CN-121986273-A - Method, device and system for classifying battery cells of battery pack in terms of their cell health

CN121986273ACN 121986273 ACN121986273 ACN 121986273ACN-121986273-A

Abstract

The invention relates to a method (10) for classifying battery cells (1100) of a battery pack (1001) with respect to their cell health. In the method (10), for each battery cell (1100) to be classified, a cell voltage (V_ Zell) and a current (I_ Zell) corresponding thereto are recorded. The internal resistance (iR) of the respective cell (1100) is thereby determined. Then, based on the determined internal resistance (iR), each battery cell (1100) is classified as healthy when the deviation DeltaiR of the corresponding internal resistance (iR) from the internal resistance reference value (iRW) is within a normal range. Here, the internal resistance reference value (iRW) is set to vary with time. The classification of the battery cells (1100) is output in the form of a classification result (KE). The invention also relates to a computer program product, an apparatus (100) and a battery system (1000) which each implement the aforementioned method (10).

Inventors

S. Em
S. Akyol
P. G. Palawal
T. SIVARAMAN

Assignees

AVL李斯特有限公司

Dates

Publication Date: 20260505
Application Date: 20240920
Priority Date: 20230921

Claims (15)

1. A method (10) for classifying battery cells (1100) of a battery pack (1001) with respect to their cell health, comprising the steps of: The cell voltage (V_ Zell) and the current (I_ Zell) corresponding to the cell voltage are recorded for each cell (1100) to be classified, Determining the internal resistance (iR) of the respective battery cell (1100) from the detected cell voltage (V_ Zell) and the detected current (I_ Zell), Classifying each of said battery cells (1100) as healthy when the deviation Δir of the respective internal resistance (iR) from the internal resistance reference value (iRW) is within a normal range, based on the determined internal resistance (iR), and The classification of the battery cells (1100) is output as a classification result (KE), It is characterized in that the method comprises the steps of, The internal resistance reference value (iRW) is time-varying.
2. The method (10) of claim 1, wherein the internal resistance reference value (iRW) Depending on the previous and preferably the last classification result (KE), Is the average value derived from the determined internal resistance (iR) of the last battery cell (1100) classified as healthy, Is the same or different for each of the battery cells (1100), and/or The initial value is an average value derived from the determined internal resistance (iR) of each of the battery cells (1100), or the initial value is an internal resistance determined at the time of battery pack manufacturing, preferably an average value derived from the internal resistance (iR) of the battery cells (1100) determined at the time of battery pack manufacturing.
3. The method (10) according to claim 1 or 2, characterized in that the deviation Δir is a deviation, preferably in percentage, of the internal resistance (iR) of the respective battery cell (1100) relative to the internal resistance reference value (iRW) based on the internal resistance reference value (iRW), and preferably the deviation Δir is determined by dividing a difference result, which is the difference between the internal resistance (iR) of the respective battery cell (1100) and the internal resistance reference value (iRW), by the internal resistance reference value (iRW).
4. Method (10) according to one of the preceding claims, characterized in that, -Determining an actual operating mode (IBM) of the battery pack (1001) from at least a curve of the current (i_ Zell) collected for the battery cell (1100), and preferably also from a curve of at least one collected cell voltage (v_ Zell), wherein the actual operating mode (IBM) comprises: o constant operating mode, in particular battery charging operating mode and/or battery discharging operating mode, which corresponds to a section (VK) of the current (I Zell) curve having a constant or substantially constant course and preferably no zero point, O dynamic operating mode, in particular driving operating mode, which corresponds to a section (VD) of the current (i_ Zell) curve having at least one current pulse (SP) and preferably having at least one zero point, and/or No-load operating mode, which corresponds to a section of the current (I Zell) curve with no or little current flow.
5. The method (10) of claim 4, wherein, Determining an internal resistance (iR) of the battery cell (1100) based on the determined actual operating mode (IBM) of the battery pack (1001), Wherein in the constant operation mode the internal resistance (iR) is determined from the potential difference between the actual no-load voltage of the battery cell (1100) and the collected cell voltage (v_ Zell) and from the collected current (i_ Zell), wherein preferably the actual no-load voltage is determined from the collected state of charge of the battery cell (1100), and/or Wherein in the dynamic operating mode, the internal resistance (iR) is determined from the difference between the cell voltages (v_ Zell) acquired at the beginning (t_0) and at the end (t_1) of the current pulse (SP) and from the current (i_ Zell) acquired at the end of the current pulse (SP).
6. The method (10) according to one of the preceding claims, characterized in that, for each of the battery cells (1100), the current (i_ Zell) is collected at an electrode (1002, 1003) of the battery pack (1001) or at an electrode (1102, 1103) of the respective battery cell (1100).
7. Method (10) according to one of the preceding claims, characterized in that, Based on the determined internal resistance (iR), for each of the battery cells (1100), the deviation Δir is classified as abnormal when it is out of a normal range, and preferably further comprises: o for each cell (1100) classified as abnormal, classifying it as severely aged when the deviation Δir is greater than an aging deviation limit, O for each cell (1100) classified as abnormal, classifying it as having a short-circuit hazard when the deviation Δir is negative and less than a short-circuit deviation limit, and preferably the deviation Δir has a rate of change greater than a rate of change limit, O for each battery cell (1100) classified as abnormal, classifying it as overheated when the deviation Δir is negative and less than a temperature deviation limit and at least one acquired battery pack (1001) temperature exceeds the temperature limit.
8. The method (10) according to one of the preceding claims, characterized in that the normal range has an upper limit and a lower limit, which are preferably defined according to the constructional structure of the battery cell (1100), Wherein preferably the values in the normal range are smaller than the ageing deviation limit, the short-circuit deviation limit or the temperature deviation limit in absolute value.
9. Method (10) according to one of the preceding claims, characterized in that, Preferably to an output device (1800) for the user: information about the result of the classification, in particular about the number of battery cells (1100) classified as healthy and preferably about the identification number, and about the total number of said battery cells (1100), O alert, and/or And a control signal (KS) for transmission to a control device of the battery pack (1001) for selectively activating or deactivating the battery cells (1100) of the battery pack (1001) according to the corresponding classification result.
10. Method (10) according to one of the preceding claims, characterized in that, The method (10) is provided for classifying the battery cells (1100) during operation of the battery pack (1001), The battery pack (1001) is provided with a voltage sensor (1101) for each battery cell (1100) to be classified, in order to detect the respective cell voltage (V_ Zell), The battery pack (1001) has at least 100 or 200 battery cells (1100), The battery pack (1001) is a lithium ion battery pack, The battery pack (1001) is a high-voltage battery pack for an electric vehicle, and/or The battery cells (1100) are connected in series in the battery pack (1001).
11. A computer program product having instructions which, when the program is executed by a computer, cause the computer to carry out the method (10) according to one of the preceding claims.
12. An apparatus (100) for classifying battery cells (1100) of a battery pack (1001) with respect to their cell health, comprising: a detection module (120) for detecting a cell voltage (V_ Zell) and a current (I_ Zell) corresponding to the cell voltage for each cell (1100) to be classified, A determination module (130) for determining the internal resistance (iR) of the respective battery cell (1100) from the acquired cell voltage (V_ Zell) and the acquired current (I_ Zell), A classification module (140) for classifying each cell (1100) based on the determined internal resistance (iR), and An output module (150) for outputting the classification of the battery cells (1100) as a classification result (KE), It is characterized in that the method comprises the steps of, The classification module (140) is configured to classify a respective internal resistance (iR) as healthy when a deviation Δir of the internal resistance reference value (iRW) with respect to the battery cell (1100) is within a normal range, wherein the internal resistance reference value (iRW) is time-varying.
13. The apparatus (100) of claim 12, wherein, An operating mode determining module (131) is provided for determining an actual operating mode (IBM) of the battery pack (1001) at least from a profile of the current (i_ Zell) detected for the battery cells (1100), and preferably also from a profile of at least one detected cell voltage (v_ Zell).
14. A battery system (1000) is provided with: At least one battery pack (1001) having a plurality of preferably serially connected battery cells (1100), A voltage sensor (1101) for detecting a cell voltage (V_ Zell) of each battery cell (1100) to be classified, and at least one current sensor (1200) for detecting a current (I_ Zell), It is characterized in that the method comprises the steps of, Device (100) for classifying battery cells (1100) of a battery pack (1001) according to claim 12 or 13 with respect to their cell health.
15. The battery system (1000) according to claim 14, wherein: At least one circuit-breaking device (1500) having a switchable separating section (1501) for interrupting the charge transport in one of the battery cells (1100), wherein the circuit-breaking device (1500) is connected to the device (100) in order to switch the circuit-breaking device (1500) as a function of the classification result (KE), and/or An output means (1800) for the user for outputting the classification result (KE).

Description

Method, device and system for classifying battery cells of battery pack in terms of their cell health Technical Field The present invention relates to a method and apparatus for classifying battery cells of a battery pack with respect to their cell health. The invention also relates to a computer program product for executing the inventive method on the basis of a computer and to a battery system having the inventive device. Background In order to be able to be used in a variety of application scenarios, the safety of the battery in its use is of paramount importance. For example, batteries with high energy storage capacity are used in conjunction with electric vehicles and household or industrial photovoltaic systems. Lithium ion batteries are often used because of their relatively high energy density compared to other battery types. To further increase the energy density, a high voltage battery with an operating voltage of at least 60 vdc may be used. However, as energy density increases, the potential risk that such energy storage devices may carry increases. Particularly problematic is the occurrence of burn-through or thermal runaway of the battery, which is also known as "Thermal Runaway". In particular, thermal runaway describes a self-enhanced thermogenic process. The process is accelerated by the temperature rise, thereby releasing heat again, which further increases the temperature, thereby further accelerating the process. This may lead to overheating of the battery, which in turn may lead to ignition and/or even explosion of the affected battery. In such cases, it is often almost impossible or impossible to extinguish a battery fire or interrupt the process chain. In batteries, especially lithium ion batteries, thermal runaway may occur due to local excessive temperatures or due to internal shorting of the electrodes. In such a short circuit, the resulting short circuit current heats the environment around the local connection point between the electrodes, so that the heating process can be locally extended and additionally release the stored energy. The cause of the internal short circuit may be various. Contamination of the separator between the electrodes (e.g., entrained foreign particles) or mechanical damage to the separator can result in a short circuit. In addition, short circuits may occur during normal use. When the battery is repeatedly charged, so-called dendrite growth may occur on the battery electrode. When the dendrites formed pierce the membrane, the dendrite growth may cause a short circuit. In general, as charge and discharge cycles progress and cell aging progresses, deposition of substances (such as dendrite growth) on the electrode is intensified. It is known from the prior art to deal with the problem of thermal runaway initiation by closely monitoring the battery temperature. A disadvantage of such a solution is that a dense temperature sensor network is required to monitor the temperature of the individual cells. This also arises from the fact that due to the high thermal insulation between the individual cells, local hot spots often cannot be detected when only a small number or, for example, a single centralized temperature sensor is used. However, dense temperature sensor networks involve high construction and cost expenditures. Another disadvantage is that the risk of thermal runaway is only identified at a point in time when thermal runaway is no longer prevented. Other solutions known from the prior art describe a method of detecting a short circuit in a battery cell, i.e. determining the internal resistance of the battery cell and comparing it with a manufacturing specific internal resistance reference value. A disadvantage of this solution is that the internal resistance can often only be estimated very inaccurately, due to the many influencing factors. Accordingly, the critical variation of the internal resistance cannot be determined with sufficient accuracy and speed. As a consequence, the risk of thermal runaway cannot be identified with these solutions at a point in time at which thermal runaway is still avoided. Disclosure of Invention The object of the invention is therefore to eliminate at least partially the abovementioned disadvantages. In particular, the object of the invention is to provide a method and a device which make it possible to reliably detect problematic changes in the interior of a battery early. In particular, those changes that may lead to thermal runaway should be identified early. The above-mentioned object is achieved by a method having the features of claim 1, a computer program product having the features of claim 11, an apparatus having the features of claim 12 and a battery system having the features of claim 14. Other advantages and features of the invention come from the dependent claims, the description and the drawings. The features and details described in connection with the inventive method are obviously also applicable her