Battery abnormality diagnostic device

Abstract

To provide a battery abnormality diagnostic device for securing the accuracy of battery abnormality diagnosis while suppressing the influence on the traveling of a vehicle.SOLUTION: The battery abnormality diagnostic device is provided with: an acquisition unit for acquiring a plurality of current values of a battery and a plurality of voltage values of the battery within a predetermined period for transferring electric power to and from a motor that is a running power source of the vehicle; a calculation unit for calculating an internal resistance value of the battery based on a dispersion value of the plurality of current values of the battery within the predetermined period, a variation amount of a charging rate of the battery within the predetermined period, and the plurality of current values and the plurality of voltage values within the predetermined period; and a diagnosis unit for executing the abnormality diagnosis processing of the battery based on the internal resistance value. The diagnostic unit executes the abnormality diagnostic processing based on the internal resistance value calculated when the dispersion value is equal to or greater than a predetermined value and the variation amount is equal to or less than a first threshold value, or when the dispersion value is less than the predetermined value and the variation amount is equal to or less than a second threshold value smaller than the first threshold value.SELECTED DRAWING: Figure 5

Description

[Technical field]

[0001] The present invention relates to a battery abnormality diagnosis device. [Background technology]

[0002] There is a technology for diagnosing a battery abnormality based on the internal resistance value of the battery that receives and transmits power to and from a motor that is a driving power source of the vehicle. The internal resistance value is calculated based on a plurality of current values ​​and a plurality of voltage values ​​of the battery within a predetermined period. Here, if the variance of the plurality of current values ​​is small, there is a risk that the accuracy of the calculation of the internal resistance value will decrease, and the accuracy of the abnormality diagnosis will decrease. For this reason, the variance of the plurality of current values ​​is ensured by increasing the power consumption of the vehicle's auxiliary equipment that uses the battery as a power source (see Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2013-125016 A Summary of the Invention [Problem to be solved by the invention]

[0004] When the power consumption of the auxiliary equipment increases as described above, the battery's charging rate may decrease, which may affect the running of the vehicle. In addition, even while the multiple current values ​​and multiple voltage values ​​for calculating the internal resistance value are being acquired, the battery repeats charging and discharging, and the battery's charging rate fluctuates. If the amount of fluctuation in the charging rate is large, the accuracy of the calculation of the internal resistance value may decrease, which may result in a decrease in the accuracy of the abnormality diagnosis.

[0005] SUMMARY OF THE PRESENT DISCLOSURE An object of the present invention is to provide a battery abnormality diagnosis device that ensures accuracy in diagnosing an abnormality in a battery while minimizing the effect on vehicle driving. [Means for solving the problem]

[0006] The above object can be achieved by a battery abnormality diagnosis device comprising: an acquisition unit that acquires multiple current values ​​and multiple voltage values ​​within a predetermined period of a battery that exchanges power with a motor that is a driving power source of a vehicle; a calculation unit that calculates an internal resistance value of the battery based on a variance value of the multiple current values ​​within the predetermined period, a fluctuation amount of the charging rate of the battery within the predetermined period, and the multiple current values ​​and the multiple voltage values ​​within the predetermined period; and a diagnosis unit that performs an abnormality diagnosis process for the battery based on the internal resistance value, wherein the diagnosis unit performs the abnormality diagnosis process based on the calculated internal resistance value when the variance value is greater than or equal to a predetermined value and the fluctuation amount is less than a first threshold value, or when the variance value is less than the predetermined value and the fluctuation amount is less than a second threshold value that is smaller than the first threshold value.

[0007] The calculation section may calculate the variance value, the amount of fluctuation, and the internal resistance value for each of the predetermined periods.

[0008] The calculation unit may calculate, as the amount of fluctuation, a difference between a maximum value and a minimum value of the charging rate within the predetermined period.

[0009] The calculation unit may calculate the amount of variation based on an integrated value of the plurality of current values ​​within the predetermined period. Effect of the Invention

[0010] According to the present invention, it is possible to provide a battery abnormality diagnosis device that ensures accuracy in diagnosing an abnormality in a battery while minimizing the effect on vehicle driving. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 is a schematic diagram of a vehicle. [Diagram 2] FIG. 2 is an IV characteristic diagram showing the relationship between the current value and the voltage value of the battery. [Diagram 3] 3A and 3B are diagrams illustrating the influence of the variance value on the calculation accuracy of the internal resistance value. [Figure 4]4A and 4B are diagrams illustrating the effect of fluctuations in the charging rate on the calculation accuracy of the internal resistance value. [Diagram 5] FIG. 5 is a flowchart illustrating an example of the abnormality diagnosis control. [Figure 6] FIG. 6 is an explanatory diagram of the calculation of the variance value, the amount of fluctuation, and the internal resistance value for each predetermined period. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] [Vehicle outline] 1 is a schematic diagram of a vehicle 1. The vehicle 1 is an electric vehicle equipped with a motor 2 as a driving power source. The vehicle 1 is equipped with the motor 2, a propeller shaft 3, a differential gear 4, a drive shaft 5, driving wheels 6, a PCU (Power Control Unit) 7, a battery 8, and an ECU (Electric Control Unit) 10.

[0013] The motor 2 functions as an electric motor that outputs torque when power is supplied. The motor 2 also functions as a generator that generates power when the vehicle 1 is braked. The stored power of the battery 8 is supplied to the motor 2 via the PCU 7. The generated power of the motor 2 is supplied to the battery 8 via the PCU 7. The ECU 10 adjusts the power exchanged between the motor 2 and the battery 8 by controlling the PCU 7.

[0014] The motor 2 is connected to drive wheels 6 via a propeller shaft 3, a differential gear 4, and a drive shaft 5. The torque of the motor 2 is transmitted to the drive wheels 6, causing the vehicle 1 to run.

[0015] The ECU 10 includes a central processing unit (CPU), a random access memory (RAM), a read only memory (ROM), a storage device, etc., and performs various controls by executing programs stored in the ROM and the storage device. The ECU 10 is an example of a battery abnormality diagnosis device, and functionally realizes an acquisition unit, a calculation unit, and a diagnosis unit, which will be described in detail later.

[0016] An ignition switch 20, a current sensor 21, and a voltage sensor 22 are electrically connected to the ECU 10. The ignition switch 20 detects the on / off state of the ignition. The current sensor 21 detects the current of the battery 8. The voltage sensor 22 detects the voltage of the battery 8.

[0017] [Calculating the internal resistance of battery 8] The ECU 10 executes an abnormality diagnosis of the battery 8 based on the internal resistance value of the battery 8. The internal resistance value of the battery 8 is calculated based on a plurality of current values ​​and a plurality of voltage values ​​of the battery 8. FIG. 2 is an IV characteristic diagram showing the relationship between the current value and the voltage value of the battery 8. The horizontal axis indicates the current value and the vertical axis indicates the voltage value. The ECU 10 acquires the current value and the voltage value of the battery 8 at a predetermined time interval based on the current sensor 21 and the voltage sensor 22. Next, the ECU 10 plots the plurality of current values ​​and the plurality of voltage values ​​on the IV characteristic diagram of FIG. 2. Next, the ECU 10 calculates a regression line showing the relationship between the plurality of current values ​​and the plurality of voltage values ​​by regression analysis using the least squares method. The ECU 10 calculates the slope of the calculated regression line as the internal resistance value of the battery 8.

[0018] The effect of the variance value of a plurality of current values ​​on the calculation accuracy of the internal resistance value will be described. FIG. 3A and FIG. 3B are explanatory diagrams of the effect of the variance value on the calculation accuracy of the internal resistance value. The variance value of the current value in FIG. 3A is larger than the variance value of the current value in FIG. 3B. In FIG. 3A, the plurality of current values ​​are widely dispersed from charging to discharging, compared with FIG. 3B. When the variance value is small as in FIG. 3B, for example, when a current value that is significantly different from other current values ​​exists, the effect on the slope of the regression line due to that current value is large. Therefore, the calculation accuracy of the internal resistance value may be reduced. When the variance value is large as in FIG. 3A, even if a current value that is significantly different from other current values ​​exists, the effect on the slope of the regression line due to that current value is small. Therefore, the calculation accuracy of the internal resistance value can be ensured. In this way, a large variance value is preferable.

[0019] The effect of the fluctuation of the charging rate of the battery 8 on the calculation accuracy of the internal resistance value will be described. FIG. 4A and FIG. 4B are explanatory diagrams of the effect of the fluctuation of the charging rate on the calculation accuracy of the internal resistance value. In FIG. 4A, the multiple current values ​​are biased toward the discharge side. This indicates that the charging rate is greatly reduced. If the current value is biased toward the discharge side, the effect of the current value on the slope of the regression line is too large, and the calculation accuracy of the internal resistance value may be reduced. In FIG. 4B, the multiple current values ​​are biased toward the charge side. This indicates that the charging rate is greatly increased. If the current value is biased toward the charge side, the effect of the current value on the slope of the regression line is too small, and the calculation accuracy of the internal resistance value may be reduced. Therefore, it is preferable that the multiple current values ​​are not biased toward the charge side or the discharge side. In other words, it is preferable that the amount of fluctuation of the charging rate is small. In this embodiment, in order to ensure the calculation accuracy of the internal resistance value and the accuracy of the abnormality diagnosis, the ECU 10 executes the abnormality diagnosis control in consideration of the variance value of the current value and the amount of fluctuation of the charging rate as follows.

[0020] [Abnormality diagnosis control] FIG. 5 is a flowchart illustrating the abnormality diagnosis control. This control is repeatedly executed while the ignition is on. As described above, the ECU 10 acquires a plurality of current values ​​and a plurality of voltage values ​​of the battery 8 within a predetermined period (step S1). In detail, the ECU 10 acquires the current value and the voltage value at each predetermined sampling interval, and acquires a total of n current values ​​and n voltage values ​​within the predetermined period. Step S1 is an example of a process executed by the acquisition unit.

[0021] Next, the ECU 10 calculates a variance value of the n current values ​​acquired within a predetermined period (step S2). Specifically, the ECU 10 calculates the variance value based on the following formula (1). TIFF2025072026000002.tif1868σ 2 is the variance value. n is the total number of current values ​​acquired within the above-mentioned predetermined period. A k is the k-th current value acquired within a predetermined period. μ is the average value of n current values ​​acquired within a predetermined period. Step S2 is an example of a process executed by the calculation unit.

[0022] Next, ECU 10 calculates the amount of variation in the charging rate of battery 8 within a predetermined period (step S3). The amount of variation in the charging rate is the difference between the maximum and minimum charging rates within the predetermined period. The amount of variation in the charging rate within the predetermined period is calculated as follows. Based on the current value acquired at each predetermined sampling interval, the amount of minute variation in the charging rate at each sampling interval is calculated. The amount of minute variation is calculated by integrating the current value over time. Next, the amount of minute variation within the predetermined period is sequentially accumulated. The current value used to calculate the amount of minute variation is a positive value during charging and a negative value during discharging.

[0023] For example, assuming that the capacity of the battery 8 is 1 [Ah], the integrated current value when the battery 8 is charged at a current value of 36 [A] for one second is +0.01 [Ah]. The amount of minute fluctuation in this case is +1 [%]. The integrated current value when the battery 8 is discharged at a current value of 36 [A] for one second is -0.01 [Ah]. The amount of minute fluctuation in this case is -10 [%]. By accumulating the amounts of minute fluctuation calculated sequentially within a predetermined period, the amount of fluctuation in the charging rate from the charging rate at the start of the predetermined period is calculated at any time.

[0024] Based on the amount of variation in the charging rate calculated in this way, the maximum and minimum values ​​of the charging rate within a predetermined period are specified. Next, the amount of variation is calculated by subtracting the minimum value from the maximum value. Step S3 is an example of a process executed by the calculation unit.

[0025] Next, the ECU 10 calculates the internal resistance value of the battery 8 based on the n current values ​​and the n voltage values ​​as described above (step S4). Step S4 is an example of a process executed by the calculation unit.

[0026] Next, the ECU 10 determines whether the variance value is equal to or greater than a predetermined value D (step S5). If the answer is Yes in step S5, the ECU 10 determines whether the amount of fluctuation is equal to or less than a first threshold value E1 (step S6). If the answer is No in step S6, this control ends. If the answer is Yes in step S6, the ECU 10 executes an abnormality diagnosis process for the battery 8 based on the calculated internal resistance value (step S8). In the abnormality diagnosis process, if the internal resistance value is within the normal range, the battery 8 is diagnosed as normal, and if the internal resistance value is outside the normal range, the battery 8 is diagnosed as abnormal.

[0027] If the answer is No in step S5, the ECU 10 determines whether the amount of fluctuation is equal to or less than a second threshold E2 (step S7). The second threshold E2 is a value smaller than the first threshold E1. If the answer is No in step S7, this control ends. If the answer is Yes in step S7, the ECU 10 executes an abnormality diagnosis process for the battery 8 based on the calculated internal resistance value (step S8). Step S8 is an example of a process executed by the diagnosis unit.

[0028] In this way, when the variance value is less than the predetermined value D, the abnormality diagnosis process is executed on the condition that the amount of variation is equal to or less than the second threshold E2, which is smaller than the first threshold E1. The decrease in the calculation accuracy of the internal resistance value due to a low variance value can be suppressed by setting the amount of variation to equal to or less than the second threshold E2. This ensures the accuracy of the abnormality diagnosis. Furthermore, there is no need to increase the power consumption of the auxiliary equipment in order to ensure the variance value. Therefore, the decrease in the charging rate of the battery 8 can be suppressed, and the impact on the traveling of the vehicle 1, for example, a decrease in the traveling distance, can be suppressed.

[0029] FIG. 6 is an explanatory diagram of the calculation of the variance value, the fluctuation amount, and the internal resistance value for each predetermined period. For example, the period from time t1 to t2, the period from time t2 to t3, and the period from time t3 to t4 each correspond to the above-mentioned predetermined period T. If the variance value in the period from time t1 to t2 is equal to or greater than the predetermined value D and the fluctuation amount is equal to or less than the first threshold value E1, the calculation accuracy of the internal resistance value in this period is deemed good, and the abnormality diagnosis process is performed based on this internal resistance value. If the variance value in the period from time t2 to t3 is less than the predetermined value D and the fluctuation amount is greater than the second threshold value E2, the calculation accuracy of the internal resistance value in this period is deemed poor, and the abnormality diagnosis process is not performed based on this internal resistance value. If the variance value in the period from time t3 to t4 is less than the predetermined value D and the fluctuation amount is equal to or less than the second threshold value E2, the calculation accuracy of the internal resistance value in this period is deemed good, and the abnormality diagnosis process is performed based on this internal resistance value.

[0030] In this way, the variance value, the fluctuation amount, and the internal resistance value are calculated every predetermined period. Also, the internal resistance value calculated based on the multiple current values ​​and multiple voltage values ​​acquired when the variance value and the fluctuation amount satisfy the above-mentioned conditions is used in the abnormality diagnosis process. For example, compared to the case where only the variance value and the fluctuation amount are calculated and the internal resistance value is calculated only when the variance value and the fluctuation amount satisfy the above-mentioned conditions, the control is prevented from becoming complicated.

[0031] In the above embodiment, the vehicle 1 is an electric vehicle, but the present invention is not limited thereto. For example, the vehicle may be a hybrid vehicle equipped with an engine and a motor as a driving power source. In the case of a hybrid vehicle, the decrease in the charging rate of the battery caused by the increase in the power consumption of the auxiliary equipment can be suppressed, and the influence on the running of the vehicle, for example, the deterioration of fuel efficiency, can be suppressed.

[0032] Although the embodiments of the present invention have been described in detail above, the present invention is not limited to such specific embodiments, and various modifications and variations are possible within the scope of the gist of the present invention described in the claims. [Explanation of symbols]

[0033] 1 vehicle 8 Battery 10 ECU (battery abnormality diagnosis device, acquisition unit, calculation unit, diagnosis unit)

Claims

1. an acquisition unit that acquires a plurality of current values ​​and a plurality of voltage values ​​within a predetermined period of a battery that receives and transmits electric power to and from a motor that is a driving power source of the vehicle; a calculation unit that calculates an internal resistance value of the battery based on a variance value of the plurality of current values ​​within the predetermined period, a fluctuation amount of a charging rate of the battery within the predetermined period, and the plurality of current values ​​and the plurality of voltage values ​​within the predetermined period; a diagnosis unit that executes an abnormality diagnosis process for the battery based on the internal resistance value, The diagnosis unit executes the abnormality diagnosis process based on the internal resistance value calculated when the variance value is greater than or equal to a predetermined value and the fluctuation amount is less than or equal to a first threshold value, or when the variance value is less than the predetermined value and the fluctuation amount is less than or equal to a second threshold value that is smaller than the first threshold value.

2. The battery abnormality diagnosis device according to claim 1 , wherein the calculation unit calculates the variance value, the fluctuation amount, and the internal resistance value for each of the predetermined periods.

3. 3. The battery abnormality diagnosis device according to claim 1, wherein the calculation unit calculates, as the amount of fluctuation, a difference between a maximum value and a minimum value of the charging rate within the predetermined period.

4. The battery abnormality diagnosis device according to claim 1 , wherein the calculation unit calculates the amount of variation based on an integrated value of the plurality of current values ​​within the predetermined period.

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