Method for operating a weight detection system for a motor vehicle or a trailer, corresponding weight detection system and motor vehicle and trailer

Abstract

A method for operating a weight detection system (16) for a motor vehicle (10) or a trailer, wherein a processor circuit (18) of the weight detection system (16) receives at least one sensor signal (Z) from a sensor arrangement (17) of the weight detection system (16), which sensor signal is dependent on a body weight of a body (11) of the motor vehicle (10) or trailer acting on a chassis (12) and / or a support, characterized in that the at least one received sensor signal (Z) successively signals individual measured values measured at different times, wherein a time series from several measurements is generated by means of the sensor arrangement (17), and the temporal course of the weight value of the body weight is sampled, and in that descriptive data (20) of at least one signal characteristic (21) is stored in the processor circuit (18), which describes a possible signal course of the at least one sensor signal (Z).as it results for a respective predetermined event (E) associated with a vibration (26) and / or a weight shift of at least one part of the motor vehicle (10) or trailer while maintaining the body weight, wherein the respective signal characteristic (21) describes the event (E) as a noise superimposed on a weight value of the body weight and / or as a structure-borne sound signal and / or as a jolt and / or as an impact, and the at least one received sensor signal (Z) is checked for a match with the at least one signal characteristic (21) by means of a predetermined comparison routine, and if the comparison routine signals a match, the presence of the event (E) described by the matching signal characteristic (21) is signaled.

Description

[0001] The invention relates to methods for operating a weight detection system for a motor vehicle or a trailer. Such a weight detection system can be provided, for example, in a truck to measure the weight of the truck's body acting on the chassis. The invention also includes a weight detection system for implementing the method, as well as a motor vehicle and a trailer each having such a weight detection system.

[0002] So-called static vehicle weight detection systems are designed to measure the vehicle's weight when stationary. The vehicle weight detection sensors required for this can detect the weight in various ways, for example, by measuring the height between the vehicle frame (chassis) and a chassis axle, by measuring strain on the axle, or by measuring inclination on the spring. However, since each of these systems is a static weight detection system, it is necessary to detect when the vehicle is moving and when it is stationary. This requires additional sensors or additional information from a vehicle's communication bus (e.g., CAN - Controller Area Network).This makes vehicle weight recording systems technically undesirably complex during vehicle integration, as additional information regarding vehicle speed is required, which makes the technical equipment of a weight recording system complex.

[0003] A weight detection system with its sensor array is just one of many measuring devices required in a motor vehicle. Events such as the presence or stay of a person in the vehicle, the theft of fuel or cargo, or even the loss of cargo are preferably also monitored or detected, each of which requires at least one additional sensor.

[0004] Typically, a dedicated sensor system from a manufacturer is required for each event to be monitored. This system features the necessary sensor arrangement and a control unit for processing the sensor signals. Detecting a person in a vehicle is particularly complex, as this may even require the use of an interior camera. However, verifying a person's presence is important, for example, to monitor prescribed driving and rest times for truck drivers or to verify compliance with these.

[0005] DE 10 2016 213 834 A1 discloses that the axle load sensor of a truck's weight monitoring system can also be used to detect fuel theft. The weight detection system is regularly activated while the truck is parked and then checked to determine whether the truck's weight has changed. These cyclical measurements allow individual statistical measurements, such as a weight reading per minute, to be checked to determine whether a trend in the values indicates fuel pumping. By evaluating the measurements from multiple sensors, it is also possible to determine whether a weight reduction has occurred in the area of the axle that also carries the fuel tank. This is considered a further indication of fuel theft.

[0006] DE 10 2013 003 893 A1 discloses an arrangement in which weight determination is implemented on a vehicle itself. In this arrangement, air springs containing pressure sensors are provided between a vehicle body and a suspension frame. These pressure sensors are intended to emit an electrical signal that is a function of the weight of the vehicle body and payload. At a constant vehicle speed, the air pressure is intended to change periodically, thus resulting in a periodic signal. From this periodic signal, a vehicle speed is to be determined in a calculation and display unit.

[0007] WO 2017 / 183 026 A1 discloses an automatic load detection system for a vehicle with tires. At least one sensor is provided that detects a distance that varies based on the compression of the tire under a load. The load detection system is intended to detect, for example, whether a child has been left behind in the vehicle or whether goods or fuel have been stolen from the vehicle.

[0008] The subsequently published document DE 10 2019 218 914 A1 discloses a method for identifying an event that leads to a mechanical excitation of at least one vehicle component of a vehicle. The mechanical excitation is detected by at least one sensor unit, which is provided on the vehicle component and / or on at least one vehicle component connected to it, generates measurement signals characterizing the mechanical excitation, and makes them available to an evaluation unit. In the method, a sample data set characterizing at least one predetermined event is also determined, which includes at least one comparison value.Furthermore, by means of the evaluation unit, at least a part of the measurement signals is compared with the at least one comparison value taking into account at least one comparison criterion, and if the comparison criterion is fulfilled, the event is assigned to the predetermined event and thus identified.

[0009] The invention is based on the object of providing a sensor system in a motor vehicle or a trailer with which an event in the motor vehicle or trailer can be detected with little technical effort.

[0010] The object is achieved by the subject matter of the independent patent claims. Advantageous embodiments of the invention are described by the dependent patent claims, the following description, and the figures.

[0011] The invention comprises a method for operating a weight detection system for a motor vehicle, wherein a processor circuit of the weight detection system receives at least one sensor signal with a temporal profile from a sensor arrangement of the weight detection system, which signal is dependent on or describes a body weight of a motor vehicle body acting on a chassis of the motor vehicle. The body of a motor vehicle is its so-called spring-mounted mass, i.e. the frame of the motor vehicle supported by the chassis with its wheels and the components mounted thereon (e.g., driver's cab, loading area, engine, fuel tank). If the motor vehicle is loaded, for example, by a passenger getting in or cargo being loaded, the body weight increases and presses with a gravitational force onto the frame, the springs, and the axles of the chassis.

[0012] This acting weight of the structure, i.e. the structure weight, can be measured by the weight detection system. The sensor arrangement of the weight detection system can have one or more sensors, with each sensor providing a sensor signal that successively signals individual measured values measured at different times. The sensor signal can be generated as an analog, continuous electrical signal or as a digital signal. Each sensor can have one "channel" with sensor data from the respective sensor. It is important here that the sensor arrangement does not determine a single measured value for the weight, but rather generates a time series from multiple measurements.By means of the sensor arrangement, the temporal course of the weight value of the body weight is thus sampled, preferably with a sampling frequency greater than 0.1 Hz, in particular greater than 1 Hz, particularly preferably with more than 10 Hz. In the case of several sensors, continuous or sampled, time-synchronized measurement signals are obtained from all sensors involved.

[0013] The weight detection system can therefore also be used to detect a rocking, bobbing, or vibration of the body. Rocking, bobbing, or vibration is generally referred to as "vibration" in the following, meaning it involves a variation or change in the measured weight of the body, such as occurs with a constant body weight due to springy or swinging movements of the body on the chassis. The acceleration forces acting here are superimposed on the weight of the body. Thus, at least one sensor signal contains a weight-related and a movement-related component. This can be evaluated both when the vehicle is stationary and when the vehicle is moving. The weight detection system is particularly advantageous for measurements when the vehicle is stationary, but there are also advantageous applications in which it can be used while the vehicle is moving.The advantage of the weight detection system is that the journey can be recognized from the dynamics of the measured values of the respective sensor signal of at least one sensor signal (e.g. based on the frequency / frequency spectrum and / or the amplitude of the change in the measured values that lie in the sensor signals of all sensors in a certain range or value interval (synchronous temporal change in several or all sensor signals)).

[0014] To achieve this objective, the invention comprises storing descriptive data for at least one signal characteristic in the processor circuit. Such a signal characteristic describes, for the at least one sensor signal, a characteristic of a possible signal profile as it results for a respective predetermined event associated with a vibration and / or a weight shift of at least one part of the motor vehicle. These are, in particular, events that can occur while maintaining the body weight of the motor vehicle, e.g., the running of a combustion engine of the motor vehicle.The at least one received sensor signal is checked for a match with the at least one signal characteristic using a predetermined comparison routine. If the comparison routine signals a match, the presence of the event described by the matching signal characteristic is signaled. In other words, the respective sensor signal of the at least one sensor of the sensor arrangement is used to detect an event, namely a dynamic event, that is accompanied by a vibration of the body of the motor vehicle or at least a part of the body and / or a weight shift.The weight detection system is therefore not only used for a statistical measurement of the body weight, but is also used for an additional purpose in that at least one sensor signal (continuous or as a sampled signal, in particular as a digital signal) is generated by means of the sensor arrangement and thus a vibration and / or weight shift in a part of the motor vehicle is recognized or detected.

[0015] The invention is based on the realization that an event can be identified by a characteristic time profile of the at least one sensor signal. For this purpose, a description of this characteristic time profile can be specified as a signal characteristic. To provide such a signal characteristic, a person skilled in the art can conduct tests, for example, using a prototype on a test site, by simulating or executing the respective event to be detected in order to measure or record the resulting at least one sensor signal of the sensor arrangement, thereby generating or recognizing the signal characteristic.The described method is intended in particular for monitoring the motor vehicle when stationary (not rolling), especially when parked (engine switched off). This is particularly advantageous because vibrations caused by rolling motion and / or an engine, in particular an internal combustion engine, are absent and therefore do not cause interference. However, the dynamics of the sensor signals are also informative while driving. Additionally or alternatively, an evaluation method, e.g., an artificial intelligence (AI) method, can be used to learn the behavior of the sensor signals and / or calibrate the weight detection system.

[0016] The invention has been described up to this point in the context of application in a motor vehicle. However, the invention can also be implemented in a trailer. The described method steps can therefore also be carried out for a trailer, in particular a trailer for a motor vehicle (motor vehicle trailer). Accordingly, the following aspects of the invention are also applicable to a trailer, but for the sake of compact description are only described in connection with a motor vehicle. The explanations nevertheless also apply to implementation in a trailer. A parked trailer or body / container can rest on a support with one or more support legs, which can then take over the function of the chassis (carrying at least part of the body weight).

[0017] The at least one sensor signal can, in particular, detect or generate the body weight at a sampling rate greater than 1 Hz, in particular 10 Hz (measurement every 100 ms), in particular greater than 50 Hz (measurement at least every 20 ms). This allows a relative movement between the body and the chassis to be detected as a vibration or oscillation with frequency components possible according to the Nyquist criterion, such as those caused by rolling and / or engine operation and / or movement processes within the motor vehicle (person walking, door closing). In particular, a running combustion engine can be detected in this way.

[0018] The described comparison routine can be implemented as program code or software in the processor circuit. A comparison characteristic can be stored in the processor circuit, for example, as descriptive data.

[0019] Of course, the method can also be used while driving. The method can also detect events that lead to a change in the vehicle's body weight, such as the detection of a loss of cargo or general cargo in the vehicle. Additionally or alternatively, a quantity estimate can be made for the remaining quantity in a vehicle's tank or container. For example, while driving or while stationary, a grit truck, fire engine, or sprinkler vehicle (for liquid spreading agents or liquid manure spreading) can check how much grit or extinguishing agent is still in the vehicle's container or tank.

[0020] The invention also includes embodiments which provide additional advantages.

[0021] One embodiment comprises a first signal characteristic for a parking event in which the motor vehicle is stationary and / or an engine of the motor vehicle is switched off, and a second signal characteristic for a driving event in which the motor vehicle is rolling and / or an engine of the motor vehicle is running, and the processor circuit uses these two signal characteristics by means of the comparison routine to determine and signal whether the motor vehicle is currently stationary or parked or the opposite is the case. In particular, the frequency or the spectrum and / or the symmetry of the signals differ when stationary and when moving, which can be described by the respective signal characteristic. In other words, the weight detection system itself can determine whether the motor vehicle is stationary, parked or moving.Thus, the so-called statistical weight measurement described above (stationary or parked state is necessary for the weight measurement) can be controlled by the weight recording system itself, i.e. no external information, for example from a communication bus, or an additional sensor is necessary to signal whether the motor vehicle is currently stationary.

[0022] Engine running detection may be disadvantageous in some applications, as some vehicles also require the engine to be on during loading and unloading (e.g., cement, liquids, etc., which are discharged by pumps, cranes, and other devices on the vehicle).

[0023] One embodiment comprises starting a weight determination routine, by means of which the body weight is determined by means of the sensor arrangement, wherein, in the event that the comparison routine signals that the motor vehicle or the trailer is stationary, a weight determination routine GB stop , which is designed for standstill, is started during standstill, and in the event that a journey is signalled by the comparison routine, a weight determination routine GB mov, which is designed for driving, is started while the vehicle is moving. However, it can also be provided that a weight determination routine, through which the body weight is determined using the sensor arrangement, is started while the vehicle is stationary only if the comparison routine signals that the vehicle is stationary. If it is signaled that the vehicle is stationary, the statistical weight determination routine described above can be started automatically by the processor circuit. This means that when the weight determination routine is started, it is ensured that the vehicle is stationary, i.e., not rolling and / or the engine is switched off. This results in a reliable and interference-free measurement of the body weight.The body weight is primarily determined while the vehicle is stationary, but it can also be determined while driving, but in this case using a different, adapted weight determination routine. When the weight determination routine is started can be determined by a state-of-the-art algorithm. Only the automated selection is relevant here. The weight determination routines GB can also be used. stop and GB mov be taken from the state of the art.

[0024] With the described sampling rate or the described rate of consecutive weight measurements, a movement of a person and / or an object, for example, a piece of cargo, taking place within the structure of the motor vehicle can be detected. One embodiment comprises the at least one signal characteristic describing a movement event of a person and / or an object in the motor vehicle and / or a movement event of a component of the motor vehicle and / or a change in a weight distribution in the motor vehicle and / or a vibration (e.g., a door slamming) and / or a temporal sequence of vibrations (e.g., footsteps). In this way, the actuation of a component of the motor vehicle, for example, a door and / or tailgate, can be detected. The walking of a person could also be detected as a characteristic sensor signal in tests with a weight detection system.

[0025] During a journey, the slipping of a load can be detected. If a slipped load is detected and / or if it is detected that the load begins to slip when the vehicle accelerates (longitudinal acceleration due to accelerating and / or braking and / or lateral acceleration due to steering and / or cornering) above a threshold, compensation can be set by the vehicle's ESP (Electronic Stability Program), which prevents acceleration greater than the threshold for predetermined driving situations. ESP works particularly during acceleration and / or emergency braking to prevent the vehicle from tipping (and, in particular, trailer tipping in vehicles with trailers).

[0026] One embodiment comprises generating a respective sensor signal for different axles and / or wheels of the motor vehicle, and at least one signal characteristic for the respective event provides a location of that area of the vehicle where the associated sensor signal exhibits the greatest intensity or amplitude change, i.e., the greatest deflection. In other words, a location of the event is also provided by means of multiple sensors in the sensor arrangement of the weight detection system. Since a vibration in the motor vehicle decays or is dampened the further it is from its source, a location for the location of the event can be determined by comparing the intensity of the sensor signals from different sensors.

[0027] One embodiment comprises that the comparison routine comprises a plausibility check step which provides that the respective event is only signaled if it is detected that the body weight remains constant during the event and / or that the motor vehicle is at a standstill (i.e., no rolling event) and / or is parked (i.e., the engine is switched off). “Constant” means that the body weight does not change or only changes at a rate that is less than a predetermined maximum rate. By specifying such a maximum rate (greater than 0), it is possible, for example, to compensate for changes in the body weight during rain or snowfall. Events such as a person walking in the motor vehicle or the shifting of cargo are only plausible if the motor vehicle is not moving, i.e., stationary and / or parked.Therefore, the detection of standstill or parked state can also be used for plausibility check to avoid false detection.

[0028] Additionally or alternatively, a multiple comparison is provided at different time intervals, and the comparison routine only signals a match if a predetermined minimum proportion (e.g., more than half, or all but one, or all) of the comparisons signal the event. The detection of an event can thus be based on multiple measurements, in that the comparison routine only signals a match with a signal characteristic if multiple comparisons performed with different sections of the at least one sensor signal result in a match for a signal characteristic. This allows external influences, such as passing vehicles whose airflow can also shake the motor vehicle, to be excluded. The multiple comparison can result in more robust detection of an event through multiple measurements.For example, the external influence of a passing vehicle, whose wind shakes the vehicle, can be compensated for, as this is only reflected in one of the measurements. The measurements can be taken at intervals of at least two seconds, preferably at least five seconds, but no more than five minutes.

[0029] One embodiment comprises detecting at least one predetermined process as a temporal sequence of successively occurring events, each of which is described by a signal characteristic. A distinction is therefore made here between individual events and processes. An event describes a homogeneous signal characteristic, e.g., steps, while a process is a sequence of different signal characteristics, e.g., steps followed by a door slamming. A process here is therefore a sequence of several individually detectable events. The events can be combined to describe a process that is more extensive or complex than the event. A description of the temporal sequence of successively occurring events can, for example, be provided by a state machine.The advantage of defining a process as a sequence of events is that a tolerance value can be specified for a time interval between the events. For example, if a person gets into a truck and opens the vehicle door, then climbs the ladder into the cab, and then slams the door shut, describing this as a single event can lead to the problem that a person takes different pauses between these activities (opening the door, entering the vehicle, closing the door) depending on the situation. If described as a single event (only one signal characteristic), these pauses would have to be compensated or modeled.If, on the other hand, each activity (opening the door, entering the vehicle, closing the door) is described as an individual event by a separate signal characteristic, the time that elapses between these events can vary without affecting the detection of the process, because only the individual detections (opening the door, climbing the stairs, closing the door) in the specified order have to be waited for.

[0030] One embodiment comprises detecting theft of cargo from the motor vehicle as a process by recognizing a change of location by moving the cargo on a loading area of the motor vehicle toward a loading opening and then unloading the cargo as a reduction in the body weight of the motor vehicle and signaling this by means of an alarm signal to protect against theft of the cargo. Thus, a theft can be detected as a process that generally results from a sequence of movement events (a person moves on the loading area by first approaching a cargo, then moving the cargo, and then unloading). The theft process can therefore comprise one or more movement events, a change of location of a person and / or a cargo.In addition, a change in the weight distribution in the vehicle, such as that resulting from the movement of general cargo, can be detected. The jerking (jerk is the time derivative of acceleration) and / or rocking of the body and / or structure-borne noise associated with the movement of general cargo can also be considered as individual events. If a reduction in the body weight is also detected, an alarm signal can be generated, which, for example, triggers an audible alarm in the vehicle and / or sends a message to a person.

[0031] One embodiment comprises the detection of a person boarding or disembarking as a process, with a door opening event, a rocking of the motor vehicle, and a door closing event being detected as associated events of the process, with a distinction being made between boarding and disembarking by a change in weight before and after the sequence of events. boarding or disembarking can also be detected in the manner described as a process consisting of individual events that are described separately or separately from one another by means of a signal characteristic. A presence and / or change in position of at least one person in the motor vehicle can be evaluated using the described location tracking. A person counter can be provided that can be decremented or reduced for each person boarding. This allows the number of people in the motor vehicle to be monitored.If the front of the vehicle or the driver's cab is identified as the location of an incident, it can be determined whether the person is in the cab or at the driver's door. Similarly, a person can be detected on the loading area of the vehicle, usually in the rear of the vehicle, and a warning signal can be issued to the driver, for example, if they attempt to start the vehicle while a person is still in the loading area, or if this has at least been detected.

[0032] The invention comprises that the respective signal characteristic describes the event as noise superimposed on a weight value of the body weight and / or as a structure-borne sound signal and / or as a jolt and / or as an impact (impulse). One embodiment comprises that the respective signal characteristic describes the event as a periodic weight shift on different springs of the motor vehicle (e.g., as rocking, teetering, pounding, and / or spring movement). To evaluate the respective sensor signal, one analysis strategy or a combination of several of the aforementioned analysis strategies can be used. The "true" or actual weight value of the body weight is never measured by a sensor insofar as noise (sensor noise, vibrations in the body of the motor vehicle, rocking due to rolling motion) is always superimposed.The characteristics of this noise can now be evaluated as an indication of a specific event, for example, to detect a rolling motion. The expert can determine which noise results from which event through tests with a prototype and store a corresponding signal characteristic in the processor circuit as a description of the respective event. A structure-borne sound signal does not require any spring movement of the vehicle's chassis springs. A jolt and / or shock and / or rocking (periodic weight shift), on the other hand, is a reaction of the chassis to a force applied, such as that caused by a person moving in the vehicle. In addition to manually creating or programming an algorithm, AI software can be trained additionally or alternatively.It can also relearn during vehicle operation if an incorrect and / or correct detection (evaluated manually or by other sensors / logic) is fed back into the weight detection system. AI can also be used to learn and / or adapt filters for the sensor signals if additional indicators expand the evaluation and / or if components in the sensor signals that are classified as interference need to be attenuated.

[0033] One embodiment includes that the respective signal characteristic and the comparison routine provide that - the signal characteristic describes a respective possible time course of the at least one sensor signal and the comparison routine comprises a correlation and / or a machine learning method and / or - the signal characteristic describes signal features (e.g. cepstral coefficients or spectral components) and the comparison routine includes a statistical detector, e.g. based on a hidden Markov model and / or a machine learning method and / or - the signal characteristic contains a quantitative description of predetermined signal properties and the comparison routine determines whether the quantitative description is correct, wherein the quantitative description indicates in particular a maximum deviation from a signal mean value and / or a signal variance.

[0034] The detection and filtering, i.e. the comparison with the at least one signal characteristic, can be supplemented or / or refined and / or automated additionally or alternatively via extended information, in particular in and / or from a cloud (internet server), by combining measured values from different vehicles.

[0035] A signal characteristic can, for example, describe an event based on the frequency / frequency spectrum and / or the amplitude of the change in the measured values that lie in the sensor signals of all sensors in a certain range or value interval (synchronous temporal change in several or all sensor signals).

[0036] Information can also be derived by comparing and / or juxtaposing and / or adjusting the sensor signals of different sensors, ie a signal characteristic can also describe differences between two or generally several sensor signals and / or a temporal development of one or more sensor signals.

[0037] The respective signal characteristic can, for example, be represented as a table or file with a description of a sensor signal, or as a statistical description (mean, variance), or by the aforementioned quantitative signal characteristics (maximum value, minimum value, duration value of a specific signal curve, e.g., a deflection from the mean to a maximum and back to a mean, or from a mean to a minimum and back to a mean). Correlation can be used to identify a specific signal shape in the respective time course. A statistical detector can, for example, evaluate a temporal sequence of a change in the mean and / or variance.A quantitative description or analysis, for example based on a respective maximum value and / or minimum value, is particularly robust because it still enables robust detection of a corresponding event even with a changing form of the respective sensor signal, as can occur due to variations in the events (people of different weights, different movements of the people). A signal characteristic can also be described by an artificial neural network or another machine learning (ML) method. The recognition of the signal characteristic in the at least one sensor signal is then achieved by providing it as an input signal to the artificial neural network or ML method. This means that the described comparison routine is implemented by the artificial neural network or the ML method. The signal characteristic can be trained, for example, by recreating the event to be detected.A feedback channel regarding the accuracy of the detection and / or a training target can also be specified here. This can be done manually and / or by transmitting data from other vehicles, e.g., via a cloud. Data about typical time profiles can be received from other vehicles, for example.

[0038] One embodiment comprises that the sensor arrangement generates the at least one sensor signal by at least one sensor, which respectively carries out the following measuring principle: - a height measurement in a respective air bellows of an air spring (in an air-sprung motor vehicle) and / or between a frame (e.g. a chassis) and axle, which is arranged parallel to a leaf spring in a tube or integrated in a shock absorber, wherein the height measurement is carried out in particular by means of ultrasound (time of flight measurement of the sound propagation time) and / or - a strain measurement on a respective axis by means of a strain sensor, which in particular has at least one strain gauge (e.g. as a film) and / or a piezo-resistive semiconductor material (integrated in a MEMS chip (MEMS - Microelectro mechanical system)), and / or - a pressure measurement in the said air bellows.

[0039] The described measurement methods have proven particularly reliable for detecting events based on sensor signals or a single sensor signal. They allow the generation of weight values with a measurement rate greater than 0.1 Hz, in particular greater than 1 Hz. This allows a corresponding temporal resolution of the at least one sensor signal to be achieved, and accordingly, events with spectral components above 0.1 Hz or above 1 Hz can also be evaluated.

[0040] One embodiment includes the processor circuit executing the comparison routine autonomously, independent of bus information from a communication bus. As already explained, there is an interest in integrating a weight detection system into a motor vehicle with as little technical integration effort as possible. If the weight detection system is designed autonomously to execute the comparison routine, no communication via a vehicle bus or communication bus, such as a CAN bus, is necessary for the comparison routine. Thus, for example, in the manner described, the weight detection system can autonomously determine whether the motor vehicle is stationary and, accordingly, can automatically start a weight determination routine when a stationary motor vehicle is detected.

[0041] The embodiments of the method are particularly helpful and / or easy to implement and / or precise in recognition when used in a preselected combination.

[0042] The invention also relates to a weight detection system for a motor vehicle, wherein, in the weight detection system, a sensor arrangement is configured to generate at least one sensor signal correlated with a body weight of the motor vehicle acting on a chassis of the motor vehicle, and a processor circuit is configured to receive the at least one sensor signal from the sensor arrangement and to check the at least one received sensor signal for a match with the at least one signal characteristic using a predetermined comparison routine. The weight detection system is configured to carry out a method according to one of the preceding claims.

[0043] The processor circuit can be implemented on the basis of at least one microprocessor. However, a microprocessor can also be used. The processor circuit can further comprise a data memory in which the described descriptive data for the at least one signal characteristic and / or a program code / software for operating the processor circuit can be stored. In particular, the described comparison routine can also be implemented this way. The weight detection system can, for example, comprise a bus connection for connection to a communications bus, for example a CAN bus, in order to transmit a corresponding event signal into the communications bus upon detection or recognition of an event. Additionally or alternatively, the raw data of the sensor signals can also be transmitted to the aforementioned cloud, where they can be evaluated, in particular using automatic AI algorithms.A cloud server computer can combine and / or filter the raw data, particularly based on data from other vehicles, to prepare it for event detection and / or to detect an event. The data from other vehicles can, for example, provide a basis for statistical analysis, for example, by checking which vibrations, e.g., which deflections, occur in multiple vehicles for a predetermined region in which the vehicles and also the motor vehicle for which event detection is to be carried out are located. For example, if a passing train causes vibrations in several vehicles, the event cannot be an internal vehicle event of a single vehicle.

[0044] The invention also relates to a motor vehicle with a weight detection system. The motor vehicle is designed, in particular, as a truck, passenger car, construction vehicle, fire engine, gritter (for road salt), or an agricultural or construction machine. A trailer with the weight detection system can also be provided in the manner described. It can be, for example, a drawbar trailer or a semi-trailer. In the case of a trailer or semi-trailer (e.g., with a container), the measurement can also be linked to a logistics unit or a vehicle via a radio unit. Supports used for a stationary trailer can also be equipped with sensors.

[0045] The invention also includes combinations of the features of the described embodiments.

[0046] Exemplary embodiments of the invention are described below. Shown are: Fig. 1 a schematic representation of an embodiment of the motor vehicle according to the invention, Fig. 2 a schematic representation of an embodiment of the weight detection system according to the invention, as it is used in the motor vehicle of Fig. 1 may be provided; Fig. 3 a diagram with a schematic curve of a sensor signal from a sensor arrangement of the weight detection system of Fig. 2; Fig. 4 a diagram with a schematic curve of two sensor signals by means of which a parking event and a driving event are detected; Fig. 5 a diagram with schematic curves of sensor signals from four sensors of the sensor arrangement.

[0047] The exemplary embodiment explained below is a preferred embodiment of the invention. In the exemplary embodiment, the described components of the embodiment each represent individual, independently considered features of the invention, which also further develop the invention independently of one another and are thus also to be considered as components of the invention, either individually or in a combination other than that shown. Furthermore, the described embodiment can also be supplemented by further features of the invention already described.

[0048] In the figures, functionally identical elements are provided with the same reference numerals.

[0049] Fig. 1 shows a motor vehicle 10, which may, for example, be a truck or an agricultural or construction machine. Application in a trailer, e.g., a semi-trailer, may also be provided. It shows how a body 11 of the motor vehicle 10 can be spring-mounted on a chassis 12 by means of a suspension 13. The chassis 12 can, for example, provide the wheels 14 and axles 15 of the motor vehicle 10. In order to detect the body weight of the body 11 acting on the chassis 12, a weight detection system 16 can be provided in the motor vehicle 10. The weight detection system 16 can have a sensor arrangement 17 with one or more sensors S1, S2, S3, S4 and a processor circuit 18. If only one sensor is provided, the processor circuit 18 and the supplied sensor can be provided in a housing or provided on an axle 15. Fig. 1 shows how several sensors S1, S2, S3, S4 of the sensor arrangement 17 can be connected to a common processor circuit 18. Additionally or alternatively, a sensor can also be installed in the center of an axle, in particular on the front axle. Each sensor of the sensor arrangement 17 can provide a sensor signal Z consisting of sensor values or measured values to the processor circuit 18. The sensor signal Z can be used to signal to the processor circuit 18 a time profile or a plurality of successively measured values from the respective sensors S1, S2, S3, S4 relating to a measured variable that depends on the body weight. The processor circuit 18 can use the sensor signals Z to detect at least one event E occurring in the motor vehicle 10 on the basis of description data 20.Thus, based on the sensor signals Z, in addition to the pure weight measurement of the body weight, monitoring or detection of at least one event E can be carried out in the motor vehicle 10 using the sensor signals Z. For this purpose, the description data 20 describe a respective signal characteristic 21 which comprises the sensor signals Z or at least one sensor signal Z when the respective event E occurs.

[0050] Fig. Figure 2 illustrates an exemplary embodiment of the sensor arrangement 17, as it can be realized on the basis of sensors S with strain gauges 22. It shows how the body 11 with its body weight G can act on the axle 15 of the chassis 12, thereby causing a deformation (bending) of the axle 15. This bending of the axle 15 can be measured by means of at least one sensor S ( Fig. 2 shows two sensors S) for the axle 15. A respective strain gauge 22 or an arrangement of several strain gauges 22 can be arranged on a plate or strip 23, which can be connected to the axle via support elements 24.

[0051] Bending forces 25 acting in the axle 15 can bend the strip 23 with the strain gauges 22 via the support elements 24. The support elements 24 can be implemented, for example, as a metal block. The strip or plate 23 can be made of metal, for example, aluminum or steel. A sensor S at each end of the axle 15 can distinguish or detect, by comparing the sensor signals Z, which side of the vehicle (right or left) bears more of the body weight G. This allows the distribution of a load to be detected.

[0052] The weight measurement can be supplemented, in particular, by at least one position sensor (axle or vehicle sensors). These can be used to compensate for measurement errors and / or to reduce the influence of disturbances. They can also provide additional information for the aforementioned evaluations. A position sensor is particularly advantageous for detecting axle inclination when using a sensor per axle. However, a position sensor can also be used in a control unit.

[0053] Fig. 3 illustrates how, over time t (shown here in seconds s), the sensor signal Z can reflect a shock 26, for example a vibration, in the body 11 or in the chassis 12. A sampling rate for the sensor signal Z can be in a range greater than 1 Hz, in particular greater than 10 Hz, preferably greater than 50 Hz. For example, sampling values or measured values can be provided in the sensor signal Z with a time interval of 10 ms. It is shown how the sensor signal Z can be reflected in the event that a parking event E stop is present, fluctuates between a maximum value 27 and a minimum value 28 around a mean value M. Since the body weight itself does not change, but is specified as a constant mean value by the mean value M, the fluctuations or changes between the minimum value 27 and the maximum value 28 result from the vibration 26. If a driving event E occurs in the motor vehicle 10 mov, the vibrations 26 are stronger or larger, so that the sensor signal Z runs between a maximum value 29 and a minimum value 30 with a larger variance or larger deflections around the mean value M. The description data 20 can describe a signal characteristic 21, which states that a parking event E stop is present when a deviation of the sensor signal Z from the mean value M is smaller than in a tolerance band 31 with a deviation 32 to a maximum tolerance value T max and a tolerance value of 33 to a minimum tolerance value T min runs, which in Fig. 3 is described by the description of the signal characteristic 21. A driving event E movoccurs when, on the other hand, sensor signal Z fluctuates outside the tolerance band 31 around the mean value M. As an analysis time window 34 for detecting or distinguishing between the events E in general, a time period in a range of ten seconds to two minutes can be used, for example.

[0054] Fig. 4 illustrates how the respective sensor signal Z1, Z2 of two sensors on different sides of the vehicle (see Fig. 2) an axis 15 can be distinguished between a standstill and a movement. This is a real measurement that illustrates that the Fig. 3 can be reliably implemented. It can even be a braking event E breakcan be detected, by which the axle 15 is relieved of load due to a pitching movement of the motor vehicle 10. A comparison of the sensor signals Z1, Z2 indicates that a load difference 35 exists between the two sides of the motor vehicle, so that a load or cargo in the motor vehicle 10 can also be localized or located.

[0055] Fig. 5 illustrates further examples of sensor signals Z1, Z2, Z3, Z4, which are obtained by way of example from the sensors S1, S2, S3, S4 of the sensor arrangement 17 of Fig. 1 can be generated. It is shown that different events E1, E2, E3, E4, E5 can be distinguished and detected based on the sensor signals Z1, Z2, Z3, Z4, whereby these can be the following events: E1: Fuel loss right E2: Fuel loss left E3: Open door left E4: Person gets out (left) E5: Charge loss (piecewise, therefore stepped progression)

[0056] The weight recording system is therefore based on a measuring device for determining the axle load or the total weight of the motor vehicle. The weight recording system can be integrated into the vehicle. By using such a sensor system, various events E can be detected in the vehicle. By continuously analyzing the sensor data (sensor signals), the events are recognized and differentiated based on the resulting signal characteristics. Based on the characteristic change in load, load distribution and thus a characteristic change in the sensor data, conclusions can be drawn about the respective known events. Through the analysis, the sensor data can be used to detect, for example, the removal of the load while the vehicle is stationary or in motion. Additionally or alternatively, it can be detected whether a person has gotten in / out and thus whether a person / driver is in the vehicle.It is also possible to detect a person who is on / in the vehicle, e.g. on the loading area, which is detected by the weight distribution.

[0057] By analyzing the sensor data from a weighing system or weight recording system integrated into the vehicle, which may be required by law under certain conditions or is optional, information about additional events can be recorded without additional sensor components. The advantage lies in the detection of events that could be recognized as side effects of a measurement system not specifically selected for this purpose. Without additional hardware, the measurement system can be enhanced with added value, which can be implemented cost-effectively. This represents a decisive advantage over systems that require additional, specific sensors. Implementation can therefore be achieved solely through suitable evaluation in the processor circuit of the sensor readout device.

[0058] This reduces development times and integration costs for the vehicle manufacturer.

[0059] In addition, self-starting can also be implemented for weight detection without the need to provide information about the vehicle's standstill via a communication bus. This is because vehicle weight detection sensors have a known noise in the signal during static measurements, i.e., when the vehicle is stationary. This noise becomes significantly higher when the vehicle is moving, as unevenness in the road or the vehicle's inertia during acceleration have a direct impact on the signals from the vehicle weight detection sensors. By evaluating the noise and measuring the maximum and minimum values, travel detection can be implemented (see Fig. 3 and Fig. 4).

[0060] On-board weighing (vehicle-specific weight recording or vehicle-specific weight recording system) thus provides additional information for journey detection (E stop , E mov ). This information can also serve as redundancy for functional safety functions.

[0061] Overall, the example shows how the invention can provide event detection or vehicle movement detection based on a vehicle weight detection system.

Claims

[1] Method for operating a weight detection system (16) for a motor vehicle (10) or a trailer, wherein a processor circuit (18) of the weight detection system (16) receives at least one sensor signal (Z) from a sensor arrangement (17) of the weight detection system (16), which sensor signal is dependent on a body weight of a body (11) of the motor vehicle (10) or trailer acting on a chassis (12) and / or a support, characterized bythat the at least one received sensor signal (Z) successively signals individual measured values measured at different times, wherein a time series is generated from several measurements by means of the sensor arrangement (17) and the temporal course of the weight value of the body weight is sampled or sampled, and that in the processor circuit (18) description data (20) of at least one signal characteristic (21) are stored, which describes a possible signal course of the at least one sensor signal (Z) as it results for a respective predetermined event (E) associated with a vibration (26) and / or a weight shift of at least one part of the motor vehicle (10) or trailer while maintaining the body weight,wherein the respective signal characteristic (21) describes the event (E) as a noise superimposed on a weight value of the body weight and / or as a structure-borne sound signal and / or as a jolt and / or as a shock, and the at least one received sensor signal (Z) is checked for a match with the at least one signal characteristic (21) by means of a predetermined comparison routine, and if the comparison routine signals a match, the presence of the event (E) described by the matching signal characteristic (21) is signaled. [2] Method according to claim 1, wherein a first signal characteristic (21) for a parking event (E stop ), in which the motor vehicle (10) or the trailer is stationary and / or an engine is switched off, and a second signal characteristic (21) for a driving event (E mov), in which the motor vehicle (10) or the trailer is rolling and / or the engine is in operation, is predetermined and the processor circuit (18) uses these two signal characteristics (21) by means of the comparison routine to determine and signal whether the motor vehicle (10) or the trailer is currently stationary. [3] Method according to claim 2, wherein a weight determination routine, by means of which the body weight is determined by means of the sensor arrangement (17), is started, wherein in the event that the comparison routine signals that the motor vehicle (10) or the trailer is stationary, a predetermined weight determination routine GB stop , which is designed for standstill, is started during standstill, and in the event that a journey is signalled by the comparison routine, a predetermined weight determination routine GB mov , which is designed for driving, is started while driving. [4] Method according to one of the preceding claims, wherein the at least one signal characteristic (21) describes a movement event of a person and / or an object in the structure (11) and / or a component of the structure (11) as a change in a weight distribution in the structure (11) and / or as a vibration (26) and / or as a temporal sequence of vibrations (26). [5] Method according to one of the preceding claims, wherein a respective sensor signal is generated for different axles (15) and / or wheels (14) of the chassis (12) and / or support legs of the support and at least one signal characteristic (21) for the respective event (E) indicates a location of that vehicle area where the location-associated sensor signal (Z) has a greatest intensity. [6] Method according to one of the preceding claims, wherein the comparison routine comprises a plausibility check step which provides that the respective event (E) is only signalled if it is detected that the body weight remains constant during the event (E) and / or that the motor vehicle (10) or trailer is at a standstill and / or in a parked state, and / or that in the case of a multiple comparison at different time intervals, a predetermined minimum proportion of the comparisons signals the event (E). [7] Method according to one of the preceding claims, wherein at least one predetermined process is recognized as a temporal sequence of successively occurring events, each of which is described by its own signal characteristic (21). [8] Method according to claim 7, wherein a theft of general cargo is detected as an operation by detecting as events (E) a change of location by moving the general cargo on a loading area of the body (11) towards a loading opening and subsequently an unloading operation of the general cargo as a reduction in the body weight of the body (11) and signaling this for theft protection of the general cargo by means of an alarm signal. [9] Method according to claim 7 or 8, wherein a person boarding or disembarking is recognized as the process, wherein a door opening event, a rocking of the body (11) and a door closing event are recognized as associated events of the process, wherein a distinction is made between boarding and disembarking by a change in weight before and after the sequence of events. [10] Method according to one of the preceding claims, wherein the respective signal characteristic (21) describes the event (E) as a periodic weight shift to different springs of the chassis (12) and / or the support. [11] Method according to one of the preceding claims, wherein the respective signal characteristic (21) and the comparison routine provide that - the signal characteristic (21) describes a respective possible time profile of the at least one sensor signal (Z) and the comparison routine comprises a correlation and / or a method of machine learning and / or - the signal characteristic (21) describes signal features and the comparison routine comprises a statistical recognizer based on a hidden Markov model and / or a machine learning method and / or - the signal characteristic (21) contains a quantitative description of predetermined signal properties and the comparison routine determines whether the quantitative description is correct, wherein the quantitative description indicates in particular a maximum deviation (32) from a signal mean value (M) and / or a signal variance. [12] Method according to one of the preceding claims, wherein the at least one sensor signal (Z) is generated by the sensor arrangement (17) by at least one sensor which respectively carries out the following measuring principle: - a height measurement in a respective air bellows of an air spring and / or between a frame and an axle (15) arranged parallel to a leaf spring in a tube or integrated in a shock absorber, wherein the height measurement is carried out in particular by means of ultrasound, and / or - a strain measurement on a respective axis (15) by means of a strain sensor, which in particular has at least one strain gauge and / or a piezo-resistive semiconductor material, and / or - a pressure measurement in the air bellows. [13] Method according to one of the preceding claims, wherein the processor circuit (18) carries out the comparison routine autonomously and independently of bus information of a communication bus. [14] Weight detection system (16) for a motor vehicle (10) or a trailer, wherein in the weight detection system (16) a sensor arrangement (17) is configured to generate at least one sensor signal (Z) which is correlated with a body weight of a body (11) of the motor vehicle (10) or trailer acting on a chassis (12) and / or a support, and a processor circuit (18) is configured to receive the at least one sensor signal (Z) from the sensor arrangement (17) and to check the at least one received sensor signal (Z) with at least one signal characteristic (21) for a match by means of a predetermined comparison routine, characterized by that the weight detection system (16) is designed to carry out a method according to one of the preceding claims. [15] Motor vehicle (10) or trailer, each with a weight detection system (16) according to claim 14.

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