Simulation method for evaluating influence of inconsistency of single batteries on electrical performance of grouped batteries

Abstract

A simulation method for evaluating the influence of single battery inconsistency on the electrical performance of a battery pack comprises the steps that a battery pack simulation model supporting a series-connection single battery inconsistency setting method and a parallel-connection single battery inconsistency setting method is constructed, battery parameters at different positions in series-parallel branches are set based on the electrical performance of the single batteries, and the influence of the single battery inconsistency on the electrical performance of the battery pack is evaluated. And the output capability of the power battery under the condition that the single batteries are inconsistent is estimated, so that the electrical performance simulation of the grouped battery for simulating the inconsistent single batteries is realized. According to the method, the influence of the inconsistency of the single batteries on the electrical performance of the grouped batteries can be conveniently evaluated, and a basis is provided for design matching and operation strategy design of a vehicle electrical system, so that the adverse influence of the inconsistency of the single batteries on the operation of the whole electrical system is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of electrical performance simulation of vehicle power batteries, and particularly to a simulation method for evaluating the influence of battery cell inconsistency on the electrical performance of battery packs. Background Art

[0002] As the main power source of hybrid / electric vehicles, the electrical performance of vehicle power batteries directly affects various performance indicators of the vehicles. Therefore, at the beginning of the design of the electrical system of hybrid / electric vehicles, it is necessary to accurately estimate the electrical performance of the power batteries. The power battery is formed by connecting multiple battery cells in series and parallel. Under ideal conditions, its electrical performance is the superposition of the electrical performance of the single cells. However, in actual use, there are slight inconsistencies in the operating temperature, initial SOC, capacity, DC internal resistance, etc. of different single cells. During long-term use, this inconsistency will cause the electrical energy output / absorbed by the single cells to be inconsistent, and further increase this inconsistency of the single cells.

[0003] The inconsistency of battery cells directly causes the decline of the electrical performance of the battery pack after grouping. At the beginning of the design of the vehicle electrical system, designers can only obtain the ideal test data of the battery cells, lacking the inconsistency of the single cells caused by the operating environment and the processing differences of the single cells, and it is difficult to evaluate the influence degree of the inconsistency of the battery cells on the electrical performance of the battery pack after grouping when the inconsistency occurs during the vehicle operation. Summary of the Invention

[0004] The present disclosure provides a simulation method for evaluating the influence of battery cell inconsistency on the electrical performance of battery packs, which can estimate the output capacity of the power battery caused by the battery cell inconsistency based on the electrical performance of the single cells.

[0005] This method constructs a battery pack simulation model based on series and parallel connections, and then sets the simulation parameters based on the electrical performance identification parameters of the battery cells, and evaluates the influence of the difference in battery cell consistency on the electrical output performance of the battery pack by simulation comparison under the same power demand.

[0006] Specifically, it includes the following steps:

[0007] S1, construct a battery pack simulation model based on the series and parallel connections of the battery cells;

[0008] S2, set the average model parameters of the battery cells, the model parameters of the battery cells in the parallel branch, and the parameters of the battery cells in the series branch based on different electrical performance identification parameters of the battery cells;

[0009] S3, during the simulation operation, obtain the parameter changes of the battery pack model in real time to evaluate the influence of the inconsistent battery cell electrical parameters on the electrical output performance of the battery pack.

[0010] Furthermore, the specific method of step S1 includes:

[0011] Construct two parallel battery cell branch models, and each battery cell branch model is called P_DT i (i = 1, 2), and the number of parallel battery cells in each branch model is n i (i = 1, 2);

[0012] Each battery cell branch model contains two series battery cell branch models, and each series battery cell branch model is called S_DT ij (i = 1, 2; j = 1, 2), and the number of series cells in each battery cell branch model is m ij (i = 1, 2; j = 1, 2), and it is satisfied that the number of series cells in the two parallel branches is the same, that is:

[0013] m 11 +m 12＝ m 21 +m 22

[0014] The total number of parallel branches of the grouped battery model is N = n1 + n2, and the total number of series branches M = m 11 +m 12＝ m 21 +m 22 , and the entire grouped battery model contains M × N cells in total.

[0015] Furthermore, the specific method of step S2 includes:

[0016] Set the initial parameters of the cells in S_DT ij (i = 1, 2; j = 1, 2) respectively, including: the current temperature T ij , (i, j = 1, 2), the capacity C ij , (i, j = 1, 2), the initial SOC ij (0), (i, j = 1, 2), the DC internal resistance offset parameter k ij (i, j = 1, 2), and the above four types of parameters are set separately in different S_DT ij (i, j = 1, 2) to represent different inconsistency indicators of the battery cells;

[0017] From these four types of parameters, calculate the DC internal resistance of S_DT ij (i, j = 1, 2) as:

[0018] r ij (0) = f r (T ij , SOC ij (0)) × k ij ×mij / n i , (i, j = 1, 2);

[0019] P_DT i The DC internal resistance of (i = 1, 2) is:

[0020] r i (0) = r i1 (0) + r i2 (0)

[0021] Among them, f r (T ij (0), SOC ij (0)) is the fitting function of the internal resistance of the battery cell with respect to the cell temperature and the cell SOC, obtained from the measured data of the single cell; the DC internal resistance offset parameter k ij(i,j＝1,2) describes the deviation of the DC internal resistance of the battery cell from the normal DC internal resistance.

[0022] Furthermore, the step S3 specifically includes:

[0023] After setting the model parameters, perform circuit simulation on the battery pack model, that is, apply a current I between the positive and negative poles of the battery pack model bat , and observe the corresponding voltage waveform U bat ;

[0024] During the simulation, based on the applied current I bat and the battery cell parameters, the parameter changes of the battery pack model are obtained in real time, including:

[0025] The output voltage of each S_DT ij (i, j = 1, 2) is:

[0026] U sij (t) = f u (T ij , SOC ij (t)) ，(i,j＝1,2)

[0027] Among them, f u (T ij (t), SOC ij (t)) is the fitting function of the battery cell voltage with respect to the cell temperature and the cell SOC, obtained from the measured data of the single cell;

[0028] The voltage of each battery cell branch P_DT i , (i = 1, 2) is:

[0029] U Pi (t) = Us i1 (t) + Us i2(t), (i, j = 1, 2)

[0030] Each battery cell branch P_DT i , the current of (i = 1, 2) is:

[0031] I P2 (t) = (U P1 (t) - U P2 (t) - I bat × r1(t)) / (r1(t) - r2(t)), I P1 (t) = I bat - I P2 (t)

[0032] The output voltage of the grouped battery model is:

[0033] U bat = U P1 (t) - I P1 (t) × r1(t) = U P2 (t) - I P2 (t) × r2(t).

[0034] Furthermore, the step S3 further includes the step of updating the SOC of the battery model S_DTij. The specific method includes:

[0035] SOCij(t + 1) = (SOCij(t) - IPi(t) × △T) / Cij, (i, j = 1, 2)

[0036] where △T is the simulation time step.

[0037] Compared with the prior art, the beneficial effects of the present disclosure are: ① constructing a battery grouping simulation model that supports two single - cell inconsistency setting methods of series and parallel, and realizing the simulation of the electrical performance of grouped batteries with single - cell inconsistency by setting the battery parameters at different positions in the series - parallel branches; ② the method is simple to implement in engineering; ③ it can provide a basis for adding more detailed design content in the design matching and operation strategy of the vehicle electrical system, and avoid the adverse effects of single - cell inconsistency on the operation of the overall electrical system. Brief Description of the Drawings

[0038] By describing the exemplary embodiments of the present disclosure in more detail in conjunction with the drawings, the above - mentioned and other objects, features, and advantages of the present disclosure will become more obvious. Among them, in the exemplary embodiment mode of the present disclosure, the same reference numerals generally represent the same components.

[0039] Figure 1 It is a flowchart of an exemplary embodiment according to the present disclosure;

[0040] Figure 2 This is a schematic diagram of the DC power grid topology for special vehicles with multi-voltage systems. DETAILED DESCRIPTION

[0041] The preferred embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although preferred embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to make the present disclosure more thorough and complete, and to fully convey the scope of the present disclosure to those skilled in the art.

[0042] The present disclosure provides a simulation method for evaluating the impact of battery cell inconsistency on the electrical performance of a battery group. The method constructs a battery group simulation model that supports both series and parallel cell inconsistency setting methods. Based on the electrical performance of the single cell, the battery parameters at different positions in the series and parallel branches are set, and the output capacity of the power battery is estimated when the battery cells are inconsistent, thereby realizing the electrical performance simulation of a battery group that simulates the inconsistency of the battery cells.

[0043] In an exemplary embodiment, a topology diagram of a multi-voltage DC power grid for special vehicles is shown in the attached figure. Figure 1 The simulation method according to the present disclosure is shown in the attached Figure 2 As shown, the specific steps include:

[0044] Step 1: Build two parallel battery cell branch models. Each battery cell branch model is called P_DT i,(i＝1,2) , the number of battery cells in parallel in each branch model is n i,(i＝1,2) .

[0045] Step 2: Each battery cell branch model contains two sets of series battery cell branch models. Each set of series cell branch models is called S_DT ij(i＝1,2；j＝1,2) , the number of series connections of each battery cell branch model is m ij(i＝1,2；j＝1,2) , and the number of series monomers in the two parallel branches is consistent, that is:

[0046] m 11 +m 12 =m 21 +m 22

[0047] According to the settings of steps 1 and 2, the total number of parallel branches in the battery group model is N=n1+n2, and the total number of series branches is M=m 11 +m 12＝ m 21 +m 22 , the entire battery group model contains a total of M×N cells.

[0048] For example: There are a total of 4 modules in a battery pack model: D11, D12, D21, and D22. Among them, D11 is 10 strings in parallel with 2 cells in each string, D12 is 2 strings in parallel with 2 cells in each string, D21 is 8 strings in parallel with 1 cell in each string, and D22 is 4 strings in parallel with 1 cell in each string;

[0049] Connect D11 and D12 in series to form a branch of 12 strings in parallel with 2 cells in each string;

[0050] Connect D21 and D22 in series to form a branch of 12 strings in parallel with 1 cell in each string;

[0051] Finally, connect the two series branches in parallel to form a branch of 12 strings in parallel with 3 cells in each string.

[0052] Step 3: Set the initial parameters of the single cells in S_DT ij(i＝1,2；j＝1,2) , including the current temperature T ij,(i,j＝1,2) , capacity C ij,(i,j＝1,2) , initial SOC ij (0) ,(i,j＝1,2) , DC internal resistance offset parameter k ij(i,j＝1,2) . The above four types of parameters can be set separately in different S_DT ij(i,j＝1,2) to represent different inconsistency indicators of the battery cells. From these four types of parameters, the initial DC internal resistance of S_DT ij(i,j＝1,2) can be calculated as:

[0053] r ij (0) = f r (T ij , SOC ij (0)) × k ij × m ij / n i，(i,j＝1,2)

[0054] P_DT i(i＝1,2) 's initial DC internal resistance is:

[0055] r i (0) = r i1 (0) + r i2 (0)

[0056] Among them, f r (T ij (0), SOC ij (0)) is the fitting function of the internal resistance of the battery cell with respect to the cell temperature and cell SOC, obtained from the measured data of the single battery cell. The DC internal resistance offset parameter k ij(i,j＝1,2) describes the deviation of the DC internal resistance of the battery cell from the normal DC internal resistance, and generally is not equal to 1.

[0057] Step 4: After setting the model parameters, circuit simulation of the grouped battery model can be carried out, that is, apply a current I between the positive and negative poles of the grouped battery modelbat , observe the corresponding voltage waveform U bat , during the simulation, based on the applied current I bat , and the parameters of the battery cells, the parameter changes of the battery model of the battery pack can be obtained in real time,

[0058] where: every S_DT ij(i,j＝1,2) The output voltage is:

[0059] U sij(t) = f u (T ij , SOC ij (t)) ，(i,j＝1,2)

[0060] where f u (T ij (t), SOC ij (t)) is the fitting function of the battery cell voltage with respect to the cell temperature and cell SOC, obtained from the measured data of the single battery;

[0061] The voltage of each battery cell branch P_DT i,(i＝1,2) is:

[0062] U Pi (t) = Us i1 (t) + Us i2 (t) ，(i,j＝1,2)

[0063] The current of each battery cell branch P_DT i,(i＝1,2) is:

[0064] I P2 (t) = (U P1 (t) - U P2 (t) - I bat × r1(t)) / (r1(t) - r2(t)), I P1 (t) = I bat - I P2 (t)

[0065] The output voltage of the battery pack model is:

[0066] U bat = U P1 (t) - I P1 (t) × r1(t) = U P2 (t) - I P2 (t) × r2(t)

[0067] The SOC of the battery model S_DT ij can be updated to:

[0068] SOC ij(t + 1) = (SOC ij (t) - I Pi (t) × △T) / C ij,(i,j＝1,2)

[0069] where △T is the simulation time step.

[0070] Based on these parameters, the impact of the cell inconsistency on the electrical performance of the battery pack can be further analyzed. The analysis method is as follows: According to the obtained parameters such as voltage and current, compare them with the requirements of the system to which the battery is applied, and evaluate whether the battery can still meet the system requirements when there is cell inconsistency, so as to clarify the impact brought by the cell inconsistency.

[0071] The above technical solution is only an exemplary embodiment of the present invention. For those skilled in the art, based on the application methods and principles disclosed in the present invention, it is easy to make various types of improvements or deformations, not limited to the methods described in the above specific embodiments of the present invention. Therefore, the above-described manner is only preferred and does not have a restrictive meaning.

Claims

1. A simulation method for evaluating the influence of battery cell inconsistency on the electrical performance of a battery pack, comprising the following steps: S1. Based on the series and parallel connection of battery cells, construct a battery pack simulation model; S2. Based on different electrical performance identification parameters of battery cells, set the average model parameters of battery cells, the model parameters of battery cells in parallel branches, and the parameters of battery cells in series branches; S3. During the simulation operation, obtain the parameter changes of the battery pack model in real time to evaluate the influence of inconsistent battery cell electrical parameters on the output electrical performance of the battery pack.

2. The method according to claim 1, characterized in that, The specific method of step S1 includes: Build a battery cell branch model with two parallel branches, and each battery cell branch model is called P_DT i (i = 1, 2), and the number of parallel battery cells in each branch model is n i (i = 1, 2); Each battery cell branch model contains two sets of series-connected battery cell branch models, and each set of series-connected cell branch models is called S_DT ij (i = 1, 2; j = 1, 2), the number of series-connected cells in each set of battery cell branch models is m ij (i = 1, 2; j = 1, 2), and it satisfies that the number of series-connected cells in the two parallel branches is the same, that is: m 11 +m 12＝ m 21 +m 22 The total number of parallel branches of the grouped battery model is N = n1 + n2, and the total number of series branches is M = m 11 + m 12＝ m 21 + m 22 , and the entire grouped battery model contains M × N single cells in total.

3. The method according to claim 2, wherein The specific method of step S2 includes: Set S_DT separately ij The initial parameters of the monomers in (i = 1, 2; j = 1, 2) include: the current temperature T ij , (i, j = 1, 2), the capacity C ij , (i, j = 1, 2), the initial SOC ij (0), (i, j = 1, 2), the DC internal resistance offset parameter k ij (i, j = 1, 2), the above four types of parameters are separately set in different S_DT ij (i, j = 1, 2) to represent different inconsistency indicators of the battery monomers; Calculate \(S_{DT}\) from these four types of parameters ij (i, j = 1, 2) has a DC internal resistance of: r ij (0) = f r (T ij , SOC ij (0)) × k ij × m ij / n i , (i, j = 1, 2); P_DT i (where \(i = 1, 2\)) the DC internal resistance is: r i (0)＝r i1 (0)+r i2 (0) Among them, f r (T ij (0), SOC ij (0)) is a fitting function of the internal resistance of the battery cell with respect to the cell temperature and the cell SOC, obtained from the measured data of the single cell; the DC internal resistance offset parameter k ij(i,j＝1,2) describes the deviation of the DC internal resistance of the battery cell from the normal DC internal resistance.

4. The method according to claim 3, wherein The specific content of step S3 includes: After setting the model parameters, perform circuit simulation on the battery pack model, that is, apply a current I between the positive and negative poles of the battery pack model bat , and observe the corresponding voltage waveform U bat ; During the simulation process, based on the applied current I bat and the parameters of the single battery cells, the parameter changes of the grouped battery model are obtained in real time. According to these parameters, the influence of the inconsistency of single battery cells on the electrical performance of the grouped batteries can be evaluated; These parameters include: Per S_DT ij (i, j = 1, 2) The output voltage is: U sij U(t) = f u (T ij , SOC ij (t)) ，(i,j＝1,2) where, f u (T ij (t), SOC ij (t)) is the fitting function of the battery cell voltage with respect to the cell temperature and the cell SOC, which is obtained from the measured data of the single cell; Each battery cell branch P_DT i , (i = 1, 2) has a voltage of: U Pi u(t) = Us i1 u(t) + Us i2 u(t), (i, j = 1, 2) Each battery cell branch P_DT i , the current of (i = 1, 2) is: I P2 (t) = (U P1 (t) - U P2 (t) - I bat × r1(t)) / (r1(t) - r2(t)), I P1 (t) = I bat -I P2 (t) The output voltage of the battery pack model is: U bat = U P1 (t) - I P1 (t) × r1(t) = U P2 (t) - I P2 (t) × r2(t).

5. The method according to any one of claims 2-4, characterized in that, The step S3 further includes the step of updating the SOC of the battery model S_DT ij , and the specific method includes: SOC ij (t + 1) = (SOC ij (t) - I Pi (t) × △T) / C ij, (i, j = 1, 2) where △T is the simulation time step.

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