JP2012026749A - Battery state estimation apparatus - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a battery state estimation apparatus capable of identifying a parameter of a secondary battery with high precision even if arithmetic operation for identification is iteratively suspended and resumed.SOLUTION: A battery state estimation apparatus detects a current and a terminal voltage of a secondary battery, uses measurements of the detected current and terminal voltage to estimate the terminal voltage of the secondary battery based on a predetermined battery model, and identifies a battery parameter of the battery model in such a manner that a differential between a value based on the measurement of the terminal voltage and an estimate of the terminal voltage is converged to zero. When arithmetic operation for identifying the battery parameter is suspended and resumed thereafter, the battery state estimation apparatus sets an initial value of the battery parameter to be used for resuming the arithmetic operation for identification on the basis of an amount of change in a battery state amount between suspension and resumption of the arithmetic operation for identification.

Description

  The present invention relates to a battery state estimation device for estimating a state inside a secondary battery.

  As a control device for a secondary battery, a predetermined battery model is defined, and based on the measured values of the current and terminal voltage of the secondary battery, the terminal voltage of the secondary battery based on the battery model is estimated as a voltage estimated value, and the voltage A control device is known that identifies battery parameters of a battery model so that the difference between a measured value and a voltage estimated value converges to zero (see, for example, Patent Document 1).

JP 2004-79472 A

  Here, in a control device such as the above-described prior art, it may be necessary to temporarily stop battery parameter identification calculation in order to maintain battery parameter identification accuracy (for example, charge / discharge current of a secondary battery). Therefore, in such a control device, in order to maintain battery parameter identification accuracy, the identification calculation is repeatedly paused and resumed. However, in the above-described prior art, when the identification calculation is temporarily stopped and then restarted again, the initial value of the battery parameter used for the identification calculation is set without considering the internal state of the battery. Therefore, there is a problem that the time for the battery parameter to converge to a true value becomes long after resuming the identification calculation, and a problem that the estimation accuracy of the battery parameter becomes insufficient after resuming the identification calculation.

  The problem to be solved by the present invention is to provide a battery state estimation device capable of identifying a parameter of a secondary battery with high accuracy even when the stop and restart of the identification calculation are repeatedly performed.

  The present invention detects a current and a terminal voltage of a secondary battery, estimates a terminal voltage of a secondary battery based on a predetermined battery model using the detected values of the detected current and terminal voltage, and measures a measured value of the terminal voltage. In the battery state estimation device for identifying the battery parameters of the battery model, the battery parameter identification calculation is stopped and then restarted so that the difference between the value based on the value and the estimated value of the terminal voltage converges to zero The above problem is solved by setting the initial value of the battery parameter used when the identification calculation is resumed based on the amount of change in the battery state quantity when the identification calculation is stopped and resumed.

  According to the present invention, when the battery parameter of the battery model is identified, the battery parameter identification calculation is stopped and then restarted. Accordingly, by setting the initial value of the battery parameter used when resuming the identification calculation, the initial value of the battery parameter used when resuming the identification calculation can be set appropriately, whereby the identification calculation is repeatedly stopped and restarted. Even in this case, the parameters of the secondary battery can be identified with high accuracy.

FIG. 1 is a diagram illustrating a configuration of a control system for a secondary battery according to the present embodiment. FIG. 2 is a functional block diagram of the electronic control unit 30 according to the first embodiment. FIG. 3 is a diagram showing an equivalent circuit model showing a battery model of the secondary battery. FIG. 4 is a configuration diagram of the adaptive identification system according to the present embodiment. FIG. 5 is a diagram illustrating an example of an open circuit voltage-charge rate characteristic of the secondary battery. FIG. 6 is a flowchart showing the estimation process of the battery parameters and the charging rate in the first embodiment. FIG. 7 is a diagram illustrating simulation results of battery parameter and charge rate estimation processing in the first embodiment. FIG. 8 is a diagram showing simulation results of battery parameter and charge rate estimation processing in the conventional example. FIG. 9 is a diagram illustrating simulation results of battery parameter and charge rate estimation processing in the first embodiment. FIG. 10 is a diagram showing simulation results of battery parameter and charging rate estimation processing in a conventional example. FIG. 11 is a functional block diagram of the electronic control unit 30 according to the second embodiment. FIG. 12 is a flowchart showing the battery parameter and charging rate estimation process in the second embodiment. FIG. 13 is a flowchart illustrating a charging rate estimation process according to the second embodiment.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings.

<< First Embodiment >>
First, a first embodiment of the present invention will be described.
FIG. 1 is a diagram illustrating a configuration of a control system for a secondary battery according to the present embodiment. The control system shown in FIG. 1 is applied to the present invention in a system that drives a load such as a motor with a secondary battery or charges a secondary battery with electric power generated by motor regeneration or power generated by an alternator using an engine as a power source. This is an example in which such a secondary battery control device is applied.

  The secondary battery 10 is formed by connecting a plurality of unit batteries in series. Examples of the unit battery constituting the secondary battery 10 include a lithium secondary battery such as a lithium ion secondary battery. An example of the load 20 is a motor.

  The current sensor 40 is a sensor that detects a charging / discharging current flowing through the secondary battery 10, and a signal detected by the current sensor 40 is sent to the electronic control unit 30. The voltage sensor 50 is a sensor that detects the terminal voltage of the secondary battery 10, and a signal detected by the voltage sensor 50 is sent to the electronic control unit 30. A temperature sensor 60 for detecting the temperature of the secondary battery 10 is provided in the vicinity of the secondary battery 10. The temperature sensor 60 is a sensor using a thermocouple or the like, and the signal detected by the temperature sensor 60 is similarly sent to the electronic control unit 30.

  The electronic control unit 30 is a control unit for controlling the secondary battery 10 and includes a CPU that calculates a program, a microcomputer that includes a ROM and RAM that stores programs and calculation results, an electronic circuit, and the like. . FIG. 2 shows a functional block diagram of the electronic control unit 30.

  As shown in FIG. 2, the electronic control unit 30 includes a current detection unit 301, a voltage detection unit 302, a temperature detection unit 303, a state variable filter calculation unit 304, an adaptive identification calculation unit 305, an open circuit voltage estimation unit 306, and an SOC estimation unit. 307, a battery state estimation unit 308, an identification calculation stop processing unit 309, and an identification calculation restart processing unit 310.

  The current detection unit 301 acquires a signal from the ammeter 40 at a predetermined cycle, and detects a charge / discharge current flowing through the secondary battery 10 based on the signal from the ammeter 40, thereby measuring a current measurement value I (k). To get. The current detection unit 301 sends the acquired current measurement value I (k) to the state variable filter calculation unit 304, the identification calculation stop processing unit 309, and the identification calculation restart processing unit 310.

  The voltage detection unit 302 acquires a signal from the voltmeter 50 at a predetermined cycle, and acquires a voltage measurement value V (k) by detecting a terminal voltage of the secondary battery 10 based on the signal from the voltmeter 50. To do. The voltage detection unit 302 sends the acquired measured current value V (k) to the state variable filter calculation unit 304, the adaptive identification calculation unit 305, the identification calculation stop processing unit 309, and the identification calculation restart processing unit 310.

  The temperature detection unit 303 acquires a signal from the temperature sensor 60 at a predetermined period, and acquires the battery temperature T (k) by detecting the temperature of the secondary battery 10 based on the signal from the temperature sensor 60. The temperature detection unit 303 sends the acquired battery temperature T (k) to the battery state estimation unit 308 and the identification calculation restart processing unit 310.

  The state variable filter calculation unit 304 defines a battery model of the secondary battery 10, and the current measurement value I (k) detected by the current detection unit 301 and the voltage measurement value V (k) detected by the voltage detection unit 302. From this, the state variable filter calculation is performed to obtain the conversion state quantity ω (k).

  Hereinafter, a method of calculating the conversion state quantity ω (k) by the state variable filter calculation unit 304 will be described.

ここで、モデル入力は電流Ｉ［Ａ］（正値は充電、負値は放電）、モデル出力は端子電圧Ｖ［Ｖ］であり、Ｒ_１〔Ω］は電荷移動抵抗、Ｒ_２［Ω］は純抵抗、Ｃ_１［Ｆ］は電気二重層容量、Ｖ_０［Ｖ］は開路電圧である。また、上記式（１）中、ｓは微分オペレータである。なお、本実施形態に係る電池モデルは、正極、負極を特に分離していないリダクションモデル（１次）であるが、実際の電池の充放電特性を比較的正確に示すことが可能である。このように本実施形態においては、電池モデルの次数を１次にした構成を例として説明する。 First, the “battery model” used in the present embodiment will be described. FIG. 3 is an equivalent circuit model showing a battery model of the secondary battery 10, and the equivalent circuit model shown in FIG. 3 is expressed by the following formula (1).

Here, the model input is current I [A] (positive value is charging, negative value is discharging), model output is terminal voltage V [V], R ₁ [Ω] is charge transfer resistance, R ₂ [Ω] Is a pure resistance, C ₁ [F] is an electric double layer capacitance, and V ₀ [V] is an open circuit voltage. In the above formula (1), s is a differential operator. Note that the battery model according to the present embodiment is a reduction model (primary) in which the positive electrode and the negative electrode are not particularly separated, but it is possible to show the actual charge / discharge characteristics of the battery relatively accurately. As described above, in the present embodiment, a configuration in which the order of the battery model is first will be described as an example.

That is, when R ₁ , R ₂ , and C ₁ are represented by the following formula (2), the above formula (1) is represented by the following formula (3).

  And in this embodiment, based on the battery model shown by said Formula (3), the state variable filter calculation part 304 performs a state variable filter calculation, and calculates | requires conversion state quantity (omega) (k).

First, assuming that the open circuit voltage V ₀ (t) is obtained by integrating a current I (t) multiplied by a variable parameter h from an initial state, the open circuit voltage V ₀ (t) is expressed by the following formula (4 ).

When the above formula (4) is substituted into the above formula (3), the following formula (5) is obtained, and when this is arranged, the following formula (6) is obtained.

ここで、Ａ（ｓ）、Ｂ（ｓ）はｓの多項式関数であり、Ａ（ｓ）とＢ（ｓ）とは次数が同じものである。 The above formula (1) and the above formula (6) respectively correspond to the following formula (7) and the following formula (8). Specifically, the above formula (1) and the above formula (6) are In the following formula (7) and the following formula (8), this corresponds to the case where the orders of A (s) and B (s) are set to primary.

Here, A (s) and B (s) are polynomial functions of s, and A (s) and B (s) have the same order.

Then, by introducing known constants k _i (i = 1, 2,..., N) into the above formula (6), the following formulas (9) and (10) can be obtained.

However, in the above formula (10), y (t) is obtained by subtracting the direct term from V (t), and therefore y (t) is represented by the following formula (11).

ただし、上記式（１２）中、φ^Ｔ＝［Ｉ_ｉ，ｂ_０ｉ］、ω＝［ｆ_Ｖｉ，ｆ_Ｉｉ］ である。 In the above formula (10), I _i and b _0i are parameters including unknown parameters (T ₁ , T ₂ , K, h), and f _Vi and f _Ii are obtained by the ammeter 40 and the voltmeter 50. This is a converted state quantity obtained by filtering I (k) and V (k), which are measurable values, with a state variable filter. And since said Formula (10) is these product sum formulas, it corresponds with following formula (12) which is a standard form of an adaptive digital filter.

However, in the above formula (12), φ ^T = [I _i , b _0i ] and ω = [f _Vi , f _Ii ].

  In this way, the state conversion amount ω (k) is calculated by the state variable filter calculation unit 304. Then, the obtained state conversion amount ω (k) is sent by the state variable filter calculation unit 304 to the adaptive identification calculation unit 305 and the open circuit voltage estimation unit 306.

  The adaptive identification calculation unit 305 calculates the battery parameter φ ^ (k) of the battery model of the secondary battery 10 by adaptive digital filter calculation based on the conversion state quantity ω (k) calculated by the state variable filter calculation unit 304. An identification operation for identification is performed.

Here, “^” attached to the right shoulder in φ ^ (k) indicates that the value is an estimated value. In FIG. 2, “^”, which is an estimated value, is set directly above “φ” of φ (k), directly above “R” of R (k), and “V” of V ₀ (k), respectively. ”Directly above“ S ”of SOC (k), as shown in the following formula (13), this is φ ^ (k), R ^ (k), V ₀ ^ (k). , And SOC ^ (k). The same applies to V ^ (k), SOC ₁ ^ (k), and SOC ₂ ^ (k).

Specifically, in the configuration diagram of the adaptive identification system as shown in FIG. 4, the adaptive identification calculation unit 305 first of the secondary battery 10 estimated from the battery model described above from the conversion state quantity ω (k). A voltage estimated value V ^ (k) that is an estimated value of the terminal voltage is estimated. The adaptive identification calculation unit 305 then calculates the voltage estimated value V ^ (k) and the voltage measurement value V (k) that is an actual measurement value detected by the voltmeter 50 and acquired by the voltage detection unit 302. An identification calculation is performed to identify the battery parameter φ ^ (k) of the battery model based on the algorithm shown in the following formula (14) by the adaptive adjustment rule so that the difference converges to zero. At this time, in this embodiment, the logical disadvantage of a simple “adaptive digital filter based on the least square method” (once the estimated value converges, accurate estimation cannot be performed again even if the parameter changes thereafter). It is possible to use a “both limit trace gain method” that improves the above. FIG. 4 is a configuration diagram of the adaptive identification system according to the present embodiment realized by the state variable filter calculation unit 304 and the adaptive identification calculation unit 305.

  The above equation (14) is a sequential equation for adaptively obtaining the battery parameter φ ^ (k), and γ (k) and Γ (k−1) are both adaptive gains, and among these, γ (k ) Is a scalar gain (error gain), and Γ (k−1) is a matrix gain (signal gain). When the conversion state quantity ω (k) at time k is obtained by the above equation (14), the estimated voltage value V ^ that is the estimated value of the terminal voltage of the secondary battery 10 estimated from the battery model. E (k) which is a difference between (k) and the voltage measurement value V (k) detected by the voltmeter 50 and acquired by the voltage detection unit 302 can be obtained, and this e (k) is converged to zero. By doing so, the battery parameter φ ^ (k) can be calculated sequentially. In this case, as the voltage measurement value V (k), a value obtained by performing a filtering process for removing measurement noise on the value acquired by the voltage detection unit 302 may be used. The voltage estimation value considering the filter characteristics may be calculated.

  Thus, the calculated battery parameter φ ^ (k) of the secondary battery 10 is sent from the adaptive identification calculation unit 305 to the open circuit voltage estimation unit 306 and the identification calculation stop processing unit 309 as shown in FIG. Sent out.

As shown in FIG. 4, in the adaptive identification system of the present embodiment realized by the state variable filter calculation unit 304 and the adaptive identification calculation unit 305, first, the current measurement value detected by the current detection unit 301. I (k), using the voltage measurement value V (k) detected by the voltage detection unit 302, the state variable filter calculation unit 304 uses the state variable filter as described above to convert the converted state quantity ω (k ) (Conversion state quantities ω ₁ (k), ω ₂ (k), ω ₃ (k), ω ₄ (k), ω ₅ (k)).

Next, in the adaptive identification system of the present embodiment, the adaptive identification calculation unit 305 uses the converted state quantity ω (k) obtained by the state variable filter calculation unit 304 and the battery model parameter φ ^ (k−1). Thus, a voltage estimated value V ^ (k) that is an estimated value of the terminal voltage based on the battery model is calculated. According to the adaptive identification system of this embodiment, the adaptive identification calculation unit 305 converts the conversion state quantity ω (k) obtained by the state variable filter calculation unit 304 and the voltage measurement detected by the voltage detection unit 302. Using the value V (k) and the estimated voltage value V ^ (k), the battery parameter φ ^ (k) (φ ₁ , φ ₂ , φ ₃ , φ ₄ , φ of the battery model according to the above equation (14) ₅ ) will be identified.

The open circuit voltage estimation unit 306 is based on the conversion state quantity ω (k) obtained by the state variable filter computation unit 304 and the battery parameter φ ^ (k) obtained by the adaptive identification computation unit 305. Is estimated, and an open circuit voltage estimated value V ₀ ^ (k) is calculated.

Specifically, the open circuit voltage estimation unit 306 is based on the battery parameter φ ^ (k) calculated by the above equation (14) and the conversion state quantity ω (k) calculated based on the above equation (10). The open circuit voltage estimated value V ₀ ^ (k) is calculated by substituting these battery parameters φ ^ (k) and the conversion state quantity ω (k) into the above equation (4).

Here, the battery parameter φ ^ (k) corresponds to the parameters I _i and b _0i including the unknown parameters (T ₁ , T ₂ , K, h) as described above. Therefore, the battery parameter φ ^ (k) calculated by the adaptive identification calculation unit 305 and the conversion state quantity ω (k) calculated by the state variable filter calculation unit 304 are used, and these are substituted into the above equation (4). By doing this, the open circuit voltage estimated value V ₀ ^ (k) can be obtained. The open circuit voltage estimated value V ₀ ^ (k) obtained in this way is sent from the open circuit voltage estimation unit 306 to the SOC estimation unit 307.

The SOC estimation unit 307 calculates the charge rate estimated value based on the predetermined open circuit voltage-charge rate characteristic of the secondary battery 10 from the open circuit voltage estimated value V ₀ ^ (k) calculated by the open circuit voltage estimation unit 306. Calculate SOC ^ (k). An example of the open circuit voltage-charge rate characteristic of the secondary battery 10 is shown in FIG. In the present embodiment, the open circuit voltage-charge rate characteristic of the secondary battery 10 is stored in advance in a ROM provided in the electronic control unit 30, and the open battery voltage and the charge rate of the secondary battery 10 are experimentally determined in advance. It can obtain by calculating | requiring the relationship. The charging rate estimated value SOC ^ (k) obtained in this way is sent from the SOC estimating unit 307 to the battery state estimating unit 308.

  Based on the battery temperature T (k) detected by the temperature detection unit 303 and the charge rate estimation value SOC ^ (k) calculated by the SOC estimation unit 307, the battery state estimation unit 308 The resistance estimated value R ^ (k) is calculated. The method for calculating the estimated internal resistance value R ^ (k) is not particularly limited. For example, it is calculated using a map that summarizes the characteristics of the internal resistance value with respect to the battery temperature and the charge rate measured in advance through experiments. Can do. The internal resistance estimated value R ^ (k) obtained in this way is sent from the battery state estimation unit 308 to the identification calculation stop processing unit 309 and the identification calculation restart processing unit 310.

Based on the current measurement value I (k) detected by the current detection unit 301 and the voltage measurement value V (k) detected by the voltage detection unit 302, the identification calculation stop processing unit 309 performs It is determined whether or not the battery parameter φ ^ (k) identification calculation process is to be stopped. Specifically, the identification calculation stop processing unit 309 performs FFT (Fast Fourier Transform) analysis on the current measurement value I (k) and the voltage measurement value V (k) that are input values. If the current measurement value I (k) and the voltage measurement value V (k) have sufficient frequency components as a result of the FFT analysis (that is, if it is a Sophistically Rich), it is determined that the identification calculation is possible. If there is not enough frequency component, it is determined that the identification calculation is impossible because the adaptive identification calculation unit 305 cannot sufficiently secure the accuracy of the identification calculation processing of the battery parameter φ ^ (k). If the identification calculation stop processing unit 309 determines that the identification calculation processing by the adaptive identification calculation unit 305 is to be stopped, the identification calculation stop processing unit 309 sends a stop signal S ₁ to the adaptive identification calculation unit 305, thereby The identification calculation process by 305 is stopped.

上記式（１５）中、Ｔ_ｄｉｖは時定数であり、このような時定数としては、同定演算に必要となる周波数成分を不要に減衰させないような範囲で設定することが望ましい。 In the present embodiment, if the FFT analysis cannot be performed in real time due to the calculation capability of the CPU provided in the electronic control unit 30, for example, an approximate differentiation process as shown in the following equation (15) is performed. It is also possible to perform the above determination using the obtained approximate differential value, which is performed on the current measurement value I (k) and voltage measurement value V (k) which are input values. Specifically, if the approximate differential value is greater than or equal to a predetermined value, it is determined that the identification calculation is possible. On the other hand, if the approximate differential value is less than the predetermined value, it is determined that the identification calculation is not possible.

In the above equation (15), T _div is a time constant, and such a time constant is desirably set in a range that does not unnecessarily attenuate frequency components necessary for the identification calculation.

As a result of the above determination, when the identification calculation processing is stopped, the identification calculation stop processing unit 309 is configured such that the battery parameter φ ^ (k) calculated by the adaptive identification calculation unit 305 when the identification calculation processing is stopped. And the internal resistance estimated value R ^ (k) calculated by the battery state estimating unit 308 is provided in the electronic control unit 30 as the battery parameter φ _s ^ when the identification calculation is stopped and the internal resistance estimated value R _s ^ when the identification calculation is stopped. Stored in the designated RAM.

The identification calculation restart processing unit 310, when the identification calculation of the battery parameter φ ^ (k) by the adaptive identification calculation unit 305 is stopped, the current measurement value I (k) detected by the current detection unit 301, and Based on the voltage measurement value V (k) detected by the voltage detection unit 302, the adaptive identification calculation unit 305 determines whether or not to restart the battery parameter φ ^ (k) identification calculation process. Specifically, the identification calculation restart processing unit 310 performs FFT (for FFT) with respect to the current measurement value I (k) and the voltage measurement value V (k) that are input values, similarly to the identification calculation stop processing unit 309 described above. (Fast Fourier transform) analysis is performed, and as a result of FFT analysis, identification calculation is possible or identification calculation is not possible based on whether the current measurement value I (k) and voltage measurement value V (k) have sufficient frequency components Make a decision. The identification calculation resumption processing unit 310, by the adaptive identification calculation unit 305, when determining that resuming identification calculation process, by sending a stop signal S ₂ to the adaptive identification calculation unit 305, the adaptive identification calculation unit The identification calculation process by 305 is resumed.

  Even when making this determination, if the FFT analysis cannot be performed in real time due to the calculation capability of the CPU provided in the electronic control unit 30, the method using the approximate differential value described above may be used. .

As a result of the determination, when resuming the identification calculation process, the identification calculation resumption processing unit 310 determines the internal resistance estimated value R ^ (k) calculated by the battery state estimation unit 308 at the start of the identification calculation process. Is taken as the internal resistance estimated value R _r ^ when the identification calculation is resumed. Further, the identification calculation restart processing unit 310 reads the identification calculation stop internal resistance estimated value R ^ _S stored in the RAM by the above-described identification calculation stop processing unit 309. Then, the identification calculation restart processing unit 310 changes the rate of change | 1- (R _r ), which is a change ratio between the internal resistance estimated value R _S ^ when the identification calculation is stopped and the internal resistance estimated value R _r ^ when the identification calculation is restarted. ^) / (R _S ^) | is calculated, and the change rate | 1- (R _r ^) / (R _S ^) | is compared with a predetermined first threshold value α.

As a result of this comparison, if | 1- (R _r ^) / (R _S ^) | <α, the identification calculation resumption processing unit 310 restarts the identification calculation processing by the adaptive identification calculation unit 305. As the initial value of the battery parameter used for the above, the identification calculation stop battery parameter φ _s ^ stored in the RAM is set by the identification calculation stop processing unit 309 described above. That is, the initial value of the battery parameter used when resuming the identification calculation process is the battery parameter φ _s ^ when the identification calculation is stopped.

On the other hand, if | 1- (R _r ^) / (R _S ^) | ≧ α, the identification calculation restart processing unit 310 uses the battery parameter as the initial value of the battery parameter used when restarting the identification calculation process. An initial battery parameter φ _i which is an initial value of a battery parameter set in advance for each temperature is set. That is, referring to the battery temperature T (k) detected by the temperature detection unit 303 for the initial value of the battery parameter used when resuming the identification calculation process, the initial battery parameter φ _i corresponding to the battery temperature T (k) is used. And In addition to the battery temperature, the initial battery parameter φ _i may be set based on the combination of the battery deterioration level or the battery SOC, or the combination of the battery temperature, the battery deterioration level, and the battery SOC. Good.

  Note that the identification calculation restart processing unit 310 may use a preset fixed value as the first threshold value α, but in the present embodiment, the first threshold value α is set according to the battery temperature T (k). The configuration is changed.

  Next, the estimation process of the battery parameter φ ^ (k) and the charging rate estimated value SOC ^ (k) in the present embodiment will be described using the flowchart shown in FIG. Note that the processing shown in FIG. 6 is performed at regular intervals (in this embodiment, every 100 msec). In the following description, I (k) is a current value (current measurement value) of the current execution cycle, I (k−1) is a current value (previous measurement value) of the previous execution cycle, The same applies to values other than current. Note that the processing described below is performed by the electronic control unit 30.

  First, in step S101, the current measurement value I (k), voltage measurement value V (k), and battery temperature T (k) are acquired by the current detection unit 301, voltage detection unit 302, and temperature detection unit 303. . The measured current value I (k) is supplied to the state variable filter calculation unit 304, the identification calculation stop processing unit 309, and the identification calculation restart processing unit 310. The measured voltage value V (k) is input to the state variable filter calculation unit 304, Battery temperature T (k) is sent to adaptive identification calculation section 305, identification calculation stop processing section 309, and identification calculation restart processing section 310, respectively, to battery state estimation section 308 and identification calculation restart processing section 310.

  In step S102, the state variable filter calculation unit 304 determines the state of the current measurement value I (k) and voltage measurement value V (k) acquired in step S101 based on the above equations (9) and (10). A state filter calculation using a variable filter is performed, and a converted state quantity ω (k) is calculated.

In step S103, the battery state estimation unit 308 calculates the internal resistance estimated value R ^ (k). Specifically, the battery state estimation unit 308 uses the battery temperature T (k) acquired in step S101 and the charge rate estimation value SOC ^ (k−1) estimated by the SOC estimation unit 307 during the previous process. Based on the map that summarizes the characteristics of the internal resistance value with respect to the battery temperature and the charging rate measured in advance through experiments, the internal resistance estimated value R ^ (k) is calculated. In this embodiment, when the electronic control unit 30 is activated, the charge rate estimated value SOC ^ (k−1) at the time of the previous process does not exist. However, immediately after the electronic control unit 30 is activated, in step S101 Since it can be determined that the acquired voltage measurement value V (k) is substantially equal to the open circuit voltage V ₀ , the charge rate estimated value is obtained using the open circuit voltage-charge rate characteristics stored in advance in the ROM of the electronic control unit 30. SOC ^ can be determined and used.

  In step S104, the identification calculation stop processing unit 309 has already stopped the identification calculation of the battery parameter φ ^ (k) by the adaptive identification calculation unit 305, and the identification calculation by the adaptive identification calculation unit 305 is stopped. A determination is made whether or not. If the identification calculation stop process by the adaptive identification calculation unit 305 is not performed and the identification calculation process is performed in the previous process, the process proceeds to step S105. On the other hand, when the identification calculation by the adaptive identification calculation unit 305 is stopped, the process proceeds to step S110.

  In step S105, the identification calculation stop processing unit 309 determines whether or not to stop the identification calculation processing of the battery parameter φ ^ (k) by the adaptive identification calculation unit 305. Specifically, the identification calculation stop processing unit 309 can perform the identification calculation according to the method described above based on the current measurement value I (k) and the voltage measurement value V (k) acquired in step S101. Alternatively, by determining whether or not the identification calculation is possible, the adaptive identification calculation unit 305 determines whether or not to stop the identification calculation process. If it is determined that the identification calculation is possible and it is determined to continue the identification calculation process, the process proceeds to step S106. On the other hand, when it is determined that the identification calculation is not possible and it is determined that the identification calculation process is to be stopped, the process proceeds to step S109.

  If it is determined in step S105 that the identification calculation process is to be continued, the process proceeds to step S106. In step S106, the identification calculation process for identifying the battery parameter φ ^ (k) by the adaptive identification calculation unit 305 is performed. Is done. Specifically, in step S106, the adaptive identification calculation unit 305 uses the conversion state quantity ω (k) calculated in step S102 and the voltage measurement value V (k) acquired in step S101 to obtain the above formula. According to (14), the battery parameter φ ^ (k) of the battery model is identified.

In step S107, based on the battery parameter φ ^ (k) calculated in step S106 by the open circuit voltage estimation unit 306 and the conversion state quantity ω (k) calculated in step S102, the open circuit voltage estimated value V ₀ ^ (K) is calculated. Then, the calculated open circuit voltage estimated value V ₀ ^ (k) is sent to the SOC estimation unit 307.

In step S108, the SOC estimation unit 307 performs charging based on the predetermined open circuit voltage-charge rate characteristic of the secondary battery 10 using the open circuit voltage estimated value V ₀ ^ (k) calculated in step S107. The rate estimated value SOC ^ (k) is calculated. And it returns to step S101 and the process of step S101-S108 mentioned above is repeated, and estimation of charge rate estimated value SOC ^ (k) based on battery parameter (phi) (k) and this battery parameter (phi) (k). The process will be repeated.

On the other hand, if it is determined by the identification calculation stop processing unit 309 that the identification calculation is impossible in step S105 described above and it is determined that the identification calculation process is to be stopped, the process proceeds to step S109. In step S109, the identification calculation stop process is performed. By the unit 309, the adaptive identification calculation unit 305 performs the process of stopping the identification calculation of the battery parameter φ ^ (k). Specifically, identification calculation stop processing unit 309 sends a stop signals S ₁ to the adaptive identification calculation unit 305, by the adaptive identification calculation unit 305, to stop the identification calculation processing, the internal resistance calculated in the step S103 estimate R ^ a (k), as identification calculation stopped when the internal resistance estimated value _{R s} ^, also at the time of the previous processing (step S106 in the previous processing), battery parameters calculated phi ^ a (k-1), The battery parameters φ _s ^ when the identification calculation is stopped are stored in the RAM provided in the electronic control unit 30, respectively.

In step S109, after the identification calculation is stopped, the process proceeds to step S107, and the open circuit voltage estimation unit 306 calculates the open circuit voltage estimated value V ₀ ^ (k). In this case, since the identification calculation process (step S106) for identifying the battery parameter φ ^ (k) by the adaptive identification calculation unit 305 is not performed, the open circuit voltage estimated value V ₀ ^ (k) Is calculated based on the battery parameter φ _s ^ at the time of stopping the identification calculation stored in the RAM provided in the electronic control unit 30 in step S109 and the conversion state quantity ω (k) calculated in step S102. It becomes. That is, when the open circuit voltage estimated value V ₀ ^ (k) is calculated, the battery parameter φ _s ^ when the identification calculation is stopped is used instead of the battery parameter φ ^ (k).

Next, the process proceeds to step S108, and the SOC estimation unit 307 uses the open circuit voltage estimated value V ₀ ^ (k) calculated in step S107 described above to determine a predetermined open circuit voltage-charge rate characteristic of the secondary battery 10. Based on the above, the charging rate estimated value SOC ^ (k) is calculated. Then, returning to step S101, it is determined in step S110 to be described later that the identification calculation process can be restarted. In steps S111 to S114, the identification calculation stop battery parameter φ _s ^ until the identification calculation restart process is performed. Is used to estimate the charging rate estimated value SOC ^ (k).

That is, when the identification calculation stop process is performed in step S109 described above, as described above, in step S107 and step S108, the open circuit voltage estimated value is determined using the battery parameter φ _s ^ when the identification calculation is stopped. Calculation of V ₀ ^ (k) and calculation of estimated charge rate SOC ^ (k) are performed. Thereafter, the process returns to step S101. In steps S101 to S103, the current measurement value I (k), voltage measurement value V (k), and battery temperature T (k) are obtained (step S101) and converted in the same manner as described above. The state quantity ω (k) is calculated (step S102), and the internal resistance estimated value R ^ (k) is calculated (step S103). In step S104, it is determined that the identification calculation is stopped, and the process proceeds to step S110.

In step S110, the identification calculation restart processing unit 310 determines whether or not the adaptive identification calculation unit 305 restarts the battery parameter φ ^ (k) identification calculation process. Specifically, the identification calculation restart processing unit 310 can perform the identification calculation according to the method described above based on the current measurement value I (k) and the voltage measurement value V (k) acquired in step S101. Alternatively, by determining whether or not the identification calculation is possible, the adaptive identification calculation unit 305 determines whether or not to restart the identification calculation process. If it is determined that the identification calculation is possible and it is determined to restart the identification calculation process, the process proceeds to step S111 in order to execute the identification calculation restart process. On the other hand, if it is determined that the identification calculation is not possible and it is determined that the identification calculation process is to be stopped, the process proceeds to step S107, and the same as above until it is determined in step S110 that the identification calculation process can be restarted. Thus, the estimation process of the estimated charge rate SOC ^ (k) using the battery parameter φ _s ^ when the identification calculation is stopped is repeatedly performed.

If it is determined in step S110 that the identification calculation is possible and it is determined that the identification calculation process is to be resumed, the process proceeds to step S111, where the identification calculation restart processing unit 310 causes the adaptive identification calculation unit 305 to use the battery parameter φ ^. (K) The identification calculation restart process is performed. Specifically, identification calculation restart processing unit 310 sends a resume signal S ₂ to the adaptive identification calculation unit 305, by the adaptive identification calculation unit 305, by transmitting a signal for resuming the identification calculation processing, adaptive A command for restarting the identification calculation process is issued to the identification calculation unit 305.

Next, in step S112, the identification calculation resumption processing unit 310 performs the identification stored in the RAM provided in the electronic control unit 30 when the process for stopping the identification calculation process is performed in step S109 described above. The estimated internal resistance value R _s ^ when the computation is stopped is read, and the estimated internal resistance value R ^ at the current processing obtained in step S103 is set to the estimated internal resistance value R _r ^ when the identification calculation is resumed. Then, the identification calculation resumption processing unit 310 calculates the rate of change | 1- (R _r ^) / (R _S ^) |, which is the ratio of these, and the rate of change | 1- (R _r ^) / (R _S ^) | Is compared with a predetermined first threshold value α.

As a result of this comparison, if it is determined that | 1- (R _r ^) / (R _S ^) | <α, the process proceeds to step S113, where the initial battery parameters used when resuming the identification calculation process As a value, the battery parameter φ _s ^ when the identification calculation is stopped is set. Next, the process proceeds to step S106, and the battery parameter φ ^ (k) is calculated using the battery parameter φ _s ^ when the identification calculation is stopped as the initial value of the battery parameter used for the identification calculation. Using parameter φ ^ (k), open circuit voltage estimated value V ₀ ^ (k) is calculated (step S107), and charging rate estimated value SOC ^ (k) is calculated (step S108).

On the other hand, if it is determined that | 1- (R _r ^) / (R _S ^) | ≧ α, the process proceeds to step S114, and the initial value of the battery parameter used when resuming the identification calculation process is as follows. An initial battery parameter φ _i that is an initial value of a battery parameter set in advance for each battery temperature is set. Note that when the initial value of the battery parameter is set to the initial battery parameter φ _i , the battery temperature T (k) acquired in step S101 is referred to. Then, the process proceeds to step S106, used for identification calculation as an initial value of the battery parameters, using the initial cell parameter phi _i, calculation of ^ cell parameters phi (k) is performed, the battery parameter calculated phi ^ ( k) is used to calculate the open circuit voltage estimated value V ₀ ^ (k) (step S107) and the charging rate estimated value SOC ^ (k) (step S108).

In this embodiment, when the identification calculation for identifying the battery parameter φ ^ (k) is stopped and then the identification calculation is restarted, the initial battery parameter used for the identification calculation of the battery parameter φ ^ (k) is used. values, the identification calculation stopped when the internal resistance estimated value _{R S} ^, is the ratio of change in the identification calculation resumption internal resistance estimated value _{R r} ^, the rate of change _{| 1- (R r ^) /} (R S ^ ) | Is selected according to |. That is, the initial value of the battery parameter used when restarting the identification calculation is selected according to the change in the internal resistance value of the secondary battery 10 when the identification calculation is stopped and restarted. Specifically, in the present embodiment, the rate of change | 1- (R _r ^) / (R _S ^) | is | 1- (R _r ^) / (R _{If S} ^) | <α, the battery parameter φ _s ^ when the identification calculation is stopped is used as the initial value of the battery parameter, while | 1- (R _r ^) / (R _S ^) When | ≧ α, the initial battery parameter φ _i that is the initial value of the battery parameter preset for each battery temperature is used as the initial value of the battery parameter. Therefore, according to the present embodiment, when the identification calculation is restarted, the battery parameter φ ^ (k) is relatively set regardless of the change in the internal resistance value of the secondary battery 10 when the identification calculation is stopped and restarted. It is possible to converge to the true value in a short time, and thereby it is possible to improve the estimation accuracy of the charging rate.

  Furthermore, according to this embodiment, when selecting the initial value of the battery parameter used when resuming the identification calculation, the internal state which is the main state quantity among the battery state quantities indicating the internal state of the secondary battery 10 is selected. Since the resistance value is used and set based on the amount of change in the internal resistance value, the above effect can be further enhanced.

In addition, according to the present embodiment, the first threshold value α described above is configured to be changed according to the battery temperature T (k). Even if the rate of change of the internal resistance value | 1- (R _r ^) / (R _S ^) | is the same when the identification calculation is stopped and restarted, if the battery temperature T (k) changes, the battery parameter What is desired as an initial value may also change. On the other hand, in the present embodiment, the initial value of the battery parameter can be set more appropriately by changing the first threshold value α according to the battery temperature T (k). Can be further enhanced.

  Here, FIG. 7 is a diagram showing a simulation result of the battery parameter and charging rate estimation processing in the present embodiment, and FIG. 8 is a diagram showing a simulation result of the battery parameter and charging rate estimation processing in the conventional example.

7 and 8, the graphs on the left side are profiles showing the change in the current measurement value I (k) from the top, profiles showing the change in the voltage measurement value V (k), and the true value of the estimated value of the charge rate SOC. The profile which shows the change of the error with respect to, and the profile which shows the change of the estimated value of the charging rate SOC. 7 and 8, the graphs on the right side are the profile of the battery parameters (parameters 1 to 4) and the profile of the rate of change of the internal resistance value from the top. Incidentally, FIG. 7, in FIG. 8, parameters 1-4 are each parameter _{T 1,} T 2, K, either h, or the parameters _{T 1,} T 2, K, of h, 2 or more This is equivalent to adding and adding arbitrarily. 7 and 8, the estimated value is indicated by a solid line and the true value is indicated by a broken line.

  7 and 8, the identification calculation of each parameter 1 to 4 is performed in “Area A” shown in FIGS. 7 and 8, and then the identification calculation of each parameter 1 to 4 is performed in “Area B”. The simulation result is shown in the case of stopping and then restarting the identification calculation in “region C”. The simulation results shown in FIGS. 7 and 8 are simulation results when the rate of change of the internal resistance value changes while the identification calculation of each parameter 1 to 4 is stopped. is there.

As shown in FIG. 7, when the internal resistance value changes during the stop of the identification calculation as in this embodiment, the battery preset for each battery temperature is used as the initial value of the battery parameter used when the identification calculation is resumed. By using the initial battery parameter φ _i which is the initial value of the parameter, each parameter 1 to 4 can be converged to the true value in a relatively short time, and as a result, the estimated value of the charging rate SOC with respect to the true value It can be confirmed that the error can be reduced.

On the other hand, as shown in FIG. 8, when the change rate of the internal resistance value changes while the identification calculation is stopped, the battery parameter φ _s ^ when the identification calculation is stopped is used as the initial value of the battery parameter. ˜4 did not converge to the true value, and as a result, an error with respect to the true value of the estimated value of the charging rate SOC was increased.

  Similarly, FIG. 9 is a diagram showing a simulation result of the battery parameter and charging rate estimation processing in the present embodiment, and FIG. 10 is a diagram showing a simulation result of the battery parameter and charging rate estimation processing in the conventional example.

  FIGS. 9 and 10 are diagrams showing simulation results as in FIGS. 7 and 8 described above. Unlike FIGS. 7 and 8, the simulation results of FIGS. 9 and 10 are “region B”. That is, it is a simulation result when the internal resistance value does not change when the identification calculation of each parameter 1 to 4 is stopped.

As shown in FIG. 9, when the identification calculation is stopped and the internal resistance value is not changed as in the present embodiment, the battery parameter φ when the identification calculation is stopped is used as the initial value of the battery parameter used when the identification calculation is restarted. By using _s ^, each parameter 1 to 4 can be converged to a true value in a relatively short time, and as a result, an error with respect to the true value of the estimated value of the charging rate SOC can be reduced. I can confirm that.

On the other hand, as shown in FIG. 8, when the internal resistance value does not change during the stop of the identification calculation, the initial battery that is the initial value of the battery parameter preset for each battery temperature is used as the initial value of the battery parameter. When the parameter φ _i is used, each of the parameters 1 to 4 does not converge to the true value, and as a result, an error with respect to the true value of the estimated value of the charging rate SOC becomes large.

<< Second Embodiment >>
Next, a second embodiment of the present invention will be described.
The second embodiment is the same as the first embodiment except that the electronic control unit 30 has the configuration shown in the functional block diagram as shown in FIG. 11 and functions as described below.

  As shown in FIG. 11, the electronic control unit 30 according to the second embodiment includes a first SOC estimation unit 307a instead of the SOC estimation unit 307, as compared with the first embodiment, and includes a second SOC estimation unit. The electronic control unit 30 is the same as the electronic control unit 30 according to the first embodiment described above except that it further includes 311 and a selection unit 312.

Similar to the SOC estimation unit 307 of the first embodiment described above, the first SOC estimation unit 307a uses a predetermined secondary battery from the open circuit voltage estimated value V ₀ ^ (k) calculated by the open circuit voltage estimation unit 306. Based on the 10 open circuit voltage-charge rate characteristics, a first charge rate estimated value SOC ₁ ^ (k) is calculated. Then, the first charging rate estimated value SOC ₁ ^ (k) obtained in this way is sent from the first SOC estimating unit 307a to the second SOC estimating unit 311 and the selecting unit 312.

The second SOC estimation unit 311 performs the identification calculation stop processing when the identification calculation stop processing unit 309 performs the identification calculation stop processing of the battery parameter φ ^ (k) by the adaptive identification calculation unit 305. In this case, the first charging rate estimated value SOC ₁ ^ (k) calculated by the first SOC estimating unit 307a is acquired, and this is set as the charging rate estimated value SOC _s ^ (k) when the identification calculation is stopped. Then, the second SOC estimation unit 311 estimates the second charge rate based on the current calculation method based on the identification calculation stop state charge rate estimated value SOC _s ^ and the current detection value I (k) detected by the current detection unit 301. The value SOC ₂ ^ (k) is calculated. Specifically, the second SOC estimator 311 obtains the remaining capacity of the secondary battery corresponding to the charging rate estimated value SOC _s ^ when the identification calculation is stopped, and uses this as the initial capacity C _ini , and the current detection value I (k ), The change in battery capacity due to the charge / discharge current flowing in the secondary battery 10 is obtained by integrating the current detection value I (k), and the obtained battery capacity C is determined as the total capacity C _{all of the} secondary battery 10. The second charging rate estimated value SOC ₂ ^ (k) is calculated by dividing by. Then, second charge rate estimated value SOC ₂ ^ (k) obtained in this way is sent from second SOC estimation unit 311 to selection unit 312.

The calculation of the second charging rate estimated value SOC ₂ ^ is started when the identification calculation stop process is performed by the adaptive identification calculation unit 305, and then the identification calculation restart processing unit 310 performs the adaptive identification calculation unit. The process is terminated when a predetermined time T (the predetermined time T will be described later) elapses after the identification calculation restart process 305 is executed.

Selection unit 312 selects whether calculation for obtaining charging rate estimated value SOC ^ (k) of secondary battery 10 is to be performed by first SOC estimation unit 307a or second SOC estimation unit 311. These are switched. Specifically, the selection unit 312
When the identification calculation is stopped by the constant calculation unit 305, the second SOC estimation unit 311 replaces the first charging rate estimated value SOC ₁ ^ (k) calculated by the first SOC estimation unit 307a. The calculated second charging rate estimated value SOC ₂ ^ (k) is switched to the charging rate estimated value SOC ^ (k) of the secondary battery 10. On the other hand, the second charging rate estimated value SOC ₂ ^ (k) calculated by the second SOC estimating unit 311 when a predetermined time T has elapsed since the identification calculation resuming process by the adaptive identification calculating unit 305 is executed. Instead, the first charging rate estimated value SOC ₁ ^ (k) calculated by the first SOC estimating unit 307a is switched to the charging rate estimated value SOC ^ (k) of the secondary battery 10. That is, the selection unit 312 uses the second charging rate estimated value SOC ₂ ^ (k) until the predetermined time T elapses after the identification calculation is stopped and the predetermined time T elapses. The first charge rate estimated value SOC ₁ ^ (k) is used until the identification calculation is stopped again. Further, when switching from the second charging rate estimated value SOC ₂ ^ (k) to the first charging rate estimated value SOC ₁ ^ (k), if there is a difference between these values, the charging rate estimated value SOC ^ ( since a step in k) can be considered that occurs, in such a case, or subjected to a change rate limiter process to the charging rate estimated value SOC ^ (k), or the second charging rate estimated value SOC ₂ ^ (K) and the first charging rate estimated value SOC ₁ ^ (k) may be linearly interpolated.

The selection unit 312 is configured to change the predetermined time T according to the rate of change | 1- (R _r ^) / (R _S ^) | calculated by the identification calculation restart processing unit 310. To do. Specifically, | 1- (R _r ^) / (R _S ^) | is | 1- (R _r ^) / (R _S ^) | <β with respect to a predetermined second threshold value β. If there is a relationship, the predetermined time T is set to a relatively short time. If | 1- (R _r ^) / (R _S ^) | ≧ β, the predetermined time T is set to be relatively small. The configuration is such that a long time is set.

  The selection unit 312 may use a preset fixed value as the second threshold β, but in the present embodiment, the first threshold β is changed according to the battery temperature T (k). The configuration is as follows.

  Next, an estimation process of the battery parameter φ ^ (k) and the charging rate estimated value SOC ^ (k) in the second embodiment will be described using the flowchart shown in FIG. The process shown in FIG. 12 is performed at regular intervals (in this embodiment, every 100 msec). Note that the processing described below is performed by the electronic control unit 30.

  First, in steps S201 to S204, similarly to steps S101 to S204 (see FIG. 6) of the first embodiment described above, the current measurement value I (k), the voltage measurement value V (k), and the battery temperature T ( k) acquisition (step S201), calculation of the conversion state quantity ω (k) (step S202), calculation of the internal resistance estimated value R ^ (k) (step S203), and identification calculation by the adaptive identification calculation unit 305 Whether or not is stopped is determined (step S204). If the identification calculation stop process by the adaptive identification calculation unit 305 has not been performed and the identification calculation process has been performed in the previous process, the process proceeds to step S205. On the other hand, when the identification calculation by the adaptive identification calculation unit 305 is stopped, the process proceeds to step S207.

  In step 205, as in step S105 (see FIG. 6) of the first embodiment described above, the adaptive identification calculation unit 305 determines whether to stop the battery parameter φ ^ (k) identification calculation process. It is. If it is determined to continue the identification calculation process, the process proceeds to step S213, and the charging rate estimation process is performed. The charging rate estimation process in step S213 will be described later. On the other hand, if it is determined to stop the identification calculation process, the process proceeds to step S206.

In step S206, as in step S109 (see FIG. 6) of the first embodiment described above, the process of stopping the identification calculation of the battery parameter φ ^ (k), and the estimated internal resistance estimated value R _s ^ when the identification calculation is stopped, The battery parameter φ _s ^ when the identification calculation is stopped is stored in a RAM provided in the electronic control unit 30. Then, after step S206 ends, the process proceeds to step S213, and a charge rate estimation process described later is performed.

  On the other hand, in the above-described step S204, when the identification calculation by the adaptive identification calculation unit 305 is stopped, the process proceeds to step S207, and the identification is performed in the same manner as in step S110 (see FIG. 6) of the first embodiment described above. A determination is made whether the computation can be resumed. If it is determined that the identification calculation can be resumed, the process proceeds to step S208. On the other hand, if it is determined that the resumption of the identification calculation is impossible, the process proceeds to step S213, and a charge rate estimation process described later is performed.

In steps S208 to S211, similarly to steps S111 to S114 (see FIG. 6) of the first embodiment described above, the resumption process of the identification calculation (step S208), the change rate | 1- (R _r ^) / (R _S ^) | is less than the first threshold value α (step S209), and initial values of the battery parameters used for the identification calculation are set (steps S210 and S211).

In step S212, the selection unit 312 sets the predetermined time T. Specifically, the selection unit 312 compares the rate of change | 1- (R _r ^) / (R _S ^) | calculated in step S209 with a predetermined second threshold value β, and according to the comparison result. The predetermined time T is set. In step S212, after the initial value for the predetermined time T is set, the process proceeds to step S213, and a charge rate estimation process described later is performed.

  Next, the charging rate estimation process in step S213 will be described. FIG. 13 is a flowchart showing the charging rate estimation process in step S213.

  First, in step S301 shown in FIG. 13, in the above-described step S206, the adaptive identification calculation unit 305 has already stopped the identification calculation of the battery parameter φ ^ (k), and the adaptive identification calculation unit 305 performs the identification calculation. A determination is made whether or not the vehicle is stopped. If the identification calculation stop process by the adaptive identification calculation unit 305 is not performed and it is determined that the identification calculation process is being performed in the previous process, the process proceeds to step S302. On the other hand, if it is determined that the identification calculation by the adaptive identification calculation unit 305 is stopped, the process proceeds to step S307.

In steps S302 and S303, as in steps S106 and S107 (see FIG. 6) in the first embodiment described above, an identification calculation process (step for identifying battery parameter φ ^ (k) is performed by adaptive identification calculation unit 305. S302) and a calculation process (step S303) of the open circuit voltage estimated value V ₀ ^ (k) are performed.

In step S304, the first SOC estimation unit 307a uses the open circuit voltage estimated value V ₀ ^ (k) calculated in step S303, based on the predetermined open circuit voltage-charge rate characteristic of the secondary battery 10. Thus, the first charging rate estimated value SOC ₁ ^ (k) is calculated. The calculated first charging rate estimated value SOC ₁ ^ (k) is sent to the second SOC estimating unit 311 and the selecting unit 312.

Next, in step S305, it is determined whether or not a predetermined time T has elapsed after the adaptive identification calculation unit 305 executes the identification calculation resumption process. If it is determined that the predetermined time T has elapsed since the resumption process of the identification calculation is executed, the process proceeds to step S306. In step S306, the selection unit 312 selects the first SOC estimation unit 307a from the first SOC estimation unit 307a and the second SOC estimation unit 311, and in step S304, the first charge calculated by the first SOC estimation unit 307a. A process of setting rate estimation value SOC ₁ ^ (k) to charge rate estimation value SOC ^ (k) of secondary battery 10 is performed.

On the other hand, when it is determined in step S301 described above that the identification calculation is stopped, or even if the identification calculation is not stopped, the adaptive identification calculation unit 305 performs the identification calculation restart process in step S305 described above. If it is determined that the predetermined time T has not elapsed since the execution of step S307, the process proceeds to step S307. In step S307, the second SOC estimation unit 311 calculates the second charging rate estimated value SOC ₂ ^ (k). Specifically, the second SOC estimation unit 311 determines the charging rate estimated value SOC _s ^ (k) at the stop of the identification calculation, which is an estimated value of the charging rate estimated when the identification calculation is stopped, and the current detection acquired at step S201. Based on the value I (k), the second charging rate estimated value SOC ₂ ^ (k) is calculated by the current integration method. The calculated second charging rate estimated value SOC ₂ ^ (k) is sent to selection section 312.

Next, in step S308 following step S307, the selection unit 312 selects the second SOC estimation unit 311 from the first SOC estimation unit 307a and the second SOC estimation unit 311. In step S307, the second SOC estimation unit 311 calculates the second SOC estimation unit 311. The second charging rate estimated value SOC ₂ ^ (k) is set to the charging rate estimated value SOC ^ (k) of the secondary battery 10.
In the second embodiment, the estimated charging rate SOC ^ (k) of the secondary battery 10 is calculated as described above.

According to 2nd Embodiment, in addition to the effect of 1st Embodiment mentioned above, there exist the following effects.
That is, in the second embodiment, when the identification calculation for identifying the battery parameter φ ^ (k) is stopped, the charging rate of the secondary battery 10 is calculated by the second SOC estimation unit 311 based on the current integration method. After the predetermined time T has elapsed, the charging rate is estimated based on the battery parameter φ ^ (k) identified by the first SOC estimation unit 307a from the estimation of the charging rate by the current integration method. To do. In the second embodiment, the predetermined time T is a rate of change that is a change ratio between the estimated internal resistance value R _S ^ when the identification calculation is stopped and the estimated internal resistance value R _r ^ when the identification calculation is resumed. 1- (R _r ^) / (R _S ^) | That is, when there is a relationship of | 1- (R _r ^) / (R _S ^) | <β with respect to the predetermined second threshold value β, the predetermined time T is set to a relatively short time, In a case where 1− (R _r ^) / (R _S ^) | ≧ β, the predetermined time T is set to a relatively long time. Therefore, according to the second embodiment, when the rate of change | 1- (R _r ^) / (R _S ^) | is small, the charging rate is estimated based on the current integration method for an unnecessarily long time. As a result, it is possible to further improve the estimation accuracy of the charging rate.

In addition, according to the second embodiment, the above-described second threshold value β is changed according to the battery temperature T (k). Even if the rate of change of internal resistance value | 1- (R _r ^) / (R _S ^) | is the same when the identification calculation is stopped and restarted, if the battery temperature T (k) changes, the predetermined time T What is desirable as well may change. On the other hand, in the present embodiment, the predetermined time T can be set more appropriately by changing the second threshold value β according to the battery temperature T (k), thereby further improving the above effect. Can be increased.

  In the embodiment described above, the current detector 301 is the current detector of the present invention, the voltage detector 302 is the voltage detector of the present invention, the temperature detector 303 is the temperature detector of the present invention, and the state variable filter. The calculation unit 304 and the adaptive identification calculation unit 305 are the identification calculation unit of the present invention, the battery state estimation unit 308 is the state quantity estimation unit of the present invention, and the identification calculation stop processing unit 309 is the calculation stop processing unit and storage unit of the present invention. In addition, the identification calculation restart processing unit 310 is the calculation restart processing unit of the present invention, the open circuit voltage estimation unit 306 is the open circuit voltage estimation unit of the present invention, and the SOC estimation unit 307 and the first SOC estimation unit 307a are the first charge of the present invention. The second SOC estimation unit 311 corresponds to the rate estimation unit, the second charging rate estimation unit of the present invention, and the selection unit 312 corresponds to the selection unit of the present invention.

  As mentioned above, although embodiment of this invention was described, these embodiment was described in order to make an understanding of this invention easy, and was not described in order to limit this invention. Therefore, each element disclosed in the above embodiment is intended to include all design changes and equivalents belonging to the technical scope of the present invention.

  For example, in the above-described embodiment, when selecting the initial value of the battery parameter used when resuming the identification calculation, the internal state that is the main state quantity among the battery state quantities indicating the internal state of the secondary battery 10 is selected. Although the configuration is shown in which the resistance value is used and set based on the amount of change in the internal resistance value, the amount of change in the state amount other than the internal resistance value among the battery state amounts is obtained and used. It may be.

DESCRIPTION OF SYMBOLS 10 ... Secondary battery 20 ... Load 30 ... Electronic control unit 301 ... Current detection part 302 ... Voltage detection part 303 ... Temperature detection part 304 ... State variable filter calculation part 305 ... Adaptive identification calculation part 306 ... Open circuit voltage estimation part 307,307a ... SOC estimation unit (first SOC estimation unit)
308 ... Battery state estimation unit 309 ... Identification calculation stop processing unit 310 ... Identification calculation restart processing unit 311 ... Second SOC estimation unit 312 ... Selection unit 40 ... Ammeter 50 ... Voltmeter 60 ... Temperature sensor

Claims (10)

Current detection means for detecting the current of the secondary battery as a current measurement value;
Voltage detection means for detecting the terminal voltage of the secondary battery as a voltage measurement value;
Temperature detecting means for detecting a battery temperature of the secondary battery;
A battery model of the secondary battery is defined, a terminal voltage of the secondary battery based on the battery model is estimated as a voltage estimated value based on the current measurement value and the voltage measurement value, and based on the voltage measurement value Identification calculation means for performing an identification calculation for collectively estimating battery parameters of the battery model so that a difference between the measured value and the voltage estimated value converges to zero,
A state quantity estimating means for estimating a battery state quantity indicating an internal state of the secondary battery;
It is determined whether or not to stop the identification calculation by the identification calculation means, and when it is determined to stop the identification calculation, calculation stop processing means for stopping the identification calculation;
Storage that saves the battery parameter and the battery state quantity at the time of stopping the identification calculation estimated by the identification calculation means and the state quantity estimation means when the identification calculation stop process is performed by the calculation stop processing means Means,
When the identification calculation is stopped, it is determined whether to restart the identification calculation, and when it is determined that the identification calculation is to be restarted, calculation restart processing means for performing the identification calculation restart processing, Prepared,
When resuming the identification calculation, the calculation resumption processing means calculates a change amount of the battery state quantity when the identification calculation is resumed with respect to a battery state quantity when the identification calculation is stopped. If it is less than one threshold, a battery parameter storage value stored in the storage means is set as an initial value of the battery parameter used when resuming the identification calculation, and the amount of change is greater than or equal to the first threshold. Is a battery state estimation device that sets a predetermined value as an initial value of a battery parameter used when resuming the identification calculation. In the battery state estimation device according to claim 1,
A battery state estimation device using a predetermined value set according to at least one of a battery temperature, a battery deterioration degree, and a battery charge rate as the initial value. The battery state estimation device according to claim 1 or 2,
An open-circuit voltage estimating means for estimating an open-circuit voltage of the secondary battery based on the parameter identified by the identification calculating means;
First charge rate estimating means for estimating the charge rate of the secondary battery based on the relationship between the open circuit voltage and the charge rate obtained in advance from the open circuit voltage estimated by the open circuit voltage estimating means. A battery state estimation device. The battery state estimation apparatus according to any one of claims 1 to 3,
The battery state quantity is an internal resistance value of the secondary battery,
The state quantity estimating means calculates the internal resistance value based on the battery temperature detected by the temperature detecting means,
The calculation restart processing means is based on whether or not an internal resistance change amount, which is a ratio between the internal resistance value at the time when the identification calculation is stopped and the internal resistance value when the identification calculation is restarted, is equal to or greater than the first threshold value. An initial value of a battery parameter used when resuming the identification calculation is set. In the battery state estimation device according to claim 3,
The battery state quantity is an internal resistance value of the secondary battery,
The state quantity estimating means calculates the internal resistance value based on at least one of the battery temperature detected by the temperature detecting means and the charging rate estimated by the first charging rate estimating means,
The calculation restart processing means is based on whether or not an internal resistance change amount, which is a ratio between the internal resistance value at the time when the identification calculation is stopped and the internal resistance value when the identification calculation is restarted, is equal to or greater than the first threshold value. An initial value of a battery parameter used when resuming the identification calculation is set. In the battery state estimation device according to any one of claims 1 to 5,
The battery resumption processing unit, wherein the calculation resumption processing unit changes the first threshold according to the battery temperature. In the battery state estimation device according to any one of claims 3 to 6,
Second charge rate estimating means for estimating the charge rate of the secondary battery by a method different from the first charge rate estimating means;
Selecting means for selecting whether to estimate the charging rate of the secondary battery by the first charging rate estimating unit or the second charging rate estimating unit;
The selection means switches from the first charging rate estimation means to the second charging rate estimation means when the calculation stop processing means determines to stop the identification calculation, and charges the secondary battery. When the calculation resumption processing means determines that the identification calculation is to be resumed, the second charge rate estimation means causes the first charging after a predetermined time has elapsed since the identification calculation was resumed. A battery state estimation device that switches to a rate estimation means and estimates the charge rate of the secondary battery. The battery state estimation apparatus according to claim 7,
The selection means sets the length of the predetermined time according to the amount of change in the battery state quantity at the time of resuming the identification calculation, with respect to the battery state quantity at the time of the stop of the identification calculation calculated by the calculation resumption processing means. A battery state estimation device characterized by: The battery state estimation device according to claim 8,
The selection means sets the predetermined time shorter when the change amount is less than a predetermined second threshold value, compared with a case where the change amount is equal to or more than the second threshold value. Battery state estimation device. The battery state estimation device according to claim 9,
The battery state estimation device, wherein the selection unit changes the second threshold value according to the battery temperature.

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