Sensor assembly for a battery of a vehicle, control method thereof, battery assembly and vehicle

Abstract

The invention relates to a sensor assembly for a battery of a vehicle, a control method thereof, a battery assembly and a vehicle. The sensor assembly (26) comprises a plurality of first sensors (28), each first sensor being configured to measure a current. Each first sensor (28) is associable with a single battery cell (20) or a group of battery cells of a string of battery cells (22). The sensor assembly (26) further comprises a second sensor (30) configured to measure a current. The second sensor (30) is associable with the string of battery cells (22). The first sensors (28) and the second sensor (30) have different measurement accuracies. The first sensors (28) and the second sensor (30) are communicatively connected. Additionally, a battery assembly (18) for a vehicle is described. Furthermore, a vehicle is shown. Moreover, a method for controlling the sensor assembly (26) is presented.

Description

Technical Field

[0001] This disclosure relates to a sensor assembly for a battery cell string in a battery pack for a vehicle.

[0002] Furthermore, this disclosure relates to a battery assembly for a vehicle.

[0003] Additionally, this disclosure relates to a vehicle.

[0004] Additionally, this disclosure relates to a method for controlling a sensor assembly. Background Technology

[0005] Recent developments in the field of battery electric vehicles demonstrate the importance of using various monitoring systems to assess the health of battery systems over time. This becomes particularly crucial during the charging and discharging of battery systems. Due to the increased energy density in these systems, early detection of potential defects is essential to ensure system safety. Such defects can include overheating, which could damage the system. Simultaneously, battery systems should be kept as simple as possible to facilitate production, maintenance, and repair. Summary of the Invention

[0006] Therefore, the purpose of this disclosure is to resolve or mitigate the conflict between high reliability and structural simplicity. In other words, reliable operation of the battery system should be ensured while maintaining the simplicity of its structure.

[0007] The problem is at least partially solved or mitigated by the subject matter of the independent claims of this disclosure, wherein further examples are incorporated in the dependent claims.

[0008] According to a first aspect, a sensor assembly for a battery cell string of a battery pack for a vehicle is provided. The sensor assembly includes a plurality of first sensors. Each first sensor is configured to measure current. Furthermore, each first sensor can be associated with a single battery cell or a group of battery cells in the battery cell string. The sensor assembly also includes a second sensor configured to measure current. The second sensor can be associated with the battery cell string. The first and second sensors have different measurement accuracies. The first and second sensors are communicatively connected. In this context, a battery cell string can be understood as a plurality of battery cells electrically connected in series with each other. Additionally, the battery cells of the battery cell string can be arranged side-by-side along an arrangement direction, for example, stacked on top of each other. The first sensors can be designated as cell-level sensors. This means that each first sensor can measure the current of an associated single battery cell or a group of associated battery cells. Thus, each first sensor measures the current of at least one battery cell within the battery cell string. The second sensor can be considered as a battery string-level sensor and / or a main sensor. The second sensor can be arranged at a different location than the first sensors. The second sensor can be located on the main board of the sensor assembly. The second sensor can measure the current of the battery cell string as a whole. Measurement accuracy can be understood as the degree to which the measurement conforms to a standard or true value. In other words, it can represent the degree of accuracy or correctness of current measurement. Measurement accuracy can also be considered as measurement precision. Using multiple first and second sensors to measure current at different locations can improve measurement accuracy. This is because multiple sensors measuring the current at various locations in the battery cell string allows for more accurate monitoring over time. It should be understood that, ideally, the current in each cell of the battery cell string is the same due to the series connection of the battery cells. Furthermore, if one of the multiple first sensors fails, the sensor assembly can still use measurement data from the other first sensors to provide an estimate of the measurement result of the failed first sensor. Therefore, the overall measurement reliability is high. In addition, first and second sensors with different measurement accuracies can help detect measurement errors. If either the second or first sensor fails, the sensor assembly can still identify potential anomalies in the current measurement based on the measurements of the remaining sensors. In other words, the fact that multiple first sensors are used and second sensors are used at the battery string level provides redundancy within the sensor assembly. From a structural point of view, using sensors with different measurement accuracies (i.e., a combination of sensors with relatively high measurement accuracy and sensors with relatively low measurement accuracy) can be advantageous because sensors with relatively low measurement accuracy can be simpler to manufacture than those with relatively high measurement accuracy. Furthermore, sensors with lower measurement accuracy can allow for easier production, maintenance, or repair of sensor assemblies.Furthermore, sensors with lower measurement accuracy can be cheaper than those with higher measurement accuracy. In this context, the difference in measurement accuracy can be compensated for by allowing the corresponding less accurate sensor to be calibrated and validated based on measurements from the more accurate sensor. Therefore, the sensor assembly is highly accurate overall.

[0009] According to the example, the measurement accuracy of the first sensor is lower than that of the second sensor. In the example, the measurement accuracy can be represented by a drift tendency. This means that the first sensor may have a higher drift tendency than the second sensor. This drift can be, for example, drift with temperature (i.e., drift caused by changing temperature), drift with use (i.e., drift caused by the use of the sensor), and / or drift with time (i.e., drift occurs over time). Therefore, using the second sensor, the drift of the first sensor can be compensated for, for example, by recalibrating based on the measurement results of the second sensor.

[0010] As illustrated in the example, the first sensor uses a first sensor technology, and the second sensor uses a second sensor technology different from the first. Typically, different sensor technologies have different measurement strengths or advantages. Therefore, using different sensor technologies can lead to more accurate and reliable measurements because the different technologies can be used complementaryly. Note that different sensor technologies may also have different sources of error. This can further improve the reliability of the sensor assembly, as different measurements can reduce the number of erroneous measurements. Furthermore, some sensor technologies may be advantageous from a manufacturing, maintenance, or repair perspective. Additionally, some sensor technologies may simply be cheaper than others. In summary, using different sensor technologies allows for the combination of the advantages of different sensor technologies while compensating for their disadvantages.

[0011] In the example, the first sensor technology and / or the second sensor technology include Hall sensors, Rogowski coils, shunt resistors, and / or thermal sensors.

[0012] According to the example, the first and second sensors are wirelessly connected to each other. Wireless connection can be achieved using radio signals, Bluetooth signals, and / or WiFi signals. Wireless connection has the following advantages: the first and second sensors can be independently positioned without being restricted by cables. Therefore, the flexibility of the first and second sensors can be improved. Furthermore, since there is no need to lay cables for the communication connection between the first and second sensors, the assembly process of the sensor assembly can be facilitated. In addition, wireless connection is less susceptible to mechanical damage compared to cables.

[0013] According to the example, the measurement accuracy of the first sensor deviates from that of the measurement accuracy of the second sensor by at least 5%.

[0014] According to a second aspect, a battery assembly for a vehicle is provided. The battery assembly includes at least one sensor assembly as described in the first aspect and a plurality of battery cells arranged in at least one battery cell string. Each first sensor of the sensor assembly is associated with a single battery cell or a group of battery cells in the battery cell string. A second sensor of the sensor assembly is associated with the battery cell string. It should be noted that more than one battery cell string may exist in the battery assembly. If so, at least some of the battery cell strings may be equipped with the sensor assembly according to the first aspect. Due to the fact that the sensor assembly allows for high accuracy and reliability of current measurement, this characteristic also applies to battery assemblies for vehicles. Based on this, the performance of the battery assembly can be further improved by using multiple first and second sensors, as control of such a battery assembly can be improved. This is because the improved accuracy and reliability of the sensor assembly can facilitate the use of measurement data in a control unit. This also applies to monitoring the health status of the battery assembly.

[0015] In the example, multiple battery cells can be cylindrical battery cells or prismatic battery cells.

[0016] According to the example, each battery cell string is equipped with a sensor component of the first aspect. In other words, one sensor component is assigned to one battery cell string, enabling accurate measurement of the current. This is because at least two sensor components are implemented when using at least two battery cell strings.

[0017] In the example, the battery assembly includes at least two sensor assemblies. These at least two sensor assemblies can be communicatively connected to each other. If one of the first or second sensors in a single sensor assembly fails, the other second and first sensors in the other sensor assemblies can still utilize measurement data from the other battery cell strings. Therefore, the overall measurement reliability can be further enhanced.

[0018] According to a third aspect, a vehicle is provided. The vehicle includes a battery assembly according to a second aspect. Therefore, the vehicle also includes at least one sensor assembly according to a first aspect of this disclosure. Due to the fact that the sensor assembly allows for high accuracy and reliability of current measurement, this characteristic also applies to the battery assembly, and therefore to the vehicle. Based on this, using multiple first and second sensors can further lead to improved performance of the battery assembly and the vehicle. This is because of the improved accuracy and reliability of the sensor assembly, and therefore the vehicle can facilitate the use of measurement data in a control unit. This also applies to monitoring the health status of the battery assembly, and therefore monitoring the health status of the vehicle.

[0019] According to a fourth aspect, a method for controlling a sensor assembly of the first aspect is provided. The method includes calibrating at least one of the first sensors based on measurements from a second sensor. In this case, the measurement accuracy of the second sensor is higher than that of the first sensor. Therefore, when calibrating at least one first sensor based on measurements from the second sensor, the measurements of at least one first sensor are adjusted and verified using precise measurement data from the second sensor. This ensures that at least one first sensor provides accurate and reliable measurement data. Calibration has the effect of providing accurate measurements from the first sensors because the errors and inaccuracies of at least one first sensor are corrected by precise data from the second sensor. Furthermore, calibration keeps at least one first sensor up-to-date, thereby further improving the reliability of at least one first sensor. Additionally, calibration helps minimize long-term drift and / or deviation of the measurement data of at least one first sensor. Therefore, the measurement stability of at least one first sensor can be improved. Simultaneously, the positive effects of a sensor with relatively low measurement accuracy (e.g., simple structure, ease of manufacture, maintenance, or repair, or simple low cost) can be utilized.

[0020] Based on the examples, calibration can be time-triggered, event-triggered, or periodic. This implies three alternatives. The first alternative includes time-triggered calibration. In this context, time-triggered can be understood as calibration occurring after a predefined time has elapsed. This ensures that the first sensor is continuously checked and adjusted, regardless of sudden changes in the external environment or measurement data. This has the effect of achieving consistent accuracy for at least one first sensor. Furthermore, time-triggered calibration allows for automatic adjustment, thereby reducing complexity and improving calibration efficiency. The second alternative includes event-triggered calibration. In this context, event-triggered can be understood as calibration being initiated due to the occurrence of a specific predefined event and / or condition and / or situation. Such a predefined event and / or condition and / or situation could be reaching a predefined current value. Additionally or alternatively, event-triggered calibration may include detecting differences in measurement data or reaching certain operational thresholds. This has the effect of performing calibration precisely when needed, resulting in immediate correction of inaccuracies in the measurement data of at least one first sensor. Furthermore, event-triggered calibration only occurs when needed, thereby improving calibration performance and efficiency. The third alternative includes periodic calibration. In this context, the rule can be viewed as calibration occurring according to a predefined pattern or rule. This rule can involve a schedule. Therefore, at least one first sensor can be continuously monitored and adjusted to maintain its accuracy. Periodic calibration can help provide consistent accuracy for at least one first sensor by making necessary adjustments. Periodic calibration can further improve the reliability of at least one first sensor because calibration is predictable, thus maintaining consistent measurement data.

[0021] According to the example, the triggering event involves a deviation of the measurement result of the first sensor from the measurement result of the second sensor exceeding a predefined calibration threshold. This means that event-triggered calibration can be performed whenever a significant difference occurs between the measurement data of at least one first sensor and the measurement data of the second sensor. This has the following effects: the accuracy of at least one first sensor can be further improved because calibration is performed immediately when the measurement data shows an unexpected deviation. Furthermore, this calibration can be viewed as a dynamic adjustment of at least one first sensor, allowing it to adjust its measurement data relative to specific predefined events and / or conditions. Therefore, calibration accuracy can be further enhanced.

[0022] As illustrated in the example, an artificial neural network is used to determine the triggering event. Using an artificial neural network in this context helps perform calibration based on complex patterns and anomalies identified by machine learning methods. Artificial neural networks can allow for the detection of more precise and complex patterns, thereby further improving calibration accuracy. Additionally, the calibration of sensor components can dynamically adapt to new conditions and measurement data as the artificial neural network continuously trains its model. Therefore, the adaptability and reliability of the calibration can be further enhanced.

[0023] It should be noted that the above examples can be combined with each other, regardless of the aspects involved.

[0024] These and other aspects of this disclosure will become apparent from the examples described below and will be illustrated with reference to the examples described below. Attached Figure Description

[0025] Examples of this disclosure will now be described with reference to the following figures.

[0026] Figure 1 A vehicle according to the present disclosure is shown, having a drive unit including a battery assembly according to the present disclosure, wherein the battery assembly includes three sensor assemblies according to the present disclosure, and wherein each sensor assembly is controlled using a method according to the present disclosure.

[0027] Figure 2 Shown in a more detailed view Figure 1 The vehicles, in which a bottom-up view perspective was used, and

[0028] Figure 3 It is illustrated in a more detailed manner. Figure 2 The drive unit. Detailed Implementation

[0029] The accompanying drawings are merely illustrative and are intended to illustrate examples of this disclosure only. Identical or equivalent elements are generally referred to by the same reference numerals.

[0030] Figure 1 A vehicle 10 is shown, including a drive unit 12, which may also be referred to as a drivetrain.

[0031] The drive unit 12 includes a motor 14.

[0032] Motor 14 can actuate drive shaft 16, causing the two rear wheels to rotate to drive vehicle 10 (see...). Figure 2 ).

[0033] Therefore, in this example, vehicle 10 includes rear-wheel drive.

[0034] The drive unit 12 also includes a battery assembly 18, which may also be referred to as a battery system.

[0035] The electrical energy stored in the battery assembly 18 can be used to power the motor 14.

[0036] Therefore, in this example, vehicle 10 is a battery-electric vehicle.

[0037] The battery assembly 18 includes multiple battery cells 20.

[0038] In this example, multiple battery cells 20 are arranged in three battery cell strings 22 (see [link]). Figure 3 ).exist Figure 3 In the example, each battery cell string 22 extends in a top-to-bottom direction.

[0039] It should be noted that other examples may exist in which multiple battery cells 20 form different numbers of battery cell strings 22.

[0040] Battery assembly 18 also includes multiple unit-level inverter units 24.

[0041] In this example, each battery cell 20 of each corresponding battery cell string 22 is equipped with and electrically connected to a cell-level inverter cell 24.

[0042] Each unit-level inverter unit 24 is electrically connected to its associated battery unit 20 and motor 14. Therefore, direct current (DC) power from the associated battery unit 20 is input to the unit-level inverter unit 24. The unit-level inverter unit is configured to convert DC power to alternating current (AC) power and then supply the AC power to the motor 14.

[0043] The battery assembly 18 also includes three sensor assemblies 26.

[0044] Each battery cell string 22 is equipped with a sensor assembly 26.

[0045] Each sensor assembly 26 includes a plurality of first sensors 28 configured to measure current.

[0046] Each first sensor 28 of each sensor assembly 26 is associated with a single battery cell 20 of the corresponding battery cell string 22.

[0047] This means that each first sensor 28 is configured to measure the current entering and / or leaving the corresponding battery cell 20.

[0048] Note that even if they are represented separately, each first sensor 28 may also be part of a corresponding cell-level inverter unit 24 electrically connected to the same battery cell 20.

[0049] Each sensor assembly 26 also includes a second sensor 30 configured to measure current.

[0050] Each second sensor 30 is arranged on the motherboard 32.

[0051] Each of the sensor assemblies 26 has a second sensor 30 associated with a corresponding battery cell string 22.

[0052] This means that each second sensor 30 is configured to measure the current entering and / or leaving the associated battery cell string 22.

[0053] In this example, the first sensor 28 uses a first sensor technology, and the second sensor 30 uses a second sensor technology that is different from the first sensor technology.

[0054] Therefore, the first sensor 28 and the second sensor 30 of each sensor assembly 26 have different measurement accuracies.

[0055] In this example, measurement accuracy can be represented by drift tendency. This means that the first sensor 28 has a higher drift tendency than the second sensor 30. Therefore, the measurement accuracy of the second sensor 30 is higher than that of the first sensor 28.

[0056] The first sensor 28 and the second sensor 30 of each sensor assembly 26 are communicatively connected to each other.

[0057] Note that the first sensor 28 and the second sensor 30 of all three battery cell strings 22 can be communicatively connected together.

[0058] More specifically, in this example, the first sensor 28 and the second sensor 30 are wirelessly connected.

[0059] Each sensor assembly 26 can be controlled in a manner that includes calibrating at least one of the first sensors 28 based on measurements from the second sensor 30. In this context, the second sensor 30, associated with the same battery cell string 22 as the first sensor 28 to be calibrated, is used for calibration.

[0060] This calibration may be particularly necessary when the measurement value of at least one of the first sensors 28 deviates from the measurement value of the second sensor 30.

[0061] Therefore, the accuracy of the measurement of at least one of the first sensors 28 can be aligned with the measurement of the second sensor 30.

[0062] Therefore, in this example, calibration is event-triggered.

[0063] The triggering event occurs when the measurement result of the first sensor 28 deviates from the measurement result of the second sensor 30 by more than a predefined calibration threshold.

[0064] In the example, the first sensor 28 measures the current leaving the corresponding battery cell 20. The second sensor 30 measures the current leaving the corresponding battery cell string 22. A trigger event occurs when the measurement results of the first sensor 28 and the second sensor 30 deviate from each other by at least a predefined calibration threshold (e.g., 10%).

[0065] In another example, an artificial neural network is used to determine the triggering event.

[0066] More specifically, the artificial neural network learns which deviations from normal measurements are significant or correlated. As a result, the artificial neural network can dynamically adjust predefined calibration thresholds to determine more precise triggering events.

[0067] Furthermore, the artificial neural network can detect inconsistencies between the measurements of the first sensor 28 and the second sensor 30. Therefore, once the inconsistent measurements exhibit a certain deviation pattern, the artificial neural network allows for calibration.

[0068] It should be understood that the same method can be performed on each of the first sensor 28 and the second sensor 30 in the battery cell string 22, so that each of the first sensor 28 in the three sensor assemblies 26 is finally calibrated.

[0069] As used herein, the phrase “at least one” when referring to a list of one or more entities should be understood to mean at least one entity selected from any one or more entities in the entity list, but not necessarily including at least one of each or every entity specifically listed in the entity list, and does not exclude any combination of entities in the entity list. This definition also allows for the optional presence of entities other than those specifically identified in the entity list referred to by the phrase “at least one,” whether related to or unrelated to those specifically identified entities. Thus, as a non-limiting example, “at least one of A and B” (or equivalently, “at least one of A or B”, or equivalently, “at least one of A and / or B”) could in one example mean at least one (optionally including more than one) A, without B (and optionally including entities other than B); in another example, at least one (optionally including more than one) B, without A (and optionally including entities other than A); and in yet another example, at least one (optionally including more than one) A and at least one (optionally including more than one) B (and optionally including other entities). In other words, the phrases “at least one,” “one or more,” and “and / or” are open-ended expressions that are both connected and separate in operation. For example, each of the expressions “at least one of A, B, and C,” “at least one of A, B, or C,” “one or more of A, B, and C,” “one or more of A, B, or C,” and “A, B, and / or C” can mean a single A, a single B, a single C, A and B together, A and C together, B and C together, A, B, and C together, and optionally any of the above combined with at least one other entity.

[0070] Based on the accompanying drawings, the disclosure, and the appended claims, those skilled in the art can understand and implement other variations of the disclosed examples in practice with respect to the claimed disclosure. In the claims, the word "comprising" does not exclude other elements or steps, and the indefinite articles "a" or "an" do not exclude multiple. A single processor or other unit can perform the functions of several items or steps recited in the claims. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used for benefit. Computer programs can be stored / distributed on suitable media, such as optical storage media or solid-state media provided with or as part of other hardware, but can also be distributed in other forms, such as via the Internet or other wired or wireless telecommunications systems. Any reference numerals in the claims should not be construed as limiting the scope of the claims.

[0071] List of reference numerals

[0072] 10 vehicles

[0073] 12 drive units

[0074] 14 Motors

[0075] 16 drive shafts

[0076] 18 Battery Components

[0077] 20 battery cells

[0078] 22 battery cell strings

[0079] 24 Inverter Units

[0080] 26 Sensor Components

[0081] 28 First Sensor

[0082] 30 Second sensor

[0083] 32 motherboard

Claims

1. A sensor assembly (26) for a battery cell string (22) of a battery pack (18) for a vehicle (10), the sensor assembly (26) comprising: Multiple first sensors (28), each first sensor (28) is configured to measure current, wherein each first sensor (28) is capable of being associated with a single battery cell (20) or a group of battery cells in the battery cell string (22), and A second sensor (30) is configured to measure current, wherein the second sensor (30) is capable of being associated with the battery cell string (22). The first sensor (28) and the second sensor (30) have different measurement accuracies, and the first sensor (28) and the second sensor (30) are communicatively connected.

2. The sensor assembly (26) according to claim 1, wherein, The first sensor (28) uses a first sensor technology, and the second sensor (30) uses a second sensor technology that is different from the first sensor technology.

3. The sensor assembly (26) according to claim 1 or 2, wherein, The first sensor (28) and the second sensor (30) are wirelessly connected to each other.

4. A battery assembly (18) for a vehicle (10), the battery assembly (18) comprising: - At least one sensor component (26) according to any one of the preceding claims. - Multiple battery cells (20), said multiple battery cells being arranged in at least one battery cell string (22), Each first sensor (28) of the sensor assembly (26) is associated with a single battery cell (20) or a group of battery cells in the battery cell string (22), and The second sensor (30) of the sensor assembly (26) is associated with the battery cell string (22).

5. The battery assembly (18) according to claim 4, wherein, Each battery cell string (22) is equipped with a sensor assembly (26) according to any one of claims 1 to 3.

6. A vehicle (10) comprising a battery assembly (18) according to claim 4 or 5.

7. A method for controlling a sensor assembly (26) according to claims 1 to 3, the method comprising calibrating at least one of the first sensors (28) based on measurements from the second sensor (30).

8. The method according to claim 7, wherein, The calibration is time-triggered, event-triggered, or periodic.

9. The method according to claim 8, wherein, The triggering event involves the measurement result of the first sensor (28) deviating from the measurement result of the second sensor (30) by more than a predefined calibration threshold.

10. The method according to claim 8 or 9, wherein, Artificial neural networks are used to determine triggering events.

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