Fastener element actuation detection

Abstract

The present invention relates to a method for detecting an actuation of a closure element (10) of a motor vehicle. The method comprises at least one step of detecting an actuation force profile acting on the closure element (10), in particular a handle element (12) of the closure element (10). The method further comprises a step of detecting (22) an actuation event as a function of the detected actuation force profile. Furthermore, the invention relates to a system for detecting an actuation of a closure element (10) of a motor vehicle.

Description

Technical field

[0001] The present invention relates to a method for detecting an actuation of a closure element of a motor vehicle. Furthermore, the invention relates to a system for detecting an actuation of a closure element of a motor vehicle. State of the art

[0002] Conventional car doors are released and opened by pulling on a door handle. A movable door handle pivots when the door handle is pulled, releasing the door through a mechanical connection to a lock. The user can then pull the door open using muscle power.

[0003] Motor vehicle doors can also be unlocked automatically and / or opened by motor. However, this also requires some form of actuation, such as pulling or touching a door handle. By adjusting and releasing the door by motor, a mechanical connection between the door handle and the lock can be dispensed with. Likewise, the door handle itself can be immobile, as no force or movement is to be mechanically transmitted to the door lock. In this case, it can be important that the door operation is reliably detected to prevent unwanted adjustment of the door.

[0004] DE 10 2021 112 324 A1 describes a system for detecting an input and controlling a downstream device, wherein a time-varying input signal in the form of a movement is detected. Thus, a user's movement is detected by a sensor device, and an evaluation or analysis of this movement is performed and interpreted. The system can be used to open a car's tailgate. Description of the invention

[0005] A first aspect of the present invention relates to a method for detecting an actuation of a closure element of a motor vehicle. The actuation of a closure element can be an operation that corresponds to an adjustment request by a user. For example, an actuation can be pulling on the closure element or pressing on the closure element, in particular on a predefined point. A closure element can be designed, for example, as a door or tailgate. However, a closure element can also be designed as a window, folding roof, or sliding roof of the motor vehicle. The closure element can be adjustable, for example, between an open position in which an access opening to the motor vehicle is at least partially released, and a closed position in which the access opening is blocked. The closure element can, for example, be rotatably mounted on one side of a body of the motor vehicle.The locking element can be designed for automatic adjustment. For example, the tailgate of the motor vehicle can be pivoted by motor between its closed and open positions. A lock can also be unlocked and / or released in the process. The adjustment can occur, for example, in response to a detected actuation of the locking element. The locking element can have an adjustment motor. For example, the tailgate can be adjustable by means of a spindle drive. The motor vehicle can be designed, for example, as a passenger car or a truck.

[0006] The method comprises a step of detecting an actuation force curve acting on the closure element. An actuation force can be an external force acting on the closure element. The actuation force can be caused, for example, by a user. A curve of an actuation force can be an actuation force at at least two different points in time. For example, the actuation force can be detected continuously as an analog signal. However, the actuation force can also be detected at discrete intervals, for example at a measuring frequency of a sensor for detecting the actuation force curve. One or more force sensors can be provided for detection. For example, a force sensor can be designed as a strain gauge. A deformation of a rigid and / or immovable part of the closure element can then be used to determine a force acting on it.

[0007] Detection can be permanently active or triggered by an activation signal. For example, detection can be activated when a remote control key for the vehicle approaches within a minimum distance and / or when the vehicle is unlocked. The actuation force curve can have a force direction. For example, the force direction can be recorded as a vector. For example, a distinction can only be made between a tensile force and a compressive force, for example by a sign of the actuation force. This allows different reactions to occur depending on the force direction. However, only an absolute level of the actuation force can be recorded for the actuation force curve.

[0008] An actuation force can also be filtered to capture the actuation force curve. For example, a raw signal from the respective force sensors can be filtered with a low-pass filter. This can reduce noise.

[0009] For example, the actuation force curve acting on a handle element of the locking element can be recorded. A handle element can be designed, for example, as a door handle or as another actuation element, such as a car manufacturer's logo. A handle element can be designed, for example, as a rigid component. The handle element can be arranged immovably or movably on the rest of the locking element. For example, only the actuation force curve acting on the handle element can be recorded. Respective sensors can be arranged on or in the handle element. This means that forces that are not intended for actuation, such as pressing against a door surface at a distance from the handle element, can generally be disregarded.

[0010] The method includes a step of detecting an actuation event based on the detected actuation force curve. An actuation event can correspond to an actual actuation request. This can be used to distinguish between other forces acting on the locking element, for example, forces caused by wind, weather, animals, and / or cleaning the motor vehicle. For example, an actuation event can be a user pulling on the door handle in a specific manner. In contrast, pulling on the door handle by a washing textile in a car wash is not an actuation event. This can prevent, for example, unwanted door opening.

[0011] The actuation event can be detected, for example, by a pattern comparison, a comparison with threshold values, values ​​derived from the actuation force curve and / or by means of a trained neural network. The neural network can have been previously trained for this purpose with synthetic or experimentally generated training data. Respective comparison data, such as patterns and / or threshold values, can be closure element-specific. For example, an actuation force curve corresponding to an actuation event can depend on a shape, a material and / or other properties of the closure element and / or the handle element. The detection of the actuation event can comprise a differentiation from forces acting on the closure element due to causes other than actuation. The method can also comprise detection of non-actuation events, such as driving through a car wash.

[0012] In response to the detection of the actuation event, the closure element can open. Opening can involve unlocking and / or moving the closure element toward the open position. The actuation event can also be responded to with automatic closing of the closure element, for example, if the closure element is in the open position. Closing can involve moving the closure element toward the closed position and / or locking.

[0013] Different actuation events can also be detected. For example, a first actuation event can open the locking element, and a second actuation event can close the locking element. Different actuation events can be distinguished based on patterns and / or the direction of force, for example. For example, pressing the door handle as an actuation event with the door in the closed position can lock the door, while pulling the door handle as an actuation event with the door in the closed position can open the door.

[0014] In a further embodiment of the method, it can be provided that the method comprises a step of detecting a temperature of the handle element. The temperature of the handle element can be detected using an integrated temperature sensor of a control device. The control device can be arranged in, on, or adjacent to the handle element. The detecting step can be carried out once or repeatedly, for example at periodic intervals. The temperature can then be detected, for example, in the form of a temperature profile as a function of time. The control device can, for example, be an evaluation device and can, for example, be configured to carry out some or all steps of the method for detecting an actuation of the closure element. The temperature sensor of the control device can be a temperature sensor implemented in the control device.For example, the control device may comprise a microcontroller and the temperature sensor may be a temperature sensor integrated on a circuit board of the microcontroller.

[0015] Alternatively or additionally, a dedicated temperature sensor can be provided, for example in and / or on the handle element, which is designed to detect the temperature of the handle element. Multiple temperature sensors can also be present, of which, for example, at least one is integrated in the control device and at least one is arranged on or in the handle element. With a temperature sensor on or in the handle element, the temperature can be detected at a location close to the handle element, for example on the handle element made of plastic. With a temperature sensor of the control device, a temperature can be detected, for example, closer to a metallic part on which the handle element itself can be arranged. Due to the different thermal conductivities of plastic and metal, a slight time offset when detecting the temperature of the handle element can be reduced.

[0016] At least one of the detection of the actuation force curve and the detection of the actuation event can be performed depending on the detected temperature of the grip element. For example, exactly one of the detection of the actuation force curve and the detection of the actuation event can be performed depending on the detected temperature of the grip element.

[0017] For example, exactly one of the recording of the actuation force curve and the detection of the actuation event can be performed independently of the detected temperature of the grip element. Alternatively, both the recording of the actuation force curve and the detection of the actuation event can be performed depending on the detected temperature of the grip element. For example, different deformation behavior of the grip element can be taken into account in the force detection.

[0018] The sensor, for example, a force sensor, for detecting the actuation force curve can be parameterized depending on the detected temperature of the grip element. Thus, an actuation force curve detected with the same sensor for a first temperature can be different from an actuation force curve detected with the sensor at a second temperature, different from the first, even though the same force can act on the sensor in both cases. However, a different force can act on the grip element in the two cases, and the dependence of the actuation force curve detection on the temperature of the grip element can compensate for a temperature dependency in the detection of the actuation force curve.For example, a corresponding temperature curve for different temperatures can be stored for a corrected recording of the actuation force curve, for example in a memory of the sensor, such as the force sensor, and / or in the control device, which can be set up, for example, to detect the actuation event.

[0019] For example, a criterion for detecting the actuation event can be modified depending on the detected temperature of the handle element. For example, at least one criterion for detecting the actuation event can be modified depending on the detected temperature of the handle element. For example, at least one of a threshold value, a pattern, comparison data, and / or other values ​​derived from the actuation force curve can be changed. Alternatively or additionally, a neural network can be trained accordingly to take the detected temperature of the handle element into account as a criterion and thus as an input variable. This means, for example, that at a first temperature an actuation event for a specific actuation force curve can be detected, whereas at a second temperature different from the first temperature an actuation event for the same actuation force curve cannot be detected.Thus, the detection of the actuation event can depend on the temperature of the handle element.

[0020] For example, a stiffness that changes with the temperature of the grip element, such as a plastic casing of the grip element, can be compensated for when recording the actuation force curve and / or detecting the actuation event. A temperature curve of the grip element stored for this compensation can depict a dependence of the actuation force curve on specific temperatures. This dependence can be linear, quadratic, or generally polynomial, or even exponential or logarithmic.

[0021] In a further embodiment of the method, at least one of the recording of the actuation force profile and the detection of the actuation event can be performed depending on the age of the handle element, for example, a plastic cover of the handle element. Alternatively or additionally, at least one of the recording of the actuation force profile and the detection of the actuation event can be performed depending on the age of the closure element.

[0022] For example, the temperature curves can be updated over time. This allows for aging of the closure element and / or the handle element to be compensated. For example, a plastic handle that has hardened over time can lead to a changed actuation force curve when detecting the actuation force on the handle element due to a change in the stiffness of the material and / or sensor degradation.

[0023] For example, a criterion for detecting the actuation event can be modified depending on the age of the handle element and / or closure element. For example, at least one criterion for detecting the actuation event can be modified depending on the age of the closure element and / or the handle element. For example, at least one of a threshold value, a pattern, comparison data, and / or other values ​​derived from the actuation force curve can be changed. Alternatively or additionally, a neural network can be trained accordingly to consider the age of the handle element and / or the closure element as criteria and thus as input variables.This allows, for example, an actuation event for a specific actuation force curve to be detected at a first age, whereas an actuation event for the same actuation force curve is not detected at a second age, different from the first. Thus, the detection of the actuation event can depend on the age of the closure element and / or the handle element.

[0024] The method may further comprise a step of determining the age of the closure element and / or the handle element. For example, the step of determining the age may comprise a step of detecting the age. For example, the age may be determined by starting a timer, for example, when the method is performed for the first time. This makes it easy to determine the age of the closure element and / or the handle element. The timer may be reset, for example, when a new closure element and / or handle element is installed.

[0025] In a further embodiment of the method, it can be provided that the detection of the actuating force curve comprises detecting a first actuating force curve with a first sensor and detecting a second actuating force curve with a second sensor. The first and the second sensor can be spatially spaced from one another. The first and the second sensor can detect the first and the second actuating force curve independently of one another. The first and the second sensor can be a first and a second force sensor. The actuating force curve can comprise or consist of the first and the second actuating force curve. Alternatively, the actuating force curve can comprise or consist of exactly one of the first and the second actuating force curve.

[0026] This can be used, for example, to create redundancy in the event of a faulty or non-existent first or second actuation force curve, for example due to a faulty first or second sensor. For example, a distinction can be made as to whether an error or a real effect, such as an actuation request, is present in the first or second actuation force curve. This way, the actuation force curve can be recorded as an individual evaluation and then depending on just one of the first actuation force curve and the second actuation force curve. Alternatively, an average value of the first and second actuation force curves can be determined as the actuation force curve. This way, for example, the actuation force curve can be determined on the basis of the first and second actuation force curves.

[0027] In a further embodiment of the method, it can be provided that the method comprises a step of determining a point of application of an actuating force and / or a direction of an actuating force based on the detected first and second actuating force profiles. For example, at least one of the point of application and the direction of the actuating force can be determined by comparing the first and second actuating force profiles. For example, a vectorization of the actuating force profile can be carried out in this way. For example, a relative force profile, which can be determined by comparing the first and second actuating force profiles, can represent the direction of the actuating force acting on the grip element. Accordingly, three, four or more sensors can also be provided for this purpose, which detect corresponding actuating force profiles.

[0028] The first and second sensors can be arranged differently. For example, in a first embodiment, the first sensor can be arranged at an upper part and the second sensor at a lower part of the handle element. This allows, for example, the direction of the actuating force to be easily determined in a vertical direction. Alternatively, the first sensor can be arranged on a left side and the second sensor on a right side of the handle element. This allows, for example, the actuating force to be easily determined in a horizontal direction. The point of application can also be easily determined vertically and / or horizontally. For example, the first sensor can be arranged at an upper left corner of the handle element and the second sensor at a lower right corner of the handle element. This allows, for example, the point of application to be determined in both a vertical and a horizontal direction.The direction of the actuating force can thus also be determined, for example, in both vertical and horizontal directions. With more than two sensors, a combination of some or all of the previously discussed arrangements can be provided.

[0029] In one embodiment, at least one of the point of application and the direction of the actuating force can be determined based on the detected first and second actuating force profiles, at least at times when both the first and second actuating force profiles can be detected. If at other times, for example due to a faulty first or second sensor, the first or second actuating force profile cannot be correctly detected, determining the point of application and determining the direction of the actuating force can be omitted. Then, only an absolute value of the actuating force can be determined, without, for example, determining the point of application and / or the direction of the actuating force.

[0030] In a further embodiment of the method, it can be provided that the detection of the actuation event comprises a comparison of the first and second actuation force curves. An actuation event for a specific point in time can be detected, for example, if the actuation event is detected in both the first and the second actuation force curves. Alternatively or additionally, a specific actuation event can be detected by comparing the first and second actuation force curves. For example, it can be detected that the grip element is pulled or pushed by a user with a specific force, with a specific point of application and / or with a specific direction of the actuation force. When comparing the first and second actuation force curves, the entire force curve can be compared.Alternatively or additionally, individual criteria of the first and second actuation force curves, such as a level or gradient of the actuation force curve, can be compared with each other. The actuation event can then be detected based on the comparison of the entire first and second actuation force curves and, alternatively or additionally, the comparison of individual criteria of the first and second actuation force curves.

[0031] In a further embodiment of the method, it can be provided that the recording of the actuation force curve is carried out at a reduced sampling rate after a certain period of time without a detected actuation event. The certain period of time can be one or more seconds, minutes, hours, days or months. For example, not a single actuation event may have been detected in the certain period of time. For example, an actuation event may be detected at a first point in time. Immediately afterwards, the actuation force curve can be recorded at a first sampling rate. The first sampling rate can be 20, 50 or 100 ms, for example. After a certain period of time, such as one week, the sampling rate can be reduced, for example to a sampling rate of once per second or once every 10 seconds.With such a second sampling rate, which is lower than the first sampling rate, the actuation force curve can then be recorded, for example, until an actuation event is detected again. If an actuation event is detected, the second sampling rate can be changed back to the first sampling rate, and thus, for example, the sampling rate can be increased.

[0032] Thus, the method can be used to implement a power-saving mode, whereby the recording of the actuation force curve is carried out at a reduced sampling rate at times when the motor vehicle has been parked for a long time, for example. This ensures that a user's intention to actuate the locking element is recognized sufficiently quickly, while at the same time the recording of the actuation force curve does not have to be carried out too frequently at certain times, thus saving power. Furthermore, the reduced sampling rate can also reduce the probability of erroneous detection of an actuation event, since, for example, an object falling onto the handle element will only exert force on the handle element once.

[0033] The period for reducing the sampling rate can, for example, also be determined depending on the battery charge level. Alternatively, the period for reducing the sampling rate can be fixed. There can be one or more specific time periods. One or more sampling rates can therefore be assigned to one or more specific time periods. For example, a specific sampling rate can be assigned to a specific time period, and different sampling rates can be assigned to different time periods. For example, if the time period becomes longer, the sampling rate can also be reduced further.Alternatively or additionally, the period of time can be determined not only as a function of the battery charge state, but also as a function of a temperature, for example an ambient temperature of the motor vehicle, and an age, for example of a battery, which can supply current to a control device for carrying out the method.

[0034] In a further embodiment of the method, it can be provided that the step of detecting the actuation event comprises calculating an actuation probability. The actuation probability can be calculated, for example, as a percentage, where 100% is a certain actuation and 0% is definitely not an actuation. The actuation probability can be calculated by merging several probabilities. For example, several pieces of data, such as an absolute level of a maximum actuation force and its duration, can be compared with threshold values. A distance to the threshold value can correspond to a probability. These probabilities can, for example, be multiplied to calculate the actuation probability. The actuation event can be detected if the calculated actuation probability is greater than a first threshold value.The first threshold can be fixed, for example, at 90%. Using an actuation probability can prevent many actuation events from being missed, thus preventing the locking element from responding. This can lead to high user acceptance.

[0035] The first threshold can also be determined depending on the recorded actuation force curve. For example, if the actuation force curve contains many interfering signals and vibrations, the first threshold can be high. This can reduce the probability of erroneous detection of an actuation event in potentially harmful situations, such as a car wash, and / or other strong external force influences. Likewise, another non-actuation event, such as driving through a car wash, can be detected depending on the recorded actuation force curve, and the first threshold can be increased in the case of a non-actuation event. This may then require a user to actuate the door more forcefully or with a particularly strong force in order for it to open.

[0036] In a further embodiment of the method, it can be provided that a wake-up signal is generated if the calculated actuation probability is greater than a second threshold. The second threshold can be smaller than the first threshold. The wake-up signal can be a trigger signal, for example. The wake-up signal can be transmitted, for example, via a CAN data bus of the motor vehicle. The wake-up signal can be used to wake up an ECU of the motor vehicle and / or the locking element. The wake-up signal can be used to activate the power supply of actuators, start authentication of an access authorization, and / or initiate further measures to prepare for an adjustment of the locking element. The wake-up signal can, for example, unlock the locking element almost without delay or even immediately and / or adjust it to its open position as soon as the actuation event has been detected.A low activation probability is used, for example, to prepare for a door opening, even if this low activation probability is not yet sufficient to trigger the actual door opening. This can increase the reaction speed without increasing the risk of unwanted adjustment. For example, when the wake-up signal is generated, no activation event has yet been detected. The second threshold can be fixed or, like the first threshold, variably specified. Furthermore, the second threshold can also have a fixed difference from a variably determined first threshold as described above.

[0037] In a further embodiment of the method, it can be provided that the actuation force curve has a level, a gradient, and a standard deviation as properties. For example, the actuation force curve can have a level, a gradient, and / or a standard deviation at one or more points in time, such as at each point in time. For example, the actuation force curve can have a level, a gradient, and / or a standard deviation in a time range. The level can, for example, be an absolute value of the actuation force at a specific point in time. The gradient can be a first derivative of the actuation force curve at a specific point in time. The gradient can be an average gradient of the actuation force in a specific time range. The standard deviation can be related to multiple values ​​of the actuation force in a time range and an average value of the actuation force in the time range.Thus, the standard deviation can define the range of the multiple actuation force values ​​in the time domain around the mean value of the actuation force in the time domain. The standard deviation can be a measure of signal noise.

[0038] Furthermore, calculating the probability of actuation can comprise calculating individual probabilities for an actuation. The individual probabilities for an actuation can each be calculated depending on only one of the properties. For example, an individual probability for an actuation can be calculated for the level. Furthermore, an individual probability for an actuation can be calculated for the gradient and for the standard deviation. For example, using a functional relationship between the level, the gradient or the standard deviation and a probability, the individual probability for an actuation can be calculated for one of the level, the gradient and the standard deviation. The calculation can be carried out, for example, using an appropriately trained neural network.This allows the calculation of individual probabilities to correspond particularly accurately to the actual probability. Alternatively or additionally, the calculation can be performed using look-up tables. This allows the calculation to be performed very quickly and with little computational effort. These look-up tables can be previously determined based on large amounts of test data. Furthermore, the neural network can also be trained with test data.

[0039] The actuation force curve can be plotted as a function of time, whereby a force can be plotted against time. The calculated individual probabilities can also be plotted on the same time scale. For example, an individual probability for the level, the gradient, and the standard deviation can be plotted for each individual point in time. The individual probabilities can be calculated for a period of the actuation force curve, for example, for a specific time window before the last recording of actuation forces.

[0040] The actuation probability can be calculated based on at least one of the calculated individual probabilities. For example, the actuation probability can be calculated based on all calculated individual probabilities. The actuation probability can, for example, be calculated for each point in time or time range for which the actuation force is also available as an actuation force curve. For example, the actuation probability for a specific point in time can be calculated based on and as a function of the individual probabilities at that point in time. For example, the actuation probability, also known as the overall actuation probability, can be calculated by averaging or multiplying the individual probabilities. Alternatively, the actuation probability, or overall actuation probability, can be calculated by integrating the individual probabilities.Thus, the probability of activation can be calculated simply and with little computational effort by calculating individual probabilities.

[0041] In a further embodiment of the method, it can be provided that the same value is calculated for the individual probability in one area of ​​the respective property. A functional relationship which maps a value of the property to the individual probability of the property can be constant in the area, i.e., for example, neither increasing nor decreasing. Different values ​​of the properties can be mapped to the same individual probability value. There can be one or more such areas. For example, there can be a first area of ​​a property, with values ​​of this area being mapped to a first individual probability. There can be a second area of ​​the same property, different from the first, with values ​​of the second area being able to be mapped to a second individual probability.The first and second individual probabilities can be different or the same.

[0042] At least one, for example exactly one, several, or all properties can have at least one range in which the same value is calculated for the individual probability. For example, if the standard deviation is very small, the individual probability of the standard deviation can be 100%, for example up to a maximum threshold of the standard deviation. If the standard deviation is below a maximum threshold, the individual probability can be 100%, and if the standard deviation is equal to or above the maximum threshold, the individual probability can be less than 100%. For example, the individual probability can then decrease with increasing standard deviation, for example linearly or quadratically.

[0043] Also, if the level has exceeded a certain threshold, the individual probability for the level can be, for example, 100%. Thus, the individual probability for the level can have a first value if the level is below a certain threshold. If the level is equal to or greater than this specific threshold, but less than another specific threshold, the individual probability can have a second value, which can be greater than the first value. For example, as the level increases, the individual probability of the level can increase, for example, in a stepwise manner.

[0044] If the gradient is greater than a certain threshold and less than another certain threshold, for example, the individual probability for the gradient can be 100%. If the gradient is outside this range, the individual probability for the gradient can be less than 100%. For example, in a certain range or corridor of the gradient, the individual probability of the gradient can be 100%. Outside this range or corridor, the individual probability can be smaller, for example, 50% or 0%. Outside the range or corridor, the individual probability can change with changing gradient, for example, linearly or quadratically.The individual probability of an actuation based on the gradient can be very high if the gradient of the actuation force curve, i.e. a temporal change in the actuation force curve, lies in this range or corridor, i.e. the user applies an actuation force to the handle element with a certain temporal change.

[0045] In a further embodiment of the method, it can be provided that the activation probability is calculated based solely on one or two of the calculated individual probabilities. For example, the activation probability can be calculated based solely on one or two of the calculated individual probabilities if at least one of the individual probabilities exceeds a certain threshold. Thus, if, for example, the level exceeds a certain individual probability, the activation probability can be determined based solely on the individual probability of the level. Alternatively or additionally, from a certain value of a property, for example from a certain level, the activation probability can be calculated based solely on a calculated individual probability.

[0046] Furthermore, the detection of the actuation event can be verified using those individual probabilities that were not used to calculate the actuation probability. For example, the actuation probability can be calculated solely based on the calculated individual probability of the level. Furthermore, a detection verification step can be performed, with the verification step being performed depending on individual probabilities for the gradient and standard deviation. For example, a rapid opening of the closure element can be performed solely based on the calculated individual probability for the gradient, in that the actuation event can be quickly detected and verified solely using the individual probability for the level.

[0047] In some cases, the level can also be used as the only individual probability to calculate the actuation probability and thus to detect the actuation event. This also allows a power-saving function to be implemented, as calculating the actuation probability can be carried out more easily and fewer calculation steps are necessary. This can also be done more quickly than if the actuation probability were calculated based on all calculated individual probabilities, and all individual probabilities then have to be calculated. Furthermore, the actuation force curve may not be continuous and be represented by a non-continuous function. For example, the gradient cannot then be determined for all times or ranges of the actuation force curve.In this case, it may be advantageous to determine the actuation probability based solely on calculated individual probabilities for the level and / or the standard deviation. This ensures that the method can be implemented even if the recorded actuation force curve cannot be represented by a continuous function.

[0048] In a further embodiment of the method, it can be provided that the detection of the actuation event is carried out depending on the standard deviation. For example, a criterion for detecting the actuation event can be modified. For example, at least one criterion for detecting the actuation event can be modified depending on the standard deviation. For example, at least one of a threshold value, a pattern, comparison data, and / or other values ​​derived from the actuation force curve can be changed. Alternatively or additionally, a neural network can be trained accordingly to take the standard deviation into account as a criterion and thus as an input variable. This means, for example, that an actuation event can be detected with a first standard deviation, whereas an actuation event cannot be detected with a second standard deviation different from the first.

[0049] For example, a criterion for detecting an actuation event can be changed by changing a threshold value. For example, a threshold value for detecting an actuation event can be increased if the standard deviation increases. For example, if the actuation force curve fluctuates more strongly within a certain range, the actuation event can only be detected at a higher level. If the standard deviation is even larger, the method for detecting an actuation event can also be terminated or switched off, for example if it is detected that the motor vehicle is in a car wash. Alternatively or additionally, a range or corridor of at least one property can be reduced if the standard deviation increases.If, for example, the standard deviation increases from a first point in time to a later point in time, a range of a property, such as the level, for which the individual probability has a relatively high value, for example 100%, can be reduced. This means that fewer values ​​of the respective properties, for example fewer values ​​of the level, can fall into this range and for fewer values ​​of this level a high value of the individual probability, in this case 100%, can be output. In this way, if the standard deviation increases, the range or corridor can be reduced. Alternatively or additionally, if the standard deviation increases, only the individual probability for the level or the gradient can be determined and the activation probability can only be determined based on this calculated individual probability.

[0050] In a further embodiment of the method, it can be provided that, if the standard deviation is above a third threshold value, the calculation of the activation probability is carried out exclusively as a function of the individual probability with respect to the level or the gradient. The activation probability can, for example, be calculated either as a function of the individual probability with respect to the level or as a function of the individual probability with respect to the gradient. For example, the activation probability can be calculated as a function of at least two, for example two or exactly two, individual probabilities with respect to two levels or two gradients at different times. For example, the activation probability can be calculated as a function of exactly two individual probabilities with respect to two levels at different times or points in time.Alternatively, the activation probability can be calculated as a function of two individual probabilities with respect to two gradients at different times or points in time. The activation probability can be calculated as a function of more than two individual probabilities with respect to multiple values ​​of a property at different times. If the standard deviation is particularly large, for example, it may be advantageous to use only the level or the gradient, but not both values, to calculate the activation probability based on the individual probabilities of the respective property.

[0051] In a further embodiment of the method, it can be provided that an actuation event is detected when the gradient is below a fourth threshold and the level is above a fifth threshold for a certain minimum duration. For example, an actuation can be detected when a user actuates the handle element with a certain force, whereby the force does not change over time more than defined above the fourth threshold and, at the same time, the magnitude of the force, i.e., the level, is above the fifth threshold for a certain minimum duration, i.e., the user pulls or pushes on the handle element with a certain minimum force.

[0052] A specific actuation event can be detected depending on the sign of the gradient. For example, it can be detected that the user is pulling or pushing. For example, only a rising or falling edge in the actuation force curve can be observed.

[0053] In a further embodiment of the method, it can be provided that the method can comprise a step of detecting a speed of the motor vehicle. The detection of the speed of the motor vehicle can be carried out using a speed sensor. The detection of the actuation event can be deactivated, for example, if the detected speed is greater than a threshold speed. For example, the threshold speed can be 3, 4, or 5 km / h. An actuation event can, for example, only be detected if the vehicle is moving at a maximum of the threshold speed. This can thus ensure, for example, that no actuation event is detected if the vehicle is moving at more than the threshold speed.This can also prevent, for example, incorrect detection and thus incorrect opening, for example of the locking element, during a journey.

[0054] In a further embodiment of the method, it can be provided that an opening signal is generated if at least one parameter of the recorded actuation force curve is greater than a bridging threshold, regardless of whether the actuation event was detected. The parameter can be, for example, a maximum tensile force within a detection period. Alternatively or additionally, the opening signal can be generated if, for example, a tensile force as actuation of the closure element exceeds a minimum tensile force for a minimum period. If multiple parameters are taken into account, each parameter can be assigned a bridging threshold. For the opening signal to be generated, for example, all, some, or only one of the parameters must exceed its assigned bridging threshold. The parameter can be, for example, a force or a derivative of the force.For example, the parameter can be a characteristic force curve, and respective bridging thresholds can represent a characteristic force curve. The bridging threshold or respective bridging thresholds can be limits at which the locking element is always opened, optionally subject to access authorization, regardless of whether an actuation event has been detected or not. This means that access to the motor vehicle can always be possible in an emergency. The opening signal can also be generated, for example, if a non-actuation event, such as driving through a car wash, has been detected. The opening signal causes, for example, an unlocking of the locking element and / or an adjustment of the locking element to the open position.

[0055] The respective override thresholds can be fixed or determined based on the detected actuation force curve. In the case of interference signals, such as vibrations, the override threshold can be increased, for example. A non-actuation event, such as driving through a car wash, can also be detected based on the detected actuation force curve, and the override threshold can be increased in the case of a non-actuation event.

[0056] In a further embodiment of the method, it can be provided that the method comprises a step of determining a first derivative of the detected actuation force curve. The first derivative of the detected actuation force curve can be a gradient or an increase of the actuation force curve. The detection of the actuation event can take place depending on the determined first derivative of the detected actuation force curve. By taking into account the first derivative of the detected actuation force curve, it can be detected more precisely whether the closure element is actually being actuated by a user or whether other forces are acting on the closure element to which the closure element should not be reacted by adjusting it.To detect the actuation event, the first derivative of the recorded actuation force curve can be used only at a single point in time, or a curve of the first derivative of the actuation force curve can be used. For example, only a maximum value of the first derivative of the recorded actuation force curve can be determined and compared with a threshold value. An upper and a lower threshold value can also be provided. The actuation event can be detected, for example, if the first derivative of the recorded actuation force curve lies within or, alternatively, outside a range defined by these threshold values. Alternatively or additionally, a form of the first derivative of the actuation force curve can be taken into account and a comparison can be made with a curve of the first derivative of the actuation force curve that is characteristic of an actuation.

[0057] In a further embodiment of the method, it can be provided that the method comprises a step of determining a second derivative of the detected actuation force curve. The detection of the actuation event can take place depending on the determined second derivative of the detected actuation force curve. The second derivative can be taken into account, for example, alternatively or in addition to the first derivative. The second derivative can indicate whether a gradient of the detected actuation force curve is decreasing or increasing. By taking the second derivative of the detected actuation force curve into account, it can be detected more precisely whether the closure element is actually being actuated by a user or whether other forces are acting on the closure element to which the closure element should not be reacted to by adjusting the closure element.To detect the actuation event, the second derivative of the recorded actuation force curve can be used only at a single point in time, or a curve of the second derivative of the actuation force curve can be used. For example, only a maximum value of the second derivative of the recorded actuation force curve can be determined and compared with a threshold value. Alternatively or additionally, a form of the second derivative of the actuation force curve can be taken into account, and a comparison can be made with a curve of the second derivative of the actuation force curve characteristic of an actuation.

[0058] In a further embodiment of the method, it can be provided that the method comprises a step of determining an interference signal depending on the detected actuation force curve. An interference signal can, for example, be a part of the detected actuation force curve that is not caused by a force applied by the user to the closure element. The interference signal can, for example, be a vibration or other periodic force. The interference signal can, for example, be caused by wind and / or weather. The interference signal can be caused by passing vehicles. The interference signal can, for example, be detected based on its periodicity and / or respective derivatives of the detected actuation force curve. The interference signal can, for example, also be compared with known interference signals, for example from car washes, by means of a pattern comparison.

[0059] In a further embodiment of the method, it can be provided that the detection of an actuation event occurs depending on the specific interference signal. For this purpose, the interference signal can, for example, be subtracted from the recorded actuation force curve. Only after this subtraction can the thus corrected actuation force curve be used to detect the actuation event. This can make the detection of the actuation event more reliable. Depending on the interference signal, a non-actuation event can also be detected, for example.

[0060] In a further embodiment of the method, it can be provided that at least one threshold value is determined depending on the specific interference signal. For example, all, some, or only one of the threshold values ​​described above can be set or changed depending on the specific interference signal. This can, for example, increase the probability of actuation at which the actuation event is detected and the closure element is opened in the case of strong interference signals.

[0061] In a further embodiment of the method, it can be provided that a force detection offset is taken into account when detecting the actuation force curve. This can also lead to a correction of the detection. For example, residual stress in the closure element, a temperature change and / or other influencing factors can lead to an offset in the detected force which is not caused by an actuation. These influencing factors can, for example, be detected and used to determine the offset. For example, a temperature of the force sensor and / or the closure element can be detected and the force detection offset can be determined depending on the detected temperature. For example, the handle element may not fully recover after actuation and a strain gauge as a force sensor may then permanently detect a force which is not caused by an actuation.By taking this into account, the detection of the actuation event can be made more reliable. The force detection offset can be used to calibrate the detection, for example, to a zero point.

[0062] In a further embodiment of the method, it can be provided that the force detection offset is determined as a function of the detected actuation force curve. This eliminates the need for additional sensors to detect the offset. For example, the force detection offset can be determined as an average of the detected actuation force curve. The determination of the force detection offset can be suspended if a change in the detected actuation force curve is greater than a change threshold. For example, the average of the detected force for a specific previous period, for example 10 seconds and / or since a last suspension of the determination, can be determined as the force offset. The average can be determined over a sliding period.The average can also be taken overall since activation or the last parking of the motor vehicle, optionally excluding suspended time periods due to the change threshold being exceeded. The suspension of the determination of the force detection offset can take place for a predetermined period of time and / or until the change in the detected actuation force curve is less than the change threshold. The suspension of the determination of the force detection offset can continue for a predetermined period of time after the change in the force curve is less than or equal to the change threshold. The change can be a first derivative. For example, the determination of the force detection offset can be suspended if a gradient is greater than a maximum gradient.However, the change can also be the absolute magnitude of a force difference at a specified time interval, which must then be greater than the change threshold to suspend the determination of the force detection offset. By suspending the determination of the force detection offset, temporary external influences, such as actual actuation or disturbances caused, for example, by a car wash, can be disregarded for calibrating a zero value for the force detection.

[0063] In a further embodiment of the method, it can be provided that the force detection offset can be taken into account via analog compensation. For example, the force detection offset can be taken into account before amplifying the detected actuation force curve. For example, an absolute value of an output signal of the force sensor can be shifted via the analog compensation. The control device, which can be configured to detect the actuation event, can also be configured, for example, to control this analog compensation. For example, this control device can control a digital-to-analog converter via digital outputs, and the analog compensation can be performed via this digital-to-analog converter.Using multiple digital-to-analog converters, which can be designed separately from the control device or integrated into it, multiple force sensors can be controlled via multiple different digital outputs of the control device. In this case, multiple different analog compensations can be performed, for example, one analog compensation per force sensor. Analog compensation, particularly before amplification, can improve the resolution of the recorded actuation force curve. This can improve the detection of the actuation event.

[0064] A second aspect relates to a system for detecting an actuation of a closure element of a motor vehicle. The system can be configured to carry out the method according to the first aspect. Respective advantages and further features can be gathered from the description of the first aspect, with embodiments of the first aspect also forming embodiments of the second aspect, and vice versa.

[0065] The system has a force detection device designed to detect an actuation force curve acting on the closure element, in particular a handle element of the closure element. The system has an evaluation device designed to detect an actuation event depending on the detected actuation force curve. The system can also have the closure element and / or the handle element. The handle element can be immovably attached to the rest of the closure element and / or be designed as a rigid component. The system can also have an actuator for the closure element. The system can have a control device designed to control the closure element depending on the detected actuation event, for example to adjust the closure element between its closed position and open position.

[0066] In a further embodiment of the method, the force-detecting device may comprise a strain gauge as a force sensor. The force-detecting device may also comprise multiple strain gauges. This allows for particularly good detection and / or differentiation of different deformation directions and thus force directions. The force sensor may, for example, be arranged in or on the closure element. For example, the strain gauge may be glued to the grip element or cast into the grip element.

[0067] In a further embodiment of the system, the force detection device may comprise a strain gauge as a sensor, for example, a force sensor. The previously described features, advantages, and embodiments regarding the strain gauge as a force sensor with respect to the embodiment of the method are also applicable here with respect to the embodiment of the system.

[0068] The strain gauge can be designed as a Wheatstone bridge. The Wheatstone bridge can be a quarter, half, or full bridge. The Wheatstone bridge can, for example, have four resistors. For example, the four resistors can be connected together to form a closed ring or square. A supply voltage can be applied across one diagonal of the square. A voltage measuring device can be connected across another diagonal of the square.

[0069] In a further embodiment of the system, the force detection device can comprise a first force sensor and a second force sensor. The force detection device can comprise additional force sensors. The first and second force sensors can be configured independently of one another to detect the actuation force curve. For example, the system comprises two strain gauges as two separate and independent Wheatstone bridges, for example, designed as half bridges or full bridges.

[0070] In a further embodiment of the system, the system can have a first digital-to-analog converter for the first force sensor and a second digital-to-analog converter for the second force sensor. The two digital-to-analog converters can be implemented on one circuit board or separately on different circuit boards. The two digital-to-analog converters can be implemented together with the evaluation device on one circuit board or separately on a different circuit board than the evaluation device. Both digital-to-analog converters can be controlled via the digital outputs of the evaluation device. The first digital-to-analog converter can be controlled via first digital outputs, and the second digital-to-analog converter can be controlled via second digital outputs different from the first digital outputs, for example independently of the first digital-to-analog converter.

[0071] The digital-to-analog converters can be configured for analog compensation of the actuation force curve by a force detection offset. Each of the digital outputs of the evaluation device can, for example, assume three states: 0, the supply voltage, or high impedance. Each digital-to-analog converter can be connected to the evaluation device via four digital outputs. Each of the digital-to-analog converters can, for example, have four bits, for example, four different resistances. Each bit can be connected to a digital output of the evaluation device. This allows 81 states to be realized. Thus, the resolution can be 81 instead of 16 with digital outputs with two states, namely 0 and the supply voltage.By selecting the resistances of the bits of the digital-to-analog converter, for example, by adjusting certain factors between the resistances of the bits, a specific behavior of the digital-to-analog converter can be achieved. For example, the resistances can differ from each other by a factor of 3. For example, a first resistor can be three times as large as a second resistor. A third resistor can be three times as large as the second resistor. This allows a nearly linear behavior of the digital-to-analog converter with a linear resolution between the 81 states to be achieved. By adjusting other factors between the individual resistors, different behaviors of the digital-to-analog converter can be achieved.

[0072] For n force sensors and, for example, n strain gauges, n digital-to-analog converters can be used. This allows for modularity, allowing the force detection offset to be easily accounted for with a single evaluation device. Hardware adaptation of the evaluation device, for example, via multiple digital-to-analog converters provided in the hardware of the evaluation device, is not necessary; instead, the digital outputs or pins normally present in such evaluation devices can be used. Modular digital-to-analog converters can then be used, and depending on the number of digital outputs, any number of digital-to-analog converters can be used.

[0073] Further embodiments and configurations of the present disclosure can be found in the following list of items: 1. A method for detecting an actuation of a closure element (10) of a motor vehicle, comprising at least the following steps: detecting (20) an actuation force curve acting on the closure element (10), in particular a handle element (12) of the closure element (10); and detecting (22) an actuation event as a function of the detected actuation force curve. 2. The method according to item 1, wherein the method comprises a step of detecting (18) a temperature of the handle element (12) using an integrated temperature sensor of a control device, and wherein at least one of the detecting (20) of the actuation force curve and the detecting (22) of the actuation event is carried out as a function of the detected temperature of the handle element (12). 3.Method according to one of the preceding claims, wherein at least one of the detection (20) of the actuation force profile and the detection (22) of the actuation event is carried out as a function of an age of the handle element (12). 4. Method according to one of the preceding claims, wherein the detection (20) of the actuation force profile comprises detecting (20a) a first actuation force profile with a first sensor (13a) and detecting (20b) a second actuation force profile with a second sensor (13b), wherein the first and second sensors (13a, 13b) are spatially spaced from one another. 5. Method according to claim 4, wherein the method comprises a step of determining (23) an application point of an actuation force and / or determining (24) a direction of an actuation force based on the detected first and second actuation force profiles. 6.Method according to item 4 or 5, wherein the detection (22) of the actuation event comprises a comparison (25) of the first and second actuation force curves. 7. Method according to one of the preceding items, wherein the detection (20) of the actuation force curve is carried out at a reduced sampling rate after a certain period of time without a detected actuation event. 8. Method according to one of the preceding items, wherein the step (22) of detecting the actuation event comprises calculating an actuation probability, wherein the actuation event is detected if the calculated actuation probability is greater than a first threshold value, in particular wherein the first threshold value is determined as a function of the detected actuation force curve. 9.Method according to item 8, wherein a wake-up signal is generated if the calculated actuation probability is greater than a second threshold, in particular wherein the second threshold is smaller than the first threshold. 10. Method according to item 8 or 9, wherein the actuation force curve (90) has a level (92), a gradient (94), and a standard deviation (96) as properties, wherein calculating the actuation probability (100) comprises calculating individual probabilities (102, 104, 106) for an actuation, wherein the individual probabilities (102, 104, 106) for an actuation are each calculated only as a function of one of the properties, and wherein the actuation probability (100) is calculated based on at least one of the calculated individual probabilities (102, 104, 106).Method according to item 10, wherein the same value is calculated for the individual probability (102, 104, 106) in each area of ​​the respective property. 12. Method according to one of items 10 or 11, wherein the actuation probability (100) is calculated based solely on one or two of the calculated individual probabilities (102, 104, 106). 13. Method according to one of items 10 to 12, wherein the detection (22) of the actuation event is performed as a function of the standard deviation. 14. Method according to one of items 10 to 13, wherein, if the standard deviation is above a third threshold value, the calculation of the actuation probability is performed exclusively as a function of the individual probability with respect to the level or the gradient, for example as a function of two individual probabilities with respect to two levels or two gradients at different times. 15.Method according to one of items 10 to 14, wherein an actuation event is detected when the gradient is below a fourth threshold and the level is above a fifth threshold for a certain minimum duration. 16. Method according to one of the preceding items, wherein the method comprises a step of detecting (26) a speed of the motor vehicle, and the detection (22) of the actuation event is deactivated if the detected speed is greater than a threshold speed. 17. Method according to one of the preceding items, wherein an opening signal is generated if at least one parameter of the detected actuation force curve is greater than a bridging threshold, regardless of whether the actuation event was detected. 18.Method according to one of the preceding subjects, wherein the method comprises a step of determining (38) a first derivative of the detected actuation force curve, and the detection (22) of the actuation event takes place as a function of the determined first derivative of the detected actuation force curve. 19. Method according to one of the preceding subjects, wherein the method comprises a step of determining a second derivative of the detected actuation force curve, and the detection of the actuation event takes place as a function of the determined second derivative of the detected actuation force curve. 20. Method according to one of the preceding subjects, wherein the method comprises a step of determining an interference signal as a function of the detected actuation force curve. 21.Method according to item 20, wherein the detection (22) of an actuation event occurs as a function of the determined interference signal and / or wherein at least one threshold value is determined as a function of the determined interference signal. 22. Method according to one of the preceding items, wherein a force detection offset is taken into account when detecting the actuation force curve. 23. Method according to one of the preceding items, wherein the force detection offset is determined as a function of the detected actuation force curve, wherein the determination of the force detection offset is suspended if a change in the detected actuation force curve is greater than a change threshold value. 24. Method according to one of the preceding items, wherein the force detection offset is taken into account via analog compensation. 25.System for detecting an actuation of a closure element (10) of a motor vehicle, in particular wherein the system is designed to carry out the method according to one of the preceding claims, wherein the system comprises a force detection device which is designed to detect an actuation force curve acting on the closure element (10), in particular a handle element (12) of the closure element (10), and an evaluation device which is designed to detect an actuation event as a function of the detected actuation force curve. 26. System according to item 25, wherein the force detection device has a strain gauge as a force sensor. 27. System according to item 26, wherein the strain gauge is designed as a Wheatstone bridge (72). 28.System according to one of items 25 to 27, wherein the force detection device has a first force sensor and a second force sensor, which are configured independently of one another to detect the actuation force curve. 29. System according to item 28, wherein the system has a first digital-to-analog converter (78a) for the first force sensor and a second digital-to-analog converter (78b) for the second force sensor, wherein both digital-to-analog converters (78a, 78b) are controlled via digital outputs (80) of the evaluation device (86), and wherein the digital-to-analog converters (78a, 78b) are configured for analog compensation of the actuation force curve by a force detection offset. Short description of the characters

[0074] Fig. 1a illustrates a schematic perspective view of a closure element of a motor vehicle designed as a door. Fig. 1b schematically illustrates an arrangement of several sensors in the handle element. Fig. 2 schematically illustrates a method for detecting an actuation of the closure element according to Fig. 1 . Fig. 3 schematically illustrates a data evaluation when detecting the actuation of the closure element according to Fig. 1. Fig. 4 illustrates a diagram of a detected force curve in a parked motor vehicle. Fig. 5 illustrates a diagram of a detected force curve in a car wash. Fig. 6 illustrates a diagram of a detected force curve during actual actuations of the closure element. Fig. 7 schematically illustrates an actuation force curve. Figs. 8a-8c schematically illustrate a calculation of individual probabilities. Fig. 9 schematically illustrates a calculation of an actuation probability based on individual probabilities. Fig. 10 schematically illustrates an analog compensation of a force detection offset. Detailed description of embodiments

[0075] Fig. 1aillustrates, in a schematic perspective view, a closure element of a motor vehicle designed as a door 10. The door 10 is automatically adjustable by means of an actuator between an open position, in which an access opening to an interior of the motor vehicle is released, and a closed position, in which the access opening is blocked. The door 10 has a rigid handle element 12. When the handle element 12 is actuated by a user, for example by pulling on the handle element 12, the door 10 is to be opened. For this purpose, a door lock is released and an adjustment of the door 10 towards an open position is controlled by the actuator. However, if the handle element 12 is otherwise acted upon, for example by cleaning brushes and cleaning cloths in a car wash, the door 10 is to remain in its closed position.

[0076] In the handle element 12, as shown schematically in Fig. 1b, in one embodiment, instead of just one sensor, a first sensor 13a and a second sensor 13b are arranged spatially spaced from each other. Fig. 1b shows a schematic cross section through the handle element 12 and a top view of the handle element 12, as a user standing in front of the handle element 12 and the closure element 10 would see the elements in the case of a transparent handle element 12. The first sensor 13a is arranged at the top left and the second sensor 13b is arranged at the bottom right. In an alternative embodiment, the two sensors 13a, 13b can also be arranged on the same horizontal line and / or vertical line. Other spatial arrangements of the two sensors 13a, 13b relative to one another are also possible, such as the first sensor 13a being arranged at the bottom left and the second sensor 13b at the top right.

[0077] In Fig. 2A method is illustrated by which the actuation of the door 10 of the motor vehicle is detected. In a first step 20, an actuation force curve acting on the handle element 12 is recorded. For this purpose, at least one strain gauge is integrated into the handle element 12 as a force sensor of a force detection device. When the handle element 12 is deformed, for example by pulling on the handle element 12, a measurement signal is generated which corresponds to the force acting on the handle element 12. In a step 22, an actuation event is detected as a function of the recorded actuation force curve by means of an evaluation device.

[0078] Furthermore, in Fig. 2shown that the method optionally comprises a step of detecting 18 a temperature of the handle element 12 according to one embodiment. The evaluation device, which is a control device, has an integrated temperature sensor for detecting 18. In one embodiment, the detection 20 of the actuation force curve is carried out as a function of the detected temperature of the handle element 12. In an alternative embodiment, the detection 22 of the actuation event is carried out as a function of the detected temperature of the handle element 12. In a further embodiment, both the detection 20 of the actuation force curve and the detection 22 of the actuation event are carried out as a function of the detected temperature of the handle element 12.For example, different temperature curves can lead to different recorded force curves when recording 20 the actuation force curve, whereby, for example, a temperature dependence of the stiffness of the handle element 12 can be compensated and thus the actuation force curve can be recorded precisely.

[0079] Furthermore, in Fig. 2 It is shown that the method optionally comprises a step of determining 16 an age of at least one of the closure element 10 and the handle element 12. The age is determined via a timer implemented on the evaluation device. At least one of the detection 20 of the actuation force profile and the detection 22 of the actuation event is performed depending on the determined age of the closure element 10 and / or the handle element 12. The steps of detecting 18 the temperature and determining 16 the age can be performed independently of one another.

[0080] In the embodiment with two sensors 13a, 13b, the detection 20 of the actuating force curve comprises a detection 20a of a first actuating force curve with the first sensor 13a and a detection 20b of a second actuating force curve with the second sensor 13b.

[0081] Furthermore, the method can optionally comprise, in the step of detecting 22 the actuation event, a step of determining 23 a point of application of an actuation force based on the detected first and second actuation force profiles. Furthermore, the detection 22 of the actuation event can comprise a step of determining 24 a direction of an actuation force based on the detected first and second actuation force profiles. As exemplified in Fig. 1bAs shown, the two sensors 13a, 13b are arranged offset from one another both vertically and horizontally. This makes it possible to determine both the point of application of the actuating force that a user exerts on the grip element 12 and the direction of this actuating force. For example, the user's actuating force can be resolved vectorially, i.e., the direction of the actuating force can be determined. This makes it possible to determine not only whether the user is pushing or pulling, but also in which area of ​​the grip element 12 the user is applying the force and in which direction.

[0082] The detection 22 of the actuation event further comprises a comparison 25 of the first and second actuation force curves. The first and second actuation force curves can be compared with each other, for example, at specific times or ranges. Based on this comparison, an actuation event can then be detected. If, for example, it is detected that both the first and second actuation force curves have a specific value in a specific time range, an actuation event can be detected. However, if, for example, only one of the first and second actuation force curves has a specific value, no actuation event can be detected.

[0083] In Fig. 2Furthermore, an optional feedback loop from the step of detecting 22 the actuation event to the step of detecting 20 the actuation force curve according to the embodiment shown is schematically illustrated. If no actuation event is detected for a specific period of time, the detection 20 of the actuation force curve is carried out at a reduced sampling rate. Thus, the detection 20 of the actuation force curve can initially be carried out at a first sampling rate. If no actuation event is then detected for the specific period of time, for example, one week, because the motor vehicle is parked and the user does not want to open the door, the evaluation device can control the detection 20 based on the detection 22 such that the sampling rate is reduced.With such a reduced, here second, sampling rate, which is lower than the first sampling rate, the recording 20 of the actuation force curve can then be continued, for example, until another actuation event is detected. After that, for example, the first sampling rate can be used again to record 20 the actuation force curve.

[0084] The method further includes a step of detecting 26 a speed of the motor vehicle. In one embodiment, the detection 22 of the actuation event is deactivated if the detected speed is greater than a threshold speed, for example, 3, 4, or 5 km / h. This ensures that no actuation event is detected if the motor vehicle is moving too fast.

[0085] Fig. 3schematically illustrates a data evaluation. In a step 30, the unprocessed sensor signal is provided by the strain gauge. In a step 32, this sensor signal is filtered with a low-pass filter in order to filter out high-frequency force changes. High-frequency force changes do not correspond to an actuation by a user, but can be caused, for example, by electronic components on the circuit board. In a step 34, the recorded actuation force curve is shifted by a force detection offset. This corrects for residual stresses remaining in the handle element 12 as well as shifts caused by aging and temperature. This is further explained using Fig. 6explained. In a step 36, the magnitude of the detected actuation force is determined, which in this case is a maximum value of a force during actuation. In a step 38, a first derivative of the detected actuation force curve is determined, in this case a gradient of the force during actuation.

[0086] In a step 40, the data generated from the recorded actuation force curve is actually analyzed in order to be able to recognize possible actuation events depending on the recorded actuation force curve. For this purpose, for example, the level of the recorded actuation force is compared with a minimum force as a threshold value. Likewise, for example, the first derivative of the recorded actuation force is compared with a further threshold value. Depending on the extent to which it is exceeded, an actuation probability is assigned to each of these parameters. Further threshold values ​​can also be provided. For example, if a maximum force is exceeded, the actuation probability is calculated as low. The maximum force can, for example, be a force that can no longer usually be generated by a user because an average person in a normal posture is too weak for this.In addition, the shape of a curve of the actuation force curve can be compared with known shapes. The respective parameters used to identify the actuation event during the analysis were previously stored in step 42. These parameters are, for example, application-specific, customer-specific, and vehicle-specific.

[0087] All calculated actuation probabilities of the previously described comparisons are multiplied together to calculate an overall actuation probability. If the calculated actuation probability is greater than a first threshold, the actuation event is detected in a step 44 and an actuation signal is generated. This actuation signal can control the adjustment of the door 10 to the open position. Optionally, a wake-up signal is also generated beforehand in step 44 if the calculated actuation probability is greater than a second threshold, wherein the second threshold is smaller than the first threshold. This allows the door to be opened in advance, even if the actuation event has not yet been detected with sufficient certainty. This allows the door 10 to be opened with a particularly short delay upon detection of the actuation event.

[0088] The Fig. 4illustrates a recorded force curve on the handle element 12 in a parked vehicle. Minor vibrations and thus deformations of the handle element 12 occur, for example, due to other road users passing by. At such low forces, no actuation event is detected. Fig. 5illustrates a recorded force curve on the handle element 12 when driving through a car wash. As can be seen in area 50, the handle element 12 is exposed to stronger vibrations, which are also essentially continuous, unlike when other road users drive past. In area 52, a washing brush contacts the handle element 12, whereby the handle element 12 is exposed to large forces and thus deformations. However, due to the analysis and consideration of the data and threshold values ​​described above, no actuation event is detected. An undesirable automatic opening of the door 10 in a car wash is thus avoided.

[0089] Fig. 6illustrates in a diagram a recorded actuation force curve during actual actuation of the door 10 or the handle element 12 by a user. Due to the shape of the force curve, the actuation event can be reliably identified in the analysis. From the comparison with Fig. 5 For example, it can be seen that the actuation events in areas 54, here pulling on the handle element 12, exhibit a characteristic force curve with a well-defined force peak as the maximum and a steep, almost linear rise. Passing the washing brush over the handle element 12, on the other hand, leads to a much more irregular force curve with many consecutive local maxima in area 52.

[0090] Fig. 6has a first curve 56, which is an unprocessed, recorded actuation force curve. As can be seen, an actuation force is continuously recorded by the force sensor - the force is never zero. In the example shown, this zero point offset is due to sensor aging and / or changes in outside temperature. Therefore, the recorded, unprocessed actuation force curve is shifted by a force detection offset, whereby the second curve 58 is generated as a compensated, recorded actuation force curve. The force detection offset corresponds to a moving average value of the first curve 56. The determination of the force detection offset or the moving average is suspended if a change in the recorded actuation force curve is greater than a change threshold value. In the example shown, this is the case in the areas 54.The duration of the suspension is illustrated by further characteristic curves 60. The suspension begins when the change threshold is exceeded and ends after a predetermined period of time when the change threshold is undershot. Accordingly, as shown in . Fig. 6 As can be seen, the suspension of the determination of the force detection offset varies in length and depends on the recorded actuation force curve.

[0091] In a region 62 of the first curve 56, it can also be seen that after actuation of the handle element 12, a residual stress remains in the handle element 12. Thus, even when the handle element 12 is not actuated, a force is detected which is higher than after the other actuation events and is caused mechanically, rather than by aging and temperature fluctuations. A larger force detection offset results in this region 62, so that in a corresponding region 64 of the second curve 58 or the compensated actuation force curve, the force again corresponds to zero. The force in the region 64 can again correspond to zero. A step can also be seen at the end of the suspension of the determination of the force detection offset.Upon subsequent actuation, the residual stress in the gripping element 12 is released again, whereby a region 66 of the unprocessed, recorded actuation force curve returns to the force value typical for an unactuated gripping element 12 due to aging and temperature. In this region 66, the previously usual force detection offset reappears, so that in a corresponding region 68 of the second curve 58 or the compensated actuation force curve again corresponds to zero. The force in the region 68 can correspond to zero. A step can also be seen at the end of the suspension of the determination of the force detection offset, but here in the opposite direction. Residual stresses in the gripping element 12 can therefore also be compensated in order to improve the reliability of detecting respective actuation events.

[0092] Fig. 7schematically illustrates an actuation force curve. Shown is the actuation force curve 90 according to a specific embodiment, wherein the actuation force curve 90, shown in Fig. 7, an actuation force is plotted on the vertical axis against time on the transverse axis. Also shown is a specific level 92, a specific gradient 94, and a specific standard deviation 96 of the actuation force curve 90. The standard deviation 96 corresponds to a scatter of individual measurement points of the actuation force curve 90. The level 92 is determined with respect to an actuation force at a specific point in time and can be determined for different points in time. The gradient 94 is determined with respect to two specific points in time, and here, for example, as the average gradient 94 of the actuation force curve 90 between the two points in time. Alternatively, the gradient 94 can also be determined as the gradient at a point, i.e. as the first derivative of the actuation force curve at a specific point in time. The standard deviation 96 is determined with respect to specific values ​​of the actuation force curve in a specific time range.Both the slope 94 and the standard deviation 96 can also be determined for different times of the actuation force curve.

[0093] Calculating the probability of activation involves calculating individual probabilities for an activation. The individual probabilities for an activation are calculated individually and depending on one of the properties. Thus, an individual probability is calculated for the level 92, another individual probability for the gradient 94, and yet another individual probability for the standard deviation 96, each depending on the respective property.

[0094] The Fig. 8a to 8c schematically illustrate the calculation of individual probabilities. Fig. 8a shows schematically the calculation of the individual probability for level 92. Fig. 8b shows schematically the calculation of the individual probability for the slope 94 and Fig. 8cshows schematically the calculation of the individual probability for the standard deviation 96. In Fig. 8a the individual probability is plotted against the force, in Fig. 8b against the force per time, i.e. the gradient of the force, and in Fig. 8c against the standard deviation. It can be seen that a certain individual probability is assigned to each specific value. For example, in Fig. 8a It can be seen that with increasing force, i.e. with increasing level 92, the individual probability for level 92 also increases. Regarding the gradient 94, it can be seen in Fig. 8b that the highest individual probability is reached in a middle range of the slope. Regarding the standard deviation 96, it can be seen in Fig. 8cshown that with increasing standard deviation 96, the individual probability for the standard deviation 96 decreases. In certain ranges of the values ​​of level, slope and standard deviation, the value of the individual probability is maximum, while the value of the individual probability outside these ranges is not maximum. In the Fig. 8a, 8b and 8c It is further shown that the same value is calculated for the individual probability within a range of a particular property. Thus, the same individual probability value can be calculated for different levels, gradients, or standard deviations.

[0095] The activation probability is calculated based on at least one of the calculated individual probabilities. For example, the activation probability can be calculated based on only one or two of the calculated individual probabilities. Alternatively, the activation probability is calculated based on all three calculated individual probabilities. Furthermore, in alternative embodiments, which are not shown in detail here, additional individual probabilities, which are not further described here, can be calculated and used to calculate the activation probability.

[0096] Fig. 9 schematically illustrates the calculation of the activation probability, or overall activation probability, based on the calculated individual probabilities. Shown in Fig. 9The probability is shown on the vertical axis, and the time is shown on the horizontal axis. The individual probabilities 100, 102, 104, and 106 are aligned with respect to time and arranged one above the other. The activation probability 100 is shown at the very top. Furthermore, the individual probability 102 for level 92, the individual probability 104 for gradient 94, and the individual probability 106 for standard deviation 96 are arranged one above the other and below the activation probability 100. The individual probabilities 102, 104, and 106 were calculated as described above, specifically for several points in time. The activation probability 100 is now calculated from these individual probabilities 102, 104, and 106 by multiplication.Alternatively, the activation probability 100 can be calculated from the individual probabilities 102, 104, and 106 using integration, averaging, summation, or other operators. The activation probability is calculated for each point in time based on the individual probability values. This is done for a time range, resulting in the progression of the activation probability 100.

[0097] For different use cases, the actuation force curve exhibits different values ​​for the properties level, gradient, and standard deviation. For example, in the use case of normal opening by the user, a high level and a moderate gradient may occur, while when the user taps the handle element 12, a medium to high level and a steep gradient occur. Other use cases exhibit different properties. An actuation event can be precisely detected using the different properties and their values.

[0098] Furthermore, the detection 22 can be performed depending not only on the individual probabilities, but also on the standard deviation itself. For example, if the standard deviation is above a third threshold, the calculation of the activation probability can be performed exclusively on the individual probabilities with respect to the level or the gradient. For example, the calculation can also be performed on the basis of several individual probabilities with respect to only one property. For example, the activation probability can be calculated on the basis of two or more individual probabilities with respect to the level or two or more individual probabilities with respect to the gradient. The two or more individual probabilities of the same property can have been calculated with respect to different points in time.

[0099] An actuation event can also be detected if the gradient is below a fourth threshold and the level is above a fifth threshold for a certain minimum duration. This allows for precise detection of the user pulling or pushing on the grip element 12 with a certain force. The actuation event can be precisely detected.

[0100] Fig. 10schematically illustrates an analog compensation of a force detection offset. A Wheatstone measuring bridge 72 is shown schematically, which has the resistors R1 to R4 and which forms a force sensor for detecting the actuation force curve. The resistors R1 to R4 each have the same electrical resistance, for example 1200 ohms. The Wheatstone measuring bridge 72 is part of an analog signal conditioning 70a. Not shown in detail is a second Wheatstone measuring bridge of a further analog signal conditioning 70b, which forms the optional second force sensor for detecting the actuation force curve. The system thus forms one or two strain gauges to detect an actuation, with each strain gauge being designed as a force sensor as such a Wheatstone measuring bridge 72, as schematically shown here.The two force sensors are designed to independently detect an actuation force curve. A potential VDD is applied to the Wheatstone bridge 72 for power supply. Potentials SG- and SG+ are also shown, which are used to detect the actuation force curve.

[0101] Furthermore, in Fig. 10A microcontroller 86 is shown schematically, which can form the evaluation device for at least partially executing steps of the method. The microcontroller 86 has an amplifier 82 and an analog-to-digital converter 84. The analog signal conditioning 70a is electrically connected to the microcontroller 86. Furthermore, as part of the analog signal conditioning 70a, a filter 74 is shown, via which the Wheatstone bridge 72 is connected to the amplifier 82. In this case, time profiles of the potentials SG-, SG+ are filtered via the filter 74 and amplified by the amplifier 82. This analog signal is then converted into a digital signal by the analog-to-digital converter 84 in order to obtain a digital signal relating to the actuation force profile.

[0102] Furthermore, the microcontroller 86 has digital outputs 80. The digital outputs 80 are designed as three-state outputs, so-called tri-state outputs 80. Either 0 V, a supply voltage of the microcontroller 86, or a high impedance can be applied to each of the digital outputs 80. Furthermore, the system has digital-to-analog converters 78a and 78b. Each analog signal conditioning unit 70a, 70b is connected to the microcontroller 86 via such a digital-to-analog converter 78a, 78b.

[0103] The digital-to-analog converter 78a has four resistors R5 to R8, which can be referred to as bits. The resistors R5 to R8 are spaced apart from each other by a factor of 3 in terms of their electrical resistance. For example, resistor R5 has an electrical resistance of 17,400 ohms, resistor R6 an electrical resistance of 52,300 ohms, resistor R7 an electrical resistance of 158,000 ohms, and resistor R8 an electrical resistance of 470,000 ohms. Using the three-state outputs, 81 states can be represented with the digital-to-analog converter 78a. The factor of 3 between the resistors R5 to R8 allows a nearly linear resolution to be achieved as the output of the digital-to-analog converter 78a. The output of the digital-to-analog converter 78a can be applied to the filtered value of the actuation force curve via an electrical connection 76.This allows the detected actuation force curve to be shifted, for example, by the force detection offset. The shifting occurs purely analogously by adding the electrical voltage applied to the digital-to-analog converter 78a to the electrical voltage output as a measurement signal by the force sensor.

[0104] Both digital-to-analog converters 78a, 78b are configured for analog compensation of the actuation force curve by a force detection offset. The two different digital-to-analog converters 78a, 78b can be controlled differently via the digital outputs 80 to compensate for a respective individual force detection offset of a respective individual Wheatstone bridge 72 and strain gauge.

[0105] A further resistor R9 is shown, via which an amplification of the actuating force curve can be implemented, for example an additional amplification to the amplification of the amplifier 82.

[0106] Referring to the schematically shown Fig. 3In accordance with the steps illustrated, the determining 23 of the point of application of the actuating force, the determining 24 of the direction of the actuating force, and the comparing 25 of the first and second actuating force curves can be carried out as part of the analysis 40 of the data. The analysis step 40 can be carried out as a function of the step of determining 16 the age of the closure element 10 and / or the handle element 12. The analysis step 40 can be carried out as a function of the step of detecting 18 the temperature. The analysis step 40 can be carried out as a function of the detection 26 of the speed. Alternatively or additionally, the detection step 44 can be carried out as a function of at least one of the steps of determining 16, 23, 24, comparing 25, and detecting 18, 26.The calculation of probabilities, such as one, several or all individual probabilities and / or the activation probability, can be carried out in at least one of the steps of analysis 40 and recognition 44. List of reference symbols

[0107] 10 Locking element / door 12 Handle element 16 Step: Determine the age of the locking element / handle element 18 Step: Determine the temperature 20 Step: Determine the actuation force curve 20a Step: Determine the first actuation force curve 20b Step: Determine the second actuation force curve 22 Step: Detect the actuation event 23 Step: Determine the point of application of an actuation force 24 Step: Determine the direction of an actuation force 25 Step: Compare the first and second actuation force curves 26 Step: Determine the speed 30 Step: Provide the unprocessed sensor signal 32 Step: Filter the sensor signal with a low-pass filter 34 Step: Shift the actuation force curve 36 Step: Determine the level of the actuation force 38 Step: Derivation of the actuation force curve 40 Step: Analyze the data 42 Step: Store comparison parameters 44 Step: Detect the actuation event and generate an actuation signal 50 Area: Background vibrationCar wash 52 Area: Contact between washing brush and handle element 54 Area: Actuation by pulling on the handle element 56 First curve / unoffset actuation force curve 58 Second curve / offset actuation force curve 60 Characteristic curve for duration of exposure 62 Area: remaining residual voltage 64 Corresponding area 66 Area: usual force value 68 Corresponding area 70a, b Analog signal conditioning 72 Wheatstone bridge 74 Filter 76 Electrical connection 78a, b Digital-to-analog converter 80 Digital outputs 82 Amplifier 84 Analog-to-digital converter 86 Microcontroller 90 Actuation force curve 92 Level 94 Slope 96 Standard deviation 100 Actuation probability 102 Individual probability level 104 Individual probability slope 106 Individual probability standard deviation SG-, SG+ Potentials R1-R9 Resistance VDD Potential

Claims

1. A method for detecting an actuation of a closure element (10) of a motor vehicle, comprising at least the following steps: - detecting (20) an actuation force curve acting on the closure element (10), in particular a handle element (12) of the closure element (10); and - detecting (22) an actuation event as a function of the detected actuation force curve.

2. The method according to claim 1, wherein the method comprises a step of detecting (18) a temperature of the handle element (12) with an integrated temperature sensor of a control device, and wherein at least one of the detecting (20) of the actuating force curve and the detecting (22) of the actuating event is carried out as a function of the detected temperature of the handle element (12).

3. Method according to one of the preceding claims, wherein the detection (20) of the actuating force curve comprises a detection (20a) of a first actuating force curve with a first sensor (13a) and a detection (20b) of a second actuating force curve with a second sensor (13b), wherein the first and the second sensor (13a, 13b) are spatially spaced from one another.

4. The method according to claim 3, wherein the method comprises a step of determining (23) a point of application of an actuating force and / or determining (24) a direction of an actuating force based on the detected first and second actuating force curves.

5. Method according to one of the preceding claims, wherein the detection (20) of the actuation force curve is carried out with a reduced sampling rate after a certain period of time without a detected actuation event.

6. The method according to any one of the preceding claims, wherein the step (22) of detecting the actuation event comprises calculating an actuation probability, wherein the actuation event is detected if the calculated actuation probability is greater than a first threshold value, in particular wherein the first threshold value is determined as a function of the detected actuation force curve.

7. The method according to claim 6, wherein the actuation force curve (90) has a level (92), a gradient (94) and a standard deviation (96) as properties, wherein the calculation of the actuation probability (100) comprises calculating individual probabilities (102, 104, 106) for an actuation, wherein the individual probabilities (102, 104, 106) for an actuation are each calculated only as a function of one of the properties, and wherein the actuation probability (100) is calculated based on at least one of the calculated individual probabilities (102, 104, 106).

8. Method according to one of the preceding claims, wherein the method comprises a step of detecting (26) a speed of the motor vehicle and the detection (22) of the actuation event is deactivated if the detected speed is greater than a threshold speed.

9. Method according to one of the preceding claims, wherein a force detection offset is taken into account when detecting the actuating force curve.

10. Method according to one of the preceding claims, wherein the force detection offset is determined as a function of the detected actuation force curve, wherein the determination of the force detection offset is suspended if a change in the detected actuation force curve is greater than a change threshold value.

11. Method according to one of the preceding claims, wherein the force detection offset is taken into account via an analog compensation.

12. System for detecting an actuation of a closure element (10) of a motor vehicle, in particular wherein the system is designed to carry out the method according to one of the preceding claims, wherein the system has a force detection device which is designed to detect an actuation force curve acting on the closure element (10), in particular a handle element (12) of the closure element (10), and an evaluation device which is designed to detect an actuation event as a function of the detected actuation force curve.

13. System according to claim 12, wherein the force sensing device comprises a strain gauge as a force sensor, which is designed as a Wheatstone bridge (72).

14. System according to one of claims 12 or 13, wherein the force detection device comprises a first force sensor and a second force sensor which are configured independently of one another to detect the actuation force curve.

15. System according to claim 14, wherein the system has a first digital-to-analog converter (78a) for the first force sensor and a second digital-to-analog converter (78b) for the second force sensor, wherein both digital-to-analog converters (78a, 78b) are controlled via digital outputs (80) of the evaluation device (86) and wherein the digital-to-analog converters (78a, 78b) are configured for analog compensation of the actuation force curve by a force detection offset.

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