A battery state of function (SOF) calculation method, a battery management system, and a power utilization device

Abstract

The application discloses a battery SOF calculation method, a battery management system and a power utilization device. The battery SOF calculation method comprises the following steps: arbitrating and calculating the first limit power of a single battery cell and / or the second limit power of the single battery cell with an offline power MAP to obtain the third limit power of the single battery cell, and calculating the limit power of a battery system based on the third limit power. Alternatively, the method comprises the following steps: obtaining the terminal voltage of the single battery cell and the internal parameter of the battery system, calculating the limit power of the single battery cell based on the change value of the terminal voltage of the single battery cell and the internal parameter of the single battery cell obtained based on the internal parameter of the battery system, and calculating the limit power of the battery system according to the calculated limit power of the single battery cell. The application improves the SOF calculation method and optimizes the battery management system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of new energy electric vehicles, in particular to a battery SOF calculation method, a battery management system and a power utilization device. BACKGROUND

[0002] The battery SOF (State of Function) is based on the current state of the battery, and predicts the maximum power capability of the battery during charging and discharging within a period of time without exceeding the given battery limit conditions, including the limit voltage, the limit SOC, the limit power and the limit current. The battery SOF provides power information for the vehicle to meet the acceleration and climbing requirements of the vehicle, and regenerative braking, and feeds back the above information to the vehicle controller, so the battery SOF is an important parameter for the state estimation of the battery management system. As the core module of the battery state estimation, the SOF estimation accuracy is not high, which will have two adverse effects on the electric vehicle: if the SOF estimation is too high, the battery is easy to overcharge or overdischarge, which affects the battery life; if the SOF estimation is too low, the power performance of the vehicle will be affected, and the set power target of the vehicle cannot be reached.

[0003] The current mainstream SOF estimation method for new energy electric vehicles is a lookup table method, that is, a large number of test data are obtained through tests, the temperature and the current SOC state are considered, and the two-dimensional power current table is looked up to obtain the maximum charging and discharging capability of the current battery. This method relies too much on test data, and if the data are insufficient, the accuracy of the SOF will be affected, and at the same time, this SOF estimation method cannot meet the comprehensive requirements of battery protection, safety, fault and power-on / off mode.

[0004] The prior art provides a battery SOF estimation method based on a model, and the limit maximum charging and discharging power obtained by the method is not constant, and the non-constant power will have fluctuation phenomena of excessive power or insufficient power in the specific use of the vehicle; in addition, in the actual use process of the vehicle, due to the extremely complex working conditions, the online parameter identification may also have the problem of unstable identified parameters, and if the ECM is simply used to estimate the battery SOF, the result obtained is often divergent and lacks necessary prevention measures.

[0005] The prior art also provides a second-order equivalent circuit model, and the model parameter theta value of the battery is estimated by using the recursive least square method. Although the model accuracy is improved, the constant power estimation of the battery within a period of time cannot be realized. In addition, the second-order equivalent circuit model has five parameters to be identified, and in the process of parameter fitting, the overfitting problem is easy to occur, which makes the stability of the entire SOF estimation module worse, and increases the demand for BMS computing power. SUMMARY

[0006] The purpose of this application is to provide a battery SOF calculation method, a battery management system, and an electrical device. The SOF calculation method of this application optimizes the SOF battery management system.

[0007] This application provides a battery SOF calculation method, comprising: arbitrarily calculating the first limiting power of a single cell and / or the second limiting power of a single cell with an offline power MAP to obtain a third limiting power of the single cell; and calculating the limiting power of the battery system based on the third limiting power, wherein the first limiting power is the limiting power of a single cell within one sampling period, and the second limiting power is the second limiting power of a single cell over a period of time, wherein the period of time includes at least one sampling period.

[0008] This application performs arbitration calculations by calculating the first limit power of a single cell within a sampling period and / or the second limit power of a single cell over a period of time, and then arbitrarily calculating the offline power MAP. This offline constraint on the power of the battery system increases the safety of the battery system.

[0009] In some embodiments, the first limiting power of a single cell is arbitrated with the offline power MAP, and the minimum absolute power value of the two is taken to obtain the third limiting power of the single cell.

[0010] In some embodiments, the second limiting power of a single cell is arbitrated with the offline power MAP, and the minimum absolute power value of the two is taken to obtain the third limiting power of the single cell.

[0011] In some embodiments, the first limiting power of a single cell within a sampling period, the second limiting power of a single cell over a period of time, and the offline power MAP are arbitrated and calculated. The third limiting power of the single cell is obtained by taking the minimum absolute value of the three power values.

[0012] In some embodiments, a battery SOF calculation method includes: obtaining the terminal voltage of a single cell and internal parameters of the battery system; calculating the limit power of a single cell based on the change value of the terminal voltage of the single cell and the internal parameters of the single cell obtained based on the internal parameters of the battery system; and calculating the limit power of the battery system based on the calculated limit power of the single cell.

[0013] This application considers the consistency and variability of individual battery cells. By testing the internal parameters of the battery system, it calculates the average parameters of individual cells and calculates the maximum power of an individual cell by measuring the change in terminal voltage under different conditions. The maximum power of each individual cell in the battery system is then calculated by taking the smallest absolute value of its maximum power. Based on the minimum maximum power of an individual cell and the number of individual cells in the battery system, the SOF of the battery system is obtained. This SOF calculation method reduces the computational power required for chip processing.

[0014] In some embodiments, the internal parameters of the battery system are obtained based on a dual Kalman filter, and the equivalent resistance Z0 is calculated.

[0015] In some embodiments, a battery SOF calculation method includes:

[0016] Obtain the terminal voltage of a single battery cell and calculate the change in terminal voltage of a single battery cell under different states;

[0017] Internal parameters of the battery system are obtained based on a dual Kalman filter.

[0018] Based on the change in the terminal voltage of a single battery cell and the obtained internal parameters of the battery system, the maximum power of a single battery cell is calculated.

[0019] The first limiting power of the obtained single cell and / or the second limiting power of the single cell are arbitrated with the offline power MAP to obtain the third limiting power of the single cell.

[0020] The ultimate power of the battery system is calculated based on the third ultimate power of a single cell.

[0021] In some embodiments, the first limiting power includes a first limiting discharge power and a first limiting charge power, calculated as follows:

[0022] Set the sampling period to Δt, within one sampling period:

[0023] The first limiting discharge current of the single battery cell is:

[0024]

[0025] The first limiting charging current of the single battery cell is:

[0026]

[0027] The first limiting discharge power is:

[0028] P max，k+1 =U min *I max，k+1

[0029] Among them, P max，k+1 This represents the first limiting discharge power of a single battery cell at time k+1;

[0030] The first maximum charging power is:

[0031] P min，k+1 =U max *I min，k+1

[0032] Among them, I max，k+1 I represents the first limiting discharge current of a single cell at time K+1; min，k+1 P represents the first limiting charging current of a single cell at time K+1. max，k+1 P represents the first limiting discharge power of a single cell at time k+1. min，k+1 U represents the first limit charging power of a single battery cell at time k+1. OC (S k U represents the open-circuit voltage of a single cell at time k. Th It is the first-order RC loop voltage, τ is the time constant of a single cell, and U min U represents the lower cutoff voltage of a single battery cell. max This represents the upper limit cutoff voltage of a single battery cell, S represents the Laplace operator, R0 represents the internal resistance of a single battery cell, and R... Th This indicates the first-order RC loop resistance, and Cap indicates the battery's rated capacity.

[0033] In some embodiments, the second limiting power includes a second limiting discharge power and a second limiting charge power, calculated as follows:

[0034] The number of samples is m, the sampling period is Δt, and within the time interval mΔt:

[0035] The second limiting discharge current is:

[0036]

[0037] The second limiting charging current is:

[0038]

[0039] The second limiting discharge power is:

[0040]

[0041] The second maximum charging power is:

[0042]

[0043] Among them, I max， k+1 I represents the second limiting discharge current of a single cell in the time interval k+m; min，k+1 P represents the second limiting charging current of a single cell during the time period k+m. max，k+1 P represents the second limiting discharge power of a single battery cell during the time period k+m. min，k+1 U represents the second-limit charging power of a single battery cell during the k+m time period. OC (S k U represents the open-circuit voltage of a single cell at time k. Th It is the first-order RC loop voltage, τ is the time constant of a single cell, and U min U represents the lower cutoff voltage of a single battery cell. max This represents the upper limit cutoff voltage of a single battery cell, S represents the Laplace operator, R0 represents the internal resistance of a single battery cell, and R... Th This indicates the first-order RC loop resistance, and Cap indicates the battery's rated capacity.

[0044] In some embodiments, the second limiting power is modified:

[0045] P max，cal，mΔt =Z mΔt *[U OC (S k )-U min ]*I max，mΔt +U min *I max，mΔt

[0046] P min，cal，mΔt =Z mΔt *[U OC (S k )-U max ]*I min，mΔt +U max *I min，mΔt

[0047] Among them, P max，cal，mΔt P represents the second limiting discharge power after correction by the correction factor during the time interval mΔt. min，cal，mΔt I represents the second limiting charging power after correction by the correction factor during the time interval mΔt. max，mΔt I represents the limiting discharge current of a single cell during the time interval mΔt. min，mΔt U represents the maximum charging current of a single cell during the time interval mΔt. min U represents the lower cutoff voltage of a single battery cell. max Z represents the upper limit cutoff voltage of a single battery cell. mΔ This represents the correction factor.

[0048] In some embodiments, the correction factor Z mΔt Calculated using the following method: Where m represents the number of samples and Δt represents the sampling period.

[0049] In some embodiments, the offline power MAP is obtained by the following method: finding a constant power value applicable to the time period mΔt using the trial power method, and setting at least two discharge times on each side of mΔt, calculating the power at each discharge time, fitting the power curve corresponding to each time, and obtaining the constant discharge power of a single cell at time mΔt.

[0050] In some embodiments, the ultimate charge / discharge power of the battery system is calculated by the following method: the battery system comprises N individual cells; the third ultimate charge / discharge power of the N individual cells in the battery system is calculated; the third ultimate charge / discharge power with the smallest absolute value of power is taken and denoted as the third ultimate charge / discharge power P of the individual cell. min，cell_N and the third limiting discharge power P of a single cell max，cell_N The maximum charge and discharge power of the battery system is expressed as:

[0051]

[0052]

[0053] Among them, P sys，min P represents the maximum charging power of the battery system. sys，max This indicates the maximum discharge power of the battery system.

[0054] In some embodiments, the average parameters of the battery system are:

[0055] θ avg =(R 0，avg R th，avg C th，avg )

[0056] Where, θ avg R is the average parameter of the battery system. 0，avg R is the average internal resistance of the battery system. th，avg C is the average polarization resistance of the battery system. th，avg This represents the average polarization capacitance of the battery system.

[0057] This application further provides a battery management system, including a memory and a processor, wherein the memory stores a computer program that can run on the processor, and the processor executes the computer program to implement the above-described calculation method.

[0058] This application further provides an electrical device, including the battery management system described above.

[0059] The beneficial effects of this application are as follows: This application provides a battery SOF calculation method, a battery management system, and a power consumption device. The calculated maximum power of a single cell is not used directly; instead, it is arbitrated with the offline power MAP and the smaller value is taken. This arbitration establishes a correspondence between the battery SOF estimate and the battery aging state, avoiding the adverse effects caused by an excessively high or low calculated maximum power. This application considers the differences between individual cells, obtaining the maximum power of a single cell through the parameters of the battery system and the individual cell. The maximum power of the battery system is further calculated by using the maximum power obtained by comparing the absolute value of the maximum power with the minimum value. This method requires relatively low computing power, and the SOF state estimation of the battery system can be completed using conventional hardware chips. Attached Figure Description

[0060] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0061] Figure 1 The calculation process for SOF in this application is as follows;

[0062] Figure 2 This is the SOC-OCV mapping curve in this application;

[0063] Figure 3 This is the pilot-scale power method process for this application. Detailed Implementation

[0064] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application. In addition, in the description of this application, the term "comprising" means "including but not limited to". The terms first, second, third, etc. are used only as illustrative purposes and do not impose numerical requirements or establish an order.

[0065] Battery SOF, also known as SOP, requires the maximum power to remain constant within a certain time period to facilitate monitoring and control by the motor and electronic control system. However, this conflicts with the traditional battery evaluation method that uses constant current. There is a significant difference between calculating battery SOF using constant power and constant current. Furthermore, although battery SOF can be estimated using equivalent circuit models, the model error will be large under extreme low-temperature conditions, resulting in low accuracy of battery SOF. At higher temperatures, although the power value calculated by the model is large, power charging and discharging can easily lead to excessive battery temperature rise, causing safety hazards. To address these issues, embodiments of this application provide a battery SOF calculation method. This method arbitrates the first and / or second limiting power of a single cell with an offline power MAP to obtain the third limiting power of the single cell. Based on the third limiting power, the limiting power of the battery system is calculated. The first limiting power is the limiting power of the single cell within one sampling period, and the second limiting power is the second limiting power of the single cell over a period of time, which includes at least one sampling period.

[0066] This application establishes a correspondence between battery SOF estimation and battery aging state by calculating the first limiting power (instantaneous limiting power) of a single cell within a sampling period and / or the second limiting power (stage limiting power) of a single cell within a certain period (including m sampling periods) and arbitrarily calculating the offline power MAP. By constraining the battery power offline, it avoids the adverse effects caused by the calculated power being too large or too small.

[0067] In different systems, one can choose to arbitrate the first limiting power with the offline power MAP, or the second limiting power with the offline power MAP, or the first and second limiting powers respectively with the offline power MAP to obtain the minimum absolute value of the limiting power (the third limiting power), which is taken as the limiting power of a single cell. The limiting power of the battery system is then calculated based on the obtained third limiting power.

[0068] In some embodiments, such as Figure 1 As shown, the SOF method of this application includes the following steps:

[0069] Obtain the internal parameters of the battery system and calculate the internal parameters of individual cells in the battery system;

[0070] Obtain the terminal voltage U of a single battery cell under different conditions L The change value;

[0071] Based on the terminal voltage U of a single battery cell L Based on the variation values ​​and internal parameters of each individual cell, the maximum power of a single cell is calculated.

[0072] The maximum power of the obtained single cell (first maximum power and / or second maximum power) is arbitrated with the offline power MAP, and the maximum power with the smallest absolute value is taken (third maximum power). Based on the number of cells in the battery system, the final maximum power of the battery system is obtained.

[0073] In some embodiments, the internal parameters of a single cell are the average of the internal parameters of the battery system, that is, the average of the internal parameters of the battery system and the number of single cells in the battery system.

[0074] In one implementation, the terminal voltage U of a single battery cell is obtained in real time via the AFE sampling chip of the BMS. L Due to the inconsistencies in individual battery cells, the terminal voltage U of each individual battery cell varies. L They are different.

[0075] In one implementation, the equivalent resistance Z0 is calculated by obtaining the internal parameters of the battery system based on a dual Kalman filter, specifically including the following steps:

[0076] The dual Kalman filter estimates the basic state of the battery through a one-step estimation and one-step correction approach, alternating between battery SOC and battery characteristic parameters. Initialization is performed using offline test data, followed by dual Kalman filter calculations to estimate the battery SOC and battery model parameters online, obtaining the internal parameters of the battery system and establishing the state equations describing the battery's equivalent circuit model.

[0077] x k =f(x) k-1 u k θ k )+w k-1

[0078] y k =g(x k u k θ k )+v k-1

[0079] Construct the parametric state-space equations:

[0080] θ k+1 =θ k +r k ;y k =g(x k u k )+e k

[0081] Where x represents the battery state vector, T represents the transpose, x k Let θ represent the state vector at time k, and let θ represent the battery parameter vector. k Let w represent the parameter vector at time k.k-1 V represents the model error. k-1 f(x) represents the observation error. k-1 u k θ k ) represents the state-space equation, which is a nonlinear function, g(x) k u k θ k The equation θ represents the observation equation. θ = (R0, R1, C1, R2, C2), where R0 represents the ohmic internal resistance of a single cell, R1 represents the polarization resistance of the first RC circuit, C1 represents the polarization capacitance, R2 represents the polarization resistance of the second RC circuit, C2 represents the polarization capacitance, and r... k For modeling error, e k This represents the measurement error; the two models share the observation equation y. k =g(x k u k ).

[0082] Based on the estimation process of the dual Kalman filter (DEKF), the battery SOC and θ can be accurately obtained. To simplify the derivation process, the subsequent related formulas all use the parameters of the first-order equivalent circuit model, and the second-order parameters can be obtained in the same way.

[0083] The recursive calculation process for the equivalent resistance Z0 is as follows:

[0084] Kirchhoff's Laws: U L，k+1 =U OC (SOC k+1 )-U Th，k+1 -I L，k+1 R0

[0085] From the zero-input zero-state response, we get:

[0086] Substitute,

[0087]

[0088] Hourly Integrals:

[0089]

[0090] Ignore the higher-order terms in the latter equation and substitute them in:

[0091] Equivalent resistance definition: Z 0，k+1 =[U OC (S k )-U L，k+1 ] / I L，k+1

[0092]

[0093] Among them, I L It is the loop current value, which can be measured; U Th U represents the first-order RC loop voltage, which can be calculated from the OCV voltage, terminal voltage, and ohmic voltage drop. L，k+1 I represents the terminal voltage of a single cell at time k+1. L，k+1 Z represents the measured current of a single cell at time k+1, R0 represents the ohmic internal resistance of a single cell, and Z... 0，k+1 U represents the equivalent resistance of a single cell at time k+1. Th，k+1 R represents the first-order RC loop voltage at time k+1. Th U represents the resistance of a first-order RC loop. OC (SOC k+1 U represents the open-circuit voltage of a single cell at time SOC k+1. OC (S k U represents the open-circuit voltage of a single cell at time k. Th，k Let k represent the first-order RC loop voltage at time k, Cap represent the rated capacity of the battery, τ represent the time constant of a single cell, τ = RC, R represent the polarization resistance of a single cell, and C represent the polarization capacitance of a single cell.

[0094] In one implementation, the current open-circuit voltage U of a single battery cell is obtained in the following manner. oc :like Figure 2 As shown, based on the mapping relationship between battery SOC and OCV embedded in the battery SOC algorithm module, the current open-circuit voltage U of a single cell is obtained according to this correspondence. oc .

[0095] Online acquisition of battery model parameters, whether using dual Kalman filtering or recursive least squares fitting algorithms, involves computational load and hardware chip power. Assuming a battery system consists of 100 individual cells connected in series, the algorithm needs to identify model parameters 100 times per sampling period, which is beyond the capabilities of conventional BMS chips. This application considers the entire battery system as equivalent to a large battery, with the internal parameters being the average of the battery system parameters.

[0096] θ avg =(R 0，avg， R th，avg C th，avg )

[0097] Where, θ avg R is the average parameter of the battery system. 0，avg R is the average internal resistance of the battery system. th，avg C is the average polarization resistance of the battery system. th，avg This represents the average polarization capacitance of the battery system.

[0098] This application analyzes the impact of the consistency differences of individual cells on the ultimate charge and discharge power of the battery system by identifying the model parameters of all individual cells in the entire battery system.

[0099] Assuming the battery system consists of two cells connected in series (cell 1 and cell 2), under extremely short-term current excitation (the current value can be considered approximately constant), the voltage change at the output terminal of each cell can be directly measured. This is based on the U... L By examining the differences and the internal parameters of the entire battery system, we can derive the internal parameters of each individual cell. The changes in individual cell values ​​are denoted as Δu1 and Δu2, respectively. Since transient voltage changes are mainly affected by the battery's ohmic internal resistance, we can obtain R. 0，1 / R 0，2 =Δu1 / Δu2, given the average internal resistance R of the battery system. 0，avg Through Δu1, Δu2 and R 0，avg With three parameters, the ohmic internal resistance R of each of the two individual battery cells can be calculated. 0，1 R 0，2 .

[0100]

[0101]

[0102] Among them, R 0，1 R represents the ohmic internal resistance of the first individual cell, Δu1 represents the voltage change at the output terminal of the first individual cell, Δu2 represents the voltage change at the output terminal of the second individual cell, and R represents the voltage change at the output terminal of the second individual cell. 0，avg R represents the average internal resistance of the battery. 0，2 This indicates the ohmic internal resistance of the second individual cell.

[0103] Let U th1 U th2 The polarization voltage of the battery, according to Kirchhoff's laws:

[0104] U th，k+1 =U OC (S k+1 )-U L，k+1 -I L，k+1 R0

[0105] Among them, U th，k+1 U represents the first-order RC loop voltage at time K+1. OC (S k+1 U represents the open-circuit voltage of a single cell at time SOC k+1. L，k+1 I represents the terminal voltage of a single cell at time k+1. L，k+1Let R0 represent the measured current of a single cell at time k+1, and R0 represent the internal resistance of the single cell. In the zero-input and zero-state response of the RC circuit, the polarization voltage between two adjacent discrete points can be expressed as (the latter equation approximates zero over a very short time):

[0106]

[0107]

[0108]

[0109]

[0110] Among them, U Th Represents the first-order RC loop voltage, R Th U represents the resistance of a first-order RC loop. thn U represents the average polarization voltage of the battery system, τn represents the average time constant of the battery system, τ = RC, U Th1，k+1 U represents the RC loop voltage of the first single cell at time k+1. Th2，k+1 U represents the RC loop voltage of the second individual cell at time k+1. Thn，k+1 U represents the RC loop voltage of the entire battery system at time k+1. Th1，k U represents the RC loop voltage of the first single cell at time k. Th2，k U represents the RC loop voltage of the second individual cell at time k. Th Let represent the first-order RC loop voltage, and n represent the number of individual cells in the battery system. It can be seen that the time constants τ1 of the first individual cell and τ2 of the second individual cell have a functional relationship with the polarization voltages of two adjacent discrete points.

[0111]

[0112]

[0113]

[0114] Given system τ n By using the proportional relationships between equations (1) and (3), and between equations (2) and (3), τ1 and τ2 can be calculated.

[0115]

[0116]

[0117] Based on the zero-input and zero-state response, the polarization resistance can be expressed as:

[0118]

[0119]

[0120]

[0121] Given system R thn By using the proportional relationships between equations (4) and (6), and between equations (5) and (6), R can be calculated. th1 and R th2 Then, based on τ1, τ2, and R... th1 R th2 Find C th1 C th2 .

[0122]

[0123]

[0124]

[0125]

[0126]

[0127] Among them, R thn C represents the polarization resistance of the system. Th1 C represents the polarization capacitance of the first individual battery cell. Th2 R represents the polarization capacitance of the second individual cell. Th1 R represents the polarization resistance of the first individual cell. Th2 This indicates the polarization resistance of the second individual cell.

[0128] Calculate the maximum charge and discharge power of N individual cells in a battery system, and take the minimum absolute value of the power, denoted as P. min，cell_N P max，cell_N The maximum charge and discharge power of the battery system is expressed as:

[0129]

[0130] The system's maximum charging power is expressed as:

[0131]

[0132] Among them, P sys，min P represents the system's maximum charging power. sys，max The value of i represents the system's maximum discharge power, and the range of i is 1 to N, where N represents the number of individual cells in the battery system.

[0133] In one implementation, the first limiting power of a single cell within a sampling period is calculated using the following method:

[0134] The sampling period for the battery SOF is set to Δt. Within a single period, the charging and discharging power and current can be approximated as constant. Taking discharging as an example, when a single cell uses its maximum discharge power, the battery output voltage is the lower limit cutoff voltage U of the single cell. min .

[0135] The first limiting discharge current of a single battery cell is as follows:

[0136]

[0137] The first limiting discharge power is:

[0138] P max，k+1 =U min *I max，k+1

[0139] Similarly, the first limiting charging current for a single battery cell is as follows:

[0140]

[0141] The first maximum charging power of a single battery cell is:

[0142] P min，k+1 =U max *I min，k+1

[0143] Among them, P min，k+1 I represents the first limiting charging power of a single battery cell at time k+1. max，k+1 I represents the first limiting discharge current of a single cell at time K+1; min，k+1 P represents the first limiting charging current of a single cell at time K+1. max，k+1 P represents the first limiting discharge power of a single cell at time k+1. min，k+1 U represents the first limit charging power of a single battery cell at time k+1. OC (S k U represents the open-circuit voltage of a single cell at time k. Th It is a first-order RC loop voltage, where τ is the time constant of a single cell, τ = RC, U min U represents the lower cutoff voltage of a single battery cell. max This represents the upper limit cutoff voltage of a single battery cell, S represents the Laplace operator, R0 represents the internal resistance of a single battery cell, and R... Th This represents the resistance of a first-order RC loop.

[0144] In one specific implementation, Δt can be set to 10ms.

[0145] In one implementation, the second limiting power of a single battery cell is calculated as follows:

[0146] As defined by the SOF (State of Charge) of a battery, predicting battery power requires time intervals, such as 2s power, 10s power, 30s power, etc. Let m be the number of samplings, and the time interval be mΔt. Assuming the current is constant within this interval, the expression for the second limiting discharge current of a single cell is as follows (using a recursive algorithm):

[0147]

[0148] The second limiting discharge power of a single battery cell is:

[0149]

[0150] Similarly, the expression for the second limiting charging current of a single battery cell is as follows:

[0151]

[0152] The second maximum charging power of a single battery cell is:

[0153]

[0154] Among them, I max，k+1 I represents the second limiting discharge current of a single cell in the time interval k+m; min，k+1 P represents the second limiting charging current of a single cell during the time period k+m. max，k+1 P represents the second limiting discharge power of a single battery cell during the time period k+m. min，k+1 U represents the second-limit charging power of a single battery cell during the k+m time period. OC (S k U represents the open-circuit voltage of a single cell at time k. Th It is the first-order RC loop voltage, τ is the time constant of a single cell, and U min U represents the lower cutoff voltage of a single battery cell. max This represents the upper limit cutoff voltage of a single battery cell, S represents the Laplace operator, R0 represents the internal resistance of a single battery cell, and R... Th This represents the resistance of a first-order RC loop.

[0155] However, this application requires the calculation of a constant power value, not a constant current value. Using the calculated limit constant current for discharge will cause the battery discharge power to continuously decrease as the battery terminal voltage drops, making it impossible to stabilize the overall vehicle output power. If the calculated limit constant power is used for discharge, this value will be significantly smaller, resulting in a waste of battery power performance.

[0156] To address the above issues, this application designs an estimation method that comprehensively considers the time period mΔt. Based on the range of values ​​for m and the battery time constant τ (τ=RC), a battery limit power correction factor Z is created.mΔ The maximum power capability of a battery under arbitrary charge-discharge recombination can be predicted by adding a correction factor to the equation.

[0157] P max，cal，mΔt =Z mΔt *[U OC (S k )-U min ]*I max，mΔt +U min *I max，mΔt

[0158] P min，cal，mΔt =Z mΔt *[U OC (S k )-U max ]*I min，mΔt +U max *I min，mΔt

[0159] Among them, P max，cal，mΔt P represents the second limiting discharge power after correction by the correction factor during the time interval mΔt. min，cal，mΔt I represents the second limiting charging power after correction by the correction factor during the time interval mΔt. max，mΔt I represents the limiting discharge current of a single cell during the time interval mΔt. min，mΔt U represents the maximum charging current of a single cell during the time interval mΔt. min U represents the lower cutoff voltage of a single battery cell. max Z represents the upper limit cutoff voltage of a single battery cell. mΔ This represents the correction factor.

[0160] Z mΔt Calculated using the following method: Where m represents the number of samples and Δt represents the sampling period.

[0161] One specific implementation provides a constant power calculation method for battery SOF estimation, addressing the power estimation problem. When m = 200 sampling periods and ΔT = 10ms, i.e., constant power for 2s... Then P max，cal，2s Expression: P max，cal，2s =Z 2s *[U OC (S k )-U min ]*I max，2s +U min *I max，2s

[0162] When m = 1000 sampling periods, i.e., 10s constant power, Then P max，cal，10s Expression: P max，cal，10s =Z 10s *[U OC (S k )-U min ]*I max，10s +U min *I max，10s

[0163] When m = 3000 sampling periods, i.e., constant power for 30 seconds, Then P max，cal，30s Expression: P max，cal，30s =Z 30s *[U OC (S k )-U min ]*I max，30s +U min *I max，30s

[0164] When calculating the SOF of a single cell over a period of time using the battery SOF calculation method in this application, the limiting current I is not used. max Instead of calculating the battery's maximum charge and discharge power, an estimation method with a correction factor based on the battery's current time constant is used. This ensures that the maximum power is approximately constant during this period, better meeting the needs of the entire vehicle.

[0165] In one implementation, the offline power MAP is calculated as follows:

[0166] To obtain the offline power map (MAP) of a single battery cell, specific current and power tests are required. This application employs a comprehensive current and power testing method. On one hand, it calculates the maximum power based on fundamental principles; on the other hand, it obtains a constant power value through iterative testing. The offline lookup table constraint method established in this application includes three dimensions: battery SOC, battery temperature, and battery state of health (SOH). The offline tables are built upon HPPC testing and constant power testing for evaluation, ultimately forming MAP power tables for various time periods, such as 2s power, 10s power, and continuous power. Generally, HPPC testing is performed from two dimensions: battery SOC and temperature, and tables are then created. HPPC is a common constant current pulse testing method, first appearing in the Freedom Car manual. The battery's DC internal resistance (DCR) at that SOC and temperature can be calculated from the voltage change and constant current value, such as R. DCR，50，25 Based on the DC internal resistance DCR, the limiting charging current I during this period can be calculated. min and limiting discharge current I max .

[0167] I min=(U OC -U max ) / R DCR

[0168] I max =(U OC -U min ) / R DCR

[0169] Among them, U OC U represents the open-circuit voltage of a single battery cell. min U represents the lower cutoff voltage of a single battery cell. max R represents the upper limit cutoff voltage of a single battery cell. DCR This represents the DC internal resistance (DCR) of a single battery cell.

[0170] This leads to the maximum charging power P. min and limiting discharge power P max :

[0171] P min =(U OC -U max ) / R DCR *U max

[0172] P max =(U OC -U min ) / R DCR *U min

[0173] The current is constant but the power is not. Therefore, a suitable constant power value needs to be found using a trial-and-error method, as follows: Figure 3 As shown: The constant power value applicable to the time period mΔt is found by the test power method, and at least two discharge times are set on both sides of mΔt. The power at each discharge time is calculated, and the power curve corresponding to each time time is fitted to obtain the constant discharge power of a single cell at time mΔt.

[0174] Taking the discharge power over 10 seconds as an example, let P1 = P max Discharge the battery at a constant power of P1 until the battery cutoff voltage at that temperature, with a discharge time of t1; let P2 = 0.9 * P max Similarly, under constant power discharge to the battery cutoff voltage at that temperature, the discharge time is t2; let P3 = 0.8 * P max P4 = 0.7 * P max P5 = 0.6 * P maxThe discharge times t3, t4, and t5 were obtained. The experiment required that at least two of the five time intervals fall on either side of the 10s power line. The constant 10s discharge power value of a single battery cell during the actual process can be evaluated by curve fitting results from the five sets of data, denoted as P. max，test，10s .

[0175] Ultimately, over a certain period, the ultimate charge / discharge power of a single battery cell needs to be determined by taking the smaller of the ECM model calculation results and the offline MAP test results, resulting in the third ultimate charge / discharge power of the single battery cell, P. min，cell and the ultimate discharge power P of a single cell max，cell Taking the corrected second limiting power and offline MAP test results as an example:

[0176] P min，cell =min{P min，cal P min，test}

[0177] P max，cell =min{P max，cal P max，test}

[0178] In one embodiment, the ultimate charge / discharge power of the battery system is obtained by the following method: This application considers the influence of the consistency and differences of individual cells on the ultimate charge / discharge power of the battery system. By selecting the factor with the greatest influence on the ultimate charge / discharge power of the battery system, the third ultimate charge / discharge power of N individual cells in the battery system is calculated, and the minimum absolute value of the power is taken as the third ultimate charge / discharge power P of the individual cell. min，cell_N and the third limiting discharge power P of a single cell max，cell_N Thus, the maximum charge and discharge power of the battery system can be calculated.

[0179] The parameters of the battery system in this application are calculated to obtain the parameters of the individual cells, and the maximum charge and discharge power of the individual cells in the battery system is calculated based on the voltage of the individual cells. This method requires less computing power and can complete the SOF state estimation of the battery system using conventional hardware chips.

[0180] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0181] The above provides a detailed description of a battery SOF calculation method, battery management system, and power consumption device provided in the embodiments of this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for calculating the SOF of a battery, characterized in that, include: Obtain the terminal voltage of individual battery cells and the internal parameters of the battery system. Based on the changes in the terminal voltage of individual battery cells and the internal parameters of individual battery cells obtained from the internal parameters of the battery system, calculate the limit power of individual battery cells. Based on the calculated limit power of individual battery cells, calculate the limit power of the battery system. Specifically, this includes: The first and second limiting powers of a single battery cell are respectively arbitrated with the offline power MAP of the single battery cell to obtain the third limiting power of the single battery cell. Based on the third limiting power, the limiting power of the battery system is calculated. The first limiting power is the limiting power of the single battery cell within one sampling period, and the second limiting power is the second limiting power of the single battery cell within a period of time, which includes multiple sampling periods. The second limiting power includes the second limiting discharge power and the second limiting charge power. The corrected second limiting discharge power and the second limiting charge power are obtained in the following way: Where m represents the number of samples. Indicates the sampling period. express The second limiting discharge power after correction factor during this period, express The second limit charging power after correction factor during this period, express The maximum discharge current of a single battery cell during this period. express The limiting charging current of a single cell during this period, where τ is the time constant of the single cell. This indicates the lower cutoff voltage of a single battery cell. This indicates the upper limit cutoff voltage of a single battery cell. This represents the open-circuit voltage of a single battery cell at time k. This represents the correction factor.

2. The battery SOF calculation method according to claim 1, characterized in that, The first limiting power includes the first limiting discharge power and the first limiting charge power, and is calculated in the following way: Within a sampling period: The first limiting discharge current of the single battery cell is: The first limiting charging current of the single battery cell is: The first limiting discharge power is: in, This represents the first limiting discharge power of a single battery cell at time k+1; The first maximum charging power is: in, This represents the first limiting discharge current of a single battery cell at time K+1; This represents the first limiting charging current of a single battery cell at time K+1. This represents the first limiting discharge power of a single battery cell at time k+1. This represents the first limit charging power of a single battery cell at time k+1. Open-circuit voltage of a single cell at time k It is the first-order RC loop voltage, where τ is the time constant of a single cell. This indicates the lower cutoff voltage of a single battery cell. This represents the upper limit cutoff voltage of a single battery cell, S represents the Laplace operator, and R0 represents the internal resistance of a single battery cell. This indicates the first-order RC loop resistance, and Cap indicates the battery's rated capacity.

3. The battery SOF calculation method according to claim 1, characterized in that, The second limiting discharge power and the second limiting charging power are calculated in the following manner: exist Within a certain time period: The second limiting discharge current of a single cell in the k+m time period is: The second limiting charging current for a single battery cell during the k+m time period is: The second limiting discharge power of a single cell in the k+m time period is: The second limiting charging power of a single battery cell in the k+m time period is: in, This represents the second limiting discharge current of a single battery cell during the time interval k+m; This represents the second limiting charging current of a single battery cell during the time period k+m. This represents the second limiting discharge power of a single battery cell during the time interval k+m. This represents the second limit charging power of a single battery cell during the k+m time period. This represents the open-circuit voltage of a single battery cell at time k. It is the first-order RC loop voltage, where τ is the time constant of a single cell. This indicates the lower cutoff voltage of a single battery cell. This represents the upper limit cutoff voltage of a single battery cell, S represents the Laplace operator, and R0 represents the internal resistance of a single battery cell. This indicates the first-order RC loop resistance, and Cap indicates the battery's rated capacity.

4. The battery SOF calculation method according to claim 1, characterized in that, The offline power MAP was obtained by the following method: finding it through the power trial method. The constant power value applicable to the time period, and At least two discharge times are set on each side. The power at each discharge time is calculated, and the power curve corresponding to each time time is fitted to obtain the power of a single cell. The constant discharge power at any given time.

5. The battery SOF calculation method according to claim 1, characterized in that, The ultimate charge / discharge power of the battery system is calculated using the following method: The battery system comprises N individual cells. The third ultimate charge / discharge power of the N individual cells in the battery system is calculated, and the third ultimate charge / discharge power with the smallest absolute value is taken as the third ultimate charge / discharge power of the individual cell. and the third limiting discharge power of a single battery cell The maximum charge and discharge power of the battery system is expressed as: in, Indicates the maximum charging power of the battery system. This indicates the maximum discharge power of the battery system.

6. The battery SOF calculation method according to claim 1, characterized in that, The average parameters of the battery system are: in, These are the average parameters of the battery system. The average internal resistance of the battery system. The average polarization resistance of the battery system. This represents the average polarization capacitance of the battery system.

7. A battery management system, characterized in that, The system includes a memory and a processor, wherein the memory stores a computer program that can run on the processor, and the processor executes the computer program to implement the calculation method according to any one of claims 1 to 6.

8. An electrical device, characterized in that, Includes the battery management system as described in claim 7.

Images