction is negative, R0 is the module ohmic internal resistance, h∈(1,s), s is the number of battery modules in the battery.

[0078] From the above description, it can be seen that by obtaining the module SOC limit to determine the overall operating range of the battery, controlling the battery and module to work in a reasonable range to ensure stability, the battery performance can be optimized to extend the life; the module SOC is calibrated based on the equivalent open circuit voltage and the reference value to improve the SOC estimation accuracy, so that the battery management system can better grasp the actual state of the battery module, optimize the charging and discharging strategy, and further improve the performance of the battery system.

[0079] Further, step S3 includes the steps of:

[0080] S31, establish the equivalent circuit of the battery module, and measure the parameters R of the battery module offline. 0_(T,SOC) , R 1_(T,SOC) , C 1_(T,SOC) , construct the discretized state equation of the battery module;

[0081] The battery module discretization state equation is:

[0082]

[0083] Where U is the equivalent capacitance C 1_(T,SOC) The voltage across the two terminals. The subscripts (T, SOC) in the parameters indicate that their values ​​are related to the module temperature T and SOC. Qm is the module capacity, SOC t , U t and SOC t+1 , U t+1They are the module SOC state and equivalent capacitor voltage state at time t and time t+1, respectively. t is the module current at time t, T s is the calculation step size, W is the process noise;

[0084] S32, constructing a measurement equation of the battery module according to the measurable state quantity of the battery module, the measurement equation being:

[0085] e t+1 =U OCV_T_t+1 -U t+1 -I t+1 R 0_(T,SOC) +V;

[0086] Among them, e t+1 It represents the module output voltage at time t+1, U OCV_T_t+1 is the open circuit voltage at time t+1, I t+1 is the module current at time t+1, V is the measurement noise, U t+1 is the equivalent capacitor voltage state at time t+1, R0 is the module ohmic internal resistance;

[0087] S33, estimating the state of charge SOC of the battery module at time t+1 by using an unscented Kalman filter algorithm UKF;

[0088] S34, summarizing the state of charge (SOC) of all battery modules in the battery at time t+1, obtaining the minimum and maximum values ​​of the state of charge (SOC) of all battery modules at time t+1, and calculating the SOC of the battery at time t+1, specifically as follows:

[0089]

[0090] Among them, SOC b is the battery's state of charge SOC, SOC m_min is the minimum SOC value of the module in the battery. m_max It is the maximum SOC value of the module in the battery.

[0091] From the above description, it can be seen that a discrete state equation of the battery module is established that takes into account the influence of temperature and SOC, a measurement equation is constructed based on the measurable state quantity, the module SOC is estimated using the unscented Kalman filter algorithm, and the battery SOC is calculated by combining the module SOC maximum value. This achieves the establishment of an accurate model to improve the accuracy of state assessment and optimize monitoring and evaluation in combination with measured values, which facilitates accurate estimation of SOC and improves the overall performance and consistency of the battery system.

[0092] Furthermore, step S4 includes the following steps:

[0093] S5, monitoring the SOC difference between the battery modules of the battery, obtaining the maximum value of the SOC difference, and when the maximum value is greater than a preset threshold, executing step S51 for the two groups of battery modules corresponding to the maximum value until the maximum value is no greater than the preset threshold;

[0094] S51, controlling the battery module with the largest SOC to discharge to the battery module with the smallest SOC at a constant power until the SOC of the discharged battery module is less than the average SOC of all battery modules or the SOC of the charged battery module is greater than the average SOC of all battery modules.

[0095] From the above description, it can be seen that by monitoring the maximum SOC difference between the battery modules, the SOC imbalance condition can be discovered in time. When the maximum value is greater than the preset threshold, the battery module with the largest SOC is controlled to discharge to the battery module with the smallest SOC until specific conditions are met, thereby achieving SOC balance adjustment, effectively reducing the difference in SOC between modules, making the SOC of each module tend to be consistent, which helps to improve the overall available capacity of the battery and ensure that the battery system can continue to operate efficiently under different operating conditions.

[0096] Furthermore, the battery is also connected to a converter, and the step S4 further includes the following steps:

[0097] The converter controls the operating power of the battery to be:

[0098]

[0099] Among them, SOC b is the battery SOC, SOC b_limit_low is the battery SOC operating lower limit, SOC b_limit_up is the upper limit of battery SOC operation, P d is the maximum discharge power of the battery, always a positive number, P c It is the maximum charging power of the battery, which is always a negative number.

[0100] From the above description, it can be seen that the power of the connected converter is controlled independently in real time according to the battery's state of charge SOC. By limiting the battery's operating power under different SOC states, power can be accurately allocated to effectively avoid overcharging and discharging, and reduce the speed of battery aging; improve the overall performance of the battery system, so that the battery can exert its optimal power capacity according to its own SOC; improve the system's operating stability, reduce voltage and current fluctuations; and adapt to complex working conditions to achieve flexible energy management.

[0101] Please refer to Figure 7A battery SOC estimation and calibration terminal includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps in the above-mentioned battery SOC estimation and calibration method are implemented.

[0102] From the above description, it can be seen that the beneficial effects of the present invention are: constructing a function curve of the corresponding relationship between the open circuit voltage of the battery module and the state of charge SOC at various temperatures to replace the battery cell curve, thereby improving the resolution of the corresponding voltage and facilitating the calibration and judgment of the open circuit voltage; obtaining the SOC calibration point based on the function curve, combining the influence of temperature, so that the battery operating range and the calibration range are dynamically adjusted, which is conducive to the full utilization of the battery and improving the SOC calibration frequency; using the unscented Kalman filter method to estimate the SOC in units of modules, and calculating the SOC of the battery based on this, so that the battery SOC estimation is more accurate and the influence of reaction temperature and other conditions can be reflected, and the SOC estimation value can be corrected in real time in combination with the battery parameters, thereby improving the estimation accuracy and the available capacity of the battery, and can be applicable to nonlinear systems.

[0103] Please refer to Figure 8 , a multi-battery energy storage system, comprising a plurality of identical batteries, a plurality of bidirectional DC / DC converters, a plurality of bidirectional AC / DC converters, a plurality of energy storage control units, a DC bus and an AC bus;

[0104] Each battery is connected to the DC bus or the AC bus through the bidirectional DC / DC converter or the bidirectional AC / DC converter;

[0105] Each battery includes a battery controller and a plurality of battery modules, the battery controller communicates with the energy storage control unit, and the energy storage control unit communicates with the bidirectional DC / DC converter or the bidirectional AC / DC converter;

[0106] The multi-battery energy storage system implements the steps in the above-mentioned method for battery SOC estimation and calibration.

[0107] From the above description, it can be seen that the beneficial effects of the present invention are: constructing a function curve of the corresponding relationship between the open circuit voltage of the battery module and the state of charge SOC at various temperatures to replace the battery cell curve, thereby improving the resolution of the corresponding voltage and facilitating the calibration and judgment of the open circuit voltage; obtaining the SOC calibration point based on the function curve, combining the influence of temperature, so that the battery operating range and the calibration range are dynamically adjusted, which is conducive to the full utilization of the battery and improving the SOC calibration frequency; using the unscented Kalman filter method to estimate the SOC in units of modules, and calculating the SOC of the battery based on this, so that the battery SOC estimation is more accurate and the influence of reaction temperature and other conditions can be reflected, and the SOC estimation value can be corrected in real time in combination with the battery parameters, thereby improving the estimation accuracy and the available capacity of the battery, and can be applicable to nonlinear systems.

[0108] A battery SOC estimation and calibration method, terminal and multi-battery energy storage system of the present invention are suitable for SOC estimation, calibration and SOC operating range control under single-battery or multi-battery working conditions.

[0109] Please refer to Figure 1 and Figure 2 Embodiment 1 of the present invention is: a method for estimating and calibrating battery SOC, wherein the battery comprises a plurality of identical battery modules, comprising the steps of:

[0110] S1. Construct a function curve of the corresponding relationship between the open circuit voltage and the state of charge SOC of the battery module at each temperature.

[0111] Step S1 includes the steps of:

[0112] S11, taking a first preset number of temperature points, and taking a second preset number of state of charge SOC points at each temperature point, and performing discharge and charge tests on the battery module at the same rest time, respectively, to obtain the discharge and charge open circuit voltages corresponding to each SOC point of the battery module at different temperature points, wherein the discharge open circuit voltage is:

[0113] V OCV =[V OCV_T1 ,...,V OCV_Tk ] T ;

[0114] in:

[0115] V ocv_Ti =[V Ti_SOC1 ,V Ti_SOC2 ,...,V Ti_SOCn ],i∈(1,k);

[0116] V Ti_SOCn is the open circuit voltage at the nth SOC point at the ith temperature point under the discharge test condition;

[0117] The charging open circuit voltage is:

[0118] V′ OCV =[V′ OCV_T1 ,...,V′ OCV_Tk ] T ;

[0119] in:

[0120] V′ ocv_Ti =[V' Ti_SOC1 ,V′ Ti_SOC2 ,...,V′ Ti_SOCn ,];

[0121] V′Ti_SOCn It is the open circuit voltage at the nth SOC point at the ith temperature point under charging test conditions.

[0122] S12, calculating a three-dimensional data set of the static open circuit voltage of the battery module at the first preset number of temperature points, wherein the calculation formula of the static open circuit voltage is:

[0123] U OCV =(V OCV +V′ OCV ) / 2.

[0124] In this embodiment, the first preset number of temperature points can be set according to actual needs. For example, k temperature points are taken, and correspondingly at T0, T1, T2, ..., T k At k temperature points, a discharge test is performed on a module with the same specifications as the module actually used, and n SOC points are preset to test the discharge open circuit voltage of the module to form a three-dimensional data set.

[0125] In this embodiment, the average of the test results of the same standing time in both the charging and discharging directions is used to offset the errors, improve the test accuracy, and shorten the test time. However, when testing under simple discharge or charging conditions, a long standing time is required at each SOC point. If the standing time is insufficient, the OCV test accuracy will be affected.

[0126] S13, performing high-order polynomial fitting on the three-dimensional data set of the static open-circuit voltage to obtain a fitting function U at the first preset number of temperature points OCV_Ti =f Ti (SOC).

[0127] Specifically, each row of the three-dimensional data set represents the data at a temperature point. OCV_Ti =f Ti (SOC) represents the fitting function at the i-th temperature point, ∈(1,k), and there are k functions in total.

[0128] In this embodiment, a module containing 52 lithium battery cells is taken, and n can be taken as 11, that is, SOC is divided into 10 intervals from 0 to 100% (each interval has a step size of 10%), and k is taken as 3 temperature points, and data are measured at 0°C, 25°C, and 45°C respectively, and the function U OCV =f(SOC) and plot it to get Figure 3 In other equivalent embodiments, the number of battery cells, the selection of SOC step length and the selection of temperature points are not limited to the above.

[0129] S2. Calculate the SOC lower limit and the SOC upper limit of each battery module at the corresponding operating temperature based on the function curve.

[0130] Step S2 comprises the steps of:

[0131] S21, obtaining the operating temperature of any battery module in the battery, performing temperature interpolation between the two function curves that are closest to the operating temperature in the function curve, and obtaining the open circuit voltage U of any module at the operating temperature. OCV data.

[0132] In this embodiment, when the module is running, the two closest functions U covering the temperature are selected from the k fitting function curves corresponding to the module. OCV_Ti =f Ti (SOC) to calculate the temperature difference between them. For example, assume that the current module average temperature (the average of all temperature sampling points in the module) is 34°C, and the k curves contain the function f at 35°C. 35 (SOC) and function f at 30℃ 30 (SOC), then select f 35 (SOC) and f 30 (SOC) Perform difference calculation at the same SOC point to obtain f 34 (SOC) function curve.

[0133] S22, selecting a step length ΔSOC based on the SOC calculation resolution to form a point set SOC_x, and calculating the open circuit voltage U at each discrete point of the calculation point set OCV The value of constitutes the point set U OCV _x.

[0134] S23, calculating the point set U according to the point set SOC_x OCV The difference between any two adjacent values ​​in _x, where the difference between any two adjacent values ​​is calculated as:

[0135] E(j)=U OCV _x(j)-U OCV _x(j-1),j∈(1,p);

[0136] Where p is the number of discrete points in SOC_x obtained by evenly dividing the SOC value range [0,100] according to the step size ΔSOC;

[0137] When the difference meets the preset condition, the SOC lower limit and the SOC upper limit of the battery module are obtained, and the corresponding open circuit voltage lower limit reference value and the open circuit voltage upper limit reference value are obtained.

[0138] In this embodiment, the point set SOC_x and the point set U OCV The number of points contained in _x is greater than the preset number of SOC points.

[0139] In this embodiment, the selection of the step size ΔSOC is based on the minimum SOC resolution required. For example, if the minimum resolution is 1%, then ΔSOC is taken as 1%. Corresponding to the 0-100% SOC range, the point set SOC_x contains p = 101 discrete points.

[0140] Reference Figure 4 , the preset condition is specifically: when E(j) < ε and E(j) < E(j - 1), the point SOC_x(j) in the point set SOC_x is the lower limit of the SOC operation of the battery module (SOC _limit_low ), corresponding to U OCV _x in the point set U OCV _x(j) is the reference value of the lower limit of the open circuit voltage of the battery module (U ocv_limit_low );

[0141] When E(j) > ε and E(j) > E(j - 1), the point SOC_x(j) in the point set SOC_x is the upper limit of the SOC operation of the battery module (SOC _limit_up ), corresponding to U OCV _x in the point set U OCV _x(j) is the reference value of the upper limit of the open circuit voltage of the battery module (U ocv_limit_up ).

[0142] In this embodiment, ε is the selected gradient value threshold. It can be seen from Figure 3 that the gradient begins to increase when the SOC is around 0.1 - 0.4 or 0.9.

[0143] S24. Repeat steps S21 to S23 until the lower limit of the SOC operation, the upper limit of the SOC operation, the reference value of the lower limit of the open circuit voltage, and the reference value of the upper limit of the open circuit voltage of all battery modules at the corresponding operating temperature are obtained.

[0144] S3. Estimate the SOC value of each battery module through the unscented Kalman filter algorithm and calculate the SOC value of the battery.

[0145] Step S3 includes the steps of:

[0146] S31. Establish the equivalent circuit of the battery module, and construct the discretized state equation of the battery module according to the parameters R 0_(T,SOC) , R 1_(T,SOC) , C 1_(T,SOC) of the battery module measured offline;

[0147] The discretized state equation of the battery module is:

[0148]

[0149] Where U is the equivalent capacitance C 1_(T,SOC) The voltage across the two terminals. The subscripts (T, SOC) in the parameters indicate that their values ​​are related to the module temperature T and SOC. Qm is the module capacity, SOC t , U t and SOC t+1 , U t+1 They are the module SOC state and equivalent capacitor voltage state at time t and time t+1, respectively. t is the module current at time t, T s is the calculation step size, and W is the process noise.

[0150] In this embodiment, Figure 5 As shown, the simulation equivalent circuit is a first-order equivalent circuit, and the obtained battery module discretization state equation is based on the first-order equivalent circuit, which contains 2 equations in total. In other equivalent embodiments, the module equivalent circuit is not limited to the first-order equivalent circuit, and can be a second-order or other order equivalent circuit. It can be known that when the equivalent circuit is second-order, the number of equations increases to 3, and so on.

[0151] S32, constructing a measurement equation of the battery module according to the measurable state quantity of the battery module, the measurement equation being:

[0152] e t+1 =U OCV_T_t+1 -U t+1 -I t+1 R 0_(T,SOC) +V;

[0153] Among them, e t+1 It represents the module output voltage at time t+1, U OCV_T_t+1 is the open circuit voltage at time t+1, I t+1 is the module current at time t+1, V is the measurement noise, U t+1 is the equivalent capacitor voltage state at time t+1, and R0 is the module ohmic internal resistance.

[0154] S33, estimating the state of charge SOC of the battery module at time t+1 by using an unscented Kalman filter algorithm UKF.

[0155] In this embodiment, Figure 6 As shown, the specific process of the UKF algorithm is:

[0156] Prediction step (state update): Based on the current state estimate and covariance, calculate the Sigma point and weight, bring Sigma into the state equation for state prediction, and calculate the predicted SOC t+1 and covariance P t+1 ;

[0157] Update step (measurement update): use SOCt+1 and covariance P t+1 Update the Sigma point with the predicted value; Substitute the Sigma point into the measurement equation to calculate the measured SOC t+1 and covariance P t+1 ; Calculate Kalman benefit and update SOC t+1 The estimated value of .

[0158] S34, summarizing the state of charge (SOC) of all battery modules in the battery at time t+1, obtaining the minimum and maximum values ​​of the state of charge (SOC) of all battery modules at time t+1, and calculating the SOC of the battery at time t+1, specifically as follows:

[0159]

[0160] Among them, SOC b is the battery's state of charge SOC, SOC m_min is the minimum SOC value of the module in the battery. m_max It is the maximum SOC value of the module in the battery.

[0161] In this embodiment, the SOC of the battery is determined according to the SOC of each module in the battery. m_max With SOC m_min When the difference is large, some of the energy will be unusable, causing the capacity of the entire battery pack to decrease accordingly.

[0162] S4, controlling the battery and each of the battery modules to operate between the corresponding SOC lower limit and SOC upper limit, and if the battery module reaches a preset calibration condition, calibrating the SOC of the battery module.

[0163] Step S4 comprises the steps of:

[0164] S41. Obtain the SOC lower limit and SOC upper limit of all battery modules in the battery and construct a data set, with the highest value of the SOC lower limit in the data set being the SOC lower limit of the battery, and the lowest value of the SOC upper limit in the data set being the SOC lower limit of the battery.

[0165] S42, controlling the battery to operate within the SOC lower limit and the SOC upper limit of the battery, and controlling the SOC of each battery module in the battery to operate within the SOC lower limit and the SOC upper limit of each battery module.

[0166] S43, calculating the equivalent open circuit voltage of the battery module, and if the current equivalent open circuit voltage is equal to the lower limit reference value of the open circuit voltage of the battery module, calibrating the SOC of the battery module to the SOC operation lower limit of the battery module;

[0167] If the current equivalent open circuit voltage is equal to the open circuit voltage upper limit reference value of the battery module, calibrating the SOC of the battery module to the SOC operating upper limit of the battery module;

[0168] The calculation formula of the equivalent open circuit voltage is:

[0169] W OCV_h =e h -I h R0;

[0170] Among them, W OCV_h is the equivalent open circuit voltage, e h is the voltage of the hth module, I h is the current of the hth module (charging direction is positive, discharging direction is negative), R0 is the module ohmic internal resistance, h∈(1,s), s is the number of battery modules in the battery.

[0171] Furthermore, the battery is also connected to a converter, and the step S4 is followed by the step of:

[0172] The converter controls the operating power of the battery to be:

[0173]

[0174] Among them, SOC b is the battery SOC, SOC b_limit_low is the battery SOC operating lower limit, SOC b_limit_up is the upper limit of battery SOC operation, P d is the maximum discharge power of the battery, always a positive number, P c It is the maximum charging power of the battery, which is always a negative number.

[0175] In this embodiment, the operating power is within the power range from Pc to Pd according to the battery's own SOC and its upper and lower limit conditions.

[0176] S5. Monitor the SOC difference between the battery modules of the battery to obtain the maximum value of the SOC difference. When the maximum value is greater than a preset threshold, execute step S51 for the two groups of battery modules corresponding to the maximum value until the maximum value is no greater than the preset threshold.

[0177] In this embodiment, each module contains a balancing transformer for bidirectional energy flow, so that energy transfer and balancing can be performed between modules. When the maximum SOC difference of the modules is greater than a preset threshold, balancing is started, that is, SOC m_max -SOC m_min When ≥δ, balancing is enabled. δ is the module consistency threshold, which is determined based on actual needs.

[0178] S51, controlling the battery module with the largest SOC to discharge to the battery module with the smallest SOC at a constant power until the SOC of the discharged battery module is less than the average SOC of all battery modules or the SOC of the charged battery module is greater than the average SOC of all battery modules.

[0179] In this embodiment, the battery module with the largest SOC discharges to the battery module with the smallest SOC at a constant power, that is, at this time, the discharged battery module is the battery module with the largest SOC, and the charged battery module is the smallest battery module.

[0180] Please refer to Figure 7 The second embodiment of the present invention is: a terminal 1 for battery SOC estimation and calibration, comprising a processor 2, a memory 3, and a computer program stored in the memory 3 and executable on the processor 2. When the processor 2 executes the computer program, the steps in the method for battery SOC estimation and calibration described in the above embodiment 1 are implemented.

[0181] Please refer to Figure 8 , Embodiment 3 of the present invention is: a multi-battery energy storage system, comprising a plurality of identical batteries, a plurality of bidirectional DC / DC converters, a plurality of bidirectional AC / DC converters, a plurality of energy storage control units, a DC bus and an AC bus;

[0182] Each battery is connected to the DC bus or the AC bus through the bidirectional DC / DC converter or the bidirectional AC / DC converter;

[0183] Each battery includes a battery controller and a plurality of battery modules, the battery controller communicates with the energy storage control unit, and the energy storage control unit communicates with the bidirectional DC / DC converter or the bidirectional AC / DC converter;

[0184] The multi-battery energy storage system implements the steps in the method for battery SOC estimation and calibration described in the first embodiment above.

[0185] In this embodiment, the battery controller of each battery implements data collection, SOC calculation, etc. for the battery; each controller communicates with the energy storage control unit to upload the collection and calculation information; the energy storage control unit also communicates with the converters connected to each battery, and outputs power instructions to each converter according to the total power requirements.

[0186] The total power of all batteries satisfies the following formula:

[0187]

[0188] Where P system is the total required power of the energy storage system, P qis the power provided by the qth battery, q∈(1,m).

[0189] Furthermore, for the converter connected to the qth battery, q∈(1,m), the average power is controlled as:

[0190]

[0191] Among them, SOC b_q is the qth battery SOC; SOC b_limit_low_q is the lower limit of SOC of the qth battery; SOC b_limit_up_q is the upper limit of the SOC of the qth battery; P d is the maximum discharge power of the battery, which is the same for all batteries and is always a positive number; P c It is the maximum charging power of the battery. It is the same for all batteries and is always a negative number.

[0192] In this embodiment, according to the SOC and upper and lower limit conditions of each battery itself, the average operating power is within the power range formed by Pc to Pd. The battery with a higher SOC increases discharge and reduces charging, and vice versa, increases charging and reduces discharge, so that the SOC of each battery tends to be consistent.

[0193] In summary, a method, terminal and multi-battery energy storage system for estimating and calibrating the battery SOC of the present invention construct a function curve of the corresponding relationship between the open circuit voltage of the battery module and the state of charge SOC at each temperature to replace the battery cell curve, thereby improving the resolution of the corresponding voltage and facilitating the calibration and judgment of the open circuit voltage; the SOC calibration point is obtained based on the function curve, and the influence of temperature is combined to dynamically adjust the battery operation range and calibration range, which is conducive to the full utilization of the battery and improve the SOC calibration frequency; the unscented Kalman filter method is used to estimate the SOC in units of modules, and the SOC of the battery is calculated accordingly, so that the battery SOC estimation is more accurate and the influence of conditions such as reaction temperature can be reflected, and the SOC estimation value can be corrected in real time in combination with battery parameters, thereby improving the estimation accuracy and the available capacity of the battery, and can be applicable to nonlinear systems.

[0194] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's specification and drawings, or directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for estimating and calibrating battery SOC, wherein the battery comprises a plurality of identical battery modules, characterized in that: Includes steps: S1. constructing a function curve of the corresponding relationship between the open circuit voltage and the state of charge SOC of the battery module at each temperature; S2. Calculating the SOC lower limit and the SOC upper limit of each battery module at the corresponding operating temperature based on the function curve; S3, estimating the SOC value of each battery module by using an unscented Kalman filter algorithm, and calculating the SOC value of the battery; S4, controlling the battery and each of the battery modules to operate between the corresponding SOC lower limit and SOC upper limit, and if the battery module reaches a preset calibration condition, calibrating the SOC of the battery module.

2. A method for estimating and calibrating battery SOC according to claim 1, characterized in that: Step S1 includes the steps of: S11, taking a first preset number of temperature points, and taking a second preset number of state of charge SOC points at each temperature point, and performing discharge and charge tests on the battery module at the same rest time, respectively, to obtain the discharge and charge open circuit voltages corresponding to each SOC point of the battery module at different temperature points, wherein the discharge open circuit voltage is: V OCV =[V OCV_T1 ,...,V OCV_Tk ] T ; in: V ocv_Ti =[V Ti_SOC1 ,V Ti_SOC2 ,...,V Ti_SOCn ],i∈(1,k); V Ti_SOCn is the open circuit voltage at the nth SOC point at the ith temperature point under the discharge test condition; The charging open circuit voltage is: V′ OCV =[V′ OCV_T1 ,...,V′ OCV_Tk ] T ; in: V′ ocv_Ti =[V' Ti_SOC1 ,V′ Ti_SOC2 ,...,V′ Ti_SOCn ,]; V′ Ti_SOCn is the open circuit voltage at the nth SOC point at the ith temperature point under the charging test condition; S12, calculating a three-dimensional data set of the static open circuit voltage of the battery module at the first preset number of temperature points, wherein the calculation formula of the static open circuit voltage is: U OCV =(V OCV +V' OCV ) / 2; S13, performing high-order polynomial fitting on the three-dimensional data set of the static open-circuit voltage to obtain a fitting function U at the first preset number of temperature points OCV_Ti =f Ti (SOC).

3. The method for estimating and calibrating battery SOC according to claim 1, characterized in that: Step S2 comprises the steps of: S21, obtaining the operating temperature of any battery module in the battery, performing temperature interpolation between the two function curves that are closest to the operating temperature in the function curve, and obtaining the open circuit voltage U of any module at the operating temperature. OCV data; S22, selecting a step length ΔSOC based on the SOC calculation resolution to form a point set SOC_x, and calculating the open circuit voltage U at each discrete point of the point set SOC_x OCV The value of constitutes the point set U OCV _x; S23, calculating the point set U according to the point set SOC_x OCV The difference between any two adjacent values ​​in _x, where the difference between any two adjacent values ​​is calculated as: E(j)=U OCV_x (j)-U OCV_x (j-1),j∈(1,p); Where p is the number of discrete points in SOC_x obtained by evenly dividing the SOC value range [0,100] according to the step size ΔSOC; When the difference satisfies a preset condition, the SOC lower limit and the SOC upper limit of the battery module are obtained, and the corresponding open circuit voltage lower limit reference value and the open circuit voltage upper limit reference value are obtained; S24, repeating steps S21 to S23 until the SOC operating lower limit, the SOC operating upper limit, the open circuit voltage lower limit reference value, and the open circuit voltage upper limit reference value of all battery modules at the corresponding operating temperature are obtained.

4. A method for estimating and calibrating battery SOC according to claim 3, characterized in that: In step S23, when the difference meets the preset condition, the SOC operation lower limit and the SOC operation upper limit of the battery module are obtained, and the corresponding open circuit voltage lower limit reference value and the open circuit voltage upper limit reference value are obtained, specifically: When E(j) < ε and E(j) < E(j - 1), the point SOC_x(j) in the point set SOC_x is the lower limit of the SOC operation of the battery module, corresponding to U in the point set U OCV _x OCV _x(j) is the reference value of the lower limit of the open - circuit voltage of the battery module; When E(j)>ε and E(j)>E(j-1), the point SOC_x(j) in the point set SOC_x is the upper limit of the SOC operation of the battery module, corresponding to the point set U OCV U in _x OCV _x(j) is the upper limit reference value of the open circuit voltage of the battery module.

5. The method for estimating and calibrating battery SOC according to claim 3, characterized in that: Step S4 comprises the steps of: S41, obtaining the SOC operation lower limit and the SOC operation upper limit of all battery modules in the battery and constructing a data set, taking the highest value of the SOC operation lower limit in the data set as the SOC operation lower limit of the battery, and taking the lowest value of the SOC operation upper limit in the data set as the SOC operation lower limit of the battery; S42, controlling the battery to operate within the SOC lower limit and the SOC upper limit of the battery, and controlling the SOC of each battery module in the battery to operate within the SOC lower limit and the SOC upper limit of each battery module; S43, calculating the equivalent open circuit voltage of the battery module, and if the current equivalent open circuit voltage is equal to the lower limit reference value of the open circuit voltage of the battery module, calibrating the SOC of the battery module to the SOC operation lower limit of the battery module; If the current equivalent open circuit voltage is equal to the open circuit voltage upper limit reference value of the battery module, calibrating the SOC of the battery module to the SOC operating upper limit of the battery module; The calculation formula of the equivalent open circuit voltage is: W OCV_h =e h -I h R0; Among them, W OCV_h is the equivalent open circuit voltage, e h is the voltage of the hth module, I h is the current of the hth module (charging direction is positive, discharging direction is negative), R0 is the module ohmic internal resistance, h∈(1,s), s is the number of battery modules in the battery.

6. A method for estimating and calibrating battery SOC according to claim 1, characterized in that: Step S3 includes the steps of: S31, establish an equivalent circuit of the battery module, and measure the parameters R of the battery module offline. 0_(T,SOC) , R 1_(T,SOC) , C 1_(T,SOC) , construct the discretized state equation of the battery module; The battery module discretization state equation is: Where U is the equivalent capacitance C 1_(T,SOC) The voltage across the two terminals. The subscripts (T, SOC) in the parameters indicate that their values ​​are related to the module temperature T and SOC. Qm is the module capacity, SOC t , U t and SOC t+1 , U t+1 They are the module SOC state and equivalent capacitor voltage state at time t and time t+1, respectively. t is the module current at time t, T s is the calculation step size, W is the process noise; S32, constructing a measurement equation of the battery module according to the measurable state quantity of the battery module, the measurement equation being: e t+1 =U OCV_T_t+1 -U t+1 -I t+1 R 0_(T,SOC) +V; Among them, e t+1 It represents the module output voltage at time t+1, U OCV_T_t+1 is the open circuit voltage at time t+1, I t+1 is the module current at time t+1, V is the measurement noise, U t+1 is the equivalent capacitor voltage state at time t+1, R0 is the module ohmic internal resistance; S33, estimating the state of charge SOC of the battery module at time t+1 by using an unscented Kalman filter algorithm UKF; S34, summarizing the state of charge (SOC) of all battery modules in the battery at time t+1, obtaining the minimum and maximum values ​​of the state of charge (SOC) of all battery modules at time t+1, and calculating the SOC of the battery at time t+1, specifically as follows: Among them, SOC b is the battery's state of charge SOC, SOC m_min is the minimum SOC value of the module in the battery. m_max It is the maximum SOC value of the module in the battery.

7. The method for estimating and calibrating battery SOC according to claim 1, characterized in that: Step S4 and subsequent steps include: S5, monitoring the SOC difference between the battery modules of the battery, obtaining the maximum value of the SOC difference, and when the maximum value is greater than a preset threshold, executing step S51 for the two groups of battery modules corresponding to the maximum value until the maximum value is no greater than the preset threshold; S51, controlling the battery module with the largest SOC to discharge to the battery module with the smallest SOC at a constant power until the SOC of the discharged battery module is less than the average SOC of all battery modules or the SOC of the charged battery module is greater than the average SOC of all battery modules.

8. The method for estimating and calibrating battery SOC according to claim 1, characterized in that: The battery is also connected to a converter, and the step S4 further includes the following steps: The converter controls the operating power of the battery to be: Among them, SOC b is the battery SOC, SOC b_limit_low is the battery SOC operating lower limit, SOC b_limit_up is the upper limit of battery SOC operation, P d is the maximum discharge power of the battery, always a positive number, P c It is the maximum charging power of the battery, which is always a negative number.

9. A battery SOC estimation and calibration terminal, comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps in the method for estimating and calibrating battery SOC described in any one of claims 1 to 8 are implemented.

10. A multi-battery energy storage system, characterized in that: It includes a plurality of identical batteries, a plurality of bidirectional DC / DC converters, a plurality of bidirectional AC / DC converters, a plurality of energy storage control units, a DC bus and an AC bus; Each battery is connected to the DC bus or the AC bus through the bidirectional DC / DC converter or the bidirectional AC / DC converter; Each battery includes a battery controller and a plurality of battery modules, the battery controller communicates with the energy storage control unit, and the energy storage control unit communicates with the bidirectional DC / DC converter or the bidirectional AC / DC converter; The multi-battery energy storage system implements the steps in a battery SOC estimation and calibration method as described in any one of claims 1-8 above.

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