JP6834416B2 - Battery system - Google Patents

Description

The present disclosure relates to a battery system, and more specifically to a battery system including an alkaline secondary battery containing nickel hydroxide as a positive electrode active material.

When the positive electrode potential of the secondary battery becomes lower than the predetermined lower limit potential or higher than the predetermined upper limit potential, a side reaction occurs at the positive electrode, and the positive electrode may deteriorate. Similarly, the negative electrode may be deteriorated when the negative electrode potential is out of the predetermined potential range. Therefore, a technique for calculating (monitoring) each of the positive electrode potential and the negative electrode potential has been proposed for the purpose of suppressing deterioration of the positive electrode and the negative electrode. For example, in International Publication No. 2013/105140 (Patent Document 1), the positive electrode potential and the negative electrode potential are calculated from the positive electrode open potential and the negative electrode open potential, respectively, and each of the positive electrode potential and the negative electrode potential changes within a predetermined potential range. As described above, a technique for controlling the charging / discharging of the secondary battery is disclosed.

International Publication No. 2013/105140 JP-A-2016-103449 Japanese Unexamined Patent Publication No. 2016-91978 Japanese Unexamined Patent Publication No. 2013-72659 Japanese Unexamined Patent Publication No. 2008-243373 Japanese Unexamined Patent Publication No. 2010-60384

In recent years, nickel-metal hydride batteries, which are a type of alkaline secondary batteries containing nickel hydroxide as a positive electrode active material, have become widespread in various applications such as in-vehicle use. It is known that an alkaline secondary battery such as a nickel-metal hydride battery can produce a memory effect. The memory effect is a state in which the discharge voltage is in the initial state (a state in which the memory effect does not occur) when charging is repeated in a state where the power stored in the alkaline secondary battery is not sufficiently consumed (so-called recharge). ) Is a phenomenon that is lower than that. The memory effect may also occur on the charging side of the alkaline secondary battery, and the memory effect causes the charging voltage to be higher than in the initial state. More specifically, when the memory effect occurs, the positive electrode open potential becomes lower at the time of discharge than in the initial state, and as a result, the discharge voltage decreases. On the other hand, during charging, the positive electrode open potential becomes higher than in the initial state, and as a result, the charging voltage rises.

The method for calculating the positive electrode potential and the negative electrode potential disclosed in Patent Document 1 is mainly applied to a lithium ion secondary battery. Since a remarkable memory effect does not occur in a lithium ion secondary battery, the method disclosed in Patent Document 1 does not consider the memory effect at all, so there is room for improvement in the calculation accuracy of the positive electrode potential of the alkaline secondary battery. To do.

The present disclosure has been made to solve the above problems, and an object of the present disclosure is to provide a technique capable of improving the calculation accuracy of the positive electrode potential in consideration of the memory effect in a battery system including an alkaline secondary battery. That is.

A battery system according to a certain aspect of the present disclosure is an alkaline secondary battery containing nickel hydroxide as a positive electrode active material, and a control device that controls charging / discharging of the alkaline secondary battery using the positive electrode potential and the negative electrode potential of the alkaline secondary battery. And. The control device uses a battery model for estimating the internal behavior of the alkaline secondary battery, which includes at least one of the voltage between the terminals of the alkaline secondary battery and the input / output current of the alkaline secondary battery as an input. The hydrogen concentration inside the positive electrode active material is calculated from the positive electrode open potential and the negative electrode open potential of the alkaline secondary battery. The control device calculates the "memory amount", which is the amount of potential change due to the memory effect from the initial potential of the positive electrode open potential, from the hydrogen concentration, and calculates the positive electrode open potential using the initial potential and the memory amount.

Preferably, the positive electrode active material is assumed to be spherical in the battery model and is virtually divided into a plurality of regions in the radial direction. The control device calculates the distribution of the "local hydrogen amount", which is the local hydrogen concentration of each of the plurality of regions, from the distribution of the hydrogen concentration in the plurality of regions. The control device calculates the initial potential from the "surface hydrogen amount" which is the local hydrogen amount in the region including the surface of the positive electrode active material, and the memory amount from the "average hydrogen amount" which is the average amount of the local hydrogen amounts in a plurality of regions. Is calculated.

Preferably, the battery system further comprises a storage device. The storage device has a "micro memory amount" which is the amount of potential change in a predetermined time due to the memory effect of the positive electrode open potential and a "hydrogen used amount" which is the average amount of hydrogen when an alkaline secondary battery is used. The relationship stores data identified for each of multiple ranges of average hydrogen content. The control device sequentially calculates the minute memory amount for each of a plurality of ranges from the amount of hydrogen used by referring to the data, and calculates the memory amount by integrating the minute memory amount for each of the plurality of ranges.

Preferably, the control device integrates a minute memory amount in the direction in which the positive electrode open potential decreases in a range in which the average amount of hydrogen is larger than the amount of hydrogen used among the plurality of ranges, and when the amount of hydrogen used increases, after the increase. In the range where the average amount of hydrogen is smaller than the amount of hydrogen used in, the amount of minute memory accumulated in the decreasing direction is set to 0. The control device integrates the minute memory amount in the direction in which the positive electrode open potential increases in the range where the average hydrogen amount is smaller than the hydrogen amount used in the plurality of ranges, and when the hydrogen used amount decreases, the hydrogen used after the decrease In the range where the average hydrogen amount is larger than the amount, the minute memory amount accumulated in the increasing direction is set to 0.

According to the above configuration, the memory amount is calculated from the local hydrogen amount (more specifically, the average hydrogen amount), and the positive electrode open potential is calculated using the initial potential of the positive electrode open potential and the memory amount. Further, the positive electrode potential can be calculated from, for example, the sum of the positive electrode open potential and the overvoltage (that is, initial potential + memory amount + overvoltage). In this way, by calculating the positive electrode open potential in consideration of the memory effect, the calculation accuracy of the positive electrode open potential is improved, so that the calculation accuracy of the positive electrode potential can be improved.

Preferably, the amount of hydrogen used is calculated using the past usage history of the alkaline secondary battery.
In the positive electrode of an alkaline secondary battery, apart from the memory effect, it is known that the positive electrode opening potential changes according to the past usage history (hysteresis) of the alkaline secondary battery. According to the above configuration, since the amount of hydrogen used is calculated in consideration of the influence of hysteresis, the amount of potential change due to hysteresis can be reflected in the positive electrode open potential. Therefore, the calculation accuracy of the positive electrode potential can be further improved.

Preferably, the control device has at least one of a first condition that the positive electrode potential is higher than a predetermined upper limit positive electrode potential and a second condition that the negative electrode potential is lower than a predetermined lower limit negative electrode potential. When the condition is satisfied, the upper limit of the charging power of the alkaline secondary battery is set smaller than that when neither of the first and second conditions is satisfied. The control device satisfies at least one of a third condition that the negative electrode potential is higher than a predetermined upper limit negative electrode potential and a fourth condition that the positive electrode potential is lower than a predetermined lower limit positive electrode potential. Is set to a smaller discharge power upper limit value of the alkaline secondary battery than in the case where neither the third nor the fourth condition is satisfied.

The upper limit positive electrode potential and the lower limit positive electrode potential are determined so that a side reaction (deterioration reaction) leading to deterioration of the positive electrode does not occur within the potential range between them. Therefore, according to the above configuration, the first or first It is possible to suppress the occurrence of a deterioration reaction at the positive electrode due to the condition 4 being satisfied. Similarly, the upper limit negative electrode potential and the lower limit negative electrode potential are determined so that a side reaction (deterioration reaction) leading to deterioration of the negative electrode does not occur within the potential range between them, so that the second or third condition is satisfied. It is also possible to suppress the occurrence of deterioration reaction at the negative electrode due to the above.

Preferably, the alkaline secondary battery is a nickel-metal hydride battery containing a hydrogen storage alloy as a negative electrode active material. The positive electrode potential and the negative electrode potential are calculated using the exchange current density of the negative electrode active material. The control device calculates an index value (crack index value) related to the amount of cracks generated in the negative electrode active material from the current input / output to the nickel-metal hydride battery and the temperature of the nickel-metal hydride battery, and uses the index value to exchange current. Calculate the density.

When the negative electrode active material is cracked due to charging / discharging or temperature change of the nickel-metal hydride battery, a new surface is exposed to the negative electrode active material and the reaction surface area is increased. As a result, the reaction resistance of the negative electrode decreases, and the exchange current density of the negative electrode active material increases. According to the above configuration, a crack index value is calculated, and the exchange current density of the negative electrode active material is calculated using this crack index value. Then, the positive electrode potential and the negative electrode potential are calculated using the exchange current density of the negative electrode active material. As described above, by considering the exchange current density of the negative electrode active material due to the occurrence of cracks, the calculation accuracy of the positive electrode potential and the negative electrode potential can be further improved.

Preferably, the negative electrode active material of the alkaline secondary battery is assumed to be spherical in the battery model and is virtually divided into a plurality of regions in the radial direction. The control device calculates the negative electrode open potential from the hydrogen concentration in the region including the surface of the negative electrode active material calculated using the battery model, and from the positive electrode open potential and the negative electrode open potential, the full charge capacity of the alkaline secondary battery. Is calculated.

According to the above configuration, the positive electrode open potential and the negative electrode open potential are calculated with high accuracy in consideration of the memory effect, and the full charge capacity of the alkaline secondary battery is further increased from the highly accurate calculated positive electrode open potential and negative electrode open potential. It is calculated. Therefore, the calculation accuracy can be improved also for the fully charged capacity.

According to the present disclosure, in a battery system including an alkaline secondary battery, the calculation accuracy of the positive electrode potential can be improved in consideration of the memory effect.

It is a block diagram which shows schematic the whole structure of the vehicle which mounted the battery system which concerns on this Embodiment. It is a figure which shows the structure of a cell cell. It is a flowchart which shows the control at the time of charging a cell. It is a flowchart which shows the control at the time of discharging a cell. It is a conceptual diagram of the battery model in this embodiment. It is a figure for demonstrating the parameter used for a battery model. It is a figure for demonstrating the calculation method of the hydrogen concentration distribution in the positive electrode active material. It is a figure which shows the relationship between an open potential and a local hydrogen amount. It is a figure which shows an example of the change of the positive electrode open potential by a memory effect. It is a figure which shows the mode that the memory amount M increases with the use of a cell. It is a figure for demonstrating the integration of the minute memory amount. It is a figure for conceptually explaining the calculation method of the charge / discharge curve after the memory effect occurs. It is a conceptual diagram of the map in this embodiment. It is a figure for demonstrating the integration method of the minute memory amount considering the amount of hydrogen used. It is a functional block diagram of the ECU regarding the potential calculation process in this embodiment. It is a functional block diagram which shows the more detailed structure of the memory amount calculation part. It is a flowchart which shows the potential calculation process in this embodiment. It is a figure for demonstrating the calculation method of the positive electrode open potential in the modification 1. It is a flowchart which shows the potential calculation process in the modification 2. It is a schematic diagram for demonstrating the crack which occurs in a negative electrode active material. It is a figure for demonstrating the calculation process of a crack index value. It is a figure which shows the relationship between the crack index value and the exchange current density of a negative electrode active material.

Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. The same or corresponding parts in the drawings are designated by the same reference numerals, and the description thereof will not be repeated.

In the following, a configuration in which the battery system according to the embodiment of the present disclosure is mounted on a vehicle will be described as an example. However, the use of the battery system is not limited to the vehicle, and may be, for example, stationary.

[Embodiment]
<Battery system configuration>
FIG. 1 is a block diagram schematically showing an overall configuration of a vehicle equipped with a battery system according to the present embodiment. The vehicle 100 is a vehicle (hybrid vehicle, electric vehicle, or fuel cell vehicle), and includes a motor generator (MG) 1, a power transmission gear 2, a drive wheel 3, and a power control unit (PCU: Power Control). It includes a Unit) 4, a System Main Relay (SMR) 5, and a battery system 200. The battery system 200 includes an assembled battery 10, a voltage sensor 21, a current sensor 22, a temperature sensor 23, and an electronic control unit (ECU) 30.

MG1 is, for example, a three-phase AC rotary electric machine. The output torque of MG1 is transmitted to the drive wheels 3 via a power transmission gear 2 including a speed reducer and a power split mechanism. The MG1 can also generate electricity by the rotational force of the drive wheels 3 during the regenerative braking operation of the vehicle 100. In a hybrid vehicle in which an engine (not shown) is mounted in addition to the MG1, the required vehicle driving force is generated by operating the engine and the MG1 in a coordinated manner. Although FIG. 1 shows a configuration in which only one MG is provided, the number of MGs is not limited to this, and a plurality (for example, two) MGs may be provided.

PCU4 includes an inverter and a converter (not shown). When the assembled battery 10 is discharged, the converter boosts the voltage supplied from the assembled battery 10 and supplies it to the inverter. The inverter converts the DC power supplied from the converter into AC power to drive the MG1. On the other hand, when charging the assembled battery 10, the inverter converts the AC power generated by the MG 1 into DC power and supplies it to the converter. The converter steps down the voltage supplied from the inverter and supplies it to the assembled battery 10.

The SMR 5 is electrically connected to a power line connecting the assembled battery 10 and the PCU 4. When the SMR 5 is closed in response to a control signal from the ECU 30, electric power can be exchanged between the assembled battery 10 and the PCU 4.

The assembled battery 10 is configured to include a plurality of (for example, several) battery blocks (not shown), and each battery block is configured to include a plurality of (for example, several to several tens) single batteries 11. .. Each of the plurality of cell cells 11 is an alkaline secondary battery. In the present embodiment, a configuration using a nickel-metal hydride battery as the alkaline secondary battery will be described as an example.

The voltage sensor 21 detects the voltage Vb of each cell 11. The current sensor 22 detects the current Ib input / output to / from the assembled battery 10. The temperature sensor 23 detects the temperature Tb of the battery block. Each sensor outputs the detection result to the ECU 30. The voltage sensor 21 may detect the voltage of the battery block. The voltage Vb of the cell 11 can be calculated by dividing the voltage of the voltage block by the number of cells. Further, the temperature sensor 23 may detect the temperature of each cell 11 or the temperature of the entire assembled battery 10.

The ECU 30 includes a CPU (Central Processing Unit) 31, a memory (ROM (Read Only Memory) and RAM (Random Access Memory)) 32, and an input / output buffer (not shown). The ECU 30 controls each device so that the vehicle 100 and the battery system 200 are in a desired state based on the signal received from each sensor and the map and program stored in the memory 32. As a main process executed by the ECU 30, there is _{a “potential calculation process” for calculating the positive electrode potential V 1} and the negative electrode potential V ₂ of the cell 11, and this process will be described later.

FIG. 2 is a diagram showing the configuration of the cell 11. Since the configuration of each cell 11 is common, only one cell 11 is typically shown in FIG. The cell 11 is, for example, a square sealed cell, and includes a case 12, a safety valve 13 provided in the case 12, an electrode body 14 housed in the case 12, and an electrolytic solution (not shown). In FIG. 2, a part of the case 12 is seen through to show the electrode body 14.

The case 12 includes a case main body 121 and a lid body 122 made of metal, and is sealed by welding the lid body 122 all around the opening provided in the case main body 121. When the pressure inside the case 12 exceeds a predetermined value, the safety valve 13 discharges a part of the gas (hydrogen gas, etc.) inside the case 12 to the outside. The electrode body 14 includes a positive electrode 141, a negative electrode 142, and a separator 143. The positive electrode 141 is inserted in the bag-shaped separator 143, and the positive electrode 141 inserted in the separator 143 and the negative electrode 142 are alternately laminated. The positive electrode 141 and the negative electrode 142 are electrically connected to a positive electrode terminal and a negative electrode terminal (not shown), respectively.

Various conventionally known materials can be used as the material of the electrode body 14 and the electrolytic solution. In the present embodiment, as an example, the positive electrode active material layer containing nickel hydroxide (nickel hydroxide (II) (Ni (OH) ₂ ) or nickel oxyhydroxide (III) (NiOOH)) is contained in the positive electrode 141. And an electrode plate containing an active material support such as nickel foam. An electrode plate containing a hydrogen storage alloy is used for the negative electrode 142. As the separator 143, a non-woven fabric made of a hydrophilized synthetic fiber is used. As the electrolytic solution, an alkaline aqueous solution containing potassium hydroxide (KOH) or sodium hydroxide (NaOH) is used.

<Charging / discharging control>
In the battery system 200, _{each of the positive electrode potential V 1} and the negative electrode potential V ₂ of the cell 11 is calculated by the potential calculation process. The positive electrode potential V ₁ is the potential of the positive electrode 141 of the cell 11 when the cell 11 is energized. The negative electrode potential V ₂ is the potential of the negative electrode 142 of the cell 11 when the cell 11 is energized. On the other hand, when the cell 11 is in the non-energized state (no load state), the potential of the positive electrode 141 of the cell 11 _{is referred to as the positive electrode open potential U 1,} and the potential of the negative electrode 142 is referred to as the negative electrode open potential U ₂ .

When the memory effect occurs, the positive electrode open potential U ₁ changes according to the degree of occurrence. In this case, the positive electrode open-circuit potential U ₁ is a positive electrode open-circuit potential in the initial state in which the memory effect has not occurred "initial potential" E _1, the potential change due to the memory effect from the initial potential E ₁ of the positive electrode open-circuit potential U ₁ It is represented by the sum of the quantity "memory amount" M. _{Further, when charging / discharging the cell 11, it is necessary to consider the “overvoltage” η 1} which is the amount of potential change according to the resistance component of the cell 11 (see the formula (10) described later). Therefore, as shown in the following equation (1), the positive electrode potential V ₁ is represented by the sum of the initial potential E ₁ , the memory amount M, and the overvoltage η _1.

On the other hand, in the negative electrode 142 of the cell 11, the memory effect need not be particularly considered. Therefore, as shown in the following equation (2), the negative electrode potential V ₂ is represented by the sum of the negative electrode open potential U ₂ and the overvoltage η _2.

When the cell 11 is charged, the positive electrode potential V ₁ becomes higher than the positive electrode open potential U ₁ by an overvoltage η _1, and the negative electrode potential V ₂ becomes lower than the negative electrode open potential U ₂ by an overvoltage η _2. On the other hand, when the cell 11 is discharged, the positive electrode potential V ₁ is lower than the positive electrode open potential U ₁ by an overvoltage η _1, and the negative electrode potential V ₂ is higher than the negative electrode open potential U ₂ by an overvoltage η _2. In the battery system 200, compared with the case where at least one of the positive electrode potential V ₁ and the negative electrode potential V ₂ is or higher may become too low, the charge and discharge of the cells 11 in order to suppress the electrode deterioration and normal Is suppressed.

FIG. 3 is a flowchart showing control during charging of the cell 11. The processing of the flowchart shown in FIG. 3 and FIG. 4 to be described later is called and executed from the main routine (not shown) every time a predetermined condition is satisfied or at a predetermined calculation cycle. Each step (hereinafter abbreviated as "S") included in these flowcharts is basically realized by software processing by the ECU 30, but a part or all of the hardware (electric circuit) manufactured in the ECU 30. May be realized by.

In S11, ECU 30 executes the potential calculating process to calculate the positive electrode potential _{V 1} and the negative electrode potential _{V 2} of the cells 11. The potential calculation process will be described in detail later.

In S12, the ECU 30 determines whether or not _{the positive electrode potential V 1} is higher than the predetermined upper limit potential UL _1. If the positive electrode potential V ₁ becomes excessively high, a deterioration reaction such as the formation of _{Ni 2} O _{3 H may occur.} The upper limit potential UL ₁ is a potential predetermined by experiments or the like so that such a deterioration reaction does not occur.

When the positive electrode potential V ₁ is equal to or less than the upper limit potential UL ₁ (NO in S12), the ECU 30 advances the process to S13 and further determines whether or not _{the negative electrode potential V 2} is less than the predetermined lower limit potential LL _2. The lower limit potential LL ₂ is a potential predetermined by an experiment or the like so that a deterioration reaction does not occur at the negative electrode of the cell 11.

When the positive electrode potential V ₁ is equal to or lower than the upper limit potential UL ₁ (NO in S12) and the negative electrode potential V ₂ is equal to or higher than the lower limit potential LL ₂ (NO in S13), the ECU 30 returns the process to the main routine.

On the other hand, when the positive electrode potential V ₁ is higher than the upper limit potential UL ₁ (YES in S12) or the negative electrode potential V ₂ is less than the lower limit potential LL ₂ (YES in S13), the ECU 30 is charged normally. Compared with the time (when the positive electrode potential V ₁ is the upper limit potential UL ₁ or less and the negative electrode potential V ₂ is the lower limit potential LL ₂ or more), the charging of the cell 11 is suppressed. Specifically, the ECU 30 sets the charging power upper limit value Win (magnitude) that allows charging of the cell 11 to be smaller than that during normal charging (S14).

By setting the upper limit value Win of the charging power to be low _{, the magnitudes of the overvoltages η 1} and η ₂ become small, so that _{the excessive rise of the positive electrode potential V 1} is suppressed and the negative electrode potential V ₂ is excessively lowered. It is suppressed. As a result, a state in which the positive electrode potential V ₁ is equal to or lower than the upper limit potential UL _{1 and the negative electrode potential V 2} is equal to or higher than the lower limit potential LL ₂ (a state during normal charging) is realized. Therefore, it is possible to suppress the occurrence of deterioration reactions at the positive electrode 141 and the negative electrode 142.

FIG. 4 is a flowchart showing the control of the cell 11 when it is discharged. In S21, ECU 30 is the potential calculating process to calculate the positive electrode potential _{V 1} and the negative electrode potential _{V 2} of the cells 11. This process is equivalent to the process of S11 (see FIG. 3) when charging the cell 11.

In S22, the ECU 30 determines whether or not _{the negative electrode potential V 2} is higher than the predetermined upper limit potential UL _2. If the negative electrode potential V ₂ becomes excessively high, a deterioration reaction of the negative electrode active material may occur. The upper limit potential UL ₂ is a potential predetermined by an experiment or the like so that such a deterioration reaction does not occur.

When the negative electrode potential V ₂ is equal to or less than the upper limit potential UL ₂ (NO in S22), the ECU 30 advances the process to S23 and further determines whether or not _{the positive electrode potential V 1} is less than the predetermined lower limit potential LL _1. If the positive electrode potential V ₁ becomes excessively low, a deterioration reaction (elution or the like) of the material (for example, cobalt or the like) contained in the positive electrode 141 may occur. The lower limit potential LL ₁ is a potential predetermined by an experiment or the like so that such a deterioration reaction does not occur.

When the negative electrode potential V ₂ is equal to or lower than the upper limit potential UL ₂ (NO in S22) and the positive electrode potential V ₁ is equal to or higher than the lower limit potential LL ₁ (NO in S23), the ECU 30 returns the process to the main routine.

On the other hand, when the negative electrode potential V ₂ is higher than the upper limit potential UL ₂ (YES in S22) or the positive electrode potential V ₁ is less than the lower limit potential LL ₁ (YES in S23), the ECU 30 discharges normally. Compared with the time (when the negative electrode potential V ₂ is the upper limit potential UL ₂ or less and the positive electrode potential V ₁ is the lower limit potential LL ₁ or more), the discharge of the cell 11 is suppressed. Specifically, the ECU 30 sets the discharge power upper limit value Wout (magnitude) that allows the discharge of the cell 11 to be smaller than that at the time of normal discharge (S24).

By setting the discharge power upper limit value Wout to a low value _{, the magnitudes of the overvoltages η 1} and η ₂ become small, so that an excessive decrease in the _{positive electrode potential V 1} is suppressed and an excessive increase in the _{negative electrode potential V 2 is suppressed.} It is suppressed. As a result, a state in which the negative electrode potential V ₂ is equal to or lower than the upper limit potential UL _{2 and the positive electrode potential V 1} is equal to or higher than the lower limit potential LL ₁ (normal discharge state) is realized. Therefore, it is possible to suppress the occurrence of deterioration reactions at the positive electrode 141 and the negative electrode 142.

<Battery model>
Next, the battery model used for calculating the positive electrode potential V ₁ and the negative electrode potential V ₂ will be described in detail.

FIG. 5 is a conceptual diagram of the battery model according to the present embodiment. The positive electrode of the nickel-metal hydride battery contains an aggregate of spherical positive electrode active materials, and the negative electrode contains an aggregate of spherical negative electrode active materials. When the nickel hydrogen battery is discharged, hydrogen ions (protons, ^{indicated by H +} ) and electrons ( ^{indicated by e −} ) are emitted at the interface between the negative electrode active material and the electrolytic solution, while the positive electrode active material and the electrolytic solution are discharged. Hydrogen ions and electrons are absorbed at the interface. When charging a nickel-metal hydride battery, a reaction opposite to the above reaction occurs with respect to the release / absorption of hydrogen ions and electrons.

In general, the computing power of the vehicle-mounted ECU is lower than the computing power of the research and development computing device. Therefore, in the vehicle-mounted battery system 200, it is required to reduce the computing load of the ECU 30. Therefore, in the present embodiment, the battery model is simplified as follows. That is, when the positive electrode 141 contains a large number of positive electrode active materials, a large number of positive electrode active materials are combined with a single positive electrode active material (positive electrode activity) under the assumption that the electrochemical reaction in each positive electrode active material is uniform. Material model) 151 is represented. Similarly, under the assumption that the electrochemical reaction in a large number of negative electrode active materials contained in the negative electrode 142 is uniform, a large number of negative electrode active materials are represented by a single negative electrode active material (negative electrode active material model) 152. .. After adopting the active material model simplified in this way, the hydrogen concentration distribution inside the positive electrode active material 151 and the hydrogen concentration distribution inside the negative electrode active material 152 are calculated.

FIG. 6 is a diagram for explaining parameters (variables and constants) used in the battery model. In the parameters described below, as in Patent Document 1 and the like, those with the subscript e mean the values in the electrolytic solution, and those with the subscript s are the values in the active material. Means that. The subscript j is for distinguishing between the positive electrode and the negative electrode, and when j = 1, it means that it is the value in the positive electrode active material 151, and when j = 2, it is the value in the negative electrode active material 152. It means that there is. When the subscript j is omitted, indicates the values in the positive electrode active material 151 and the negative electrode active material 152 comprehensively.

FIG. 7 is a diagram for explaining a method for calculating the hydrogen concentration distribution inside the positive electrode active material 151. In this battery model, it is assumed that the hydrogen concentration distribution in the circumferential direction of the polar coordinates is uniform inside the spherical positive electrode active material 151, and only the hydrogen concentration distribution in the radial direction is considered. In other words, the positive electrode active material 151 is a one-dimensional model in which the moving direction of hydrogen is limited to the radial direction.

The positive electrode active material 151 is virtually divided into N regions (N: 2 or more natural numbers) in the radial direction, and each region is distinguished by a subscript k (k = 1 to N). The hydrogen concentration _{c s1k} in region k, and the position _{r 1k} region k in the radial direction of the positive electrode active material 151, is expressed as a function of the time t (the following formula (3) refer).

Although details will be described later approach, in the present embodiment, for each area k, the hydrogen concentration c _s1k is calculated (i.e. the concentration distribution is calculated), further, the calculated hydrogen concentration c _s1k is normalized .. Specifically, as shown in the following formula (4), for the maximum concentration (limit hydrogen _{concentration) c s1, max} of hydrogen, the ratio of hydrogen concentration _{c s1k} in the region k is calculated. It is assumed that the critical hydrogen concentrations _{cs1 and max are known.}

Hereinafter, the value θ _1k after standardization is referred to as the “local hydrogen amount” in the region k. The local hydrogen amount θ _1k is a standardized value and can change in the range of 0 to 1 depending on the amount of hydrogen present in the region k of the positive electrode active material 151.

_{Further, the local hydrogen amount θ 1N} in the outermost peripheral region N (that is, the surface of the positive electrode active material 151) where k = N is referred to as “surface hydrogen amount”. Further, as shown in the following formula (5), _{the average amount of the local hydrogen amount θ 1k} in the entire region k (k = 1 to N) is referred to as “average hydrogen amount” and is represented by _{θ 1, ave.}

In FIG. 7, the positive electrode active material 151 has been described as an example, but _{the calculation method of the hydrogen concentration (distribution) cs2k} and the local hydrogen amount (distribution) θ _2k inside the negative electrode active material 152 is also the same. The positive electrode active material 151 and the negative electrode active material 152 may have different numbers of divisions, but in the present embodiment, the number of divisions is assumed to be N for simplification of description.

FIG. 8 is a diagram showing the relationship between the open potential and the amount of local hydrogen. FIG. 8A shows the relationship between the surface hydrogen amount θ _1N of the positive electrode active material 151 and the initial potential E ₁ of the positive electrode open potential (positive electrode open potential U _{1 in the state where the memory effect does not occur).} FIG. 8B shows the relationship between the surface hydrogen amount θ _2N of the negative electrode active material 152 and the negative electrode open potential U _2.

As shown in FIGS. 8A and 8B, the initial potential E ₁ and the negative electrode open potential U ₂ have the property of changing depending on the surface hydrogen amount θ _1N and the surface hydrogen amount θ _{2N, respectively.} Therefore, in the initial state of the cell 11 (for example, the state immediately after production), _{the relationship between the surface hydrogen amount θ 1N} and the initial potential E ₁ and the relationship between the surface hydrogen amount θ _2N and the negative electrode open potential U ₂ are measured. Accordingly, to create a map MP1 which defines change characteristics of the negative electrode open-circuit potential U ₂ with respect to the initial change in the characteristics of the potential E _1, and the change of the surface amount of hydrogen theta _2N relative surface amount of hydrogen theta change in _1N, and stored in the memory 32 deep. The ECU 30 can calculate the initial potential E ₁ and the negative electrode open potential U _{2 from the surface hydrogen amounts θ 1N} and θ _2N , respectively, by referring to the map MP1. A data table or a function may be used instead of the map MP1.

<Memory effect of nickel-metal hydride batteries>
Since the map MP1 (especially FIG. 8 (A) refer) shown in Figure 8 does not reflect the influence of the memory effect, in detail below method to reflect the influence of the memory effect in the positive electrode open-circuit potential U ₁ explain.

Figure 9 is a diagram showing an example of a change in the positive electrode open-circuit potential U ₁ by the memory effect. _{The positive electrode open potential U 1} (= initial potential E ₁ ) in the state where the memory effect does not occur (initial state) is represented by a alternate long and short dash line, and the positive electrode open potential U ₁ in the state where the memory effect occurs is represented by a solid line.

In FIG. 9A, the horizontal axis represents the SOC of the cell 11 and the vertical axis represents the potential. When the cell 11 is discharged after being left for a certain period of time, the positive electrode open potential U ₁ becomes lower than the _{initial potential E 1 due} to the memory effect on the discharge side. The potential difference (potential difference between discharge curves) due to the memory effect on the discharge side is referred to as "discharge memory amount" Mdc.

Although not shown, when the cell 11 is charged, the positive electrode open potential U ₁ becomes higher than the initial potential E _{1 due to the memory effect on the charging side.} The potential difference (potential difference between charging curves) due to the memory effect on the charging side is referred to as "charging memory amount" Mch. The memory amount M described in the formula (1) comprehensively represents the discharge memory amount Mdc and the charge memory amount Mch.

9 (A) is a diagram showing a change in the positive electrode open-circuit potential _{U 1} by the memory effect on SOC. On the other hand, in the present embodiment, as shown in FIG. 9B, the horizontal axis is changed from SOC to the average hydrogen amount θ _{1, ave of the} positive electrode active material 151. In this way, by changing the viewpoint (cut) when considering the effect of the memory effect from SOC to the average hydrogen amount θ _{1, ave} , the bridge between the hydrogen concentration distribution (local hydrogen amount distribution) and the memory amount M can be achieved. This is to be possible.

When the cell 11 is discharged, the hydrogen concentration _cs1 in the positive electrode active material 151 increases (see FIG. 5), so that the average hydrogen amount θ _{1, ave} increases. That is, the changing direction of SOC and the changing direction of average hydrogen amount θ _{1, ave} are opposite to each other.

The average amount of hydrogen when the cell 11 is used (here, the average amount of hydrogen before the start of discharge) is referred _{to as "amount of hydrogen used" θ 0.} The memory effect on the discharge side occurs in the range of the average hydrogen amount θ _{1, ave higher than the hydrogen amount used θ 0.} The magnitude of the discharge memory amount Mdc differs depending on the average hydrogen amount θ _{1, ave} (the average hydrogen amount larger than the hydrogen amount used θ _0). Although not shown, the magnitude of the charge memory amount Mch _{also differs depending on the average hydrogen amount θ 1, ave} (the average hydrogen amount less than the hydrogen amount used θ _0). Therefore, a specific calculation method of the memory amount M (Mdc, Mch) at each average hydrogen amount θ _{1, ave will be described below.}

<Integration of minute memory amount>
FIG. 10 is a diagram showing how the memory amount M increases with the use of the cell 11. In FIG. 10, the horizontal axis represents the elapsed time from the initial state of the cell 11, and the vertical axis represents the amount of memory M (magnitude).

The present inventors have conducted various evaluation tests for evaluating the amount of memory generated in the cell 11 used under various usage conditions (for example, under conditions where the temperature Tb and the like are different), and for each usage condition of the cell 11. Data showing the relationship between the amount of memory M and the elapsed time was acquired. In Figure 11 Figure 10 and described below, for ease of understanding, an example will be described in which the curve L _A ~L _C is acquired respectively corresponding to the three operating conditions A through C, in fact, more A similar curve is obtained for the conditions of use of. From the results of the above evaluation test, the present inventors have found that the amount of memory M generated during the elapse of a certain period is, for example, the amount of memory generated during Δt at each predetermined calculation cycle Δt. It was found that it can be calculated by sequentially calculating ΔM and integrating the minute memory amount ΔM. Further, the present inventors have found that the minute memory amount ΔM can be integrated even if it changes on the way.

FIG. 11 is a diagram for explaining the integration of the minute memory amount ΔM. In FIG. 11, the horizontal axis indicates the elapsed time from the initial state of the cell 11. The vertical axis indicates the usage conditions (for example, temperature Tb) of the cell 11 and the magnitude of the memory amount M in order from the top. Here, as shown in the above figure, a case where the usage condition is determined each time the calculation cycle Δt elapses and the usage condition changes in the order of A, B, and C will be described.

First, under use conditions A is referred to a curve L _A, small amount of memory ΔM is calculated for each calculation cycle Delta] t, it is further integrated. As a result, the amount of memory M produced with the use condition A, the M _A.

Next, when the use conditions are changed from A to B at time tb, the curve L _B curve in terms of memory capacity M = M _A in _(curve translating the curve L _B shown in the time axis direction in FIG. 10) L _B is referenced. Then, the minute memory amount ΔM is calculated for each calculation cycle Δt and further integrated. If the amount of memory M produced under conditions of use B is _{M B,} the amount of memory M at the end of the use condition B is the sum of the _{M A} and _{M B (M} A + _{M B).}

Furthermore, the use conditions are changed from B to C at time tc, the curve _{L C} terms of memory quantity M _{= (M} B + _{M C)} at (curve translating the curve _{L C} shown in the time axis direction in FIG. 10) curve _{L C} is referenced from. Then, the minute memory amount ΔM is calculated for each calculation cycle Δt and further integrated. If the amount of memory M generated under use conditions C is _{M C,} amount of memory M generated in the entire period is the sum of the _{M A} and _{M B} and _{M C (M A +} M B + _{M C).}

As described above, in the present embodiment, when the usage conditions of the cell 11 change, the curve referred to for calculating the minute memory amount ΔM is switched from one curve to another. The memory amount M calculated according to the curve before switching can be inherited even after switching. Then, from the time of switching, the minute memory amount ΔM is calculated according to the curve after switching, and is integrated into the memory amount M inherited from before the switching. It should be noted that such integration (curve inheritance) is possible when the memory amount M calculated according to a certain curve and the memory amount M calculated according to another curve are equal to the positive electrode active material 151. This is because the state of is considered to be the same.

<Range of average hydrogen amount>
As described with reference to FIG. 9B, when the cell 11 is charged from the _{amount of hydrogen used θ 0} when the cell 11 is used, the average amount of hydrogen θ _{1 is less than the amount of hydrogen used θ 0. In the range of, ave} , the positive electrode open potential U ₁ is higher by the amount of charge memory Mch as compared with the initial state. On the other hand, when the cell 11 is discharged, the positive electrode open potential U ₁ becomes lower by the discharge memory amount Mdc than in the initial state _{in the range of the average hydrogen amount θ 1, ave} , which is larger than the _{hydrogen amount used θ 0.} ..

In this way, in order to calculate how the _{positive electrode open potential U 1} changes during charging / discharging of the cell 11 after the memory effect occurs, charging / discharging with the _{amount of hydrogen used θ 0} as the starting point (reference point) It is necessary to calculate the curve (see, for example, the solid line in FIG. 9B). The charge-discharge curve, as described below, calculates the discharge amount of memory Mdc at each value within the range of greater than the amount of hydrogen used theta ₀ average hydrogen amount theta _{1, ave,} the amount of hydrogen used theta ₀ It can be obtained by calculating the charge memory amount Mch at each value within the range of the _{average hydrogen amount θ 1, ave} , which is smaller than that.

FIG. 12 is a diagram for conceptually explaining a method of calculating the charge / discharge curve after the memory effect occurs. In FIG. 12, the horizontal axis represents the average hydrogen amount θ _{1, ave} of the positive electrode active material 151, and the vertical axis represents the electric potential.

As described above, the memory amount M differs depending on the _{average hydrogen amount θ 1, ave.} Therefore, in the present embodiment, _{the range of the average hydrogen amount θ 1} (range of 0 to 1) is divided into 20 ranges of, for example, 0.05 each. Then, every time a predetermined calculation cycle Δt elapses for each of the 20 ranges, the minute memory amount ΔM is continuously calculated according to the usage conditions of the cell 11, and the calculated minute memory amount Δt is integrated. The memory amount M in each range is calculated by.

More specifically, the usage condition of the cell 11 depends on _{the combination (θ 1, ave} , T) of _{the average hydrogen amount θ 1, ave} and the absolute temperature T of the cell 11 during the elapsed calculation cycle Δt. It is a fixed condition. The map MP2 can be prepared in advance by performing an evaluation test in advance for each usage condition (θ _{1, ave, T) of the cell 11.}

FIG. 13 is a conceptual diagram of the map MP2 in the present embodiment. In the map MP2, the average hydrogen amount of 20 pieces is separately set for each range of _{θ 1, ave under the usage conditions (θ 1, ave} , T) of the cell 11 and the usage conditions (θ _{1, ave} , T). data indicating the correspondence relation between small memory amount ΔM occurring during the calculation period Δt has elapsed (see, for example, the curve L _a ~L _C in FIG. 10) is defined. The data format is not particularly limited, and may be a data table or a function (relational expression).

The ECU 30 refers to the data (curve) according to _{the usage conditions (θ 1, ave} , T) of the cell 11 during the calculation cycle Δt for each range of 20 average hydrogen amounts θ _{1, ave.} , The minute memory amount ΔM newly generated during the calculation cycle Δt is calculated. Further, the ECU 30 calculates the memory amount M by integrating the minute memory amount ΔM for the entire period up to that point for each of the 20 ranges. As described above, even if the usage conditions change in the middle, the minute memory amount ΔM can be integrated.

By using as large a value as possible regarding the number of divisions in the range of the average hydrogen amount θ _{1, ave} (20 in the above example) and the number of usage conditions in each range, a more detailed evaluation test result can be mapped MP2. The calculation accuracy of the memory amount M is improved because it can be reflected in. On the other hand, if the number of divisions becomes excessively large or the number of usage conditions becomes excessively large, the map size (the amount of data of the map MP2) increases, the capacity required for the memory 32 increases, and the computing load of the CPU 31 increases. Can be large. Therefore, it is desirable to determine the number of divisions in the range of the average hydrogen amount θ _{1, ave} and the number of usage conditions within each range so as to balance the calculation accuracy of the memory amount M and the processing capacity of the ECU 30.

<Elimination of memory effect>
When the cell 11 is charged and discharged, the average amount of hydrogen θ _{1 and the} amount of hydrogen used θ _{0 of} ave may change. In such a case, _{the change in the amount of hydrogen used θ 0} can be reflected in the integration result of the minute memory amount ΔM by doing the following.

FIG. 14 is a diagram for explaining an integration method of a minute memory amount ΔM in consideration of the _{amount of hydrogen used θ 0.} In FIG. 14, the horizontal axis represents the average hydrogen amount θ _{1, ave} , and the vertical axis represents the memory amount M. Here, a case will be described in which the cell cell 11 is discharged during the period from time t1 to time t2, and then the cell cell 11 is charged during the period from time t2 to time t3.

The integration result of the minute memory amount Δt up to the time t1 is shown in the upper part of FIG. Memory effect of the discharge side, not occur with a small average amount of hydrogen theta _{1, ave} range than the amount of hydrogen used theta _0, it occurs only to the extent of more than the amount of hydrogen used theta ₀ average hydrogen amount theta _{1, ave.} Therefore, the discharge memory amount Mdc is calculated by accumulating the minute memory amount ΔM only in the range of the average hydrogen amount θ _{1, ave , which is larger than the hydrogen amount used θ 0.} On the other hand, the memory effect of the charge side is not generated in the range of more than the amount of hydrogen used theta ₀ average hydrogen amount theta _{1, ave,} occurs only in the range of less than the amount of hydrogen used theta ₀ average hydrogen amount theta _{1, ave} .. Therefore, the charge memory amount Mch is calculated by accumulating the minute memory amount ΔM only in the range of the average hydrogen amount θ _{1, ave , which is smaller than the hydrogen amount used θ 0.}

When the cell 11 is discharged during the period from time t1 to time t2, the amount of hydrogen used θ ₀ increases. Then, in the range of the average hydrogen amount θ _{1, ave} , which is smaller than the increased hydrogen consumption amount θ ₀ , the memory effect on the discharge side is eliminated and the discharge memory amount Mdc becomes 0. However, the amount of discharge memory Mdc at the amount of _{hydrogen used θ 0 after the increase remains unresolved immediately.} As a result, for example, in FIG. 9B, when the discharge curve at time t1 is a curve shown by a solid line, at time t2, the discharge curve is shown by a dotted line (indicated by L (t = t2)). The shape changes.

On the contrary, when the cell 11 is charged during the period from the time t2 to the time t3, the amount of hydrogen used θ ₀ decreases. Then, in the range of the average hydrogen amount θ _{1, ave} , which is larger than the reduced hydrogen consumption amount θ ₀ , the memory effect on the charging side is eliminated, and the charging memory amount Mch becomes 0. However, the charge memory amount Mch at the reduced hydrogen consumption amount θ ₀ remains without being immediately eliminated.

As described above, in the present embodiment, the minute memory amount ΔM according to the usage conditions (θ _{1, ave , T) of the cell 11 is continuously calculated for each of the 20 ranges of the average hydrogen amount θ 1 and ave.} Then, the process of accumulating the calculated minute memory amount ΔM is repeatedly executed. At the time of this integration, the integrated amount up to that point is reset to 0 according to how _{the average hydrogen amount θ 1, ave} used hydrogen amount θ _{0 changes.}

<Functional block>
FIG. 15 is a functional block diagram of the ECU 30 related to the potential calculation process according to the present embodiment. The ECU 30 includes a battery parameter determination unit 310, a current density calculation unit 320, an overvoltage calculation unit 330, a concentration distribution calculation unit 340, a hydrogen amount calculation unit 350, an open potential calculation unit 360, and a memory amount calculation unit 370. , The potential calculation unit 380 and the like.

The battery parameter determination unit 310 receives the voltage Vb of the cell 11 from the voltage sensor 21 and the temperature Tb of the battery block (not shown) from the temperature sensor 23. The battery parameter determination unit 310 sets the voltage Vb as the voltage V between the terminals of the cell 11 and converts the temperature Tb into the absolute temperature T (unit: Kelvin). Further, the battery parameter determination unit 310 determines other parameters in the battery model formula described later according to the absolute temperature T and the like. More specifically, the battery parameter determination unit 310 determines parameters such as the exchange current density i _oji , the diffusion coefficient D _sj of the active material, the reaction resistance Rr, and the DC resistance Rd according to the absolute temperature T and the like.

More specifically, the exchange current density _io1 is the current density when the oxidation current density (anode current density) in the positive electrode active material 151 and the reduction current become equal. The exchange current density i _o1 has a characteristic that changes depending on the surface hydrogen amount θ _{1N and the absolute temperature T.} Therefore, the surface calculated by the hydrogen amount calculation unit 350 by preparing in advance a characteristic map (not shown) that defines the correspondence between the exchange current density _io1 and the surface hydrogen amount θ _{1N and the absolute temperature T. The exchange current density io1} can be calculated from the amount of hydrogen θ _1N (described later) and the absolute temperature T. Since the same applies to the exchange current density _io2 , the detailed description will not be repeated.

The reaction resistance Rr is a resistance component when charges are transferred and received on the surfaces of the positive electrode active material 151 and the negative electrode active material 152. The reaction resistance Rr can be calculated from the absolute temperature T and the exchange current density _ioji (j = 1, 2) according to the following formula (6).

The DC resistance Rd is a resistance component when hydrogen ions and electrons move between the positive electrode active material 151 and the negative electrode active material 152. The DC resistance Rd has a characteristic that changes depending on the absolute temperature T. Therefore, the DC resistance Rd is calculated from the absolute temperature T by preparing in advance a characteristic map (not shown) that defines the correspondence between the DC resistance Rd and the absolute temperature T based on the measurement result of the DC resistance Rd. can do.

Similarly, the diffusion coefficient D _sj of the active material has a dependence on the surface hydrogen amounts θ ₁ , θ ₂ and the absolute temperature T, and therefore can be calculated using a map (not shown) prepared in advance. It is not essential to use both the surface hydrogen amounts θ _1N , θ _2N and the absolute temperature T as arguments for each of the above maps, and although the accuracy may decrease, only one of them (for example, only the absolute temperature T) should be used. It may be an argument. Each parameter determined by the battery parameter determination unit 310 is appropriately output to another functional block.

The current density calculation unit 320 receives parameters such as the voltage V between terminals, the exchange current density _ioj, and the DC resistance Rd from the battery parameter determination unit 310, and also receives the positive electrode open potential U ₁ and the negative electrode open potential U _{2 from the potential calculation unit 380.} Receive. The current density calculation unit 320 calculates the current density I according to the following equation (7). As the positive electrode open potential U ₁ and the negative electrode open potential U ₂ in the equation (7), the calculation results in the previous calculation cycle are substituted.

Equation (7) is a nonlinear equation. To calculate the current density I from equation (7), an iterative method such as Newton's method is used. That is, after assuming the initial value of the current density I, the current value of the voltage V between the terminals is calculated by substituting each parameter such _{as the exchange current density ioj with the absolute temperature T or the like as an argument.} The current density I is obtained from the equation (7) by iteratively calculating until the voltage V between the terminals calculated in this way and the voltage V between the terminals detected by the voltage sensor 21 converge within a predetermined error. be able to. Although an example of voltage input has been described here, the current density I may be calculated from the current input, that is, the value detected by the current sensor 22, and in the case of current input, the convergence calculation becomes unnecessary.

The current density calculation unit 320 may calculate the current density I by using the following formula (8) instead of the formula (7). Equation (8) is a simplified equation of equation (7). Specifically, in the formula (8), the arcsinh term is linearly approximated in the formula (7), and the parameter on the right side of the above formula (6) included in the formula (7) is replaced with the reaction resistance Rr. is there.

Furthermore, the current density calculating unit 320 calculates the reaction current density j _j from the current density I, and outputs the overvoltage calculation unit 330 and the density distribution calculation section 340. The reaction current density j _j corresponds to the hydrogen production rate per unit volume of the active material. Since the following equation (9) holds between the current density I and the reaction current density j _j , the current density I can be converted _{into the reaction current density j j.}

Overvoltage calculating unit 330, along with receiving the absolute temperature T and exchange current densities _{i oj} from the battery parameter determining section 310 receives a reaction current density _{j j} from the current density calculating unit 320. _{The overvoltage calculation unit 330 sets the overvoltage η 1} on the positive electrode side and the overvoltage η ₂ on the negative electrode side according to the following equation (10) (see Patent Document 1 for details) derived from the Butler-Volmer relational equation. It is calculated and output to the potential calculation unit 380.

_{The concentration distribution calculation unit 340 receives the diffusion coefficient D sj} of the active material from the battery parameter determination unit 310 _{and the reaction current density j j} from the current density calculation unit 320. Details are described in Patent Document 1 and the like, but the following equation (11) is a diffusion equation in a polar coordinate system. The boundary conditions of the equation (11) can be set as the following equations (12) and (13). Density distribution calculation section 340, equation (11) to according to (13), the interior of the hydrogen concentration distribution _c s1k of the positive electrode active material 151 and (k = 1 to N), the interior of the hydrogen concentration distribution _{c S2K} of the negative electrode active material 152 Is calculated and output to the hydrogen amount calculation unit 350.

The hydrogen amount calculation unit 350 receives the hydrogen concentration distribution c _sjk (j = 1, 2) from the concentration distribution calculation unit 340. Hydrogen amount calculation unit 350, calculates the local surface weight theta _1N of the positive electrode active material 151 on the basis of the hydrogen concentration distribution _{c s1k,} to calculate the surface amount of hydrogen theta _2N of the negative electrode active material 152 on the basis of the hydrogen concentration distribution _{c S2K,} It is output to the open potential calculation unit 360 (see the above equation (4)). Further, the hydrogen amount calculation unit 350 calculates the average hydrogen amount θ _{1, ave} (more specifically, the hydrogen amount used θ _{0 ) from the hydrogen concentration distribution c s1k} according to the above equation (5), and the memory amount calculation unit 370. Output to.

The open potential calculation unit 360 receives the absolute temperature T from the battery parameter determination unit 310 and the surface hydrogen amounts θ _1N and θ _2N from the hydrogen amount calculation unit 350. The open potential calculation unit 360 calculates the initial potential E _{1 from the surface hydrogen amount θ 1N} and calculates the negative electrode open potential U ₂ from the surface hydrogen amount θ _2N by referring to the map MP1 shown in FIG. The calculated initial potential E ₁ and the negative electrode open potential U ₂ are output to the potential calculation unit 380.

The memory amount calculation unit 370 calculates the memory amount M for each range _{of the average hydrogen amount θ 1, ave by doing as follows.}

FIG. 16 is a functional block diagram showing a more detailed configuration of the memory amount calculation unit 370. The memory amount calculation unit 370 includes a usage condition setting unit 371, a minute memory amount calculation unit 372, and an integration unit 373.

The use condition setting unit 371 receives the absolute temperature T from the battery parameter determination unit 310 and the hydrogen amount θ ₀ used from the hydrogen amount calculation unit 350. By referring to the map MP2 shown in FIG. 13, the usage condition setting unit 371 _{draws a curve according to the usage conditions (θ 1, ave} , T) of the cell 11 for each range of the average hydrogen amount θ _{1, ave.} It is selected and output to the minute memory amount calculation unit 372.

The minute memory amount calculation unit 372 uses the curve from the usage condition setting unit 371 to calculate the minute memory amount ΔM newly generated during the predetermined calculation cycle Δt for each range _{of the average hydrogen amount θ 1, ave.} , Output to the integration unit 373.

The integration unit 373 integrates the minute memory amount ΔM from the minute memory amount calculation unit 372 for each range _{of the average hydrogen amount θ 1, ave.} When the amount of hydrogen used θ ₀ changes, the accumulated amount up to that point is appropriately reset (set to 0) as described with reference to FIG. The memory amount M in each range of the average hydrogen amount θ _{1, ave is output to the potential calculation unit 380.}

Returning to Figure 15, the potential calculating unit 380 receives the initial potential E1 and the negative electrode open-circuit potential _{U 2} from the open voltage calculating unit 360 receives the amount of memory M from the memory amount calculating section 370, the overvoltage eta ₁ from overvoltage calculating section 330, Receive η _2. The potential calculation unit 380 outputs the positive electrode open potential U ₁ and the negative electrode open potential U ₂ to the current density calculation unit 320. Further, the potential calculation unit 380 calculates the positive electrode potential V ₁ according to the above formula (1) (V ₁ = E ₁ + M + η ₁ ), and calculates the _{negative electrode potential V 2} according to the above formula (2) _{(V 2} = U). ₂ + η ₂ ). _{The positive electrode potential V 1} and the negative electrode potential V ₂ calculated by the potential calculation unit 380 are output to a charge / discharge control unit (not shown), and the charge / discharge control unit executes the charge / discharge control described with reference to FIGS. 3 and 4. Will be done.

<Processing flow of potential calculation processing>
FIG. 17 is a flowchart showing the potential calculation process (process of S11 of FIG. 3 and S21 of FIG. 4) in the present embodiment. The flowchart shown in FIG. 17 and FIG. 19 described later is called and executed from the main routine (not shown) every predetermined calculation cycle Δt (for example, Δt = 100 ms). Each step included in these flowcharts is basically realized by software processing by the ECU 30, but a part or all of them may be realized by hardware (electric circuit) manufactured in the ECU 30.

In S101, the ECU 30 acquires the voltage Vb of the cell 11 from the voltage sensor 21 and the temperature Tb of the battery block (not shown) from the current sensor 22. In the subsequent processing, the ECU 30 uses the voltage Vb as the voltage V between the terminals and converts the temperature Tb into the absolute temperature T.

The ECU30 memory 32, calculated in the previous computation cycle, the hydrogen concentration distribution _c s1k inside of the positive electrode active material 151 (k = 1~N), hydrogen concentration distribution _{c S2K} inside of the negative electrode active material 152 Is remembered. The ECU 30 reads out the hydrogen concentration distribution c _sjk (j = 1, 2) calculated in the previous calculation cycle. In the first calculation cycle after the start switch (not shown) of the vehicle 100 is pressed (for example, the ignition is turned on), the hydrogen concentration distribution c _{sjk stored in the memory 32 in the calculation cycle immediately before the ignition of the vehicle 100 is turned off.} Is read out. The ECU 30 calculates the surface hydrogen amount θ _{1N from the hydrogen concentration c s1N in} the outermost peripheral region of the positive electrode active material 151, and calculates the surface hydrogen amount θ _{2N from the hydrogen concentration c s2N in} the outermost peripheral region N of the negative electrode active material 152. (Refer to the above equation (4)) (S102).

In S103, the ECU 30 calculates the initial potential E _{1 from the surface hydrogen amount θ 1N} and calculates the negative electrode open potential U ₂ from the surface hydrogen amount θ _2N by referring to the map MP1 shown in FIG.

In S104, the ECU 30 calculates each parameter _{of the exchange current density i oji} , the reaction resistance Rr, the DC resistance Rd, and the diffusion coefficient D _{sj of the active material.} Since this calculation method has been described in detail with reference to FIG. 15, the description will not be repeated.

In S105, the ECU 30 calculates the current density I from the positive electrode open potential U ₁ , the negative electrode open potential U ₂ , the exchange current density _ioj, and the absolute temperature T according to either of the above equations (7) and (8). .. Further, the ECU 30 converts the current density I into the reaction current density j _j (j = 1, 2) according to the above equation (9).

In S106, the ECU 30 calculates the overvoltage η _j (j = 1, 2) from the absolute temperature T, the reaction current density j _j, and the exchange current density _{ioj according to the above equation (10).}

_{In S107, the ECU 30 has a hydrogen concentration distribution c s1k} (k = 1 to N) inside the positive electrode active material 151 and a hydrogen concentration distribution c inside the negative electrode active material 152 according to the above equations (11) to (13). _{Calculate s2k} . The calculation result of the hydrogen concentration distribution c _sjk (j = 1, 2) is stored in the memory 32 in preparation for the processing of S102 in the next calculation cycle.

_{In S108, the ECU 30 calculates the local hydrogen amount distribution θ 1k} (k = 1 to N) _{from the hydrogen concentration distribution c s1k} inside the positive electrode active material 151 calculated in S107 according to the above formula (4).

In S109, the ECU 30 calculates _{the average hydrogen amount θ 1, ave} , which is the average amount of the entire region k, from _{the local hydrogen amount distribution θ 1k} calculated in S108 (see the above equation (5)). This average hydrogen amount θ _{1, ave} is used as the hydrogen amount used θ ₀ .

In S110, the ECU 30 calculates the minute memory amount ΔM in the current calculation cycle for each range of _{20 average hydrogen amounts θ 1, ave.} Since this calculation method has been described in detail with reference to FIGS. 12 and 13, the description will not be repeated.

In S111, the ECU 30 calculates the memory amount M by integrating the minute memory amount ΔM calculated in S110 for each of the above 20 ranges. As the charge and discharge of the cells 11, if the amount of hydrogen used theta ₀ from the previous operation cycle has changed in a range between the amount of hydrogen used theta ₀ before the change and the amount of hydrogen used theta ₀ after the change, The accumulated amount up to that point is reset as appropriate. Since the method of integration and reset has also been described in detail in FIG. 14, the description will not be repeated.

In S112, ECU 30 includes a initial potential _{E 1} calculated in S103, the overvoltage eta ₁ calculated in S106, by using the amount of memory M calculated in S111, to calculate the positive electrode potential _{V 1} (See equation (1)). This positive electrode open-circuit potential U _1, by adding an overvoltage eta ₁ calculated in S106, the positive potential V1 is calculated. When the initial potential E ₁ and the memory amount M are added for _{each of the above 20 ranges, the positive electrode open potential U 1} may not be smoothly connected between the adjacent ranges. Therefore, an appropriate function (for example, a linear function) can be used to complement a range and a range adjacent to the range. Thereby, a smooth positive electrode open potential U ₁ can be obtained with respect to the average hydrogen amount θ _{1, ave.}

Further, the ECU 30 calculates the negative _{electrode potential V 2} for each of the above 20 ranges by using _{the negative electrode open potential U 2} calculated in S103 and the overvoltage η ₂ calculated in S106 (Equation (2). )reference).

As described above, according to the present embodiment, by referring to the map MP2 (see FIG. 13) prepared in advance, the usage conditions (θ) of the cell 11 are set for each range of the _{average hydrogen amount θ 1, ave. The minute memory amount ΔM according to 1, ave} , T) is calculated one after another and further integrated. Thus the amount of memory M, which is calculated by the map MP1 is added to the initial potential E ₁ calculated from the surface amount of hydrogen theta _1N by reference (see FIG. 8). As a result, the influence of the memory effect generated on the positive electrode 141 can be reflected in the _{positive electrode open potential U 1} , so that the calculation accuracy of the _{positive electrode potential V 1 can be improved.}

Further, as described in S105 of the flowchart shown in FIG. 17, when calculating the current density I, the calculation results _{of the positive electrode open potential U 1} and the negative electrode open potential U _{2 in the previous calculation cycle are used.} .. Since the positive electrode open potential U ₁ is calculated with high accuracy in consideration of the influence of the memory effect, the current density I is also highly accurate as compared with the case where the influence of the memory effect is not taken into consideration. Can be calculated. As a result, the reaction current density j ₂ and the overvoltage η ₂ of the negative electrode active material 152 are also calculated with high accuracy (see equation (10)). As a result, at S112, it is possible to improve the negative electrode calculation accuracy of the potential V ₂ in the current calculation cycle (Equation (2) refer).

Further, in the present embodiment, as an example of charge / discharge control, when the positive electrode potential V ₁ becomes higher than the upper limit potential UL ₁ during charging (YES in S12 of FIG. 3), charging is performed as compared with the normal state. The power upper limit value Win is set small (S14). Further, when the positive electrode potential V ₁ becomes lower than the lower limit potential LL ₁ at the time of discharging (YES in S23 of FIG. 4), the discharge power upper limit value Wout is set smaller than that at the normal time (S24). According to this embodiment, since it is possible to calculate the positive electrode potential V ₁ with high accuracy, the determination based on the positive potential V1 can be performed appropriately. As a result, the positive electrode 141 can be protected from deterioration due to a side reaction. Although the detailed description will not be repeated, the negative electrode 142 can be similarly protected from deterioration due to a side reaction.

In the present embodiment, the case where a nickel-metal hydride battery is used as an example of the alkaline secondary battery has been described, but the alkaline secondary battery to which the method described in the present embodiment can be applied is limited to this. is not it. The method of the present embodiment can also be applied to other alkaline secondary batteries (for example, nickel-cadmium batteries or nickel-zinc batteries) containing nickel hydroxide as a positive electrode active material and generating a memory effect.

[Modification 1]
In the positive electrode of a nickel-metal hydride battery, a phenomenon is known in which the _{positive electrode open potential U 1} changes according to the past usage history (hysteresis) of the cell 11 apart from the memory effect. Therefore, it is preferable to calculate the positive electrode open potential U _{1 in consideration of this phenomenon.} In the first modification, a method of calculating the _{positive electrode open potential U 1 after further considering the hysteresis will be described.}

Figure 18 is a diagram for illustrating a calculation method of the positive electrode open-circuit potential U ₁ in Modification 1. In FIG. 18, the horizontal axis represents the average local hydrogen amount θ _{1, ave} , and the vertical axis represents the electric potential.

In the first modification, in order to consider hysteresis _{, instead of the amount of hydrogen used θ 0} used in the above-described embodiment, the “average amount of hydrogen used” θ _0, which is the time average of the amount of hydrogen used θ _{0 in a predetermined period, is θ 0. , Mean} is used. Further, hysteresis occurs within a range in which the amount of hydrogen used θ _{0 changes in a predetermined period.} Therefore, the maximum value of the amount of hydrogen used theta ₀ in the predetermined time period "maximum amount of hydrogen used," a represents a theta _{0, max,} the minimum value of the amount of hydrogen used theta ₀ "minimum amount of hydrogen used" a theta _{0, Expressed as min} .

In the range where the average hydrogen amount θ _{1, ave} is greater than or equal to the maximum hydrogen amount θ _{0, max} , the influence of hysteresis does not need to be considered, so _{it is between two adjacent positive electrode open potentials U 1} (between two adjacent points). ) Is linearly complemented. Similarly, in the range where the average hydrogen amount θ _{1, ave} is the minimum hydrogen amount θ _{0, min} or less, the space between the two adjacent positive electrode open potentials U ₁ is linearly interpolated.

On the other hand, in the range where the average hydrogen amount θ _{1, ave} is between the average hydrogen consumption θ _{0, main} and the maximum hydrogen consumption θ _{0, max} , the influence of hysteresis can occur. However, when the average amount of hydrogen used is θ _{0 and main , the potential is close to the initial potential E 1} as described in FIG. 9B, so that the influence of hysteresis is considered to be relatively small.

Therefore, in the modified example 1, instead of the complementing method described in S112 of the flowchart shown in FIG. 17 (a method of linearly complementing the entire adjacent range, for example), the positive electrode open potential at an _{average hydrogen consumption θ 0, mean.} and U _1, complement is performed so as to connect the positive electrode open-circuit potential U ₁ at maximum amount of hydrogen used θ _{0, max.} As an example, as shown in the following equation (14), complementation by a power function with a natural number n as a power exponent can be performed. The natural number n is predetermined by an experiment or the like.

On the other hand, in the range where the average hydrogen amount θ _{1, ave} is between the minimum hydrogen consumption θ _{0, min} and the average hydrogen consumption θ =, the complementation by the power function shown in the following equation (15) is performed.

As described above, according to the first modification, in addition to the memory effect, because the influence of the hysteresis of the cell 11 can be reflected in the positive electrode open-circuit potential U _1, to improve the calculation accuracy of the positive electrode open-circuit potential U ₁ As a result, the calculation accuracy of the _{positive electrode potential V 1 can be improved.}

[Modification 2]
The electrolytic solution, hydroxide ions which are reactants (OH ^-) concentration c _e of change over time, the concentration gradient may occur. _{As a result, a concentration overvoltage Δφ e} due to the concentration gradient is generated between the positive electrode active material 151 and the negative electrode active material 152, and the positive electrode potential V ₁ and the negative electrode potential V ₂ may be affected. In the second modification, in addition to the memory effect, by further considering the concentration overpotential [Delta] [phi _e, described technique of the calculation accuracy of the positive electrode potential V ₁ and the negative electrode potential V ₂ is further improved.

FIG. 19 is a flowchart showing the potential calculation process in the second modification. This flowchart differs from the flowchart of the embodiment (see FIG. 17) in that it further includes the processing of S206A and S206B.

In S206A, ECU 30 calculates a density difference .DELTA.c _e reactant between the positive electrode active material 151 and negative electrode active material 152. Density difference .DELTA.c _e reactant, the effective diffusion coefficient _D ^{e eff} of the electrolytic solution, the volume fraction of electrolyte epsilon _e and hydroxide ions ^- transport number t of (OH) _- because it depends on the ^o, for example, the following It can be calculated according to the formulas (16) to (18) (see Patent Document 4 for details). In the equation (16), the parameter with (t) indicates that it belongs to the previous calculation cycle, and the parameter with (t + Δt) indicates that it belongs to the current calculation cycle.

In S206b, ECU 30 calculates the concentration overpotential [Delta] [phi _e from the density difference .DELTA.c _e reactant calculated in S206A. Specifically, by determining the form of a map (not shown) determined by preliminary evaluation experiments the correspondence between the density difference .DELTA.c _e and concentration overpotential [Delta] [phi _e, calculates the concentration overpotential [Delta] [phi _e from the density difference .DELTA.c _e can do.

In the embodiment, it has been explained that the current density I is calculated according to the above equation (7) or (8) in S105 of the flowchart shown in FIG. On the other hand, in the modified example 2, the following equation (19) or equation (20) is used for calculating the current density I (S205). As a result, the current density I is calculated by further using _{the concentration overvoltage Δφ e} calculated in the previous calculation cycle in addition to _{the initial potential E 1} and the negative electrode open potential U _{2 calculated in the previous calculation cycle.} Therefore, the influence of the concentration overvoltage Δφ _e can be reflected in the current density I.

Since the remaining processes of S201 to S204, S206, and S207 to S212 are the same as the processes of S101 to S104 and S106 to S112 in the flowchart of the embodiment, the description will not be repeated.

As described above, according to the modified example 2, the current density I is calculated in consideration of the _{concentration overvoltage Δφ e} caused by the concentration distribution of the reactants in the electrolytic solution. Accordingly, in order to improve the accuracy of calculation of the current density I, it is possible to turn improve the calculation accuracy of the positive electrode potential V ₁ and the negative electrode potential V ₂ more.

[Modification 3]
In Modification 2, an example was described by referring to a pre-prepared map, the concentration overvoltage [Delta] [phi _e from the density difference .DELTA.c _e reactant is calculated. However, the _{method for calculating the concentration overvoltage Δφ e} is not limited to the method using a map, and the calculation formula described below can also be used.

The following equation (21) is established between the potential φ _{e of the} electrolytic solution, the concentration c _e of the reactant, and the reaction current density j _j. In the formula (21), the effective ionic conductivity of _{the electrolytic solution is represented by κ e} ^eff , and the effective diffusion conductivity of the electrolytic solution is represented by κ _D ^eff .

First, assuming that the voltage drop due to the DC resistance Rd and the concentration overvoltage Δφ _e in the electrolytic solution are independent of each other, the following equation (22), which is a difference equation of the above equation (21), is derived.

Since the value in parentheses on the left side of the above equation (22) is 0, the following equation (23) is further derived from the equation (22).

As shown in the following formula (24) may represent the concentration overpotential [Delta] [phi _e as a function of the concentration c _e of the reactants from the above equation (23). The coefficient γ means the following equation (25). In equation (25), _{the correlation between the amount of change in salt concentration (ce} ) and the amount of change in average activity coefficient (f _± ) is obtained in advance by experiments or the like, and is retained as a map or function to obtain salt concentration. The amount of change in the average activity coefficient with respect to the amount of change can be calculated.

By further modifying the above equation (24), the following equation (26) is obtained. In formula (26), the concentration of the reactant at the positive electrode and the concentration of the reactant at the negative electrode are represented by _ce1 and _{ce2, respectively.} In addition, the concentration (initial concentration) of the reactant before the concentration gradient is generated is represented _{by ce and ini.} The initial concentrations _{ce and ini} are known values.

Since the equation (26) includes a logarithm, the following approximation equation (27) can be obtained by linear approximation.

Equation (27) expresses the concentration overvoltage Δφ _e as a linear equation of the concentration difference Δ c _e. Accordingly, in S206B of the flowchart shown in FIG. 19, even if no if ECU30 has a memory of high processing power and large capacity, it is possible to easily calculate the concentration overpotential △ phi _e from the density difference .DELTA.c _e it can.

[Modification example 4]
_{If the hydrogen concentration distribution cs2k} inside the negative electrode active material 152 of the hydrogen storage alloy is biased, the amount of local volume change will differ for each region k (k = 1 to N) of the negative electrode active material 152. Distortion can occur in the crystal lattice of the hydrogen storage alloy. Due to this strain, stress is generated in the negative electrode active material 152, and when the generated stress exceeds the mechanical limit strength of the negative electrode active material 152, cracks may occur in the negative electrode active material 152.

FIG. 20 is a schematic view for explaining the cracks generated in the negative electrode active material 152. As shown in FIG. 20, the formation of cracks 153 in the negative electrode active material 152 exposes a new surface. For example, in a lithium ion secondary battery, when a crack occurs in the negative electrode active material, a film is formed on the exposed surface by the reaction between the negative electrode active material and the electrolytic solution, and the reaction resistance of the negative electrode increases. In the cell 11, the influence of such film formation is extremely small. In the cell 11, the reaction surface area of the negative electrode active material 152, which can contribute to the battery reaction, is simply increased. Therefore, the reaction resistance of the negative electrode (negative electrode active material 152) decreases, which increases _{the exchange current density io2 of the negative electrode.} As a result, the current density I and the reaction current density j _j change, so that the positive electrode open potential U ₁ and the negative electrode open potential U ₂ may change (see equations (7) to (10) above). ). Therefore, in the cell 11, it is preferable to consider the effect that _{the exchange current density io2} of the negative electrode active material 152 increases due to the generation of cracks 153 as time passes.

The amount of cracks 153 (crack amount) generated in the negative electrode active material 152 can be expressed using the crack index value X as described below. The crack amount is an index value that can include both the number of cracks 153 and the depth of the cracks 153.

FIG. 21 is a diagram for explaining the calculation process of the crack index value X. In FIG. 21, the horizontal axis represents the elapsed time, and the vertical axis represents the stress Fs acting in the negative electrode active material 152.

When the stress Fs exceeds the mechanical limit strength (typically the tensile limit strength) of the negative electrode active material 152, crack 153 occurs. Therefore, as shown with diagonal lines, the progress of damage due to cracks within a predetermined period is performed by time-integrating the excess amount (in other words, the damage amount) ΔF, which is the amount of stress Fs exceeding the limit strength Flim. The degree can be calculated.

More specifically, as shown in the following equation (28), the crack index value X (t2) at the time t2 when the period Δt has elapsed from the time t1 is the increase amount ΔX of the crack index value during Δt at the time t1. It is calculated by adding to the crack index value X (t1) in.

In the formula (28), the increase amount ΔX of the crack index value is calculated by multiplying the “crack generation coefficient δ” per unit time based on the stress excess amount ΔF at time t2 (or time t1) by the period Δt. (See equation (29) below).

Regarding the relationship between the excess stress ΔF and the crack generation coefficient δ, the durability test of the cell 11 is performed in advance under various conditions in which the combination (Ib, Tb) of the current Ib flowing through the cell 11 and the temperature Tb is different. It can be quantified by doing so. Specifically, the following quantification method can be adopted.

After performing the durability test under various above conditions, the cell 11 is disassembled, and the negative electrode active material 152 is observed by SEM (Scanning Electron Microscope) or subjected to various image processing to combine the conditions (Ib). , Tb), the amount of cracks generated can be quantified. On the other hand, the stress Fs generated in the negative electrode active material 152 during the durability test for each combination (Ib, Tb) is hooked to, for example, the hydrogen concentration distribution calculation (see S107 in FIG. 17) using the diffusion equation (11). It can be calculated by further incorporating the stress calculation according to the law of. Therefore, the critical strength Flim can be defined by specifying the conditions under which cracks are confirmed (conditions under which cracks begin to occur) by SEM observation or the like and calculating the stress Fs under those conditions. As a result, it is possible to calculate the amount of increase ΔX of the crack index value due to the stress Fs exceeding the limit strength Flim and the time when the stress Fs exceeds the limit strength Flim. Can be specified in. In this way, the crack generation coefficient δ can be prepared in advance as a map (not shown) for each combination of conditions (Ib, Tb) and stored in the memory 32.

FIG. 22 is a diagram showing the relationship between the crack index value X and the exchange current density _{io2 of the negative electrode active material 152.} In FIG. 22, the horizontal axis indicates the elapsed time. The vertical axis shows the crack index value X, the reaction resistance of the negative electrode active material 152, and the exchange current density _io2 of the negative electrode active material 152 (the upper direction is the increasing direction) in this order from the top.

As shown in FIG. 22, as the crack index value X increases, the reaction resistance of the negative electrode active material 152 decreases, and thereby the exchange current density _io2 of the negative electrode active material 152 increases. A relationship as shown in FIG. 22 as an example is stored in the memory 32 of the ECU 30 as a map.

The ECU 30 sequentially integrates the increase amount ΔX by another routine (not shown) according to the above equations (28) and (29), and calculates the crack index value X. Then, ECU 30 is (see S104 in FIG. 17) when calculating the exchange current density _{i o2} in potential calculating process to calculate the exchange current density _{i o2} from cracking index X using the map shown in FIG. 22. Thus, it is possible to reflect the increase in the exchange current density i _o2 due to cracks 153 may occur in the negative electrode active material 152, as a result, is possible to further improve the calculation accuracy of the positive electrode potential V ₁ and the negative electrode potential V ₂ it can.

[Modification 5]
In a nickel-metal hydride battery, the hydrogen concentration inside the positive electrode active material can be changed by inserting hydrogen ions into the positive electrode active material by self-discharge. In general, the effect of self-discharge in a nickel-metal hydride battery is larger than the effect of self-discharge in a lithium ion secondary battery or the like. Therefore, in the modified example 5, a configuration that further considers the governing equation regarding self-discharge will be described.

The self-discharge current density (self-discharge current density i ₁ ^side ) can be expressed using, for example, the Tafel equation or the Butler-Volmer equation. The following equation (30) expresses the _{self-discharge current density i 1} ^{side by the Tafel equation.} In the formula (30), the reference potential at which self-discharge occurs is represented by _Ueq.

The self-discharge current density i ₁ ^side is a function of the absolute temperature T and also a function of _{the surface hydrogen amount θ 1N of the positive electrode active material 151.} Therefore, the dependence of the self-discharge exchange current density i _{0, 1} ^{side on} the absolute temperature T and the surface hydrogen amount θ _{1 N is} obtained by a preliminary evaluation test, and a map (not shown) is created in advance to obtain the self-discharge current density. i ₁ ^side can be calculated.

By further include formula (30) to the battery model, the influence of the self-discharge is further reflected in the positive electrode open-circuit potential U _1. As a result, the calculation accuracy of the positive electrode open potential U ₁ can be improved, and the calculation accuracy of the positive electrode potential V _{1 can be further improved.}

[Modification 6]
In the positive electrode of the cell 11, the _{generation of Ni 2} O ₃ H causes deterioration in which the unipolar capacity of the positive electrode is reduced, and in the negative electrode, the negative electrode active material is inactivated by the negative electrode oxidation, so that the unipolar capacity of the negative electrode is reduced. Deterioration can occur. Further, a composition correspondence deviation (so-called negative electrode charge reserve deviation or discharge reserve deviation) is likely to occur between the positive electrode and the negative electrode. As a result, the full charge capacity of the cell 11 is reduced (see Patent Document 1 for details of the reduction in the full charge capacity). _{In the sixth modification, a method of calculating the full charge capacity Q d} of the deteriorated single battery 11 by using three deterioration parameters (k1, k2, ΔQs) will be described (see, for example, Patent Documents 1 and 6).

The positive electrode capacity Q ₁ of the deteriorated cell 11 is represented by the product of the positive electrode capacity retention rate k1 and the positive electrode capacity Q _{1, ini in the initial state (Q 1} = k ₁ × Q _{1, ini} ). Similarly, the negative electrode capacity Q ₂ of the deteriorated cell 11 is represented by the product of the negative electrode capacity retention rate k ₂ and the negative electrode capacity Q _{2, ini in the initial state (Q 2} = k ₂ × Q _{2,). ini} ). On the other hand, the composition correspondence deviation capacity ΔQ _s between the positive electrode and the negative electrode is represented by ΔQ _s = k ₂ × Q _{2, ini} × Δθ ₂ . Here, Δθ ₂ is the amount of deviation of the negative electrode composition axis with respect to the positive electrode composition axis.

The deterioration parameters k ₁ , k ₂ , and ΔQ _s can be calculated from _{the positive electrode open potential U 1} and the negative electrode open potential U ₂ by using a known method as described in, for example, Patent Document 6. Then, by using the deterioration parameters calculated from the positive electrode open potential U ₁ and the negative electrode open potential U ₂ , the full charge capacity Qd of the cell 11 can be calculated according to the following formula (31).

In equation (31), the influence of the deterioration parameter _{k 1} to a thickness _{L 1} and volume fraction epsilon _s1 of the positive electrode active material 151 of the positive electrode 141 are reflected _{(L 1 = L 10 × √k} 1, ε s1 = ε _s10 × √k _{1, however, L 10} and epsilon _s10 represents the initial value before deterioration). The plate area is represented by S.

Further, in the equation (31), the local hydrogen amount θ _1N when the SOC of the cell 11 corresponds to 100% is represented by θ _{1_100} , and the local hydrogen amount θ _1N when the SOC corresponds to 0% is θ _{1_0} . Represent. The effects of the memory effect are reflected in these values θ _{1_100} and θ _{1_0 by the method described in the embodiment.}

As described above, according to the modification 6, in consideration of the memory effect positive electrode open-circuit potential U ₁ is calculated, isolated using a positive electrode open-circuit potential U ₁ calculated with high precision, and a negative electrode open-circuit potential U ₂ The full charge capacity Q _d of the battery 11 is further calculated. Therefore, the calculation accuracy can be improved also for the full charge capacity Q _d.

In the above-described embodiment and each modification, a method of integrating the amount of memory for each range of the _{amount of hydrogen used θ 0 in increments of 0.05 has been described.} However, in a system in which the dependence on the amount of hydrogen used θ ₀ is small and the memory effect is produced almost uniformly, the amount of memory may be integrated regardless of the _{amount of hydrogen used θ 0.} In this case, since the calculation load of the ECU 30 can be reduced, the configuration is more suitable for in-vehicle use.

The embodiments disclosed this time should be considered as exemplary in all respects and not restrictive. The scope of the present invention is shown by the scope of claims rather than the description of the embodiment described above, and is intended to include all modifications within the meaning and scope equivalent to the scope of claims.

1 Motor generator (MG), 2 Power transmission gear, 3 Drive wheels, 4 Power control unit (PCU), 5 System main relay (SMR), 10 sets of batteries, 11 cell cells, 12 cases, 13 safety valves, 14 electrode bodies, 21 Voltage sensor, 22 Current sensor, 23 Temperature sensor, 30 Electronic control unit (ECU), 31 CPU, 32 Memory, 100 Vehicles, 121 Case body, 122 lid, 141 positive electrode, 142 negative electrode, 143 separator, 151 positive electrode active material , 152 Negative electrode active material, 153 cracks, 200 Battery system, 310 Battery parameter determination unit, 320 Current density calculation unit, 330 Overvoltage calculation unit, 340 Concentration distribution calculation unit, 350 Hydrogen amount calculation unit, 360 Open potential calculation unit, 370 memory Amount calculation unit, 371 usage condition setting unit, 372 minute memory amount calculation unit, 373 integration unit, 380 potential calculation unit.

Claims (7)

An alkaline secondary battery containing nickel hydroxide as a positive electrode active material,
A control device for controlling charging / discharging of the alkaline secondary battery using the positive electrode potential and the negative electrode potential of the alkaline secondary battery is provided.
The control device executes the potential calculation process every calculation cycle,
The potential calculation process
Using a battery model for estimating the internal behavior of the alkaline secondary battery, which includes either the voltage between the terminals of the alkaline secondary battery or the input / output current of the alkaline secondary battery as an input , each is used. The hydrogen concentration is calculated from the positive electrode open potential and the negative electrode open potential of the alkaline secondary battery calculated in the previous calculation cycle, and the hydrogen concentration inside the positive electrode active material, and the hydrogen concentration calculated in the previous calculation cycle. The initial potential of the positive electrode open potential is calculated from
From the hydrogen concentration, to calculate the amount of memory which is the potential change amounts due to the memory effect from the prior Symbol Initial potential,
A battery system including a process of calculating the positive electrode open potential using the initial potential and the amount of memory , and calculating the positive electrode potential based on the calculated positive electrode open potential. The positive electrode active material is assumed to be spherical in the battery model, and is virtually divided into a plurality of regions in the radial direction.
The control device is
From the distribution of hydrogen concentration in the plurality of regions, the distribution of the local hydrogen amount, which is the local hydrogen concentration in each of the plurality of regions, is calculated.
The initial potential was calculated from the amount of surface hydrogen, which is the amount of local hydrogen in the region including the surface of the positive electrode active material.
The battery system according to claim 1, wherein the memory amount is calculated from an average hydrogen amount which is an average amount of the local hydrogen amounts in the plurality of regions. The relationship between the minute memory amount, which is the amount of potential change of the positive electrode open potential due to the memory effect in a predetermined time, and the hydrogen consumption amount, which is the average hydrogen amount when the alkaline secondary battery is used, is described above. Further equipped with a storage device for storing data specified for each of a plurality of ranges of the average hydrogen amount,
The control device sequentially calculates the minute memory amount for each of the plurality of ranges from the amount of hydrogen used by referring to the data, and integrates the minute memory amount for each of the plurality of ranges. The battery system according to claim 2, wherein the amount of memory is calculated. The control device is
In the range in which the average amount of hydrogen is larger than the amount of hydrogen used in the plurality of ranges, the amount of minute memory is integrated in the direction in which the positive electrode open potential decreases, and when the amount of hydrogen used increases, after the increase. In the range where the average amount of hydrogen is smaller than the amount of hydrogen used, the minute memory amount accumulated in the decreasing direction is set to 0.
In the range in which the average amount of hydrogen is smaller than the amount of hydrogen used in the plurality of ranges, the amount of minute memory is integrated in the direction in which the positive electrode open potential increases, and when the amount of hydrogen used decreases, after the decrease. The battery system according to claim 3, wherein the minute memory amount integrated in the increasing direction is set to 0 in a range in which the average hydrogen amount is larger than the hydrogen amount used. The control device is
When at least one of the first condition that the positive electrode potential is higher than the predetermined upper limit positive electrode potential and the second condition that the negative electrode potential is lower than the predetermined lower limit negative electrode potential is satisfied. , The upper limit of the charging power of the alkaline secondary battery is set smaller than that in the case where neither the first and the second conditions are satisfied.
When at least one of the third condition that the negative electrode potential is higher than the predetermined upper limit negative electrode potential and the fourth condition that the positive electrode potential is lower than the predetermined lower limit positive electrode potential is satisfied. The battery system according to claim 1, wherein the upper limit value of the discharge power of the alkaline secondary battery is set smaller than that in the case where none of the third and fourth conditions are satisfied. The alkaline secondary battery is a nickel-metal hydride battery containing a hydrogen storage alloy as a negative electrode active material.
The control device is
The input / output current is calculated based on the exchange current density of the negative electrode active material.
Based on the input / output current, the positive electrode reaction current density corresponding to the hydrogen production rate per unit volume of the positive electrode active material and the negative electrode reaction current density corresponding to the hydrogen production rate per unit volume of the negative electrode active material are determined. Calculate and
It is configured to calculate the hydrogen concentration inside the positive electrode active material and the hydrogen concentration inside the negative electrode active material based on the positive electrode reaction current density and the negative electrode reaction current density.
The control device calculates an index value related to the amount of cracks generated in the negative electrode active material from the current input / output to the nickel-metal hydride battery and the temperature of the nickel-metal hydride battery, and uses the index value to perform the exchange. The battery system according to claim 1, wherein the current density is calculated. The negative electrode active material of the alkaline secondary battery is assumed to be spherical in the battery model, and is virtually divided into a plurality of regions in the radial direction.
The control device is
The negative electrode open potential was calculated from the hydrogen concentration in the region including the surface of the negative electrode active material calculated using the battery model.
The battery system according to claim 1, wherein the full charge capacity of the alkaline secondary battery is calculated from the positive electrode open potential and the negative electrode open potential.

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