DE102008053005A1 - Method and system for influencing the movement of a controllable in his movements vehicle structure of a motor vehicle and vehicle - Google Patents

Abstract

The invention relates to a method for generating signals for influencing the movement of a vehicle body of a motor vehicle which can be controlled or regulated in its motion sequences, the movement of the vehicle body being sensed, the sensor signals corresponding to the determined sensor values being fed to a damper controller, and the damper controller receiving at least one control signal for Actuation of actuators, in particular semi-active or active dampers, provides, by means of which the movement of the vehicle body can be influenced. It is provided that the course and / or the magnitude of the sensor signal of at least one sensor detecting the movement of the vehicle body is compared with sensor signals of at least one further sensor and depending on this comparison on a plausibility and / or an error of the at least one sensor supplied sensor signal is closed.

Description

The The invention relates to a method for generating signals for Influencing the movement of one in his movements controllable or controllable vehicle body of a motor vehicle, wherein the motion of the vehicle body is sensed, the sensor signals corresponding to the sensor values determined a damper controller supplied, the damper controller at least a control signal for controlling actuators, in particular of semi-active or active dampers, provides, by means of which the movement of the vehicle body can be influenced. The invention further relates to a system for carrying out the method and a vehicle, in particular motor vehicle, with a system for Influencing the movement of a controllable in his movements or adjustable vehicle body.

Methods and systems of the generic type are known. For example, this is off DE 39 18 735 A1 a method and a device for damping movements of chassis of passenger and commercial vehicles known in which from a sensorially detected movement of two vehicle masses by means of a signal processing circuit, a control signal for a controllable, acting on the vehicle masses actuator is formed. For a comfortable yet safe suspension tuning is provided to direct the sensor-detected signals via a signal processing circuit belonging circuit arrangement with frequency-dependent transmission behavior. This is intended to ensure that, due to the frequency-dependent processing of the sensor signals, no static characteristic is used for the actuator control or actuator control, but an actuator control or actuator control dependent on the frequency content of the movement sequence takes place. In this way, the aim of the highest possible driving comfort is to be achieved with a safe in border regions of the driving condition design of the chassis. This approach is based on the idea that the conflict of objectives between the desired ride comfort, ie comfortable and soft design, and driving dynamics, ie sporty and tight coordination, on the one hand and sufficient driving safety on the other hand should be met. For ride comfort and driving dynamics damping of the movement of the body is critical, while for a driving safety a wheel load or wheel load fluctuation is crucial.

Known are essentially three damper systems for vehicles, wherein a spring arrangement between the wheel and the structure of an actuator is connected in parallel. Are known passive, semi-active and active Damper systems. For passive damper systems is a change in the damper force during the Driving operation not provided. For semi-active damper systems The damper force can be changed by changing an oil fluid flow changed using one or more valves become. In this way, the damping properties to be changed. Semi-active damper systems work purely energy-absorbing. In active damper systems can dampening a desired damper force as well as providing energy in each direction.

Of the Desire for more comfort, safety-relevant vehicle functions and legal regulations have become ever larger Number of electronic systems in the vehicle. The increase in software implemented functions and the so associated complexity increase make it necessary to qualitative and integrate diagnostic elements into the software. A Early integration of the diagnosis becomes crucial contribute to the quality of the later product - the automobile - too secure and improve. For the diagnosis arise the following goals, with the driver on one side and the Vehicle manufacturer (OEM) on the other. The driver has direct or indirectly the expectation of the diagnosis that in the maintenance or Repair case causes are resolved quickly. It also reflects customer satisfaction through a fail-safe and thus robust electronics again. For the OEM stands in the context of Diagnose the maintainability and quality assurance of vehicles over the entire development and life cycle in the foreground.

The Suspension of a vehicle transmits occurring Forces between the roadway and the vehicle body, leaving him the central importance in terms of driving dynamics coincides. It is therefore significantly responsible for the Driving characteristics and determines significantly the ride comfort as well the driving safety. Consequently, attempts are made by constructive measures and by additional components the system behavior on to improve. This results from the purely mechanical spring and damper system through the mechatronic integration of actuators, sensors and information processing an active or semi-active chassis.

For these systems, fault detection, diagnostics and tolerance play a significant role, for which the following reasons can be formulated. The (semi-) active systems usually allow a deeper and more extensive intervention in the process than classical systems and thus can influence the process in case of a malfunction correspondingly stronger. In addition, the environmental influences occurring in a vehicle, such as mechanical stress conditions, vibrations, corrosion, temperature fluctuations and / or electromagnetic influences, demands on the installed components.

The The primary goal of the diagnosis is to find the smallest replaceable unit that is faulty and become a failure symptom in the vehicle. The special challenges for the diagnosis here are the increasing complexity of the motor vehicle. The diagnosis ensures that the cause of the error quickly and in the first attempt is found. To achieve a high diagnostic quality, this must be made measurable. It need both during development, as well present in service measured variables to achieve the goal to be able to measure. Furthermore, the sensor diagnosis can also to simplify maintenance / repairs. The information can search for the defective component accordingly the occurrence of a fault symptom easier or even superfluous do. In addition, the diagnosis is a valuable tool during the development phase of control devices.

The Diagnosis is basically in on-board and off-board diagnosis divided. On-board diagnosis is the location of a function within the vehicle; It can be used at the same time as the operating functions be executed or activated. She often becomes too referred to as vehicle self-diagnosis and normally by the customer not perceived. The electronic components of the vehicle are monitored for possible errors. Any errors will be dealt with by an application-specific error handling responding. On-board diagnostics are used in ECU development realized by the respective developer. In off-board diagnostics is the location of a function outside the vehicle; therefore it can only be carried out under certain operating conditions or activated. It is usually located in an external one Diagnostic tester in the workshop. In addition, she should not be closer to be viewed as. To communicate with the on-board diagnostics has every modern vehicle a diagnostic interface. The on-board diagnosis in an embedded system can be divided into the following elements become. The error detection includes the detection of errors in the periphery, on the one hand to the hardware of the microcontroller and on the other hand to the connected sensors and actuators. The error storage is used for storing recognized errors. The error handling includes the failure analysis, the damage and failure assessment and the Timely recovery of a stable system state. The error analysis includes the analysis of the error messages in relation to the current one Time, the current system states and other important boundary conditions. In the case of damage / failure assessment, the information is removed the error message used to prevent error propagation.

at Sensor diagnoses are distinguished between plausibility diagnoses, where the value of a sensor is within a permitted range of the current operating state, matching diagnostics which several sensors are compared with each other, "stucco" diagnosis, which checks if the value is at changed transient conditions and gradient monitoring, where a check is made, whether the increase a sensor signal is possible in real terms. In actor diagnoses Usually, the actuator is checked for an over Sensors measured control responded accordingly. For system diagnostics It is determined whether the output values of a system over a required time under changed conditions acceptable are.

In terms of Sensor errors can be divided into two classes of errors. For sensor errors such as noise, failure, overrange and outliers are directly detectable sensor errors, due to their considerable influence on the time behavior of the measurement signal can be detected with signal-based methods. For the detection of smaller offset and gain errors usually model-based procedures are necessary. For the detection of process errors are also model-based methods necessary, as this requires a partially detailed understanding of the process is.

One Diagnosis entry is with a comprehensible functional description the vehicle easier. With increasing expert knowledge (users, Customer, workshop, development) this description can become more and more detailed become. After a limitation to a few functions, under note the functional dependencies among themselves and their distribution on the ECU hardware, become the responsible Considered components. For a function-oriented monitoring technical systems is a structured and modular approach required in the detection and evaluation of errors (diagnostics). The diagnostic task itself is basically in Error detection, fault localization and fault identification subdivided.

The most important task of a diagnostic algorithm or diagnostic program is the detection of the abnormal state or the malfunction of a system. If an error has occurred, it must be evaluated. For this purpose, it is necessary to evaluate various measured values, for example electrical voltages, currents, rotational speed values or state variables, and important communication signals from the system. at On-board diagnostic systems, this is done immediately in real time. This depends on the system state, the functions, priority distributions and the like. After the occurrence of an error, a so-called debounce counter is first started. If the error does not disappear before the debounce time has elapsed, the entry is made in the error memory and, if necessary, the control lamp is switched on.

One Circumstance, which causes considerable problems especially in the workshop that results are sporadically occurring errors, that is the error is no longer at the time of the workshop visit reproducible and can not be so in many cases be found reliably. System immanent are the most Errors reported from function-oriented diagnostics in the workshop no longer adjustable, as they are on certain scenarios are based and by special external influences were caused. Therefore, here must go further than usual be taken to ensure that no misdiagnosis take place.

Under Error event is a deviation of at least one Feature of a viewing component; the system functionality can while being unimpaired from the outside and still cause a partial failure. Error detection describes this Detecting Abnormal States in Components and the recognition of the misconduct in functions. Errors are detected here, localized and their influence on the system and functions suppressed or limited. Under fault diagnosis respectively Diagnosis will analyze and evaluate all of a fault detection understood errors. The result is a statement about Error type, error location and cause of error. Furthermore, the diagnosis describes a process based on observed symptoms as well as additional Information about the system to be diagnosed at least provides the state of the system and the underlying cause. The function itself describes one or more tasks (user functions), which are executed by the system. The term scenario is a name for an operation or mode a function.

A Function can again consist of several scenarios. diagnosis Relevant are the one scenario triggering and the successful one Graduation identifying sizes.

A Software component is a closed, binary software component, the one application-oriented, semantically related Has functionality that interfaces to the outside is made available. Under function-oriented Process monitoring is the monitoring and diagnostic control of the correct operation. The System vehicle as well as the individual control devices are can be described as a network of various functions and sub-functions.

OBD systems (On-Board Diagnostics Systems) were established in 1988 by the American Authority for keeping the air clean "(California Air Resources Board = CARB) in the US. basis was the consideration that it is not enough in the approval to comply with the emission regulations, but that compliance over the lifetime should be ensured. The OBD-I standard looks among other things, that the vehicle has its own electronic Self-monitoring systems. While of the driving operation, all exhaust gas-influencing systems are monitored, In addition, various other important data, the built-in Software of various control units accessible are. These have exhaust-related errors, about a signal lamp integrated in the fittings - the so-called MIL (Malfunction Indicator Light) - show. Furthermore must have errors in one, with on-board means (for example Blinkcode) readable, memory can be stored. Becoming errors the driver via a warning light and displayed in the respective Control unit permanently stored. The results can be over a standardized plug, via a serial interface with standardized protocol (see for example K-line) or over the CAN bus, for example, be read by a specialist workshop. Meanwhile, the data can also be through special software applications be read on standard notebooks. About the Diagnostic interface sends the connected workshop or Notebook computer. Commands to one of the controllers that over his address is activated, and then receives Results back.

In addition to OBD in the engine control unit, diagnostics are also used in all other control units in various forms. However, in the current approach to error detection and diagnosis, a component-oriented approach is mainly used. This means that errors are only considered locally on individual components and also the actual error handling (diagnosis) can only be done locally. The vehicle with its high functional networking and the interdependencies of the components with each other can therefore be difficult to detect as a complete system. It is quite possible that an error entry in one component does not indicate the cause because the malfunction was caused by a defect in another control device involved in the function. Diagnostics in embedded systems must go beyond detecting line breaks or short circuits. In to Future software systems in motor vehicles must serve to master the increasing complexity of electronic systems.

was standing The technique in systems with controlled dampers is the Use of body acceleration sensors and relative displacement sensors. alternative In addition, body and wheel acceleration sensors are used in other systems used.

One Acceleration sensor is a sensor (sensor) that the Acceleration measures by acting on a test mass inertial force is determined. Thus it can be determined, for example, whether a Speed increase or decrease takes place. In the last Miniaturized acceleration sensors have become increasingly important for years. These are micro-electro-mechanical systems and are made of silicon produced. These sensors are spring-mass systems in which the "springs" only a few microns wide silicon bridges are and also the mass is made of silicon. By the Deflection during acceleration can be suspended between the suspension Part and a fixed reference electrode a change of electrical capacity to be measured. This kind of acceleration sensors has the advantage of relatively low unit costs (mass production) and high reliability (some such sensors can even accelerations up to a thousand times the measuring range without Survive damage). Due to the small size They are also characterized by their high measuring speed. you will be Therefore, for example, to trigger airbags in vehicles used.

in the Electronic chassis control systems become common capacitive measuring vertical acceleration sensors used. These usually have a measuring range of one to several g and are usually earth acceleration compensated. State of Technology is electrical diagnostics for the most diverse Lines shorted to ground, short to battery, Cable breakage, implausible tension and the like.

In The technique is called drifting a relative slow change of a value or a property of a System or device. For example, there is the frequency drift (frequency warping) and the drift of the output voltage. The drift can be in one direction go, but also lead back to the original state, it can be cyclical, it can be influenced by ambient conditions (temperature, Humidity) or depend on the aging of the component. The Drift is usually very undesirable. Especially to take into account is drift during calibration (for example when determining a zero point) of devices. unwanted Drift shifts this point. The effect becomes even bigger the closer to zero is measured (for example, at large Enlargements or reinforcements). One speaks in this context also of zero point drift. A drift can by the standard diagnoses mentioned above, for example of the permissible voltage range, can not be detected.

in the The following is not to be considered the drift due to slow / quasi-stationary movements in the measuring direction, as for example vertically measuring acceleration sensors on mountain rides, (hill) hills, larger ones Have waves and the like.

in the Prior art, many methods exist that deal with the compensation to deal with zero deviations. These are found all use in the calibration of sensors or for calibration purposes in certain operating conditions. Such a condition can for example, the level of a stationary vehicle on a level Be a surface. A calibration while driving at Any operating conditions is with these calculations not possible. Just cause temperature influences however, often to drift effects. If now a sensor in a sensor cluster, for example due to component tolerances, has a very high or too high temperature influence, so this is not detectable in the prior art.

As a general rule be installed in the vehicle acceleration sensors to Verbau never calibrated again. Thus, for example, aging effects also have an effect or the like directly as disorders and are neither compensable nor detectable in the prior art.

In the prior art nowadays can not be determined by electrical diagnostics in acceleration sensors, a signal short circuit against the so-called terminal 30 , The signal value then usually remains constant at the last value, ie at any values in the working range of the sensor. When the sensor is excited, there is no change in the signal value. In the prior art, this case is usually not diagnosed or detected. However, this means that this sensor is effectively no longer to use for a control.

Assuming now that the acceleration signal values are offset-compensated, this leads to the fact that no body movement is detected more and so, for example, no force is requested for a connected damper control. That means in the worst case, the dampers are on soft, even if the vehicle moves, resulting in a limitation of Driving safety can lead.

Farther Rotary angle sensors are often used to calculate the distance. These usually work with non-contact internal Hall sensors and an angle measurement with, for example, three segments a 120 °. Internal sensor signal processing becomes common a risc controller is used, as signal output is either a digital PWM signal (at 200 Hz, 800 Hz or the like) or but an analog signal is used. This will follow in the digital case converted into an analog signal and then over a rotational-angle-path characteristic or a PWM-path characteristic converted into Relativwegwerte.

was standing The technology is electrical diagnostics, including the sensors for the most diverse lines, with short circuit to ground, short circuit to Battery, cable break, implausible voltage and the like. In order to but are all cases where a sensor while electric works error-free but outputs a nonsensical value undetectable. For example, hardware errors such as broken, bent levers, faulty sensor mounting direction or sensor alignment, wrong bodyshell connections or also internal sensor errors like Offset or wrong gain.

Just in the ever stronger networking of electrical systems among each other and the ever increasing use electromechanical systems, this approach is problematic. Furthermore, it can lead to being non sensory Errors are issued more erroneously, for example because of faulty sensor signals an error image in another diagnosis results. Furthermore, especially in the multiple use of the sensors important in systems that they output functionally correct values. Redundant sensors account for cost reasons more frequently.

Farther not common today is a diagnosis of actuators, such as the damper, to a correct output / Stellbereich. Again, it is precisely with regulated dampers due to their strongly different adjustment range makes sense, a diagnostic functionality integrate.

Of the Invention is therefore based on the object, a method and a Specify system of the generic type, means in a simple and secure way to regulate the movement a vehicle body with electronically controllable actuators (Dampers) is possible.

According to the invention This object is achieved by a method having the features mentioned in claim 1 solved. Because of the course and / or the size the sensor signal at least one of the movement of the vehicle body detecting sensors with sensor signals of at least one other Sensor is compared and depending on this comparison to a plausibility and / or an error in the is closed at least one sensor supplied sensor signal is advantageously possible, a function-oriented process monitoring in the damper control system of the vehicle. Any errors can be detected step by step and depending on the state of the damper control be taken into account.

The System "vehicle" is functionally oriented according to the invention considered, the process of diagnosis is modularized and the process individual functions or states monitored.

These Methodology of function-oriented process monitoring opened several decisive advantages. Errors are not only based on the hardware, but specifically about the behavior of the function (scenarios, States). In the event of an error, it is immediately clear Statement about the affected function possible. It can additionally an exact assignment of the responsible Hardware to the functions done because in the function-oriented Diagnostic knowledge also exists the function component assignment is. If required, additional diagnostic principles may also be provided be started for detailed investigations.

The following Targets can be at the invention functional diagnosis defined and considered accordingly or implemented. It can be a solution implemented which does not require any hardware adjustments or changes. The drift of a sensor in a sensor network can be detected. Under drift here are all slow changes of the or the sensor values are understood. The only exception form quasi-stationary deviations due to a slow Movement in measuring direction. These act on sensors with the same measuring direction to the same extent and by suitable filter combinations considered in more detail below become.

The sensor with the highest deviation within the sensor network can be detected, with only sensors with the same or a similar measurement principle and / or measurement direction being compared with one another, for example vertically measuring acceleration sensors. A 100% error hit ratio can be realized, whereby a cause of error can be clearly assigned. The detection is independent of suggestions or driving conditions or special boundary conditions, such as vehicle position on a straight line or the like. Possible misdiagnosis, for example, by special operating conditions, such as uphill, towing and the like, or by external influences, such as natural frequencies of holders can be safely excluded. The required runtime and memory requirements are low and the diagnosis is simple and robust. The underlying error pattern can be described as follows. With or without excitation of the sensor, for example due to vehicle movements, the stationary portion of the sensor value has a value deviating from the defined stationary value, for example "zero".

suggestions like hill climb, hill climb or long-wave road profiles can also lead to this error depending on the sensor used. Although acceleration sensors can often be stationary Shares, such as the gravitational force, compensate, quasi-stationary Deviations become quasi-stationary due to the measuring principle Shares that deviate from zero.

at Uses of multiple sensors arranged on a body are and have the same direction of measurement, these quasi-stationary affect Shares on all sensors the same. In the application of a damper control These are quasi-stationary shares on the construction acceleration signals undesirable because the actuators used, that is Damper, can only apply dynamic forces and not quasi-stationary. Consequently, therefore, should the control signals also contain no stationary components, because they only affect you as a disruption. Become accordingly mostly filter structures used, these signal components from the Outline the signal. Therefore, only quasi-stationary ones should be diagnosed Deviations that occur in a sensor compared to the other sensors of the sensor cluster, as this otherwise for example during further processing of these sensor values too disturbed Can lead to values and accordingly as a fault can affect the entire control process.

The inventive solution is thus based on the principle of not diagnosing a single sensor itself but instead a diagnosis of a sensor in a sensor network perform. The diagnostic concept according to the invention is preferably based on the following approach. There is a sensor cluster which includes at least three sensors that are comparable to each other Include signal values, such as the three or four acceleration sensors. Based on a determination of the single quasi-stationary (sensor) signal values is over a suitable method is a "cluster" average all sensors to be considered formed. Subsequently the individual sensor values are compared with the total value. If one goes beyond the defined permissible level Deviation in the positive and / or negative direction occurs so is the sensor with the largest deviation than to look at incorrectly.

Essential Affecting the diagnosis is the method for determining the Cluster mean. Here both different calculations are conceivable as well as a combination of different calculation methods. in the In the simplest case, a mean value image can be used. Prefers is provided that individual signal values before the averaging weighted, for example, differences in signal amplitudes to take into account, for example, due to different Sensor areas, sensor resolutions, installation locations, directions of movement the body to which the sensors are attached and the like.

Prefers is also a weighting of the individual sensor values, for example in the form of a mathematical function such as quadrature or the like, to correspond in this way larger deviations different, for example stronger, to be able to weight. Squaring is often not recommended for the reason because values smaller than 1 are smaller and larger 1 enlarge. This could lead to misdiagnosis to lead. Furthermore, a possible sign difference to consider the individual signals. Here is in the Framework of the inventive solution of proposed new approach, averages of the signals themselves and absolute values to use the means for forming the sum mean value, whereby these individual results to each other or to each other to combine. Furthermore, it is preferred for the same deviations from an average, the signal with the highest or lowest absolute mean value.

The Aufzählung represents only a small part of the conceivable calculations, with the inventive Procedures are possible.

at The use of three sensors or more is more preferred Embodiment of the invention possible, an exclusion method of one or more sensors to be included in the calculation, however, summing up to at least two signal values based. So it is for example also possible one each Signal mean value with the sum of the two other signal average values too compare and so on.

A further advantage of the drift diagnosis method according to the invention is that stationary deviations can be detected in addition to quasi-stationary drift phenomena. If, for example, a sensor remains at a value not equal to the defined zero value due to a short circuit, then so the signal value drifts until the new stationary value is reached.

The Method is in a further preferred embodiment of the invention also usable, the detected drift deviation of a To eliminate sensors from the sensor cluster. In this regard, is the calculation to extend a correction step in which the signal value to be corrected by the difference between sum and Single value is modified. This is especially useful for continuous, very slow deviations, because here phase distortions not lead to significant negative effects.

The inventive functional diagnosis is further based in a preferred embodiment of the invention on the consideration that in case of a short circuit of the signal value against terminal 30 the signal value does not give any change even when the sensor is excited along the measuring direction. Thus, a sensor can be defined as "standing" if and only if there is no change in the signal output upon excitation of the body on which it is mounted. This results in the following task of determining the movement of a body. This can be done, for example, by looking at one or more other sensors that are also attached to that body and provide a signal value in the same measurement direction. Thus, the acceleration sensors attached to the structure can each be used for plausibility. If one of them shows an acceleration, at least one other sensor must also indicate an acceleration. The same applies to the consideration of arranged on a body displacement sensors, for example, path difference between the structure and the wheel.

It can be a "standing" sensor in a sensor network be detected. Under "standing" is hereby understood a constant output signal at the present input excitation, where only the "standing" signal of a Sensor is detected within the sensor network.

The underlying error image can be described as follows. For a "standing" sensor leads a any excitation of the sensor (along the measuring direction) to no changes in the Sensor output. It should be noted that one too little movement of the vehicle (for example also the state of the vehicle) also shows this output signal. It is also possible that, depending on the form of excitation of the vehicle, individual ones attached to it Sensors also output no output signal. This regular Operating states must be evaluated correctly are not allowed to lead to a faulty entry.

outgoing from a determination of the individual (sensor) signal values is over a suitable method is a "cluster" average all sensors to be considered formed. Well done a comparison of the movement of the individual sensor values with the movement of the total value. If the individual sensor or signal value too low a height compared to the overall movement has, the sensor is detected as standing. In the simplest case The movement of the sensor converts a sum of the individual signal values a period x, where both negative and positive parts are to be evaluated or alternatively in the form of an absolute value all deviations are added.

Instead of a sum (the Abolutwerte) are also any other conceivable mathematical methods, such as quadrature and the same. Also conceivable is a combination that the Signal value below both an absolute value and the sum value got to. The method is thus also able to diagnose sensors, which have a reduced output level.

In a further preferred embodiment of the invention is provided that over the sum value too far exceeding signal level as is detected incorrectly. This error image arises for example in a non-fixed sensor. Here, however, is appropriate to consider that, for example, natural frequencies of the sensor, of the holder or body (to which the sensor is attached is) do not cause erroneous detection. Likewise is on it to pay attention that (quasi) stationary deviations to none lead to a faulty picture. The presented method is based on the assumption that only mean-free signals are considered accordingly become. That is usually one is first To do a mean value adjustment. It is also important to that the calculations are only done if all Signals are averaging and that further a possible mean deviation has subsided so far that no negative effects result.

Significantly influencing the diagnosis is the method for determining the cluster value. Here are both different calculations conceivable as well as a combination of different calculation methods. In the simplest case, a mean value image can be used. It is preferably provided that individual signal values are weighted before the averaging so as to take into account, for example, differences in the signal amplitudes, for example due to different sensor areas, sensor resolutions, mounting locations, directions of movement of the body on which the sensors are mounted and the like. Corresponding is also a weighting of the individual sensor values, for example in the form of a mathematical function such as quadrature or the like imaginable in order to be able to weight larger deviations correspondingly differently (for example stronger) in this way.

at the use of three or more sensors it is also possible an exclusion method of one or more sensors with in to include the calculation, but with a summation up based on at least two signal values. So it is, for example possible in each case a signal mean value with the sum of to compare two other signal mean values.

Further is provided in a preferred embodiment of the invention, the the body structure and wheel mounted sensor elements between them to make the signal values plausible. So includes the signal value for the relative / damper path at one corner also information about the construction and / or Rad acceleration at this corner and vice versa. In the simplest case this may look like if a sensor indicates movement, so should these are also present in a certain form in the other sensor. If there is too much discrepancy then this is either the case that a sensor erroneously signal movement or a sensor erroneously outputs no signal movement. The simplest way to evaluate this is for attached to a construction point sensor pairs, such as the body accelerations and relative paths at a single Building corner.

In Another preferred embodiment of the invention is provided, the functional diagnosis with a classification in (operating) states but with a model approach or other sources of information to combine. In the former case states are evaluated and using known state information to detect which one Error is exactly present. For example, in stationary Vehicle condition no movement of the sensors expected. When starting up At least a minimal pitching motion is expected, similar applies to the braking process.

In the second case, when using a model approach, one uses physical model information to determine expected sensor states. The basis can be, for example, 1/4 vehicle models or single track models and the like. A very simple example case looks like this. One goes with a ¼ vehicle model m × aA = -d × vD-c × zD with body mass m, body acceleration aA, damper constant d, damper speed vD, spring constant c and spring travel zD off. That means there is a minimal movement with the body acceleration MW (SB (aA))> fak × c / m × MW (SB (zD)) where MW (SB (x)) represents the mean value of the offset-free signal motion and fak is a factor for the lower limit of the motion.

In front The determination of the signal movement is first an offset correction performed so as to cause interference avoid. The signal movement can be through the most diverse (mathematical) methods are shown, such as as absolute value, quadrature and the like. The important thing is that positive and negative signal components considered accordingly become. In principle, the consideration of the signal movement is sufficient. However, since most signals have noise and / or noise it is recommended to average the signal movement, to reduce the impact of these inaccuracies.

at the use of such approaches are possible sources of interference consider. For example, there is a large proportion To interference movements by the Haltereigenfrequen, so can these are explicitly hidden via filter structures. Furthermore, physical information can be considered become. The models are eigenfrequencies, for example of construction and Rad, under. Accordingly filter structures can be used, the only construction or only wheel or only body and wheel parts accordingly Weighting, allowing a subsequent signal movement as well contains only the defined proportions.

Next In this very simple example, further preferred Embodiments of the invention provide for defining bands, within which signal quantities have to move.

Further is preferred based on the sensor signals and with the knowledge of Command value the correct functionality of an actor. For example, the attenuation of the Signal movement of the structure can be used to detect to what extent damper forces are made real. Furthermore, it is also conceivable here about models bands to specify for movements based on the manipulated variable maximum may result. Accordingly, so Sensors can also be used to diagnose actuators.

It can be detected a correct function of a sensor in a sensor network, the sensor network consists of at least two sensors with different measurement principle, such as an acceleration sensor and egg a displacement sensor. The source of error can be limited by the additional use of (physical) information, such as model equations, natural frequencies, or (operating) states with defined motion pictures.

The Task is further by a system for influencing the movement one in his movements controllable or controllable Vehicle body of a motor vehicle with the mentioned in claim 24 Characteristics solved. Because of the damper exciter and / or a control module comprises modules, by means of which the circulation and / or the size of the sensor signal at least one of the movement of the vehicle body detecting sensors compared with sensor signals of at least one other sensor and depending on this comparison on a plausibility and / or an error of the one provided in the at least one sensor Sensor signal is shot is advantageous possible modular build the damper controller and in the vehicle existing systems, for example in a control unit, to integrate in a simple manner, in particular faulty sensor signals easy and safe to recognize and appropriate consideration could find in the damper control.

Further preferred embodiments will be apparent from the others, in the subclaims mentioned features.

The Invention will be described below in embodiments the accompanying drawings explained. Show it:

1 schematically a motor vehicle with a damper control;

2 a schematic diagram of a motor vehicle with vertical corner construction speeds;

3 a schematic diagram of a motor vehicle with vertical modal body speeds;

4 a schematic diagram of a motor vehicle with arranged in the damper system sensors and the resulting wheel, body and damper speeds;

5 a coarse structure of the functional modules of a damper control; and

6 to 8th Various flowcharts for the calculation of faulty sensor signals.

1 shows schematically in plan view a total with 10 designated motor vehicle. Structure and function of motor vehicles are well known, so that will not be discussed in the context of the present description.

The car 10 has four wheels 12 . 14 . 16 and 18 , The wheels 12 . 14 . 16 and 18 are about a known suspension on a body 20 of the motor vehicle 10 attached. Under construction 20 In the context of the invention, the vehicle body is generally understood to mean the passenger compartment. Between the wheels 12 . 14 . 16 and 18 on the one hand and the construction 20 is a damper in each case 22 . 24 . 26 respectively 28 arranged. The dampers 22 . 24 . 26 and 28 are arranged parallel to springs, not shown. The dampers 22 . 24 . 26 and 28 For example, are designed as a semi-active damper, that is, by applying a control signal to an actuating means of the damper, the damper force can be varied. The adjusting means is usually designed as an electromagnetic valve, so that the control signal is a control current for the valve.

Each wheel or damper is a displacement sensor 30 . 32 . 34 respectively 36 assigned. The displacement sensors are designed as Relativwegsensoren, that is, these measure a change in the distance of the structure 20 from the respective wheel 12 . 14 . 16 respectively 18 , Typically, so-called rotation angle displacement sensors are used here, whose structure and function are generally known.

The structure 20 further comprises three vertical acceleration sensors arranged at defined points 38 . 40 and 42 , These acceleration sensors 38 . 40 and 42 are stuck to the construction 20 arranged and measured the vertical acceleration of the structure in the area of the wheels 12 . 14 respectively 18 , In the area of the left rear wheel 16 For example, the acceleration from the three other acceleration sensors can be determined by calculation, so that the arrangement of a separate acceleration sensor can be omitted here.

The Arrangement of the sensors is merely exemplary here. It can Other sensor arrangements, such as a vertical body acceleration sensor and two rotation angle sensors or the like are used.

The car 10 further comprises a controller 44 , via signal or control lines with the adjusting means of the damper 22 . 24 . 26 and 28 , the displacement sensors 30 . 32 . 34 and 36 and the acceleration sensors 38 . 40 and 42 connected is. The control unit 44 adopts the damper control to be explained in more detail below. In addition, the control unit 44 Of course, further, not to be considered here functions within the motor vehicle 10 take. The car 10 also includes a switching means 46 For example, a button, a rotary knob or the like, by means of which a vehicle driver a request to the movement of the structure 20 can be chosen. Here, for example, it is possible to choose between the requirement "comfort", the requirement "sport" and the requirement "basis". The choice is either stepwise between the three modes or stepless with appropriate intermediate modes possible.

The switching means 46 is also with the controller 44 connected.

2 shows a schematic diagram of the motor vehicle 10 , here the construction 20 is indicated as a flat surface. At the corners of the construction 20 are each the wheels 12 . 14 . 16 and 18 arranged in a conventional manner via a spring-damper combination. The spring-damper combination consists of the dampers 22 . 24 . 26 and 28 and in each case parallel connected springs 48 . 50 . 52 and 54 , At the corners of the construction 20 are the in 1 shown acceleration sensors 38 . 40 respectively 42 arranged by means of which the vertical speed at the corners of the construction 20 can be determined. These are the speeds vA_vl (front-left speed), vA_vr (front-right speed), vA_hl (rear-left speed), and vA_hr (rear-right speed). The speed can be calculated from the accelerations measured by means of the acceleration sensors by integration.

3 again shows the schematic diagram of the motor vehicle 10 , wherein the same parts as in the preceding figures provided with the same reference numerals and are not explained again. In a focal point 56 are the modal movements of construction 20 clarified. This is a hub on the one hand 58 in the vertical direction (z-direction), a nod 61 that is a rotational movement about a transverse axis lying in the y-axis, and a wobble 63 that is a rotational movement about a longitudinal axis of the motor vehicle lying in the x-axis 10 ,

4 shows a further schematic diagram of the motor vehicle 10 , here, in addition to the illustration in 2 , further signals are shown. In addition, here are the damper speeds vD shown, where vD_vl the damper speed for the damper 22 (front left), vD_vr the damper speed for the damper 24 (front right), vD_hl the damper speed for the damper 26 (rear left) and vD_hr the damper speed for the damper 28 (back right) is. The damper speeds can be differentiated from the signals of the displacement sensors 30 . 32 . 34 respectively 36 ( 1 ) be determined. In 4 Furthermore, the wheel speeds vR are indicated. Here speed vR_vl stands for the wheel 12 (front left), vR_vr for the wheel 14 (front right), vR_hl for the bike 16 (back left) and vR_hr for the bike 18 (back right). The wheel speeds vR can be determined, for example, via wheel acceleration sensors.

There both the body speeds vA, the damper speeds vD and the wheel speeds vR all the same direction vector own (in the z-direction), there is the connection vD = vA - vR. As a result, not all measured variables in the form of measurement signals, but may be off the other measured variables are calculated.

Structure and function of controlled dampers are well known, so that will not be discussed in the context of the present description. Here either semi-active dampers or active dampers are used. It is crucial that the damper force can be adjusted by influencing the damper speed. The damper force acts in parallel with the forces of the springs (cf. 2 to 4 ), so that over this the movement of the construction 20 can be influenced in his movements.

to Influencing the damper speed is due to the dampers an electromagnetic valve or other suitable valve arranged by applying a corresponding control current a flow cross-section for a medium, in particular a hydraulic oil, are influenced.

Based The previous explanations make it clear that it is for an effective control of the movement of the body on the Provision of a control current for the control means the damper arrives, to determine a correct Providing the sensor signals is important.

5 shows a block diagram of a coarse structure of the functional modules for damper control according to the invention. The individual modules are shown encapsulated for reasons of clarity and clarity. The entire structure is advantageously constructed hierarchically over several levels. The function modules are in a damper controller, preferably the controller 44 ( 1 ) integrated. The damper control comprises a signal input module 60 , an auxiliary function module 62 , a regulator module 64 , an evaluation module 66 and a signal output module 68 , In the signal input module 60 become the sensor signals of the displacement sensors 30 . 32 . 34 respectively 36 and the acceleration sensors 38 . 40 and 42 as well as others, via the CAN bus of the motor vehicle available stationary signals are read. The auxiliary function module 62 includes a man-machine interface module 70 , a filter module 72 and a load detection module 74 ,

The controller module 64 includes a road detection module 76 , an end-of-range damping module 78 , a transverse dynamics module 80 , a longitudinal dynamics module 82 and a vertical dynamics module 84 , The evaluation logic module 66 includes a current calculation module 86 , The regulator modules 76 . 78 . 80 . 82 and 84 advantageously generate a current, or a quantity which is proportional to the current. In the current calculation module 86 The current calculation of all controller output variables is used to control variables for the dampers 22 . 24 . 26 respectively 28 instead of. Via the signal output module 68 These control currents are provided to the dampers. Both the signal input module 60 as well as the signal output module 68 Optionally, of course, can also receive or output other signals, depending on the equipment of the relevant motor vehicle.

6 shows an example of a flowchart for calculating an undesirably large or erroneous drift of an acceleration sensor, taking into account operating conditions according to a first embodiment of the invention.

7 shows an example of a flowchart for calculating a standing sensor signal according to another embodiment of the invention.

Finally shows 8th for example, a flowchart for calculating a sensor signal with too small or too large signal movement using an acceleration sensor signal and a displacement sensor signal.

10

motor vehicle

12

wheel

14

wheel

16

wheel

18

wheel

20

construction

22

damper

24

damper

26

damper

28

damper

30

displacement sensor

32

displacement sensor

34

displacement sensor

36

displacement sensor

38

accelerometers

40

accelerometers

42

accelerometers

44

control unit

46

switching means

48

feather

50

feather

52

feather

54

feather

56

main emphasis

58

stroke

60

Signal input module

61

nod

62

Auxiliary function module

63

waver

64

Control module

66

Signal output module

68

Signal output module

70

Man-machine interface module

72

filter module

74

Load recognition module

76

Road detection module

78

Endlagendämpfungsmoduls

80

Lateral dynamics module

82

Longitudinal dynamics module

84

Vertical dynamics module

86

Power calculation module

QUOTES INCLUDE IN THE DESCRIPTION

This list The documents listed by the applicant have been automated generated and is solely for better information recorded by the reader. The list is not part of the German Patent or utility model application. The DPMA takes over no liability for any errors or omissions.

Cited patent literature

• - DE 3918735 A1 [0002]

Claims (25)

Method for generating signals for influencing the movement of a vehicle body of a motor vehicle which can be controlled or regulated in its motion sequences, the movement of the vehicle body being sensed, the sensor signals corresponding to the determined sensor values being fed to a damper exciter and the damper exciter at least one control signal for actuating actuators, in particular semi-active or active dampers, provides, by means of which the movement of the vehicle body can be influenced, characterized in that the course and / or the size of the sensor signal of at least one of the movement of the vehicle body detecting sensor is compared with sensor signals at least one other sensor and in dependence on this comparison, a plausibility and / or an error of the sensor signal supplied by the at least one sensor is concluded. Method according to claim 1, characterized in that that a drift of a sensor is detected. Method according to one of the preceding claims, characterized in that a sensor cluster consisting of at least three sensors attached to the vehicle body used where the drift is determined by comparing the individual quasi-stationary signal values compared to a sum quasi-stationary value of at least three sensors results. Method according to claim 1, characterized in that that a sensor with a too large deviation of the quasi stationary value is detected. Method according to claim 4, characterized in that that for diagnosis a sensor cluster consisting of at least three Sensors, which are attached to the vehicle body, is used, wherein a comparison between the quasi-stationary values of a sensor in comparison to a sum quasi stationary value to be determined of the sensor cluster the measure for calculating the deviation of the represents individual sensor or signal values. Method according to one of the preceding claims, characterized in that at a detected drift of a Sensors the unwanted drift is eliminated. Method according to one of the preceding claims, characterized in that the detection of the drift and / or the Deviation is applied to acceleration sensors. Method according to one of the preceding claims, characterized in that the detection of the at least one Sensor signal during any intended Use of the sensors takes place. Method according to one of the preceding claims, characterized in that the total station value at least two signals is formed, with mathematical calculations, in particular Averaging, averaging the absolute values, quadrature averaging, averaging selected ones Signals or the like can be used. Method according to one of the preceding claims, characterized in that one over a definable positive or negative deviation of the quasi-stationary value deviation exceeding the sum quasistation value Error is output whereby in each case the sensor with the largest positive or negative deviation is classified as defective. Method according to one of the preceding claims, characterized in that a detected error only then as valid error is issued if the detected error is over a predetermined period exists. Method according to one of the preceding claims, characterized in that a once valid error up to a defined deletion process is held. Method according to claim 1, characterized in that that a "standing" sensor or a Sensor is detected with too low a signal level. Method according to claim 13, characterized in that that for calculation / diagnosis a sensor cluster consisting of at least two sensors attached to a body are used is, wherein a "standing" signal value from the Comparison of the individual mean-free signal movements via a predetermined period of time compared to a mean-free (Sum) signal movement of at least one other sensor results. Method according to claim 1, characterized in that that a loose sensor and / or sensor with a too large Signal level is detected. A method according to claim 15, characterized in that for calculation / diagnosis, a sensor cluster consisting of at least two sensors, which are attached to a body, are used, which is too large a signal value Comparison of the individual mean-value signal movements over a period of time compared to a mean-free (sum) signal movement of at least one other sensor results. Method according to one of the preceding claims, characterized in that the signal movement is from a mathematical Evaluation of the waveform over a period of time, in particular by summation of the absolute value, quadrature and the like, where, prior to this calculation, an averaging of the Signals takes place, so that a possible signal offset no Has influence on the calculation of the signal movement. Method according to one of the preceding claims, characterized in that the detection is based on acceleration and / or displacement sensors is applied. Method according to one of the preceding claims, characterized in that a sum signal movement at least is formed of two signals and that mathematical calculations, in particular averaging, averaging of the absolute values, Averaging with averaging, averaging of selected ones Signals and the like can be used. Method according to one of the preceding claims, characterized in that via a definable positive or negative deviation of the individual movement from the (sum) comparison movement exceeding deviation in minimum or maximum direction as a fault is output, where in each case the sensor with the largest Minimum and / or maximum deviation is classified as faulty. Method according to one of the preceding claims, characterized in that for calculation / diagnosis a sensor cluster, consisting of at least two sensors, the different measuring principles be used, which is a faulty signal value from the comparison of the signal movement of the individual sensors with each other results and that further information, in particular operating conditions, mathematical models, physical system knowledge and the like and to narrow down the cause of the error or to Determining the faulty signal movement serve. Method according to claim 21, characterized that it also detects the correct functionality used by actuators. Method according to one of the preceding claims, characterized in that the signal movement is from a mathematical Evaluation of the waveform over a period of time, in particular by summation of the absolute value, quadrature and the like where, prior to this calculation, an averaging of the Signals takes place, so that a possible signal offset no Has influence on the calculation of the signal movement. System for influencing the movement of one in his Movements of controllable or controllable vehicle body a motor vehicle, with sensors that control the movement of the vehicle body capture, with controllable or controllable actuators, in particular semi-active or active dampers between the vehicle body and the vehicle wheels are arranged with a damper exciter, by means of which the sensor signals are processed and at least a drive signal is provided for the actuators, characterized in that the damper exciter and / or a control unit comprises modules, by means of which the course and / or the size of the sensor signal at least one of the movement of the vehicle body detecting sensors with sensor signals at least one further sensor is compared and in dependence this comparison to a plausibility and / or a Error of the sensor signal supplied in the at least one sensor is closed. Vehicle, in particular motor vehicle, with a System for influencing the movement of one in his movements controllable or controllable vehicle body according to claim 24.