METHOD FOR MONITORING THE CONDITION OF JOINTS OF A VEHICLE AND CORRESPONDING SYSTEM

Abstract

The present invention provides a system and a method for monitoring the condition of the joints on the busbar (110) of the battery cell terminals (108) in a vehicle (102) in real time. In particular, the present invention describes the acquisition of signals from: a) a distributed fiber optic sensor (DFOS, 112) arranged either on the busbar (110) or the battery cell terminals (108), or both; and b) accelerometers (114, 218) arranged on the battery pack (104) and the vehicle's suspension assembly. The signals from the DFOS (112) are associated with a first oscillation frequency corresponding to the joints and a load induced in the DFOS (112). Furthermore, the signals from the accelerometers (114, 218) are associated with a second oscillation frequency.These signals are fed into a pre-trained model (116, 206) which analyzes the signals to determine the condition of the joints in real time.

Description

TECHNICAL AREA

[0001] The present invention relates generally to monitoring the condition of joints in a vehicle and in particular to monitoring the condition of joints on the busbar of battery cell tabs in a vehicle. BACKGROUND

[0002] The following description contains information that may be useful for understanding the present invention. It does not constitute an admission that the information contained herein forms part of the prior art or is relevant to the present invention, or that any publication to which express or implicit reference is made forms part of the prior art.

[0003] A vehicle is subject to vibrations when driving on a road, especially if the roads are uneven, have many bumps and potholes, or are worn. These vibrations are transmitted to all parts of the vehicle through energy conversion and lead to a deterioration of the vehicle's performance over time, as the condition of the various vehicle components deteriorates.

[0004] Particularly in an electric or hybrid vehicle, where a battery pack is used for charging and propulsion, the stress caused by vibrations significantly impairs the battery pack's characteristics in terms of lifespan, capacity, and performance. This, in turn, affects the performance and reliability of the electric or hybrid vehicle. To further clarify: A battery pack in an electric or hybrid vehicle consists of multiple battery cells connected to a busbar via cell assemblies. The cell assemblies are typically joined to the busbar using one or more welding techniques, creating both an electrical and a mechanical connection between the battery cells and the busbar.During operation of the electric or hybrid vehicle, the joints on the power rail are subjected to both mechanical and thermal stresses. Mechanical stresses arise from dynamic loads, random vibrations, and fatigue, while thermal stresses occur during the charging and discharging of the battery pack. Furthermore, as the vehicle ages, these joints are subjected to constant vibration due to mechanical and thermal stresses, leading to the following results: A) Expansion of the volume of the joints due to constant thermal stress, B) Increased thermal resistance due to the formation of air gaps in the joints as a result of the vibration movement, C) The deformation of the joints leads to a reduction in the contact area of ​​the joints, resulting in a high electrical resistance for the current flow from the terminals of the battery cells to the busbar.

[0005] Furthermore, these thermal and electrical resistances lead to temperature fluctuations in the battery cells and thus to fluctuations in the current flow. This, in turn, accelerates the aging of the battery pack and leads to battery degradation and a reduction in battery health, which in turn affects the vehicle's range. If the joint breaks due to such vibrations, a short circuit occurs, leading to thermal runaway, which can prove catastrophic.

[0006] In engineering, there are certain solutions designed to monitor the condition of a battery pack. One such solution is described in DE102022204775A1 (hereinafter referred to as publication '775').

[0007] Publication 775 describes a method for monitoring a battery in a motor vehicle, in which signals are acquired using at least one vibration sensor, providing information about the battery's vibration load, and further signals from the battery are acquired, providing information about the battery's operation, which makes it possible to describe the battery's corrosion using a corrosion model. Essentially, Publication 775 describes how the information about the battery's vibration load and the information about the battery's operation are used together to detect any impairment of the battery's operation.

[0008] However, publication '775 describes how the vibration sensors present in the vehicle, e.g., in the airbag or the IPB (Integrated Power Brake), are used to estimate or determine the total vibration load of the vehicle and thus also of the battery. Therefore, the estimate of the vibration load on the battery pack is not so precise.

[0009] Therefore, there is a need for a system and a procedure that overcomes the aforementioned limitations and enables accurate monitoring of the condition of the joints connecting the battery cells to the busbar, where the condition of the joints is severely affected by vibrational movements. SUMMARY

[0010] The present invention overcomes one or more shortcomings of the prior art and offers additional advantages. Embodiments and aspects of the invention described in detail herein are considered part of the claimed invention.

[0011] In a non-limiting embodiment of the present invention, a method for monitoring the condition of joints on busbars of battery cell terminals in a vehicle is disclosed. The method comprises receiving a first signal from a distributed fiber optic sensor (DFOS) arranged above a busbar and / or a plurality of battery cell terminals connecting each battery cell to the busbar. The method further comprises determining a first oscillation frequency from the received first signal, corresponding to the joints and strain induced in the DFOS by a vibrational movement of the joints on the busbar of the battery cell terminals. The method further comprises receiving a second signal from the vehicle's suspension unit and battery pack. The method further comprises determining a second oscillation frequency from the received second signal.Furthermore, the procedure includes correlating the determined values ​​of the first frequency, the second frequency, and the induced load with a test dataset using a pre-trained model. The procedure also includes monitoring the condition of the joints on the current rail of battery cell tabs, based on this correlation. In addition, the procedure includes determining the degree of joint deterioration based on this monitoring.

[0012] In another, non-limiting embodiment of the present invention, the method for determining the strain induced in the DFOS further comprises the transmission of photon pulses through the DFOS by means of a pulsed source. The method further comprises the detection of a plurality of photons backscattered by the DFOS by a detector.

[0013] In a further, non-limiting embodiment of the present invention, the received first signal comprises information about the plurality of photons backscattered by the DFOS. Furthermore, the method for determining the strain from the received signal comprises determining an intensity of the plurality of photons backscattered by the DFOS as a function of the wavelength from the received first signal and determining the strain induced in the DFOS based on the intensity.

[0014] In a further, non-limiting embodiment of the present invention, the second oscillation frequency corresponding to the battery pack and suspension unit of the vehicle is determined by analyzing the received second signal obtained from acceleration sensors installed on the battery pack and suspension unit of the vehicle.

[0015] In a further, non-limiting embodiment of the present invention, the pre-trained model is trained on the basis of the test data set, which comprises a plurality of quantitative joint deterioration values ​​indicating the condition of the joints and obtained by subjecting the joints to a plurality of test conditions in multiple frequency ranges. In one exemplary aspect, the plurality of test conditions includes at least: one or more types of roads, one or more battery charging conditions, one or more battery aging conditions, one or more battery discharging conditions, and one or more driving profiles. Furthermore, in one exemplary aspect, each frequency range is associated with a corresponding acceleration value acting on the vehicle during the test.

[0016] In a further non-limiting embodiment of the present invention, a system for monitoring the condition of joints on busbars of battery cell tabs in a vehicle is disclosed. In one exemplary aspect, the processor is configured to receive a first signal from a distributed fiber optic sensor (DFOS) arranged over at least one of the following: a busbar and a plurality of battery cell terminals connecting each battery cell to the busbar. The processor is further configured to determine from the received first signal a first oscillation frequency corresponding to the joints and strain induced in the DFOS by a vibrational movement of the joints on the busbar of the battery cell tabs. The processor is further configured to receive a second signal from the vehicle's suspension unit and battery pack.The processor is further configured to determine a second oscillation frequency from the received second signal. In addition, the processor is configured to correlate the determined values ​​of the first frequency, the second frequency, and the induced load with a test dataset using a pre-trained model. The processor is also configured to monitor the condition of the joints on the current rail of the battery cell tabs based on this correlation and to determine the degree of joint deterioration based on this monitoring.

[0017] In a further, non-limiting embodiment of the present invention, the system for determining the strain induced in the DFOS further comprises a DFOS signal analyzer with a pulsed source and a detector. In one exemplary aspect, the DFOS signal analyzer is operationally coupled to the DFOS and the processor. The DFOS signal analyzer is configured to send photon pulses through the DFOS and detect a plurality of photons backscattered by the DFOS.

[0018] The foregoing summary serves only for illustration and is in no way intended to be limiting. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features will become clear by reference to the drawings and the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The features, nature, and advantages of the present invention will become clearer from the detailed description below in conjunction with the drawings, in which identical reference numerals are consistently marked accordingly. Some embodiments of systems and / or methods in accordance with embodiments of the present subject matter are now described only by way of example and with reference to the accompanying figures, in which: Fig. Figure 1 shows an exemplary environment 100 for monitoring the condition of joints on busbars of battery cell tabs in a vehicle according to an embodiment of the present invention. Fig. Figure 2 shows a block diagram 200 of a system for monitoring the condition of joints on busbars of battery cell tabs in a vehicle according to an embodiment of the present invention, Fig.Figure 3 shows an exemplary representation 300 of photon scattering as a function of wavelength according to an embodiment of the present invention, and Fig. Figure 4 shows in the form of a flowchart a method 400 for monitoring the condition of joints on busbars of battery cell tabs in a vehicle according to an embodiment of the present invention.

[0020] The person skilled in the art should know that all block diagrams contained herein represent conceptual views of systems embodying the principles of the subject matter at hand. Likewise, it will be understood that all flowcharts, process diagrams, state transition diagrams, pseudocodes, and the like represent various processes, essentially represented in a computer-readable medium and executable by a computer or processor, whether or not such a computer or processor is explicitly depicted. DETAILED DESCRIPTION

[0021] The foregoing has broadly outlined the features and technical advantages of the present invention to facilitate a better understanding of the subsequent detailed description. It should be readily apparent to those skilled in the field that the disclosed concept and specific embodiment can be used as a basis for modifying or constructing other structures to achieve the same purposes as the present invention.

[0022] The novel features, which are considered characteristic of the invention both in terms of their organization and their operation, along with other objects and advantages, will be better understood from the following description when considered in conjunction with the accompanying figures. It should be expressly understood, however, that each of the figures is provided for illustrative and descriptive purposes only and is not intended to define the limits of the present invention.

[0023] As described in the "Background" section, the joints between the battery cells and the busbar deteriorate over time due to vibrations during battery charging and vehicle operation, which can adversely affect battery life and consequently vehicle performance. To address these challenges, the present invention provides a system and a method that monitors the condition of the joints on the busbar of battery cell terminals in a vehicle in real time. In particular, the present invention describes the acquisition of signals from a) a distributed fiber optic sensor (DFOS) mounted either on the busbar or on the battery cell terminals, or both, and b) accelerometers mounted on the battery pack and the vehicle's suspension assembly.The signals from the DFOS are associated with a first vibration frequency corresponding to the joints and a strain induced in the DFOS by the joints' vibration. Furthermore, the signals from the accelerometers are assigned a second vibration frequency corresponding to the vehicle's battery pack and suspension unit. These signals are fed into a pre-trained model that analyzes them to determine the joint state in real time. A detailed description of the proposed solution is provided in the following sections in conjunction with the [references / documents]. Fig. 1-2 explained.

[0024] Fig. 1 shows an exemplary environment 100 for monitoring the condition of joints on busbars of battery cell tabs in a vehicle, according to an embodiment of the present invention. In particular, a vehicle 102 is shown with a battery pack 104, which is responsible for providing energy to power the vehicle. The battery pack 104 comprises a plurality of battery cells 106, which are connected to a busbar 110 via a plurality of cell terminals 108. Furthermore, the plurality of cell terminals 108 can be connected to the busbar 110 by one or more welding techniques, including, but not limited to, ultrasonic welding, laser welding, etc. The person skilled in the art will further see that the plurality of battery cells 108, as shown in Fig.As shown in Figure 1, they have a cylindrical shape. However, the shape and structure of the multitude of battery cells 108 can vary depending on the battery type and / or battery configuration, and therefore the one shown in Fig. The form of the multitude of battery cells shown in Figure 108 should not be understood as restrictive. Fig. Figure 1 further shows a distributed fiber optic sensor (DFOS) 112, which is attached to the busbar 110 such that the DFOS 112 covers the entire length of the busbar 110. In another exemplary embodiment, however, the DFOS 112 can be arranged on the plurality of cell terminals 108 or a combination thereof, depending on the battery type and / or battery configuration.

[0025] In Fig.The acceleration sensors 114 are also shown in Figure 1. In an exemplary embodiment, the acceleration sensors 114 can be mounted on the battery pack 104 and a suspension unit (not shown) of the vehicle 102. Furthermore, a first signal can be obtained from the battery pack 104, corresponding to the vibration frequency (F1) of the joints on the busbar and a strain induced in the DFOS 112. In addition, a second signal can be obtained from the acceleration sensors 114, corresponding to the vibration frequency (F2) associated with the battery pack 104 and the suspension unit. These signals are then fed into a pre-trained model 116, which determines / monitors the state 117 of the joints on the busbar in real time. A detailed description of the exemplary environment 100 is given in the following sections in conjunction with Fig. 2 explained.

[0026] Fig.Figure 2 shows a block diagram 200 of a system 202 for monitoring the condition of joints on busbars of battery cell tabs in a vehicle according to an embodiment of the present invention. In an exemplary embodiment, the system 202 can include a memory 204, a processor 210, a DFOS (Distributed Fiber Optic Sensor) signal analyzer 212, and accelerometers 218 (analogous to those in Figure 2). Fig.The DFOS signal analyzer 212 comprises accelerometers 114 (as shown in Figure 1) and an I / O interface 220. In another exemplary embodiment, however, the DFOS signal analyzer 212 and the accelerometers 218 can be located outside the system 202 and be operationally coupled to the system 202. In one implementation, the memory 204 can contain a pre-trained model 206 and a test data set 208 that was used to train the pre-trained model 206. Furthermore, the DFOS signal analyzer 212 can comprise a pulsed source 214 and a detector 216. In addition, the DFOS signal analyzer 212 and the accelerometers 218 can be operationally coupled to the processor 210, which can also be communicatively / operationally coupled to the memory 204 and the I / O interface 220.

[0027] In an implementation, the Processor 210 can be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuits, and / or any devices that process signals based on operating instructions. Among other capabilities, the Processor 210 can be configured to retrieve and execute computer-readable instructions stored in Memory 204. The I / O Interface 220 can include a variety of software and hardware interfaces, such as a web interface, a graphical user interface, and the like.

[0028] As in Fig.As described in Figure 1, the DFOS 112 can be attached to the power rail 110 of the battery pack 104. The DFOS 112 can be operationally coupled to the DFOS signal analyzer 212. The pulsed source 214 of the DFOS signal analyzer 212 can generate photon pulses and transmit the generated photon pulses through the DFOS 112. Due to the oscillatory motion, a large number of photons can be backscattered among the photons passing through the DFOS 112. The backscattered photons can be detected by the detector 216, and information about the backscattered photons can be received by the processor 210 as a first signal. In an exemplary embodiment, the photons passing through the DFOS 112 can be backscattered based on Rayleigh and Brillouin scattering, as described in Figure 1. Fig.Figure 3 illustrates this. From the received first signal, the processor 210 can determine the first oscillation frequency (F1) corresponding to the joints on the busbar 110 of the plurality of battery cell terminals 108. The processor 210 can further determine an intensity (T) of the backscattered plurality of photons as a function of the wavelength (λ) and can then determine from the determined intensity a strain induced in the DFOS 112 due to the oscillatory motion of the joints on the busbar 110 of the plurality of battery cell terminals 108.

[0029] Subsequently, the processor 210 can receive the second signal from the accelerometers 218, which are mounted above the battery pack 102 and the suspension unit of the vehicle 102. The processor 210 can then determine the second vibration frequency (F2) from the received second signal. After determining the first vibration frequency (F1), the strain induced in the DFOS 112, and the second vibration frequency (F2), the processor 210, using the pre-trained model 206, can correlate the first vibration frequency (F1), the strain induced in the DFOS 112, and the second vibration frequency (F2) with the test data set 208 to monitor the condition of the joints in real time.

[0030] In an exemplary embodiment, the pre-trained model 206 can be a mixed-effects model described by the following equation (1) y=βo+∑βixi+γ+ε

[0031] Here, y is the response variable. β o is the global intersection x i is the measured value of the variable with fixed effect i th , β i is the expected additive change caused by the value of each of the fixed-effect variables, γ is a drawing from the distribution of the means of the categories for a normally distributed variable with random effect, and ε is a selection from the normal distribution of residuals

[0032] In an exemplary embodiment, the variables with a fixed effect can correspond to the first vibration frequency (F1) and the strain induced in the DFOS 112, and the variable with a random effect can correspond to the second vibration frequency (F2).

[0033] The pre-trained model 206 can be trained to predict at least a qualitative state of the joints and a quantitative degree of joint degradation. For example, the pre-trained model 206 can output whether the current state of the joints is "good" or "bad," or it can output a "percentage degree of joint degradation," or a combination thereof. Specifically, if the pre-trained model 206 provides a qualitative output—that is, if the pre-trained model 206 predicts the state of the joints as "good" or "bad"—it can incorporate a threshold for joint degradation based on battery type, welding materials, connection method, busbar materials, and welding type.

[0034] To train the model, a variety of trials can be conducted, with the joints being subjected to a variety of test conditions in each trial, including at least the following: one or more road types, one or more battery charging conditions, one or more battery aging conditions, one or more battery discharge conditions, and one or more driving profiles. One or more exemplary subcategories for each of the multiple test conditions are shown in Table 1 below. Table 2 - Exemplary subcategories for the individual test conditions Test conditions Subcategories Types of roads High-speed tracks, slow-speed tracks, off-road tracks, fatigue tracks, endurance tracks Battery aging conditions Start of service life; country-specific warranty periods (2 to 4 years); special warranty periods for individual components. In this case, the battery (8 years); end of service life Battery charging conditions Alternating current (AC), Direct current (DC) Battery discharge conditions 80% to 20% state of charge (SoC); 50% to 20% SoC; 100% to 0% SoC Drive profile Worldwide Harmonised Test Procedure for Light Vehicles (WLTP), Vmax

[0035] Furthermore, each test can encompass several frequency ranges between 7 Hz and 200 Hz, and each frequency range can be assigned a corresponding acceleration value that acts on a vehicle during the test, as shown in Example Table 2 below. Table 2: Frequency range and corresponding acceleration value Frequency range Acceleration value applied to the vehicle 7Hz - 18Hz 1G 18Hz - 50Hz Peak acceleration gradually increased to 8 G at 50 Hz 50Hz - 200Hz Peak acceleration of 8 G up to 200 Hz

[0036] Each trial during the test can then yield a quantitative degradation score, indicating the degree of joint degradation and providing insight into the joint's condition. An example test dataset is shown in Table 3 below. Table 3 - Exemplary test data set Type of road Drive profile 1 Frequency range Exposure by DFOS Condition of the joints (percentage of degradation) High-speed rail line WLTP Any value between 7Hz - 200Hz Any value between -300 and 300 0 High-speed rail line Vmax 20 Slow-speed section WLTP 40 Slow-speed section Vmax 60 Off-road track WLTP 60 Off-road track Vmax 80

[0037] In real time, the processor 210, using the pre-trained model 206, can correlate the fixed-effect and random-effect variables with the test data set 208 based on equation (1) described above and taking into account various parameters such as battery type, welding materials, connection method, busbar material, and welding type according to battery set 104, in order to obtain the value of the response variable "y". The response variable "y" can indicate at least one of the following values: qualitative condition of the joints and quantitative degree of joint deterioration.

[0038] The condition of the joints can be communicated to the driver of vehicle 102 via the I / O interface 220 with appropriate displays / alarms if the condition of the joints deteriorates beyond a certain critical value. Thus, system 202 can enable real-time monitoring of the joint condition based on the varying vibrations of vehicle 102 during road traffic.

[0039] Fig.Figure 4 illustrates, by means of a flowchart, an exemplary method 400 for monitoring the condition of joints on busbars of battery cell tabs in a vehicle according to an embodiment of the present invention. Method 400 can also be described in the general context of computer-executable instructions. In general, computer-executable instructions can include routines, programs, objects, components, data structures, procedures, modules, and functions that perform specific functions or implement specific abstract data types.

[0040] The order in which Procedure 400 is described is not to be understood as a restriction, and any number of the described procedure blocks can be combined in any order to carry out the procedure. Furthermore, individual blocks can be omitted from the procedures without this being contrary to the spirit and scope of the subject matter described.

[0041] In step 402, the method 400 can include receiving a first signal from a distributed fiber optic sensor (DFOS) 112, which is arranged over at least one of the following elements: a busbar 110 and a plurality of battery cell terminals 108, each connecting a battery cell to the busbar 110. In an exemplary embodiment, the first signal can be received by the processor 210. In an exemplary embodiment, a pulsed source 214 of a DFOS signal analyzer 212 can generate photon pulses and transmit the generated photon pulses through the DFOS 112. Due to the oscillatory motion, a plurality of photons can now be backscattered among the photons moving through the DFOS 112. The backscattered photons can be detected by the detector 216, and information about the backscattered photons can be received by the processor 210 as a first signal.

[0042] In step 404, the procedure 400 can include determining a first oscillation frequency (F1) from the received first signal, which corresponds to the joints and the strain induced in the DFOS 112 due to a vibrational movement of the joints on the busbar 110 of the battery cell covers 108. As an example, to determine the strain induced in the DFOS 112, the processor 210 can first determine an intensity of the backscattered multitude of photons as a function of the wavelength and then determine the strain induced in the DFOS 112 from this intensity.

[0043] In step 406, the procedure 400 can include receiving a second signal from the suspension unit and battery pack 104 of the vehicle 102. In one exemplary aspect, the second signal can be received by the processor 210 from the accelerometers 114, 218, which are attached to the battery pack 104 and the suspension unit of the vehicle 102.

[0044] In step 408, the procedure 400 can include determining a second oscillation frequency (F2) from the received second signal. As an example, the processor 210 can be used to determine the second oscillation frequency (F2).

[0045] In step 410, the procedure 400 can include correlating the determined values ​​of the first frequency (F1), the second frequency (F2), and the induced strain with a test dataset 208 using a pre-trained model 116, 206. In one exemplary aspect, the correlation can be performed by the processor 210 using the pre-trained model 116, 206. Furthermore, in another exemplary aspect, the pre-trained model 116, 206 can be trained by conducting a variety of experiments, in each of which the joints can be subjected to a variety of test conditions, including at least the following: one or more road types, one or more battery charging conditions, one or more battery aging conditions, one or more battery discharge conditions, and one or more driving profiles.Furthermore, each test can span multiple frequency ranges between 7 Hz and 200 Hz, and each frequency range can be associated with a corresponding acceleration value applied to a vehicle during the test. As an example, the test data set 208 can contain a joint condition in the form of a deterioration percentage for various combinations of the multitude of test conditions. Using the pre-trained model 116, 206, the processor 210 can correlate the fixed-effect variables (first vibration frequency (F1) and the strain induced in the DFOS 112) and the random-effect variables (second vibration frequency (F2)) with the test data set 208 based on equation (1) described above and taking into account various parameters such as battery type, welding materials, joining methods, busbar material, and welding type according to the battery set 104.

[0046] In step 412, the procedure 400 can include monitoring the condition of the joints on the busbar 110 of the battery cell covers 108 based on the correlation. As an example, the processor 210 can determine the value of the response variable “y” based on the correlation described above. The response variable “y” can indicate a qualitative condition of the joints in the form of either “good” or “bad”.

[0047] In step 414, procedure 400 may include determining the degree of joint deterioration based on monitoring. As an example, the response variable “y” may also indicate the quantitative degree of joint deterioration as a percentage of the deterioration or in other suitable terms such as an absolute value or grade, etc.

[0048] The steps described serve to illustrate the exemplary embodiments shown, and it should be assumed that ongoing technological development will change the way certain functions are performed. These examples are for illustrative purposes only and do not represent a limitation. Furthermore, the boundaries of the function blocks have been arbitrarily defined here for the sake of simplicity. Other boundaries can be defined as long as the specified functions and relationships are appropriately implemented.

[0049] Furthermore, one or more computer-readable storage media can be used in the implementation of embodiments according to the present invention. A computer-readable storage medium refers to any type of physical storage on which information or data that can be read by a processor can be stored. Thus, a computer-readable storage medium can store instructions for execution by one or more processors, including instructions that cause the processor(s) to perform steps or stages corresponding to the embodiments described herein. The term "computer-readable medium" should be understood to include tangible objects and exclude carrier waves and transient signals, i.e., it is non-volatile.Examples include random access memory (RAM), read-only memory (ROM), volatile memory, non-volatile memory, hard disks, CD-ROMs, DVDs, flash drives, floppy disks and all other known physical storage media.

[0050] Suitable processors include, for example, a general-purpose processor, a special-purpose processor, a conventional processor, a digital signal processor (DSP), a graphics processing unit (GPU), multiple microprocessors, one or more microprocessors in conjunction with a DSP core, a control unit, a microcontroller, application-specific integrated circuits (ASICs), FPGA (field programmable gate array) circuits, any other type of integrated circuit (IC) and / or a state machine. The advantages of the embodiment of the present invention are described herein.

[0051] In one embodiment, the present invention provides a system for predicting / monitoring / determining the condition of the joints within the battery pack in real time while the vehicle is in operation.

[0052] In a further embodiment, the present invention provides a system that accurately determines the effect of vibration movements on the condition of the joints within the battery pack by using a distributed fiber optic sensor within the battery pack.

[0053] In a further embodiment, the present invention provides a system that increases the safety of the battery pack and consequently of the vehicle by mitigating short-circuit scenarios of the battery pack due to the separation of the joints and thereby avoiding thermal spin-out scenarios. REFERENCE MARK 102 vehicles 104 battery pack 106 battery cells 108 battery cell connections 110 busbar 112, 212 Distributed fiber optic sensor 114, 218 accelerometers 116, 206 Pre-trained model 202 System 204 storage 208 Test data set 210 processor 214 Pulsed Source 214 Detector 220 I / O interface 400 procedures 402-414 Procedure steps QUOTES INCLUDED IN THE DESCRIPTION

[0000] This list of documents cited by the applicant was automatically generated and is included solely for the reader's convenience. The list is not part of the German patent or utility model application. The DPMA accepts no liability for any errors or omissions. Cited patent literature

[0000] DE 102022204775A1

[0006]

Claims

[1] Method for monitoring the condition of joints on busbars (110) of battery cell terminals (108) in a vehicle (102), the method comprising: Receiving (402) a first signal from a distributed fiber optic sensor (DFOS) (112) arranged over at least one of the following elements: a busbar (110) and a plurality of battery cell terminals (108) connecting each battery cell (106) to the busbar (110); Determine (404), from the received first signal, a first oscillation frequency (F1) corresponding to the joints and the strain induced in the DFOS (112) due to an oscillatory movement of the joints on the busbar (110) of the battery cell tabs (108); Receipt (406) of a second signal from the suspension unit and battery pack (104) of the vehicle (102); Determination (408) of a second oscillation frequency (F2) from the received second signal; Correlate (410) the determined values ​​of the first frequency (F1), the second frequency (F2) and the induced strain with a test data set (208) using a pre-trained model (116, 206); Monitoring (412) the condition of the joints on the busbar (110) of battery cell tabs (108), based on the correlation; and Determination (414) of a degree of deterioration of the joints based on monitoring. [2] Method according to claim 1, wherein the method for determining the strain induced in the DFOS further comprises: Transmission of photon pulses from a pulsed source (214) through the DFOS (112); and Detecting a large number of photons backscattered by DFOS (112) by a detector (216). [3] Method according to claim 2, wherein the received first signal comprises information about the plurality of photons backscattered by the DFOS (112), and wherein the method for determining the strain from the received first signal further comprises: Determine, from the received first signal, an intensity of the multitude of photons backscattered by the DFOS (112) as a function of wavelength; and Determination of the strain induced in the DFOS based on the intensity (112). [4] Method according to claim 1, wherein the second oscillation frequency (F2) corresponding to the battery pack (104) and the suspension unit of the vehicle (102) is determined by analyzing the received second signal obtained from acceleration sensors (114, 218) installed on the battery pack (104) and the suspension unit of the vehicle (102). [5] Method according to claim 1, wherein the pre-trained model (116, 206) is trained on the basis of the test data set (208) comprising: a variety of quantitative joint deterioration scores indicating the condition of joints, obtained by subjecting the joints to a variety of test conditions in multiple frequency ranges, the variety of test conditions including at least: one or more types of roads, one or more battery charge levels, one or more conditions that contribute to battery aging, and one or more battery discharge states, and one or more drive profiles where each frequency range is linked to a corresponding acceleration value that acts on the vehicle during the test. [6] System (202) for monitoring the condition of joints on the busbar (110) of battery cell terminals (108) in a vehicle (102), the system (202) comprising: a memory (204); and a processor (210) that is operationally coupled to the memory (204), wherein the processor (210) is configured to: to receive a first signal from a distributed fiber optic sensor (DFOS, 112) arranged over at least one of the following elements: a busbar (110) and a plurality of battery cell terminals (108) connecting each battery cell (106) to the busbar (110); to determine from the received first signal a first oscillation frequency (F1) which corresponds to the joints and the strain induced in the DFOS (112) due to an oscillatory movement of the joints on the busbar (110) of the battery cell tabs (108); to receive a second signal from the suspension unit and battery pack (104) of the vehicle (102); to determine a second oscillation frequency (F2) from the received second signal; to correlate the determined values ​​of the first frequency (F1), the second frequency (F2) and the induced strain with a test data set (208) using a pre-trained model (116, 206); to monitor the condition of the joints on the busbar (110) of the battery cell tabs (108) based on the correlation; and to determine the degree of joint deterioration based on monitoring. [7] System according to claim 6, wherein the system for determining the strain induced in the DFOS (112) further comprises: a DFOS signal analyzer (212) comprising a pulsed source (214) and a detector (216), wherein the DFOS signal analyzer (212) is operationally coupled to the DFOS (112) and the processor (210), and wherein the DFOS signal analyzer (212) is configured to: to transmit photon pulses through the DFOS (112); and to detect a large number of photons backscattered by DFOS (112). [8] System according to claim 7, wherein the first signal received by the processor (210) comprises information about the plurality of photons backscattered by the DFOS (112), and wherein the processor (210) is further configured to determine the strain induced in the DFOS (112) such that it: from the received first signal, an intensity of the multitude of photons backscattered by the DFOS (112) is determined as a function of the wavelength; and based on the intensity, the strain induced in the DFOS (112) is determined. [9] System according to claim 6, further comprising: Accelerometers (114, 218) installed on the battery pack (104) and the suspension unit of the vehicle (102) to provide the second signal associated with the second vibration frequency (F2). [10] System according to claim 6, wherein the processor (210) is further configured to train the model on the basis of the test data set (208) which comprises the following: a variety of quantitative joint deterioration scores indicating the condition of joints, obtained by subjecting the joints to a variety of test conditions in multiple frequency ranges, the variety of test conditions including at least: one or more types of roads, one or more battery charge levels, one or more conditions that contribute to battery aging, one or more battery discharge states, and one or more drive profiles where each frequency range is linked to a corresponding acceleration value that acts on the vehicle during the test.

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