SOC estimation method

Abstract

To enable the SOC of an iron phosphate-lithium ion cell that includes a cathode formed from iron lithium phosphate to be estimated with good accuracy.SOLUTION: Provided is a method for estimating the SOC of an iron phosphate-lithium ion cell that includes a cathode formed from iron lithium phosphate. This method includes: calculating an overvoltage due to cathode reaction, on the basis of at least the measured value of a cell voltage and an OCV acquired from a first map that defines the relationship between the SOC and the OCV of the iron phosphate-lithium ion cell; when it is assumed that the cathode is composed of a plurality of particles, each including lithium, calculating the overvoltage of each particle, using a second map defined on the basis of the overvoltage due to cathode reaction and the relationship between the lithium composition of the iron lithium phosphate and the OCV of the cathode; calculating an estimated cell current of the iron phosphate-lithium ion cell from the current density of each particle based on the overvoltage of each particle; and estimating the SOC on the basis of the estimated cell current.SELECTED DRAWING: Figure 4

Description

[Technical field]

[0001] The present disclosure relates to a method for estimating the SOC of a lithium iron phosphate ion battery that includes a positive electrode formed from lithium iron phosphate. [Background technology]

[0002] In recent years, lithium iron phosphate ion batteries including a positive electrode (hereinafter referred to as "LiFePO positive electrode") formed of lithium iron phosphate such as LiFePO4 are being adopted as a replacement for secondary batteries mounted on electric vehicles (BEVs) and hybrid vehicles (HEVs) and lead-acid batteries (12V batteries) mounted on vehicles. The LiFePO positive electrode of a lithium iron phosphate ion battery exhibits peculiar behavior (polarization behavior) such as memory effect, path dependency, and voltage hysteresis in which the OCV (open circuit voltage) changes between charging and discharging. In addition, as a model for explaining the behavior of the LiFePO positive electrode, a many-particle model is known that assumes that the LiFePO positive electrode is composed of a large number of spherical particles with different particle radii that are electronically and ionically connected to each other (see, for example, Non-Patent Document 1). By using such a multi-particle model, the behavior of the LiFePO positive electrode can be comprehensively grasped. [Prior art documents] [Non-patent literature]

[0003] [Non-Patent Document 1] Comprehensive Study of the Polarization Behavior of LiFePO4 Electrodes Based on a Many-Particle Model Hiroki Kondo, Tsuyoshi Sasaki, Pallab Barai and Venkat Srinivasan Journal of The Electrochemical Society, Volume 165, Number 10 Published 6 July 2018 Summary of the Invention [Problem to be solved by the invention]

[0004] In ternary lithium-ion batteries and the like, the SOC is generally estimated by combining a current integration method, which estimates the SOC by integrating measured current values, with an estimation method using the relationship between the SOC and the OCV. In contrast, in lithium iron phosphate batteries, the rate of change in OCV relative to changes in SOC becomes very small in a wide range other than the high SOC and low SOC ranges, and the voltage hysteresis and the like are present, making it difficult to accurately estimate the SOC from the relationship between the SOC and the OCV. For this reason, a method for accurately estimating the SOC of lithium iron phosphate batteries is required, but the above-mentioned Non-Patent Document 1 does not disclose any method for estimating the SOC of lithium iron phosphate batteries.

[0005] Therefore, a primary object of the present disclosure is to enable accurate estimation of the SOC of a lithium iron phosphate ion battery that includes a positive electrode formed from lithium iron phosphate. [Means for solving the problem]

[0006] The SOC estimation method disclosed herein is a SOC estimation method for estimating the SOC of a lithium iron phosphate ion battery including a positive electrode formed from lithium iron phosphate, and includes the steps of: calculating an overvoltage due to a reaction of the positive electrode based on a measured voltage of the lithium iron phosphate ion battery and an OCV obtained from a first map determined in advance so as to define the relationship between the SOC and OCV of the lithium iron phosphate ion battery; calculating an overvoltage of each particle when it is assumed that the positive electrode is composed of a plurality of particles, each of which contains lithium, using the overvoltage due to the reaction of the positive electrode and a second map determined in advance based on the relationship between the lithium composition of the lithium iron phosphate and the OCV of the positive electrode; calculating a current density of each particle based on the overvoltage of each particle; calculating an estimated battery current of the lithium iron phosphate ion battery based on the current density of each particle; and estimating the SOC of the lithium iron phosphate ion battery based on the estimated battery current.

[0007] The SOC estimation method of the present disclosure uses a multi-particle model that assumes that the positive electrode formed of lithium iron phosphate is composed of multiple particles each containing lithium. When estimating the SOC of the lithium iron phosphate ion battery, an overvoltage caused by the reaction of the positive electrode is calculated based on at least the measured voltage of the lithium iron phosphate ion battery and the OCV obtained from a first map that is predetermined to define the relationship between the SOC and OCV of the lithium iron phosphate ion battery. Furthermore, the overvoltage of each of the multiple particles that constitute the positive electrode is calculated using the overvoltage caused by the reaction of the positive electrode and a second map that is predetermined based on the relationship between the lithium composition of the lithium iron phosphate and the OCV of the positive electrode. Then, the current density of each of the multiple particles is calculated based on the overvoltage of each of the multiple particles, and the estimated battery current of the lithium iron phosphate ion battery is calculated from the current density of each of the multiple particles. As a result, the SOC of the lithium iron phosphate ion battery can be estimated based on the estimated battery current calculated to offset the difference between the OCV obtained from the first map and the actual OCV. As a result, it is possible to accurately estimate the SOC of lithium iron phosphate-ion batteries that contain a positive electrode made of lithium iron phosphate, which exhibits unique behavior such as memory effect, path dependency, and voltage hysteresis.

[0008] Also, the overvoltage due to the reaction of the positive electrode may be calculated by subtracting at least the previous OCV corresponding to the previous SOC obtained from the first map from the measured voltage value of the lithium iron phosphate battery, the overvoltage of each particle may be calculated from the overvoltage due to the reaction of the positive electrode and the reference voltage of each particle obtained from the second map, and the current SOC of the lithium iron phosphate battery may be estimated from the previous SOC, the estimated battery current, and the battery capacity, and the current OCV corresponding to the current SOC may be obtained from the first map. This makes it possible to converge the estimated SOC value to an actual value by repeatedly estimating the SOC of the lithium iron phosphate battery.

[0009] Furthermore, the first map may be created by subtracting the OCV of the negative electrode of the lithium iron phosphate battery from the average voltage of the two spinodal points of the positive electrode for each SOC, and the second map may be created by offsetting the relationship between the lithium composition of the lithium iron phosphate and the OCV of the positive electrode so that the average voltage of the two spinodal points of the positive electrode becomes 0 V. This makes it possible to more appropriately calculate the overvoltage of each of the multiple particles using the overvoltage due to the reaction of the positive electrode and the second map.

[0010] In addition, the amount of change in the lithium concentration of each particle may be calculated based on the current density of each particle, and the current lithium concentration may be calculated from the previous lithium concentration and the amount of change, and the reference voltage of each particle corresponding to the lithium composition based on the previous lithium concentration may be obtained from the second map, which makes it possible to more appropriately calculate the reference voltage and thus the overvoltage of each of the multiple particles.

[0011] Furthermore, the overvoltage caused by the reaction of the positive electrode may be calculated by subtracting the previous OCV, the salt concentration overvoltage, and the product of the measured current and the internal resistance of the lithium iron phosphate ion battery from the measured voltage value of the lithium iron phosphate ion battery, thereby reducing the calculation load and making it possible to more appropriately calculate the overvoltage caused by the reaction of the positive electrode. [Brief description of the drawings]

[0012] [Figure 1] 1 is a schematic configuration diagram of a vehicle equipped with a battery including a lithium iron phosphate battery to which the SOC estimation method of the present disclosure is applied. [Diagram 2] 1 is a diagram showing the relationship between the lithium composition of lithium iron phosphate and the OCV of a LiFePO positive electrode. [Diagram 3]1A is a graph showing the relationship between the SOC of a lithium iron phosphate ion battery and the average voltage of the OCV of the positive electrode, FIG. 1B is a graph showing the relationship between the SOC of a lithium iron phosphate ion battery and the OCV of the negative electrode, and FIG. 1C is a graph showing an example of a first map that specifies the relationship between the SOC and OCV of a lithium iron phosphate ion battery. [Figure 4] 4 is a flowchart for explaining a SOC estimation method according to the present disclosure. [Diagram 5] 4 is a chart showing an example of a second map used in the SOC estimation method of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] Next, an embodiment of the present disclosure will be described with reference to the drawings.

[0014] 1 is a schematic diagram showing a vehicle V equipped with a battery 1 including a lithium iron phosphate battery to which the SOC estimation method of the present disclosure is applied. The vehicle V shown in the figure is an electric vehicle (BEV) or a hybrid vehicle (HEV, PHEV) including, in addition to the battery 1, a motor generator (three-phase AC motor) MG that is connected to the battery 1 via a power control device (not shown) including an inverter and the like and that is capable of exchanging power with the battery 1 to output driving power and regenerative braking power.

[0015] The battery 1 is a so-called high-voltage battery including a battery stack including a plurality of battery modules connected in series, for example, and a case that houses the battery stack, and each battery module includes a plurality of battery cells 2 that are connected in series, for example, and housed in a module case. In this embodiment, the battery cells 2 that make up the battery module are lithium iron phosphate ion batteries that include a positive electrode (LiFePO positive electrode) formed of lithium iron phosphate having an olivine crystal structure, which is LiFePO4, and a negative electrode formed of a graphite-based carbon material or the like, and the positive electrode and the negative electrode are housed inside an exterior body together with a separator and an electrolyte solution, which is an organic solvent or the like.

[0016] FIG. 2 is a diagram showing the relationship between the lithium composition x ("x" in LixFePO4) of lithium iron phosphate and the OCV (open circuit voltage) of the LiFePO positive electrode obtained by an experiment. As shown in the figure, when a lithium iron phosphate battery is charged and discharged, a reaction proceeds in the LiFePO positive electrode in a state in which a Li-rich phase, a Li-poor phase, and a region in which the two phases coexist exist. In addition, as shown in the figure, the OCV of the LiFePO positive electrode decreases approximately in proportion to the decrease in the lithium composition x between the spinodal point on the Li-rich phase side and the spinodal point on the Li-poor phase side, and the voltage difference between the two spinodal points is approximately 20 mV. Furthermore, the average voltage of the two spinodal points (the equilibrium voltage in the coexistence phase of the Li-rich phase and the Li-poor phase) is approximately 3.43 V.

[0017] Here, in consideration of the unique behavior (polarization behavior) of the LiFePO positive electrode, such as the memory effect, path dependency, and voltage hysteresis, a many-particle model is introduced that assumes that the LiFePO positive electrode is composed (formed) of N spherical particles with different particle radii that are electronically and ionically connected to each other. From FIG. 2, the OCV of each particle can be obtained from the lithium composition x of each of the particles. In addition, when an overvoltage occurs due to the reaction of the LiFePO positive electrode, each of the particles that constitute the LiFePO positive electrode has an overvoltage η according to the lithium composition. j (where “j” is an integer from 1 to N). Furthermore, the overvoltage η j The overvoltage caused by the reaction of the LiFePO positive electrode during charging and discharging of a lithium iron phosphate battery is called "ΔV MPM ” and the OCV of the jth particle obtained from Figure 2 is “OCV j " and the average voltage of the two spinodal points is "V AVE ", the overvoltage of N particles is expressed as follows (1), j The average value of the overvoltage ΔV MPM Matches.

[0018]

number

[0019] In addition, the overvoltage η j The current density of the jth particle with i j " Then, the current density i j is expressed as the following equation (2), and the estimated current applied to the LiFePO positive electrode, i.e., the estimated battery current of the lithium iron phosphate battery, is defined as "I app "Then, the estimated battery current I app is expressed as the following formula (3). In formula (2), "F" is the Faraday constant, "k" is the reaction rate constant, and "c j " is the lithium ion concentration of the jth particle, and "c e " is the lithium ion concentration of the electrolyte (in this embodiment, a predetermined constant value), and "c max " is the maximum lithium concentration in the active material, "R" is the gas constant, "T" is the battery temperature (temperature of the battery cell), and the charge transfer coefficients of the anode and cathode reactions are 0.5. Also, "S" in equation (3) j " is the surface area of ​​the jth particle, and the particle radius of the jth particle is "r j ", then S j =4πr j 2 As a result, by utilizing the relationship between the lithium composition x and the OCV of the LiFePO positive electrode shown in Figure 2 and the multi-particle model, the estimated battery current I of a lithium iron phosphate battery taking into account the unique behavior of the LiFePO positive electrode, such as the memory effect, path dependency, and voltage hysteresis, can be calculated. app can be calculated.

[0020]

number

[0021] On the other hand, the overvoltage ΔV due to the reaction of the LiFePO positive electrode during charging and discharging of a lithium iron phosphate battery MPMis the voltage during charging and discharging of the lithium iron phosphate battery (battery cell) “V(t)”, the previous value of the OCV of the lithium iron phosphate battery is “OCV(t-1)”, and the salt concentration overvoltage of the electrolyte is “dV dce ", the current during charging and discharging of the lithium iron phosphate battery is "I(t)", and the internal resistance of the lithium iron phosphate battery is "Rd", then it can be expressed as in the following equation (4). In addition, for the voltage V(t) and current I(t) in equation (4), actual measured values ​​(measured values) can be used, and the salt concentration overvoltage dV dce can be calculated based on the following formula (5).

[0022]

number

[0023] Therefore, by obtaining the previous value OCV(t-1) of the OCV of the lithium iron phosphate battery, the overvoltage ΔV due to the reaction of the LiFePO positive electrode can be calculated from equation (4). MPM In addition, as described above, by utilizing the relationship between the lithium composition x and the OCV of the LiFePO positive electrode shown in FIG. 2 and the multi-particle model, the estimated battery current I app Based on this, in this embodiment, the reaction (polarization) of the LiFePO positive electrode is ignored with respect to the OCV of the LiFePO positive electrode, and as shown in FIG. 3(a), the OCV of the LiFePO positive electrode is calculated to be the average voltage V AVE (constant value). In this embodiment, the average voltage V AVE A first map that defines the relationship between SOC and OCV of the lithium iron phosphate battery as shown in FIG. 3(c) is prepared by subtracting the OCV of the negative electrode of the lithium iron phosphate battery (see FIG. 3(b)) from the SOC, and the previous value OCV(t-1) of the OCV of the lithium iron phosphate battery is obtained from the first map.

[0024] In this embodiment, the total number N of particles in the multi-particle model is, for example, 200 to 2000, the average size of the particle radius is, for example, 100 nm, and the particle radius is distributed in a log-normal distribution with a standard deviation of, for example, 80 nm. In addition, in the multi-particle model, the center of gravity of a plurality of particles forming the LiFePO positive electrode corresponds to the SOC of the lithium iron phosphate ion battery, and the relationship between the SOC according to the center of gravity of the plurality of particles and the OCV of the LiFePO positive electrode also has the same characteristics as those shown in Figure 2, and the voltage difference between the two spinodal points is about 20 mV, and the average voltage of the two spinodal points is about 3.43 V. Furthermore, in the multi-particle model, since there can be a plurality of particle distribution states for each SOC, the OCV of the positive electrode has a width of about 20 mV in the high SOC region and the low SOC region. Therefore, even in the multi-particle model, the rate of change in OCV of the LiFePO positive electrode relative to the change in SOC of the lithium iron phosphate ion battery is very small in a wide range other than the high SOC and low SOC ranges, making it difficult to accurately estimate the SOC of the lithium iron phosphate ion battery from the relationship between SOC and OCV.

[0025] Next, a procedure for estimating the SOC of each battery cell 2 included in the battery 1 will be described in detail with reference to Figures 4 and 5. Figure 4 is a flowchart showing an example of an SOC estimation routine executed by an electronic control unit 10 (hereinafter referred to as "ECU 10") mounted on the vehicle V to manage the battery 1. The SOC estimation routine in Figure 4 is repeatedly executed by the ECU 10, for example, every 10-100 ms while the system of the vehicle V is activated.

[0026] 4, the ECU 10 first sets a variable m, i.e., the number of the battery cells 2 included in the battery 1, to a value of 1 (step S100). The ECU 10 also sets the voltage of the m-th battery cell 2 (hereinafter, referred to as "battery cell 2") measured by a voltage sensor (not shown). m The current (current) measurement value V(t) of the voltage (terminal voltage) of the battery cell 2 measured by a current sensor (not shown) is mThe current (current) measurement value I(t), salt concentration overvoltage dV dce , battery cell 2 m Previous OCV value OCV(t-1), battery cell 2 m The previous value C of the lithium concentration of each particle when the LiFePO positive electrode is assumed to be composed of multiple particles j (t-1), battery cell 2 detected by a temperature sensor (not shown) m The temperature T of the battery cell 2 m The information required to estimate the SOC of the salt concentration overvoltage dV dce is calculated separately based on the above formula (5), and m The previous value of the OCV, OCV(t-1), and the previous value of the lithium concentration of each particle, C j (t-1) was calculated the previous time the SOC estimation routine was run.

[0027] Next, the ECU 10 calculates the measured voltage and current values ​​V(t), I(t) and the salt concentration overvoltage dV dce Overvoltage ΔV due to the reaction of the LiFePO positive electrode MPM (Step S120). In addition, the ECU 10 calculates the overvoltage ΔV MPM and the previous lithium concentration value C obtained in step S110. j Using the second map shown in FIG. 5, the overvoltage η j In step S130, the ECU 10 calculates the previous value C j Based on (t-1), the lithium composition of each particle x j (=C j (t-1) / C max ) and then calculate the lithium composition x from the second map. j The second map shown in FIG. 5 shows the relationship between the lithium composition x of the lithium iron phosphate (LixFePO4) shown in FIG. 2 and the OCV of the LiFePO positive electrode, as an average voltage V AVEIn other words, the reference voltage obtained from the second map is the previous value C j Lithium composition x based on (t-1) j OCV compatible with j to average voltage V AVE Furthermore, in step S130, the ECU 10 subtracts the obtained reference voltage from the overvoltage ΔV MPM By subtracting from the overvoltage η of each of the particles in the multi-particle model, j Calculate.

[0028] After the process of step S130, the ECU 10 calculates the overvoltage η j and the previous value of lithium concentration C j Based on (t-1) and temperature T, the current density i of each of the multiple particles in the multi-particle model is j (Step S140). Furthermore, the ECU 10 calculates the current density i j Based on the surface area Sj of each particle, the battery cell 2 m Estimated battery current I app (step S150). Then, the ECU 10 calculates the calculated estimated battery current I app The value calculated by dividing by the battery capacity C is the SOC of battery cell 2 calculated in the previous execution of the SOC estimation routine. m By adding the previous SOC(t-1), which is the SOC of battery cell 2, m Then, the current SOC value SOC(t) is calculated (step S160).

[0029] In addition, the ECU 10 determines the battery cell 2 from the first map shown in FIG. m The current SOC value SOC(t) of battery cell 2 m In step S170, the ECU 10 obtains the current value OCV(t) of the OCV of the current density i j The change in lithium concentration of each particle based on ∂C j / ∂t is calculated, and the calculated change amount ∂C j / ∂t is the previous lithium concentration C calculated in the previous run of the SOC estimation routine. j (t-1) to obtain the current value of the lithium concentration of each particle, C j (t) is calculated (step S180). j " is the volume of the jth particle (=4 / 3 π r j 3 ) The battery cell 2 calculated in step S170 m The current OCV value OCV(t) is used as the previous OCV value OCV(t-1) the next time the SOC estimation routine is executed, and the current lithium concentration value C j (t) is the previous value of the lithium concentration C when the SOC estimation routine is next executed. j It is used as (t-1).

[0030]

number

[0031] In step S180, the current value C of the lithium concentration of each particle j After calculating (t), the ECU 10 increments the variable m (step S190), and determines whether or not the variable m exceeds the total number M of the battery cells 2 in the battery 1 (step S200). If the ECU 10 determines that the variable m is equal to or smaller than the total number M (step S200: NO), it executes the processes of steps S110-S190 again. If the ECU 10 determines that the variable m exceeds the total number M (step S200: YES), it temporarily ends the routine of FIG. 4 at that point.

[0032] As described above, when estimating the SOC of each battery cell 2 of the battery 1, which is a lithium iron phosphate ion battery, a multi-particle model is used, which assumes that the LiFePO positive electrode formed of lithium iron phosphate (LiFePO4) is composed of multiple particles containing lithium. In addition, when estimating the SOC of each battery cell 2, at least the battery cell 2 m The measured voltage V(t) of the lithium iron phosphate battery (cell 2) m The SOC and OCV of the battery cell 2 are obtained from a first map that is predefined to define the relationship between the SOC and OCV of the battery cell 2. m Based on the previous OCV value OCV(t-1), the overvoltage ΔV due to the reaction of the LiFePO positive electrode MPM is calculated (step S120). Furthermore, the overvoltage ΔV due to the reaction of the LiFePO positive electrode is calculated. MPM 5, which is determined in advance based on the relationship between the lithium composition x of lithium iron phosphate (LixFePO4) shown in FIG. 2 and the OCV of the LiFePO positive electrode, the overvoltage η j is calculated (step S130). Then, the overvoltage η j From the current density i of each of the particles, j is calculated (step S140), and the current density i j From battery cell 2 m Estimated battery current I app is calculated (step S150).

[0033] More specifically, battery cell 2 m The overvoltage ΔV due to the reaction of the positive electrode is calculated by subtracting the previous OCV value OCV(t-1) corresponding to the previous SOC value SOC(t-1) obtained from at least the first map from the measured voltage V(t). MPM is calculated (step S120). In addition, the overvoltage ΔV due to the reaction of the positive electrode MPM and the reference voltage of each of the plurality of particles obtained from the second map, the overvoltage η j is calculated (step S130). Furthermore, the previous SOC value SOC(t-1) and the estimated battery current Iapp From the battery capacity C and battery cell 2 m A current value SOC(t) of the SOC is calculated (estimated) (steps S140-S160), and a current value OCV(t) of the OCV corresponding to the current value SOC(t) is obtained from the first map (step S170).

[0034] As a result, the battery cell 2 obtained from the first map m The estimated battery current I is calculated to offset the difference between the previous OCV value OCV(t-1) and the actual value. app Based on battery cell 2 m In other words, if the previous value OCV(t-1) obtained from the first map is smaller than the actual OCV, the overvoltage ΔV calculated in step S120 is MPM As the estimated battery current I app is calculated to be large so as to offset the deviation of the OCV, and if the previous value OCV(t-1) obtained from the first map is larger than the actual OCV, the overvoltage ΔV calculated in step S120 MPM The estimated battery current I app is calculated to be small so as to offset the OCV deviation. m By repeatedly estimating the SOC, the estimated SOC value, i.e., the current SOC(t), can be converged to the actual value. As a result, it is possible to accurately estimate the SOC of each battery cell 2 including a LiFePO positive electrode formed of lithium iron phosphate (LiFePO4), which exhibits peculiar behaviors such as memory effect, path dependency, and voltage hysteresis.

[0035] Further, in the above embodiment, the first map is a graph showing the average voltage V of the two spinodal points of the LiFePO positive electrode for each SOC. AVE The first map was created by subtracting the OCV of the negative electrode of the lithium iron phosphate battery from the average voltage V AVE This is created by offsetting the positive electrode reaction voltage ΔVMPM and the second map to calculate the overvoltage η j It is possible to more appropriately calculate

[0036] In the above embodiment, the current density i j The change in lithium concentration of each particle based on ∂C j / ∂t is calculated, and the previous value of the lithium concentration C j (t-1) and the change ∂C j / ∂t and the current value of lithium concentration C j (t) is calculated (step S180), and in step S130 of FIG. 4, the previous value C j Lithium composition x based on (t-1) j Thus, the reference voltages of the particles, and hence the overvoltage η j It is possible to more appropriately calculate

[0037] Furthermore, in step S120 of FIG. m From the measured voltage V(t), the previous OCV value OCV(t-1) and the salt concentration overvoltage dV dce and battery cell 2 m The product of the measured current I(t) and the internal resistance Rd is subtracted to obtain the overvoltage ΔV due to the reaction of the LiFePO positive electrode. MPM This reduces the computational load while minimizing the overvoltage ΔV due to the reaction at the positive electrode. MPM However, in step S120 of FIG. 2, m Without using the measured current I(t) of battery cell 2, m From the measured voltage V(t), the previous OCV value OCV(t-1) and the salt concentration overvoltage dV dce The overvoltage due to the reaction at the positive electrode is calculated by subtracting MPM and the overvoltage due to internal resistance Rd, ΔV MPM+IR may be calculated. In this case, |ΔV MPM+IR -(ΔV MPM +I app ·Rd)| minimizing the overvoltage ΔVMPM and the estimated battery current I app may be derived by iteration.

[0038] The battery 1 including a plurality of battery cells 2 that are lithium iron phosphate batteries is not limited to being a high-voltage battery that exchanges power with the motor generator MG. In other words, the battery 1 may be configured as a low-voltage battery such as an auxiliary battery (12V battery).

[0039] In addition, the invention of the present disclosure is not limited to the above embodiment, and various modifications can be made within the scope of the present disclosure. Furthermore, the above embodiment is merely a specific form of the invention described in the Summary of the Invention, and does not limit the elements of the invention described in the Summary of the Invention. [Industrial Applicability]

[0040] The present disclosure is applicable to fields such as the production of lithium iron phosphate batteries. [Explanation of symbols]

[0041] 1 battery, 2 battery cells, 10 electronic control units (ECUs), MG motor generators, V vehicle.

Claims

[Claim 1] 1. A method for estimating an SOC of a lithium iron phosphate ion battery including a positive electrode formed of lithium iron phosphate, comprising: calculating an overvoltage caused by a reaction of the positive electrode based on at least a measured value of the voltage of the lithium iron phosphate battery and an OCV obtained from a first map that is predetermined to define a relationship between an SOC and an OCV of the lithium iron phosphate battery; calculating an overvoltage of each particle on the assumption that the positive electrode is composed of a plurality of particles each containing lithium, using an overvoltage due to a reaction of the positive electrode and a second map that is predetermined based on a relationship between the lithium composition of the lithium iron phosphate and an OCV of the positive electrode; Calculating a current density of each of the particles based on the overpotential of each of the particles; Calculating an estimated battery current of the lithium iron phosphate battery based on the current density of each of the particles; An SOC estimation method for estimating an SOC of the lithium iron phosphate battery based on the estimated battery current.

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