Lithium battery SOC estimation method based on high-precision ampere-hour integral algorithm

Abstract

The invention belongs to the field of lithium battery SOC calculation, and particularly relates to a lithium battery SOC estimation method based on a high-precision ampere-hour integral algorithm. The method comprises the following steps: establishing and solving an ampere-hour integral mathematical model, and performing Taylor expansion on the solution; and investigating two-point slopes of the interval, obtaining an average slope by means of linear combination of the three-point slopes, and ensuring that the three-order Taylor expansion and the equivalent formula have the same precision. When the algorithm is executed, the charge state and the capacity value are initialized, the sampling time is obtained according to the sampling frequency, then relevant parameters are calculated according to the current sampling value, and finally the current SOC is calculated according to the specific value and the three slopes and loop iteration is carried out. According to the method, the ampere-hour integration precision can be improved, and accumulated errors and SOC jump can be weakened.

Description

Technical Field

[0001] The present invention belongs to the field of lithium battery SOC calculation, and in particular relates to a lithium battery SOC estimation method based on a high-precision ampere-hour integration algorithm. Background Art

[0002] Lithium battery SOC is an important parameter to measure the remaining power of the battery. It indicates the percentage of the current power of the battery relative to its maximum power. Accurately estimating the SOC of lithium batteries is crucial for battery management systems, which can help optimize battery performance, extend battery life, and improve safety in use. The importance of SOC is mainly reflected in the following three points. First, battery management. Accurate SOC estimation can help prevent overcharging and over-discharging, extend battery life, and ensure that the battery operates within a safe range; second, energy management. In electric vehicles or energy storage systems, SOC information can help optimize energy distribution and improve system efficiency and reliability; finally, user experience. Accurate SOC display can help users understand the remaining battery power, reasonably arrange charging and use plans, and improve convenience. Lithium battery SOC estimation is a complex and important task involving multiple technologies and methods. By reasonably selecting and optimizing the estimation method, high-precision and high-reliability SOC estimation can be achieved, thereby improving the overall performance and user experience of the battery system.

[0003] The existing SOC algorithms mainly include the open circuit voltage method, the model estimation method and the ampere-hour integration method. The open circuit voltage method is mainly used in static situations, and its start-up conditions are very limited; the model in the model estimation method is highly complex, the model parameters are difficult to obtain, and the computing resources are high; the ampere-hour integration is easily affected by the cumulative error. Therefore, this patent proposes a method to improve the accuracy of the ampere-hour integration, thereby reducing the long-term cumulative error, and reducing the jump of SOC under the hybrid algorithm. Summary of the invention

[0004] In view of the technical problems existing in the background technology, the present invention proposes a method for estimating battery SOC with reasonable design, simple method, strong theoretical basis and capable of improving the accuracy of ampere-hour integration.

[0005] In order to achieve the above object, the technical solution adopted by the present invention comprises the following steps:

[0006] S1. First, establish the mathematical model of ampere-hour integration Where i is the current, soc is the state of charge, cap is the capacity of the battery, soc′ is the first-order derivative of soc, and the change of each variable over time is omitted, f is the first-order derivative of soc and the relationship between current i and soc, soc0 represents the initial state of the state of charge soc;

[0007] S2. Then the solution of the mathematical model of ampere-hour integration is soc = soc(i), and Taylor expansion is performed on this solution. where soc′(i n ), soc″(i n ), soc″′(i n ) are the first, second and third order derivatives of soc(i), Δ represents the unit time difference, i.e. Δ=t n+1 -t n ,i n It represents the current value measured at the nth moment. Under the consideration of ensuring accuracy and small amount of calculation, only the first four terms of Taylor's formula are taken;

[0008] S3, then examine the interval (i n ,i n+1 ) where i n+p ,i n+q are two points in the interval, the slope between the two points is K2, K3, K1 is x n The slope at which K1=f(i n ,soc n ). According to the improved Euler format, we can get K2 = f(i n +pΔ,soc n +pΔK1) and then K3=f(i n +qΔ,soc n +qΔ(rK1+sK2)), where r and s are parameters used to adjust the slope combination method;

[0009] S4, finally with the help of three points x n ,x n+p ,x n+q The linear combination of the slopes K1, K2, and K3 gives the average slope. At this point, the Taylor formula is equivalent to soc n+1 =soc n +Δ(λ1K1+λ2K2+λ3K3), where λ1, λ2, λ3 are linear coefficients. To ensure that the third-order Taylor expansion and the equivalent formula have the same accuracy, the following equation needs to be satisfied A special case where the solution satisfies the equation is

[0010] As a preferred embodiment, the detailed process of algorithm execution is as follows:

[0011] Step 1: First, initialize the value of the state of charge soc0, which is generally read from the non-volatile memory. According to the single cell capacity and grouping mode of the battery pack, calculate the theoretical capacity value, i.e., the cap value;

[0012] Step 2: Secondly, the sampling time Δ is obtained according to the sampling frequency of the current sensor by the battery management system BMS;

[0013] Step 3: Again, according to the current sampling value i0 at the current moment, the K1 value is calculated using the ampere-hour integral mathematical model and a special case that satisfies the equation. The K2 value can be calculated according to the Δ value, and the K3 value can be calculated according to the values ​​K1 and K2.

[0014] Step 4. Finally, the current soc1 value can be calculated based on the current soc0 value and the three slopes K1, K2, and K3. At this time, the current current value i1 is sampled again, and the three slopes K1, K2, and K3 are calculated first, and then soc2 can be calculated based on the known soc1 value. Repeat the cycle to calculate the current SOC of the lithium battery.

[0015] Compared with the prior art, the advantages and positive effects of the present invention are that a lithium battery SOC estimation method based on a high-precision ampere-hour integration algorithm is proposed, which can improve the accuracy of ampere-hour integration and reduce long-term cumulative errors. Under the hybrid algorithm, the jump of SOC can be reduced and the SOC of the lithium battery can be estimated more accurately. The slope of two points in the interval is estimated to reduce the error of SOC, and the error is smaller than the forward Euler algorithm that only considers the first two terms in the Taylor formula. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 It is the ampere-hour integral model;

[0018] Figure 2 It is a flow chart of high-precision algorithm model;

[0019] Figure 3 This is the error analysis diagram of the high-precision ampere-hour algorithm; DETAILED DESCRIPTION

[0020] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described below in conjunction with the accompanying drawings and embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0021] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways than those described herein. Therefore, the present invention is not limited to the specific embodiments of the following disclosure.

[0022] Embodiment, in the application of lithium batteries, it is very important to accurately estimate their SOC. Existing SOC algorithms such as open circuit voltage method, model estimation method and ampere-hour integration method all have certain limitations. The open circuit voltage method is mainly suitable for static occasions and has limited start-up conditions; the model estimation method has high model complexity, difficult parameter acquisition, and high requirements for computing resources; the ampere-hour integration method is easily affected by cumulative errors. In order to overcome these problems, the present invention proposes a lithium battery SOC estimation method based on a high-precision ampere-hour integration algorithm, which aims to improve the accuracy of ampere-hour integration, weaken long-term cumulative errors, and reduce SOC jumps under a hybrid algorithm, thereby more accurately estimating the SOC of the lithium battery and improving the performance and reliability of the battery management system.

[0023] First, the mathematical model of ampere-hour integration is established. Figure 1 Knowable Where i is the current, soc is the state of charge, cap is the capacity of the battery, soc′ is the first-order derivative of soc, and the change of each variable over time is omitted, f is the first-order derivative of soc and the relationship between current i and soc, soc0 represents the initial state of the state of charge soc;

[0024] Then the solution of the mathematical model of ampere-hour integration is soc = soc(i), and the Taylor expansion of this solution is performed. where soc′(i n ), soc″(i n ), soc″′(i n ) are the first, second and third order derivatives of soc(i), Δ represents the unit time difference, i.e. Δ=t n+1 -t n ,i n It represents the current value measured at the nth moment. Under the consideration of ensuring accuracy and small amount of calculation, only the first four terms of Taylor's formula are taken;

[0025] Next, we examine the interval (i n ,i n+1 ) where i n+p ,i n+q are two points in the interval, the slope between the two points is K2, K3, K1 is x n The slope at which K1=f(i n ,soc n ). According to the improved Euler format, we can get K2 = f(i n +pΔ,socn +pΔK1) and then K3=f(i n +qΔ,soc n +qΔ(rK1+sK2)), where r and s are parameters used to adjust the slope combination method;

[0026] Finally, with the help of three points x n ,x n+p ,x n+q The linear combination of the slopes K1, K2, and K3 gives the average slope. At this point, the Taylor formula is equivalent to soc n+1 =soc n +Δ(λ1K1+λ2K2+λ3K3), where λ1, λ2, λ3 are linear coefficients. To ensure that the third-order Taylor expansion and the equivalent formula have the same accuracy, the following equation needs to be satisfied A special case where the solution satisfies the equation is

[0027] The detailed process of algorithm execution is as follows Figure 2 As shown. First, initialize the value of the state of charge soc0. Generally, this value is read from the non-volatile memory. According to the single cell capacity and grouping mode of the battery pack, calculate the theoretical capacity value, that is, the cap value; secondly, obtain the sampling time Δ according to the sampling frequency of the current sensor of the battery management system BMS; thirdly, calculate the K1 value according to the current sampling value i0 at the current moment and use the ampere-hour integral mathematical model and a special case that satisfies the equation. The K2 value can be calculated according to the Δ value, and the value K3 can be calculated according to the values ​​K1 and K2; finally, the current soc1 value can be calculated according to the current soc0 value and the three slopes K1, K2, and K3. At this time, sample the current current value i1 again, and according to the three slopes K1, K2, and K3 calculated first, soc2 can be calculated based on the known soc1 value. Repeat the cycle to calculate the current SOC of the lithium battery.

[0028] When the algorithm ends, the soc is stored in non-volatile memory. When only the first two terms in the Taylor formula are considered, that is, only the first-order derivative, the calculation of SOC is forward Euler, and its error is as follows Figure 3 As shown in the figure, soc(i), soc1(t) and soc3(t) represent the real SOC curve, the Euler method SOC curve and the SOC curve of this algorithm respectively. Figure 3 It can be seen intuitively that the error of the algorithm is smaller than that of the Euler algorithm. p and i q The slope is estimated, thereby reducing the error of SOC. As the number of estimated intervals increases, the calculation accuracy will increase, but it will consume a lot of computing resources, and ultimately only two points in two sampling intervals are estimated.

[0029] The above description is only a preferred embodiment of the present invention and does not limit the present invention in other forms. Any technician familiar with the profession may use the technical content disclosed above to change or modify it into an equivalent embodiment with equivalent changes and apply it to other fields. However, any simple modification, equivalent change and modification made to the above embodiment based on the technical essence of the present invention without departing from the content of the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A lithium battery SOC estimation method based on a high-precision ampere-hour integration algorithm, characterized in that: The following steps are involved: S1. First, establish the mathematical model of ampere-hour integration Where i is the current, soc is the state of charge, cap is the capacity of the battery, soc′ is the first-order derivative of soc, and the change of each variable over time is omitted, f is the first-order derivative of soc and the relationship between current i and soc, soc0 represents the initial state of the state of charge soc; S2. Then the solution of the mathematical model of ampere-hour integration is soc = soc(i), and Taylor expansion is performed on this solution. where soc′(i n ), soc″(i n ), soc″′(i n ) are the first, second and third order derivatives of soc(i), Δ represents the unit time difference, i.e. Δ=t n+1 -t n ,i n It represents the current value measured at the nth moment. Under the consideration of ensuring accuracy and small amount of calculation, only the first four terms of Taylor's formula are taken; S3, then examine the interval (i n ,i n+1 ) where i n+p ,i n+q are two points in the interval, the slope between the two points is K2, K3, K1 is x n The slope at which K1=f(i n ,soc n ). According to the improved Euler format, we can get K2 = f(i n +pΔ,soc n +pΔK1) and then K3=f(i n +qΔ,soc n +qΔ(rK1+sK2)), where r and s are parameters used to adjust the slope combination method; S4, finally with the help of three points x n ,x n+p ,x n+q The linear combination of the slopes K1, K2, and K3 gives the average slope. At this point, the Taylor formula is equivalent to soc n+1 =soc n +Δ(λ1K1+λ2K2+λ3K3), where λ1, λ2, λ3 are linear coefficients. To ensure that the third-order Taylor expansion and the equivalent formula have the same accuracy, the following equation needs to be satisfied A special case where the solution satisfies the equation is 2. The method for estimating SOC of a lithium battery based on a high-precision ampere-hour integration algorithm according to claim 1, characterized in that: The detailed process of algorithm execution is as follows: Step 1: First, initialize the value of the state of charge soc0, which is generally read from the non-volatile memory. According to the single cell capacity and grouping mode of the battery pack, calculate the theoretical capacity value, i.e., the cap value; Step 2: Secondly, the sampling time Δ is obtained according to the sampling frequency of the current sensor by the battery management system BMS; Step 3: Again, according to the current sampling value i0 at the current moment, the K1 value is calculated using the ampere-hour integral mathematical model and a special case that satisfies the equation. The K2 value can be calculated according to the Δ value, and the K3 value can be calculated according to the values ​​K1 and K2. Step 4. Finally, the current soc1 value can be calculated based on the current soc0 value and the three slopes K1, K2, and K3. At this time, the current current value i1 is sampled again, and the three slopes K1, K2, and K3 are calculated first, and then soc2 can be calculated based on the known soc1 value. Repeat the cycle to calculate the current SOC of the lithium battery.

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