JP7634438B2 - Battery storage system and battery maintenance support method - Google Patents

Description

The present invention relates to a battery storage system capable of determining the health of a battery storage system having cooling capacity, and a battery maintenance support method.

To operate a battery storage system safely and securely, it is necessary to manage the battery temperature to keep it within an appropriate range. Therefore, it is important to have technology that allows for proper maintenance according to the state of the battery storage system.

In a battery system equipped with a cooling mechanism, the maximum temperature the battery can reach is determined by a combination of factors, including the battery's deterioration rate, internal resistance, outside temperature, cooling capacity and its rate of decline, and the load pattern (power or current). Therefore, when a battery overheats beyond its specifications, it is necessary to separate the causes, identify the main cause, and implement appropriate measures according to that main cause at the appropriate time.

For this reason, it is particularly important to detect the cooling capacity and its rate of decline among other factors, and there is a demand for technology that can detect this without the need for additional flowmeter sensors or the like. Patent Document 1 discloses a technology that manages storage battery systems, the main use of which is automobiles, and calculates the amount of clogging in a filter that prevents dust from entering the storage battery system as an index of the rate of decline in the cooling capacity of a cooling mechanism that uses an outside air intake fan, and determines the timing for filter replacement.

Patent Document 2 also discloses a battery monitoring device and a battery system, which lists various index values for objectively evaluating the state of a storage battery, and describes how the rate of increase in internal resistance due to deterioration of the battery cell, SOHR (hereinafter simply referred to as "SOHR"), is calculated and used as a battery management index.

JP 2016-177971 A JP 2021-44145 A

The cooling system for the vehicle battery pack in Patent Document 1 is used under completely different conditions depending on the behavioral patterns of the vehicle user to which it is applied. Therefore, in order to realize the calculation of the cooling capacity decline rate estimation, it is necessary to obtain a huge amount of pre-evaluation data for parameter identification.

In response to this, the inventors have calculated the SOHR as a storage battery management index disclosed in Patent Document 2, and examined whether it is possible to simplify the process by applying the SOHR to the estimation of the cooling capacity decline rate as described in Patent Document 1. The present invention has been made in consideration of the above problems, and its purpose is to provide a storage battery system that can determine the decline in cooling capacity without acquiring a huge amount of advance evaluation data.

The present invention, which solves the above problem, is a storage battery system capable of estimating the state of a storage battery equipped with cooling capacity for a mobile body and supporting maintenance. The system includes a battery temperature recording unit that detects and records the maximum temperature Tmax reached on a daily basis using a temperature sensor attached to the storage battery, an environmental temperature recording unit that detects and records the maximum value Tamb,max of the environmental temperature Tamb during the time period going back from the time when the maximum temperature Tmax was detected to the start time of operation on that day, and a maintenance support information table that stores countermeasure policies associated with the state of the storage battery. The system determines the degree of cooling capacity decline based on the maximum temperature Tmax and the maximum value Tamb,max of the environmental temperature Tamb, estimates the state of the storage battery based on the result of the capacity decline determination, and is capable of outputting information selected from the maintenance support information table based on the estimated state of the storage battery.

The present invention provides a battery storage system that can determine whether cooling capacity has decreased without acquiring a large amount of pre-evaluation data. Problems, configurations, and effects other than those described above will become clear from the description of the following embodiment.

1 is a functional block diagram for explaining the configuration of a railway storage battery system (hereinafter also referred to as "this system") according to an embodiment of the present invention. 2 is a graph showing a two-dimensional area used to determine a decrease in cooling capacity in the system of FIG. 1 . 2 is a graph showing the correlation between the degree of battery deterioration and SOHR in the system of FIG. 1 . This is a list of countermeasure policies that are determined based on the results of classification judgment according to the positions where the cause judgment index and the environmental temperature Tamb are plotted on the graph of FIG. 2. 1 is a flowchart showing an outline of a battery maintenance support method according to an embodiment of the present invention (hereinafter also referred to as "the method").

<Summary>
The present system 20 (FIG. 1) will be described below with reference to FIGS. 1 to 4. The present system 20 exemplifies the overall cooling capacity of a storage battery 1, the main application of which is railroads, including an associated cooling mechanism 2, as an object to be managed. The present system 20 determines a decrease in cooling capacity by utilizing the characteristic that a patterned load is repeated according to a railroad operation schedule. As a result, the present system 20 determines a decrease in cooling capacity without acquiring a large amount of related pre-evaluation data.

Based on the result of this determination, the system 20 provides the execution body with information on measures to resolve the malfunction of the storage battery system 20. The execution body prompts the subject (decision department) or a maintenance worker to execute a countermeasure policy based on the information received from the system 20.

The subject refers to a human driver or driving command, as well as a computer such as an operation management system or an automatic driving system. A maintenance worker, etc. refers to a person who can perform maintenance work such as replacing the storage battery 1. In addition, this system 20 identifies parts to be replaced, notifies the user of the arrival of the end of the life that requires replacement, and issues information to encourage the replacement of the parts.

<Configuration>
Fig. 1 is a functional block diagram for explaining the configuration of the present system 20. In Fig. 1, the battery system 20 is composed of a battery group (hereinafter also simply referred to as a "storage battery") 1, a cooling mechanism 2, a battery management device 3, a battery current recording unit 4, a battery voltage recording unit 5, a battery temperature recording unit 6, and an environmental temperature recording unit 7.

The storage battery 1 may be, but is not limited to, a lithium ion battery, a lead storage battery, a nickel metal hydride battery, a nickel cadmium battery, etc. If the cooling mechanism 2 is a forced air cooling system (not shown), it may be, for example, a heat dissipation fin connected to the can of the storage battery 1, which is a heat generating body, in a thermally conductive manner, and a blower fan that sends air to the fin. Other examples include a liquid cooling system (not shown). Regardless of the cooling system used for the cooling mechanism 2, it is possible to determine a decrease in cooling capacity in combination with the present system 20.

The battery management device 3 is composed of a resistivity calculation unit 8, a maximum temperature extraction unit 9, a factor determination index calculation unit 10, and a factor determination unit 11. The resistivity calculation unit 8 calculates the resistivity. Methods for calculating the resistivity include, but are not limited to, a method in which the resistance value calculated from the ratio of the current change to the voltage change is divided by a reference resistance value, and a Kalman filter. The Kalman filter is used to estimate a quantity that changes over time from observations with discrete errors.

The storage battery 1 is configured as a battery group (also called a battery pack) by connecting an appropriate number of battery cells in series and parallel. The status detection device may also determine the rate of rise SOHR of the internal resistance of the entire battery group 1 based on the rate of rise SOHR of the internal resistance of each battery cell that configures the battery group (storage battery) 1.

As an example, the SOHR can be calculated by the following formula (1), but it may be calculated by other methods. In the formula (1), Rc is the current internal resistance value of the battery cell, and Ro is the internal resistance value of the battery cell at the beginning of use.
SOHR=100×(Rc/Ro) (1)

The maximum temperature extraction unit 9 extracts the maximum battery temperature Tmax and the maximum outside air temperature Tamb,max during daily train operation. The factor determination index calculation unit 10 calculates the cooling capacity degradation determination index using the resistivity, the maximum battery temperature Tmax, and the maximum outside air temperature Tamb,max as shown in the following formula (2).
(Tmax-Tamb,max)/SOHR...(2)

The factor determination unit 11 determines whether the cooling capacity has decreased using the cooling capacity decrease determination index and the maximum outside air temperature Tamb,max. Details of the determination method are described below with reference to Figures 2 to 4.

Fig. 2 is a graph showing a two-dimensional area used to determine the cooling capacity decrease in the system 20 of Fig. 1. In the graph of Fig. 2, the horizontal axis is the outside air temperature Tamb [°C], and the vertical axis is the cooling capacity decrease determination index, which is shown in the following formula (3).
(Tmax-Tamb)/SOHR=ΔT/SOHR[K]...(3)

In the graph in Figure 2, the threshold boundary is indicated by a diagonal dashed line sloping downward to the right. If the maximum temperature reached Tmax [℃] and the maximum outside air temperature Tamb,max [℃] are plotted as daily observed values on this graph, and the position is below the threshold boundary, it is determined that there is no decrease in cooling capacity, and if it is above, there is a decrease in cooling capacity.

Figure 3 is a graph showing the correlation between the rate of increase in internal resistance due to deterioration of a battery cell, SOHR [%], and the degree of battery deterioration in the system 20 of Figure 1. As shown in Figure 3, if the battery cell is brand new, the SOHR is small, and if the battery is a deteriorated product that needs to be replaced, the SOHR is large. This means that, as shown in formula (1) above, the current internal resistance value Rc of the battery cell gradually increases with deterioration, compared to the internal resistance value Ro of the battery cell at the beginning of use.

Figure 4 is a table showing countermeasure policies determined based on the results of classification judgment according to the position where the factor judgment index ΔT/SOHR [K] of the above formula (2) and the environmental temperature Tamb [°C] are plotted on the graph of Figure 2. This table shows, from the left, the temperature and countermeasure policies as horizontal items, and, from the top, shows, from the top, the no temperature deviation (suitable temperature), SOHR rise, decreased cooling capacity, outside temperature rise (rare hot day), and disturbance of operation schedule as vertical items.

In FIG. 4, the temperature indicates whether the position where the daily observed value is plotted on the graph in FIG. 2 is above the boundary line that is the threshold value or below it. The countermeasure policy further specifies whether the countermeasure is a battery replacement, a cooling replacement, or a control replacement. With this system 20, it is particularly important to detect the cooling capacity and its rate of decline among other factors, and this can be detected without the need for additional flowmeter sensors, etc.

As described above, the plot position is classified according to the position on the graph in Figure 2, and based on the result, a countermeasure policy is decided, indicated by O, X or △ in the table in Figure 4. O means replacement is not necessary, and × means replacement is necessary. In the case of △, replacement is only required if the SOHR [%] value is greater than a specified value. Therefore, △ means that it is temporarily required.

The first row in Figure 4 shows a case where there are no features in the plot and no temperature deviation. In this case, a policy is shown in which none of the measures of battery replacement, cooling replacement, or control replacement is required.

The second row in Figure 4 shows a case where there is no characteristic in the plot and the SOHR is rising. In this case, regardless of the environmental temperature Tamb [℃], the battery needs to be replaced, and a control exchange is temporarily required.

The third row in Figure 4 shows a case where cooling capacity has decreased because many of the plotted positions are above the threshold boundary line. In this case, cooling replacement is required, and depending on SOHR, battery replacement may also be required.

The fourth row in Figure 4 shows the case where the plotted position is on the threshold boundary and the outside temperature is rising. In this case, depending on the SOHR, a policy is shown that requires either a battery exchange or a control exchange.

The fifth row in Figure 4 shows a case where there is only one plotted point above the threshold boundary line, indicating a disruption in the schedule. In this case, a policy requiring battery replacement is indicated depending on the SOHR.

<Operation>
FIG. 5 is a flowchart showing an outline of the procedure of the method. In the method, the system 20 is used to estimate the state of the storage battery 1 equipped with a cooling capacity for a mobile body and to support maintenance through steps (S1 to S8) shown in FIG. 5. Note that, prior to step (S1), a user (installer, manager) of the system 20 prepares a maintenance support information table in which countermeasure policies associated with the state of the storage battery 1 are stored and held so as to be freely readable. Step (S1) and subsequent steps are executed by the system 20. The processing functions are realized by a computer (not shown) constituting the system 20 executing a program stored in a memory.

The computer executing this method can freely read out a maintenance support information table that stores and holds information on countermeasure policies associated with the state of the storage battery 1 (S1). The system 20 detects and records the maximum temperature Tmax reached on a daily basis using a temperature sensor attached to the storage battery 1 (S2). The maintenance support information table has an amount of information on the order of that shown in FIG. 4, and it is sufficient to have a simple list rather than a huge amount of pre-evaluation data. It is preferable that the maintenance support information is based on empirical rules (database) that objectively take into account the existing maintenance cycle and conditions such as busy times and weather, and is therefore capable of leading to optimal judgments.

The system 20 detects and records the maximum value Tamb,max of the environmental temperature Tamb during the time period going back from the time when the maximum temperature Tmax was detected to the start of operation on that day (S3). The system 20 determines whether the cooling capacity has decreased based on the maximum temperature Tmax and the maximum value Tamb,max of the environmental temperature Tamb (S4).

The system 20 estimates the state of the storage battery 1 based on the result of the determination of the decrease in cooling capacity (S5). The system 20 outputs information selected from the maintenance support information table based on the estimated state of the storage battery 1 (S6).

In this method, the system 20 uses the SOHR calculated by the resistivity calculation unit 8 as a battery management index, allowing the degree of cooling capacity decline to be estimated by a simple calculation. As a result, this method makes it possible to determine the decline in cooling capacity without acquiring a huge amount of pre-evaluation data. In addition, existing sensors for measuring voltage, current, and temperature are sufficient, so there is no need to install additional sensors, or the burden of doing so is minimal.

The system 20 calculates a limit cooling capacity decline index at which the maximum temperature of the storage battery 1 falls within the upper limit temperature (S7). In a part replacement timing prediction step (S8), the system 20 predicts and notifies the appropriate time for part replacement based on the current cooling capacity decline index and the predicted amount of cooling capacity decline due to operation.

In this method, the parts to be replaced are at least one of the storage battery 1 itself and the cooling mechanism parts. As to which parts are to be replaced, the countermeasure policy determined in the manner shown in the table in Figure 4 should be followed.

In this way, with this system 20, it is possible to predict the cause and near-future of a decline in cooling capacity. Therefore, this system 20 is effective by encouraging the operator or maintenance worker to take the optimal measure to eliminate the cause identified as either battery replacement, cooling (mechanical part) replacement, or control change as shown in Figure 4.

In the part replacement timing prediction step (S8), the system 20 may notify the appropriate time for part replacement as the number of remaining possible runs until part replacement based on the predicted amount of cooling capacity decline per day of operation. In other words, according to this method, for the part identified to be replaced in order to eliminate the cause of the decline in cooling capacity, future replacement dates can be clearly notified if operation continues at the current operating frequency.

In the part replacement timing prediction step (S8), the system 20 may calculate a limit cooling capacity decline index that can determine a decline in cooling capacity from the deterioration rate of the storage battery 1 and the operation information. The calculation result of this method can obtain information on the frequency of use of the managed object from the operation information, so that the degree of decline in cooling capacity according to that frequency can be quantitatively determined. As a result, according to this method, it is possible to urge the operation entity or maintenance worker, etc. to replace parts at an appropriate time, not too early and not too late, before a failure caused by a defective part occurs.

In the part replacement timing prediction step (S8), the system 20 may calculate the limit cooling capacity degradation index using information on weather conditions during the operation period. In this method, if the calculation result of the limit cooling capacity degradation index is overheating due to extreme heat, for example, information on appropriate countermeasures is issued.

In the part replacement timing prediction step (S8), the system 20 may use the regular maintenance plan and operation plan of the railway vehicle to notify the regular maintenance timing just before the predicted value of the cooling capacity deterioration index exceeds the limit cooling capacity deterioration index as the part replacement timing. In this way, the operation body or maintenance worker can be urged to replace the part at an appropriate time, not too early and not too late, before a failure caused by a defective part occurs.

Based on the result of this determination, this system 20 provides information to an execution entity that can execute measures for the storage battery 1 and its associated cooling mechanism 2 that are under management. The execution entity exerts its effectiveness by encouraging a subject (decision-making unit) or a maintenance worker to execute a countermeasure policy based on the information received from this system 20.

In this system 20, the SOHR calculated by the resistivity calculation unit 8 is used as a battery management index, so the degree of cooling capacity decline can be estimated by simple calculation. As a result, this system 20 can determine the decline in cooling capacity without acquiring a huge amount of pre-evaluation data.

This system 20 can estimate the state of the storage battery 1 based on the result of the determination of the decrease in cooling capacity, and output maintenance support information selected from the maintenance support information table 11 based on the estimated state of the storage battery 1. This allows this system 20 to determine the decrease in cooling capacity without acquiring a huge amount of pre-evaluation data related to it.

In other words, even if the maximum reached value Tamb,max of the environmental temperature Tamb detected during the operating hours of the day is high, if the maximum reached temperature Tmax of the storage battery 1 does not exceed the upper limit temperature, the cooling capacity is functioning sufficiently and it can be considered that there is no decrease in cooling capacity.

In addition, when the maximum reached value Tamb,max of the environmental temperature Tamb is abnormally high, if the maximum reached temperature Tmax of the storage battery 1 also exceeds the upper limit temperature, this is not considered to be a malfunction of the storage battery 1 or the storage battery system 20, but rather a natural phenomenon. If overheating is unavoidable on an unexpectedly hot day, a decision is made to suspend operation of the managed railway vehicles.

In other words, the cooling capacity of the storage battery 1 and the storage battery system 20 is designed to be just a little bit higher than the minimum required to ensure that the upper limit temperature of the storage battery 1 is not exceeded even in the heat of the day. The premise is that the design will not allow the battery 1 to overheat, so that the upper limit temperature is not exceeded even on extremely hot days, let alone when it is not hot.

Conversely, if the maximum temperature Tmax of the storage battery 1 becomes abnormally high even though the maximum value Tamb,max of the environmental temperature Tamb is not high, it is considered that at least either the storage battery 1 or the storage battery system 20 has failed and the cooling capacity has decreased to the extent that it deviates from the standard.

In this case, the system 20 checks the maximum temperature Tmax of the storage battery 1 against at least one of the environmental temperature specifications (e.g., -15°C≦air temperature 50°C) and the heat resistance design (e.g., -20°C≦air temperature 55°C) of the railway vehicle being managed. Depending on the check result, the system 20 determines that the failure occurred within the range of normal use defined in the specifications. In other words, it is a failure that should not occur, and urges the operator or maintenance worker to take measures against the failure.

Based on technical information including such empirical rules, it is known that the cooling capacity of the storage battery 1 and storage battery system 20 deteriorates over time, even if they are designed to comply with product specifications at the time of manufacture. Therefore, this system 20 detects cooling capacity at an early stage and outputs optimal maintenance information.

For this purpose, the present system 20 is able to determine the decline in cooling capacity without acquiring a huge amount of pre-evaluation data. Furthermore, the present system 20 makes it possible to detect the cooling capacity and its rate of decline, which are particularly important factors, using existing voltage, current, and temperature sensors without the need to install additional flowmeter sensors, etc.

<Additional Information>
The system 20 illustrated here is for use in railways, and has a function of detecting a decrease in the cooling capacity of the storage battery 1 and issuing information indicating a countermeasure policy. In this manner, the application of the system 20 to railway vehicles has been described. However, the application field of the present invention is not limited to this. Other embodiments conceivable within the scope of the technical concept of the present invention are also included within the scope of the present invention. For example, the system is also suitable for a storage battery system for automobiles whose daily operating patterns are patterned, or for battery-powered forklifts, etc.

This system 20 makes more effective use of a battery group (storage battery) 1 having multiple battery cells than conventional methods, and has the effect of making it possible to reduce the number of battery cell replacements as much as possible. This system 20 is a computer equipped with a central processing unit (CPU) and a storage device (memory).

The computer can be a one-chip microcomputer, but it may also be part of a computer for other purposes, and it may be configured to communicate wirelessly between the computer in the ground equipment and the mobile body. In that case, of the functional configuration blocks shown in Figure 1, at least the storage battery 1, cooling mechanism 2, battery current recording unit 4, battery voltage recording unit 5, battery temperature recording unit 6, and environmental temperature recording unit 7 should be arranged on the mobile body side as on-board equipment. If the corresponding battery management device 3 is ground equipment, data can be transferred between them via wireless communication.

The CPU determines whether or not the battery group 1 needs to be replaced based on the degree of deterioration of each battery cell calculated based on the detection results of the current sensor and the voltage sensor. When the CPU determines that the battery group 1 needs to be replaced, it identifies the battery group 1 to be replaced based on the degree of deterioration of the battery group 1. Furthermore, it is preferable that the CPU calculates the parameters of the new battery group 1 to be replaced with the battery group 1 to be replaced, or the number of replacements, based on the allowable current value of the new battery group 1.

The degree of cooling capacity decline may be either quantitative or qualitative. Quantitative means expressing the situation or state of something in numbers. Conversely, qualitative means expressing the change or quality of something in words or letters rather than numbers. In this system 20, if the thresholds and judgment criteria set for quantitative judgment are appropriate, qualitative expressions such as "cooling capacity declined" or "no cooling capacity declined" are also useful.

This system 20 is capable of predicting the degree, cause, and near-future of the decline in the cooling capacity of the storage battery 1 or storage battery system 20 under management, using at least one of quantitative and qualitative expressions. In other words, this system 20 is effective by encouraging the operating entity or maintenance workers to take optimal measures to eliminate the identified cause in some way.

This system can be summarized as follows.
[1] This system 20 estimates the state of a storage battery 1 equipped with a cooling capacity for a mobile body and supports its maintenance. As shown in Fig. 1, this system 20 includes a battery temperature recording unit 5, an environmental temperature recording unit 7, and a maintenance support information table (11).

As shown in FIG. 1, the battery temperature recording unit 6 records the daily maximum temperature Tmax detected by a battery sensor attached to the storage battery 1. The environmental temperature recording unit 7 detects and records the maximum value Tamb,max of the environmental temperature Tamb during a period from the start of operation on that day to the time when the maximum temperature Tmax was detected on that day.

Based on the maximum temperature Tmax detected and recorded according to these rules and the maximum value Tamb,max of the environmental temperature Tamb, the system 20 determines the degree of cooling capacity decline. Note that if the state (degree of deterioration, cooling capacity) of the storage batteries 1 that constitute the storage battery system 20 is the same, the maximum temperature Tmax is environmentally dependent and is determined by the outside air temperature Tamb.

In addition, in batteries for mobile applications where the same patterned power load is repeated daily, it is possible to take advantage of the property that the maximum temperature Tmax achieved when the battery system state (level of deterioration, cooling capacity) is the same is determined by the outside air temperature Tamb.

The degree of cooling capacity decline can be determined by where the daily observed value determined by two parameters, the maximum outside air temperature Tamb,max and the daily maximum reached temperature Tmax minus the maximum outside air temperature Tamb,max dating back from the time the daily maximum reached temperature Tmax was recorded to the start of operation on that day, is plotted. The degree of cooling capacity decline can be determined by where the daily observed value determined by two parameters, the maximum outside air temperature Tamb,max and the daily maximum reached temperature Tmax, is plotted. The existing sensors for measuring voltage, current, and temperature are sufficient, so there is no need or only a small burden of installing additional sensors.

[2] The system 20 described in [1] above preferably has a cooling capacity degradation index calculation unit and a part replacement time prediction unit based on the principles shown in Figures 2 to 4. These are configured to satisfy the requirements of the functional block diagram in Figure 1. These do not necessarily have to be named according to the names of the functional block diagram described using Figure 1. As long as the cooling capacity degradation index calculation unit and the part replacement time prediction unit are functions that are described at various times, they may be named in any way and in any distributed form. The cooling capacity degradation index calculation unit calculates a limit cooling capacity degradation index at which the maximum temperature of the storage battery 1 falls within the upper limit temperature.

That is, the cooling capacity decline index calculation unit determines the cooling capacity decline judgment index by dividing ΔT, which is calculated by subtracting the daily maximum temperature Tmax from the maximum outside air temperature Tamb,max dating back from the time when the daily maximum temperature Tmax was recorded to the start of operation on that day, by the resistivity SOHR of the storage battery 1, using the above formulas (2) and (3). As shown in Figure 2, the system 20 determines whether or not there is a decline in cooling capacity based on where the two parameters, the cooling capacity decline judgment index and the maximum outside air temperature Tamb,max, are plotted.

The part replacement timing prediction unit can notify the appropriate time for part replacement based on the current cooling capacity degradation index and the predicted amount of cooling capacity degradation due to operation. The parts to be replaced are at least either the storage battery 1 itself or the cooling mechanism parts. As for which parts are to be replaced, it is sufficient to follow the countermeasure policy determined in the manner shown in the table in Figure 4.

In this way, with this system 20, it is possible to predict the cause and near-future status of a decline in cooling capacity, and to encourage the operation body or maintenance workers to take optimal measures. In this way, in order to eliminate the identified cause, this system 20 appropriately issues support information such as battery replacement, cooling (mechanical part) replacement, or control change, as shown in FIG. 4.

[3] In the present system 20 described in [2] above, the part replacement timing prediction unit is able to notify the appropriate time for part replacement as the number of remaining possible runs before part replacement, based on the predicted value of the amount of cooling capacity decline per day of operation. In other words, according to the present system 20, it is possible to clearly notify the limit at which operation can continue at the current operating frequency for a replacement part identified to eliminate the cause of the decline in cooling capacity, i.e., the deadline for future replacement.

[4] In the system 20 described in [3] above, the part replacement time prediction unit preferably calculates a limit cooling capacity degradation index based on the deterioration rate of the storage battery 1 and the operation information. This part replacement time prediction unit is configured to satisfy the requirements of the functional block diagram of Figure 1. The degree of cooling capacity degradation can be quantitatively determined based on the calculation results of the part replacement time prediction unit.

[5] In the system 20 described in [4] above, it is preferable that the part replacement time prediction unit calculates the limit cooling capacity decline index using information on weather conditions during the operation period. Here, too, the part replacement time prediction unit is configured to have the requirements of the functional block diagram of Figure 1. The degree of cooling capacity decline can be quantitatively determined based on the result of the limit cooling capacity decline index calculated by the part replacement time prediction unit.

The battery storage system 20 that is the subject of management by this method is designed so that its cooling capacity does not exceed the upper limit, even on extremely hot days, let alone when the weather conditions are cool. Despite this, if the calculation result of the limit cooling capacity decrease index in this system 20 indicates overheating, information on appropriate countermeasures is issued.

[6] In the system 20 described in [5] above, the part replacement timing prediction unit uses the regular maintenance plan and operation plan of the railway vehicle to notify the part replacement timing of the regular maintenance immediately before the predicted value of the cooling capacity deterioration index exceeds the limit cooling capacity deterioration index.

This system 20 is suitable for managing mainly a storage battery system 20 for railway applications (including storage battery 1). In a storage battery system 20 for railway applications, roughly the same pattern of power load characteristics (load pattern) is repeated every day in accordance with the train schedule.

Therefore, when the frequency of use is constant and continuous, such as in the case of scheduled service vehicles, not only for railways but also for various other types of transport vehicles, the degree of deterioration of components can be estimated by multiplying the rate of deterioration according to the frequency of use by the elapsed time. A scheduled maintenance plan for railway vehicles here is a time chart that determines the replacement timing for each part with a known usable lifespan.

Furthermore, this system 20 determines the timing of regular maintenance to be the period immediately before the predicted value of the cooling capacity degradation index exceeds the limit cooling capacity degradation index. This system 20 incorporates the regular maintenance timing into a time chart for each train and provides it for calendar (schedule) management. By performing calendar management, this system 20 notifies maintenance workers, etc. of the regular maintenance timing.

The timing of regular maintenance notified in this way is immediately before the predicted value of the cooling capacity degradation index exceeds the limit cooling capacity degradation index. This timing is set based on common technical knowledge of quality control, with respect to the known specific lifespan of each managed part, while eliminating waste and leaving a minimum of leeway. As a result, this system 20 is effective by urging the operation entity or maintenance worker, etc. to replace parts at an appropriate time, neither too early nor too late, before a breakdown caused by a defective part occurs.

On the other hand, even for equipment and devices used only on railways, if the frequency of use is sporadic and irregular, the degree of deterioration of components does not necessarily progress at the same rate as deterioration over time. In this case, the system 20 replaces parts at the optimal timing by revising the regular maintenance plan established for each railway vehicle forward or backward based on an index of frequency of use calculated from the train operation plan.

In other words, in this system 20, if train operation plans are infrequent, the maintenance cycle is extended. Conversely, in this system 20, if train operation plans are frequent, the maintenance cycle is shortened. In this way, it is effective in encouraging the operation body or maintenance workers to replace parts at the appropriate time, not too early and not too late, before a breakdown caused by a defective part occurs.

20... battery system (this system), 1... battery group (storage battery), 2... cooling mechanism, 3... battery management device, 4... battery current recording unit, 5... battery voltage recording unit, 6... battery temperature recording unit, 7... environmental temperature recording unit, 8... resistivity calculation unit, 9... maximum reached temperature extraction unit, 10... factor determination index calculation unit, 11... factor determination unit, SOHR... rate of increase in internal resistance value due to deterioration of battery cell, Tamb... environmental temperature, Tamb,max... maximum reached value of (Tamb environmental temperature), Tmax... maximum reached temperature

Claims (12)

A storage battery system capable of estimating a state of a storage battery having a cooling capacity for a mobile body and supporting maintenance,
a battery temperature recorder that detects and records a maximum temperature Tmax on a daily basis using a temperature sensor attached to the storage battery;
an environmental temperature recording unit that detects and records a maximum reached value Tamb,max of the environmental temperature Tamb in a time period going back from the time when the maximum reached temperature Tmax was detected to the start time of the operation of the day;
a maintenance support information table in which countermeasure policies associated with the states of the storage batteries are stored;
Equipped with
A decrease in cooling capacity is determined based on the maximum reached temperature Tmax and the maximum reached value Tamb,max of the environmental temperature Tamb;
estimating a state of the storage battery based on the result of the determination of the cooling capacity decrease;
and outputting information selected from the maintenance support information table based on the estimated state of the storage battery.
Battery storage system. a cooling capacity degradation index calculation unit that calculates a limit cooling capacity degradation index at which a maximum temperature of the storage battery falls within an upper limit temperature;
a part replacement timing prediction unit that notifies the user of an appropriate time for part replacement based on a current cooling capacity deterioration index and a predicted cooling capacity deterioration amount due to operation;
Further comprising
The battery system according to claim 1 . the part replacement time prediction unit notifies the appropriate time for part replacement as the number of remaining possible operations until part replacement based on a predicted value of a cooling capacity decrease per day of operation;
The battery system according to claim 2 . The part replacement time prediction unit calculates a limit cooling capacity deterioration index capable of determining a deterioration in cooling capacity from a deterioration rate of the storage battery and operation information.
The battery system according to claim 3 . The part replacement time prediction unit calculates the limit cooling capacity deterioration index using information on weather conditions during an operation period.
The battery system according to claim 4. the part replacement timing prediction unit uses a regular maintenance plan and an operation plan for the railway vehicle and notifies, as a part replacement timing, a regular maintenance timing immediately before a predicted value of a cooling capacity deterioration index exceeds the limit cooling capacity deterioration index.
The battery system according to claim 5 . A storage battery maintenance support method in which a computer estimates a state of a storage battery having a cooling capacity for a mobile object and supports maintenance, comprising:
The computer includes:
a step of freely reading out a maintenance support information table in which information on countermeasure policies associated with the state of the storage battery is stored;
A step of detecting and recording a maximum temperature Tmax reached by the storage battery on a daily basis using a temperature sensor attached to the storage battery;
A step of detecting and recording a maximum reached value Tamb,max of the environmental temperature Tamb in a time period going back from the time when the maximum reached temperature Tmax was detected to the start time of operation of the day;
A step of determining a decrease in cooling capacity based on the maximum reached temperature Tmax and a maximum reached value Tamb,max of the environmental temperature Tamb;
estimating a state of the storage battery based on a result of the determination of the cooling capacity decrease;
outputting information selected from the maintenance support information table based on the estimated state of the storage battery;
having
Storage battery maintenance support method. A step of calculating a limit cooling capacity deterioration index at which the maximum temperature of the storage battery falls within an upper limit temperature;
a part replacement timing prediction step of predicting and notifying an appropriate time for part replacement based on a current cooling capacity deterioration index and a predicted value of a cooling capacity deterioration amount due to operation;
Further comprising
The battery maintenance support method according to claim 7. The part replacement time prediction step notifies an appropriate time for part replacement as a remaining number of possible operations until part replacement based on a predicted value of a cooling capacity decrease amount per day of operation.
The battery maintenance support method according to claim 8. The part replacement time prediction step calculates a limit cooling capacity deterioration index capable of determining a cooling capacity deterioration based on a deterioration rate of the storage battery and operation information.
The battery maintenance support method according to claim 9. The part replacement time prediction step calculates the limit cooling capacity deterioration index using information on weather conditions during an operation period.
The battery maintenance support method according to claim 10. The part replacement timing prediction step uses a regular maintenance plan and an operation plan of the railway vehicle, and notifies the timing of regular maintenance immediately before the predicted value of the cooling capacity deterioration index exceeds the limit cooling capacity deterioration index as the part replacement timing.
The battery maintenance support method according to claim 11.

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