Patent Description:
As a method of inspecting the internal state of a secondary battery, an AC impedance analysis method based on a frequency response analysis (FRA) method is well known, and a method of applying an equivalent circuit model to decompose the secondary battery into time-constant elements in order to interpret various internal reactions of the secondary battery is established.

Patent Literature <NUM> discloses an internal impedance diagnostic system for estimating cell impedance parameters from an impedance equivalent circuit model including the application or detection of a time-varying current signal through a cell, measurement of voltage and current variations, application of an adaptive filter on the sampled data to identify the m-order transfer function for the measured system, constructing a set of simultaneous equations, extracting individual impedance parameter values from the equations, running diagnostic tests and algorithms to analyze the change in cell impedance values and computing accurate cell related estimation parameters and conditions.

However, multipoint measurements from a high frequency range of about <NUM> up to a low frequency range of about <NUM> to <NUM> are required for the AC impedance analysis. Therefore, the inspection of the secondary battery takes a long time. Further, since a dedicated measuring device is required, it is difficult to put the method into practical use in such a scene that a short takt time is prerequisite such as a mass production line. Although an inspection machine having a certain degree of accuracy in a short time is required upon mass production shipment inspection of secondary batteries and product acceptance inspection, since the characteristics of each battery is changing depending on the operating state of the battery (such as voltage (SOC), operating current, and battery temperature), inspection must be performed by setting constant conditions. Therefore, an inspection device with good reproducibility is desired. Although pass/fail determination criteria are set from a statistical population distribution in the mass production line or the like, such settings are possible only when the inspection conditions are fixed, and there were hardly any methods of being able to determine pass/fail of a secondary battery on the market.

Therefore, the object of the present invention is to provide a secondary battery inspection device or the like capable of improving inspection accuracy while simplifying the inspection of a secondary battery.

The secondary battery inspection device and the secondary battery inspection method according to the present invention are defined in the appended claims.

A secondary battery inspection device <NUM> as one embodiment of the present invention illustrated in <FIG> is composed of a processor (arithmetic processing unit), a memory (storage device), an I/O circuit, and the like. In the memory or a storage device separate from this memory, a program (software) is stored and held in addition to various data such as parameters for defining a secondary battery model. For example, each of plural identifiers for identifying a secondary battery or the type of a target machine element (identified by the standard and specifications) in which this secondary battery is installed, and each of plural secondary battery models are stored and held in the memory in association with each other. The processor reads necessary program and data from the memory, and executes arithmetic processing according to the program based on the data to execute arithmetic processing or a task to be described later.

The secondary battery inspection device <NUM> includes an OCV detection element <NUM>, a subtraction element <NUM>, a temperature compensation element <NUM>, a first sampling period output element <NUM>, a first model parameter setting element <NUM>, a first voltage estimation element <NUM>, a first division element <NUM>, a second sampling period output element <NUM>, a second model parameter setting element <NUM>, a second voltage estimation element <NUM>, a second division element <NUM>, a first evaluation element <NUM>, a second evaluation element <NUM>, and a third evaluation element <NUM>.

Each of the secondary battery models is a model representing voltage V(t) output from a secondary battery <NUM> when current I(t) is input to the secondary battery <NUM>. The voltage V(t) is defined by equation (<NUM>) using an open circuit voltage OCV of the secondary battery <NUM> and a transfer function H(t) of the internal resistance.

The transfer function H(t) of an equivalent circuit model of the internal resistance of the secondary battery is defined by equation (<NUM>). <NUM>] <MAT>.

"H<NUM>(t)," "Hi(t)," "HW(t)," and "HL(t)" are defined by parameters representing the characteristics of the internal resistance of the secondary battery.

In <FIG>, an example of an equivalent circuit of the internal resistance of the secondary battery <NUM> is illustrated. In this example, the equivalent circuit of the internal resistance is defined by a series circuit of a connection resistance component R<NUM>, the i-th RC parallel circuit (i = <NUM>, <NUM>,. , m) composed of charge transfer resistances Ri and capacitors Ci, a Warburg impedance W<NUM>, and a coil L. In <FIG>, the number, m, of RC parallel circuits connected in series is "<NUM>. " As illustrated in <FIG>, the number, m, of RC parallel circuits connected in series may be smaller than <NUM>, or may be larger than <NUM>. As illustrated in <FIG>, respectively, the Warburg impedance W<NUM> may also be connected in series with a resistance R in at least any one of RC parallel circuits (for example, in the first RC parallel circuit). Further, each capacitor C may be replaced with a CPE (Constant Phase Element). In addition, the coil L may be omitted.

The transfer function H<NUM>(z) of the resistance R<NUM> is defined by equation (<NUM>). In <FIG>, a block diagram representing the transfer function H<NUM>(z) of the resistance R<NUM> is illustrated.

The dependency of R<NUM> on temperature θ is predetermined according to the equation (<NUM>) based on the measurement results of Nyquist plots of a reference secondary battery at different temperatures θ (see <FIG>), respectively. In other words, the coefficient R<NUM> is defined as a dependent variable or a function when the temperature θ for defining the transfer function H<NUM>(z) of the resistance R<NUM> is taken as the main variable.

The transfer function Hi(z) of the i-th RC parallel circuit is defined by equation (<NUM>) as an IIR (Infinite Impulse Response) system. In <FIG>, a block diagram representing the transfer function Hi(z) of the i-th RC parallel circuit is illustrated.

A transfer function Hi(s) of the i-th RC parallel circuit in an s region is expressed by equation (<NUM>).

When the transfer function Hi(s) is bilinear-transformed (s → (<NUM>/T)(<NUM>-z-<NUM>)/(<NUM> + z-<NUM>) (where T is a sampling period)), the transfer function Hi(z) of the i-th RC parallel circuit in a z region is expressed by equation (<NUM>).

From a comparison between the equations (<NUM>) and (<NUM>), each of coefficients b<NUM>, bi, and ai in the IIR transfer function is defined by each of equations (<NUM>) to (<NUM>), respectively. <MAT><MAT><MAT>.

The dependencies of Ri and Ci on temperature θ are predetermined according to the equation (<NUM>) based on the measurement results of Nyquist plots of the secondary battery at different temperatures θ (see <FIG>), respectively. In other words, each of the coefficients b<NUM>, bi, and ai that define the transfer function Hi(z) of the i-th RC parallel circuit is defined as a dependent variable or a multivariable function when the temperature θ and sampling frequency T are taken as main variables.

The transfer function HL(z) of the coil L is defined by equation (<NUM>) as the transfer function of the IIR system. In <FIG>, a block diagram representing the transfer function HL(z) of the coil L is illustrated.

A transfer function HL(s) of the coil L in the s region is expressed by equation (<NUM>).

When the transfer function HL(s) is bilinear-transformed, the transfer function HL(z) of the coil L in the z region is represented by equation (<NUM>).

From a comparison between the equations (<NUM>) and (<NUM>), each of the coefficients b<NUM>, bi, and ai in the IIR transfer function is defined by each of equations (<NUM>) to (<NUM>), respectively. <MAT><MAT><MAT>.

The dependence of L<NUM> on temperature θ is predetermined according to the equation (<NUM>) based on the measurement results of Nyquist plots of the reference secondary battery at each of different temperatures θ (see <FIG>), respectively. In other words, each of the coefficients b<NUM> and bi that define the transfer function Hi(z) of the coil L is defined as a dependent variable or a multivariable function when the temperature θ and sampling frequency T are taken as main variables.

The transfer function HW(z) of the Warburg impedance W<NUM> is defined by equation (<NUM>) as a transfer function of a FIR (Finite Impulse Response) system. In <FIG>, a block diagram representing the transfer function HW(z) of the Warburg impedance W<NUM> is illustrated. <NUM>] <MAT>.

A transfer function HW(s) of the Warburg impedance W<NUM> in the s region is represented by equation (<NUM>).

When the transfer function HL(s) is bilinear-transformed, the transfer function HW(z) of the Warburg impedance W<NUM> in the z region is represented by equation (<NUM>).

Thus, from a comparison between the equations (<NUM>) and (<NUM>), it is found to be difficult to determine each of the coefficient hk in the FIR transfer function, respectively. Therefore, the dependencies of RW, TW, and p on temperature θ are determined according to the equation (<NUM>) based on the measurement results of Nyquist plots of the reference secondary battery at each of different temperatures θ (see <FIG>), respectively. Then, the equation (<NUM>) is subjected to inverse-FFT transform to be extracted as the coefficients of delay elements zk (k = <NUM> to n, where n is, for example, about several tens to <NUM>) in order to approximately define the transfer function HW(z) of the Warburg impedance W<NUM> as an FIR transfer function as in equation (<NUM>). This is derived from the fact that the influence of the Warburg impedance W<NUM> is reflected on a low frequency side in the Nyquist plots. In other words, each of the coefficients hk that define the transfer function HW(z) of the Warburg impedance W<NUM> is defined as a dependent variable or a multivariable function when the temperature θ and sampling frequency T are taken as main variables.

In <FIG>, an example of Nyquist plots representing the measurement results of a complex impedance Z of the secondary battery <NUM> is illustrated together with an approximate curve of the plots. The horizontal axis is the real part ReZ of the complex impedance Z, and the vertical axis is the imaginary part -ImZ of the complex impedance Z. In a region of -ImZ > <NUM>, lower frequency complex impedance Z is represented as ReZ increases.

A value of ReZ when -ImZ = <NUM> (<FIG> (first evaluation section)) corresponds to the connection resistance component R<NUM> of the secondary battery <NUM> (see <FIG>). A section in a region of -ImZ < <NUM> (first evaluation section) surrounded by the dot-and-dash line in <FIG> corresponds to the impedance of wiring inductance L<NUM> of the electrodes and the like of the secondary battery <NUM> (see <FIG>). A crushed semicircular shaped section in a region of -ImZ > <NUM> (second evaluation section) surrounded by the long dashed double-dotted line in <FIG> corresponds to reaction resistance and electric double layer (impedance of the first to the m-th RC parallel circuits) at the electrode interface of the secondary battery <NUM> (see <FIG>). The radius tends to be smaller as the temperature T of the secondary battery <NUM> increases. The influence of the Warburg impedance W<NUM> of the secondary battery <NUM> is reflected in an approximately linear section standing up at about <NUM>° in a low frequency range in a region of ImZ > <NUM> (third evaluation section) surrounded by the dashed line in <FIG> (see <FIG>).

The approximate curve of the complex impedance Z of the secondary battery, which is represented by solid Nyquist plots in <FIG> is determined under the assumption that the transfer function H(t) of the equivalent circuit model of the internal resistance of the secondary battery is defined according to the equation (<NUM>). Thus, values of parameters R<NUM> (see the equation (<NUM>)), Ri and Ci (see the equation (<NUM>)), L<NUM> (see the equation (<NUM>)), RW, TW, and p (see the equation (<NUM>)) are determined at each temperature θ. The value of the open circuit voltage OCV in each secondary battery model is identified by the measured value of the open circuit voltage OCV (see the equation (<NUM>)). Then, secondary battery models are established by the parameter values for various types of secondary batteries <NUM>.

An inspection method of the secondary battery <NUM> executed by the secondary battery inspection device <NUM> having the configuration mentioned above will be described.

The impulse current I(t), the voltage V(t), and the temperature θ(t) of the secondary battery <NUM> are measured by a current sensor S1, a voltage sensor S2, and a temperature sensor S0, respectively, when the impulse current I(t) is applied by a charge/discharge device <NUM> to the secondary battery <NUM> to be inspected. the measurement result of the temperature θ(t) of the secondary battery <NUM> is input to the temperature compensation element <NUM>, and a temperature compensation model parameter according to the measurement result is output from the temperature compensation element <NUM>. Specifically, values R<NUM>(θ), Ri(θ), Ci(θ), L<NUM>(θ), RW(θ), TW(θ), and p(θ) of the parameters R<NUM> (see the equation (<NUM>)), Ri and Ci (see the equation (<NUM>)), L<NUM> (see the equation (<NUM>)), and RW and TW (see the equation (<NUM>)) according to the temperature θ are determined. These model parameters can be determined as average values of a good product population from mass-produced products of secondary batteries, and used as a reference model for pass/fail determination.

The temperature compensation model parameter is input from the temperature compensation element <NUM> to the first model parameter setting element <NUM>, and the IIR model parameters b<NUM>(θ, T<NUM>), bi(θ, T<NUM>), and ai(θ, T<NUM>) are determined by the first model parameter setting element <NUM> based on the temperature compensation model parameters Ri(θ) and Ci(θ) according to the first sampling period T<NUM> (see the equations (<NUM>) to (<NUM>)). The IIR model parameters b<NUM>(θ, T<NUM>), bi(θ, T<NUM>), and ai(θ, T<NUM>) are determined by the first model parameter setting element <NUM> based on the temperature compensation model parameter L<NUM>(θ) according to the first sampling period T<NUM> (see the equations (<NUM>) to (<NUM>)). The FIR model parameter hk(θ, T<NUM>) is determined by the first model parameter setting element <NUM> based on the temperature compensation model parameters RW(θ, T<NUM>), TW(θ, T<NUM>), and p(θ, T<NUM>) according to the first sampling period T<NUM> (see the equation (<NUM>)).

The voltage V(t) of the secondary battery <NUM> is inferred by the first voltage estimation element <NUM> based on the measurement result of the impulse current I(t) of the secondary battery <NUM> according to the secondary battery model defined by the transfer function H(t) according to the first sampling period T<NUM> as a short period (for example, about <NUM>) (see the equation (<NUM>)). In <FIG>, the measured values of the voltage V of the secondary battery <NUM> at the time of discharge are illustrated by the dotted line, approximate curves representing the measured values of the OCV of the secondary battery <NUM> in each first sampling period T<NUM> are illustrated by the dashed line, and approximate curves representing the estimation results of the voltage V(t) of the secondary battery <NUM> in each first sampling period T<NUM> by the first voltage estimation element <NUM> are illustrated by the solid line, respectively. Since the open circuit voltage OCV is not considered in the secondary battery model, the estimation results D of the voltage V(t) of the secondary battery <NUM> in each first sampling period T<NUM> by the first voltage estimation element <NUM> is inferred based on the OCV (see <FIG>/down arrow D).

The temperature compensation model parameter is input from the temperature compensation element <NUM> to the second model parameter setting element <NUM>, and the IIR model parameters b<NUM>(θ, T<NUM>), bi(θ, T<NUM>), and ai(θ, T<NUM>) are determined by the second model parameter setting element <NUM> based on the temperature compensation model parameters Ri(θ) and Ci(θ) according to the second sampling period T<NUM> (see the equations (<NUM>) to (<NUM>)). The IIR model parameters b<NUM>(θ, T<NUM>), bi(θ, T<NUM>), and ai(θ, T<NUM>) are determined by the second model parameter setting element <NUM> based on the temperature compensation model parameter L<NUM>(θ) according to the second sampling period T<NUM> (see the equations (<NUM>) to (<NUM>)). The FIR model parameter hk(θ, T<NUM>) is determined by the second model parameter setting element <NUM> based on the temperature compensation model parameters RW(θ, T<NUM>), TW(θ, T<NUM>), and p(θ, T<NUM>) according to the second sampling period T<NUM> (see the equation (<NUM>)).

The voltage V(t) of the secondary battery <NUM> is inferred by the second voltage estimation element <NUM> based on the measurement result of the impulse current I(t) of the secondary battery <NUM> according to the secondary battery model defined by the transfer function H(t) according to the second sampling period T<NUM> as a long period (for example, about <NUM>) (see the equation (<NUM>)). In <FIG>, the measured values of the voltage V of the secondary battery <NUM> at the time of discharge are illustrated by the solid line, an approximate curve representing the measured values of the OCV of the secondary battery <NUM> in each second sampling period T<NUM> is illustrated by the dashed line, and an approximate curve representing the estimation result of the voltage V(t) of the secondary battery <NUM> in each second sampling period T<NUM> by the second voltage estimation element <NUM> is illustrated by the solid line. Since the open circuit voltage OCV is not considered in the secondary battery model, the estimation result E of the voltage V(t) of the secondary battery <NUM> by the second voltage estimation element <NUM> is inferred based on the OCV (see <FIG>/down arrow E).

The voltage V(t) of the secondary battery <NUM> is input to the secondary battery inspection device <NUM>, and the open circuit voltage OCV(t) of the secondary battery <NUM> is detected by the OCV detection element <NUM> based on input A concerned. Then, a difference C = A - B of input A = V(t) and output B = OCV(t) of the OCV detection element <NUM> is output by the subtraction element <NUM>. The difference C is illustrated by the down arrow C in each of <FIG>, and <FIG>, which represents a difference between the measured value (solid line) of the voltage V of the secondary battery <NUM> at the time of discharge and the measured value dotted line) of the OCV.

The difference C is input from the subtraction element <NUM> to the division element <NUM>, and the estimation result D of the voltage V(t) of the secondary battery <NUM> is input from the first voltage estimation element <NUM> to calculate a ratio C/D of both inputs.

C/D at each point of time in a first period (see <FIG>/region surrounded by the dashed box) immediately after the impulse current I(t) starts flowing from the division element <NUM> is input to the first evaluation element <NUM>, and the connection resistance component R<NUM> and the inductance element L<NUM> of the secondary battery <NUM> in the first evaluation section is evaluated by the first evaluation element <NUM> based on a statistical index value, such as an average value of the input, a variance value, a deviation value, or an intermediate value of the maximum value and the minimum value. Here, since contribution by L<NUM> is only the impedance on the imaginary axis and there is no contribution as the resistance value, the component to be evaluated is only R<NUM> after all. The closer C/D to <NUM>, the smaller the change in the connection resistance component R<NUM> of the secondary battery <NUM> is evaluated compared with the initial state or the good product population.

C/D at each point of time in a second period (see <FIG>/region surrounded by the dashed box) longer than the first period and starting at the elapse of the first period after the impulse current I(t) starts flowing from the division element <NUM> is input to the second evaluation element <NUM>, and the reaction resistance and electric double layer (impedance of the first to the m-th RC parallel circuits) at the electrode interface of the secondary battery <NUM> in the second evaluation section are evaluated by the second evaluation element <NUM> based on the statistical index value of the input. The closer the C/D to <NUM>, the smaller the change in the reaction resistance and electric double layer (impedance of the first to the m-th RC parallel circuits) at the electrode interface of the secondary battery <NUM> is evaluated compared with the initial state or the good product population. A tolerance level can be set to the calculated value of C/D for pass/fail determination.

The difference C is input from the subtraction element <NUM> to the division element <NUM>, and the estimation result E of the voltage V(t) of the secondary battery <NUM> is input from the second voltage estimation element <NUM> to calculate a ratio of C/E of both inputs.

C/E at each point of time in a third period (see <FIG>/region surrounded by the dashed box) longer than the second period and starting at the elapse of the first period after the impulse current I(t) starts flowing from the division element <NUM> is input to the third evaluation element <NUM>, and the Warburg impedance W<NUM> of the secondary battery <NUM> in the third evaluation section is evaluated by the third evaluation element <NUM> based on the statistical index value of the input. The closer C/E to <NUM>, the smaller the change in the Warburg impedance W<NUM> of the secondary battery <NUM> is evaluated compared with the initial state or the good product population. A tolerance level can be set to the calculated value of C/E for pass/fail determination.

The evaluation results of the first evaluation element <NUM>, the second evaluation element <NUM>, and the third evaluation element <NUM> are output to an output interface wired or wirelessly connected to the secondary battery inspection device <NUM>.

Each of the first evaluation element <NUM>, the second evaluation element <NUM>, and the third evaluation element <NUM> can make the determination with one measurement to estimate which component of the secondary battery is the cause of a failure depending on the combination of the determination results.

According to the secondary battery inspection device <NUM> of the present invention and the secondary battery inspection method executed thereby, for example, as illustrated in Table <NUM>, when the determination result of C/D related to the first evaluation section has a relation to a first determination reference value γ1 as expressed in equation (<NUM>), it is evaluated to be "OK (the resistance value of the cell constituent material is within a reference range)," while when the determination result of C/D does not have the relation expressed in the equation (<NUM>), it is evaluated to be "NG (the resistance value of the cell constituent material exceeds the reference).

Further, as illustrated in Table <NUM>, when the determination result of C/D related to the second evaluation section has a relation to a second determination reference value γ2 as expressed in equation (<NUM>), it is evaluated to be "OK (there is no abnormality in reactivity between the positive electrode and the negative electrode)," while when the determination result of C/D does not have the relation expressed in the equation (<NUM>), it is evaluated to be "NG (there is abnormality in reactivity between the positive electrode and the negative electrode).

Further, as illustrated in Table <NUM>, when the determination result of C/E related to the third evaluation section has a relation to a third determination reference value γ3 as expressed in equation (<NUM>), it is evaluated to be "OK (there is no shortage of electrolyte, no deterioration of the electrolyte, or the like)," while when the determination result of C/E does not have the relation expressed in the equation (<NUM>), it is evaluated to be "NG (there is a shortage of electrolyte, a deterioration of the electrolyte, or the like).

Thus, according to the present invention, not only can the pass/fail determination of the secondary battery be simply made but also it can be estimated which of components of the secondary battery causes a problem by one measurement.

The evaluation results may be transmitted from the secondary battery inspection device <NUM> to a client such as a smartphone, a tablet terminal, or a personal computer, and output to and displayed on an output interface (display) that constitutes part of the client. Thus, since a defect factor can also be estimated while facilitating the inspection of the secondary battery <NUM>, not only can the inspection accuracy be improved, but also a user of the client who engages in the production process can get smooth feedback.

Claim 1:
A secondary battery inspection device comprising:
a voltage recognition element configured to recognize a measurement result of voltage of a secondary battery when an impulse current flows into the secondary battery;
a model parameter setting element configured to identify, based on a sampling period, a value of a model parameter of a secondary battery model in which impedance of internal resistance of the secondary battery is expressed by transfer functions respectively representing an IIR system and an FIR system;
a voltage estimation element which, when the impulse current is input to a specified model as the secondary battery model the value of the model parameter of which is identified by the model parameter setting element, is configured to estimate a model output voltage as a voltage change form output from the specified model; and
an evaluation element which is configured to evaluate based on a ratio (C/D) which is a ratio of a difference (C) between a measured value of the voltage of the secondary battery recognized by the voltage recognition element with respect to an estimation result (D) estimated by the voltage estimation element in each first sampling period as a short period, whether or not a resistance value of a cell constituent material of the secondary battery according to the first sampling period is within a reference range, whether or not a reactivity of a positive electrode or a negative electrode is abnormal, and to evaluate, based on a ratio (C/E) which is a ratio of the difference (C) between the measured value of the voltage of the secondary battery recognized by the voltage recognition element with respect to an estimation result (E) estimated by the voltage estimation element in each second sampling period as a long period, whether or not there is a shortage or a deterioration of an electrolytic solution of the secondary battery according to the second sampling period.