JP6428402B2 - Battery energy prediction device - Google Patents

Description

  The present invention relates to a battery energy prediction apparatus that predicts the remaining energy of a secondary battery based on a battery model of a secondary battery.

  2. Description of the Related Art Conventionally, as can be seen in Patent Document 1 below, a technique is known for grasping how long an EV travel mode in which a vehicle is driven by a motor generator alone, which is a vehicle-mounted main machine, can be continued. In this technology, first, the required output is output from the secondary battery over a specified time from the present for each case where the secondary battery charge rate (SOC) is temporarily set to various values from 0 to 100%. The voltage between the terminals of the secondary battery when it is assumed to continue is calculated in relation to the charging rate. Here, a battery model in which the internal resistance is modeled by a DC resistance is used for the calculation of the inter-terminal voltage.

  And among the voltages between the terminals of the secondary battery calculated in association with the charging rate, the charging rate corresponding to the allowable lower limit value of the voltage between the terminals of the secondary battery is calculated as the lower limit charging rate. Then, the energy of the secondary battery that can be used until the current charging rate of the secondary battery decreases to a threshold charging rate that is higher than the lower limit charging rate is predicted as the energy margin. According to this energy margin, it is possible to grasp how long the EV travel mode can be continued.

JP2012-103131A

  Here, the battery model described in Patent Document 1 does not have a configuration capable of expressing the characteristics of the current-voltage nonlinear region of the secondary battery. Specifically, the current-voltage nonlinear characteristic of the secondary battery becomes more dominant as the secondary battery becomes colder, and the nonlinear characteristic cannot be ignored particularly in the region of 0 ° C. or lower. Therefore, in the technique described in Patent Document 1, the accuracy of predicting the energy margin when the secondary battery is at a low temperature is lowered, and the grasping accuracy of how long the EV travel mode can be continued may be lowered.

  The main object of the present invention is to provide a battery energy prediction device capable of improving the accuracy of predicting the residual energy of a secondary battery even when the secondary battery is at a low temperature.

  Hereinafter, means for solving the above-described problems and the operation and effects thereof will be described.

  The present invention relates to a battery energy predicting apparatus that predicts the remaining energy of the secondary battery based on the battery model of the secondary battery (20a), wherein the battery model represents a DC resistance (Rs) of the secondary battery. A DC resistance model, a model representing the reaction resistance of the secondary battery, a reaction resistance model including a reaction resistance parameter (β) derived from a Butler-Volmer equation and correlated with an exchange current density, a resistance and a capacitor RC equivalent circuit model including a parallel connection body, and a diffusion resistance model representing a diffusion resistance of the secondary battery, and based on the battery model, over a period until a specified time elapses from now Voltage prediction means for calculating a predicted voltage that is a voltage across the terminals of the secondary battery when it is assumed that the required power continues to be output from the secondary battery, a charging rate of the secondary battery, and the Storage means (31) for storing relationship information in which the charging rate, the temperature of the secondary battery, and the predicted voltage are related in advance so that the predicted voltage becomes lower as the temperature of each secondary battery becomes lower; The difference between the predicted voltage derived from the relationship information using each of the current charging rate of the secondary battery and the current temperature of the secondary battery as input, and the predicted voltage calculated by the voltage predicting unit. A correction unit that corrects the relationship information so as to match, and the charge rate when the predicted voltage is an allowable lower limit value of the inter-terminal voltage of the secondary battery in the relationship information corrected by the correction unit; Based on the corrected relationship information, the charging rate is defined as the energy of the secondary battery that can be used before the current charging rate of the secondary battery decreases to the lower limit charging rate. And an energy predicting means for predicting the remaining energy.

  In the above invention, the voltage between the terminals of the secondary battery is defined as the predicted voltage when it is assumed that the required power is continuously output from the secondary battery over the period from the present until the specified time elapses. In the above invention, the relationship information in which the charging rate, the temperature of the secondary battery, and the predicted voltage are related in advance is stored so that the predicted voltage decreases as the charging rate of the secondary battery and the temperature of the secondary battery decrease. Stored in the means. Then, the charging rate when the predicted voltage is the allowable lower limit value of the inter-terminal voltage of the secondary battery in the relationship information is defined as the lower limit charging rate, and the current charging rate of the secondary battery is the lower limit charging based on the relationship information. The energy of the secondary battery that can be used until the rate drops is predicted as the remaining energy.

  Here, the relationship information stored in the storage means may deviate from the relationship information representing the actual characteristics of the secondary battery due to the progress of deterioration of the secondary battery, individual differences of the secondary battery, and the like. In this case, there is a concern that the prediction accuracy of the remaining energy of the secondary battery based on the relationship information may be reduced.

  Therefore, in the above invention, first, the predicted voltage is calculated by the voltage predicting means. Here, in order to calculate the predicted voltage, a battery model including a reaction resistance model is used in addition to the DC resistance model and the diffusion resistance model. The reaction resistance model is a parameter correlated with the Butler-Volmer exchange current density, and includes a reaction resistance parameter correlated with the temperature of the secondary battery. By including this reaction resistance model in the battery model, for example, the current-voltage non-linear characteristic at low temperatures that could not be expressed by the battery model described in Patent Document 1 can be expressed with high accuracy. For this reason, in the said invention, the calculation precision of an estimated voltage can be improved also at the time of the low temperature of a secondary battery.

  And in the said invention, it is related so that the shift | offset | difference of the prediction voltage derived | led-out from the relationship information by inputting each of the present charging rate and the present temperature of a secondary battery, and the prediction voltage calculated by the voltage prediction means may correspond. Correct the information. By correcting the related information, the lower limit charging rate is updated. Since the calculation accuracy of the predicted voltage can be improved even when the secondary battery is at a low temperature, the correction accuracy of the related information can be improved.

  Then, based on the corrected relationship information, the secondary battery energy that can be used until the current charging rate of the secondary battery decreases to the updated lower limit charging rate is predicted as the remaining energy. Thereby, the prediction accuracy of the residual energy of the secondary battery can be improved even at the low temperature of the secondary battery.

The lineblock diagram of the battery pack concerning a 1st embodiment. The block diagram which shows the process of battery ECU. The figure which shows a battery model. The block diagram which shows the process of a DC resistance voltage calculation part. The block diagram which shows the process of the reaction resistance voltage calculation part. The figure which shows the relationship between a reaction resistance parameter and battery temperature. The figure which shows the temperature dependence of the electric current-voltage characteristic in reaction resistance. The block diagram which shows the process of a polarization voltage calculation part. The figure which shows a constant power characteristic map. The figure which shows the prediction method of the residual energy using a constant power characteristic map. The flowchart which shows the correction process of a constant power characteristic map. The time chart which shows transition of each voltage. The figure which shows the correction method of a constant power characteristic map. The figure which shows the correction method of the constant power characteristic map concerning 2nd Embodiment.

(First embodiment)
Hereinafter, a first embodiment of the present invention will be described with reference to the drawings. The present embodiment is applied to, for example, a rotating electric machine (motor generator) as an in-vehicle main machine and a vehicle (for example, a hybrid car) including an engine, and a vehicle (for example, an electric car) including only a motor generator as the in-vehicle main machine.

  As shown in FIG. 1, the battery pack 10 includes an assembled battery 20 and a battery ECU 30. The assembled battery 20 is composed of a series connection body of a plurality of battery cells 20a, and exchanges power with a motor generator or the like (not shown). The battery cell 20a is a secondary battery, and a lithium ion secondary battery is used in this embodiment.

  The battery pack 10 includes a voltage sensor 21, a temperature sensor 22, and a current sensor 23. The voltage sensor 21 is voltage detection means for detecting the voltage between the terminals of each battery cell 20a. The temperature sensor 22 is temperature detection means for detecting the temperature of the assembled battery 20 (each battery cell 20a). The current sensor 23 is current detection means for detecting a charge / discharge current flowing through the assembled battery 20 (each battery cell 20a).

  The battery ECU 30 is configured as a computer including a CPU, a memory 31 as storage means, and an I / O (not shown). The CPU includes a single cell calculation unit 32 and an energy prediction unit 33 corresponding to each of the plurality of battery cells 20a. Detection values of the voltage sensor 21, the temperature sensor 22, and the current sensor 23 are input to the battery ECU 30.

  The battery ECU 30 performs processing for predicting the remaining energy of the assembled battery 20. Hereinafter, this prediction process will be described in the order of the single cell calculation unit 32 and the energy prediction unit 33.

<1. Processing of Single Cell Operation Unit 32>
With reference to FIG. 2, an outline of processing performed by each single cell arithmetic unit 32 (CPU) will be described. The single cell calculation unit 32 includes a DC resistance voltage calculation unit 34, a reaction resistance voltage calculation unit 35, a polarization voltage calculation unit 36, an SOC conversion unit 37, and the like.

  Each calculation part 34-36 estimates each parameter of the battery cell 20a shown in FIG. Here, FIG. 3 shows a battery model expressing the internal impedance and the like of each battery cell 20a. In the present embodiment, the battery model is represented as a series connection body of a DC resistance model, a reaction resistance model, and a diffusion resistance model. In FIG. 3, “Rs” indicates a direct current resistance representing the current resistance of the solution or the electrode, and “Vs” indicates a potential difference (hereinafter referred to as direct current resistance voltage) in the direct current resistance Rs. “Vbv” indicates a potential difference in reaction resistance (hereinafter referred to as reaction resistance voltage) representing an electrode interface reaction between the positive electrode and the negative electrode. “Rw1, Rw2, Rw4, Rw4” indicates a resistance component term in diffusion resistance representing ion diffusion in the active material or solution, and “Cw1, Cw2, Cw3, Cw4” indicates that the resistance changes with time. , “Vw1, Vw2, Vw3, Vw4” indicates the polarization voltage at each diffused resistor. In the present embodiment, the diffusion resistor has a configuration in which a plurality of parallel connection bodies of resistance components and capacitance components (four in this embodiment) are connected in series. An equivalent circuit in which a resistance component and a capacitance component are connected in parallel is called a Foster-type equivalent circuit.

  In the present embodiment, the reaction resistance model shown in FIG. 3 is represented only by DC resistance for convenience, and the time constant in the model is ignored. This is because in this embodiment, one processing cycle of the single cell calculation unit 32 (CPU) is set sufficiently longer than the time constant in the reaction resistance.

  First, the DC resistance voltage calculation unit 34 will be described with reference to FIG.

  In the DC resistance voltage calculation unit 34, the Rs calculation unit 34 a calculates the DC resistance Rs based on the battery temperature Ts detected by the temperature sensor 22. The reason why the battery temperature Ts is used for calculating the DC resistance Rs is that the DC resistance Rs depends on the temperature of the battery cell 20a. In the present embodiment, the DC resistance Rs is calculated using an Rs map in which the DC resistance Rs and the battery temperature Ts are related in advance. In the present embodiment, the Rs map is adapted such that the higher the battery temperature Ts, the lower the DC resistance Rs. In the present embodiment, the Rs map is stored in the memory 31.

  The first multiplication unit 34b calculates a DC resistance voltage Vs as a multiplication value of the DC resistance Rs calculated by the Rs calculation unit 34a and a current detected by the current sensor 23 (hereinafter, detected current Is). Incidentally, in this embodiment, the discharge current of the battery cell 20a is represented by a negative value. For this reason, in this embodiment, the DC resistance voltage Vs becomes a negative value when the battery cell 20a is discharged.

  Next, the reaction resistance voltage calculation unit 35 will be described with reference to FIG.

  In the reaction resistance voltage calculation unit 35, the β calculation unit 35a calculates a reaction resistance parameter β based on the battery temperature Ts. The battery temperature Ts is used to calculate the reaction resistance parameter β because the reaction resistance parameter β depends on the temperature of the battery cell 20a. In the present embodiment, the reaction resistance parameter β is calculated using a β map in which the natural logarithm “lnβ” of the reaction resistance parameter β and the battery temperature Ts (absolute temperature) are related in advance. Hereinafter, the reaction resistance parameter β will be described.

  The Butler-Volmer equation in electrochemistry is represented by the following equation (eq1).

上式（ｅｑ１）において、「ｉ」は電流密度を示し、「ｉｏ」は交換電流密度を示し、「αｓ」は電極反応の移動係数（酸化反応）を示し、「ｎ」は電荷数を示し、「Ｆ」はファラデー定数を示し、「η」は過電圧を示し、「Ｒ」は気体定数を示し、「Ｔ」は絶対温度を示す。

In the above equation (eq1), “i” represents the current density, “io” represents the exchange current density, “αs” represents the transfer coefficient (oxidation reaction) of the electrode reaction, and “n” represents the number of charges. , “F” indicates a Faraday constant, “η” indicates an overvoltage, “R” indicates a gas constant, and “T” indicates an absolute temperature.

  In the above equation (eq1), for the sake of simplicity, assuming that the positive and negative electrodes are equivalent (that is, the charge / discharge efficiency is the same) and “a = αs = 1−αs”, the above equation (eq1) is the following equation (eq2): Become.

双曲線正弦関数と指数関数との関係を用いて、上式（ｅｑ２）を下式（ｅｑ３）のように変形する。

Using the relationship between the hyperbolic sine function and the exponential function, the above equation (eq2) is transformed into the following equation (eq3).

上式（ｅｑ３）を過電圧ηについて解くと、下式（ｅｑ４）となる。

When the above equation (eq3) is solved for the overvoltage η, the following equation (eq4) is obtained.

一方、過電圧ηと反応抵抗電圧Ｖｂｖとの関係を、比例定数γを用いて下式（ｅｑ５）で表す。また、電流密度ｉと電池セルに流れる電流Ｉとの関係を、比例定数γを用いて下式（ｅｑ６）で表す。

On the other hand, the relationship between the overvoltage η and the reaction resistance voltage Vbv is expressed by the following equation (eq5) using the proportionality constant γ. Further, the relationship between the current density i and the current I flowing through the battery cell is expressed by the following equation (eq6) using a proportional constant γ.

上式（ｅｑ４）に上式（ｅｑ５），（ｅｑ６）を代入すると、下式（ｅｑ７）が導かれる。

Substituting the above equations (eq5) and (eq6) into the above equation (eq4) leads to the following equation (eq7).

ここで、上式（ｅｑ７）を下式（ｅｑ８）のように整理する。

Here, the above equation (eq7) is arranged as the following equation (eq8).

上式（ｅｑ８）において、「β」は上記反応抵抗パラメータを示し、「α」は定数を示し、「γ」は適合定数を示し、電池セルに流れる充放電電流Ｉと反応抵抗電圧Ｖｂｖとを反応抵抗パラメータβによって関係付けることが可能なことを示している。上式（ｅｑ８）からわかるように、バトラーボルマー式から導かれる反応抵抗パラメータβは、電池セルに流れる電流を独立変数とし、反応抵抗電圧Ｖｂｖを従属変数とする逆双曲線正弦関数において、逆双曲線正弦関数と反応抵抗電圧Ｖｂｖとの関係を定める係数となる。

In the above equation (eq8), “β” represents the reaction resistance parameter, “α” represents a constant, “γ” represents a conformance constant, and the charge / discharge current I flowing through the battery cell and the reaction resistance voltage Vbv are expressed as follows. It shows that it can be related by the reaction resistance parameter β. As can be seen from the above equation (eq8), the reaction resistance parameter β derived from the Butler-Volmer equation is an inverse hyperbola in an inverse hyperbolic sine function with the current flowing through the battery cell as an independent variable and the reaction resistance voltage Vbv as a dependent variable. This is a coefficient that determines the relationship between the sine function and the reaction resistance voltage Vbv.

  Here, since the exchange current density io depends on the battery temperature T, the reaction resistance parameter β also depends on the battery temperature T. For this reason, in the present embodiment, according to the Arrhenius plot, a β map in which the natural logarithm of the reaction resistance parameter β is adapted to be the inverse of the battery temperature Ts or a linear expression with respect to the battery temperature Ts is stored in the memory 31. Yes. Here, FIG. 6 illustrates a β map in which the natural logarithm of the reaction resistance parameter β is adapted in the form of a linear expression with respect to the reciprocal of the battery temperature Ts.

  Returning to the description of FIG. 5, the reaction resistance parameter β calculated by the β calculator 35a is input to the potential difference calculator 35b. The potential difference calculating unit 35b receives the reaction resistance parameter β and the detected current Is as inputs, and calculates the reaction resistance voltage Vbv based on the above equation (eq8). As shown in FIG. 7, the above equation (eq8) is an equation in which the reaction resistance voltage Vbv becomes nonlinear with respect to the current when the temperature becomes low. When the temperature of the battery cell is low, the reaction resistance voltage Vbv that accurately represents the current-voltage nonlinear characteristic can be calculated by using the reaction resistance parameter β.

  Next, the polarization voltage calculation unit 36 will be described with reference to FIG. The polarization voltage calculator 36 calculates a parameter related to the diffusion resistance. Hereinafter, after describing parameters related to the diffusion resistance, a method for calculating the polarization voltage will be described.

  Based on the diffusion equation in electrochemistry, the Warburg impedance Z relating to the diffusion resistance is derived. Here, the impedance Z is expressed by the following equation (eq9).

上式（ｅｑ９）において、分子は、起電圧が物質の表面濃度の自然対数に比例することを示すネルンストの式に基づくものである。分子において、「Ｃｏ」は平均濃度を示し、「ΔＣ」は平均濃度Ｃｏに対する濃度変化を示し、「ｘ」は電極からの位置を示す。分母は、単位時間に単位面積を通過する物質量が濃度勾配に比例することを示すフィックの第１法則に基づくものである。分母において、「Ｄ」は拡散係数を示す。

In the above equation (eq9), the numerator is based on the Nernst equation indicating that the electromotive force is proportional to the natural logarithm of the surface concentration of the substance. In the molecule, “Co” indicates an average concentration, “ΔC” indicates a concentration change with respect to the average concentration Co, and “x” indicates a position from the electrode. The denominator is based on Fick's first law indicating that the amount of a substance passing through a unit area per unit time is proportional to the concentration gradient. In the denominator, “D” indicates a diffusion coefficient.

  By arranging the above equation (eq9), the following equation (eq10) is derived.

ここで、電極に交流電圧を印加した場合において、電圧が正弦波で変化すると、濃度も正弦波で変化すると仮定する。このとき、濃度変化ΔＣを虚数ｊと角速度ωとを用いて下式（ｅｑ１１）で表すこととする。

Here, it is assumed that when an AC voltage is applied to the electrodes, if the voltage changes with a sine wave, the concentration also changes with a sine wave. At this time, the density change ΔC is expressed by the following equation (eq11) using the imaginary number j and the angular velocity ω.

上式（ｅｑ１１）において、｜Δｖ｜，｜ΔＣ｜は複素振幅を示す。ここで、フィックの第２法則は下式（ｅｑ１２）で表される。

In the above equation (eq11), | Δv | and | ΔC | indicate complex amplitudes. Here, Fick's second law is expressed by the following equation (eq12).

上式（ｅｑ１２）の左辺は、上式（ｅｑ１１）の時間微分値であるので「ｊωΔＣ」となる。このため、上式（ｅｑ１２）の一般解は、定数ｋ１，ｋ２を用いて下式（ｅｑ１３）で表わされる。

The left side of the above equation (eq12) is “jωΔC” because it is the time differential value of the above equation (eq11). For this reason, the general solution of the above equation (eq12) is expressed by the following equation (eq13) using the constants k1 and k2.

ここで、「Ｌ」を拡散長として定義する。「ｘ＝Ｌ」となる場合に濃度変化ΔＣが０になるとの条件を課すと、上式（ｅｑ１３）は下式（ｅｑ１４）となる。

Here, “L” is defined as the diffusion length. When the condition that the density change ΔC is 0 when “x = L” is imposed, the above equation (eq13) becomes the following equation (eq14).

したがって、濃度変化ΔＣは、下式（ｅｑ１５）で表される。

Therefore, the concentration change ΔC is expressed by the following equation (eq15).

上式（ｅｑ１５）をｘで偏微分すると、下式（ｅｑ１６）となる。

When the above equation (eq15) is partially differentiated by x, the following equation (eq16) is obtained.

上式（ｅｑ１５），（ｅｑ１６）を上式（ｅｑ１０）に代入すると、上式（ｅｑ１０）の一部が下式（ｅｑ１７）のように表される。

When the above equations (eq15) and (eq16) are substituted into the above equation (eq10), a part of the above equation (eq10) is expressed as the following equation (eq17).

したがって、上式（ｅｑ１０）のワールブルグインピーダンスＺは、ラプラス演算子ｓ（＝ｊ×ω）を用いて、下式（ｅｑ１８）で表すことができる。

Therefore, the Warburg impedance Z of the above equation (eq10) can be expressed by the following equation (eq18) using the Laplace operator s (= j × ω).

本実施形態では、「Ｒｄ」を第１パラメータと称し、「τｄ」を第２パラメータと称すこととする。ここで、拡散係数Ｄは下式（ｅｑ１９）で表される。

In the present embodiment, “Rd” is referred to as a first parameter, and “τd” is referred to as a second parameter. Here, the diffusion coefficient D is expressed by the following equation (eq19).

上式（ｅｑ１９）において、「Ｄｏ」は温度に依存しない定数を示し、「Ｅ」は活性化エネルギを示す。上式（ｅｑ１９）を用いると、第１，第２パラメータＲｄ，τｄは、下式（ｅｑ２０）で表される。

In the above equation (eq19), “Do” represents a temperature independent constant, and “E” represents activation energy. When the above equation (eq19) is used, the first and second parameters Rd, τd are represented by the following equation (eq20).

上式（ｅｑ２０）は、第１，第２パラメータＲｄ，τｄが電池温度Ｔに依存することを示している。上式（ｅｑ２０）の自然対数をとると、下式（ｅｑ２１）が導かれる。

The above equation (eq20) indicates that the first and second parameters Rd, τd depend on the battery temperature T. Taking the natural logarithm of the above equation (eq20), the following equation (eq21) is derived.

本実施形態では、アレニウスプロットに従って、第１，第２パラメータＲｄ，τｄの自然対数を、電池温度Ｔの逆数、又は電池温度Ｔｓに対する１次式となる形で適合したＲｄマップ，τｄマップをメモリ３１に記憶させている。

In this embodiment, according to the Arrhenius plot, an Rd map and τd map in which the natural logarithm of the first and second parameters Rd and τd is adapted to be a reciprocal of the battery temperature T or a linear expression for the battery temperature Ts are stored in the memory. 31 is stored.

  In the polarization voltage calculation unit 36, the Rd calculation unit 36a calculates the first parameter Rd using the Rd map and the battery temperature Ts described above. The τd calculation unit 36b calculates the second parameter τd using the τd map and the battery temperature Ts described above.

  Based on the first parameter Rd, the resistance component calculation unit 36c calculates the resistance values Rw1 to Rw4 of the first to fourth resistances constituting the diffusion resistance by the following equation (eq22).

上式（ｅｑ２２）において、「ｍ」は正の整数（本実施形態では、ｍ＝１，２，３，４）を示す。容量成分算出部３６ｄは、第１，第２パラメータＲｄ，τｄに基づいて、拡散抵抗を構成する第１〜第４キャパシタの各容量Ｃｗ１〜Ｃｗ４を下式（ｅｑ２３）によって算出する。

In the above formula (eq22), “m” represents a positive integer (in this embodiment, m = 1, 2, 3, 4). The capacitance component calculation unit 36d calculates the capacitances Cw1 to Cw4 of the first to fourth capacitors constituting the diffusion resistance based on the first and second parameters Rd and τd by the following equation (eq23).

上式（ｅｑ２２），（ｅｑ２３）によって第ｍ抵抗の抵抗値Ｒｗｍ，第ｍキャパシタの容量Ｃｗｍを算出できるのは、上式（ｅｑ１８）によって表されるワールブルグインピーダンスに合致する等価回路と、ワールブルグインピーダンスと等価になる級数化された等価回路の定数の法則性とを、本発明者らが文献等によって調べた結果に基づくものである。なお、上記文献としては、例えば、「Ｍｏｄｅｌｌｉｎｇ Ｎｉ−ｍＨ ｂａｔｔｅｒｙ ｕｓｉｎｇ Ｃａｕｅｒ ａｎｄ Ｆｏｓｔｅｒ ｓｔｒｕｃｔｕｒｅｓ． Ｅ．Ｋｕｈｎ ｅｔ ａｌ．ＪＯＵＮＡＬ ｏｆ Ｐｏｗｅｒ Ｓｏｕｒｓｅｓ １５８（２００６）」がある。

The resistance value Rwm of the m-th resistor and the capacitance Cwm of the m-th capacitor can be calculated by the above equations (eq22) and (eq23) because an equivalent circuit that matches the Warburg impedance represented by the above equation (eq18) and the Warburg impedance This is based on the result of investigation by the inventors of the literature on the constant law of the equivalent circuit in the series equivalent to the above. In addition, as said literature, there exists "Modeling Ni-mH battery using Cauer and Foster structures. E. Kuhn et al. JOUNAL of Power Sources 158 (2006)", for example.

  The first voltage calculation unit 36e is based on the detection current Is, the first resistance value Rw1 calculated by the resistance component calculation unit 36c, and the first capacitance Cw1 calculated by the capacitance component calculation unit 36d. A first polarization voltage Vw1 is calculated. In the present embodiment, the current first polarization voltage Vw1 is sequentially calculated based on an expression obtained by discretizing a transfer function representing a parallel circuit of a resistor and a capacitor constituting the diffusion resistance model. Specifically, in the present embodiment, the first polarization voltage Vw1 calculated in the previous processing cycle, the detection current Is in the previous processing cycle, and the current (current processing cycle) detection current Is are input. The first polarization voltage Vw1 is calculated using the following equation (eq24).

上式（ｅｑ２４）において、「ΔＴ」は１処理周期を示す。なお、第２，第３，第４電圧算出部３６ｆ，３６ｇ，３６ｈも、第１電圧算出部３６ｅと同様に、抵抗値Ｒｗ２，Ｒｗ３，Ｒｗ４と、容量Ｃｗ２，Ｃｗ３，Ｃｗ４と、電池セル２０ａに流れる電流Ｉｐとに基づいて、現在の第２，第３，第４分極電圧Ｖｗ２，Ｖｗ３，Ｖｗ４を算出する。なお本実施形態において、第１〜第４電圧算出部３６ｅ〜３６ｈが「第１分極電圧算出手段」に相当する。

In the above equation (eq24), “ΔT” indicates one processing cycle. Similarly to the first voltage calculation unit 36e, the second, third, and fourth voltage calculation units 36f, 36g, and 36h also have resistance values Rw2, Rw3, and Rw4, capacitances Cw2, Cw3, and Cw4, and a battery cell 20a. Current second, third and fourth polarization voltages Vw2, Vw3 and Vw4 are calculated based on the current Ip flowing through In the present embodiment, the first to fourth voltage calculators 36e to 36h correspond to “first polarization voltage calculator”.

  Returning to the description of FIG. 2, the first addition unit 38 calculates the total polarization voltage Vwt as an addition value of the polarization voltages Vw1 to Vw4 calculated by the voltage calculation units 36e to 36h. The second addition unit 39 calculates an addition value of the DC resistance voltage Vs, the reaction resistance voltage Vbv, and the total polarization voltage Vwt. The open end voltage calculation unit 40 calculates the open end voltage OCV of the battery cell 20a by subtracting the output value of the second addition unit 39 from the inter-terminal voltage CCV of the battery cell 20a detected by the voltage sensor 21.

  The SOC conversion unit 37 calculates the charging rate SOCr of the battery cell 20a based on the open-circuit voltage OCV calculated by the open-circuit voltage calculation unit 40. In the present embodiment, the charging rate SOCr is calculated using an SOC map in which the open-circuit voltages OCV and SOCr are related in advance. In the present embodiment, the SOC map is stored in the memory 31.

<2. Processing of Energy Predictor 33>
Next, the remaining energy prediction process of the assembled battery 20 performed by the energy predicting unit 33 will be described. This process is a process for predicting the remaining energy Ebat [Wh] of the assembled battery 20 when it is assumed that the required power Ptgt has been continuously output from the assembled battery 20 over the period from the present until the specified time Tff elapses. is there. The reason why the prediction target is energy is that it is easy to use for vehicle travel control. The required power Ptgt can be set as follows, for example, as shown in FIG.

  A specific example when the battery ECU 30 is mounted on a hybrid vehicle will be described. In this case, the required power Ptgt is used to start the engine in a situation where only the first motor generator is driven to rotate among the engine as the main engine and the first motor generator and the vehicle is traveling in the EV traveling mode. The electric power required for the second motor generator is set. In this case, by predicting the residual energy Ebat, it is possible to grasp how much the vehicle can travel in the EV traveling mode while securing energy for starting the engine.

  A specific example when the battery ECU 30 is mounted on an electric vehicle will be described. In this case, the required power Ptgt is set to the power required for the main motor generator for accelerating the vehicle in a situation where the vehicle is traveling in the EV traveling mode.

  In the present embodiment, the remaining energy Ebat of the assembled battery 20 is predicted using a constant power characteristic map stored in the memory 31. The constant power characteristic map is provided corresponding to each battery cell 20a. As shown in FIG. 9, the constant power characteristic map shows the relationship between the charging rate SOC and the predicted voltage Vff so that the predicted voltage Vff continuously decreases as the charging rate SOC and the battery temperature T of the battery cell 20a decrease. Is map information defined for each battery temperature T. FIG. 9 illustrates battery temperatures T of −30 ° C., −20 ° C., 25 ° C., 50 ° C., and 60 ° C. Here, the predicted voltage Vff is a voltage between the terminals of the battery cell 20a when it is assumed that the required power Ptgt is continuously output from the assembled battery 20 over a period from the current time until the specified time Tff elapses. According to the constant power characteristic map, it is not necessary to temporarily set the charging rate SOC to various values and calculate the predicted voltage Vff each time, so that the calculation load of the CPU can be reduced.

  First, the energy prediction unit 33 receives the current battery temperature Ts as input, and selects map information that defines the relationship between the charging rate SOC and the predicted voltage Vff corresponding to the current battery temperature Ts from the constant power characteristic map. Then, as shown in FIG. 10, the energy Ecell of each battery cell 20a that can be used until the charging rate of the battery cell 20a decreases from the current charging rate SOCr to the lower limit charging rate Smin is calculated by the following equation (eq25). . Here, the lower limit charging rate Smin is a charging rate at which the predicted voltage Vff becomes an allowable lower limit value of the inter-terminal voltage of the battery cell 20a (hereinafter, allowable lower limit voltage Vmin). FIG. 10 illustrates a region indicating the remaining energy Ecell when the battery temperature Ts is −20 ° C.

上式（ｅｑ２５）において、「Ａｈｆ」は電池セル２０ａの満充電容量を示す。満充電容量Ａｈｆは、電池温度Ｔｓに依存する。満充電容量Ａｈｆは、例えば上記特許文献１に記載されているように、電池セル２０ａの充電率が第１充電率ＰＡとなってから第２充電率ＰＢとなるまでの期間における電池セル２０ａの充放電電流の時間積分値を、第１充電率ＰＡと第２充電率ＰＢとの差の絶対値で除算することにより算出すればよい。

In the above equation (eq25), “Ahf” indicates the full charge capacity of the battery cell 20a. The full charge capacity Ahf depends on the battery temperature Ts. For example, as described in Patent Document 1, the full charge capacity Ahf is the battery cell 20a in the period from when the charge rate of the battery cell 20a becomes the first charge rate PA to the second charge rate PB. What is necessary is just to calculate by dividing the time integration value of charging / discharging current by the absolute value of the difference between 1st charge rate PA and 2nd charge rate PB.

  And the residual energy Ebat of the assembled battery 20 is estimated as a total value of the residual energy Ecell of each battery cell 20a calculated using the above equation (eq25).

  Here, the constant power characteristic map stored in advance in the memory 31 due to the progress of the deterioration of the battery cell 20a or the individual difference of the battery cells 20a represents the actual power characteristic of the battery cell 20a. Can deviate from the map. In this case, there is a concern that the prediction accuracy of the remaining energy Ebat of the assembled battery 20 is lowered. Therefore, in the present embodiment, correction processing for correcting the constant power characteristic map is performed. Hereinafter, the correction method will be described.

  FIG. 11 shows the procedure of the constant power characteristic map correction process. This process is executed by the energy prediction unit 33.

  In this series of processing, first, in step S10, the current battery temperature Ts is acquired.

  In the subsequent step S11, the predicted voltage Vfa of each battery cell 20a is calculated when it is assumed that the required power Ptgt is continuously output from the assembled battery 20 over the period from the present until the specified time Tff elapses.

  Specifically, first, a process of searching for the discharge current Ip of each battery cell 20a at which the power Pr of the assembled battery 20 at the timing when the specified time Tff elapses from the present time is equal to or greater than the required power Ptgt and closest to the required power Ptgt. Do. In the present embodiment, a range from 0 to the allowable upper limit current is set as the search range of the discharge current Ip. In particular, in this embodiment, a bisection method is used for this search.

  The terminal voltage Va of the battery cell 20a corresponding to the discharge current Ip temporarily set to various values in the search process and the current battery temperature Ts can be calculated by the following equation (eq26).

上式（ｅｑ２６）において、開放端電圧ＯＣＶは、先の図２の開放端電圧算出部４０によって算出された値を用いる。直流抵抗電圧Ｖｓは、先の図４の直流抵抗電圧算出部３４において、第１乗算部３４ｂに入力する電流を、検出電流Ｉｓに代えて、仮設定された放電電流Ｉｐとすることで算出された値を用いる。反応抵抗電圧Ｖｂｖは、先の図５の反応抵抗電圧算出部３５において、電位差算出部３５ｂに入力する電流を、検出電流Ｉｓに代えて、仮設定された放電電流Ｉｐとすることで算出された値を用いる。なお、上式（ｅｑ２６）の右辺において、「Ｖｓ＋Ｖｂｖ＋Ｖｗｒ＋Ｖｗｓ＋ΔＯＣＶ」が先の図１０のΔＶに相当する。

In the above equation (eq26), the open-circuit voltage OCV uses the value calculated by the open-circuit voltage calculator 40 in FIG. The direct current resistance voltage Vs is calculated in the direct current resistance voltage calculation unit 34 of FIG. 4 by replacing the current input to the first multiplication unit 34b with a temporarily set discharge current Ip instead of the detection current Is. Value is used. The reaction resistance voltage Vbv was calculated by replacing the current input to the potential difference calculation unit 35b with the temporarily set discharge current Ip instead of the detection current Is in the reaction resistance voltage calculation unit 35 of FIG. Use the value. In the right side of the above equation (eq26), “Vs + Vbv + Vwr + Vws + ΔOCV” corresponds to ΔV in FIG.

  Further, “Vwr” in the above equation (eq26) represents the total remaining voltage at the timing when the specified time Tff has elapsed from the present time. In the present embodiment, the total remaining voltage Vwr is predicted for each battery cell 20a based on the continuous time equation represented by the following equation (eq27).

上式（ｅｑ２７）において、現在の第１，第２，第３，第４分極電圧Ｖｗ１，Ｖｗ２，Ｖｗ３，Ｖｗ４は、仮設定された放電電流Ｉｐと現在の電池温度Ｔｓとを入力として第１，第２，第３，第４電圧算出部３６ｆ，３６ｇ，３６ｈによって算出されたものである。本ステップでは、各分極電圧Ｖｗ１〜Ｖｗ４のそれぞれについて残電圧を予測し、予測した各残電圧の合計値として、合計残電圧Ｖｗｒを算出する。合計残電圧Ｖｗｒは、上式（ｅｑ２７）からわかるように、時間とともに減少する。なお本実施形態において、合計残電圧Ｖｗｒを予測する処理が「残電圧予測手段」に相当する。

In the above equation (eq27), the current first, second, third, and fourth polarization voltages Vw1, Vw2, Vw3, and Vw4 are the first with the temporarily set discharge current Ip and the current battery temperature Ts as inputs. , Second, third, and fourth voltage calculation units 36f, 36g, and 36h. In this step, the remaining voltage is predicted for each of the polarization voltages Vw1 to Vw4, and the total remaining voltage Vwr is calculated as the total value of the predicted remaining voltages. The total remaining voltage Vwr decreases with time, as can be seen from the above equation (eq27). In the present embodiment, the process of predicting the total remaining voltage Vwr corresponds to “remaining voltage predicting means”.

  Further, in the above equation (eq26), “Vws” is a future polarization newly generated at the timing when the specified time Tff elapses from the present when it is assumed that no charge is accumulated in each capacitor Cwm constituting the diffusion resistance model. Indicates the voltage (hereinafter, future polarization voltage). The future polarization voltage Vws is predicted based on the continuous time expression expressed by the following expression (eq28). In the present embodiment, the process of predicting the future polarization voltage Vws corresponds to “second polarization voltage calculation means”.

上式（ｅｑ２７）に基づいて予測される合計残電圧Ｖｗｒと、上式（ｅｑ２８）に基づいて予測される将来分極電圧Ｖｗｓとの合計値が、現在から規定時間Ｔｆｆ経過するタイミングの分極電圧を表す。

The total value of the total remaining voltage Vwr predicted based on the above equation (eq27) and the future polarization voltage Vws predicted based on the above equation (eq28) is the polarization voltage at the timing when the specified time Tff elapses from the present time. Represent.

  Furthermore, in the above equation (eq26), ΔOCV is the amount of change in the open-circuit voltage OCV (hereinafter referred to as the open circuit) when it is assumed that the discharge current Ip flows through the battery cell 20a over the period from the present until the specified time Tff elapses. End voltage change amount). The open circuit voltage change amount ΔOCV may be calculated based on the current open circuit voltage OCV calculated by the open circuit voltage calculator 40, for example. Specifically, for example, when it is assumed that the discharge current Ip temporarily set over a period from the present to the lapse of the specified time Tff, the specified time Tff has elapsed from the present for each of the battery cells 20a. The amount of change in the SOC in the period until it is calculated is calculated. The change in the SOC is a negative value during discharge. Then, the amount of change in the SOC is added to the current charging rate SOCr calculated by the SOC conversion unit 37, and this added value is converted into an open-circuit voltage using an SOC map. Then, the open circuit voltage change amount ΔOCV is calculated by subtracting the current open circuit voltage OCV from the converted open circuit voltage.

  Incidentally, when the ratio of the open circuit voltage change amount ΔOCV to the predicted voltage Vfa is small, the term of the open circuit voltage change amount ΔOCV may be removed from the right side of the above equation (eq26).

  In FIG. 12, the outline | summary of the prediction method of the voltage Va between the terminals of the battery cell 20a is shown. 12A shows the transition of the current Ip flowing through the battery cell 20a, FIG. 12B shows the transition of the terminal voltage Va, FIG. 12C shows the polarization voltage Vwt, the total residual voltage Vwr, and the future polarization. The transition of voltage Vws is shown.

  As shown in the figure, the total remaining voltage Vwr is used to predict the terminal voltage Va. The total remaining voltage Vwr is a polarization voltage that remains at the timing when the current polarization voltage in the diffusion resistance decreases with time and the specified time Tff elapses from now. That is, when the current charge is stored in the m-th capacitor constituting the diffusion resistance model, the influence of the current polarization voltage on the diffusion resistance remains even after the specified time Tff has elapsed. For this reason, by calculating the total remaining voltage Vwr, it is possible to take into account the effect of the accumulated charge amount of the m-th capacitor, and the accuracy of calculation of the predicted voltage Vfa when the state of the battery cell 20a becomes a transient state. Improvements can be made.

  Using the temporarily set discharge current Ip and the current battery temperature Ts as inputs, the total value of the voltage Va between the terminals of each battery cell 20a calculated based on the above equation (eq26), and the temporarily set discharge current Ip By multiplying, the power Pr of the battery pack 20 corresponding to the temporarily set discharge current Ip is calculated. By temporarily setting the discharge current Ip to various values in the search process, the power Pr of the assembled battery 20 corresponding to each discharge current Ip can be calculated. Then, a search is made for the discharge current Ip of each battery cell 20a in which the power Pr of the assembled battery 20 is equal to or greater than the required power Ptgt and is closest to the required power Ptgt. Then, the terminal voltage Va of each battery cell 20a corresponding to the searched discharge current Ip is calculated as the predicted voltage Vfa of each battery cell 20a. That is, the predicted voltage Vfa is a terminal voltage when it is assumed that the searched discharge current Ip is continuously discharged from the battery cell 20a over the specified time Tff from the present time.

  Returning to FIG. 11, in the following step S12, the constant power characteristic map corresponding to each battery cell 20a is corrected based on the calculated predicted voltage Vfa. Specifically, as shown in FIG. 13, first, map information corresponding to the current battery temperature Ts is selected, and a predicted voltage Vff corresponding to the current charge rate SOCr is calculated from the selected map information. Then, the map information corresponding to the current battery temperature Ts is updated so that the difference between the predicted voltage Vff calculated from the constant power characteristic map and the predicted voltage Vfa calculated in step S11 is zero. In FIG. 13, in the orthogonal biaxial coordinate system with the charging rate SOC and the predicted voltage Vff as axes, the map information corresponding to the battery temperature of 25 ° C. is moved in a direction parallel to the axis of the predicted voltage Vff. In this example, the difference is set to zero. The reason why the constant power characteristic map can be corrected in this way is that map information corresponding to each battery temperature has a substantially similar relationship to each other.

  The constant power characteristic map is corrected and updated in relation to the current battery temperature Ts. Based on the updated constant power characteristic map, the above-described remaining energy Ebat of the assembled battery 20 is predicted.

  As described above, in the present embodiment, the predicted voltage Vff calculated from the constant power characteristic map using each of the current charging rate SOCr and the current battery temperature Ts of the battery cell 20a as inputs, and step S11 of FIG. The constant power characteristic map was corrected each time so that the difference from the predicted voltage Vfa calculated by the processing was zero. Based on the corrected constant power characteristic map, the current charging rate SOCr, and the current battery temperature Ts, the remaining energy Ebat of the assembled battery 20 is predicted. For this reason, it is possible to predict the remaining energy Ebat of the assembled battery 20 each time, excluding the energy for starting the engine and the energy for accelerating the vehicle. Further, the residual energy Ebat can be predicted by taking into account the degree of deterioration of each battery cell 20a and the temperature of each battery cell 20a. Thereby, the prediction accuracy of the residual energy Ebat can be improved, and it can be accurately grasped how long traveling can be continued in the EV traveling mode.

  In particular, in the present embodiment, including the reaction resistance model including the reaction resistance parameter β in the battery model contributes to improving the calculation accuracy of the predicted voltage Vfa. Moreover, the calculation of the polarization voltage using the above equations (eq27) and (eq28) contributes to improving the calculation accuracy of the predicted voltage Vfa in the transient state of the battery cell 20a. By improving the calculation accuracy of the predicted voltage Vfa, it is possible to improve the correction accuracy of the constant power characteristic map, and thus improve the prediction accuracy of the remaining energy Ebat.

(Second Embodiment)
Hereinafter, the second embodiment will be described with reference to the drawings with a focus on differences from the first embodiment. As shown in FIG. 14, the constant power characteristic map according to the present embodiment has a reference temperature (for example, 25 ° C.) of the battery cell 20a in an orthogonal biaxial coordinate system with the predicted voltage Vft and the charging rate SOCt as axes. In contrast, reference information in which the predicted voltage Vft and the charging rate SOCt are related is included. In the present embodiment, this reference information is represented by a fourth-order polynomial of the following equation (eq29).

上式（ｅｑ２９）において、ａ，ｂ，ｃ，ｄ，ｅは定数を示す。基準情報は、例えば、上記第１実施形態で説明した定電力特性マップの元となるデータであって、電池温度毎に充電率及び予測電圧が関係付けられたデータから作成される。

In the above equation (eq29), a, b, c, d, and e are constants. The reference information is, for example, data that is the basis of the constant power characteristic map described in the first embodiment, and is created from data in which the charging rate and the predicted voltage are associated with each battery temperature.

  Then, as shown in the following equations (eq30) and (eq31), in the coordinate system, the first movement amount y of the reference information in the direction parallel to the axis of the predicted voltage Vft and the direction parallel to the axis of the charging rate SOCt Each of the second movement amounts x of the reference information is determined according to the battery temperature T. Each movement amount x, y is stored in the memory 31 in association with the battery temperature T.

以下、メモリ３１に記憶された各移動量ｘ，ｙの初期値について説明する。基準温度と電池温度Ｔｓとが一致する場合、各移動量ｘ，ｙを０とする。一方、基準温度に対して電池温度Ｔｓが高いほど、予測電圧Ｖｆｔが高くなる方向への基準情報に対する第１移動量ｙを大きくし、また、充電率ＳＯＣｔが低くなる方向への基準情報に対する第２移動量ｘを大きくする。他方、基準温度に対して電池温度Ｔｓが低いほど、予測電圧Ｖｆｔが低くなる方向への基準情報に対する第１移動量ｙを大きくし、また、充電率ＳＯＣｔが高くなる方向への基準情報に対する第２移動量ｘを大きくする。ここで、現在の充電率ＳＯＣｒは、上式（ｅｑ３１）のＳＯＣｔに入力される。

Hereinafter, initial values of the movement amounts x and y stored in the memory 31 will be described. When the reference temperature and the battery temperature Ts match, the movement amounts x and y are set to zero. On the other hand, as the battery temperature Ts is higher than the reference temperature, the first movement amount y with respect to the reference information in the direction in which the predicted voltage Vft becomes higher is increased, and the first movement amount with respect to the reference information in the direction in which the charging rate SOCt becomes lower. 2 Increase the movement amount x. On the other hand, as the battery temperature Ts is lower than the reference temperature, the first movement amount y with respect to the reference information in the direction in which the predicted voltage Vft is lowered is increased, and the first movement amount y in the direction in which the charging rate SOCt is increased is increased. 2 Increase the movement amount x. Here, the current charging rate SOCr is input to SOCt in the above equation (eq31).

  According to the constant power characteristic map of the present embodiment, it is not necessary to store map information corresponding to each of a plurality of battery temperatures in the memory 31, and the amount of map information stored in the memory 31 can be reduced.

  Next, a method for correcting the constant power characteristic map according to the present embodiment will be described. In the present embodiment, the current charging rate SOCr and the current battery temperature Ts are input, and the predicted voltage Vft calculated using the above equations (eq29) to (eq31) and the previous step S11 in FIG. Each of the first movement amount y and the second movement amount x is corrected in relation to the current battery temperature Ts so that the difference from the calculated predicted voltage Vfa is zero. As a result, each of the movement amounts x and y is updated from the initial value. FIG. 14 shows an example in which the movement amounts x and y are corrected when the reference temperature and the battery temperature Ts match.

  According to the present embodiment described above, the same effect as that of the first embodiment can be obtained.

(Third embodiment)
Hereinafter, the third embodiment will be described with reference to the drawings with a focus on differences from the second embodiment. In the present embodiment, in the coordinate system shown in FIG. 14, the first magnification A of the reference information in the direction parallel to the axis of the predicted voltage Vft and the second magnification of the reference information in the direction parallel to the axis of the charging rate SOCt. Each of B is determined according to the battery temperature T. Each magnification A and B (> 0) is stored in the memory 31 in association with the battery temperature T.

以下、メモリ３１に記憶された各倍率Ａ，Ｂの初期値について説明する。基準温度と電池温度Ｔｓとが一致する場合、各倍率Ａ，Ｂを１とする。一方、基準温度に対して電池温度Ｔｓが高いほど、各倍率Ａ，Ｂを大きくする。この場合、各倍率Ａ，Ｂは１よりも大きい値とする。他方、基準温度に対して電池温度Ｔｓが低いほど、各倍率Ａ，Ｂを小さくする。この場合、各倍率Ａ，Ｂは０よりも大きくてかつ１未満の値とする。

Hereinafter, initial values of the magnifications A and B stored in the memory 31 will be described. When the reference temperature matches the battery temperature Ts, each magnification A and B is set to 1. On the other hand, as the battery temperature Ts is higher than the reference temperature, the magnifications A and B are increased. In this case, the magnifications A and B are values larger than 1. On the other hand, as the battery temperature Ts is lower than the reference temperature, the magnifications A and B are reduced. In this case, each magnification A and B is set to a value greater than 0 and less than 1.

  Next, a method for correcting the constant power characteristic map according to the present embodiment will be described. In the present embodiment, the first magnification is set so that the difference between the predicted voltage Vft calculated by the above equations (eq29) to (eq31) and the predicted voltage Vfa calculated in step S11 of FIG. Each of A and the second magnification B is corrected in relation to the current battery temperature Ts. Thereby, each magnification A, B is updated from its initial value.

  Also by this embodiment described above, the same effect as the second embodiment can be obtained.

(Other embodiments)
Each of the above embodiments may be modified as follows.

  In the second and third embodiments, the mathematical expression representing the reference information is not limited to the above expression (eq29), and may be another mathematical expression.

  Even if the constant power characteristic map is expressed by combining the first and second movement amounts x and y described in the second embodiment and the first and second magnifications A and B described in the third embodiment. Good.

  In the first embodiment, the search method for searching for the discharge current Ip is not limited to the bisection method, and other search methods such as the golden section method may be used.

  -The diffusion resistance model is not limited to an RC equivalent circuit model in which four parallel connection bodies of resistors and capacitors are connected in series, but is an RC equivalent circuit model in which a plurality of the parallel connection bodies (other than four) are connected. May be. The diffusion resistance model is not limited to an RC equivalent circuit in which a plurality of parallel connection bodies of resistors and capacitors are connected, and the parallel connection body may be a single RC equivalent circuit for simplification.

  The secondary battery is not limited to a lithium ion secondary battery, but may be another secondary battery such as a nickel metal hydride battery.

  In each of the above embodiments, the battery temperature used for each process is not limited to the detection value of the temperature sensor 22, and may be a battery temperature estimated by some method.

  The vehicle to which the present invention is applied includes an idling stop system that automatically stops the main engine when a predetermined automatic stop condition is satisfied, and then restarts the main engine when the predetermined restart condition is satisfied. It may be a vehicle. In this case, the remaining energy Ebat is predicted when it is assumed that the power required for starting the starter for starting the engine is output from the battery connected to the starter over a specified time from the present. Then, by dividing the remaining energy Ebat by the current flowing from the battery to the starter and the battery voltage, it is possible to grasp the time during which the engine can be automatically stopped.

  -The application object of this invention is not restricted to a vehicle.

  20a ... battery cell, 30 ... battery ECU.

Claims (12)

In the battery energy predicting device for predicting the remaining energy of the secondary battery based on the battery model of the secondary battery (20a),
The battery model is
A DC resistance model representing the DC resistance (Rs) of the secondary battery;
A model representing a reaction resistance of the secondary battery, the reaction resistance model including a reaction resistance parameter (β) derived from a Butler-Volmer equation and correlated with an exchange current density;
An RC equivalent circuit model including a parallel connection body of a resistor and a capacitor, the diffusion resistance model representing a diffusion resistance of the secondary battery,
Based on the battery model, a predicted voltage that is a voltage across the terminals of the secondary battery is calculated when it is assumed that the required power is continuously output from the secondary battery over a period from the current time until the specified time elapses. Voltage prediction means;
Relation information in which the charging rate, the temperature of the secondary battery, and the predicted voltage are related in advance so that the predicted voltage decreases as the charging rate of the secondary battery and the temperature of the secondary battery decrease. Storage means (31) for storing
The difference between the predicted voltage derived from the relationship information using each of the current charging rate of the secondary battery and the current temperature of the secondary battery as input, and the predicted voltage calculated by the voltage predicting unit. Correction means for correcting the relationship information to match,
In the relation information corrected by the correction means, the charging rate when the predicted voltage is an allowable lower limit value of the inter-terminal voltage of the secondary battery is defined as a lower limit charging rate, and based on the corrected relation information And an energy predicting means for predicting, as the remaining energy, the energy of the secondary battery that can be used before the current charging rate of the secondary battery decreases to the lower limit charging rate. Prediction device.   The battery energy prediction apparatus according to claim 1, wherein the relationship information is map information in which a relationship between the charging rate and the predicted voltage is defined for each temperature of the secondary battery.   2. The battery energy prediction apparatus according to claim 1, wherein the relationship information is map information that is expressed as a function using the predicted voltage as a dependent variable and the charging rate and the temperature of the secondary battery as independent variables. The relationship information includes reference information in which the predicted voltage and the charging rate are related to a reference temperature of the secondary battery in an orthogonal biaxial coordinate system having the predicted voltage and the charging rate as axes. And in the coordinate system, the first movement amount of the reference information in a direction parallel to the axis of the predicted voltage and the second movement amount of the reference information in a direction parallel to the axis of the charging rate are It is determined according to the temperature of the secondary battery,
The battery energy prediction apparatus according to claim 3, wherein the correction unit corrects each of the first movement amount and the second movement amount so as to match the deviation. The relationship information includes reference information in which the predicted voltage and the charging rate are related to a reference temperature of the secondary battery in an orthogonal biaxial coordinate system having the predicted voltage and the charging rate as axes. And in the coordinate system, each of the first magnification of the reference information in a direction parallel to the axis of the predicted voltage and the second magnification of the reference information in a direction parallel to the axis of the charging rate are the second order. It is determined according to the battery temperature,
5. The battery energy prediction apparatus according to claim 3, wherein the correction unit corrects each of the first magnification and the second magnification so that the deviations coincide with each other. The energy predicting means is configured such that the full charge capacity of the secondary battery is Ahf, the current charge rate of the secondary battery is SOCr, the lower limit charge rate is Smin, the current charge rate in the corrected relation information and the When the predicted voltage corresponding to the current temperature of the secondary battery is Vff, the remaining energy E is

The battery energy prediction apparatus according to claim 1, which predicts based on The battery energy prediction device is applied to a vehicle including a main machine rotating electrical machine and a main engine that are driving power sources, and an auxiliary machine rotating electrical machine for starting the main engine.
The required power is set to a power supplied to the auxiliary rotating electrical machine to start the main engine in a situation where only the main rotating electrical machine is used as a driving power source of the vehicle. The battery energy prediction apparatus according to any one of the above. The battery energy prediction device is applied to a vehicle including a main rotating electrical machine that serves as a driving power source,
The said required electric power is set to the electric power supplied to the said main machine rotary electric machine in order to accelerate the said vehicle in the condition which uses only the said main machine rotary electric machine as the driving power source of the said vehicle. The battery energy prediction apparatus according to claim 1. The voltage predicting means includes
A formula including circuit constants of the RC equivalent circuit model, and a first polarization voltage calculating means for calculating the current polarization voltage based on a discrete expression for calculating the current polarization voltage of the diffusion resistance model;
An equation including the circuit constant, wherein the current polarization voltage decreases to a continuous time equation for predicting a residual voltage, which is the polarization voltage remaining after the lapse of the specified time from the present, and the current polarization voltage. A residual voltage predicting means for predicting the residual voltage by inputting
A second polarization voltage calculation means for predicting the future polarization voltage based on a continuous time formula for predicting the future polarization voltage of the diffusion resistance model newly generated after the lapse of the specified time from the present time, and the residual voltage The battery energy according to any one of claims 1 to 8, wherein the predicted voltage is calculated based on a total value of the current and the future polarization voltage, a potential difference in the DC resistance model, and a potential difference in the reaction resistance model. Prediction device. The RC equivalent circuit model is a model configured by N (N is an integer of 1 or more) the parallel connection bodies,
In the diffusion resistance model, the resistance value of the resistor of the m-th (m is a positive integer) constituting the RC equivalent circuit model is defined as Rwm, and the capacitance of the capacitor is defined as Cwm.
The residual voltage prediction means defines the residual voltage Vwr by defining the specified time as Tff and the current polarization voltage as Vwm.

Based on
The second polarization voltage calculating means defines the future polarization voltage Vws as Ip when a current discharged from the secondary battery over a period from the present to the lapse of the specified time is defined as Ip.

The battery energy prediction apparatus according to claim 9, which predicts based on The voltage predicting means defines the potential difference Vbv in the reaction resistance when β is defined as the reaction resistance parameter, α and γ are constants, Ip is the current discharged from the secondary battery, and T is the temperature of the secondary battery.

The battery energy predicting device according to claim 9 or 10, wherein the battery energy predicting device is calculated based on the above.   The voltage predicting unit is configured to determine a discharge current of the secondary battery that has a power that can be output from the secondary battery after the lapse of the specified time from the present time is equal to or greater than the required power and is closest to the required power. The secondary battery when it is assumed that the discharge current searched by the searcher continues to be discharged from the secondary battery over a period from the present to the lapse of the specified time. The battery energy prediction apparatus according to claim 1, wherein a battery terminal voltage is calculated as the predicted voltage.

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