DE10003739C2 - Method and system for identifying system parameters in vehicles - Google Patents
Method and system for identifying system parameters in vehiclesInfo
- Publication number
- DE10003739C2 DE10003739C2 DE10003739A DE10003739A DE10003739C2 DE 10003739 C2 DE10003739 C2 DE 10003739C2 DE 10003739 A DE10003739 A DE 10003739A DE 10003739 A DE10003739 A DE 10003739A DE 10003739 C2 DE10003739 C2 DE 10003739C2
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- vehicle
- measured values
- determined
- system parameters
- measurement
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Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W10/00—Conjoint control of vehicle sub-units of different type or different function
- B60W10/04—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G17/00—Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load
- B60G17/015—Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load the regulating means comprising electric or electronic elements
- B60G17/018—Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load the regulating means comprising electric or electronic elements characterised by the use of a specific signal treatment or control method
- B60G17/0182—Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load the regulating means comprising electric or electronic elements characterised by the use of a specific signal treatment or control method involving parameter estimation, e.g. observer, Kalman filter
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G17/00—Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load
- B60G17/015—Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load the regulating means comprising electric or electronic elements
- B60G17/0195—Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load the regulating means comprising electric or electronic elements characterised by the regulation being combined with other vehicle control systems
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60K—ARRANGEMENT OR MOUNTING OF PROPULSION UNITS OR OF TRANSMISSIONS IN VEHICLES; ARRANGEMENT OR MOUNTING OF PLURAL DIVERSE PRIME-MOVERS IN VEHICLES; AUXILIARY DRIVES FOR VEHICLES; INSTRUMENTATION OR DASHBOARDS FOR VEHICLES; ARRANGEMENTS IN CONNECTION WITH COOLING, AIR INTAKE, GAS EXHAUST OR FUEL SUPPLY OF PROPULSION UNITS IN VEHICLES
- B60K28/00—Safety devices for propulsion-unit control, specially adapted for, or arranged in, vehicles, e.g. preventing fuel supply or ignition in the event of potentially dangerous conditions
- B60K28/10—Safety devices for propulsion-unit control, specially adapted for, or arranged in, vehicles, e.g. preventing fuel supply or ignition in the event of potentially dangerous conditions responsive to conditions relating to the vehicle
- B60K28/16—Safety devices for propulsion-unit control, specially adapted for, or arranged in, vehicles, e.g. preventing fuel supply or ignition in the event of potentially dangerous conditions responsive to conditions relating to the vehicle responsive to, or preventing, skidding of wheels
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60T—VEHICLE BRAKE CONTROL SYSTEMS OR PARTS THEREOF; BRAKE CONTROL SYSTEMS OR PARTS THEREOF, IN GENERAL; ARRANGEMENT OF BRAKING ELEMENTS ON VEHICLES IN GENERAL; PORTABLE DEVICES FOR PREVENTING UNWANTED MOVEMENT OF VEHICLES; VEHICLE MODIFICATIONS TO FACILITATE COOLING OF BRAKES
- B60T8/00—Arrangements for adjusting wheel-braking force to meet varying vehicular or ground-surface conditions, e.g. limiting or varying distribution of braking force
- B60T8/17—Using electrical or electronic regulation means to control braking
- B60T8/172—Determining control parameters used in the regulation, e.g. by calculations involving measured or detected parameters
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G2400/00—Indexing codes relating to detected, measured or calculated conditions or factors
- B60G2400/05—Attitude
- B60G2400/052—Angular rate
- B60G2400/0521—Roll rate
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G2400/00—Indexing codes relating to detected, measured or calculated conditions or factors
- B60G2400/05—Attitude
- B60G2400/052—Angular rate
- B60G2400/0523—Yaw rate
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G2400/00—Indexing codes relating to detected, measured or calculated conditions or factors
- B60G2400/10—Acceleration; Deceleration
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G2400/00—Indexing codes relating to detected, measured or calculated conditions or factors
- B60G2400/10—Acceleration; Deceleration
- B60G2400/104—Acceleration; Deceleration lateral or transversal with regard to vehicle
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G2400/00—Indexing codes relating to detected, measured or calculated conditions or factors
- B60G2400/10—Acceleration; Deceleration
- B60G2400/106—Acceleration; Deceleration longitudinal with regard to vehicle, e.g. braking
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G2400/00—Indexing codes relating to detected, measured or calculated conditions or factors
- B60G2400/20—Speed
- B60G2400/204—Vehicle speed
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G2400/00—Indexing codes relating to detected, measured or calculated conditions or factors
- B60G2400/40—Steering conditions
- B60G2400/41—Steering angle
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G2600/00—Indexing codes relating to particular elements, systems or processes used on suspension systems or suspension control systems
- B60G2600/18—Automatic control means
- B60G2600/187—Digital Controller Details and Signal Treatment
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G2600/00—Indexing codes relating to particular elements, systems or processes used on suspension systems or suspension control systems
- B60G2600/18—Automatic control means
- B60G2600/187—Digital Controller Details and Signal Treatment
- B60G2600/1871—Optimal control; Kalman Filters
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G2600/00—Indexing codes relating to particular elements, systems or processes used on suspension systems or suspension control systems
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- B60G2600/187—Digital Controller Details and Signal Treatment
- B60G2600/1873—Model Following
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G2800/00—Indexing codes relating to the type of movement or to the condition of the vehicle and to the end result to be achieved by the control action
- B60G2800/70—Estimating or calculating vehicle parameters or state variables
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G2800/00—Indexing codes relating to the type of movement or to the condition of the vehicle and to the end result to be achieved by the control action
- B60G2800/90—System Controller type
- B60G2800/91—Suspension Control
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G2800/00—Indexing codes relating to the type of movement or to the condition of the vehicle and to the end result to be achieved by the control action
- B60G2800/90—System Controller type
- B60G2800/92—ABS - Brake Control
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G2800/00—Indexing codes relating to the type of movement or to the condition of the vehicle and to the end result to be achieved by the control action
- B60G2800/90—System Controller type
- B60G2800/95—Automatic Traction or Slip Control [ATC]
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G2800/00—Indexing codes relating to the type of movement or to the condition of the vehicle and to the end result to be achieved by the control action
- B60G2800/90—System Controller type
- B60G2800/96—ASC - Assisted or power Steering control
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G2800/00—Indexing codes relating to the type of movement or to the condition of the vehicle and to the end result to be achieved by the control action
- B60G2800/90—System Controller type
- B60G2800/97—Engine Management System [EMS]
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W2050/0001—Details of the control system
- B60W2050/0019—Control system elements or transfer functions
- B60W2050/0028—Mathematical models, e.g. for simulation
- B60W2050/0031—Mathematical model of the vehicle
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/10—Longitudinal speed
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/12—Lateral speed
- B60W2520/125—Lateral acceleration
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/14—Yaw
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2540/00—Input parameters relating to occupants
- B60W2540/18—Steering angle
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
- F16H—GEARING
- F16H59/00—Control inputs to control units of change-speed-, or reversing-gearings for conveying rotary motion
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Description
Die Erfindung betrifft ein Verfahren und ein System zur Identi fikation von Systemparametern in Fahrzeugen nach dem Oberbeg riff des Anspruches 1 bzw. 10.The invention relates to a method and a system for identi System parameters in vehicles after the upper beg Reef of claim 1 and 10 respectively.
Zur Beurteilung des Fahrverhaltens von Fahrzeugen werden übli cherweise im Fahrbetrieb oder auf einem Prüfstand Zustandsgrö ßen des Fahrzeugs gemessen und aus den gewonnenen Messgrößen Kennwerte ermittelt, über die das Fahrverhalten des Fahrzeugs charakterisierbar ist, beispielsweise der Eigenlenkgradient, der Schwimmwinkelgradient oder der Wankwinkelgradient. Anhand dieser Kenngrößen kann das Fahrverhalten des Fahrzeuges im Zeitbereich oder Frequenzbereich beurteilt werden. Um die ge wünschten Kenngrößen gewinnen zu können, muss zunächst ein ma thematisches Fahrzeug-Ersatzmodell formuliert werden, mit des sen Bewegungsgleichungen das Fahrverhalten des Fahrzeugs nähe rungsweise zu beschreiben ist. Das Fahrzeug-Ersatzmodell ist üblicherweise in der Weise aufgebaut, dass zumindest die Quer dynamik des Fahrzeuges - Querbeschleunigung und Gierbeschleuni gung - zu erfassen sind. Unter Berücksichtigung der Messgrößen und der Bewegungsgleichungen des Fahrzeug-Ersatzmodells können die gesuchten Kenngrößen aus den Parametern des Ersatzmodelles bestimmt werden.To assess the driving behavior of vehicles, übli Usually in driving mode or on a test bench measured from the vehicle and from the measurements obtained Characteristic values determined by means of the driving behavior of the vehicle can be characterized, for example the self-steering gradient, the slip angle gradient or the roll angle gradient. Based these parameters can determine the driving behavior of the vehicle Time range or frequency range can be assessed. To the ge To be able to gain the desired parameters, a ma thematic vehicle replacement model can be formulated with the equations of motion approximate the driving behavior of the vehicle is to be described approximately. The vehicle replacement model is usually constructed in such a way that at least the cross vehicle dynamics - lateral acceleration and yaw acceleration supply - are to be recorded. Taking into account the measurands and the equations of motion of the vehicle replacement model the parameters sought from the parameters of the replacement model be determined.
Die interessierenden Kenngrößen müssen mit hinreichender Genau igkeit bestimmt werden, damit eine verlässliche Aussage über das Fahrverhalten des Fahrzeuges anhand dieser Kenngrößen mög lich ist. Um die Kenngrößen mit der erforderlichen Güte bestimmen zu können, muss bei den bisher üblichen Identifikationsmo dellen zur Bestimmung von Systemparametern während der Mess fahrt ein breites Spektrum von Fahrmanövern und von unter schiedlichen. Straßenanregungen abgedeckt werden, um sicherzu stellen, dass dem Identifikationsmodell die für die Parameter identifikation erforderlichen Daten zugeführt werden können. Die Vielzahl von Fahrmanövern unter unterschiedlichen Bedingun gen sind zeitintensiv durchzuführen und nicht immer mit hinrei chender Genauigkeit reproduzierbar.The parameters of interest must be accurate enough be determined so that a reliable statement about the driving behavior of the vehicle based on these parameters is. To determine the parameters with the required quality To be able to, with the usual identification mo dents to determine system parameters during the measurement drives a wide range of driving maneuvers and under retired union. Road excitations are covered to ensure safe make that the identification model for the parameters identification required data can be supplied. The variety of driving maneuvers under different conditions conditions are time-consuming and not always necessary reproducible accuracy.
Identifikationsverfahren, die auf einem linearen Einspurmodell eines Fahrzeuges basieren, sind beispielsweise in den Druck schriften DE 42 26 749 A1 und DE 43 25 413 A1 beschrieben wor den.Identification procedure based on a linear single-track model of a vehicle are, for example, in the print Writings DE 42 26 749 A1 and DE 43 25 413 A1 described wor the.
In der DE 199 45 688 A1 wird ein Verfahren und eine Vorrichtung zur Filterung eines Meßsignals beschrieben. Dabei wird angenom men, daß sich das Meßsignal (xk) aus einem Nutzsignal (sk) und einem Rauschsignal (nk) zusammensetzt. In Abhängigkeit des ak tuellen Meßsignals und eines für das aktuelle Nutzsignal vor ausberechneten ersten Schätzwertes (V.k - 1) wird eine dem aktu ellen Meßsignal zugrundeliegende Signaldynamik (ik) ermittelt. Diese Signaldynamik wird zur Ermittlung eines zweiten Schätz wertes (V.k) für das aktuelle Nutzsignal ausgewertet. Ist die vorige Signaldynamik viel größer als die aktuelle Signaldynamik - dabei beziehen sich vorige und aktuelle Signaldynamik auf diskrete Zeitschritte - dann wird die aktuelle Signaldynamik mittels eines Wichtungsfaktors (Gk) vernachlässigt. Ist dagegen die vorige Signaldynamik viel kleiner als die aktuelle, dann wird die aktuelle Signaldynamik mittels eines Wichtungsfaktors berücksichtigt. Die Filterung ist dergestalt realisiert, daß für das im Meßsignal enthaltene Nutzsignal sk ein Schätzwert Vk mit Hilfe eines iterativen Verfahrens ermittelt wird. D. h. der ermittelte Schätzwert ersetzt das im Meßwert enthaltene Nutz signal.DE 199 45 688 A1 describes a method and a device described for filtering a measurement signal. It is assumed men that the measurement signal (xk) from a useful signal (sk) and a noise signal (nk). Depending on the ak current measurement signal and one for the current useful signal calculated first estimate (V.k - 1) will be the current The signal dynamics (ik) on which the measurement signal is based are determined. This signal dynamic is used to determine a second estimate values (V.k) evaluated for the current useful signal. Is the previous signal dynamics much larger than the current signal dynamics - previous and current signal dynamics refer to discrete time steps - then the current signal dynamics neglected by means of a weighting factor (Gk). Is against the previous signal dynamics much smaller than the current one, then the current signal dynamics using a weighting factor considered. The filtering is implemented in such a way that an estimated value Vk for the useful signal sk contained in the measurement signal is determined using an iterative process. I.e. the the estimated value replaced replaces the useful value contained in the measured value signal.
Aus dem Artikel "Modellgestützte Sensorüberwachung eines ESP- Systems" in der atp 41 (1999) Heft 7, Seiten 35 bis 42, ist ein Konzept zur Überwachung von ESP-Sensoren (Elektronisches Stabi litätsprogramm) bekannt. Das Konzept basiert auf einer modell gestützten Residuengenerierung. Diese modellgestützte Sensor überwachung ist in der Lage, die Sensorfehler, insbesondere die Fehler mit großem Gradienten, während der Fahrt zu entdecken.From the article "Model-based sensor monitoring of an ESP Systems "in atp 41 (1999) issue 7, pages 35 to 42, is a Concept for monitoring ESP sensors (electronic stabilization lity program). The concept is based on a model supported residual generation. This model-based sensor monitoring is able to detect the sensor errors, especially the Large gradient errors to discover while driving.
Außerdem wird im Artikel "Identifikation der Wankdynamik eines Kraftfahrzeugs mit Parameterschätzverfahren und Neuronalen Net zen", at - Automatisierungstechnik 46 (1998) 9, Seiten 420 bis 425, eine Identifikation der Wankdynamik mit Hilfe verschiede ner mathematischer Methoden offenbart. Hierzu werden zwei Vor gehensweisen vorgestellt. Zum einen ein physikalisch- mathematisches Modell, dessen unbekannte Parameter auf der Ba sis von Meßergebnissen realer Fahrversuche mittels konventio neller Parameterschätzverfahren bestimmt werden. Bei weniger starken Anregungssignalen wird eine Reduktion des Schätzprob lems herbeigeführt, was zu einer Verminderung der Parameterzahl führt. Zum anderen wird eine Identifikation unter Verwendung dynamischer neuronaler Netze beschrieben.In addition, the article "Identification of the roll dynamics of a Motor vehicle with parameter estimation method and neural net zen ", at - Automatisierungstechnik 46 (1998) 9, pages 420 to 425, an identification of the roll dynamics with the help of various mathematical methods. To do this, two before way presented. First, a physical mathematical model, whose unknown parameters on the Ba sis of measurement results of real driving tests using convention normal parameter estimation method can be determined. With less strong excitation signals becomes a reduction of the estimation sample lems brought about, which leads to a reduction in the number of parameters leads. On the other hand, an identification is used dynamic neural networks.
Der Erfindung liegt das Problem zugrunde, die Identifikation von Systemparametern eines Fahrzeuges zu verbessern bzw. zu Vereinfachen. Es soll insbesondere eine Möglichkeit angegeben werden, den Messaufwand ohne Beeinträchtigung der Qualität der Kenngrößen zu reduzieren.The invention is based on the problem of identification system parameters of a vehicle to improve or Simplify. One possibility in particular is to be given the measuring effort without impairing the quality of the Reduce parameters.
Dieses Problem wird erfindungsgemäß mit den Merkmalen des An spruches 1 bzw. 10 gelöst. This problem is solved according to the invention with the features of the Proverbs 1 and 10 solved.
Gemäß dem neuen Verfahren wird zur Identifikation von Systempa rametern in Fahrzeugen ein Parameterschätzverfahren verwendet, welches zweckmäßig auf der Methode der Covariance-Intersection basiert, welche eine Weiterentwicklung des Kalman-Filters für Schätzungs-, Filterungs- und Datenfusionsapplikationen dar stellt. Die Covariance-Intersection-Methode ist jedoch im Un terschied zum Kalman-Filter in der Lage, eine Parameteridenti fikation auch dann mit hoher Qualität durchzuführen, wenn Schätzwerte des Verfahrens und Fehler- bzw. Rauschanteile kor relieren. Die Covariance-Intersection erlaubt die Fusion von Größen, deren Korrelationsgrad unbekannt ist. According to the new procedure for the identification of system pa parameters in vehicles uses a parameter estimation method, which is expedient on the method of covariance intersection which is a further development of the Kalman filter for Estimation, filtering and data fusion applications provides. However, the covariance intersection method is in the Un Unlike the Kalman filter, it was able to identify a parameter to carry out high-quality fication even if Estimated values of the process and error or noise components cor relieren. The covariance intersection allows the fusion of Quantities whose degree of correlation is unknown.
Erfindungsgemäß ist vorgesehen, dass zur Identifikation der Systemparameter eine iterative Berechnungsvorschrift durchge führt wird, in welcher ein Optimierungsparameter berücksichtigt wird, mit dem die Anteile aus der Schätzung und aus der Messung in Abhängigkeit der Güte der Messwerte unterschiedlich gewich tet werden können. Der Optimierungsparameter wird hierbei über eine Optimierungsfunktion gemäß einem vorgegebenen Funktional bestimmt.According to the invention it is provided that the System parameters an iterative calculation rule in which an optimization parameter is taken into account with which the shares from the estimate and from the measurement weighted differently depending on the quality of the measured values can be tet. The optimization parameter is over an optimization function according to a given functional certainly.
Die Bewegungsgleichungen des Fahrzeug-Ersatzmodells werden ins besondere über die Berechnungsvorschrift der Covariance- Intersection-Methode berücksichtigt. In der Regel reicht ein Einspur-Fahrzeug-Ersatzmodell zur Bestimmung der Querdynamik und der Wankdynamik eines Fahrzeuges für die Ermittlung der Systemparameter aus.The equations of motion of the vehicle replacement model are ins particular about the calculation rule of covariance Intersection method considered. Usually it is enough Single-track vehicle replacement model for determining the lateral dynamics and the roll dynamics of a vehicle for determining the System parameters.
Das auf der Covariance-Intersection-Methode basierende Verfah ren zur Identifikation von Systemparametern bietet den Vorteil, dass über die in jedem Iterationsschritt neu zu treffende Be stimmung des Optimierungsparameters eine der Güte der aktuellen Messwerte entsprechende Gewichtung im Iterationsalgorithmus zwischen Schätzwerten und Messwerten durchgeführt wird. Dadurch funktioniert das Schätzverfahren auch bei einer geringen oder einer fehlenden Anregung ohne Verschlechterung der Ergebnisse für die Systemparameter, da im Falle einer geringen oder feh lenden Anregung der Schätzanteil in der Berechnungsvorschrift für die Parameteridentifikation bedeutend stärker gewichtet wird als der Messanteil. Im umgekehrten Fall, wenn die Messung wesentlich mehr Informationen beinhaltet als die Schätzung, wird dementsprechend der Messanteil stärker gewichtet als der Schätzanteil.The method based on the covariance intersection method for the identification of system parameters offers the advantage that the Be. to be met in each iteration step the optimization parameter is one of the quality of the current one Weighting corresponding to measurement values in the iteration algorithm between estimates and measurements. Thereby does the estimation method work even with a low or a lack of excitation without worsening the results for the system parameters, since in the case of a low or wrong lent suggestion of the estimated proportion in the calculation rule weighted significantly more for parameter identification is called the measurement portion. Conversely, when the measurement contains much more information than the estimate, accordingly, the measurement portion is weighted more than that Estimated share.
Ein weiterer Vorteil der Anwendung des Covariance-Intersection- Verfahrens liegt darin, dass ein Divergieren der Verfahrensergebnisse im Gegensatz zu bisher bekannten Verfahren in der Re gel ausgeschlossen werden kann.Another advantage of using the covariance intersection The process is that the process results diverge in contrast to previously known methods in Re gel can be excluded.
Als Systemparameter werden insbesondere der Eigenlenkgradient, der Schwimmwinkelgradient und der Wankwinkelgradient bestimmt. Die bei der Messfahrt aufzunehmenden Messgrößen sind insbeson dere die Längsgeschwindigkeit des Fahrzeuges, die Querbeschleu nigung, die Giergeschwindigkeit sowie gegebenenfalls die Wank geschwindigkeit, der Lenkgradwinkel und die Quergeschwindig keit. Diese Messgrößen werden zur Bestimmung der Systemparame ter herangezogen.In particular, the self-steering gradient, the slip angle gradient and the roll angle gradient are determined. The measurands to be recorded during the measurement trip are in particular the longitudinal speed of the vehicle, the transverse acceleration inclination, the yaw rate and, if necessary, the roll speed, the steering angle and the cross speed ness. These measurands are used to determine the system parameters ter used.
Die online identifizierten Systemparameter können zur Bewertung des Fahrverhaltens herangezogen werden. Darüber hinaus ist es auch möglich, im Anschluss an die Parameteridentifikation Fahr manöver des Fahrzeug-Ersatzmodells im Zeit- oder Frequenzbe reich zu simulieren, um zu einer weiteren bzw. genaueren Bewer tung des Fahrverhaltens zu gelangen.The system parameters identified online can be used for evaluation of driving behavior can be used. Beyond that it is also possible after the parameter identification Fahr maneuvers of the vehicle replacement model in time or frequency richly simulate in order to make another or more accurate reviewer direction of driving behavior.
Das erfindungsgemäße System zur Durchführung des Verfahrens um fasst eine Messeinrichtung, mit der im Fahrzeug die benötigten Fahrzeug-Zustandsgrößen gemessen bzw. ermittelt werden können, sowie eine Recheneinheit, die ebenfalls im Fahrzeug angeordnet ist und in der die in der Messeinrichtung aufgenommenen Mess größen insbesondere unter Anwendung der Covariance- Intersection-Methode ausgewertet werden. In dieser Ausführung stehen die das Fahrverhalten charakterisierenden Systemparame ter online im Fahrzeug zur Verfügung und können gemäß einer be vorzugten Weiterbildung für die Erzeugung von Steilsignalen he rangezogen werden, über die das Fahrverhalten des Fahrzeuges beeinflusst werden kann. Derartige Stellsignale werden bei spielsweise den Stellgliedern eines aktiven, regelbaren Fahr werks, eines Anti-Blockier-Systems, eines Antriebs-Schlupf- Regelungssystems, einer Motorsteuerung oder einer Getriebesteu erung zugeführt. Man ist damit in der Lage, das Fahrzeug- Fahrverhalten für den Fall positiv manipulieren zu können, dass die das Fahrverhalten charakterisierenden Kenngrößen außerhalb eines definierten Bereichs liegen, wodurch konstruktive Abwei chungen von einem Idealwert ebenso ausgeglichen werden können wie Produktions- oder Montagefehler oder Verschleiß im Fahr zeug.The system according to the invention for performing the method holds a measuring device with which the required ones are in the vehicle Vehicle state variables can be measured or determined, and a computing unit, which is also arranged in the vehicle and in which the measurement recorded in the measuring device sizes in particular using the covariance Intersection method can be evaluated. In this version are the system parameters that characterize the driving behavior are available online in the vehicle and can be used according to a be preferred training for the generation of steep signals he be drawn about the driving behavior of the vehicle can be influenced. Such control signals are used for example the actuators of an active, controllable driving plant, an anti-lock braking system, a drive slip Control system, an engine control or a transmission control supply. This enables you to To be able to positively manipulate driving behavior in the event that the parameters characterizing the driving behavior outside a defined area, which means constructive deviation can also be compensated for by an ideal value such as production or assembly errors or wear and tear while driving convincing.
Weitere Vorteile und zweckmäßige Ausführungsformen sind den weiteren Ansprüchen, der Figurenbeschreibung und der Zeichnung zu entnehmen, die ein Ablaufdiagramm mit den Verfahrensschrit ten zur Messung von Zustandsgrößen, Identifikation von System parametern und Erzeugung von das Fahrverhalten beeinflussenden Steilsignalen zeigt.Further advantages and practical embodiments are the further claims, the description of the figures and the drawing refer to the flow chart with the process step for measuring state variables, identifying systems parameters and generation of driving behavior influencing Shows steep signals.
Das Covariance-Intersection-Verfahren, welches für die Online-
Identifikation von Systemparametern θ in Fahrzeugen herangezo
gen wird, geht aus von einer iterativ durchzuführenden Berech
nungsvorschrift auf der Grundlage der Gleichungen
The covariance intersection method, which is used for the online identification of system parameters θ in vehicles, is based on an iterative calculation rule based on the equations
P-1 k+1 = ωP-1 k + (1 - ω)HT k+1R-1Hk+1
P -1 k + 1 = ωP -1 k + (1 - ω) H T k + 1 R -1 H k + 1
P-1 k+1θk+1 = ωP-1 kθk + (1 - ω)HT k+1R-1yk+1.P -1 k + 1 θ k + 1 = ωP -1 k θ k + (1 - ω) H T k + 1 R -1 y k + 1 .
Hierin bezeichnen "k" den den aktuellen Iterationsschritt an zeigenden Index, "P" eine Kovarianzmatrix, "θ" die zu ermit telnden Systemparameter, "R" eine in der Regel konstante Mo dellvarianzmatrix, "H" eine von Messwerten und den Bewegungs gleichungen des zu Grunde liegenden Fahrzeug-Ersatzmodells ab hängige Jacobimatrix, "ω" einen Optimierungsparameter und "y" Messwerte, wobei "k" und "ω" skalare Größen sind, "y" und "θ" Vektoren bezeichnen und "P", "H" und "R" Matrizen sind.Here, "k" denotes the current iteration step index, "P" a covariance matrix, "θ" to be determined telenden system parameters, "R" a generally constant Mo dell variance matrix, "H" one of measured values and the motion equations of the underlying vehicle replacement model pending Jacobi matrix, "ω" an optimization parameter and "y" Measured values, where "k" and "ω" are scalar quantities, "y" and "θ" Denote vectors and are "P", "H" and "R" matrices.
Das Covariance-Intersection-Verfahren wird online im Fahrzeug
iterativ durchgeführt. Hierfür ist das Fahrzeug mit einer Messeinrichtung
zur Messung von Fahrzeug-Zustandsgrößen und einer
Recheneinheit zur Auswertung der Messergebnisse und gegebenen
falls zur Erzeugung von Steilsignalen, die das Fahrverhalten
beeinflussende Fahrzeugaggregate zuzuführen sind, ausgerüstet.
Die Messung umfasst folgende Fahrzeug-Zustandsgrößen, die in
einem Messvektor z zusammen gefasst sind:
The covariance intersection procedure is carried out iteratively online in the vehicle. For this purpose, the vehicle is equipped with a measuring device for measuring vehicle state variables and an arithmetic unit for evaluating the measurement results and, if appropriate, for generating steep signals which are to be supplied to vehicle assemblies which influence driving behavior. The measurement includes the following vehicle state variables, which are summarized in a measurement vector z:
Zk+1 = [yT k+1, uT k+1]T,
Z k + 1 = [y T k + 1 , u T k + 1 ] T ,
wobei mit "y" die Messwerte der Systemausgänge und mit "u" die
Messwerte der Systemeingänge bezeichnet sind. Die Messwerte y
der Systemausgänge entsprechen den Bewegungsgleichungen h des
mathematischen Fahrzeug-Ersatzmodells nach dem Zusammenhang
where "y" denotes the measured values of the system outputs and "u" denotes the measured values of the system inputs. The measured values y of the system outputs correspond to the equations of motion h of the mathematical vehicle replacement model according to the context
y = h(uk+1, θ).y = h (u k + 1 , θ).
Die Messwerte u der Systemeingänge fließen unmittelbar in die Berechnung der rechten Seite der Bewegungsgleichungen ein.The measured values u of the system inputs flow directly into the Calculate the right side of the equations of motion.
Im Falle eines Einspur-Fahrzeugmodells mit Berücksichtung der
Fahrzeug-Querdynamik und der Fahrzeug-Wankdynamik lautet der
Vektor der Messwerte y der Systemausgänge
In the case of a single-track vehicle model taking into account the vehicle lateral dynamics and the vehicle roll dynamics, the vector of the measured values is y of the system outputs
y = [ay, d2Ψ/dt2, ϕ]T
y = [a y , d 2 Ψ / dt 2 , ϕ] T
mit der Querbeschleunigung ay, der Gierbeschleunigung d2Ψ/dt2
und dem Wankwinkel ϕ. Die Bewegungsgleichungen h werden in der
Recheneinheit gemäß dem hinterlegten Ersatzmodell berechnet;
die Bewegungsgleichungen h hängen von den Systemparametern θ
und den Messwerten u der Systemeingänge ab, wobei im Einspurmo
dell im Messvektor u gemäß
with the lateral acceleration a y , the yaw acceleration d 2 Ψ / dt 2 and the roll angle ϕ. The equations of motion h are calculated in the computing unit according to the stored substitute model; the equations of motion h depend on the system parameters θ and the measured values u of the system inputs, with u in the single-track model in the measurement vector
u = [vx, vy, dΨ/dt, dϕ/dt, δH]T
u = [v x , v y , dΨ / dt, dϕ / dt, δ H ] T
die Fahrzeug-Längsgeschwindigkeit vx, die Fahrzeug- Quergeschwindigkeit vy, die Giergeschwindigkeit dΨ/dt, die Wankgeschwindigkeit dϕ/dt und der Lenkwinkel δH zu berücksich tigen sind.the longitudinal vehicle speed v x , the transverse vehicle speed v y , the yaw rate dΨ / dt, the roll speed dϕ / dt and the steering angle δ H must be taken into account.
Die Kovarianzmatrix P und die Systemparameter θ im Covariance-
Intersection-Algorithmus werden, ausgehend von vorzugebenden
Startwerten P0, θ0, iterativ bestimmt. Die Jacobimatrix H wird
gemäß dem Zusammenhang
The covariance matrix P and the system parameters θ in the covariance intersection algorithm are determined iteratively based on the starting values P 0 , θ 0 that are to be specified. The Jacobian matrix H is according to the context
HT k+1 = dhT(uk+1, θ)/dθ
H T k + 1 = ie T (u k + 1 , θ) / dθ
als Differenzial oder als Differenzenquotient aus den Bewe gungsgleichungen h und den Systemparametern θ bestimmt.as a differential or as a quotient of differences from the be equations h and the system parameters θ are determined.
Der Optimierungsparameter ω, der das Verhältnis von Schätzwer
ten zu Messwerten im Covariance-Intersection-Verfahren be
stimmt, wird zweckmäßig in der Weise festgelegt, dass das Opti
mierungskriterium
The optimization parameter ω, which determines the ratio of estimated values to measured values in the covariance intersection method, is expediently determined in such a way that the optimization criterion
det(Pk+1) = Minimum,
det (P k + 1 ) = minimum,
wonach die Determinante der Kovarianzmatrix P ein Minimum erge ben soll, erfüllt ist. In alternativen Ausführungen kann es a ber auch angezeigt sein, hiervon abweichende Kostenfunktionale für die Bestimmung des Optimierungsparameters ω vorzugeben.according to which the determinant of the covariance matrix P is a minimum should be fulfilled. In alternative versions, a Be also indicated, different cost functions for determining the optimization parameter ω.
Zusammengefasst lässt sich das Covariance-Intersection-
Verfahren unter Berücksichtigung zweckmäßiger Umformungen für
ein Einspur-Fahrzeugmodell mit dem Gleichungssatz
In summary, the covariance intersection method can be calculated using the equation theorem, taking into account appropriate transformations for a single-track vehicle model
θk+1 = θk + Kk+1[yk+1 - h(uk+1, θk)]
θ k + 1 = θ k + K k + 1 [y k + 1 - h (u k + 1 , θ k )]
Kk+1 = (1 - ω)PkHT k+1[Hk+1PkHT k+1 + R]-1
K k + 1 = (1 - ω) P k H T k + 1 [H k + 1 P k H T k + 1 + R] -1
HT k+1 = dhT(uk+1, θ)/dθ
H T k + 1 = ie T (u k + 1 , θ) / dθ
P-1 k+1 = ωP-1 k + (1 - ω)HT k+1R-1Hk+1
P -1 k + 1 = ωP -1 k + (1 - ω) H T k + 1 R -1 H k + 1
ω aus: det(Pk+1) = Minimum
beschreiben.ω off: det (P k + 1 ) = minimum
describe.
Zur Verdeutlichung wird der Algorithmus für die ersten beiden
Iterationsschritte mit k = 0 und k = 1 aufgeführt:
k = 0 (Initialisierungsschritt):
For clarification, the algorithm for the first two iteration steps is listed with k = 0 and k = 1:
k = 0 (initialization step):
θ1 = θ0 + K1[y1 - h(u1, θ0)]
θ 1 = θ 0 + K 1 [y 1 - h (u 1 , θ 0 )]
K1 = (1 - ω)P0HT 1[H1P0HT 1 + R]-1
K 1 = (1 - ω) P 0 H T 1 [H 1 P 0 H T 1 + R] -1
HT 1 = dhT(u1, θ)/dθ
H T 1 = dh T (u 1 , θ) / dθ
P-1 1 = ωP-1 0 + (1 - ω)HT 1R-1H1
P -1 1 = ωP -1 0 + (1 - ω) H T 1 R -1 H 1
ω aus: det(P1) = Minimum,
wobei die Modelvarianzmatrix R konstante Werte aufweist und θ0,
P0 als Startwerte für die Systemparameter bzw. die Kovarianz
matrix vorgegeben werden. Mit "K" ist eine Korrekturmatrix be
zeichnet.
k = 1
ω off: det (P 1 ) = minimum,
where the model variance matrix R has constant values and θ 0 , P 0 are specified as starting values for the system parameters or the covariance matrix. With "K" is a correction matrix.
k = 1
θ2 = θ1 + K2[y2 - h(u2, θ1)]
θ 2 = θ 1 + K 2 [y 2 - h (u 2 , θ 1 )]
K2 = (1 - ω)P1HT 2[H2P1HT 2 + R]-1
K 2 = (1 - ω) P 1 H T 2 [H 2 P 1 H T 2 + R] -1
HT 2 = dhT(u2, θ)/dθ
H T 2 = dh T (u 2 , θ) / dθ
P-1 2 = ωP-1 1 + (1 - ω)HT 2R-1H2
P -1 2 = ωP -1 1 + (1 - ω) H T 2 R -1 H 2
ω aus: det(P2) = Minimum.ω off: det (P 2 ) = minimum.
Das in der Figur dargestellte Ablaufdiagramm verdeutlicht die Funktionsweise der Covariance-Intersection-Methode bzw. die Funktionsweise des in ein Fahrzeug integrierten Systems, in welchem diese Methode zur Online-Identifikation von Fahrzeugpa rametern implementiert ist.The flow chart shown in the figure illustrates the How the covariance intersection method works Functioning of the system integrated in a vehicle, in which this method for online identification of vehicle pa rametern is implemented.
In einem ersten Ablaufschritt 1 wird zu Beginn des Verfahrens zunächst der den Iterationsschritt repräsentierende Index k auf den Wert Null initialisiert. Im nächsten Ablaufschritt 2 werden über die in das Fahrzeug integrierte Messeinrichtung bei beweg tem Fahrzeug Messwerte aufgenommen, insbesondere Zustandsgrößen des Fahrzeugs auf Lage-, Geschwindigkeits- und Beschleunigungs ebene. Es wird der Vektor der Messwerte zk+1 ermittelt, der so wohl Systemausgangs-Messwerte yk+1 als auch Systemeingangs- Messwerte uk+1 umfasst. Im Anschluss an die Messung werden im Ablaufschritt 3 unter Berücksichtigung der Messwerte yk+1 und uk+1 die Bewegungsgleichungen h ermittelt, welche auf dem aktu ell eingesetzten Fahrzeug-Ersatzmodell beruhen. Es wird weiter hin der Optimierungsparameter ω berechnet, insbesondere aus der Bedingung, dass die Determinante der Kovarianzmatrix ein Minimum einnimmt. Gemäß der Covariance-Intersection-Methode werden die Systemparameter θk+1 ermittelt, welche zweckmäßig zu mindest den Eigenlenkgradienten, den Schwimmwinkelgradienten und den Wankwinkelgradienten umfassen.In a first process step 1 , the index k representing the iteration step is initially initialized to the value zero at the beginning of the method. In the next sequence step 2 , measured values are recorded via the measuring device integrated in the vehicle when the vehicle is moving, in particular state variables of the vehicle at the position, speed and acceleration level. The vector of the measured values z k + 1 is determined, which probably includes system output measured values y k + 1 as well as system input measured values u k + 1 . Following the measurement, the equations of motion h, which are based on the currently used vehicle replacement model, are determined in sequence step 3 , taking into account the measured values y k + 1 and u k + 1 . The optimization parameter ω is also calculated, in particular from the condition that the determinant of the covariance matrix takes a minimum. According to the covariance intersection method, the system parameters θ k + 1 are determined, which expediently comprise at least the self-steering gradient, the slip angle gradient and the roll angle gradient.
Im Schritt 4 werden die ermittelten Systemparameter einer Güte abfrage unterzogen. Sofern der Betragwert |θk+1| eines Systempa rameters außerhalb eines zulässigen, vorgegebenen Bereiches θLi mit liegt, wird der "Ja"-Verzweigung entsprechend zum Ablaufschritt 6 fortgefahren und es wird in der Recheneinheit ein Stellsignal SSt erzeugt, um ein Stellglied eines Fahrzeugaggre gates zu manipulieren, mit dem die fahrdynamischen Eigenschaf ten des Fahrzeugs beeinflusst werden können. Hierfür kommen ak tiv regelbare Komponenten des Fahrwerks in Frage, aber auch Komponenten, über die der Zustand der Bremsen, des Motors oder des Getriebes zu beeinflussen ist. Über die Manipulation eines den Fahrzustand beeinflussenden Aggregates können Abweichungen der Systemparameter von einem Idealwert online im Fahrzeug kom pensiert werden.In step 4 , the system parameters determined are subjected to a quality check. If the absolute value | θ k + 1 | a Enhancement rameters outside an acceptable, predetermined range θ Li with is, the "yes" branch is continued according to procedural step 6 and it is generated in the arithmetic unit, a control signal S St to an actuator of a Fahrzeugaggre manipulate gates with which the driving dynamic properties of the vehicle can be influenced. For this, actively controllable components of the chassis come into question, but also components via which the condition of the brakes, the engine or the transmission can be influenced. Manipulating an aggregate influencing the driving condition can compensate for deviations in the system parameters from an ideal value online in the vehicle.
Nach der Erzeugung des Stellsignals SSt wird zum Ablaufschritt 5 fortgefahren, in welchem der Index k um den Wert eins erhöht wird. Anschließend wird das Verfahren von Neuem durchlaufen, beginnend bei Ablaufschritt 2, der Messung der Fahrzeug- Zustandsgrößen.After the control signal S St has been generated, the process proceeds to step 5 , in which the index k is increased by the value one. The method is then run through again, starting with step 2 , the measurement of the vehicle state variables.
Sofern der Betragwert |θk+1| eines Systemparameters in der Ab frage nach Ablaufschritt 4 innerhalb des zulässigen, vorgegebe nen Bereiches θLimit liegt, wird der "Nein"-Verzweigung entspre chend unmittelbar zum Ablaufschritt 5 zur Erhöhung des Index k um den Wert eins verfahren und schließlich zum Anfang des Ver fahrens zum Ablaufschritt 2 zurückgekehrt.If the absolute value | θ k + 1 | a system parameter in the query for sequence step 4 is within the permissible, predetermined range θ limit , the "no" branch is accordingly moved to sequence step 5 to increase the index k by the value one and finally to the beginning of the method returned to step 2 .
Es kann gegebenenfalls zweckmäßig sein, das Verfahren nach dem Ablaufschritt 3, der Messung der Zustandsgrößen und der Ermitt lung der Systemparameter, abzubrechen und die gewonnenen Er kenntnisse über die Systemparameter einer konstruktiven Anpas sung des Fahrzeugs zu Grunde zu legen.It may be expedient to terminate the method after sequence step 3 , the measurement of the state variables and the determination of the system parameters, and to base the knowledge gained on the system parameters on a constructive adaptation of the vehicle.
Claims (16)
dass über einen Optimierungsparameter (ω) das Verhältnis von Schätzwerten und Messwerten in der Berechnungsvorschrift zur Parameteridentifikation gewichtet wird, wobei die Gewichtung in der Weise erfolgt, dass
für den Fall, dass die Messung im aktuellen Messschritt mehr Informationen als die Schätzung enthält, die Messung stärker berücksichtigt wird und
für den Fall, dass die Messung im Verhältnis zur Schätzung keine neuen Informationen liefert, die Schätzung stärker be rücksichtigt wird.1.Procedure for identifying system parameters in vehicles, measured values (y, u) representing vehicle state variables during vehicle operation and evaluated in a computing unit in accordance with a calculation rule for determining the system parameters (θ), the equation of motion being used in the calculation rule (h) a vehicle calculation model and both estimated values and measured values (y, u) are taken into account, characterized in that
that the ratio of estimated values and measured values in the calculation rule for parameter identification is weighted via an optimization parameter (ω), the weighting taking place in such a way that
in the event that the measurement in the current measurement step contains more information than the estimate, the measurement is taken into account more and
in the event that the measurement does not provide any new information in relation to the estimate, the estimate is taken into account more.
f(Pk+1) = Funktional.2. The method according to claim 1, characterized in that the optimization parameter (ω) is determined in such a way that a function of the covariance matrix (P) corresponds to a predetermined functional:
f (P k + 1 ) = functional.
det(Pk+1) = Minimum.3. The method according to claim 2, characterized in that the optimization parameter (ω) is determined in such a way that the determinant of the covariance matrix (P) takes a minimum:
det (P k + 1 ) = minimum.
dass die Berechnungsvorschrift gemäß dem Zusammenhang
P-1 k+1 = ωP-1 k + (1 - ω)HT k+1R-1Hk+1
P-1 k+1θk+1 = ωP-1 kθk + (1 - ω)HT k+1R-1yk+1
iterativ durchgeführt wird, worin
k den den aktuellen Iterationsschritt anzeigenden Index
P eine Kovarianzmatrix
θ die zu ermittelnden Systemparameter
R eine Modellvarianzmatrix
H eine von Messwerten abhängige Jacobimatrix
ω den Optimierungsparameter und
y die Messwerte
bezeichnet und die Jacobimatrix (H) in Abhängigkeit von Mess werten (u) und Bewegungsgleichungen (h) aus dem Differenzial bzw. dem Differenzenquotienten
HT k+1 = dhT(uk+1, θ)/dθ
ermittelt wird, wobei der Optimierungsparameter (ω) mittels der Optimierungsfunktion bestimmt wird. 4. The method according to any one of claims 1 to 3, characterized in
that the calculation rule according to the context
P -1 k + 1 = ωP -1 k + (1 - ω) H T k + 1 R -1 H k + 1
P -1 k + 1 θ k + 1 = ωP -1 k θ k + (1 - ω) H T k + 1 R -1 y k + 1
is carried out iteratively, in which
k the index showing the current iteration step
P is a covariance matrix
θ the system parameters to be determined
R is a model variance matrix
H is a Jacobian matrix dependent on measured values
ω the optimization parameter and
y the measured values
referred to and the Jacobian matrix (H) as a function of measured values (u) and equations of motion (h) from the differential or the difference quotient
H T k + 1 = ie T (u k + 1 , θ) / dθ
is determined, the optimization parameter (ω) being determined by means of the optimization function.
die Längsgeschwindigkeit (vx), die Quergeschwindigkeit (vy),
die Querbeschleunigung (ay), die Giergeschwindigkeit (dΨ/dt),
die Wankgeschwindigkeit (dϕ/dt) und der Lenkradwinkel (δH).7. The method according to any one of claims 1 to 6, characterized in that one or more of the following variables are measured:
the longitudinal speed (v x ), the transverse speed (v y ),
the lateral acceleration (a y ), the yaw rate (dΨ / dt),
the roll speed (dϕ / dt) and the steering wheel angle (δ H ).
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Cited By (3)
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DE102004030782A1 (en) * | 2004-06-25 | 2006-01-19 | Fev Motorentechnik Gmbh | Vehicle control unit with a neural network |
DE102009013291A1 (en) * | 2009-03-14 | 2010-09-16 | Audi Ag | Method for preparing control process for active vehicle component influencing driving dynamics of vehicle, involves simulating defined vehicle maneuver by vehicle-modeling system for vehicle components |
CN102967728A (en) * | 2012-11-19 | 2013-03-13 | 珠海德百祺科技有限公司 | Method and device for detecting automobile motion state by using acceleration sensor |
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DE10318111A1 (en) | 2003-04-22 | 2004-11-11 | Continental Aktiengesellschaft | Method and device for recognizing a driving state |
AT500978B8 (en) * | 2003-05-13 | 2007-02-15 | Avl List Gmbh | METHOD FOR OPTIMIZING VEHICLES |
CN108829121B (en) * | 2018-06-15 | 2021-11-12 | 北京空天技术研究所 | Separation controller based on parameter identification |
DE102021206880A1 (en) | 2021-06-30 | 2023-01-05 | Robert Bosch Gesellschaft mit beschränkter Haftung | Method and device for the optimal parameterization of a driving dynamics control system for vehicles |
AT525592A1 (en) * | 2021-11-09 | 2023-05-15 | Avl List Gmbh | Method for creating a virtual prototype of a vehicle |
CN116577997B (en) * | 2023-07-06 | 2023-10-03 | 西北工业大学 | Omnidirectional trolley parameter identification method based on concurrent learning |
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DE19945688A1 (en) * | 1999-09-23 | 2000-05-18 | Siemens Ag | Method of filtering measurement signal for process measurement applications enables time averaging to be performed with high level of signal smoothing, low useful signal distortion |
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Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE102004030782A1 (en) * | 2004-06-25 | 2006-01-19 | Fev Motorentechnik Gmbh | Vehicle control unit with a neural network |
DE102009013291A1 (en) * | 2009-03-14 | 2010-09-16 | Audi Ag | Method for preparing control process for active vehicle component influencing driving dynamics of vehicle, involves simulating defined vehicle maneuver by vehicle-modeling system for vehicle components |
CN102967728A (en) * | 2012-11-19 | 2013-03-13 | 珠海德百祺科技有限公司 | Method and device for detecting automobile motion state by using acceleration sensor |
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