WO2016067586A1

WO2016067586A1 - Battery parameter estimation device

Info

Publication number: WO2016067586A1
Application number: PCT/JP2015/005364
Authority: WO
Inventors: 厚志馬場; 修一足立
Original assignee: カルソニックカンセイ株式会社; 学校法人慶應義塾
Priority date: 2014-10-31
Filing date: 2015-10-26
Publication date: 2016-05-06
Also published as: JP6450565B2; JP2016090322A

Abstract

A battery parameter estimation device is provided that is capable of handling hysteresis without increasing the hysteresis elements of an equivalent circuit of a battery. A battery parameter estimation device for successively estimating parameters including the resistance or capacity of an equivalent circuit model (41) of a battery (1) on the basis of at least one from among the battery voltage and the battery current is characterized in that the equivalent circuit model of the battery is formed using the resistance associated with the maximum voltage drop range and input current characteristic in a hysteresis model expressing the hysteresis generated with the characteristic of the battery charge state and open-circuit voltage.

Description

Battery parameter estimation device

Cross-reference to related applications

This application claims the priority of Japanese Patent Application 2014-222959 (filed on October 31, 2014), the entire disclosure of which is incorporated herein by reference.

The present invention relates to a battery parameter estimation device capable of sequentially estimating parameters of a battery equivalent circuit model using a Kalman filter.

As a conventional battery internal state / parameter estimation device, for example, the one described in Patent Document 1 is known. This conventional battery parameter estimation device detects the charge / discharge current and terminal voltage of the battery, and uses them as inputs, the parameter and internal state quantity of the battery with a Kalman filter using an equivalent circuit model of the battery including resistance and capacity , Estimate (calculate) the open circuit voltage value.

The SOC-OCV characteristics of the battery can be represented in the above-described battery equivalent circuit model. However, in an actual battery, a hysteresis phenomenon may occur in which SOC-OCV characteristics differ between after charging and after discharging. In this case, the SOC-OCV characteristics of the battery can not be accurately represented. The hysteresis phenomenon is caused by the material of the electrode, and particularly when lithium phosphate is used, the influence of the hysteresis phenomenon is significant.

Here, a model is proposed in which a hysteresis element representing a voltage drop due to hysteresis is added to the equivalent circuit of the battery in order to handle the hysteresis phenomenon of the battery. For example, a battery internal state / parameter estimation device described in Patent Document 2 and Non-Patent Document 1-2 is known. Note that the hysteresis phenomenon of the battery means that, in the fluctuation of the state accompanying charging and discharging of the battery, the equilibrium state of the battery fluctuates due to the fluctuation history. In other words, a battery without hysteresis returns to the original equilibrium state by leaving it for a certain period of time regardless of the battery's charge / discharge history, but with a battery with hysteresis, it remains the original regardless of the battery's charge / discharge history. It may not return to equilibrium.

JP, 2014-74682, A Patent No. 4511600

Inherently, the hysteresis phenomenon of the battery appears as a result of the electrochemical reaction inside the battery, and is closely related to the charge transfer process inside the battery and the diffusion process of ions. However, in Patent Document 1 and Non-patent Document 1-2, independent reactions (dynamics) are handled separately from the resistance and capacity corresponding to the charge transfer process inside the battery and the diffusion process of ions as handling hysteresis of the open circuit voltage. Has been added. Therefore, the hysteresis element is added to the equivalent circuit of the battery. Also, this hysteresis element has a problem that it is not associated with the charge transfer process or the diffusion process of ions.

An object of the present invention made in view of such circumstances is to provide a battery parameter estimation device capable of handling hysteresis without increasing the hysteresis element in the equivalent circuit of the battery.

In order to solve the above-mentioned subject, a parameter estimation device of a battery concerning the 1st viewpoint is:
In a battery parameter estimation device for sequentially estimating a parameter including the resistance or the capacitance in an equivalent circuit model of the battery based on at least one of a battery voltage and a battery current.
In the hysteresis model representing the hysteresis generated in the characteristics of the battery state of charge and the open circuit voltage, it is characterized in that the equivalent circuit model of the battery is formed by the maximum range of voltage drop and the resistance related by the characteristics of input current. I assume.

In order to solve the above-mentioned subject, the parameter estimating device of the battery concerning the 2nd viewpoint is:
A battery parameter estimation device for a battery, wherein the equivalent circuit model of the battery is formed using the maximum range of the voltage drop in the hysteresis model and the capacitance related by the characteristics of the speed of voltage drop in the hysteresis model.

In order to solve the above-mentioned subject, the parameter estimating device of the battery concerning the 3rd viewpoint is:
Assuming that the maximum range of the voltage drop is M (t) and the input current is u (t), the resistance R _h (t) is

It is characterized by.

In order to solve the above-mentioned subject, a parameter estimation device of a battery concerning the 4th viewpoint is:
Assuming that the maximum range of the voltage drop is M (t) and the speed of the voltage drop is Γ (t), the capacitance C _h (t) is

It is characterized by.

In order to solve the above-mentioned subject, the parameter estimating device of the battery concerning the 5th viewpoint is:
The resistance R _h (t) is expressed by

It is characterized by.

In order to solve the above-mentioned subject, the parameter estimating device of the battery concerning a 6th viewpoint is:
The resistance R _h (t) is expressed by

It is characterized by.

According to the battery parameter estimation device pertaining to the first aspect, it is possible to handle hysteresis without increasing the hysteresis element in the equivalent circuit of the battery.

According to the battery parameter estimation device according to the second aspect, hysteresis can be handled without increasing the hysteresis element in the equivalent circuit of the battery.

According to the battery parameter estimation device pertaining to the third aspect, hysteresis can be handled without increasing the hysteresis element in the equivalent circuit of the battery.

According to the battery parameter estimation device pertaining to the fourth aspect, hysteresis can be handled without increasing the hysteresis element in the equivalent circuit of the battery.

According to the battery parameter estimating device relating to the fifth aspect, since the hysteresis can be accurately handled, it is possible to obtain an accurate estimated value more quickly.

According to the battery parameter estimating device relating to the sixth aspect, the model configuration is simple and the hysteresis phenomenon can be easily handled.

It is a figure which shows the functional block of the parameter estimation apparatus of the battery which connected to the battery concerning embodiment of this invention. It is a figure explaining the equivalent circuit model of a battery. It is a figure which shows the relationship between the open circuit voltage of a battery, and a charging rate. FIG. 7 is a diagram showing an n-order Foster RC ladder circuit which approximates a Warburg impedance. It is a figure which shows the n-order Cawell type RC ladder circuit which approximated the Warburg impedance. It is a graph which shows the measurement result of the SOC-OCV characteristic of lithium iron phosphate. It is an enlarged view of the broken-line enclosure part of FIG. 5A. It is a figure which shows the equivalent circuit of the hysteresis model by Plett. Is a diagram representing the RC parallel circuit constituted by a variable resistor R _h and the variable capacitor C _h. It is a figure showing RC parallel circuit corresponding to the hysteresis model which consists of charge transfer resistance Rct and electric double layer capacity Cdl which modeled a charge transfer process. It is a figure which models the diffusion process of ion and represents the Foster type | mold circuit corresponding to a hysteresis model.

Hereinafter, embodiments according to the present invention will be described in detail with reference to the drawings.

First Embodiment
The battery parameter estimation device of the first embodiment is used for a vehicle such as an electric vehicle or a hybrid electric vehicle. Such a vehicle is equipped with an electric motor for driving the vehicle, a battery, a controller thereof, etc., supply (discharge) of electric power to the electric motor, regeneration of braking energy from the electric motor at the time of braking, ground charging equipment Power recovery (charging) from the battery to When such charge and discharge current flows into and out of the battery, the internal state of the battery changes, and the internal state is monitored while being estimated by the parameter estimation device of the battery, so that the remaining amount of the battery, etc. It has collected the necessary information.

As shown in FIG. 1, the parameter estimation device of the battery 1 includes a voltage sensor (terminal voltage detection unit) 2, a current sensor (charge / discharge current detection unit) 3, an estimation unit 4, and a charge amount calculation unit 5. The charging rate calculating unit 6 and the soundness calculating unit 7 are provided. The estimation unit 4, the charge amount calculation unit 5, the charging rate calculation unit 6, and the soundness calculation unit 7 are configured by, for example, a vehicle-mounted microcomputer.

The battery 1 is, for example, a rechargeable battery (secondary battery). Although battery 1 is described as being a lithium ion battery in the present embodiment, other types of batteries may be used.

The terminal voltage detection unit 2 is, for example, a voltage sensor, and detects a terminal voltage value v of the battery 1. The terminal voltage detection unit 2 inputs the detected terminal voltage value v to the estimation unit 4.

The charge / discharge current detection unit 3 is, for example, a current sensor, and detects a charge / discharge current value i of the battery 1. The charge / discharge current detection unit 3 inputs the detected charge / discharge current value i to the estimation unit 4.

The estimation unit 4 includes a battery equivalent circuit model 41 of the battery 1 and a Kalman filter 42. The estimation unit 4 can estimate (calculate) the parameter value of the battery equivalent circuit model 41, the open circuit voltage OCV (Open Circuit Voltage) of the battery 1, and the internal state amount of the battery 1 using the Kalman filter 42. . In the present embodiment, estimation unit 4 simultaneously estimates and estimates the parameter value and the internal state quantity based on terminal voltage v from terminal voltage detection unit 2 and charge / discharge current i from charge / discharge current detection unit 3. The open circuit voltage OCV is calculated based on the determined parameter value. Details of the estimation / calculation processing performed by the estimation unit 4 will be described later. Further, the estimation unit 4 inputs the calculated open circuit voltage OCV to the charging rate calculation unit 6 and the soundness calculation unit 7.

In the battery equivalent circuit model 41, as described later, the Foster type RC ladder circuit represented by an approximation of the sum of infinite series, in which a parallel circuit of a resistor and a capacitor is connected, and the resistor connected in series are grounded by a capacitor It consists of a Kawell RC ladder circuit or the like represented by approximation by continuous fraction expansion. The resistor and the capacitor are parameters of the battery equivalent circuit model 41.

The Kalman filter 42 designs a model of the target system (in the case of this embodiment, the battery equivalent circuit model 41), inputs the same input signal to this model and the real system, and compares the outputs of that case. If there is an error in them, this error is multiplied by the Kalman gain and fed back to the model to correct the model so as to minimize both errors. By repeating this, the parameters of the model are estimated.

The charge amount calculation unit 5 receives the charge / discharge current value i of the battery 1 detected by the charge / discharge current detection unit 3 and sequentially integrates this value to obtain the charge amount in / out of the battery 1. The charge amount calculation unit 5 calculates the charge amount Q that the battery 1 currently has by subtracting the charge amount that has come in and out from the remaining charge amount stored before the successive integration operation. The charge amount Q is output to the soundness level calculation unit 7.

Since the relationship between the open-circuit voltage value and the charging ratio is unlikely to be affected by the temperature and the deterioration of the battery 1, the charging rate calculation unit 6 uses relationship data obtained by obtaining these relationships in advance by experiment etc. I remember. Then, based on this characteristic table, the state of charge SOC (State of Charge) at that time is estimated from the open circuit voltage estimation value estimated by the estimation unit 4. The charging rate SOC is used for battery management of the battery 1.

The health level calculation unit 7 has a characteristic table that represents the relationship between the charge amount Q and the open circuit voltage OCV for each of the health levels SOH (State of Health) divided into predetermined widths. The details of the characteristic table are disclosed, for example, in Japanese Patent Application Laid-Open No. 2012-57956 filed by the present applicant. The openness voltage OCV estimated by the estimation unit 4 and the charge amount Q calculated by the charge amount calculation unit 5 are input to the soundness calculation unit 7, and these fall within any soundness SOH range of the above characteristic table. Is calculated, and the applicable soundness level SOH is output.

Here, the equivalent circuit model 41 of the battery 1 will be described. Generally, the electrode reaction of a battery includes a charge transfer process at the interface between the electrolyte and the active material, and a diffusion process of ions in the electrolyte or the active material. For example, in a non-faradaic process battery such as a lithium ion battery, ie, a battery in which the diffusion phenomenon is dominant, the influence of the Warburg impedance which is an impedance resulting from the diffusion process becomes dominant.

First, as shown in FIG. 2, it is assumed that an open circuit having an open circuit voltage (open circuit voltage) OCV and in which an internal resistance R ₀ and a Warburg impedance Z _w are connected in series as a model of a battery.

The open circuit voltage OCV is a non-linear function of the charging rate SOC as shown in FIG. The charging rate SOC is expressed by equation (1) using a charge / discharge current value i and a full charge capacity FCC (Full Charge Capacity).

Further, the transfer function of the Warburg impedance Z _w is expressed by equation (2).

Where s is the Laplace operator, and the diffusion resistance R _d is the low frequency limit (ω → 0) of Z _w (s). Also, the diffusion time constant τ _d means the speed of the diffusion reaction. The diffusion capacitance C _d is defined by equation (3) using the diffusion resistance R _d and the diffusion time constant τ _d .

In Equation (2), it is difficult to convert the Warburg impedance Z _w into the time domain as it is because there is a square root of the Laplace operator s. For this reason, an approximation of the Warburg impedance Z _w is considered. The Warburg impedance Z _w can be approximated by, for example, a sum of infinite series, or an approximation by continued fraction expansion.

First, approximation by the sum of infinite series will be described. The Warburg impedance Z _w can be expressed as a sum of infinite series, as shown in equation (4).

However,

It is. If the above-mentioned approximate expression is expressed in a circuit diagram, it is an n-order Foster type circuit in which n parallel circuits of a resistor and a capacitor are connected in series (see FIG. 4A). As apparent from the equations (5) and (6), according to the n-order Foster-type equivalent circuit model approximating the Warburg impedance Z _w , the diffusion capacitance C _d and the diffusion resistance R _d are used to obtain an equivalent circuit. Other parameters (resistor R _n , capacitor C _n ) can be calculated.

Next, approximation by continuous fraction expansion will be described. The Warburg impedance Z _w can be represented by a continued fraction expansion as shown in equation (7).

However,

It is. If the above-mentioned approximate expression is expressed in a circuit diagram, it is an n-order Kawell type circuit in which each of n resistors R connected in parallel is connected between n capacitors C connected in series (see FIG. 4B). ). As apparent from the equations (8) and (9), according to the n-th order Kawell-type equivalent circuit model approximating the Warburg impedance Z _w , the diffusion capacitance C _d and the diffusion resistance R _d are used to generate the other circuit. Parameters (resistance R _n , capacitor C _n ) can be calculated.

Next, the process of the estimation unit 4 will be described. In the present embodiment, the estimation unit 4 simultaneously estimates the internal state quantity and the parameter value of the battery using the Kalman filter 42 in the battery equivalent circuit model 41 of either the Foster type or the Cawell type. Preferably, the internal state quantity of the battery includes the SOC of the battery, and the parameter value includes at least one of the diffusion capacitance C _d or the diffusion resistance R _d . In the present embodiment, an unscented Kalman filter (UKF: Unscented Kalman Filter) is used as the Kalman filter 42, but another filter may be used. UKF uses weighted sample points called sigma points to approximate the probability distribution and calculate each weighted transition. Specifically, the average value and variance after transition are calculated for each sigma point, and they are added according to the weight. By doing this, it is possible to approximate the probability distribution after the transition closer to the true value and without increasing the amount of calculation too much. Also, since the probability distribution is approximated by sigma points instead of approximating the system, there is no restriction on the nonlinearity of the system.

The SOC-OCV characteristics of the battery can be represented in the above-described battery equivalent circuit model. However, in an actual battery, a hysteresis phenomenon may occur in which the SOC-OCV characteristics differ between after charging and after discharging. In this case, the SOC-OCV characteristics of the battery can not be accurately represented. The hysteresis phenomenon is caused by the material of the electrode, and particularly when lithium phosphate is used, the influence of the hysteresis phenomenon is significant.

FIG. 5A shows the measurement results of the SOC-OCV characteristics of a lithium iron phosphate battery. According to FIG. 5A, it can be seen that there is a difference in OCV between the characteristics during charging and the characteristics during discharging. Moreover, in FIG. 5B which expanded the broken-line enclosure part of FIG. 5A, even if it is made to discharge at SOC about 30%, it turns out that a hysteresis characteristic is shown. The above-described battery equivalent circuit model can not accurately handle the SOC-OCV characteristics of the battery in which the hysteresis phenomenon occurs.

A hysteresis model by Plett, which is one of models representing such a hysteresis phenomenon, is represented by an equivalent circuit of FIG. Here, the element V _H is an element that represents a hysteresis voltage. This hysteresis model is expressed by the following equation (10).

Here, v _h (t) is the hysteresis voltage, Γ (t) is the voltage drop speed of the hysteresis model (corresponding to the slope of the SOC-OCV curve), and M (t) is the maximum range of the voltage drop of the hysteresis model u (t) is a parameter representing the input current.

Inherently, the hysteresis of a battery appears as a result of an electrochemical reaction inside the battery, and is closely related to the charge transfer process inside the battery and the diffusion process of ions. However, the hysteresis model by Plett expresses v _h (t) by adding a reaction independent of the charge transfer process and the diffusion process of ions. Therefore, when estimating the battery state based on the equation (10), it is necessary to estimate Γ (t) and M (t) representing the hysteresis voltage, in addition to the estimation of the resistance and capacity of the RC parallel circuit. That is, the parameters to be estimated are increased by two (Γ and M) as compared with the estimation of the battery model not considering the hysteresis.

Here, in the present embodiment, such independent reactions are integrated into a model corresponding to the charge transfer process and the ion diffusion process. In equation (10) representing the hysteresis model,

And put. At this time, the equation (10) representing the hysteresis model can be rewritten as the following equation (13).

This can be interpreted as being equivalent to the equation representing an RC parallel circuit configured by the variable resistor R _h and the variable capacitor C _h shown in FIG. In particular, as represented by the equation (11), it is characterized that the resistance of the model is a variable resistance which is variable according to the magnitude of the current.

A variable resistor and a variable capacitance hysteresis model of the first embodiment can be applied to the RC parallel circuit of the charge transfer resistance R _ct and the electric double layer capacity C _dl models the charge transfer process. The Plett hysteresis model is represented by an equivalent circuit in which a hysteresis element is added to the RC parallel circuit as shown in the left of FIG. On the other hand, if the hysteresis model of the present embodiment is used, it is represented by a parallel circuit of variable resistance and variable capacitance as shown in the right of FIG. In this equivalent circuit, the variable resistor R _{ct, h} (t) and the variable capacitance C _{dl, h} (t) are expressed as the following equations (14) and (15).

Here, M _ct (t) indicates the maximum range of the hysteresis voltage drop generated by the charge transfer process, and Γ _ct (t) is the speed of the hysteresis voltage drop generated by the charge transfer process (corresponding to the slope of the SOC-OCV characteristic) Indicates As described above, if the hysteresis model of the present modification is used, hysteresis can be handled without increasing the hysteresis element in the equivalent circuit of the battery. Therefore, the hysteresis phenomenon can be handled by estimating the same number of parameters (resistance and capacity) as the battery model estimation that does not consider hysteresis. In addition, since it is possible to obtain the parameter by integrating the hysteresis phenomenon into the resistance and capacity of the battery model which does not consider the hysteresis within the time constant matched to the charge transfer process and the diffusion process of ions, accuracy improves. . Further, according to the model in which the denominator of the equation representing the variable resistance R _h is the absolute value | u (t) | of the input current u (t) as in the equation (14), the model configuration is simple and easily It can handle hysteresis phenomena.

Further, the variable resistance and the variable capacitance of the hysteresis model of the first embodiment can be applied to the Foster type circuit representing the diffusion process of ions. The Plett hysteresis model is represented by an equivalent circuit in which a hysteresis element is added to the n-order Foster type circuit as shown in FIG. On the other hand, if the hysteresis model of this embodiment is used, the hysteresis model can be represented by an equivalent circuit in which an n-order Foster circuit as shown in the lower part of FIG. 9 is configured by a variable resistor and a variable capacitor. Here, the circuit parameters of the Foster type circuit (FIG. 9 upper) before applying the variable resistor and the variable capacitance are

The circuit parameters of the Foster type circuit (FIG. 9 bottom) after application of variable resistance and variable capacitance are

It is. That is, instead of estimating the diffusion resistance R _d and diffusion capacitance C _d, the variable resistor R _{d, h} and the variable capacitance C _d, may be estimated _h incorporating a hysteresis phenomenon.

The variable resistance and variable capacitance of the hysteresis model of the first embodiment can also be applied to a Kawell-type circuit that represents the diffusion process of ions. In this case, as in the case of applying to the Foster type circuit, the circuit parameters may be replaced with the values of the variable resistor and the variable capacitance. As described above, according to the battery parameter estimation device according to the first embodiment, regardless of the type of the battery equivalent circuit, the resistance and the capacitance of the equivalent circuit are simply replaced with the variable resistance and the variable capacitance. A hysteresis model can be applied. Thus, hysteresis can be handled without increasing the hysteresis element in the equivalent circuit of the battery. Therefore, the hysteresis phenomenon can be handled by estimating the same number of parameters (resistance and capacity) as the battery model estimation that does not consider hysteresis. In addition, since it is possible to obtain the parameter by integrating the hysteresis phenomenon into the resistance and capacity of the battery model which does not consider the hysteresis within the time constant matched to the charge transfer process and the diffusion process of ions, accuracy improves. .

Second Embodiment
In the first embodiment, by expressing the resistance of the hysteresis model as the variable resistance R _{h in} the form of equation (11), it is possible to handle the hysteresis without increasing the hysteresis element in the equivalent circuit of the battery. In the second embodiment, a case will be described in which a form other than the equation (11) is used as a form representing the variable resistance R _h of the hysteresis model. The description overlapping with the first embodiment is omitted.

In the equation (11), the variable resistor R _{h of the} hysteresis model is represented by a function having the absolute value | u (t) | of the input current u (t) as a denominator. On the other hand, in order to handle the hysteresis phenomenon more accurately, it is conceivable to extend and express the denominator of the equation representing the variable resistance R _h as a function of the input current u (t). Here, f (| u (t) |) is defined as a function of the input current u (t). In general, the function f (x) represents the output for the input x, and the relationship between the input x and the output f (x) is arbitrarily determined. When the variable resistor R _h is represented using a function f (| u (t) |), the following equation (22) is obtained.

Also in the equation (22), it is characterized that the resistance of the model is a variable resistance which is variable according to the magnitude of the current.

One of the forms of the function f (x) is a linear function. This is a form expressed as f (x) = αx + β, and α and β are constants. Expressing the variable resistor R _h in this form, it becomes as shown in equation (23).

If β> 0 in the equation (23), the variable resistance R _h takes a finite value when u (t) = 0. That is, when estimating the variable resistance R _h , the model becomes stable without diverging to infinity, and approaches an actual model. Further, if β = 1 in the equation (23), then R _h (t) = M (t) in the case of u (t) = 0, so that the model parameters can be easily understood. As described above, according to the battery parameter estimation device according to the present embodiment, since the hysteresis can be accurately handled, it is possible to obtain an accurate estimated value more quickly. In particular, according to the model of equation (23) in the form of f (| u (t) |) = α | u (t) | + β, an accurate estimated value can be obtained more quickly.

Further, if α = 1 and β = 0 in the equation (23), then f (│u (t) │) = │u (t) │ and the model is expressed in the form of the equation (11). Since this makes it possible to simplify the model configuration, it is possible to handle the hysteresis phenomenon more easily.

As mentioned above, although a linear function was demonstrated as a form of function f (x), it is not restricted to this. It may be a polynomial such as a quadratic function, or it may be a rational function, an irrational function, a logarithmic function or an exponential function. Regardless of the type, hysteresis can be handled without increasing the hysteresis element in the equivalent circuit of the battery, and accurate estimated values can be obtained by selecting coefficients as a model conforming to the hysteresis characteristics.

As described above, the battery parameter estimation device according to the second embodiment sequentially estimates a parameter including resistance or capacity in the equivalent circuit model of the battery based on at least one of the battery voltage and the battery current. In the battery parameter estimation device, when the maximum range of voltage drop due to hysteresis is M (t), the speed of voltage drop is 入力 (t), and the input current is u (t), the resistance R _h (t) is The expression R _h (t) = M (t) / f (| u (t) |) as a function of the input current, and the capacitance C _h (t) is an expression C _h (t) = 1 / Γ (t) It is characterized by being represented by M (t). According to the battery parameter estimation device according to the second embodiment, by replacing the resistance and capacitance of the equivalent circuit with a variable resistance and a variable capacitance, it is possible to handle hysteresis without increasing the hysteresis element in the battery equivalent circuit. .

In addition, among the second embodiment, an embodiment in which f (| u (t) |) = α | u (t) | + β can be considered. The battery parameter estimation device according to this embodiment is a battery parameter estimation device that sequentially estimates a parameter including resistance or capacity in an equivalent circuit model of the battery based on at least one of a battery voltage and a battery current. Assuming that the maximum range of voltage drop due to hysteresis is M (t), the speed of voltage drop is Γ (t), and the input current is u (t), the resistance R _h (t) is expressed as a function of the input current R _h (t) = M (t) / (α | u (t) | + β), and the capacity C _h (t) is expressed by the equation C _h (t) = 1 / Γ (t) M (t) It is characterized by According to the battery parameter estimation device according to this embodiment, it is possible to get closer to the actual model and obtain an accurate estimated value more quickly.

Further, in the embodiment in which f (| u (t) |) = α | u (t) | + β, f (| u (t) |) = | u (t), with α = 1 and β = 0. An embodiment representing | can be considered. The battery parameter estimation device according to this embodiment is a battery parameter estimation device that sequentially estimates a parameter including resistance or capacity in an equivalent circuit model of the battery based on at least one of a battery voltage and a battery current. Assuming that the maximum range of voltage drop due to hysteresis is M (t), the speed of voltage drop is Γ (t), and the input current is u (t), the resistance R _h (t) is expressed as a function of the input current R _h (t) = M (t) / | u (t) | and the capacity C _h (t) is expressed by the equation C _h (t) = 1 / Γ (t) M (t) Do. According to the battery parameter estimation device according to this embodiment, the model configuration is simple and the hysteresis phenomenon can be easily handled.

Although the present invention has been described based on the drawings and examples, it should be noted that those skilled in the art can easily make various changes or modifications based on the present disclosure. Therefore, it should be noted that these variations or modifications are included in the scope of the present invention. For example, each component, each function included in each step, etc. can be rearranged so as not to be logically contradictory, and it is possible to combine or divide a plurality of components and steps into one. It is.

For example, in the above-described embodiment, the Warburg impedance Z _w is approximated by the infinite series expansion or the continued fraction expansion, but may be approximated by any method. For example, approximation using an infinite product expansion can be considered.

1 Battery 2 Voltage sensor (terminal voltage detector)
3 Current sensor (charge and discharge current detector)
4 estimation unit 41 battery equivalent circuit model 42 Kalman filter 5 charge amount calculation unit 6 charge ratio calculation unit 7 soundness calculation unit

Claims

In a battery parameter estimation device for sequentially estimating a parameter including resistance or capacity in an equivalent circuit model of the battery based on at least one of a battery voltage and a battery current,
In the hysteresis model representing the hysteresis generated in the characteristics of the battery state of charge and the open circuit voltage, it is characterized in that the equivalent circuit model of the battery is formed by the maximum range of voltage drop and the resistance related by the characteristics of input current. Battery parameter estimation device.
In the battery parameter estimation device according to claim 1,
A battery parameter estimation device for a battery, wherein the equivalent circuit model of the battery is formed using the maximum range of the voltage drop in the hysteresis model and the capacitance related by the characteristics of the speed of voltage drop in the hysteresis model.
In the battery parameter estimation device according to claim 1,
Assuming that the maximum range of the voltage drop is M (t) and the input current is u (t), the resistance R h (t) is

An apparatus for estimating a parameter of a battery, wherein
In the battery parameter estimation device according to claim 2,
Assuming that the maximum range of the voltage drop is M (t) and the speed of the voltage drop is Γ (t), the capacitance C h (t) is

An apparatus for estimating a parameter of a battery, wherein
In the battery parameter estimation device according to claim 3,
The resistance R h (t) is expressed by

An apparatus for estimating a parameter of a battery, wherein
In the battery parameter estimation device according to claim 3,
The resistance R h (t) is expressed by

An apparatus for estimating a parameter of a battery, wherein