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WO2008095620A1 - Procédé d'optimisation d'une boîte de vitesses automatique à commande électronique pour une automobile - Google Patents

Procédé d'optimisation d'une boîte de vitesses automatique à commande électronique pour une automobile Download PDF

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Publication number
WO2008095620A1
WO2008095620A1 PCT/EP2008/000620 EP2008000620W WO2008095620A1 WO 2008095620 A1 WO2008095620 A1 WO 2008095620A1 EP 2008000620 W EP2008000620 W EP 2008000620W WO 2008095620 A1 WO2008095620 A1 WO 2008095620A1
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WO
WIPO (PCT)
Prior art keywords
parameters
determined
transmission
control
characteristic parameters
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/EP2008/000620
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German (de)
English (en)
Inventor
Ahmet Satiryigit
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Fatec Fahrzeugtechnik GmbH
Original Assignee
Fatec Fahrzeugtechnik GmbH
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Fatec Fahrzeugtechnik GmbH filed Critical Fatec Fahrzeugtechnik GmbH
Publication of WO2008095620A1 publication Critical patent/WO2008095620A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • 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
    • F16H61/00—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing
    • F16H61/04—Smoothing ratio shift
    • F16H61/0437—Smoothing ratio shift by using electrical signals
    • 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
    • G05B13/0205—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric not using a model or a simulator of the controlled system
    • G05B13/024—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric not using a model or a simulator of the controlled system in which a parameter or coefficient is automatically adjusted to optimise the performance
    • 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
    • F16H61/00—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing
    • F16H2061/0075—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing characterised by a particular control method
    • F16H2061/0081—Fuzzy logic
    • 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
    • F16H61/00—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing
    • F16H2061/0075—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing characterised by a particular control method
    • F16H2061/0084—Neural networks
    • 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
    • F16H61/00—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing
    • F16H2061/0075—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing characterised by a particular control method
    • F16H2061/0087—Adaptive control, e.g. the control parameters adapted by learning

Definitions

  • Switching operations between the transmission stages of a transmission are carried out by an electronic transmission control (EGS) depending on operating parameters, for example the transmission input torque, the transmission input speed or the transmission temperature, whereby also driver actions, such as a manual change from a comfort setting to a sport setting, can affect the switching operations by the EGS.
  • EGS electronic transmission control
  • driver actions such as a manual change from a comfort setting to a sport setting, can affect the switching operations by the EGS.
  • an individual adaptation is required for motor vehicles for every combination of vehicle body, engine and transmission.
  • the various control parameters are varied, wherein for each control parameter set, characteristic parameters are determined with which one is able to improve the quality of the circuit used, for example with regard to comfort and spontaneity grading characterize.
  • the control parameter set to be investigated after determining and evaluating the characteristic parameters for a control parameter set, the control parameter set to be investigated next can be done directly with the aid of a fuzzy logic based model, for example, with the correlation between the individual characteristic parameters and the various control parameters was determined on the basis of a comparative measurement.
  • a method for determining characteristics of an automatic transmission in which circuits are carried out between individual gear ratios on a final test bench. It will be determines the time courses of the transmission input speed, the transmission output speed, the transmission input torque and the transmission output torque. From these measured variables, a filling time, a filling pressure, a reaction time, a coefficient of friction of the lamellae and a pressurized fluid charge are determined as characteristic quantities of the automatic transmission for the clutch engaging in the switching operation. These parameters are stored in a memory, with the EGS correcting the pressure level and the switching times as a function of these parameters. The selected parameters are characterized by the fact that they allow direct conclusions about the transmission behavior, in particular control and gearbox tolerances can be detected and corrected. For a precise determination of the parameters, a large number of circuits are to be carried out between the individual gear ratios in the design of the automatic transmission.
  • the publication DE 102 38 474 A1 relates to a method for adapting shifting sequences of an automatic transmission, in which adaptation values depend on speed of the shift quality determining events takes place.
  • the adaptation to the individual vehicles equipped with the automatic transmission takes place on the basis of an individual adaptation characteristic determined for the respective vehicle.
  • the object is achieved by a method according to claim 1.
  • Characteristic parameters in the context of the invention are parameters which are suitable for characterizing the circuit which has been carried out and for describing them by objective numerical values.
  • Typical characteristic parameters are, for example, the duration of the switching process, which is a measure of the spontaneity, and the time course of the longitudinal acceleration or the change in the connection force of a rigidly held on a dynamometer motor vehicle.
  • Each characteristic parameter (KP x ) can be represented as a function of the various control parameters (SP j ) and the respective operating point, with respect to the operating point often only the transmission input speed and the transmission input torque and not the transmission temperature are taken into account. Accordingly:
  • KP x f (SPi, ... SP j , transmission input speed, transmission input torque)
  • the invention is based in particular on the knowledge that the characteristic parameters behave qualitatively the same with differentiation of the control parameters at different operating points as a function of the variation of the individual control parameters.
  • the difference in the behavior of the characteristic parameters with variation of the control parameters at different operating points is therefore essentially limited to the quantitative classification of their physical units.
  • a so-called D-optimal test plan described in the specialist literature is suitable for defining the control parameters SP 1 to SP j for each of the tests to be carried out.
  • characteristic parameters are determined from the connection force signal at the vehicle binding and the transmission input speed, with which the quality of the circuit that has been effected is characterized (objectification). This results in a link between the control parameter sets on the one hand and the associated characteristic parameters on the other.
  • switching operations are also performed only for a preferred set of control parameters, even for a second set of operating points.
  • the switching operations of the second set of operating points without a variation of the control parameters can be approached several times in succession, where from the measured values measured then identification parameters are identified and fed to a Ausr exerterbegraphy and averaging.
  • the operating point adaptation the algorithms previously determined in the modeling are applied to the second set of operating points, whereby a variation of the control parameters is numerically simulated on the basis of the control parameters which were determined for the second set of operating points in the test bench phase and determining parameters for the simulated control parameter sets.
  • the application of the algorithms to the second set of operating points is possible because the qualitative behavior of the characteristic parameters in the variation of the control parameter sets for different operating points matches qualitatively, so that the difference in the Kennparameter s and the variation of the control parameters at different operating points on the quantitative classification of their physical units is limited.
  • the assigned characteristic parameters must be known only for a preferred set of control parameters (actual state), on which basis the numerical modeling can be carried out with the generally valid algorithms determined during the modeling.
  • an evaluation factor for the quality of the associated switching operation is determined for each control parameter set and each operating point by means of evaluation functions, wherein the evaluation functions are preferably determined by a fuzzy logic model.
  • a variation of the operating point-specific control parameters is performed in order to determine a maximum weighting factor, wherein typically the control parameter sets having the highest weighting factors are stored.
  • the stored control parameter sets can be checked in a final verification phase by test measurements on the chassis dynamometer or an aggregate test bench, in which case the actually most suitable control parameter sets are selected from the stored control parameter sets.
  • Fig. 2 is a schematic representation of the inventive method for optimizing an electronically controlled automatically switching
  • Fig. 1 shows a chassis dynamometer 1, which is used in the context of the inventive method in a test phase P to determine the transmission system behavior of a built-in a motor vehicle 2 transmission.
  • the motor vehicle 2 is connected rigidly to a support 4 via a vehicle restraint 3, wherein a force-measuring element for determining the connection force is integrated in the vehicle restraint 3.
  • the temporal course of the connection force during a switching process is an important tuning signal for comfort evaluation, which is quasi-proportional to the longitudinal acceleration in a moving vehicle.
  • the electronic gearbox Controller 5 (EGS) is connected to a control computer 6, whereby the control parameters of the EGS 5 can be adjusted in real time between individual switching operations.
  • the time course of the connection force is also recorded in the control computer 6.
  • the driving resistance of a roller 7 of the chassis dynamometer 1 and the settings of a driving robot 8 is varied by the control computer 6, wherein the start of desired load and speed ranges is performed by the driving robot 8, which operates the accelerator pedal and can change the speed levels.
  • a deceleration or acceleration of the motor vehicle 2 is typically carried out by an active intervention in the control of the chassis dynamometer 1, so that the service brake of the motor vehicle 2 remains largely unused. Switching operations are usually not performed by moving the selector lever in manual mode, but by a digital command on the EGS 5, so that time delays between the gear request and tripping are avoided.
  • Fig. 2 shows schematically the sequence of the method according to the invention, wherein first in the test bed phase P on the test stand 1 shown in Fig. 1 switching operations for the identification of the transmission system behavior are performed. According to the invention, the further modeling and optimization is carried out using numerical models.
  • test bench hours for chassis dynamometers are relatively expensive, the test stands are rather rare and consequently the workloads are very high, it is always necessary to keep the duration of the effective test stand usage as low as possible. Consequently, when identifying the transmission system behavior, methods based on efficient design of the experiment must be used.
  • the transmission system behavior is identified by intelligent test planning. This is often referred to as so-called DoE (Design of Experiments) plans, which generate based on various optimization criteria for each of the different boundary conditions best possible experimental design.
  • DoE Design of Experiments
  • characteristic parameters are determined from the connection force signal and the transmission input speed with which one is able to characterize the quality of the circuit that has been made (objectification).
  • objectification the result is therefore a table in which the corresponding characteristic parameters KP DO E are available for each test circuit line, ie for each test program line and control parameter combination SP D0 E. Inputs and outputs of the measured system are therefore clearly defined.
  • the first line of the test plan stands for the so-called reference line, ie for the current state of the EGS 5 without the variation of control parameters.
  • this control parameter combination is called SPD O E, Ref.
  • the empirical modeling of the transmission model G can be done by numerous methods, such. B. polynomial models of higher orders or artificial neural networks.
  • the goal is to mathematically describe the behavior of the system identified by the test bench measurement. Therefore, the behavior of the parameter KP DO E with the
  • a special feature in the application of the process cycle shown in FIG. 2 is the processing of the data necessary for the model creation (control and characteristic parameter values). Modeling and application are carried out with respect to the transmission of the model information to unknown areas preferably in the general, normalized range between zero and one. The modeled characteristic parameter behavior is therefore no longer expressed in physical absolute values, but in dimensionless values.
  • Kennparamermodellen can be done.
  • the absolute characteristic parameter value KP B p The new operating point must therefore be normalized.
  • the characteristic parameter limits are needed for the normalization of the absolute characteristic parameter value KP BP .
  • the control parameter values of the DoE test plan (SP DO E) set in EGS 5 are available.
  • This is a matrix with i rows (i tries, ie i different control parameter combinations) and j columns (j varied control parameters).
  • the first line of this matrix has the name SP Ref and stands for the so-called reference line, in which the gear is not adjusted.
  • control parameter values SP B p [SP B pi SP B p.2 ⁇ SP B p ,, J and, on the other hand, associated characteristic parameter values KP B p of the new operating point.
  • a control parameter starting value in which z. If, for example, the ratio between the pressure to be switched on and off is five times higher than the original DoE measurement on the test bench, the characteristic parameter behavior will be different overall, while maintaining the same percentage control parameter variation, than one in which the ratio will be much lower. It is therefore necessary to make the reference line of the new test plan (new operating point: SP B p, R e f) comparable with the actual measurement (SP Ref ).
  • SPD is O E ( I , 2 ) the highly sensitive control parameter, hereinafter referred to as SP Ref, s.
  • SP Ref the highly sensitive control parameter
  • This newly created matrix ie this newly created operating point-individual experimental plan with (i + 1) rows, is normalized for every column, ie for each control parameter, with 0 ⁇ (SPD O E, BP ⁇ j X j £ 1.
  • the evaluation process B has the task of evaluating the quality of the simulated switching operations and in particular the suggestions of the optimization cycle O, so that based on these results new control parameter values can be calculated, which gradually approach an optimum value.
  • the evaluation is based on the principles of fuzzy logic, whereby a weighting factor BF is calculated, which quantifies the switching processes simulated in the office by calculating a key figure.
  • Inputs of the evaluation system are the normalized characteristic parameter values KP BP .
  • ⁇ of each characteristic parameter considered eg switching time, delay time, gradients, peak-to-peak values, .
  • KP B p, n For each standardized characteristic parameter value KP B p, n , a degree of membership is calculated which takes input into the set of rules (inference). The result is a weighting factor BF, which quantifies and outputs the relevant Kennparamterkombination.
  • the weighting factor BF is thus - in addition to the formulated relationships in the set of rules - dependent on the calculated degrees of membership of the inputs, which in turn depend on the nature and location of the membership function. If one moves the membership functions of the inputs on the abscissa to the right or to the left, one likewise shifts the target value of the relevant characteristic parameter. A high weighting factor BF is only obtained if the characteristic parameters input into the fuzzy system find that meet these targets. By actively shifting the membership functions of the input, it is thus possible to set the target specifications. This process is called abscissa shift. A high weighting factor BF therefore means that the parameter combination found corresponds very well with the formulated targets.
  • the optimization cycle can be carried out in the context of the inventive method based on an evolution model. It belongs to the class of stochastic search methods and also allows the treatment of complicated problems, which are no longer manageable due to excessive computational effort with traditional optimization methods.
  • a standardized characteristic parameter target value is calculated:
  • BFMAX theoretically maximum possible weighting factor
  • the optimization factors of the comfort determining parameters are started with relatively small factors, and it is assumed that there is no solution in the search space corresponding to these targets, which is expressed by small weighting factors.
  • the evaluation factors BFM A X found are compared with the theoretically maximum possible weighting factor and the associated control parameter combination is stored as soon as the value is greater than 90% of BF M Ax, theoretical.
  • the optimization factor is increased and approximated to the actual state. As soon as the characteristic parameter setpoint value exceeds the actual value by the continuous increase of the optimization factors, the optimization cycle O is ended.
  • test bench utilization times with respect to the known from the prior art method can typically be reduced to one third, with an even greater time savings can be achieved with increasing number of gear stages, since a parameter optimization always for all upshifts and downshifts between must be performed in each case adjacent transmission stages.

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  • Engineering & Computer Science (AREA)
  • General Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Health & Medical Sciences (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Evolutionary Computation (AREA)
  • Medical Informatics (AREA)
  • Software Systems (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)

Abstract

L'invention concerne un procédé d'optimisation d'un mécanisme de commutation automatique contrôlé de manière électronique pour une automobile. Pendant une phase de banc d'essai (P), le comportement du système mécanique est varié par une action de commutation entre deux étapes mécaniques pour au moins un point de fonctionnement grâce à la variation de paramètres de contrôle (SPDOE) pour cette action de commutation, des actions de commutation étant mises en oeuvre de manière supplémentaire pour une deuxième série de points de fonctionnement respectivement seulement pour une série préférée de paramètres de contrôle (SPBp). À partir de la variation des paramètres de contrôle (SPDOE), des algorithmes d'un modèle mécanique (G) sont formés, qui lient de manière empirique le comportement général de paramètres caractéristiques spécifiques (KPDOE) avec la variation des paramètres de contrôle (SPDOE). Ces algorithmes sont ensuite utilisés sur la seconde série de points de fonctionnement, une simulation numérique des séries de paramètres de contrôle et une détermination des paramètres caractéristiques affectés ayant lieu. Pour une évaluation de la qualité d'une action de commutation pour une série de paramètres de contrôle, un facteur d'évaluation est déterminé à partir des paramètres caractéristiques grâce à une fonction d'évaluation.
PCT/EP2008/000620 2007-02-06 2008-01-26 Procédé d'optimisation d'une boîte de vitesses automatique à commande électronique pour une automobile Ceased WO2008095620A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE200710006616 DE102007006616B3 (de) 2007-02-06 2007-02-06 Verfahren zur Optimierung eines elektronisch gesteuerten automatisch schaltenden Getriebes für ein Kraftfahrzeug
DE102007006616.5 2007-02-06

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WO2008095620A1 true WO2008095620A1 (fr) 2008-08-14

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Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
AT11001U3 (de) * 2009-10-28 2010-08-15 Avl List Gmbh Verfahren zum betreiben einer prüfanordnung
AT10998U3 (de) * 2009-10-28 2010-09-15 Avl List Gmbh Verfahren zum betreiben einer prüfanordnung
AT10999U3 (de) * 2009-10-28 2010-09-15 Avl List Gmbh Verfahren zum betreiben einer prüfanordnung
AT11003U3 (de) * 2009-10-28 2010-09-15 Avl List Gmbh Verfahren zum betreiben einer prüfanordnung
JP2017512954A (ja) * 2014-04-11 2017-05-25 アーファオエル・リスト・ゲーエムベーハー 自動車のトランスミッションのシフト挙動を評価するための方法
CN113339499A (zh) * 2021-07-04 2021-09-03 聊城大学 一种基于Q-Learning强化学习算法的智能换挡规律控制方法
CN115144191A (zh) * 2022-03-08 2022-10-04 中国地质大学（北京） 车辆直线加速模型的建立方法及利用其评价舒适性的方法

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102017006687B4 (de) 2017-07-14 2023-06-15 Audi Ag Prüfsystem zur Stückprüfung von Prüflingen und Verfahren

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DE19916006A1 (de) * 1999-04-09 2000-10-26 Zahnradfabrik Friedrichshafen Verfahren zur Anpassung von Parametern in einem Kennfeld
WO2002092379A1 (fr) * 2001-05-11 2002-11-21 Ricardo Mtc Limited Qualite de changement de rapport dans un vehicule
WO2004102287A1 (fr) * 2003-05-13 2004-11-25 Avl List Gmbh Procede d'optimisation de vehicules et de moteurs servant a l'entrainement de tels vehicules

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DE19643305A1 (de) * 1996-10-21 1998-04-23 Zahnradfabrik Friedrichshafen Verfahren zur Bestimmung von Kenngrößen eines Automatgetriebes
DE10057093A1 (de) * 2000-11-17 2002-05-23 Zahnradfabrik Friedrichshafen Verfahren zur Adaption von Schaltabläufen eines Automatgetriebes
DE10208205B4 (de) * 2001-02-27 2015-04-02 Schaeffler Technologies AG & Co. KG Verfahren zur Steuerung/Regelung optimaler Einkuppel-Verläufe beim Anfahren und Wiedereinkupplen nach Gangwechseln
DE10238474A1 (de) * 2002-08-22 2004-03-04 Zf Friedrichshafen Ag Verfahren zur Adaption von Schaltabläufen eines Automatgetriebes

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Publication number Priority date Publication date Assignee Title
DE19916006A1 (de) * 1999-04-09 2000-10-26 Zahnradfabrik Friedrichshafen Verfahren zur Anpassung von Parametern in einem Kennfeld
WO2002092379A1 (fr) * 2001-05-11 2002-11-21 Ricardo Mtc Limited Qualite de changement de rapport dans un vehicule
WO2004102287A1 (fr) * 2003-05-13 2004-11-25 Avl List Gmbh Procede d'optimisation de vehicules et de moteurs servant a l'entrainement de tels vehicules

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
AT11001U3 (de) * 2009-10-28 2010-08-15 Avl List Gmbh Verfahren zum betreiben einer prüfanordnung
AT10998U3 (de) * 2009-10-28 2010-09-15 Avl List Gmbh Verfahren zum betreiben einer prüfanordnung
AT10999U3 (de) * 2009-10-28 2010-09-15 Avl List Gmbh Verfahren zum betreiben einer prüfanordnung
AT11003U3 (de) * 2009-10-28 2010-09-15 Avl List Gmbh Verfahren zum betreiben einer prüfanordnung
JP2017512954A (ja) * 2014-04-11 2017-05-25 アーファオエル・リスト・ゲーエムベーハー 自動車のトランスミッションのシフト挙動を評価するための方法
CN113339499A (zh) * 2021-07-04 2021-09-03 聊城大学 一种基于Q-Learning强化学习算法的智能换挡规律控制方法
CN115144191A (zh) * 2022-03-08 2022-10-04 中国地质大学（北京） 车辆直线加速模型的建立方法及利用其评价舒适性的方法
CN115144191B (zh) * 2022-03-08 2023-08-18 中国地质大学（北京） 车辆直线加速模型的建立方法及利用其评价舒适性的方法

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