Battery diagnostic procedures in a motor vehicle

Abstract

Method for battery diagnostics in a motor vehicle, in which at least one sensor signal (10, 12) which carries information on the severity of an accident of the motor vehicle is evaluated in order to classify the accident and, on the basis of this classification, to classify a possible damage to a battery caused by the accident using a classification algorithm (24) and, depending on this classification, to take at least one measure.

Description

[0001] The invention relates to a method for battery diagnostics in a motor vehicle and an arrangement for carrying out the method. State of the art

[0002] Vehicles with electric drive systems, such as electric and hybrid vehicles, use high-performance batteries, also known as high-voltage batteries or high-voltage traction batteries, to store electrical energy. Efficiency in storing and delivering electrical energy is a crucial characteristic of such high-voltage (HV) batteries.

[0003] It should be noted that aging and / or damage, for example from an accident, can cause a deterioration of this property. A decrease in efficiency directly impacts the vehicle's range. A diagnostic procedure for such a battery involves recording and evaluating electrical parameters of the battery to determine its characteristics.

[0004] German patent application DE 10 2013 201 451 A1 describes a method and a system for battery diagnostics. In this method, an amount ΔE of a theoretical energy balance based on a theoretical battery model is determined at two points in time defining a diagnostic period. Furthermore, the amount of energy drawn and the amount of energy supplied are determined during the diagnostic period. An efficiency factor is then calculated, which allows for an assessment of the battery's state of health. Disclosure of the invention

[0005] Against this background, a method according to claim 1 and an arrangement with the features of claim 12 are presented. Further advantages and embodiments of the invention will become apparent from the dependent claims and the description.

[0006] The presented method is used for battery diagnostics in a motor vehicle. This method evaluates at least one sensor signal, carrying information about the severity of a vehicle accident, to classify the accident. Based on this classification, a classification algorithm is used to estimate potential battery damage caused by the accident, specifically classifying this potential damage. Then, at least one measure is taken to prevent potential harm to persons and the vehicle.

[0007] Therefore, actual battery damage is not directly determined; instead, damage is assumed and assigned to a category through classification. This classification can utilize data from previous accidents. The classification algorithm can also be designed as an adaptive system.

[0008] The procedure involves, in particular, a diagnosis of the battery in a motor vehicle equipped with an electric drive, where the battery is designed to supply the drive with electrical energy; that is, the battery is typically a high-voltage (HV) battery. Performing a diagnosis means determining the battery's condition by evaluating at least one sensor signal and classifying the severity of the accident based on this signal. The diagnosis thus includes classifying the severity of the accident to infer the battery's condition and to classify any potential battery damage.

[0009] The presented method assesses the severity of battery damage after and / or during an accident. If only minor or no accident damage to the battery system is expected, further driving may be permitted. In this context, the following points are referred to: Fig. 1 referred.

[0010] In cases of moderate accident severity where battery damage may occur, a self-diagnosis of the battery is performed. The result determines whether limited continued operation, i.e., "limp home" mode (no charging / reduced discharge power), is possible. After an inspection at the workshop, full battery performance can be restored.

[0011] Therefore, in the event that the accident is classified as medium severity, a self-diagnosis of the battery is performed. This self-diagnosis can determine any self-discharge of the battery within a specific diagnostic period and / or check individual battery cells, in particular all battery cells, for high-frequency voltage fluctuations.

[0012] The categories to which the battery can be assigned are as follows: minor damage, moderate damage, severe damage. The assignment to these categories is called classification.

[0013] The method can evaluate at least one sensor signal from at least one sensor assigned to an airbag of the motor vehicle. Alternatively or additionally, at least one sensor signal from at least one battery sensor assigned to the battery can be evaluated.

[0014] The sensor signal(s) can carry information about kinematic quantities, such as acceleration, or about other quantities, such as pressure.

[0015] The presented method uses a suitable classification algorithm to assess the severity of potential battery damage during or after an accident. If the assessment indicates that only minor damage is expected, it is not necessary to disconnect the battery permanently, for example, via a fuse. Thus, continued driving can typically be guaranteed without restrictions. If a moderate accident severity is detected, battery damage may occur. In this case, the battery performs an internal self-diagnosis. If this is successful, either full or limited battery power can be enabled, for example, as part of an emergency running function or "limp home" mode, i.e., no charging and reduced discharge power. If there is a high risk of battery damage, the battery is permanently disconnected from the vehicle.

[0016] The presented method can take into account that many modern vehicles with high-voltage (HV) batteries have an integrated HV deactivation function in the airbag control unit, which allows the HV system to be switched off in the event of an accident or crash. "Switching off" can mean disconnecting the HV battery from the vehicle's electrical system or disconnecting connections elsewhere in the HV system, for example, at the charging electronics. This disconnection can be reversible via contactors or irreversible via pyrotechnic actuators.

[0017] A separation can typically occur both during driving and during the charging process of the HV battery.

[0018] The following self-diagnoses are examples of feasible: During a diagnostic period, each cell is tested for excessive self-discharge. At the beginning of the self-discharge test, the cell voltage U(t) is measured. start) stored and this is compared to the cell voltage at the end of the diagnostic period U(t end ) compared. If the voltage difference exceeds a threshold THD, i.e. U(tstart)−U(tend)>THD, This suggests a battery defect, such as an internal short circuit. Alternatively, the cell voltage change caused by the relaxation process, typically the same for all cells, can be compensated for. The average cell voltage change of all cells can be calculated for this purpose using: Urelax=ϕU(tstart)−ϕU(tend) and subtracted from the voltage difference: U(tstart)−U(tend)−Urelax>THD.

[0019] The duration of the analysis period is adjustable, e.g., approximately 5 to 10 minutes. The duration can also depend on the severity of the accident.

[0020] Alternatively or additionally, each cell can be checked for unusual high-frequency voltage fluctuations during a diagnostic period. If the battery is not in use, no or only slight, slow voltage changes (relaxation) should be detected. Short, high-frequency voltage changes indicate internal battery short circuits. The duration of the analysis period is adjustable, e.g., approximately 5 to 10 minutes. The duration may also be related to the severity of the accident.

[0021] During self-diagnosis, a beep or light signal can warn other people that a battery self-diagnosis is in progress and that the battery has not been irreversibly disconnected.

[0022] If the self-diagnosis fails, another signal tone or light signal can warn other people that the battery is no longer safe and that there is a danger, e.g. from a fire and / or from insulation problems.

[0023] In the event of an expected serious battery damage, an audible or visual signal can immediately indicate a battery hazard.

[0024] The presented arrangement is designed to carry out the procedure described herein and is implemented, for example, in hardware and / or software. The arrangement can be integrated into a vehicle control unit or designed as such.

[0025] It is understood that the features mentioned above and those to be explained below can be used not only in the combination specified in each case, but also in other combinations or on their own, without departing from the scope of the present invention. Short description of the drawings Fig. Figure 1 shows a schematic representation of an exemplary classification or categorization of possible battery damage. Fig. Figure 2 shows a schematic, highly simplified representation of a vehicle with an arrangement for carrying out the described procedure. Fig. Figure 3 shows a possible sequence of the presented procedure in a flowchart. Embodiments of the invention

[0026] The invention is schematically illustrated with reference to embodiments in the drawings and is described in detail below with reference to the drawings.

[0027] Fig. Figure 1 illustrates the classification of potential battery damage using the presented battery diagnostic procedure. Inputs are first sensor signals 10 from airbag sensors and second sensor signals 12 from additional battery sensors. The first sensor signals 10 carry information on kinematic quantities and are fed into an airbag algorithm 14 assigned to an airbag control unit. This algorithm 14 processes the information. The second sensor signals 12 carry, for example, information on acceleration and pressure and are fed into a battery damage calculation unit 16. The information is also processed in this unit 16.

[0028] The Airbag algorithm 14 inputs initial information 20 about the accident or crash type and second information 22 about the accident severity into a classification algorithm 24 for classifying the accident. The calculation unit 16 also inputs information 26, based on the performed evaluation, into this classification algorithm 24.

[0029] The classification algorithm 24 then outputs a classification or rating 28 regarding the severity of the battery damage or a rating of the extent of the damage or impairment of the battery caused by the accident.

[0030] On the right side of the diagram are different battery damage categories: minor damage 50, moderate damage 52, and severe damage 54. The first category, minor damage, indicates (arrow 60) that no battery damage is expected and normal operation is possible. The second category, moderate damage 54, indicates (arrow 62) that a self-diagnosis of the battery must be performed before further operation is permitted. Limited operation may be possible during this self-diagnosis. The third category, severe damage 54, indicates (arrow 64) that serious or severe battery damage is expected and further operation is not possible initially. A warning signal may also be emitted to indicate this condition and, for example, to alert emergency services to the associated hazards.a fire is indicated. Disconnecting the battery from the vehicle's electrical system, for example via a contactor, is also possible.

[0031] In Fig. Figure 2 is a highly simplified schematic representation of a motor vehicle, which is designated with the reference numeral 100. This motor vehicle has an electric drive 102, which in turn is supplied by a battery 104.

[0032] Vehicle 100 is further equipped with a device 110 for carrying out the procedure described herein. Device 110 includes a classification algorithm 112, which enables an assessment, classification, or categorization of any potential damage to battery 104 caused by the accident. This takes into account the severity of the accident.

[0033] For this purpose, the classification algorithm 112 evaluates sensor signals 120, 122 or quantities derived from these sensor signals 120, 122 from an airbag sensor 130, which is assigned to an airbag control unit 132, and a battery sensor 140, which is assigned to the battery 104.

[0034] Fig.Figure 3 shows a flowchart illustrating an embodiment of the presented method. In a first step 150, an accident occurs. This is detected by suitable sensors in the vehicle, which, for example, record accelerations caused by the accident. In a step 152, both during and after the accident, sensor signals are evaluated and assessed. The severity of the accident is then classified based on the information obtained from these sensor signals. This allows for an estimation of the severity of potential battery damage in a step 154. This damage is then classified, i.e., assigned to predefined damage areas or categories. Finally, in a step 156, a suitable measure is taken, adapted to the selected category. QUOTES CONTAINED 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 10 2013 201 451 A1

[0004]

Claims

[1] Method for battery diagnosis in a motor vehicle (100), in which at least one sensor signal (10, 12, 120, 122) carrying information on the severity of an accident of the motor vehicle (100) is evaluated in order to classify the accident and, on the basis of this classification, to classify possible damage to a battery (104) caused by the accident by means of a classification algorithm (24, 112) and to take at least one measure depending on this classification. [2] Method according to claim 1, wherein the possible damage to the battery (104) is classified by means of the classification algorithm (24, 112) into one of the categories minor damage (50), moderate damage (52) and severe damage (54). [3] Method according to claim 2, wherein, in the event that the damage is classified in the medium damage category (52), a self-diagnosis of the battery (104) is carried out. [4] Method according to claim 3, wherein, as part of the self-diagnosis, a self-discharge of the battery (104) is determined in a diagnosis period. [5] Method according to claim 3 or 4, wherein, as part of the self-diagnosis, cells of the battery (104) are checked for high-frequency voltage fluctuations. [6] Method according to one of claims 3 to 5, wherein during the self-diagnosis a signal indicating the self-diagnosis is emitted. [7] Method according to claim 3, wherein a warning signal is emitted in the event that the damage is classified in the severe accident severity category (54). [8] Method according to one of claims 1 to 7, in which at least one sensor signal (10, 12, 120, 122) of at least one sensor (130) associated with an airbag control unit (132) of the motor vehicle (100) is evaluated. [9] Method according to one of claims 1 to 8, in which at least one sensor signal (10, 12, 120, 122) of at least one battery sensor (140) associated with the battery (104) is evaluated. [10] A method according to any one of claims 1 to 9, carried out during the accident. [11] A method according to any one of claims 1 to 10, carried out after the accident. [12] Arrangement for battery diagnosis, wherein the arrangement (110) is arranged to carry out a method according to one of claims 1 to 11.

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