CN108614216B - Battery health state estimation device and method - Google Patents

Abstract

A battery health status estimation device includes: a control module, which outputs a control signal when a battery module is charging and the charging state reaches a preset target value, so that the current of the battery module changes to a preset current value and maintains it for a preset test time; a correction module, which, when receiving the control signal, obtains the temperature of the battery module during the preset test time and obtains a voltage correction value accordingly; and an estimation processing unit, which, when receiving the control signal, obtains a voltage change and a current change of the battery module during the preset test time, corrects the voltage change according to the voltage correction value to obtain a voltage change correction value, and estimates a health status based on the voltage change correction value, the current change and a rated full charge capacity.

Description

Battery state of health estimation device and method

technical field

The present invention relates to an estimation device and method, and in particular to a battery state of health estimation device and method.

Background technique

In recent years, with the rising awareness of environmental protection and energy saving, the related technologies of electric vehicles equipped with rechargeable battery modules have developed vigorously. Therefore, how to detect the health status of rechargeable battery modules in electric vehicles has become a research and development focus. . At present, the methods of estimating the state of health of the rechargeable battery module by the existing battery state of health estimating device can be roughly divided into a full charge-discharge method and an internal resistance method.

However, the full charge-discharge method needs to fully charge the rechargeable battery module first, and then discharge the rechargeable battery module with a specific current. state of charge and state of health, and random discharge of rechargeable battery modules may cause safety issues. The internal resistance method needs to provide an input voltage to the rechargeable battery module, and measure and calculate the input voltage through the existing battery state of health estimating device, and use a special high voltage in the existing battery state of health estimating device. Only by measuring the internal resistance of the rechargeable battery module with a frequency measuring instrument (the instrument is relatively expensive), the state of health of the rechargeable battery module can be estimated, which leads to the high cost of the existing battery state of health estimating device. In addition, if the current battery state of health estimating device uses the full charge-discharge method or the internal resistance method, the rechargeable battery module must be disassembled to estimate the state of health, which is extremely inconvenient to the user.

SUMMARY OF THE INVENTION

The first objective of the present invention is to provide a battery state of health estimation device that can overcome the shortcomings of the prior art.

The battery health state estimation device of the present invention is suitable for estimating a health state of a battery module, and the battery health state estimation device includes a control module, a calibration module and an estimation processing unit.

The control module outputs a control signal when the battery module is being charged and a charging state of the battery module reaches a preset target value, so that a current of the battery module is changed to a preset current value and Maintaining a predetermined test time, causing a voltage of the battery module to drop during the predetermined test time.

The calibration module is electrically connected to the control module to receive the control signal. When receiving the control signal, the calibration module obtains a temperature of the battery module during the preset test period, and obtains the temperature according to the temperature. A voltage correction value.

The estimation processing unit is electrically connected to the calibration module and the control module to receive the voltage calibration value and the control signal respectively. When receiving the control signal, the estimation processing unit obtains the battery module in the preset test of the segment A voltage change amount and a current change amount in time, and the error of the voltage change amount due to the influence of the temperature is corrected according to the voltage correction value, so as to obtain a voltage change correction value, and according to the voltage change correction value, The current variation and a rated full charge capacity of the battery module are used to estimate the state of health of the battery module.

In the battery state of health estimation device of the present invention, the calibration module obtains the voltage calibration value according to the following equation: V _C =a×(T ₁ -T ₀ ) ² -b×(T ₁ -T ₀ )+c, V _C represents the voltage correction value, a, b, and c each represent a predetermined constant, T ₁ represents the temperature, and T ₀ represents a predetermined temperature.

In the battery state of health estimation device of the present invention, the calibration module obtains the voltage calibration value according to the following equation: V _C =-d×(T ₁ -T ₀ )+e, V _C represents the voltage calibration value, d, e each represents a preset constant, T ₁ represents the temperature, and T ₀ represents a preset temperature.

In the battery state of health estimation device of the present invention, the current variation is the current difference between the preset current value of the battery module and the current immediately before the change, and the voltage variation is the battery module at the predetermined current value. Set a voltage difference between a voltage at a starting point of the test time and a voltage at an end point of the preset test time.

In the battery state of health estimation device of the present invention, the estimation processing unit includes: a processing module electrically connected to the calibration module and the control module to receive the voltage calibration value and the control signal respectively, when the control signal is received When , the processing module obtains the voltage variation and the current variation, corrects the voltage variation according to the voltage correction value to obtain the voltage variation correction value, and obtains one of the battery modules according to the voltage variation correction value a current ratio; and an estimation module electrically connected to the processing module to receive the current variation and the current ratio, and estimate the state of health according to the current ratio, the current variation and the rated full charge capacity.

In the battery state of health estimation device of the present invention, the processing module adds the voltage correction value and the voltage change amount to obtain the voltage change correction value, and obtains the voltage change correction value according to a description of the relationship between the current ratio and the voltage change correction value The predetermined voltage mapping function maps the voltage variation correction value to the current ratio.

In the battery state of health estimation device of the present invention, the estimation module estimates the state of health according to the following equation: SOH=[(ΔI/CR)/AH_spec]×100%×K ⁻¹ , SOH represents the state of health, and ΔI represents the state of health The current variation, CR represents the current ratio, AH_spec represents the rated full charge capacity, and K ^-1 represents a preset offset constant.

The battery health state estimation device of the present invention further comprises: a sensing module, electrically connected to the battery module, the control module, the calibration module and the estimation processing unit, and periodically senses the battery module A voltage, a current, a state of charge and a temperature of the battery module to generate a sensing signal indicating the voltage, the current, the state of charge and the temperature of the battery module, the sensing module The sensing signal output to the control module, the calibration module and the estimation processing unit, the calibration module obtains the temperature of the battery module in the preset test time according to the sensing signal, and the estimation processing unit according to the The sensing signal obtains the voltage variation and the current variation of the battery module during the preset test period.

The second object of the present invention is to provide a battery state of health estimation method that can overcome the shortcomings of the prior art.

The battery state of health estimation method of the present invention is suitable for estimating a state of health of a battery module, and is executed by a battery state of health estimation device. The battery state of health estimation method includes the following steps:

(A) Using the battery state of health estimating device to determine whether the state of charge of the battery module has reached a preset level according to a sensing signal indicating a temperature, a current, a voltage and a state of charge of the battery module target value;

(B) when the determination result of step (A) is yes, use the battery state of health estimating device to output a control signal, so that the current of the battery module is changed to a preset current value and maintained for a preset test time, cause the voltage to drop within the preset test time;

(C) using the battery state of health estimating device to obtain a voltage variation and a current variation of the battery module during the preset test period according to the sensing signal;

(D) using the battery state of health estimating device to obtain a voltage correction value according to the temperature of the battery module during the predetermined test period indicated by the sensing signal; and

(E) Using the battery state of health estimating device to correct the error of the voltage variation due to the influence of the temperature according to the voltage correction value, so as to obtain a voltage variation correction value, and according to the voltage variation correction value, the current variation and a rated full charge capacity of the battery module to estimate the state of health of the battery module.

In the battery state of health estimation method of the present invention, in step (D), the battery state of health estimation device obtains the voltage correction value according to the following equation: V _C =a×(T ₁ -T ₀ ) ² -b× (T ₁ -T ₀ )+c, _VC represents the voltage correction value, a, b, c each represent a predetermined constant, T ₁ represents the temperature, and T ₀ represents a predetermined temperature.

In the battery state of health estimation method of the present invention, in step (D), the battery state of health estimation device obtains the voltage correction value according to the following equation: V _C =-d×(T ₁ -T ₀ )+e, V _C represents the voltage correction value, d and e each represent a predetermined constant, T ₁ represents the temperature, and T ₀ represents a predetermined temperature.

In the battery state of health estimation method of the present invention, step (E) includes the following sub-steps: (E1) using the battery state of health estimation device to add the voltage correction value and the voltage change amount to obtain the voltage change correction value, and mapping the voltage variation correction value into a current ratio according to a predetermined voltage mapping function; and (E2) using the battery state of health estimating device to estimate the current ratio, the current variation and the rated full charge capacity health status.

In the battery state of health estimation method of the present invention, in sub-step (E2), the battery state of health estimation device estimates the state of health according to the following equation: SOH=[(ΔI/CR)/AH_spec]×100%×K ^-1 , SOH represents the state of health, ΔI represents the current variation, CR represents the current ratio, AH_spec represents the rated full charge capacity, and K ^-1 represents a preset offset constant.

The beneficial effect of the present invention is that: the control module starts the change of the current of the battery module when the battery module is being charged, and does not need to spend a lot of time to discharge the battery module, which can prevent the random Safety problems that may be caused by the discharge of the battery module, and after correcting the error of the voltage variation due to the influence of different temperatures by using the calibration module, the accuracy of the state of health estimated by the estimation processing unit can be improved. Effective promotion.

Description of drawings

FIG. 1 is a block diagram illustrating an embodiment of the battery state of health estimating device of the present invention for use with a battery module;

FIG. 2 is a timing diagram illustrating the voltage and current of the battery module;

FIG. 3 and FIG. 4 are a flowchart illustrating that the battery state of health estimating apparatus of the embodiment executes a battery state of health estimating method to estimate a state of health of the battery module;

FIG. 5 is a measurement graph illustrating the variation of the state-of-health error rate on cycle life with the implementation of the battery state-of-health estimation method of the embodiment; and FIG.

FIG. 6 is a measurement graph illustrating the variation of state-of-health error rate versus cycle life for this embodiment without implementing the battery state-of-health estimation method.

Detailed ways

Referring to FIG. 1 and FIG. 2 , the embodiment of the battery state of health estimating device 1 of the present invention is suitable for being installed in a carrier 2 . The carrier 2 includes a charging module 21 , a battery module 22 , a display module 23 and other necessary components (not shown). The battery module 22 is electrically connected to the charging module 21 . The charging module 21 is used to receive an AC power source, convert the AC power source into a DC power source, and provide the battery module 22 to charge the battery module 22 . The charging module 21 is operable to adjust the amount of DC power supplied to the battery module 22 to vary the current flowing through the battery module 22 . It should be noted that the vehicle 2 may be a pure electric vehicle or a hybrid electric vehicle, and may be in the form of, for example, a locomotive, a car or a bus.

The battery state of health estimation apparatus 1 of this embodiment is suitable for estimating a state of health (SOH) of the battery module 22 . It should be noted that the state of health is the quality factor of the state of the battery module 22 compared to its ideal state, and the unit of the state of health is a percentage (100%=the state of the battery module 22 matches the battery specification). Typically, the state of health due to the battery module 22 is ideally 100% as manufactured, and declines with time and use. In this embodiment, the battery state of health estimation device 1 includes a control module 11 , a calibration module 12 , an estimation processing unit 13 and a sensing module 14 .

The sensing module 14 is electrically connected to the battery module 22, and periodically (eg, continuously) senses a voltage, a current, a state of charge (SOC) and a temperature of the battery module 22, to generate a sensing signal indicating the voltage, the current, the state of charge and the temperature of the battery module.

The control module 11 is suitable for electrically connecting the charging module 21 and the sensing module 14 and receiving the sensing signal from the sensing module 14 . The control module 11 determines that the battery module 22 is being charged and the charging state of the battery module 22 reaches a preset value according to the current and the charging state of the battery module 22 indicated by the sensing signal. When the target value is reached, a control signal is output to the charging module 21 so that the charging module 21 changes the current flowing through the battery module 22 to a predetermined current value It and maintains a predetermined test time Tt. Changing the current flowing through the battery module 22 to the preset current value It makes the current of the battery module 22 change and causes the voltage of the battery module 22 to drop during the preset test time Tt. It should be noted that the preset target value is preferably in a range from 70% to 80%, and in this embodiment, it is 70%. In addition, for different examples of the control signal, the preset current value It may be the same or different. For the preset current value It, the preset current value It may be zero, so that the battery module 22 is neither in charging nor discharging, that is, the battery module 22 is not in use. Alternatively, the preset current value It can keep the battery module 22 in charging, or can keep the battery module 22 in discharging.

The calibration module 12 is electrically connected to the control module 11 to receive the control signal, and is adapted to be electrically connected to the sensing module 14 to receive the sensing signal. When receiving the control signal, the calibration module 12 obtains the temperature of the battery module 22 during the preset test period according to the temperature of the battery module 22 indicated by the sensing signal, and according to the temperature Get a voltage correction value. It should be noted that the temperature change of the battery module 22 during the preset test time Tt is very small, so the temperature of the battery module 22 is sensed at any point in the preset test time Tt. Temperature can be used to derive this voltage correction value.

In this embodiment, the calibration module 12 obtains the voltage calibration value according to the following equation (1):

V _C =a×(T ₁ -T ₀ ) ² -b×(T ₁ -T ₀ )+c Equation (1),

V _C represents the voltage correction value, a, b, c each represent a preset constant, T ₁ represents the temperature of the battery module 22 during the preset test time, and T ₀ represents a preset temperature, the preset temperature Let the temperature T ₀ be related to the preset temperature when the following equation (3) is established, for example, 25 degrees. The preset constants a, b, and c are different depending on the state of charge of the battery module 22 . For example, when the state of charge is equal to 70%, the preset constant a is equal to 2×10 ⁻⁵ , the preset constant b is equal to 0.0022, and the preset constant c is equal to 0.0825, so V _C =2×10 ⁻⁵ ×(T ₁ -T ₀ ) ² -0.0022×(T ₁ -T ₀ )+0.0825. When the state of charge is equal to 80%, the preset constant a is equal to 3×10 ⁻⁵ , the preset constant b is equal to 0.0024, and the preset constant c is equal to 0.0881, so V _C =3×10 ⁻⁵ ×(T ₁ −T ₀ ) ² -0.0024×(T ₁ -T ₀ )+0.0881.

It should be noted that, in other embodiments, equation (1) of the present invention can be replaced by equation (2) to obtain the voltage correction value, but the voltage correction value obtained by equation (1) is more accurate . In this case, equation (2) is as follows:

V _C =-d×(T ₁ -T ₀ )+e equation (2),

The definitions of V _C , T ₁ , and T ₀ are the same as those of equation (1), and d and e each represent a preset constant. When the state of charge is equal to 70% or 80%, the preset constant d is equal to 0.0008, and the preset constant e varies depending on the state of charge of the battery module 22 . For example, when the state of charge is equal to 70%, the default constant e is equal to 0.0629, so V _C =-0.0008×(T ₁ −T ₀ )+0.0629. When the state of charge is equal to 80%, the preset constant e is equal to 0.0667, so V _C =-0.0008×(T ₁ −T ₀ )+0.0667.

The estimation processing unit 13 is electrically connected to the calibration module 12 and the control module 11 to receive the voltage correction value V _C and the control signal respectively, and is adapted to be electrically connected to the sensing module 14 to receive the sensing signal. In this embodiment, the estimation processing unit 13 includes a processing module 131 and an estimation module 132 .

The processing module 131 is electrically connected to the calibration module 12 and the control module 11 to receive the voltage correction value V _C and the control signal respectively, and is adapted to be electrically connected to the sensing module 14 to receive the sensing signal. When receiving the control signal, the processing module 131 performs the following actions: (1) According to the voltage of the battery module 22 indicated by the sensing signal, obtain the preset test time of the battery module 22 in the segment A voltage variation ΔV in the a current variation ΔI; (3) correcting the error of the voltage variation ΔV due to the influence of the temperature T1 according to the voltage correction value _VC to obtain a voltage variation correction value ΔV'; and (4) according to a description A preset voltage mapping function of the relationship between a current ratio (C rate) of the battery module 22 and the voltage variation correction value ΔV', mapping the voltage variation correction value ΔV' of the battery module 22 to the battery module This current ratio for group 22. It should be noted that the voltage variation ΔV is the voltage difference between the voltage V1 of the battery module 22 at a starting point t1 of the preset test time Tt and the voltage V2 at an end point t2 of the preset test time Tt (ie, , V1-V2). The current variation ΔI is the current of the battery module 22 between the preset current value It and the current immediately before the change (ie, the current corresponding to the current immediately before the starting point t1 of the preset test time Tt). difference. The current ratio is used to represent the ratio of the magnitude of the current when the battery module 22 is charged and discharged.

In this embodiment, the processing module 131 adds the voltage correction value _VC and the voltage variation ΔV to obtain the voltage variation correction value ΔV' (ie, ΔV'= _VC +ΔV). The predetermined voltage mapping function is expressed as, for example, CR=a'×ΔV'+b', CR represents the current ratio of the battery module 22 , and a' and b' are predetermined constants. The predetermined voltage mapping function can be derived from measurement results associated with the battery module 22 .

The estimation module 132 is electrically connected to the processing module 131 to receive the current variation ΔI and the current ratio CR, and is adapted to be electrically connected to the sensing module 14 to receive the sensing signal, and adapted to be electrically connected to the display Module 23. The estimation module 132 estimates the state of health of the battery module 22 according to the current ratio CR, the current change amount ΔI and a rated full charge capacity relative to the voltage change correction value ΔV', and outputs the state of health to the display module 23 to be displayed on the display module 23 .

In this embodiment, the estimation module 132 estimates the state of health of the battery module 22 according to the following equation (3):

SOH=[(ΔI/CR)/AH_spec]×100%×K ^-1 Equation (3),

SOH represents the state of health of the battery module 22 , AH_spec represents the rated full charge capacity of the battery module 22 , and K ⁻¹ represents a preset offset constant. The rated full charge capacity of the battery module 22 can be known from the specification of the battery module 22 .

Referring to FIG. 3 and FIG. 4 , it is illustrated that the battery state of health estimation apparatus 1 executes a battery state of health estimation method to estimate the state of health of the battery module 22 . During operation, the sensing module 14 is used to sense the temperature, current, voltage and charging state of the battery module 22 to generate the sensing signal (ie, step 30 ). Next, the battery state of health estimation apparatus 1 executes the battery state of health estimation method to estimate the state of health of the battery module 22 . Finally, the health status is displayed using the display module 23 (ie, step 36). In this embodiment, the battery state of health estimation method includes the following steps:

Step 31 : Use the control module 11 in the battery state of health estimating device 1 to determine whether the charging state of the battery module 22 reaches the preset target value according to the sensing signal. If yes, go to step 32; if not, go to step 30.

Step 32: Use the control module 11 in the battery state of health estimation device 1 to output the control signal, so that the current of the battery module 22 changes to the preset current value It and maintains the preset test time Tt , and the current of the battery module 22 is changed to the preset current value It, which not only makes the current change but also causes the voltage of the battery module 22 to drop during the preset test time Tt.

Step 33: Using the processing module 131 in the battery state of health estimation device 1 to obtain the voltage variation ΔV and the current variation of the battery module 22 during the preset test time Tt according to the sensing signal ΔI.

Step 34: Using the calibration module 12 in the battery state of health estimating device 1 to obtain the voltage calibration value V _C according to the temperature of the battery module 22 in the preset test time Tt indicated by the sensing signal .

Step 35: Use the estimation processing unit 13 in the battery state of health estimation device 1 to correct the error of the voltage variation ΔV due to the influence of the temperature according to the voltage correction value _VC , so as to obtain the voltage variation correction value ΔV ', and the state of health of the battery module 22 is estimated according to the voltage change correction value ΔV', the current change amount ΔI and the rated full charge capacity of the battery module 22 .

It should be noted that, in step 35, the detailed flow of sub-steps 351 and 352 is further included.

Sub-step 351: Use the processing module 131 in the battery state of health estimating device 1 to add the voltage correction value _VC and the voltage variation ΔV to obtain the voltage variation correction value ΔV', and according to the preset The voltage mapping function maps the voltage variation correction value ΔV' to the current ratio.

Sub-step 352: Use the estimation module 132 in the battery state of health estimation device 1 to estimate the state of health according to the current ratio, the current variation ΔI and the rated full charge capacity.

Referring to FIG. 5 and FIG. 6 , FIG. 5 illustrates the measurement result of the battery state of health estimating device 1 using the calibration module 12 to correct the error of the voltage variation ΔV due to the influence of the temperature, and FIG. 6 illustrates the measurement result without The measurement result after correcting the voltage variation ΔV by the correcting module 12 . The state of health error rate is defined as the state of health (measured value) obtained by actually de-discharging the battery module 22 minus the state of health (theoretical value) obtained by the present invention according to equation (3). The definition of one cycle life means that the battery module 22 is discharged from a fully charged battery to a battery cut-off voltage.

It can be seen from Figure 5 that after correcting the voltage variation ΔV, the maximum value of the error rate of the state of health is 4.23%, and the minimum value of the error rate of the state of health is -0.86%, and the error range of the error rate of the state of health is 5.09% ( That is, 4.23%-(-0.86%)=5.09%). Furthermore, the average error rate is 2.59%. It can be seen from Figure 6 that after the voltage variation ΔV is not corrected, the maximum value of the error rate of the state of health is 6.44%, and the minimum value of the error rate of the state of health is -0.81%, and the error range of the error rate of the state of health is 7.25% ( That is, 6.44%-(-0.81%)=7.25%). Furthermore, the average error rate is 3.66%. That is to say, when the battery state of health estimating device 1 uses the calibration module 12 to correct the voltage variation ΔV, the estimated state of health of the battery module 22 is more accurate, so that the state of health error rate is increased. The error range, the average error rate, and the maximum and minimum values of the state of health error rate are reduced.

To sum up, the above-mentioned present embodiment has the following advantages:

1. Since the battery state of health estimating device 1 of the present invention can estimate the state of health of the battery module 22 when the battery module 22 is being charged, it is not necessary to disassemble the rechargeable battery module as in the prior art The health status can only be estimated after that, so it is convenient for users to use.

2. Since the battery state of health estimation device 1 of the present invention can estimate the state of health of the battery module 22 without spending a lot of time to discharge the battery module 22, it can prevent the battery module 22 from being arbitrarily Safety issues that may arise from discharge.

3. Since the battery state of health estimating device 1 of the present invention activates the charging module 21 to change the current of the battery module 22 when the battery module 22 is being charged, the voltage of the battery module 22 changes accordingly, Then, the voltage variation ΔV of the battery module 22 is calibrated by the calibration module 12 to obtain the state of health of the battery module 22 according to the above equation (3). Therefore, the battery state of health estimation device 1 of the present invention The state of health of the rechargeable battery module can be estimated without using a special high-frequency measuring instrument to measure the internal resistance of the rechargeable battery module as in the existing battery state of health estimating device. Therefore, the battery state of health estimating device 1 of the present invention can reduce the manufacturing cost compared with the existing battery state of health estimating device.

4. Since the battery module 22 has different activities under different temperature conditions, it will cause an error in its own voltage response, so that the voltage variation ΔV obtained by the processing module 131 also has an error, which further affects the estimated value. The accuracy of the state of health of the battery module 22 . Therefore, the battery state of health estimating device 1 of the present invention can correct the error of the voltage variation ΔV caused by the influence of different temperatures by using the calibration module 12, so that the estimated value of the battery module 22 can be adjusted. The accuracy of this health status is effectively improved.

The above are only examples of the present invention, and should not limit the scope of the present invention, that is, any simple equivalent changes and modifications made according to the claims of the present invention and the contents of the description still belong to the present invention. scope of invention.

Claims (13)

1. A battery state of health estimation device is applicable to estimating a state of health of a battery module, and is characterized in that: the battery health state estimation device comprises:

a control module, outputting a control signal when the battery module is in charge and a charge state of the battery module reaches a preset target value, so that a current of the battery module changes to a preset current value and maintains for a preset test time, and a voltage of the battery module is reduced in the preset test time;

the correction module is electrically connected with the control module to receive the control signal, and when the control signal is received, the correction module obtains a temperature of the battery module in the preset test time and obtains a voltage correction value according to the temperature; and

and the estimation processing unit is electrically connected with the correction module and the control module to respectively receive the voltage correction value and the control signal, when the control signal is received, the estimation processing unit obtains a voltage variation and a current variation of the battery module in the preset test time, corrects an error of the voltage variation caused by the influence of the temperature according to the voltage correction value to obtain a voltage variation correction value, and estimates the health state of the battery module according to the voltage variation correction value, the current variation and a rated full charge capacity of the battery module.

2. The battery state of health estimation device of claim 1, wherein: the correction module obtains the voltage correction value according to the following equation:

V_C＝a×(T₁-T₀)²-b×(T₁-T₀)+c，

V_Crepresenting the voltage correction value, a, b, c each representing a predetermined constant, T₁Represents the temperature, and T₀Representing a preset temperature.

3. The battery state of health estimation device of claim 1, wherein: the correction module obtains the voltage correction value according to the following equation:

V_C＝-d×(T₁-T₀)+e，

V_Crepresenting the voltage correction value, d, e each representing a predetermined constant, T₁Represents the temperature, and T₀Representing a preset temperature.

4. The battery state of health estimation device of claim 1, wherein: the current variation is a current difference between the preset current value and the current immediately before the change, and the voltage variation is a voltage difference between a voltage of the battery module at a starting point of the preset test time and a voltage at an end point of the preset test time.

5. The battery state of health estimation device of claim 1, wherein: the estimation processing unit includes:

the processing module is electrically connected with the correction module and the control module to respectively receive the voltage correction value and the control signal, and when the control signal is received, the processing module obtains the voltage variation and the current variation, corrects the voltage variation according to the voltage correction value to obtain the voltage variation correction value, and obtains a current ratio of the battery module according to the voltage variation correction value; and

and the estimation module is electrically connected with the processing module to receive the current variation and the current ratio and estimate the health state according to the current ratio, the current variation and the rated full charge capacity.

6. The battery state of health estimation device of claim 5, wherein: the processing module adds the voltage correction value and the voltage variation to obtain the voltage variation correction value, and maps the voltage variation correction value to the current ratio according to a preset voltage mapping function describing the relationship between the current ratio and the voltage variation correction value.

7. The battery state of health estimation device of claim 5, wherein: the estimation module estimates the health state according to the following equation:

SOH＝[(ΔI/CR)/AH_spec]×100％×K^-1，

SOH represents the state of health, Δ I represents the amount of change in the current, CR represents the current ratio, AH _ spec represents the rated full charge capacity, and K^-1Representing a predetermined offset constant.

8. The battery state of health estimation device of claim 1, wherein: the battery health state estimation device further comprises:

the sensing module is electrically connected with the battery module, the control module, the correction module and the estimation processing unit and is used for periodically sensing a voltage, a current, a charging state and a temperature of the battery module so as to generate a sensing signal indicating the voltage, the current, the charging state and the temperature of the battery module, the sensing module outputs the sensing signal to the control module, the correction module and the estimation processing unit, the correction module obtains the temperature of the battery module in the preset testing time according to the sensing signal, and the estimation processing unit obtains the voltage variation and the current variation of the battery module in the preset testing time according to the sensing signal.

9. A battery health state estimation method is suitable for estimating a health state of a battery module and is executed by a battery health state estimation device, and is characterized in that: the battery health state estimation method comprises the following steps:

(A) judging whether the charging state of the battery module reaches a preset target value or not by using the battery health state estimation device according to a sensing signal indicating the temperature, the current, the voltage and the charging state of the battery module;

(B) if the judgment result in the step (A) is yes, outputting a control signal by using the battery health state estimation device, so that the current of the battery module is changed to a preset current value and is maintained for a preset test time, and the voltage is reduced in the preset test time;

(C) obtaining a voltage variation and a current variation of the battery module in the preset testing time by using the battery health state estimation device according to the sensing signal;

(D) obtaining a voltage correction value by using the battery health state estimation device according to the temperature of the battery module in the preset test time indicated by the sensing signal; and

(E) and correcting the error of the voltage variation caused by the temperature influence by using the battery health state estimation device according to the voltage correction value to obtain a voltage variation correction value, and estimating the health state of the battery module according to the voltage variation correction value, the current variation and a rated full charge capacity of the battery module.

10. The battery state of health estimation method of claim 9, wherein: in step (D), the battery state of health estimation device obtains the voltage correction value according to the following equation:

V_C＝a×(T₁-T₀)²-b×(T₁-T₀)+c，

V_Crepresenting the voltage correction value, a, b, c each representing a predetermined constant, T₁Represents the temperature, and T₀Representing a preset temperature.

11. The battery state of health estimation method of claim 9, wherein: in step (D), the battery state of health estimation device obtains the voltage correction value according to the following equation:

V_C＝-d×(T₁-T₀)+e，

V_Crepresenting the voltage correction value, d, e each representing a predetermined constant, T₁Represents the temperature, and T₀Representing a preset temperature.

12. The battery state of health estimation method of claim 9, wherein: step (E) comprises the sub-steps of:

(E1) adding the voltage correction value and the voltage variation by using the battery health state estimation device to obtain the voltage variation correction value, and mapping the voltage variation correction value into a current ratio according to a preset voltage mapping function; and

(E2) and estimating the state of health by using the battery state of health estimation device according to the current ratio, the current variation and the rated full charge capacity.

13. The battery state of health estimation method of claim 12, wherein: in sub-step (E2), the battery state of health estimation device estimates the state of health according to the following equation:

SOH＝[(ΔI/CR)/AH_spec]×100％×K^-1，

SOH represents the state of health, Δ I represents the amount of change in the current, CR represents the current ratio, AH _ spec represents the rated full charge capacity, and K^-1Representing a predetermined offset constant.

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