Patent Description:
<CIT> is known as an energy storage system for starting the engine of a vehicle. The energy storage system of this kind employs, in place of a lead-acid battery, a secondary battery such as a lithium ion battery, which can be reduced in size or weight as compared to the lead-acid battery.

A lithium ion battery including an energy storage device whose positive electrode is made of lithium iron phosphate and whose negative electrode is made of graphite resembles a lead-acid battery in operational voltage range, and is more compatible with a lead-acid battery than a secondary battery made of other materials. However, the correlation between a state of charge (SOC) and an open circuit voltage (OCV) of an energy storage device whose positive electrode is made of lithium iron phosphate and whose negative electrode is made of graphite has a small-variation region where variations in OCV is small over a wide range of about from <NUM> to <NUM> [%] of the SOC. This makes it difficult to estimate, based on the OCV, any abnormal state of the energy storage device such as deterioration or abnormality of the energy storage device. It is particularly difficult to detect a minute internal short-circuit (soft short-circuit) in the small-variation region. <CIT>relates to a state estimation device which is configured to estimate a full-charge capacity of a secondary battery. A residual capacity Cp is calculated based on a measured open voltage at a point P included in a constant region F1 and the C-V correlation characteristic. Based on the determined residual capacitance Cp and an accumulated charge discharge amount X, a full charge capacity of the energy storage device is estimated and compared to a full charge condition. <CIT> discloses a degradation determination device with a measuring unit for measuring an open-circuit voltage characteristic that indicates an open-circuit voltage variation with respect to a lithium ion secondary battery capacity variation, and a determining unit that determines a degradation state due to wear and precipitation of lithium using parameter for identifying the open-circuit voltage characteristic that substantially coincides with the measured open-circuit voltage characteristic. <CIT> relates to a secondary battery system, which can accurately detect a state of a secondary battery system (such as a secondary battery state and a secondary battery system failure). The secondary battery system includes dV/dQ calculation means, which calculates a dV/dQ value as a ratio of a change amount dV of a battery voltage V of a secondary battery against a change amount dQ of an accumulation amount Q when the accumulation amount Q of the secondary battery is changed. The secondary battery system detects the state of the secondary battery system by using the dV/dQ value.

The present specification will disclose a technique for estimating whether or not an energy storage device is in an abnormal state.

Firstly, a description will be given of the overview of a state estimation apparatus disclosed in the present embodiment.

A state estimation apparatus according to an aspect of the present invention is configured to estimate a state of an assembled battery including a plurality of energy storage devices. The energy storage devices each have a small variation region where an open circuit voltage (OCV) variation amount relative to a residual capacity is smaller, and a variation region where the OCV variation amount relative to the residual capacity is greater than that in the small-variation region. The state of the assembled battery is estimated based on a varying position of the variation region relative to an actual capacity of the plurality of energy storage devices.

The technique disclosed in the present specification can estimate any deterioration or abnormality in the energy storage devices and assembled battery, based on the varying position of the variation region. When the position of the variation region in any of the energy storage devices largely varies, such as (<NUM>) when the ordinal levels of the variation region of the energy storage devices change places, or (<NUM>) when the position of the variation region in the energy storage devices deviates from the allowable range, the state estimation apparatus can estimate that deterioration or abnormality in the energy storage devices and assembled battery has occurred.

An unused energy storage device whose positive electrode is made of an iron-based material and whose negative electrode is made of a graphite-based material is generally known that, in the SOC-OCV correlation, the range where the SOC is about from <NUM> to <NUM> [%] is a small-variation region where variations in OCV is flat (smaller), and the range where the SOC is equal to or smaller than <NUM> [%] or equal to or greater than <NUM> [%] is a variation region where variations in OCV is greater than that in the small-variation region.

As a result of study on deterioration of energy storage devices, the present inventors have learned that, with an energy storage device whose positive electrode is made of an iron-based material and whose negative electrode is made of a graphite-based material, when the energy storage device deteriorates, in the relationship between the deterioration of the energy storage device and the SOC-OCV correlation, the small-variation region where the SOC is from <NUM> [%] to <NUM> [%] shortens.

The present inventors have focused on the fact that, in accordance with the shortening of the small-variation region associated with the deterioration of the energy storage device, the position of the variation region in the energy storage device varies.

The "SOC" refers to the state of charge of an energy storage device <NUM> where the SOC of <NUM> [%] indicates the full-charge state, and to a percentage of the residual capacity of the energy storage device at each time point relative to the capacity of the energy storage device in the full-charge state (a battery capacity). The present inventors have arrived at the idea of estimating the state of the assembled battery based on the varying position of the variation region using the correlation between the residual capacity and the OCV by comparing the varying position of the variation region of the energy storage devices in the correlation between the residual capacity and the OCV.

With such a configuration, in the case where the position of the variation region of any of the energy storage devices largely changes, such as when the ordinal levels of the variation region of the energy storage devices change places, or the position of the variation region of any of the energy storage devices deviates from the allowable range, it can be estimated that any deterioration or abnormality is occurring with the energy storage device, and consequently with the assembled battery. It is also possible to estimate an occurrence of a minute internal short-circuit in the small-variation region.

The energy storage devices each have an intermediate region being the variation region between the small-variation regions being two in number, and the state estimation apparatus estimates the state of the assembled battery based on a varying position of the intermediate region relative to the actual capacity of the plurality of energy storage devices.

The present inventors have found that, in the range of about from <NUM> to <NUM> [%] of the residual capacity, while little variations associated with deterioration of the energy storage device is shown in the small-variation region at a position where the residual capacity is smaller than the intermediate region (the variation region) with a slight potential difference between two small-variation regions (around the point where the residual capacity is about <NUM> [%]), the small-variation region at a position where the residual capacity is greater shortens in accordance with the deterioration of the energy storage device. Further, the present inventors have focused on the fact that the energy storage device of this kind is used in the range where the residual capacity is about from <NUM> to <NUM> [%] in order to secure the performance of the high input performance and the high output performance.

The present inventors have found that, by estimating the state of the energy storage devices or the assembled battery based on the varying position of the intermediate region, estimation can be performed more frequently than the case where the estimation is performed with the other
variation regions (the variation regions at a position where the residual capacity is smaller, or with the variation region where the residual capacity is greater).

That is, by more frequently estimating the state of the energy storage devices or the assembled battery based on the varying position of the intermediate region, the estimation precision improves as compared to, for example, the case where the estimation is performed with the variation region at a position where the residual capacity is smaller, or with the variation region where the residual capacity is greater.

The state estimation apparatus may estimate the state of the assembled battery based on a comparison as to the varying position of the intermediate region in each of the energy storage devices.

With such a configuration, by conducting a relative comparison as to the intermediate region of each of the energy storage devices, for example, in relation to the ordinal levels of the varying position of the intermediate region of the energy storage devices changing places, it can be estimated that any deterioration or abnormality is occurring with the energy storage devices, and consequently with the assembled battery without any complicated process or the like.

The state estimation apparatus may estimate the state of the assembled battery by calculating a variation amount of the actual capacity in each of the energy storage devices based on a first position being a position of the intermediate region of the plurality of energy storage devices at an unused time point or before last use and a second position being a position of the intermediate region of the plurality of energy storage devices after use.

With such a configuration, the state of the energy storage devices, such as deterioration or abnormality of the energy storage devices, can be estimated from the variation amount of the actual capacity of the energy storage devices based on the first position of the energy storage devices at an unused time point or before last use and the second position after use.

The state estimation apparatus may estimate an occurrence of abnormality with the assembled battery, when the variation amount of the actual capacity in each of the energy storage devices becomes outside an allowable range within a predetermined time.

With such a configuration, also in the case where abnormality occurs with every energy storage device within a predetermined time such as within a month, abnormality of the energy storage devices can be estimated.

The technique disclosed in the present specification is applicable to a state estimation method and a state estimation program for estimating the state of an assembled battery.

With reference to <FIG>, a description will be given of embodiments disclosed in the present specification.

As shown in <FIG>, the present embodiment is an energy storage apparatus <NUM> installed in an engine room <NUM> of a vehicle <NUM>. In the engine room <NUM>, the energy storage apparatus <NUM> is connected to a vehicle load <NUM> such as a starting motor for starting the engine or an electronic component, and a vehicle power generator <NUM> such as an alternator.

As shown in <FIG>, the energy storage apparatus <NUM> includes a battery case <NUM> having a block shape. As shown in <FIG>, the battery case <NUM> houses an assembled battery <NUM> made up of a plurality of (four in the present embodiment) energy storage devices <NUM> connected in series, a control board <NUM>, and the like.

In the following description, the top-bottom direction shown in <FIG> and <FIG> indicates the top-bottom direction of the battery case <NUM> when the battery case <NUM> is horizontally placed on the installation surface with no inclination. The front-rear direction shown in <FIG> and <FIG> indicates the direction along the short-side portion (the depth direction) of the battery case <NUM>, in which the front left side in the drawings indicates the front side of the battery case <NUM>. The right-left direction shown in <FIG> and <FIG> indicates the direction along the long-side portion of the battery case <NUM>, in which the front right side in the drawings indicates the right side of the battery case <NUM>.

The battery case <NUM> is made of synthetic resin. As shown in <FIG>, the battery case <NUM> includes a case body <NUM> having a box-shape and opening upward, a positioning member <NUM> positioning a plurality of energy storage devices <NUM>, a middle lid <NUM> mounted on an upper part of the case body <NUM>, and a top lid <NUM> mounted on an upper part of the middle lid <NUM>.

As shown in <FIG>, in the case body <NUM>, a plurality of cell chambers 13A respectively housing the plurality of energy storage devices <NUM> are juxtaposed to each other in the right-left direction.

The energy storage devices <NUM> each may be, for example, a lithium ion battery using a negative active material of a graphite-based material such as graphite, easily graphitizable carbon, less graphitizable carbon, or the like, and a positive active material of iron phosphate such as lithium iron phosphate. Such an energy storage device <NUM> shows, for example, correlation between an open circuit voltage (OCV) and a state of charge (SOC) shown in <FIG> (hereinafter, referred to as a "SOC-OCV correlation"). As shown in <FIG> and <FIG>, with the SOC-OCV correlation, the state of charge of the energy storage device <NUM> can be divided into the following five regions.

In regions II and IV of the five regions, the variations in OCV of an energy storage device <NUM> have a slope of less than a predetermined value relative to the SOC. That is, the variations in OCV are extremely small relative to the variations in SOC (hereinafter, these regions are referred to as "the small-variation regions" II, IV). Specifically, a small-variation region is, for example, a region where the variations in OCV are from <NUM> to less than <NUM> [mV] relative to a variation of <NUM> [%] in SOC.

On the other hand, in the remaining three regions I, III, V (the regions other than the small-variation regions II, IV), the variations in OCV of the energy storage device <NUM> have a positive slope of at least a predetermined value relative to the SOC. That is, as compared to the small-variation regions, variations in OCV relative to the SOC are relatively great (hereinafter, these regions are referred to as "the variation regions" I, III, V). Specifically, in the variation regions, for example, variations in OCV is from <NUM> to <NUM> [mV] or greater relative to a variation of <NUM> [%] in SOC. The variation region III in which the SOC is around <NUM> [%] corresponds to the intermediate region between the two small-variation regions II and IV.

As shown in <FIG>, a plurality of bus bars <NUM> are disposed on the upper surface of the positioning member <NUM>. By the positioning member <NUM> being disposed at the upper part of the plurality of energy storage devices <NUM> disposed in the case body <NUM>, the plurality of energy storage devices <NUM> are positioned. The plurality of energy storage devices <NUM> are connected in series by the plurality of bus bars <NUM>, to structure the assembled battery <NUM>.

The middle lid <NUM> is substantially quadrangular as seen in a plan view. As shown in <FIG> and <FIG>, at the opposite ends in the right-left direction of the middle lid <NUM>, a pair of external terminal portions <NUM> to which not-shown battery terminals of the vehicle <NUM> are connected is provided as being embedded in the middle lid <NUM>. The pair of external terminal portions <NUM> is made of, for example, metal such as lead alloy. Of the pair of external terminal portions <NUM>, one is a positive electrode terminal portion 12P and the other one is a negative electrode terminal portion 12N.

As shown in <FIG>, the middle lid <NUM> houses the control board <NUM>. By the middle lid <NUM> being mounted on the case body <NUM>, the assembled battery <NUM> and the control board <NUM> are connected to each other.

A description will be given of the electric configuration of the energy storage apparatus <NUM>.

As shown in <FIG>, the energy storage apparatus <NUM> includes the assembled battery <NUM>, a battery management unit (hereinafter referred to as the "BMU", an example of "state estimation apparatus") <NUM>, a current detecting resistor <NUM>, a current breaking apparatus <NUM>, a temperature sensor <NUM>, and discharge circuits <NUM>.

The assembled battery <NUM>, the current detecting resistor <NUM>, and the current breaking apparatus <NUM> are connected in series via an energizing line L. The positive electrode of the assembled battery <NUM> is connected to the positive electrode terminal portion 12P via the current breaking apparatus <NUM>, and the negative electrode is connected to the negative electrode terminal portion 12N via the current detecting resistor <NUM>.

The current detecting resistor <NUM> is a resistor that detects current of the assembled battery <NUM>. By the voltage across the opposite ends of the current detecting resistor <NUM> being read by the BMU <NUM>, the current of the assembled battery <NUM> is detected.

The current breaking apparatus <NUM> is, for example, a semiconductor switch such as an FET or a relay. In response to an instruction (a control signal) from the BMU <NUM>, the current breaking apparatus <NUM> breaks the current between the assembled battery <NUM> and the positive electrode terminal portion 12P.

The temperature sensor <NUM> is of the contact type or the contactless type, and measures the temperature of the assembled battery <NUM>.

As shown in <FIG>, the discharge circuits <NUM> are respectively provided at the energy storage devices <NUM> in parallel connection to the energy storage devices <NUM>. The discharge circuits <NUM> are each a circuit in which a not-shown discharge resistor and a not-shown discharge switch are connected in series. In response to an instruction from the BMU <NUM>, the discharge circuits <NUM> close their respective discharge switches, thereby individually discharging the energy storage devices <NUM>.

The BMU <NUM> includes a voltage detecting circuit <NUM>, a CPU <NUM> being the central processing unit, a memory <NUM>, and a timer <NUM>, which are mounted on the control board <NUM>. Further, the BMU <NUM> is supplied with power from the assembled battery <NUM> by being connected to the energizing line L.

The voltage detecting circuit <NUM> is connected to the opposite ends of the energy storage devices <NUM> via voltage detecting lines L2. In response to an instruction from the CPU <NUM>, the voltage detecting circuit <NUM> detects the cell voltage of each energy storage device <NUM> and the battery voltage of the assembled battery <NUM> (the total voltage of the plurality of energy storage devices <NUM>).

The memory <NUM> is, for example, a nonvolatile memory such as a flash memory or an EEPROM. The memory <NUM> stores various programs such as a program for managing the energy storage devices <NUM> or the assembled battery <NUM>, a state estimation program for estimating deterioration or any abnormal state of the energy storage devices <NUM> and the assembled battery <NUM>, and data required in executing the programs (the actual capacity of the energy storage devices <NUM>, the allowable deterioration value, and the like).

The actual capacity of each energy storage device <NUM> is explained as follows. For example, each manufactured energy storage device <NUM> is subjected to constant current constant voltage charge to attain the full-charge state (e.g., <NUM> [V], <NUM> [A] or lower). Subsequently, the energy storage device <NUM> is discharged to reach the end-of-discharge voltage (e.g., <NUM> [V] (1C)). The current amount discharged from the full-charge state to the end-of-discharge voltage by the rated current is the actual capacity (the capacity that can be extracted from the fully charged energy storage device <NUM>).

The timer <NUM> measures time. For example, the timer <NUM> measures the time of the voltage detecting circuit <NUM> measuring the voltage of the energy storage devices <NUM> and the time difference between voltage measurements, and outputs them to the CPU <NUM>.

The CPU <NUM> is the central processing unit, and monitors the current, voltage, and the like of the energy storage devices <NUM> based on the output of the current detecting resistor <NUM>, the voltage detecting circuit <NUM>, and the like. Upon detecting any abnormality, the CPU <NUM> activates the current breaking apparatus <NUM>, thereby preventing the assembled battery <NUM> from malfunctioning.

The assembled battery <NUM> is installed having the plurality of energy storage devices <NUM> connected in series and arranged in close proximity to each other in the case body <NUM>. Accordingly, when the energy storage apparatus <NUM> is used, the energy storage devices <NUM> disposed centrally attain higher temperatures than the energy storage devices <NUM> disposed on the outer side. Then, when the energy storage apparatus <NUM> is used for a predetermined period, deterioration of the energy storage devices <NUM> disposed centrally further deteriorates in addition to normal deterioration, and the actual capacity thereof reduces.

Though the energy storage devices <NUM> of the assembled battery <NUM> are manufactured through the identical process, they vary from each other in actual capacity. Specifically, in the case where the actual capacity of four energy storage devices <NUM> being unused since manufacture is measured by the above-described method, the energy storage devices <NUM> vary from each other in actual capacity, for example as follows: the first energy storage device showing <NUM> [Ah], the second energy storage device showing <NUM> [Ah], the third energy storage device showing <NUM> [Ah], and the fourth energy storage device showing <NUM> [Ah].

Further, the present inventors have learned that, with the energy storage device <NUM> whose positive electrode is made of an iron-based material and whose negative electrode is made of a graphite material, there exists the characteristic, in the relationship between the deterioration of the energy storage device <NUM> and the SOC-OCV correlation, that the small-variation region IV (the small-variation region where the SOC is in the range of from <NUM> [%] to <NUM> [%]) shortens when the energy storage device <NUM> has deteriorated.

The present inventors have focused on the fact that, when the position of the full-charge state is fixed in the SOC-OCV correlation of the energy storage device <NUM>, the position of the variation region III varies in accordance with the shortening of the small-variation region IV. The present inventors have found that an occurrence of any deterioration or abnormality of the energy storage devices <NUM> and consequently of the assembled battery <NUM> can be estimated by conducting a state estimation process based on the varying position of the variation region III at periodical or arbitrary timing at a predetermined time interval (e.g., one month).

A description will be given of the relationship between the deterioration of the energy storage device <NUM> and the SOC-OCV correlation. Subsequently, with reference to <FIG>, a description will be given of the state estimation process.

The "SOC" refers to the state of charge of the energy storage device <NUM>. The SOC attains <NUM> [%] in the full-charge state and attains <NUM>% when the end-of-discharge voltage is reached.

In relation to the deterioration of the energy storage device <NUM>, when the unused energy storage device <NUM> and the deteriorated energy storage device <NUM> are compared against each other based on the SOC-OCV correlation in which the X-axis indicates a SOC [%], SOC <NUM> [%] and SOC <NUM> [%] become the same in position in the SOC-OCV correlation.

That is, the proportion of the variations in OCV extends longer in the X-axis direction (the direction in which the SOC varies) in the SOC-OCV correlation of the deteriorated energy storage device <NUM> than the SOC-OCV correlation of the unused energy storage device <NUM>. In view of the foregoing, in order to clarify the relationship between the residual capacity and the OCV of the energy storage device, the graphs of <FIG> show the correlation between the residual capacity and the OCV (hereinafter referred to as the "residual capacity-OCV correlation") in which the X-axis indicates a residual capacity [Ah] of the energy storage devices <NUM> and the Y-axis indicates an OCV [V]. In the graphs of <FIG>, an unused energy storage device α is represented by the solid line, and the deteriorated energy storage device β is represented by the dashed-dotted line, both of which of the energy storage devices <NUM> being aligned to each other at the position of the full-charge state.

In the graph of <FIG>, comparing the unused energy storage device α and the deteriorated energy storage device β against each other, the variation region I and the small-variation region II in which the residual capacity is smaller than that in the variation region III show little variations in capacity in accordance with deterioration of the energy storage device <NUM>.

However, the small-variation region IV of the deteriorated energy storage device β is shortened as compared to the small-variation region IV of the unused energy storage device α, from which a reduction in actual capacity of the energy storage device <NUM> can be seen.

That is, aligning the unused energy storage device <NUM> and the deteriorated energy storage device <NUM> at the position of the full-charge state, as shown in <FIG>, it can be seen that the position of the variation region III shifts toward the higher residual capacity when the energy storage device <NUM> has deteriorated.

In the state estimation process, a CPU <NUM> calculates the deterioration amount of the energy storage devices <NUM> based on the capacity difference between the actual capacity of the energy storage devices <NUM> at an unused time point or before last use and the actual capacity of the used energy storage devices <NUM>, and estimates whether or not any deterioration or abnormality is occurring with the assembled battery <NUM>.

As shown in <FIG>, the CPU <NUM> determines whether or not the energy storage devices <NUM> are unused (S11). When the energy storage devices <NUM> are unused since manufacture (S11: YES), the CPU <NUM> measures the actual capacity of the energy storage devices <NUM> at an unused time point and the residual capacity-OCV correlation at this time point (S13), and calculates the capacity difference (the capacity variations) between the reference device which is the energy storage device <NUM> whose actual capacity is the smallest and each of the other energy storage devices <NUM> as the capacity difference at the first position (see <FIG>).

Then, the CPU <NUM> stores, in the memory <NUM> of the BMU <NUM>, the relationship between the variation region III in the residual capacity-OCV correlation of the energy storage devices <NUM> and the capacity difference between the reference device and each of the other energy storage devices <NUM> corresponding to the variation region III (S14).

Specifically, it is assumed that the actual capacity of the four energy storage devices <NUM> unused since manufacture is measured as follows, for example: <NUM> [Ah] for the first energy storage device A; <NUM> [Ah] for the second energy storage device B; <NUM> [Ah] for the third energy storage device C; and <NUM> [Ah] for the fourth energy storage device D. In this case, the CPU <NUM> calculates the actual capacity of the energy storage devices <NUM> and, as shown in <FIG>, the capacity difference between the third energy storage device (<NUM> [Ah]) being the reference device and each of the other energy storage devices <NUM> (<NUM> [Ah] being a capacity difference ΔCn1 for the first energy storage device, <NUM> [Ah] being a capacity difference ΔCn2 for the second energy storage device, <NUM> [Ah] being a capacity difference ΔCn4 for the fourth energy storage device), and stores the result in the memory <NUM> of the BMU <NUM>.

The CPU <NUM> stores, in the memory <NUM> of the BMU <NUM>, the correspondence between the residual capacity-OCV correlation acquired from the energy storage devices <NUM> shown in <FIG> and <FIG> and the capacity difference between the reference device and each of the other energy storage devices <NUM> (the capacity difference ΔCn1 between the third energy storage device (<NUM>[Ah]) being the reference device and the first energy storage device, the capacity difference ΔCn2 between the third energy storage device and the second energy storage device, and the capacity difference ΔCn4 between the third energy storage device and the fourth energy storage device).

On the other hand, when the energy storage devices <NUM> are not unused since manufacture (S11: NO), the CPU <NUM> employs the capacity difference at a second position, which will be described later, calculated in the previous state estimation process as the capacity difference of the first position, and executes S15 which will be described later (S12).

Next, the CPU <NUM> charges the energy storage devices <NUM> while adjusting the charging with the discharge circuits <NUM> so as to reduce the difference in charge amount among the energy storage devices <NUM>, until the SOC of every energy storage device <NUM> attains <NUM> [%] (the full-charge state) (S15). When the energy storage devices <NUM> are unused since manufacture, when the assembly of the energy storage apparatus <NUM> is completed, the CPU <NUM> charges the energy storage devices <NUM> while adjusting the charging with the discharge circuits <NUM> until the SOC of every energy storage device <NUM> attains <NUM> [%] (the full-charge state).

Then, the CPU <NUM> discharges the energy storage devices <NUM> by, for example, self discharge or discharge to the vehicle load <NUM> after installed in the vehicle. The CPU <NUM> measures, with the timer <NUM>, the time taken for the OCV of the reference device (the third energy storage device) to reach the variation region III in the residual capacity-OCV correlation, and stores the measured time in the memory <NUM> as the reference time (S16).

The self discharge or the discharge to the vehicle load <NUM> after installed in the vehicle is realized by dark current with a small current value and substantially no variations in OCV. For example, the discharge current is <NUM> [A] or smaller.

The CPU <NUM> measures, with the timer <NUM>, the reaching time taken for every other energy storage device <NUM> to reach the variation region III (S17). The CPU <NUM> calculates, based on the relationship between the residual capacity-OCV correlation of the energy storage devices <NUM> stored in the memory <NUM> and the capacity difference between the reference device and each of the other energy storage devices <NUM> corresponding thereto and using the time difference between the reference time and the reaching time of each of the other energy storage devices <NUM>, the capacity difference between the reference device (the third energy storage device) and each of the other energy storage devices <NUM> as the capacity difference at the second position (see <FIG>) (S18).

The capacity difference between the reference device and each of the other energy storage devices <NUM> at the second position can be calculated from, for example, the reaching time taken for the energy storage devices <NUM> to reach the variation region III in the residual capacity-OCV correlation and the discharge current value at this time.

Next, the CPU <NUM> calculates, as the deterioration amount of each of the energy storage devices <NUM>, the difference between each capacity difference at the first position stored in S12 and each capacity difference at the second position corresponding thereto calculated in S14 (S19). The CPU <NUM> estimates whether or not the deterioration amount of the energy storage devices <NUM> is smaller than an allowable deterioration value (S20). When the deterioration amount of the energy storage devices <NUM> is equal to or smaller than the allowable deterioration value (S20: YES), the CPU <NUM> estimates that the deterioration degree of the assembled battery <NUM> (the energy storage devices <NUM>) is small and the assembled battery <NUM> is not in the abnormal state, and determines that the assembled battery <NUM> is continuously usable (S21).

On the other hand, when the deterioration difference is greater than the allowable deterioration value (S20: NO), the CPU <NUM> estimates that the deterioration degree of the assembled battery <NUM> (the energy storage devices <NUM>) is great and the assembled battery <NUM> is in the abnormal state, and determines that the assembled battery <NUM> is unusable (S22).

Specifically, the graphs of <FIG> and <FIG> show the residual capacity-OCV correlation in an unused energy storage device <NUM> and used energy storage devices <NUM>. The curve of a dashed-two dotted line Z represents an unused energy storage device <NUM>, and the remaining curves represent used energy storage devices <NUM>. The variation region III in which the residual capacity is around <NUM> [Ah] corresponds to the first position, and the variation region III in which the residual capacity is around from <NUM> to <NUM> [Ah] corresponds to the second position.

For example, in the case where the capacity difference ΔCu4 between the reference device (the third energy storage device C) and the fourth energy storage device D both after use (at the second position) shown in <FIG> is <NUM> [Ah], and the capacity difference ΔCn4 between the reference device and the fourth energy storage device D both being unused since manufacture (at the first position) shown in <FIG> is <NUM> [Ah] - <NUM> [Ah] = <NUM> [Ah], the deterioration amount of the fourth energy storage device is calculated as follows: <NUM> [Ah] - <NUM> [Ah] = <NUM> [Ah]. For example, when the allowable deterioration value is <NUM> [Ah], since the deterioration degree of the fourth energy storage device D is smaller than the allowable deterioration value and falls within the allowable range, the CPU <NUM> estimates that the assembled battery <NUM> is not in the abnormal state, and determines that the assembled battery <NUM> is continuously usable.

On the other hand, when the capacity difference ΔCu2 between the reference device (the third energy storage device C) and the second energy storage device B both after use (at the second position) shown in <FIG> is <NUM> [Ah], and the capacity difference ΔCn2 between the reference device and the second energy storage device B both being unused since manufacture (at the first position) shown in <FIG> is <NUM> [Ah] - <NUM> [Ah] = <NUM> [Ah], the deterioration amount of the second energy storage device B is calculated as follows: <NUM> [Ah] - <NUM> [Ah] = <NUM> [Ah]. Accordingly, when the allowable deterioration value is <NUM> [Ah], since the deterioration amount exceeds the allowable deterioration value, the CPU <NUM> estimates that the deterioration degree of the second energy storage device B is great and the assembled battery <NUM> is in the abnormal state.

In the above-described case, the CPU <NUM> determines that the assembled battery <NUM> is unusable based on that the second energy storage device B is estimated to be in the abnormal state while no abnormality is estimated with the third energy storage device C and the fourth energy storage device D.

For example, when the deterioration amount between the reference device (the third energy storage device C) and the second energy storage device B is <NUM> [Ah] and the deterioration amount between the third energy storage device C and the fourth energy storage device D is also <NUM> [Ah], the deterioration difference exceeds the allowable deterioration value (<NUM> [Ah]) as to both the second energy storage device B and the fourth energy storage device D.

In this case, the CPU <NUM> estimates that the deterioration degree of the third energy storage device C is great and the third energy storage device C is in the abnormal state, and determines that the assembled battery <NUM> is unusable.

That is, in the state estimation process, whether or not any abnormality due to deterioration or the like is occurring with the assembled battery <NUM> (the energy storage devices <NUM>). When it is estimated that some abnormality is occurring with the assembled battery <NUM> (the energy storage devices <NUM>) as a result of the state estimation process, for example, an alert may be displayed on the display unit <NUM> (see <FIG>) provided in the cabin of the vehicle <NUM> indicating that the energy storage apparatus <NUM> is unusable, alerting the user thereto.

As described above, the present inventors have focused on the fact that, in the relationship of residual capacity-OCV correlation (the SOC-OCV correlation), when the variation curves of the energy storage devices <NUM> are aligned at the position of the full-charge state as shown in <FIG> and <FIG>, deterioration of the energy storage devices <NUM> shortens the small-variation region IV, and shifts the varying position of the variation region III. The present inventors have found that the deterioration degree of the assembled battery <NUM> (the energy storage devices <NUM>) can be estimated based on the varying position (the change in the position of the variation region III from the first position to the second position).

That is, in the state estimation process according to the present embodiment, the capacity difference between the energy storage devices of the assembled battery <NUM> (the energy storage devices <NUM>) at an unused time point or before last use (the first position), and the capacity difference between the energy storage devices of the assembled battery <NUM> (the energy storage devices <NUM>) after use (at the second position) are calculated. Next, by calculating the deterioration amount of the energy storage devices <NUM> from the capacity differences (the varying position in the residual capacity-OCV correlation), the deterioration degree of the assembled battery <NUM> (the energy storage devices <NUM>) can be estimated.

From the deterioration degree, whether or not the assembled battery <NUM> (the energy storage devices <NUM>) is in the abnormal state can be estimated, and whether or not the assembled battery <NUM> (the energy storage devices <NUM>) is continuously usable can be determined.

As described above, though deterioration degree of the assembled battery <NUM> (the energy storage devices <NUM>) can be estimated by the state estimation process, when the frequency of performing the process is small, the precision of the determination as to the usability of the assembled battery <NUM> (the energy storage devices <NUM>) reduces.

However, according to the present embodiment, the high input performance and the high output performance, such as for cranking discharge required in starting the engine of the vehicle <NUM> or regenerative charge in decelerating the vehicle <NUM>, are required. The deterioration degree of the assembled battery <NUM> (the energy storage devices <NUM>) is estimated by performing the state estimation process based on the varying position of the variation region III where the residual capacity of the assembled battery <NUM> falls within a range of about from <NUM> to <NUM> [%].

The frequency of performing the state estimation process can be increased as compared to the case where the state estimation process is performed in the variation region I or the variation region V of the variation regions. That is, the present embodiment improves the estimation precision in estimating whether or not the assembled battery <NUM> (the energy storage devices <NUM>) is in the abnormal state.

According to the present embodiment, by calculating the deterioration degree and comparing the result against the allowable deterioration value, whether or not the assembled battery <NUM> (the energy storage devices <NUM>) is usable is estimated. Thus, as compared to the case where the deterioration amounts between the energy storage devices are relatively compared against each other, the estimation precision in estimating whether or not the assembled battery <NUM> (the energy storage devices <NUM>) is in the abnormal state further improves.

Next, with reference to <FIG> and <FIG>, a description will be given of a second embodiment.

The second embodiment is obtained by changing the process in S14 and the processes in S18 and the following steps in the state estimation process according to the first embodiment. Accordingly, the structure, operation, and effect identical to those of the first embodiment are not described for avoiding overlaps. Further, the structures identical to those of the first embodiment are denoted by identical reference characters.

As shown in <FIG>, in the state estimation process according to the second embodiment, after measuring the actual capacity of the energy storage devices <NUM> in S13, the CPU <NUM> determines the ordinal levels of the energy storage devices <NUM> at an unused time point or before last use as the ordinal levels at the first position based on the actual capacity of the energy storage devices <NUM>, and stores the ordinal levels in the memory <NUM> of the BMU <NUM> (S24).

After measuring the reaching time in S17, the CPU <NUM> determines the ordinal levels based on the actual capacity of the assembled battery <NUM> (the energy storage devices <NUM>) after use from the reference time and the reaching time measured in S16 and S17 as the ordinal levels at the second position (S28).

The CPU <NUM> determines whether or not the ordinal levels at the first position of the energy storage devices <NUM> stored in S24 and the ordinal levels at the second position of the energy storage devices <NUM> determined in S28 have changed (S29). When the ordinal levels have not been changed (S29: YES), the CPU <NUM> estimates that the assembled battery <NUM> is not in the abnormal state based on that there exist no significantly deteriorated energy storage devices <NUM> and the deterioration degree of the assembled battery <NUM> is small, and the CPU <NUM> determines that the assembled battery <NUM> is continuously usable (S30).

On the other hand, when the ordinal levels have changed (S29: NO), the CPU <NUM> estimates that the assembled battery <NUM> is in the abnormal state based on that there exist significantly deteriorated energy storage devices <NUM> and the deterioration degree of the assembled battery <NUM> is great, and the CPU <NUM> determines that the assembled battery <NUM> is unusable (S31).

Specifically, in the residual capacity-OCV correlation of the energy storage device <NUM>, as shown in <FIG>, when the ordinal levels of the reaching time for the energy storage devices <NUM> before use of the assembled battery to reach the variation region III are in order of the third energy storage device C, the first energy storage device A, the fourth energy storage device D, and the second energy storage device B, the ordinal levels in ascending order of the actual capacity of the energy storage devices <NUM> are determined as in order of the third energy storage device C, the first energy storage device A, the fourth energy storage device D, and the second energy storage device B.

As shown in <FIG>, when the ordinal levels of the reaching time for the deteriorated energy storage devices <NUM> due to use of the assembled battery <NUM> to reach the variation region III of are in order of the third energy storage device C, the first energy storage device A, the second energy storage device B, and the fourth energy storage device D, the ordinal levels in ascending order of the actual capacity of the energy storage devices <NUM> are determined as in order of the third energy storage device C, the first energy storage device A, the second energy storage device B, and the fourth energy storage device D.

Next, whether or not the ordinal levels have changed before and after use of the assembled battery <NUM> is determined.

The ordinal level of the second energy storage device B and that of the fourth energy storage device D are reversed before use (see <FIG>) and after use (see <FIG>). That is, the CPU <NUM> estimates that the deterioration degree of one of the energy storage devices <NUM>, i.e., the second energy storage device B or the fourth energy storage device D, is great and the assembled battery <NUM> is in the abnormal state, and the CPU <NUM> determines that the assembled battery <NUM> is unusable.

Without the necessity of performing complicated processes, such as calculating the capacity difference between the energy storage devices <NUM> and calculating the deterioration amount of the energy storage devices <NUM>, by comparing the ordinal levels of the energy storage devices <NUM> at an unused time point or before last use and the ordinal levels of the energy storage devices <NUM> after use against each other, whether or not the assembled battery <NUM> is in the abnormal state can be estimated. Thus, whether or not the assembled battery <NUM> (the energy storage devices <NUM>) is usable can be determined.

As has been described above, in the present embodiment, just the comparison between the ordinal levels of the energy storage devices <NUM> at an unused time point or before last use and the ordinal levels of the energy storage devices <NUM> after use is performed. The present disclosure is not limited thereto, and just when the ordinal levels have been changed, the capacity difference of the energy storage devices <NUM> may be calculated and the deterioration amount may be estimated. Alternatively, the deterioration amount may be estimated just for the energy storage devices <NUM> whose ordinal levels have been changed.

The technique disclosed in the present specification is not limited to the embodiments described above and the drawings referred to, and includes the following various modes, for example. In the above-described embodiments, a lithium ion battery using a positive active material of iron phosphate is employed as an exemplary electrochemical device. The present disclosure is not limited thereto.

Claim 1:
A state estimation apparatus (<NUM>) configured to estimate a state of an assembled battery (<NUM>) including a plurality of energy storage devices (<NUM>),
wherein the energy storage devices (<NUM>) each have a correlation between an open circuit voltage, OCV, and a residual capacity, SOC, each of the correlations having a first small-variation region (II) and a second small-variation region (IV), where an OCV variation amount relative to the SOC has a slope less than a predetermined value, and variation regions (I, III, V), where the OCV variation amount relative to the SOC has a slope of at least the predetermined value, including an intermediate region (III) being the variation region between the two small-variation regions (II, IV),
characterized in that
the state estimation apparatus (<NUM>) is configured to estimate an occurrence of an abnormal state of the assembled battery (<NUM>) based on a position of the intermediate region (III) in each of the correlations between the OCV and the SOC.