Patent Application
20150046109
The present invention relates to systems and methods for managing the maintenance of a battery system.
A lithium ion battery has a far higher energy density than a nickel hydrogen battery. The lithium ion battery also has the characteristic that its memory effect is small. Thus, lithium ion batteries are widely used in portable telephones, notebook computers and other portable devices, and in hybrid vehicles, electric vehicles, and other vehicles.
The lithium ion battery has the characteristics that as the battery is repeatedly charged and discharged, oxidization of electrolytic solution and destruction of a crystal structure occur on the positive electrode side, while precipitation of metallic lithium occurs on the negative electrode side. Because of such characteristics, repetition of charging and discharging decreases the lithium ion battery capacity. If the capacity continues to decrease, the lithium ion battery ceases to be capable of providing necessary electric power to a device as the destination for electric power supply. Accordingly, the lithium ion battery needs to be regularly replaced. Particularly, in a large-scale battery system including a number of lithium ion batteries and capable of providing large amounts of electric power, the efficiency of replacement of a number of lithium ion batteries as they degrade needs to be increased.
As an example of the literature describing the background art of the relevant technical field, Patent Literature 1 is cited. The Abstract portion of the literature reads that “Provided is a vehicular battery diagnosis system capable of presenting a control plan for improving the operating life of a battery mounted on a vehicle, and modifying control information regarding vehicle control.
As another example of the literature describing the background art of the relevant technical field, Patent Literature 2 is cited. The Abstract portion of the literature reads: “The remaining operating life of a battery mounted or to be mounted on an automobile that travels using power from an electric motor is diagnosed with increased adequacy”; and “Operating life information associating the use state of end-of-life batteries with their operating life results (such as the charge characteristics of the end-of-life batteries) is prepared in the form of a database. When the remaining operating life of a battery for diagnosis is diagnosed, an operating life charge voltage variation ΔVmcli is acquired from a region of the database corresponding to the use state of the battery for diagnosis (S140), a diagnosis charge voltage variation ΔVmccu at the time of charging the battery for diagnosis according to a charge sequence is acquired (S170, S180), and a remaining operating life distance Rd or a remaining operating life time Rt of the battery for diagnosis is computed from the relationship between the acquired diagnosis charge voltage variation ΔVmccu and the operating life charge voltage variation ΔVmcli (S190)”.
As another example of the literature describing the background art of the relevant technical field, Patent Literature 3 is cited. The Abstract portion of the literature reads: “When it is determined that the battery 12 has reached the end of its operating life, the use environment of the battery 12 (such as the type of equipped vehicle, area of use, purpose of use, or travel history) is stored in a hard disk drive 54 of the management server 50 as part of an operating life information database, in association with use state information (such as the charge and discharge characteristics of the battery 12, total travel distance Lsum, or total use time Tsum). In this way, the operating life information database can be made more adequate”.
Patent Literature 1: JP 2010-119223 A
Patent Literature 2: JP 2011-64571 A
Patent Literature 3: JP 2011-69693 A
Patent Literature 1 describes that the vehicle control plan for improving the operating life of the battery is presented based on battery diagnosis information (it is merely described that the battery charge state is calculated based on a current value or a voltage value for diagnosis), and that the vehicle control information is modified in accordance with a control plan selected by the user. Patent Literature 1, however, does not disclose a technology for designating the replacement timing for individual battery.
Patent Literatures 2 and 3 disclose the technology for accurately diagnosing the remaining operating life of a battery mounted or to be mounted on an automobile. However, the literatures do not disclose the technology for designating the replacement timing in accordance with degradation of the individual battery system.
The present invention provides a battery system maintenance management system that determines the replacement timing of an individual battery module.
In order to solve the problem, the present invention provides the following processes (function units):
(1) A degradation degree estimation unit (process) that estimates the degradation degree of each battery module of a battery system by collating capacity-voltage profile data of the battery module according to manufacturing state and degradation state, capacity-voltage profile data at the time of shipping of the battery module, and most recent capacity-voltage profile data of the battery module.
(2) A use pattern estimation unit (process) that estimates a future use pattern based on past charge/discharge results data of the battery module.
(3) A remaining operating life computation unit (process) that computes remaining operating life based on the degradation degree, the use pattern of the battery module, and characteristics degradation data.
(4) A replacement timing indication unit (process) that indicates the replacement timing of the individual battery module based on the remaining operating life computed for the battery module.
According to the present invention, the efficiency of battery system maintenance can be increased by determining the replacement timing of each battery module of a battery system. As a result, the operating ratio of the battery system as a whole can be increased.
Other problems, configurations, and effects will become apparent from the following description of embodiments.
In the following, modes of implementation of the present invention will be described with reference to the attached drawings.
The maintenance management system 100 includes a data input/output processing unit 110; a computation processing unit 120; and a database unit 130.
The computation processing unit 120 may include a computer, for example. In this case, the computation processing unit 120 includes a CPU; a RAM; a ROM; an internal storage device (such as a hard disk); and an input/output interface. A maintenance management function which will be described below is provided through a program read from the internal storage device or the like and executed. When the computation processing unit 120 is realized by a general-purpose computer, a function according to the executed program is provided. To the computation processing unit 120, a display or a printer may be connected.
As the maintenance management functions of the embodiment, the computation processing unit 120 includes a degradation degree estimation processing unit 121; a use pattern estimation processing unit 122; a remaining operating life computation processing unit 123; and a replacement timing indication processing unit 124. The processing units are realized through the execution of the computer program. The details of the process operation executed by each processing unit will be described later.
The database unit 130 includes an operational results database 131; a manufacturing inspection results database 132; a performance degradation database 133; an environment results database 134; and a check plan database 135.
According to the present embodiment, to the maintenance management system 100, a plurality of battery systems 200 are connected. The plurality of battery systems 200 may not be present at one location and may be distributed at a plurality of locations.
Each of the battery systems 200 is connected to the device 300, for example, as the object for the supply of electric power. The device 300 is not limited to a device that uses electricity and may include a device that can generate electricity. For example, the device 300 may include a wind power generation facility. In this case, the battery system 200 may be used as a device for accumulating the generated electricity and also as an auxiliary power supply for stabilizing the electricity output. The device 300 may also include a solar power generation facility. The device 300 may include an information system, such as a server or a data center. When the device 300 is a server, the battery system 200 may be an uninterruptible power supply device (UPS).
According to the present embodiment, the battery systems 200 are configured as assemblies of a plurality of lithium ion battery modules. The battery modules are not limited to lithium ion battery modules. In the case of the present embodiment, each battery module includes a plurality of lithium ion battery cells connected together. The battery module may include a single lithium ion battery cell.
In the positive electrode material manufacturing step, first, various raw materials for the positive electrode material are kneaded and blended to prepare a slurry material. The slurry material is then applied to metal foil processed into a film. Thereafter, the metal foil with the slurry coating is processed (such as compressed or cut), manufacturing a film of positive electrode material.
In the negative electrode material manufacturing step, the same procedure as for the positive electrode material manufacturing step is performed with the exception that the various materials used as raw material are different from those of the positive electrode material manufacturing step. First, the various materials as raw material for the negative electrode material are kneaded and blended to prepare a slurry material. The slurry material is then applied to a metal foil processed into a film. Thereafter, the metal foil with the slurry coating is processed (such as compressed or cut), manufacturing a film of negative electrode material.
Then, the battery cell assembly step is performed. First, a winding step is performed. In the winding step, necessary sizes of the positive electrode and negative electrode for the battery cell are cut from the films of positive electrode material and negative electrode material. A necessary size of a separator for the battery cell is also cut from a film of separator material used for separating the positive electrode material from the negative electrode material. Thereafter, the separator is sandwiched between the positive electrode and the negative electrode, and they are wound together in a superposed manner. Next, a weld/assembly step is performed. In the weld/assembly step, a group of pairs of the electrodes comprising the positive electrode, the negative electrode, and the separator wound together is assembled and welded. In the next fluid injection step, the group of welded electrode pairs is disposed in a battery can into which electrolytic solution is injected. The battery can is then completely sealed in a sealing step, producing a battery cell. Thereafter, a cell inspection step is performed. The cell inspection step includes a step of repeatedly charging and discharging the lithium ion battery cell produced in the previous step, and inspection of the battery cell performance and reliability (such as the capacity and voltage of the battery cell, the current and voltage during charging or discharging). The battery cell is thus completed and the battery cell assembly step ends.
Next, the battery module assembly step is performed. The battery module assembly step includes a module assembly step and a module inspection step. In the module assembly step, a plurality of battery cells are combined in series, forming a battery module. To the battery module, a battery control unit for charge/discharge control is connected, manufacturing the battery system 200. Then, the module inspection step is performed. In the module inspection step, the assembled battery module is inspected regarding performance and reliability. For example, battery module capacity and voltage, and charge or discharge current and voltage are inspected.
The battery control unit 203 implements creation and management of operational results information (operation history data) regarding charging and discharging, capacity, voltage and the like of the battery cells and the battery module. The battery control unit 203 includes a timer for measuring the time and date of charging and discharging of the battery module 201. The battery control unit 203 acquires operational results data of the battery module at the time of charging and discharging and at the time of stop state, and stores the data in the operational results database 131 of the database unit 130 of the battery system maintenance management system 100. A concrete configuration of the operational results data will be described later.
During charge inspection, changes in output voltage of the battery module are measured while the battery module is being charged with a predetermined current value. The charge inspection ends when the measured output voltage reaches a charge end voltage. The changes in the relationship between the voltage and capacity that has been measured from the start to end of charging provide charge characteristics data (charge profile data). It should be noted that the “capacity” is not measured data but is computed based on the product of the charging current value and the charge time. The capacity is denoted by the unit Ah. As illustrated in
During discharge inspection, changes in output voltage of the battery module are measured while the battery modules is being discharged at a predetermined current value. The discharge inspection ends when the measured output voltage reaches a discharge end voltage. The changes in the relationship between voltage and capacity that has been measured from the start to end of discharging provide discharge characteristics data (discharge profile data). In this case too, the “capacity” is not measured data but is computed based on the product of the discharge current value and the discharge time. The capacity is also denoted by the unit Ah. As illustrated in
The charge/discharge characteristics data of each battery module obtained as described above are stored in the manufacturing inspection results database 132 of the database unit 130 of the maintenance management system 100 before the battery systems 200 are shipped.
The data records of the operational results information may be created only at the timing of sensing of a battery module status change. Obviously, the time of detection of status change is recorded as the results acquisition date/time.
The initial value of the capacity (100, for example) of the operational results information is the capacity of the battery system 200 charged at the time of product shipping. When the battery system 200 has been discharged, the discharge capacity (=discharge current×elapsed time) is subtracted from the capacity of the previous data record to determine the capacity of the data record that is recorded this time. On the other hand, when the battery system 200 has been charged, the charge capacity (=charge current×elapsed time) is added to the capacity of the previous data record to determine the capacity of the data record that is recorded this time.
A secondary battery such as the lithium ion battery suffers a large amount of self-discharge even in stop state. Thus, in the stop state status, past results are referred to in accordance with the current capacity, a self-discharge capacity multiplied by the stop time is subtracted from the capacity of the previous data record, and the computed value is set as the capacity of the data record recorded this time.
In the voltage of the operational results information, a current measurement value at the time noted in the results acquisition date/time is stored.
It may be a waste of store capacity to automatically record the data record with the status of stop state at 10 minute intervals. Thus, only the data record of the time at which the status switched to stop state and the data record of a predetermined measurement time immediately before switching to another status may be recorded, while omitting the recording of intervening data records.
As mentioned above, according to the present embodiment, it is necessary to leave a charge state history as operational results information for predicting a charge sequence. Thus, the discharge state history may also be omitted as in the stop state.
As described with reference to
b) is a graph illustrating the discharge characteristics data information. The horizontal axis of the graph shows capacity, and the vertical axis shows voltage. During actual operation, not all of the battery modules may be completely discharged. Thus, in accordance with the discharge characteristics (estimate) indicated by the dotted line in the graph, the discharge characteristics are managed by the depth of discharge (DOD) starting from the voltage at the start of discharge. In
a) compares the degradation over time of battery performance of three battery modules with different manufacturing conditions A, B, and C (such as temperature), where the discharge capacity of each battery module was measured, by the same method as in
b) compares the degradation over time of battery performance of three battery modules in a case where the battery modules were used differently (i.e., when the operational results are different) and had the same accumulated operation time condition. It will be seen from the figure that the operational results influence battery degradation. From the measurement results of
In the performance degradation database 133, with respect to a combination of manufacturing state and degradation state, capacity-voltage profile data is stored in advance as charge/discharge characteristics data.
The data correspond to the charge/discharge characteristics data of a battery module manufactured in each manufacturing state and measured at the time of shipping when the degradation state is zero, and to the charge/discharge characteristics data measured when the accumulated use capacity is a predetermined value.
The manufacturing state is identified by the manufacturing condition (such as the temperature at the time of manufacture) of the battery module. The degradation state is indicated by the time for which the battery module manufactured in the corresponding manufacturing state is let stand. In the example of
Referring to
First, the computation processing unit 120, with respect to each battery module of the battery systems 200, reads various results data from the database unit 130.
For example, the computation processing unit 120 reads from the operational results database 131 (
If the capacity-voltage profile data concerning the most recent charge process is that of a process by which only a small portion of the entire capacity was charged, an older operation history may be incorporated to the object of search so that the capacity-voltage profile data of a charge process with greater charge capacity may be read.
When the discharge capacity in the most recent discharge process is large, the relationship between capacity and voltage in the capacity-voltage profile data may be inverted with respect to left and right, and the computed capacity-voltage profile data may be substituted as the capacity-voltage profile data concerning the charge process.
The computation processing unit 120 reads from the manufacturing inspection results database 132 (
The computation processing unit 120 also reads from the environment results database 134 (
The computation processing unit 120 also reads from the check plan database 135 check plan data corresponding to the battery system number.
The computation processing unit 120 (specifically, the degradation degree estimation processing unit 121) performs a process of collating the capacity-voltage profile data at the time of shipping acquired in step S101 and the most recent capacity-voltage profile data with the capacity-voltage profile data stored in the performance degradation database 133 (
The computation processing unit 120 (specifically, the use pattern estimation processing unit 122) creates a past use pattern from the past operational results data acquired in step S101 and the environment results data to estimate a future use pattern for each battery module. Specifically, based on the past use pattern, the future use capacity of the battery module is estimated in terms of a distribution having a use capacity average value and a standard deviation at elapsed time intervals.
The computation processing unit 120 (specifically, the remaining operating life computation processing unit 123), using the degradation degree of the battery module computed in step S102 and degradation transition data of the corresponding battery module with respect to the accumulated use capacity, and the future use pattern of the relevant battery module computed in step S103, computes a distribution having an average value of the maximum capacity and a standard deviation at elapsed time intervals of the relevant battery module.
The computation processing unit 120 (specifically, the replacement timing indication processing unit 124), using the check plan data acquired in step S101 and the remaining operating life data of the relevant battery module computed in step S103, designates a battery module to be replaced at each time of checking. If it is computed that the necessary capacity cannot be ensured before the next time of checking, an indication for modifying the check timing is issued.
The degradation degree estimation processing unit 121 compares the capacity-voltage profile data at the time of shipping acquired in step S101 with the corresponding data stored in the performance degradation database 133 to estimate corresponding data closest to the manufacturing state of the battery module as the object for processing. In
For the estimating process here, the pattern matching method described in
Measurement data Qm(V) of the battery module is expressed by the following expression.
Q
m(V)=f(v) (Expression 1)
where f(V) is a function of the voltage V.
Then, the degradation degree estimation processing unit 121 acquires the capacity-voltage profile data as the matching object from the performance degradation database 133 (step S302).
The matching object data Qi(V) is expressed by the following expression:
Q
i(V)=f(v) (Expression 2)
where f(V) is a function of voltage V.
The degradation degree estimation processing unit 121 then calculates a difference Δ between the measurement data Qm(V) and the matching object data Qi(V) according to the following expression.
The degradation degree estimation processing unit 121 calculates the difference Δ from the measurement data Qm(V) with respect to all of the matching object data Qi(V), and selects its minimum value.
Thereafter, the degradation degree estimation processing unit 121 acquires attributes (manufacturing state, degradation state) of the capacity-voltage profile data selected in step S303 (step S304).
The degradation degree estimation processing unit 121 acquires the capacity-voltage profile data of each degradation state registered with respect to the manufacturing state estimated in step S201. Specifically, the degradation degree estimation processing unit 121 acquires all of the capacity-voltage profile data arranged in the same vertical column as the capacity-voltage profile data indicated by “Process result of S201” in
The degradation degree estimation processing unit 121 compares the capacity-voltage profile data representing the operational results information of the battery module as the current charge object that has been read in step S101 with the capacity-voltage profile data of each degradation state acquired in step S202 to estimate the corresponding data closest to the degradation state of the relevant battery module. In
In this estimating process too, the capacity-voltage profile data corresponding to the degradation state such that the difference Δ is minimized is selected using the pattern matching method illustrated in
The voltage range (indicated by solid line in a bottom frame of
From the above reasons, when the capacity-voltage profile data representing the operational results information is selected, the accuracy of the pattern matching process can be increased by selecting the operational results information having a voltage range close to the voltage range of the capacity-voltage profile data stored in the performance degradation database as much as possible.
The use pattern estimation processing unit 122 computes the accumulated use capacity for each tallying interval from the operational results data of the relevant battery module that has been acquired in step S101 for each of predetermined tallying intervals that are set in advance.
The use pattern estimation processing unit 122 computes an average value and a standard deviation of the accumulated use capacity between the tallying intervals from the accumulated use capacity for each of the tallying intervals computed in step S301. For example, the use pattern estimation processing unit 122, with respect to the accumulated use capacity in the past N tallying intervals, computes its average value and standard deviation. The value of N is set such that the object intervals are from several days to several months.
The use pattern estimation processing unit 122, based on the result of computation of the average and standard deviation of the past accumulated use capacity between the tallying intervals computed in step S302, estimates a distribution of the accumulated use capacity for each of the future tallying intervals with respect to the relevant battery module. For example, the distribution of the accumulated use capacity for the coming whole day is created from the average and standard deviation of the accumulated use capacity for the past seven days. For the subsequent distribution of the accumulated use capacity, the average and standard deviation of the accumulated use capacity including days even before the past seven days are computed. Thus, when the distribution of the future accumulated use capacity is estimated, the range of the past results is increased so as to reflect the future uncertainty in the distribution.
Another process operation preferable for step S103 will be described. Specifically, a method of using past operational results data and environment results data for estimating the future use pattern will be described.
The use pattern estimation processing unit 122 computes the accumulated use capacity for each tallying interval from the operational results data of the relevant battery module acquired in step S101 for each of the predetermined tallying intervals set in advance. This process is the same as step S401.
The use pattern estimation processing unit 122 computes an average value of the environment results data for each tallying interval from the environment results data of the relevant battery system acquired in step S101, for each of the predetermined tallying intervals set in advance. It is assumed that, as the environment results data, the temperature, humidity, wind speed (average wind speed, maximum wind speed), the amount of sunlight and the like at the location of installation of the battery system are regularly measured.
The use pattern estimation processing unit 122, using the accumulated use capacity for each tallying interval computed in step S501 and the average value data of the environment results for each tallying interval computed in step S502, creates a mathematical model representing the relationship between the accumulated use capacity and the environment results. For example, the use pattern estimation processing unit 122 creates the mathematical expression of the relationship between the environment results data and the accumulated use capacity by performing multiple regression computation using the accumulated use capacity as the objective variable and each of the environment results data items as the explanatory variable.
The use pattern estimation processing unit 122 computes a change over time of the environment results, using the past environment results data. For example, for the change over time in one day, a temporary change in each day of the week is calculated on a weekly basis by computing an average value and a standard deviation of each tallying interval. The change per day on a weekly basis is calculated by computing an average value and a standard deviation of each day of the week on a monthly basis.
The use pattern estimation processing unit 122 substitutes the change over time of the average and standard deviation of the environment results data computed in step S504 into the mathematical expression model created in step S503 representing the relationship between the accumulated use capacity and the environment results, and computes a use pattern distribution corresponding to the change over time of the environment results.
The remaining operating life computation processing unit 123 acquires the performance degradation data acquired in step S101, the degradation degree of the relevant battery module computed in step S203, and the performance degradation data used for the computation.
The remaining operating life computation processing unit 123, based on the information acquired in step S601, sets an initial value indicating the current point state of the performance degradation data indicating the relationship between the accumulated use capacity of the relevant battery module and the capacity.
The remaining operating life computation processing unit 123 substitutes, into the performance degradation change data with respect to the use capacity from the current point of the relevant battery module acquired in step S602, the distribution data of the relevant battery module use pattern computed in step S403 or step S505, to compute a distribution (average value and standard deviation) of transition of the performance degradation with respect to the future change over time of the relevant battery module.
Thereafter, in step S603, the transition of the future use capacity is substituted into the relationship between the accumulated use capacity and capacity degradation change following the initial value of the performance degradation data, so as to compute the distribution of transition of the performance degradation with respect to the future change over time. For example, the graph on the right on
The replacement timing indication processing unit 124 acquires the check plan information for the relevant battery system and device.
The replacement timing indication processing unit 124, using the computed result of the remaining operating life for each battery module computed in step S603, computes the probability of the capacity of each battery module becoming lower than (deviating from) a threshold value with respect to each check point in time acquired in step S701.
The replacement timing indication processing unit 124, with respect to the battery module of which the probability computed in step S702 exceeds the allowable value, indicates that the administrator should replace the battery module at a check timing before the allowable value is exceeded. On the other hand, if the probability of deviating the capacity threshold value at the next check timing exceeds the allowable value, information “Replace immediately” is output. The indication may involve an alert sound, a warning lamp, or voice, or a display of characters or illustrations and the like on an administrator screen.
In the columns for check plans 1 to 3, the probability of the capacity of the battery module deviating from the threshold value at the time of execution of each check is displayed. For example, when the probability of the capacity deviating from the threshold value has an allowable value of 20%, the battery module MO2 exceeds the allowable value at the point in time of the check timing 2. Thus, the “check plan 1” which is two timings earlier is identified as the replacement timing, and an indication message “Replace at check 1” is displayed in the replacement indication column. The battery module MO3 already exceeds the allowable value at the point in time of the next check plan 1. Thus, in the replacement indication column corresponding to the battery module MO3, “Replace immediately” is displayed. The battery modules MO1 and MO4 do not exceed the allowable value within the three most-recent check plans, so that no replacement indication is issued.
In
By using the maintenance management system 100 according to the present embodiment, the replacement timing can be determined for each battery module by considering the manufacturing variation or operational results variation of each battery module, and an indication can be issued. Based on the relationship with the check plan that is expected for a battery system, the replacement timing indication can be issued. Thus, battery system maintenance can be managed efficiently, whereby the operating ratio of the battery system as a whole can be increased.
The present invention is not limited to the above implementation examples and may include various modifications. The foregoing implementation examples have been described for the purpose of facilitating an understanding of the present invention, and the present invention is not limited to an implementation example having all of the described configurations. A part of one implementation example may be replaced by the configuration of another implementation example, or the configuration of the other implementation example may be incorporated into the configuration of the one implementation example. With regard to a part of the configuration of each implementation example, addition, deletion, or substitution of other configurations may be made.
Some or all of the configurations, functions, processing units, process means and the like may be realized by an integrated circuit or other hardware. The configurations, functions and the like may be realized by a processor interpreting and executing a program configured to realize the respective functions. Namely, the configurations, functions and the like may be realized by software. The program for realizing the functions and information about tables, files and the like may be stored in a storage device such as a memory, a hard disk, or a solid state drive (SSD), or a storage medium such as an IC card, an SD card, or a DVD.
The control lines and information lines indicate only those considered necessary for description and may not necessarily represent all of the control inlines or information lines required in a product. It may be considered that almost all configurations are mutual connected in reality.
| Number | Date | Country | Kind |
|---|---|---|---|
| 2012-097757 | Apr 2012 | JP | national |
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/JP2013/060425 | 4/5/2013 | WO | 00 |
