Method for managing the DC internal resistance of secondary batteries

Abstract

To more accurately estimate the DC-IR [Ω] internal resistance of a secondary battery. [Solution] The ECU includes the steps of: setting up a battery model (S1) in which multiple resistance elements that contribute to the change in the overall DC internal resistance DC-IR [Ω] of the secondary battery in response to a change in the cell battery temperature T [°C] are represented by a mathematical model; creating a relational expression to create a mathematical formula that expresses the DC internal resistance DC-IR [Ω] as the sum of each of the multiple resistance elements; a measurement step (S2) in which the cell battery temperature T [°C] and the voltage E [V] of the resistance elements of the battery model, measured simultaneously, are accumulated; and modifying the relational expression for each of the resistance elements based on the current [A], voltage [V], and temperature T [°C] accumulated in the measurement step.

Description

[Technical Field]

[0001] This paper relates to a method for managing the DC internal resistance of secondary batteries, and more specifically, to a method for managing the DC internal resistance of secondary batteries that can estimate the DC-IR more accurately. [Background technology]

[0002] Secondary batteries, such as lithium-ion secondary batteries, are used as power sources for vehicles such as electric electric vehicles (BEVs) and hybrid electric vehicles (HVs) due to their large capacity and ability to handle high current input and output. For vehicle power sources, battery packs are formed by combining battery modules, which are stacked with multiple cell batteries, and controlled by the vehicle's ECU (Electronic Control Unit). In this case, when controlling the battery pack, accurately estimating the characteristics of each cell battery constituting the battery module, especially the DC-IR (Direct Current Internal Resistance) [Ω], improves the accuracy of control for current [A] and voltage [V], as well as the accuracy of estimating the SOC (State of Charge) based on these characteristics.

[0003] However, the DC-IR internal resistance [Ω] has the characteristic of changing with temperature T [°C]. Patent Document 1 discloses a management device for an energy storage device. Figure 6 is a map showing the relationship between temperature T [°C] and the temperature correction coefficient disclosed in Patent Document 1. In the invention described in Patent Document 1, the DC internal resistance DC-IR [Ω] is measured according to the temperature T [°C], and a map of the temperature correction coefficient for each temperature T [°C] is created from the results. Then, the internal resistance value [Ω] is corrected and estimated for each temperature T [°C] using this map.

[0004] According to the energy storage device management device described in Patent Document 1, the DC internal resistance DC-IR [Ω], which changes in response to changes in temperature T [°C], can be estimated, and the energy storage device can be managed based on this DC internal resistance DC-IR [Ω]. [Prior art documents] [Patent Documents]

[0005] [Patent Document 1] Japanese Patent Publication No. 2023-006978 [Overview of the project] [Problems that the invention aims to solve]

[0006] However, in the energy storage device management device disclosed in Patent Document 1, since the energy storage device contains multiple resistance elements with different temperature T[°C] characteristics, data for all temperature T[°C] is required to accurately obtain the DC internal resistance DC-IR[Ω], which changes in a complex manner in response to changes in temperature T[°C]. Therefore, there was a problem in that it was not possible to accurately obtain the DC internal resistance DC-IR[Ω] without data corresponding to all temperature T[°C].

[0007] The problem that the present invention's method for managing the DC internal resistance of a secondary battery aims to solve is to estimate the DC internal resistance DC-IR [Ω] more accurately. [Means for solving the problem]

[0008] To solve the above problems, in the method for managing the DC internal resistance of a secondary battery according to the present invention, it is a method for managing the DC internal resistance of a secondary battery executed by a control device, comprising: a step of setting a battery model representing, by a mathematical model, a plurality of resistance elements contributing to the change in the overall DC internal resistance DC-IR [Ω] of the secondary battery in response to the change in the temperature T [°C] of the secondary battery; a step of creating a relational expression representing the DC internal resistance DC-IR [Ω] of the set battery model of the secondary battery as the sum of each of the plurality of resistance elements; a step of measuring the temperature T [°C] when the secondary battery is measured and simultaneously measuring and accumulating the voltage E [V] of each of the resistance elements of the battery model; and a step of correcting the relational expression based on the current [A], the voltage E [V], and the temperature T [°C] accumulated in the measuring step for each of the resistance elements.

[0009] The relationship of the change in the DC internal resistance DC-IR corresponding to the change in the temperature T [°C] of the resistance element can be stored in the relational expression. The resistance [Ω] of the resistance element is related by the voltage [V] of each resistance element with respect to the voltage [V] of the cell battery, and the voltage of the resistance element can include any one of the negative electrode film resistance voltage [V], the component resistance voltage [V], the reaction overvoltage [V], and the liquid resistance voltage [V].

[0010] The relational expression is for the voltage applied to all DC internal resistances DC-IR

[0011]

Number

[0012] The voltage applied to the component resistance

[0013]

Number

[0014] The voltage applied to the SEI resistance

[0015]

number

[0016] Other voltages are voltages across other resistors.

[0017]

number

[0018] When this is the case, the voltage across all DC internal resistances (DC-IR) is

[0019]

number

[0020] It is also acceptable to represent it as follows. The relationship between the change in the DC-IR internal resistance of the resistive element and the change in its temperature T[°C] may be stored in a map.

[0021] The DC internal resistance DC-IR [Ω] of the resistive element in the battery model may be determined by complex impedance analysis. The measurement step may be performed if the measured current value [A] differs from the previously measured value by a set threshold [A / s], and this difference is considered to indicate the occurrence of a pulsed current PI [A].

[0022] This method can also be suitably implemented when the secondary battery is a lithium-ion secondary battery 1. [Effects of the Invention]

[0023] According to the method for managing the DC internal resistance of a secondary battery of the present invention, it is possible to estimate the DC internal resistance DC-IR [Ω] more accurately. [Brief explanation of the drawing]

[0024] [Figure 1]This map shows the relationship between temperature T [°C] and component resistance Rz and film resistance Rsei. [Figure 2] This is a flowchart showing the procedure for managing the resistance of lithium-ion rechargeable batteries. [Figure 3] This figure shows the battery model of this embodiment. [Figure 4] This is a time chart showing the state when a pulsed current is input to a secondary battery. [Figure 5] This figure shows a conventional battery model. [Figure 6] This graph shows the relationship between conventional temperature and temperature correction coefficients. [Modes for carrying out the invention]

[0025] The method for controlling the DC internal resistance of a secondary battery of the present invention will be described below with reference to Figures 1 to 6, using an example of an embodiment of the method for controlling the DC internal resistance DC-IR [Ω] of a lithium-ion secondary battery 1. This embodiment is not intended to be interpreted as limiting the present invention.

[0026] (Summary of this embodiment) <Problems with conventional technology> As described in the background information, Patent Document 1 discloses a management device for an energy storage device. Figure 6 is a map showing the relationship between temperature T[°C] and the temperature correction coefficient disclosed in Patent Document 1. In the invention described in Patent Document 1, the DC internal resistance DC-IR[Ω] is measured according to the temperature T[°C], and a map of the temperature correction coefficient for each temperature T[°C] is created from the results. Then, the internal resistance value [Ω] is estimated at each temperature T[°C] using this map. As can be seen from the graph in Figure 6, it draws an irregular curve with three or more inflection points. This indicates that the change in DC internal resistance DC-IR[Ω] in response to the change in temperature [°C] is based on a complex change. With such a curve, it is difficult to show the relationship between temperature T[°C] and the temperature correction coefficient even by simply approximating it with a cubic or quartic equation. Therefore, with the method described in Patent Document 1, it is difficult to estimate the DC internal resistance DC-IR[Ω] for temperatures T[°C] for which there is no data, as shown in Figure 6.

[0027] <Principle of this embodiment> Therefore, in this embodiment, the elements of the change in the DC internal resistance DC-IR[Ω] with respect to the temperature change of the entire cell are decomposed into elements with different temperature characteristics by creating a battery model BM, and the relationship between the DC internal resistance DC-IR[Ω] with respect to the temperature change is analyzed for each element. By this method, the DC internal resistance management method of the lithium-ion secondary battery 1 in this embodiment can accurately estimate the DC internal resistance DC-IR[Ω] of the entire cell over the entire temperature range. As a result, accurate estimation of SOC[%] becomes possible, and the charging and discharging of the cell becomes appropriately controlled.

[0028] <DC-IR internal resistance of lithium-ion secondary battery 1 [Ω]> The DC-IR [Ω] of the lithium-ion secondary battery 1 can be measured by applying a DC current to the lithium-ion secondary battery 1 and measuring the open-circuit voltage OCV [V].

[0029] Figure 5 shows a conventional battery model BM. Here, the lithium-ion secondary battery 1 is a complex circuit including resistors RS, R1 and a capacitor C1, but it can be represented as a mathematical model such as an equivalent circuit, which is the battery model BM. In addition, the battery model BM can be further represented in detail as resistors and capacitors for each component such as the positive electrode plate and negative electrode plate, but in this embodiment, the simplest method is used for explanatory purposes.

[0030] Furthermore, the lithium-ion secondary battery 1 can be measured using, for example, EIS (Electrochemical Impedance Spectroscopy). ESI is an electrochemical measurement method that generates an impedance spectrum by applying and sweeping a small-amplitude sinusoidal potential or current and measuring the response current or potential. This spectrum reflects the change in complex impedance with frequency in the electrochemical system, and for example, a Nyquist plot can be output to measure the resistance RS of the lithium-ion secondary battery 1. By using this EIS, when a high-frequency current is applied, the resistance value [Ω] of capacitor C1 in a CR circuit consisting of resistor R1 and capacitor C1 can be reduced to a negligible degree, making the resistance value [Ω] of the CR circuit itself almost zero. In this case, the resistance value [Ω] of resistor RS alone can be measured while ignoring the CR circuit.

[0031] <Resistance RS> Resistor RS is composed of SEI resistors, CEI resistors, component resistors, resistance due to reaction overvoltage, and liquid resistors.

[0032] SEI resistance is a type of resistance that arises from the fact that decomposition products generated on the positive electrode surface are transported to the negative electrode surface by the potential gradient, forming an SEI layer (Solid Electrolyte Interface / negative electrode film resistance).

[0033] CEI resistance is a type of resistance that arises from the fact that, on the positive electrode side, the additive is oxidized at a lower potential than the non-aqueous electrolyte and decomposed preferentially over the non-aqueous electrolyte, thereby forming a CEI layer (Cathode Electrolyte Interface / positive electrode film resistance) on the positive electrode surface.

[0034] Component resistance is the resistance originating from metal components such as current collectors, internal terminals, and external terminals. In lithium-ion secondary batteries 1, the positive electrode is mainly made of Al material and the negative electrode is made of Cu material, so the temperature characteristics of the component resistance are a combination of the temperature characteristics of Al and Cu.

[0035] The resistance due to reaction overpotential is the resistance associated with the movement of ions other than Li ions during charging and discharging. The liquid resistance of a non-aqueous electrolyte is a resistance that originates from the resistance of the non-aqueous electrolyte itself.

[0036] Of these, the proportion of SEI resistance and component resistance is large, so in this embodiment, resistance RS is treated as being composed of SEI resistance and component resistance. Of course, by considering other resistances as well, the DC internal resistance DC-IR [Ω] can be estimated more accurately.

[0037] <Estimation of DC-IR [Ω] internal resistance in this embodiment> As described above, in this embodiment, the ratio of SEI resistors to component resistors is large, so in this embodiment, resistor RS is treated as being composed of SEI resistors and component resistors.

[0038] Figure 1 shows the relationship between temperature T [°C] and component resistivity RR. z [Ω / cm 2 ] and SEI resistivity RR sei [Ω / cm 2 This map shows the relationship between temperature and temperature. The horizontal axis represents temperature T [°C], with the center being 0 [°C], the right side representing high temperature, and the left side representing low temperature. The vertical axis represents the resistivity RR [Ω / cm] per unit area with respect to temperature change. 2 The upper part is the resistivity RR [Ω / cm]. 2is large.

[0039] Graph G shown as a straight line z is the component resistivity RR z [Ω / cm 2 of the resistivity RR [Ω / cm 2 with respect to the change in temperature T [°C]. It is a graph approximated by a straight line from a large number of plot points, for example, by the least squares method. As the temperature T [°C] increases, the resistivity RR [Ω / cm 2 can be seen to increase.

[0040] Graph G shown as a curve sei is the SEI resistivity R sei [Ω / cm 2 of the resistivity RR [Ω / cm 2 with respect to the change in temperature T [°C]. It is a graph approximated by a quadratic curve from a large number of plot points, for example, by the least squares method. As the temperature T [°C] increases, the resistivity RR [Ω / cm 2 can be seen to decrease.

[0041] From these combined component resistivity RR z [Ω / cm 2 and SEI resistivity RR sei [Ω / cm 2 , a graph showing the relationship between the conventional temperature T [°C] and the temperature correction coefficient shown in FIG. 6 has been derived. Conversely, from the relationship in FIG. 6, graphs G z , graph G sei cannot be derived.

[0042] In addition, in this embodiment, the relationship between the temperature T [°C] and the component resistivity RR z [Ω / cm 2 and the SEI resistivity RR sei [Ω / cm 2 was obtained by the method shown in FIG. 1. However, it is not limited to this. For example, the component resistivity RR z [Ω / cm 2Since the intrinsic values ​​of Al and Cu at temperature T[°C] are known, the ratio of Al to Cu can be determined from these values. Also, the SEI resistivity RR sei [Ω / cm 2 These can be theoretically determined based on the Arrhenius equation, etc.

[0043] <Battery Model BM> Figure 3 shows the battery model BM of this embodiment. Compared to the conventional battery model BM shown in Figure 5, it differs in that the resistor RS is divided into two resistors, RS1 and RS2. In this embodiment, the resistance of resistor RS1 is the component resistance R z [Ω] is shown, and the resistance of resistor RS2 is the SEI resistivity R sei It is shown in [Ω]. The state of resistance RS can be expressed by the following relation:

[0044] Equation 5 is an equation that shows the voltage of the DC-IR internal resistance of lithium-ion secondary battery 1, expressed using the battery model BM. When a DC current flows through resistors RS1 and RS2, The sum of the voltages [V] across the DC-IR internal resistance is

[0045]

number

[0046] Let's assume that. Component resistance voltage

[0047]

number

[0048] Let's assume that "p" represents a pulse. SEI resistor voltage

[0049]

number

[0050] Let's assume that. Other resistance voltages

[0051]

number

[0052] In that case, the sum of the voltages [V] across the DC-IR internal resistance is:

[0053]

number

[0054] It is represented as follows.

[0055]

number

[0056] Equation 6 is the determinant for finding the distribution coefficient "α" using the least squares method. As shown in Equation 6, let "A" be "the voltage (resistance value) × (pulse current value) of the resistive element at each temperature T [°C] obtained from the graph shown in Figure 1". Let "x" be the voltage correction coefficient to be found. Let "b" be "total voltage difference - voltage obtained from the model". Estimating this procedure under at least two temperature conditions and substituting it into the equation on the right and solving it gives α z and α sei This can be determined.

[0057] Then, using the determinant shown in Equation 6, we solve the least squares method to find the distribution coefficient α. From the distribution coefficient α obtained here, we find A and b.

[0058]

number

[0059] We find x using this method. <Measurement timing> Figure 4 is a time chart showing the state when a pulsed current is input to lithium-ion secondary battery 1. The voltage (resistance value) [V] of each resistive element cannot be accurately estimated unless a certain amount of current flows through it.

[0060] Therefore, in this embodiment, measurement and system updates are performed when a "pulsed current" is detected. Here, in this embodiment, a "pulsed current" is determined to have occurred when the current value sampled at a predetermined interval of 1 [sec] or less differs from the previously sampled current by ±10 [A], which is a threshold value. Needless to say, the sampling time and threshold can be appropriately optimized by those skilled in the art.

[0061] (Procedure of this embodiment) Figure 2 is a flowchart showing the procedure for managing the DC-IR [Ω] internal DC resistance of lithium-ion secondary battery 1. The procedure for managing the DC-IR [Ω] internal DC resistance of lithium-ion secondary battery 1 will be explained below with reference to this flowchart.

[0062] First, as a premise, the lithium-ion secondary battery 1 of this embodiment is a cell battery that constitutes a well-known battery pack for driving a vehicle (not shown). This battery pack is equipped with various sensors that monitor the state of each cell. The current, voltage, and temperature collected by these sensors are calculated by the computer of the ECU (Electric Control Unit) of the battery pack, which is the control device of the present invention, to estimate the State of Charge (SOC) and manage the charging and discharging of each cell.

[0063] Then, a battery model BM as shown in Figure 3 is stored in the ECU (S1). Then, the vehicle starts operating the battery (S2). When operation starts, the ECU monitors the current of the cell battery using a current sensor. It then stores the measured voltage change and temperature when a pulsed current is applied, as well as the voltage of each resistive element of the battery model BM at the same time (S3). A pulsed current is applied when the current is monitored at 1-second intervals and a change of ±10[A] or more occurs. When a pulsed current is applied, the ECU collects and stores the cell battery voltage [V] and temperature T [°C] using a sensor.

[0064] For example, once 100 data points have been stored, the voltage correction coefficient for each resistor element is calculated from the voltage of each resistor element in the battery model BM using the formulas shown in "Equation 5" to "Equation 7" above, and the battery model BM in the ECU is updated and stored (S4).

[0065] For example, if the battery operation is terminated due to the vehicle being shut down (S5:YES), the battery operation is terminated; otherwise (S5:NO), the procedure from S3 is repeated. (Operation of this embodiment) In this embodiment, the elements of the change in the DC internal resistance DC-IR[Ω] with respect to the temperature change of the entire cell are decomposed into elements with different temperature characteristics by creating a battery model BM, and the relationship between the DC internal resistance DC-IR[Ω] with respect to the temperature change is analyzed for each element. By this method, the DC internal resistance management method of the lithium-ion secondary battery 1 in this embodiment accurately estimates the DC internal resistance DC-IR[Ω] of the entire cell over the entire temperature range. As a result, accurate estimation of SOC[%] becomes possible, and the charging and discharging of the cell becomes appropriately controlled.

[0066] (Effects of this embodiment) (1) The method for managing the DC-IR [Ω] internal DC resistance of the lithium-ion secondary battery 1 of this embodiment has the effect of being able to estimate the DC-IR [Ω] internal DC resistance more accurately.

[0067] (2) The ECU sets up a battery model BM, which represents the multiple resistive elements that contribute to the change in the overall DC internal resistance DC-IR [Ω] of the lithium-ion secondary battery 1 in response to the change in the temperature T [°C] of the lithium-ion secondary battery 1, using an equivalent circuit. This has the effect of enabling appropriate management tailored to the characteristics of each lithium-ion secondary battery 1.

[0068] (3) Create a formula that expresses the DC internal resistance DC-IR[Ω] of the set battery model BM as the sum of the resistances of each of the multiple resistance elements. This has the effect of simplifying the DC internal resistance DC-IR[Ω], which changes in a complex way with respect to changes in temperature T[°C].

[0069] (4) The temperature T [°C] measured when lithium-ion secondary battery 1 is measured, and the voltage E [V] of the resistive elements of the battery model BM, which is measured simultaneously, are stored. For each resistive element, the relational equation is modified based on the current [A], voltage [V], and temperature T [°C] stored in the measurement step. This has the effect of constantly updating the battery model BM using this data to accurately estimate the DC internal resistance DC-IR [Ω].

[0070] (5) The relationship between the change in the DC internal resistance DC-IR in response to the change in the temperature T [°C] of the resistive element is stored in a relational equation. This has the effect of allowing the ECU to update the battery model BM in real time and accurately estimate the DC internal resistance DC-IR [Ω].

[0071] (6) The resistance [Ω] of the resistive elements is shown in relation to the voltage [V] of each resistive element with respect to the voltage [V] of the cell battery, and the voltage of the resistive elements includes one of the following: negative electrode film resistance voltage [V], component resistance voltage [V], reaction overvoltage [V], or liquid resistance voltage [V]. This has the effect of allowing for a more accurate estimation of the DC-IR internal resistance.

[0072] (7) The relational expression represents the voltage across all DC internal resistances (DC-IR) using the voltage across all DC internal resistances (DC-IR), the voltage across component resistances, the voltage across SEI resistances, and the voltage across other resistors. Therefore, it has the effect of allowing for a more accurate estimation of DC internal resistances (DC-IR).

[0073] (8) The resistive elements in the battery model BM are determined by complex impedance analysis to find their DC internal resistance DC-IR [Ω]. This has the effect of allowing accurate measurement of only the resistance RS in the battery model BM.

[0074] (9) The measurement step is performed when the measured current value [A] is found to have a pulsed current PI [A] if the difference exceeds a set threshold of 10 [A / s] compared to the previously measured value. This has the effect of collecting data with less measurement noise.

[0075] (Alternative example) The present invention is not limited to this embodiment and can be implemented in the following forms. ○In this embodiment of the battery pack control method, we have exemplified a battery pack that constitutes a battery pack installed for propulsion in an electric vehicle or a hybrid vehicle mounted on a vehicle, but the application is not limited as long as it is a battery pack made by combining cell batteries CB.

[0076] ○In this embodiment, a lithium-ion secondary battery 1 was used as an example. However, secondary batteries are not limited to this, and the invention can be broadly applied to secondary batteries that are composed of combinations of single cells, such as other non-aqueous electrolyte secondary batteries, alkaline electrolyte secondary batteries like NiMH secondary batteries, and all-solid-state batteries.

[0077] ○The drawings are for the purpose of understanding the invention and may be exaggerated or omitted in some parts, but they do not limit the present invention. ○The battery model BM shown in Figure 3 is just one example; its configuration is not limited as long as the procedure of the present invention can be carried out.

[0078] ○The flowchart shown in Figure 2 is an example of an implementation of the present invention, and it goes without saying that those skilled in the art can implement it by adding, deleting, rearranging, or changing the steps. The numerical values, ranges, graphs, etc., exemplified in this embodiment are merely examples for explaining the present invention, and are not limited to these numerical values ​​and ranges. They can be appropriately optimized and implemented by those skilled in the art.

[0079] ○Furthermore, the present invention is not limited to this embodiment, and can be implemented by those skilled in the art by adding, deleting, or modifying as appropriate without departing from the scope of this disclosure. [Explanation of symbols]

[0080] 1…Lithium-ion rechargeable battery DC-IR[Ω]…DC internal resistance T[°C]…Temperature RS…Resistance R sei [Ω / cm 2 ]...Film resistance R z [Ω / cm 2 ]...Component resistor α...distribution coefficient α z ...parts allocation coefficient α sei ...coating distribution coefficient ν[V]...resistive voltage ν z [V]...Component resistance voltage ν sei [V]...film resistance voltage ν rest [V]...Other resistance voltage p...pulse

Claims

1. A method for managing the DC internal resistance of a secondary battery, which is performed by a control device, The steps include setting up a battery model in which multiple resistive elements that contribute to the change in the overall DC internal resistance DC-IR [Ω] of the secondary battery in response to a change in the temperature T [°C] of the secondary battery are represented by mathematical models, and A step of creating a relational expression, which expresses the DC internal resistance DC-IR [Ω] of the battery model of the set secondary battery as the sum of the resistance elements, A measurement step of storing the temperature T [°C] when the secondary battery was measured, and the voltage E [V] of the resistance element of the battery model measured simultaneously, For each of the aforementioned resistance elements, a relationship modification step is performed in which the relationship is modified based on the current [A], voltage E [V], and temperature T [°C] accumulated in the measurement step, A method for managing the DC internal resistance of a secondary battery equipped with [a specific feature / equipment].

2. The method for managing the DC internal resistance of a secondary battery according to claim 1, characterized in that the relationship between the change in the DC internal resistance DC-IR in response to the change in the temperature T [°C] of the resistive element is stored in the relational expression.

3. The method for managing the DC internal resistance of a secondary battery according to claim 1, wherein the resistance [Ω] of the resistive elements is shown in relation to the voltage [V] of each resistive element with respect to the voltage [V] of the cell battery, and the voltage of the resistive elements includes any of the negative electrode film resistance voltage [V], component resistance voltage [V], reaction overvoltage [V], or liquid resistance voltage [V].

4. The above relation is, The voltage across all DC internal resistances DC-IR [Math 1] The voltage across the component resistor [Math 2] The voltage across the SEI resistor [Math 3] Other voltages are voltages across other resistors. [Math 4] When this is the case, the voltage across all DC internal resistances DC-IR is [Math 5] A method for managing the DC internal resistance of a secondary battery according to claim 1, characterized by being expressed as follows.

5. The method for managing the DC internal resistance of a secondary battery according to claim 1, characterized in that the relationship between the change in the DC internal resistance DC-IR in response to a change in the temperature T [°C] of the resistive element is stored in a map.

6. The method for managing the DC internal resistance of a secondary battery according to claim 1, characterized in that the DC internal resistance DC-IR [Ω] of the resistive element in the battery model is determined by complex impedance analysis.

7. The method for managing the DC internal resistance of a secondary battery according to claim 1, characterized in that the measurement step is performed when the measured current value [A] is found to have a difference exceeding a set threshold [A / s] compared to the previously measured value, and it is determined that a pulsed current PI [A] has occurred.

8. The method for managing the DC internal resistance of a secondary battery according to claim 1, characterized in that the secondary battery is a lithium-ion secondary battery.

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