Device for determining the inner pressure in a lithium-ion battery

Abstract

The invention relates to a method for determining the inner pressure in a lithium-ion battery (3) made up of one or more battery modules (4) each with a plurality of braced-together single battery cells, which is used in a vehicle as a traction battery for an at least partially electric drive. The method according to the invention is characterised in that in driving mode, a control device software of the vehicle is used to estimate a current state of health (SOHc) of the battery (3), after which the inner pressure of the battery module or the single battery cells installed therein is determined based on a stored characteristic curve or a stored characteristic map of the specific pressure-dependent state of health of the type of battery module (4) being monitored and the single battery cells installed therein.

Description

[0001] Device for determining the internal pressure in a lithium-ion battery

[0002] The invention relates to a method for determining the internal pressure in a lithium-ion battery comprising several battery modules, each with several individual battery cells clamped together.

[0003] Lithium-ion batteries are subject to volume changes both during charging and discharging, as well as through the aging of their individual battery cells. Aging essentially results in cell thickness growth with increasing age. This cell thickness growth results from chemical reactions of the active electrode materials, which in principle also occur during charging and discharging, but in particular increase irreversibly with aging. Within the lithium-ion battery or a battery module, of which the lithium-ion battery can comprise several, the individual battery cells are generally mechanically stressed, for example, in the case of prismatic cells, they are stacked to form a cell stack and clamped between end plates or pressure glasses. This mechanical stress causes an increase in pressure in the battery when the layer structures of the individual

[0004] Individual battery cells expand and the individual battery cells increase their volume.

[0005] The state-of-charge-dependent volume change, also known as cell "breathing," can be measured very well. This can therefore be easily incorporated into the mechanical design of the battery or module housing. Aging-related cell thickness growth, on the other hand, is very difficult to handle. On the one hand, it is difficult and expensive to test because irreversible cell thickness growth is an aging phenomenon, and various aging scenarios occur that can be so diverse that it is never possible to reliably and completely test all of them in advance. Often, the scenarios and their impact on cell thickness growth remain unknown. The rapid development cycles for lithium-ion batteries with varying cell structures that are common in today's automotive industry result in a constantly changing internal structure, i.e., in the chemical composition and / or mechanical layer structure of the individual battery cells.However, this very factor has a decisive influence on aging-related cell thickness growth. Furthermore, manufacturing processes and materials vary significantly from manufacturer to manufacturer, resulting in significant manufacturer variance in addition to unavoidable production tolerances despite the same underlying structure. In the worst case, these differences can escalate with the production tolerances. Another reason is that newer developments increasingly involve the use of highly expanding active materials, such as silicon compounds in the anode, which are involved in the active conversion. These compounds amplify any design inaccuracies in critical pressure and expansion ranges, which are therefore more difficult to predict and control design-wise.All in all, uncontrolled aging-related cell growth that exceeds the expected magnitude can have safety-critical consequences. This can lead to mechanical deformation of the battery and / or module housing, even leading to cracks, short circuits, or similar events. In the worst case, this can have serious safety implications, for example, in extreme cases, it can lead to a battery fire.

[0006] It would therefore be highly desirable to have appropriate information about the internal pressure of the battery in order to be able to shut down the battery in good time before a safety-critical maximum pressure is reached. To generate such information, appropriate sensors can be installed, such as pressure sensors or sensors for measuring the distance / length of the battery module, busbars installed on the module, or the like. This is complex and requires a certain amount of space for the arrangement of the sensors and the cable routing. Furthermore, with a large number of additional sensors, there is always the risk of an additional failure or the danger that false positive sensor readings could trigger undesirable scenarios.

[0007] Studies on the pressure- and force-dependent aging behavior of lithium-ion cells are fundamentally known from the literature, for example from the article “Effects of module stiffness and initial compression on lithium-ion cell aging”, T. Deich et al., Journal of Power Sources 506 (2021) 230163.

[0008] The object of the present invention is to provide a method for determining the internal pressure in a battery, which enables reliable predictions of the internal pressure in a simple, cost-effective and low-error manner.

[0009] According to the invention, this object is achieved by a method having the features in claim 1, and in particular in the characterizing part of claim 1. Advantageous embodiments and further developments emerge from the dependent claims.

[0010] The method according to the invention for determining the internal pressure of a lithium-ion battery utilizes the vehicle's control unit software, which estimates the current health status of the battery module during operation. The internal pressure of the battery module is then determined based on a stored characteristic curve or a stored characteristic map of the specific pressure-dependent health status of the respective type of monitored battery module and the individual battery cells installed therein.

[0011] According to the invention, by parameterizing the pressure-dependent aging behavior within the vehicle software, the state of health and damage rate (SOH / State of Health and Dc / Damage Rate) during ferry operation can be determined based on the existing internal battery pressure. To achieve this reliably, the inclusion of module-specific capacity aging is crucial, since different modules from different manufacturers and with different installed materials exhibit different aging behaviors and thus ultimately different cell thickness growth under the same scenario, i.e., the same temperature influences, changes in state of charge, and the like. The method according to the invention uses the stored characteristic curve or the stored characteristic map of precisely this specific pressure-dependent state of health of the respective type of battery module or its individual battery cells used.These data are determined experimentally once for each type and can then be stored accordingly in the characteristic curve or the characteristic map in order to be able to draw conclusions about the internal battery pressure based on the current aging state determined by the vehicle software.

[0012] According to a very advantageous development of the method according to the invention, it can be provided that a single-cell-related characteristic curve or a single-cell-related characteristic map is derived from the characteristic curve or the characteristic map, wherein the position of the respective single battery cell in the battery module is taken into account. Depending on the arrangement of the single battery cells in the battery module, for example, in a stack of prismatic single battery cells, closer to the edge of the module or in its center, different forces act on the single battery cells, since those in the edge area are more likely to deflect than those arranged in the center. Thus, the highest force typically acts on these cells, which means the highest pressure occurs here.

[0013] According to a further very advantageous embodiment of the method according to the invention, it can then further be provided that the individual battery cell with the worst health status is used to estimate the maximum pressure. This can, for example, be an individual battery cell located closer to the center of the module. If the health status is estimated based on this "worst-case" cell, a correspondingly high level of safety can be ensured, since an action resulting from the health status and the resulting maximum pressure, such as a safety-related shutdown of the entire lithium-ion battery, is always carried out based on the "weakest link in the chain." This ensures the highest level of safety.

[0014] The entire process is simple, efficient, and reliable, and does not require any failure-prone measurement technology or sensors to record pressure or mechanical deformation. This increases vehicle safety and thus the safety of passengers, as the lithium-ion battery can simply be shut off if a critical pressure is reached. Furthermore, the process allows for a better prognosis of the expected future development of health, with positive effects on future age-related range estimations and the vehicle's residual value, as battery life can be optimized through more or less unobtrusive adjustments to battery management by the person using the vehicle.According to a very advantageous embodiment of the method according to the invention, it is provided that at least the capacity development and / or the development of the internal resistance of the battery module and / or the individual battery cells of the battery module are taken into account when determining the state of health. Depending on the electrical measurement technology present in the module or in the area of ​​the individual cells of the module, the capacity development of the entire module or individual battery cells and / or the development of the internal resistance can ideally be considered as typical parameters for the state of health and the damage rate.

[0015] Another very advantageous embodiment can also provide for the health status to be determined during ferry operation using predefined and / or learned estimation algorithms. Such estimation algorithms, which start with a basic algorithm, are suitable for estimating the health status based on corresponding models. In addition to pure specifications, they can also be further developed using machine learning or artificial intelligence. This allows for improved adaptation of the material installed in the respective vehicle to be specifically developed. Due to the increasing adaptation to the specific battery, which is monitored internally, increasingly better values ​​are delivered with increasing operating time. This reduces the effort required to determine the predefined values.

[0016] According to a very advantageous development of this variant of the method according to the invention, it can further be provided that the estimation algorithms are adjusted based on the determined internal pressure. The estimation algorithms can thus be adjusted accordingly based on the determined internal pressure as the new initial pressure. Here, too, artificial intelligence or, in particular, machine learning can help to further improve the results.

[0017] As already mentioned above, according to a very advantageous embodiment of the method according to the invention, at least one warning message, an adjustment in the operating management and / or, in the worst case, a shutdown of the affected battery module can be implemented as soon as the internal pressure determined using the method according to the invention exceeds at least a predetermined limit pressure. This predetermined limit pressure can be the pressure referred to as the maximum pressure in the sense described above. It is the pressure for which safe operation can be guaranteed in any case due to the mechanical structure of the lithium-ion battery. If the determined internal pressure exceeds this predetermined limit pressure, a potentially safety-critical situation must be expected, which will result in at least one warning message, an adjustment in the operating management and / or a shutdown of the affected battery module.In principle, several limit pressures can be provided, for example, to first make an adjustment in the operating management system at a lower limit pressure, to issue a warning at a medium limit pressure, and finally to initiate an emergency shutdown of the affected battery module at an upper / maximum limit pressure. This escalation sequence has the advantage that a person using the vehicle can still prepare for this to a certain extent.

[0018] As already mentioned at the beginning, according to an advantageous embodiment of the method according to the invention, it can be provided that the characteristic curve or the characteristic map for each type of battery module and the individual battery cells installed therein is determined in advance on a module-specific basis based on the aging measurement of one or more battery modules of the respective type and is made available for storage in the respective control unit. In addition to measuring the module types intended for installation before such modules are mounted in a vehicle, they can also be measured type-specifically. However, new types of modules can also be measured continuously. For example, the corresponding characteristic curve or the characteristic map can be made generally available via a cloud in order to have the corresponding data for the newly installed replacement battery module or the newly installed replacement battery easily and efficiently available, for example when changing a battery.A corresponding update can be performed at the workshop, for example, when replacing the battery, but can also be implemented over the air. This offers the opportunity to readjust the maps if new insights into module-specific aging have been discovered for installed battery modules that have been in operation for some time, thus ensuring even further improvements in existing systems via a software update.

[0019] Another extremely advantageous variant of the method according to the invention can now further provide for the remaining service life of the battery to be determined based on the current state of health. An advantageous development of this can then further provide for this remaining service life of the battery to be saved and / or updated or even visualized for a user. This makes it possible, for example, to read out the expected remaining service life of the battery easily and efficiently during a workshop visit. Furthermore, in the interest of maximum transparency, this can also be visualized for the user of the vehicle, either directly in the vehicle or, for example, in an application connected to the vehicle on a computer or mobile device.

[0020] Further advantageous embodiments of the method according to the invention also emerge from the exemplary embodiment which is illustrated in more detail below with reference to the figures.

[0021] Figure 1 shows a schematic diagram explaining the method according to the invention. The block on the far left comprises the measurement of battery values ​​in the vehicle and is designated 1. The measured values ​​are values ​​that are required anyway to control battery 3 (see Figure 2), i.e., for what is known as battery management. The current state of health (SOHc) of the lithium-ion battery 3 installed in the vehicle as a traction battery is then determined in control unit software indicated as an example and designated 1A. This state of health SOHc, estimated using estimation algorithms, is then transferred, as indicated by the arrow, to a battery control unit designated 2 in its entirety. In a first control module 2A of this battery control unit 2, the current states of health SOHc in the individual cells are then determined with regard to their arrangement in the respective battery module.This is indicated here by the graph of the current health states SOHc over the local position of the individual cells in the battery module, whereby the x-axis of the diagram shows the length of the module from a first edge cell R in the area of ​​the y-axis, over the module center M to an opposite edge cell R as an example.

[0022] In principle, the module- or cell-specific pressure-dependent state of health (SOH) can be experimentally characterized in advance for each type of battery, single cell, or cell module. For this purpose, for example, tests can be conducted on aging behavior at different pressures. The aging behavior is determined in particular based on the development of capacity and / or internal resistance. This data can then be stored in the vehicle as a characteristic curve or map during the further course of the process.

[0023] In addition, the stacking of the individual battery cells within each cell module results in different pressure distributions. Typically, those individual battery cells at the edge, located at an end plate, are subject to softer boundary conditions than those individual battery cells in the center of the module. Here, stiffer boundary conditions apply. Thus, the greatest internal pressure typically builds up from the individual battery cells in the center M of each battery module, while this pressure decreases accordingly toward the edge R, as the end plates allow for a certain amount of deformation. Pressure-dependent aging thus results in an inhomogeneous pressure distribution.

[0024] In the illustration in Figure 2, this is shown using the example of a lithium-ion battery 3 consisting of 10 battery modules 4.1 - 4.10.

[0025] In module 2B of battery control unit 2, the final calibration is performed by determining a local damage rate using the difference quotient df (SOHc) / dETP, where ETP describes the energy throughput. Battery control unit 2 then forwards the target information or the data for generating the target information to the block labeled 5 on the far right. This is where the pressure is ultimately determined based on the estimated aging or the estimated health status of each of the individual battery cells.

[0026] By determining the SOHc state of health during ferry operation using suitable estimation algorithms, the pressure that must have acted on the respective individual battery cell can be deduced from the characteristic curve recorded through experimental characterization mentioned above. This has two crucial advantages:

[0027] First, with a known pressure, better future forecasts for the further development of the state of health (SOH) of the lithium-ion battery 3 are possible, since pressure has a significant influence on the state of health (SOH). This allows for improved predictions regarding the future remaining state of health and thus the remaining range or the remaining useful life of the lithium-ion battery 3. Second, the pressure determined in this way allows for a strategy to respond to increased pressures and avoid safety-critical pressure scenarios by shutting down the lithium-ion battery, or if the design allows it, the affected battery module 4, accordingly, particularly when a maximum limit pressure is reached.

[0028] The process ultimately requires only two things: the product-specific pressure-dependent aging behavior, which must be determined experimentally and can be stored as a characteristic curve / map in the vehicle control unit. Second, an estimation of the SOH state of health (SOHc) must be implemented on the battery control unit 2, which compares the current SOHc state of health with the characteristic curve / map to determine the applied pressure.

[0029] The procedure can essentially be implemented using the following four steps:

[0030] First, all individual capacities are determined accordingly in order to determine the current health status SOHc for each of the battery individual cells.

[0031] In the second step, the individual battery cells are sorted according to their location within the respective module 4, so that a function of the current health status f(SOHc) can be determined. This essentially consists of a sequence of the current health statuses SOHci of the individual battery cells. f(SOHc)=[SOHCj ,SOHc i+i ,SOHc i+2 SOHc n ]

[0032] In the third step, the local damage rate is determined using the difference quotient df(SOHc) / dETP mentioned above.

[0033] In the fourth step, the damage rate distribution is then classified into the characteristic map in order to then determine the corresponding pressure as the desired target information.

Claims

Mercedes-Benz Group AG Patent claims 1. Method for determining the internal pressure in a lithium-ion battery (3) comprising one or more battery modules (4), each having a plurality of individual battery cells clamped together, which is used in a vehicle as a traction battery for an at least partially electric drive, characterized in that, during driving operation, a current state of health (SOHc) of the battery (3) is estimated via control unit software of the vehicle, after which the internal pressure of the monitored battery module (4) and the individual battery cells installed therein are determined on the basis of a stored characteristic curve or a stored characteristic map of the specific pressure-dependent state of health of the type of battery module (4) used in each case and of the individual battery cells installed therein.

2. Method according to claim 1, characterized in that a single-cell-related characteristic curve or a single-cell-related characteristic diagram is derived from the characteristic curve or the characteristic diagram, wherein the position of the respective single battery cell in the battery module is taken into account.

3. Method according to claim 1 or 2, characterized in that the single battery cell with the worst state of health (SOHci) is used to estimate the maximum pressure that occurred.

4. Method according to claim 1, 2 or 3, characterized in that at least the capacity development and / or the development of the internal resistance of the battery module and / or the individual battery cells of the battery module are taken into account in determining the state of health (SOHc) during ferry operation.

5. Method according to one of claims 1 to 4, characterized in that the determination of the state of health during ferry operation is carried out on the basis of predetermined and / or learned estimation algorithms.

6. The method according to claim 5, characterized in that the estimation algorithms are adapted to the type based on a starting algorithm by means of machine learning or artificial intelligence.

7. Method according to claim 5 or 6, characterized in that the estimation algorithms are adapted based on the determined internal pressure.

8. Method according to one of claims 1 to 7, characterized in that as soon as the determined internal pressure exceeds at least a predetermined limit pressure, a warning message, an adjustment in the operating management and / or a shutdown of the affected battery module (4) is triggered.

9. Method according to one of claims 1 to 8, characterized in that the characteristic curve or the characteristic map for each type of battery (3) of a battery module (4) and its individual battery cells installed therein is determined in advance on a module-specific basis based on the measurement of the aging of one or more such battery modules (4) and is made available for storage in the respective control unit.

10. Method according to one of claims 1 to 9, characterized in that a remaining service life of the battery (3) is determined based on the currently estimated state of health (SOHc).

11. Method according to claim 10, characterized in that the determined remaining service life is stored and updated accordingly in a storage medium and / or visualized in a display device.

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