Method and device for estimating an internal resistance of a battery cell

Description

[0001] Method and device for estimating an internal resistance of a battery cell The invention relates to a method and a device for estimating an internal resistance of a battery cell.

[0002] Battery cells age over time, which has a negative impact on their properties. This ageing is particularly evident in an increase in internal resistance and a decrease in the battery cell's electrical capacity. Battery cell aging can be monitored by tracking the internal resistance. However, the internal resistance cannot be measured directly; it can only be estimated using a voltage across the battery cell and a current flowing through the battery cell. Various influences can complicate such an estimation: measurement noise, an inequality in internal resistance during charging and discharging, the RC element-like behavior of the battery cell, and the fact that an equivalent circuit model commonly used in modeling cannot perfectly represent the electrochemical processes in the battery cell.

[0003] CN111 426 968 A discloses a method for estimating the internal resistance of a battery cell using voltage differentials. JP 2008 164417 A discloses the use of differentiating filters in conjunction with determining the internal resistance of a battery.

[0004] The invention is based on the object of providing a method and a device for estimating an internal resistance of a battery cell, with which the internal resistance of the battery cell can be reliably estimated.

[0005] The object is achieved according to the invention by a method having the features of patent claim 1 and a device having the features of patent claim 7. Advantageous embodiments of the invention emerge from the subclaims.In particular, a method for estimating an internal resistance of a battery cell is provided, comprising the following measures: detecting a voltage at the battery cell, detecting a current at the battery cell, determining a detected voltage differential by differentiating the detected voltage using a filter, determining a modeled voltage differential from the detected current and a current internal resistance estimate by differentiating using a filter, determining a correction factor from the detected voltage differential and the modeled voltage differential, and estimating a new current internal resistance estimate from the determined correction factor and the previous current internal resistance estimate, providing the new current internal resistance estimate as the estimated internal resistance of the battery cell.

[0006] Furthermore, in particular, a device for estimating an internal resistance of a battery cell is provided, comprising interfaces configured to receive a voltage detected at the battery cell and a current detected at the battery cell, and a control device, wherein the control device is configured to determine a detected voltage differential by differentiating the detected voltage using a filter, to determine a modeled voltage differential from the detected current and a current internal resistance estimate by differentiating using a filter, to determine a correction factor from the detected voltage differential and the modeled voltage differential, and to estimate a new current internal resistance estimate from the determined correction factor and the previous current internal resistance estimate.and provide the new current internal resistance estimate as the estimated internal resistance of the battery cell.

[0007] The method and the device make it possible to learn the internal resistance of a battery cell, in particular starting from a reference value. The learning takes place in particular on the basis of a differentially determined internal resistance, i.e. the internal resistance is determined in particular as a differential internal resistance. The reference value initially corresponds in particular to the nominal internal resistance of the battery cell. The reference value is set in particular as the first current internal resistance estimate and is then updated to a new current internal resistance estimate with each current iteration by the measures of the method. The updating is carried out as follows: A modeled voltage is estimated from the recorded current and the current internal resistance estimate. Differentials are formed from the recorded voltage and the modeled voltage by means of (differentiating) filters by differentiating.The underlying idea is that internal resistance can be determined and learned particularly well when the voltage (or current) changes. A correction factor is determined from the ratio of the differentials. A new current internal resistance estimate is then calculated from the determined correction factor and the (previous) current internal resistance estimate. The new current internal resistance estimate is provided as an estimated internal resistance of the battery cell, preferably in the form of an analog or digital signal.

[0008] The advantage The advantage of the method and device is that the internal resistance of the battery cell can be reliably determined. The use of differentiating filters allows both the differentials to be determined and measurement noise to be reduced.

[0009] The method is carried out repeatedly in particular in order to continuously obtain a current internal resistance estimate and in this way to be able to track the ageing of the battery cell via the estimated internal resistance.

[0010] The voltage and current are measured, in particular, by means of sensors designed for this purpose. The sensors can also be part of the device.

[0011] Parts of the device, in particular the control unit, can be implemented individually or collectively as a combination of hardware and software, for example, as program code executed on a microcontroller or microprocessor. However, it can also be provided that parts are implemented individually or collectively as an application-specific integrated circuit (ASIC) or field-programmable gate array (FPGA).

[0012] Part of the procedure is explained below using formulas. It is assumed that a change in current or load leads to a change in the measured voltage, which is proportional to the internal resistance. R 0 of the battery cell. The internal resistance can be calculated using the following equation for the differential resistance R diff be determined: R diff = dU dI

[0013] Here, you the voltage differential and dI is the current differential.

[0014] Using the differentiating filters FILTER (·) are calculated from the measured voltage U and the recorded current I the measured voltage differential and the modeled voltage differential are determined: dU erfasst = FILTER U dU Modell = FILTER I ⋅ R 0

[0015] If a jump in the current occurs, the following must apply: dU erfasst = dU Modell

[0016] A correction factor can then be calculated from a ratio of the voltage differentials α k be determined: dU erfasst dU Modell = R 0 Real dI f k R 0 Referenz dI = α k

[0017] Here, R 0 Referenz in particular the nominal internal resistance of the battery cell, which is taken as a reference value, that is to say, in particular the internal resistance that the battery cell had upon delivery, whereas R 0 Real is the real internal resistance of the battery cell. This real internal resistance is estimated and provided as the current internal resistance estimate using the above equation.

[0018] Under ideal conditions, a new correction factor f for each subsequent iteration by f k + 1 = α k f k be obtained.

[0019] In this way, a current internal resistance estimate can be estimated for each iteration step from the measured voltage and current.

[0020] In one embodiment, the filters are designed as antisymmetric filters with a finite impulse response. These are particularly well suited for achieving both differentiation and noise reduction. Noise reduction is achieved, in particular, through the low-pass behavior of the filter(s). The antisymmetric filter with a finite impulse response is designed, in particular, to differentiate for low frequencies and reduce noise (low-pass behavior).

[0021] In one embodiment, when determining the correction factor, it is estimated using at least one estimation filter. This allows short-term fluctuations to be reduced. In particular, the at least one estimation filter has a smoothing effect over time.

[0022] In a further embodiment, the at least one estimation filter is designed as a Kalman filter. The advantage is that a Kalman filter can provide not only the estimated result but also a measure of the confidence of the estimated result, thus providing additional information about the reliability of the estimated internal resistance of the battery cell.

[0023] In one embodiment, at least one of the voltage differentials is compared with a predefined threshold value, wherein the measures for determining the estimated internal resistance are triggered when a value of one of the voltage differentials reaches or exceeds the predefined threshold value. This has the advantage that the measures for determining the new current internal resistance are carried out (only) when ideal conditions prevail for learning the internal resistance of the battery cell, i.e., when there is a large voltage and / or current change that leads to a good signal-to-noise ratio. A suitable threshold value can be determined, for example, empirically and / or by simulation.

[0024] In one embodiment, it is provided that a power flow direction is differentiated, wherein for this purpose a current direction is determined and, depending on the determined current direction, an estimated internal charging resistance and / or an estimated internal discharging resistance is determined and these are provided as internal resistances of the battery cell that are dependent on the power flow direction. This allows an internal resistance to be determined depending on the power flow. The procedure for both cases is fundamentally analogous to the procedure described above. In particular, however, it is provided that a separate current estimated internal resistance is determined for each power flow direction (charging / discharging). In particular, a direction of power flow is determined, in particular based on a current direction (at a corresponding voltage). This allows the correction factor(s) to be learned even if the current changes sign.For example, if a current jump occurs from -100 A to 50 A at a constant polarity voltage, the first two-thirds of this jump can be assigned to a negative power flow direction (e.g., charging), while the last third can be assigned to a positive power flow direction (e.g., discharging). The first two-thirds of the signal jump are then used to estimate the internal resistance at negative power flow, and the last third to estimate the internal resistance at positive power flow. For example, the individual values ​​of the antisymmetric finite impulse response filter can be evaluated accordingly in a range-wise manner. For this purpose, the antisymmetric finite impulse response filter is positioned temporally, particularly at the center of the signal jump.Since the coefficients in the first part of the antisymmetric filter are negative and the second part is positive (or vice versa), the respective parts can be used to determine a moving average of the current values ​​before and after the signal step with power flow change. Using the moving averages, signal noise can be reduced, thus improving the signal-to-noise ratio.

[0025] Further features of the device design will become apparent from the description of embodiments of the method. The advantages of the device are the same as those of the embodiments of the method.

[0026] Furthermore, a vehicle is also proposed, comprising at least one device according to one of the described embodiments. A vehicle is, in particular, a motor vehicle. In principle, however, a vehicle can also be another land, rail, water, air, or space vehicle. In principle, however, the method and device can also be used in other mobile or stationary devices.

[0027] The invention will be explained in more detail below using preferred embodiments with reference to the figures. Herein: Fig. 1 is a schematic representation of an embodiment of the device for estimating an internal resistance of a battery cell; Fig. 2a is a schematic diagram of the detected current over time; Fig. 2b is a schematic diagram of the modeled voltage differential over time; Fig. 3 is a schematic representation to illustrate an embodiment of the method; Figs. 4a, 4b are schematic diagrams to illustrate the method described in this disclosure; Figs. 5a, 5b are schematic diagrams to illustrate an embodiment of the method.

[0028] In Fig. 1 A schematic representation of an embodiment of the device 1 for estimating an internal resistance 20 of a battery cell is shown. The device 1 is configured to carry out the method described in this disclosure. The method is explained using the device 1.

[0029] The device 1 comprises interfaces 2 configured to receive a voltage 10 detected at the battery cell and a current 11 detected at the battery cell. It can also be a combined interface 2. The voltage 10 is detected by a voltage sensor 50 at the battery cell. The current 11 is detected by a current sensor 51 at the battery cell.

[0030] Furthermore, the device 1 comprises a control device 3. The control device 3 comprises a computing device 4 and a memory 5. The computing device 4 is, for example, a microprocessor or a microcontroller on which program code is executed to carry out the method described in this disclosure. However, hard-wired hardware components can also be provided that partially or completely execute the method. The device 1 can also be part of a battery controller (not shown).

[0031] The control device 3 is configured to determine a detected voltage differential 15 by differentiating the detected voltage 10 using a filter. The filter is, in particular, an antisymmetric filter with a finite impulse response. Furthermore, the control device 3 is configured to determine a modeled voltage differential 13 from the detected current 11 and a current internal resistance estimate 9 by differentiating using a filter. The filter is, in particular, an antisymmetric filter with a finite impulse response.

[0032] The control device 3 further determines a correction factor 17 from the detected voltage differential 15 and the modeled voltage differential 13. Furthermore, the control device 3 estimates a new current internal resistance estimate 9 from the determined correction factor 17 and the previous current internal resistance estimate 9 and provides the new current internal resistance estimate 9 as an estimated internal resistance 20 of the battery cell, for example as an internal resistance signal 21, for example at an interface 6. The estimated internal resistance 20 or the internal resistance signal 21 can be supplied, for example, to a battery controller 52.

[0033] It can be provided that when determining the correction factor 17, this is estimated by means of at least one estimation filter.

[0034] In a further development, it can be provided that the at least one estimation filter is designed as a Kalman filter.

[0035] It can be provided that at least one of the voltage differentials 13, 15 is compared with a predetermined threshold value 14, wherein the measures for determining the estimated internal resistance 20 are triggered when a value of one of the voltage differentials 13, 15 reaches or exceeds the predetermined threshold value 14.

[0036] This is shown schematically in the Figures 2a and 2b clarified. The Fig. 2a shows the measured current 11 in A over time 12 in seconds. The Fig. 2bshows the absolute value of the modeled voltage differential 13 in volts per second over time 12 in seconds, which was determined from the recorded current 11 and the current internal resistance estimate of the battery cell by differentiating using the filter, in particular using the antisymmetric filter with finite impulse response. At a time of approximately 150 seconds, the absolute value of the modeled voltage differential 13 exceeds the specified threshold 14. After reaching or exceeding the specified threshold 14, the measures for determining the estimated internal resistance 20 are carried out, so that an updated estimated internal resistance 20 ( Fig. 1 ) of the battery cell. This allows favorable values ​​of voltage 10 and current 11 to be used to learn the current internal resistance 20 with regard to a signal-to-noise ratio.

[0037] This embodiment is shown as a schematic flow diagram in the Fig. 3 In the control device 3 ( Fig. 1 ) For example, modules 100 to 103 are designed for this purpose ( Fig. 3 ). The detected current 11 is converted into a voltage in a module 100 using the current internal resistance estimate. This voltage is converted into the modeled voltage differential 13 using a differentiating filter, in particular an antisymmetric filter with a finite impulse response. This modeled voltage differential 13 is compared in a module 101 with a predetermined threshold value (see also Fig. 2b). If the threshold comparison in module 101 results in the threshold being reached or exceeded, the measures for determining a new current internal resistance estimate or an updated internal resistance 20 are started in a module 103; otherwise, the threshold comparison with current values ​​for the detected current is continuously repeated.

[0038] To execute the measures in module 103, a detected voltage differential 15 is supplied to module 103, which is generated in module 102 from the detected voltage 10 using a differentiating filter, in particular using an antisymmetric filter with a finite impulse response. Furthermore, the modeled voltage differential 13 is supplied to module 103. A (new, updated) correction factor is then learned in module 103, with which a current internal resistance 20 of the battery cell can be estimated.

[0039] It can be provided that a power flow direction is distinguished. For this purpose, the control device 3 ( Fig. 1 ) a current direction. The control device 3 determines an estimated internal charging resistance and / or an estimated discharging resistance depending on the determined current direction and provides these as power flow direction-dependent internal resistances 20l, 20e (charging, discharging) of the battery cell.

[0040] In the Figures 4a and 4b Schematic diagrams are shown to illustrate the method described in this disclosure. Shown are curves of the recorded voltage differential 15 as well as a voltage differential 16, which was determined using the nominal internal resistance (as reference internal resistance or starting internal resistance) of the battery cell, and the modeled voltage differential 13 in V over time 12 in seconds. It can be seen that at the beginning of the method, i.e., after approximately 160 seconds ( Fig. 4a ) the modeled voltage differential 13 matches the voltage differential 16 and exhibits deviations from the recorded voltage differential 15, particularly at the peaks. After approximately 2270 seconds, however, the modeled voltage differential 13 has adjusted to the recorded voltage differential 15, which was achieved primarily by adjusting the current internal resistance estimate using the correction factor. The learning effect is thus clearly visible.

[0041] In the Figures 5a and 5bSchematic diagrams are shown to illustrate an embodiment of the method. It is provided that a power flow direction is distinguished, wherein for this purpose a current direction is determined, and depending on the determined current direction, an estimated internal charge resistance and / or an estimated discharge resistance are determined, and these are provided as internal resistances of the battery cell that are dependent on the power flow direction. Furthermore, the embodiment provides that when determining the correction factors 17l, 17e, these are each estimated using an estimation filter, wherein the estimation filters are each designed as Kalman filters.

[0042] In the Fig. 5a The correction factor 17l, 17e of the internal charge resistance estimate is shown over time 12 in seconds. Fig. 5bThe correction factor 17l, 17e of the estimated internal discharge resistance is plotted against time 12 in seconds. It can be seen that the values ​​of the correction factors 17l, 17e for the estimated internal charge resistance and the estimated internal discharge resistance differ from each other. Accordingly, the estimated internal charge resistance determined using the correction factor 17l and the estimated internal discharge resistance determined using the correction factor 17e also differ from each other.

[0043] Furthermore, it is clearly visible how, from an initial value (=1) of the correction factors 17l, 17e, the respective value gradually approaches a value of the respective ground truth 19 over time.

[0044] The method and device enable the reliable estimation of a battery cell's internal resistance. Advantages include, in particular, the ability to learn a correction factor whenever a favorable signal-to-noise ratio is achieved. Furthermore, power-flow-dependent internal resistances can be estimated and provided, allowing a distinction to be made between internal resistance during charging and internal resistance during discharging. List of reference symbols

[0045] 1Device 2Interface 3Control device 4Computing device 5Memory 6Interface 9Current internal resistance estimate 10Detected voltage 11Detected current 12Time 13Modeled voltage differential 14Predetermined threshold 15Detected voltage differential 16Voltage differential (reference internal resistance) 17Correction factor 17lCorrection factor (charging) 17eCorrection factor (discharging) 19Ground truth 20Internal resistance 20lInternal resistance (charging) 20eInternal resistance (discharging) 21Internal resistance signal 50Voltage sensor 51Current sensor 52Battery controller 100-103Modules

Claims

1. Method for estimating an internal resistance (20) of a battery cell, comprising the following measures: detecting a voltage (10) at the battery cell, detecting a current (11) at the battery cell, determining a detected voltage differential (15) by differentiating the detected voltage (10) by means of a filter, determining a modeled voltage differential (13) from the detected current (11) and a present internal resistance estimated value by differentiating by means of a filter, determining a correction factor (17) from the detected voltage differential (15) and the modeled voltage differential (13), and estimating a new present internal resistance estimated value from the determined correction factor (17) and the previous present internal resistance estimated value, and providing the new present internal resistance estimated value as the estimated internal resistance (20) of the battery cell.

2. Method according to claim 1, characterized in that the filters are designed as antisymmetric filters which have a finite impulse response.

3. Method according to claim 1 or 2, characterized in that, when determining the correction factor (17), the correction factor is estimated by means of at least one estimation filter.

4. Method according to claim 3, characterized in that the at least one estimation filter is designed as a Kalman filter.

5. Method according to any of the preceding claims, characterized in that at least one of the voltage differentials (13, 15) is compared with a predetermined threshold value (14), the measures for determining the estimated internal resistance (20) being triggered when a value of one of the voltage differentials (13, 15) reaches or exceeds the predetermined threshold value (14).

6. Method according to any of the preceding claims, characterized in that a power flow direction is distinguished, a current direction being determined for this purpose and, depending on the determined current direction, a charging internal resistance estimated value and / or a discharging internal resistance estimated value being determined, and these being provided as internal resistances (20) of the battery cell, which are dependent on a power flow direction.

7. Apparatus (1) for estimating an internal resistance (20) of a battery cell, comprising: interfaces (2) which are configured to receive a voltage (10) detected at the battery cell and a current (11) detected at the battery cell, and a control device (3), wherein the control device (3) is configured to determine a detected voltage differential (15) by differentiating the detected voltage (10) by means of a filter, to determine a modeled voltage differential (13) from the detected current (11) and a present internal resistance estimated value by differentiating by means of a filter, to determine a correction factor (17) from the detected voltage differential (15) and the modeled voltage differential (13), and to estimate a new present internal resistance estimated value from the determined correction factor (17) and the previous present internal resistance estimated value, and to provide the new present internal resistance estimated value as the estimated internal resistance (20) of the battery cell.

8. Apparatus (1) according to claim 7, characterized in that the filters are designed as antisymmetric filters which have a finite impulse response.

9. Apparatus (1) according to claim 7 or 8, characterized in that, when determining the correction factor (17), the correction factor is estimated by means of at least one estimation filter.

10. Apparatus (1) according to claim 9, characterized in that the at least one estimation filter is designed as a Kalman filter.