WO2022043105A1 - Procédé et appareil de commande d'un convertisseur électronique au moyen de procédés d'apprentissage automatique - Google Patents

Procédé et appareil de commande d'un convertisseur électronique au moyen de procédés d'apprentissage automatique Download PDF

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Publication number
WO2022043105A1
WO2022043105A1 PCT/EP2021/072646 EP2021072646W WO2022043105A1 WO 2022043105 A1 WO2022043105 A1 WO 2022043105A1 EP 2021072646 W EP2021072646 W EP 2021072646W WO 2022043105 A1 WO2022043105 A1 WO 2022043105A1
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WO
WIPO (PCT)
Prior art keywords
control signal
electronic
electronic converter
converter
course
Prior art date
Application number
PCT/EP2021/072646
Other languages
German (de)
English (en)
Inventor
Maja Rita Rudolph
Michael JIPTNER
Dennis Bura
Samuel Vasconcelos Araujo
Original Assignee
Robert Bosch 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 Robert Bosch Gmbh filed Critical Robert Bosch Gmbh
Publication of WO2022043105A1 publication Critical patent/WO2022043105A1/fr

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Classifications

    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02M—APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF
    • H02M1/00—Details of apparatus for conversion
    • H02M1/0003—Details of control, feedback or regulation circuits
    • H02M1/0025—Arrangements for modifying reference values, feedback values or error values in the control loop of a converter
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02M—APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF
    • H02M1/00—Details of apparatus for conversion
    • H02M1/0003—Details of control, feedback or regulation circuits
    • H02M1/0012—Control circuits using digital or numerical techniques

Definitions

  • the invention relates to controlling electronic converters using control signals.
  • the present invention relates to measures for shaping the control signals in order to achieve improved operating characteristics of the electronic converter.
  • Control signals are controlled using one or more control signals.
  • control signals follow predetermined courses for different events.
  • the commutation of transistors is often controlled via voltage or current signals via their gate inputs.
  • control signals are generated by a control unit or driver unit. These signals often have steps or ramps and/or periodic profiles in order to achieve the desired behavior of the electronic system.
  • a method for operating an electronic system with an electronic converter controlled by at least one original control signal for an electromechanical device or a power converter is provided, with the following steps:
  • Electronic systems often include an electronic transducer that is part of or drives electronic circuitry.
  • the electronic converter usually has active electronic components such. B. transistors, a MOSFET or the like and is driven by one or more control signals that are provided by a control unit or control circuit. For its part, the converter often controls electromechanical actuators, electrical machines or the like.
  • the one or more control signals can be determined by pulse signals, their pulse shapes, periodicities, in particular their cycle frequencies, pulse duty factors and the like, which bring about a corresponding reaction in the converter.
  • the behavior of the one or more control signals can decisively determine the behavior of the electronic system. For example, losses and faults in the electronic system, the service life of the System and loads on the converter can be largely determined by the time course of the state transition or state course of the control signal.
  • the control signal model is trained to provide an optimized/modified course of the modified control signal depending on the time course of the control signal or the course of the specified state transition or the given state course of the control signal, operating parameters of the electronic converter and its component properties and/or system properties to generate.
  • the course of the optimized/modified control signal is optimized with regard to a behavior of the electronic converter with regard to one or more criteria.
  • the behavior of the electronic converter can be simulated using a circuit simulation tool such as SPICE, or a circuit simulation, or with the (differential) equations that map the system behavior and those in the electronic circuit resulting response signals or the effect of applying the one or more control signals to the electronic converter are evaluated according to the criteria. So, for example, for a given control signal losses that z. B. correspond to the required switching energy, disturbances such. B. Vibrations as a step response to the state transition of the control signal, as well as loads on the electronic converter or the entire system that can affect the service life, such. B. temporary overvoltages or overcurrents, as well as high temperatures due to strong heat development.
  • a circuit simulation tool such as SPICE, or a circuit simulation, or with the (differential) equations that map the system behavior and those in the electronic circuit resulting response signals or the effect of applying the one or more control signals to the electronic converter are evaluated according to the criteria. So, for example, for a given control signal losses that z. B. correspond to the required switching
  • a performance measure can be provided to optimize performance.
  • One or more of the criteria for the behavior of the electronic system can be evaluated and, in particular, mapped to the behavior measure via a (differentiable) cost function.
  • the behavior measure is used to train the data-based control signal model. In doing so, a optimized/modified behavior measure of the modified control signal (provided by the control signal model) is used to train the data-based control signal model by minimizing this behavior measure.
  • the cost function for determining the behavior measure and the model equations of the circuit simulation must be automatically differentiable. This allows the calculation of the behavior measure based on the original and modified control signals to be combined directly with other components of the control signal model.
  • the model equations of the circuit simulation e.g. simulation tool, especially SPICE, or differential equations that describe the system behavior
  • the model parameters of the data-based control signal model can be trained directly with gradient-based methods (e.g. backpropagation). .
  • control signal model can be designed as a trainable data-based model, in particular as an artificial neural network, such as. B. a multi-layer perceptron or a recursive neural network.
  • the curve of the original control signal for controlling the electronic converter can be parameterized or defined by control signal parameters and/or the curve of the modified control signal can be parameterized or defined by corresponding control signal parameters.
  • the profile of the original control signal and/or the modified control signal can be parameterized by time segments and the values of an electrical variable, in particular a voltage or a current, assigned to the time segments.
  • Further control signal parameters can be a cycle frequency of a periodic control, in particular a frequency and/or pulse width modulation, a degree of modulation, a duty cycle, a pulse duration and/or a pulse shape.
  • the operating conditions of the electronic converter to be controlled can relate to the operation of the electronic converter and in particular can include one or more of the following variables: one on the electronic Converter applied voltage, a current flowing through the electronic converter current at the current time and a current temperature of the electronic converter.
  • the operating characteristics may relate to general characteristics of the type of electronic converter, in particular a transistor, and in particular may include one or more of the following parameters: a threshold voltage, a leakage current at the gate terminal, an on-state resistance and their variances of these quantities .
  • control signal model can be trained by optimizing a behavior measure that results from the control signal model and a downstream circuit simulation in order to adapt model parameters of the control signal model, the circuit simulation, in particular with model equations, being designed to convert a modified control signal into one or more behavior variables to be determined, a behavior measure being able to be determined as a function of the one or more behavior variables, which indicate the behavior of the electronic system in response to modified control signals, as a function of a predefined cost function.
  • the one or more behavioral variables can indicate a performance of the electronic system when controlled by the modified control signal, the behavioral variable being a power loss, a degree of interference, in particular in the form of oscillations or overshoots, a thermal load in particular on the electronic system and/or a indicates an expected service life of the electronic converter or the electronic circuit influencing the load level ?? Sentence.
  • the optimization is carried out taking into account a side condition that the achievement of the control signal in the electronic system function ensured by the modified control signal and / or wherein the cost function for calculating the measure of behavior takes into account a parameter that evaluates how the function caused by the control signal is achieved by the modified control signal.
  • a device for operating an electronic system with an electronic converter controlled by at least one original control signal for an electromechanical device or a power converter, the device being designed for:
  • an electronic system with a converter with an electronic circuit and the above device is provided.
  • FIG. 1 shows a schematic representation of an electronic system with an electronic converter which is to be controlled in an optimized manner with one or more optimized control signals;
  • FIG. 3 shows a possibility for parameterizing the control signal
  • Figure 4 is a flowchart to illustrate a method for operating the electronic converter in the electronic system of Figure 1.
  • Figure 1 shows a schematic representation of an electronic system 1 with an electromechanical device 2, such as. B. an electrical machine, an electromechanical actuator, or a power converter, which is coupled in any way with an electronic converter 3.
  • the electronic converter 3 can be, for example, an inverter, an H-bridge circuit, a B6 bridge circuit, any other electronic power circuit with transistors, such as. B. MOSFETS o. ⁇ ., Or the like.
  • the electronic converter 3 is activated as a function of one or more control signals S in order to carry out a function in the electromechanical device 2, it being possible for the electronic converter 3 to be part of the electromechanical device 3 or separate therefrom.
  • the one or more control signals S are provided by a control unit 4 .
  • the one or more control signals S can be a current or voltage signal and can be applied to a control input of the electronic converter 3 in order to implement a desired function.
  • the one or more control signals S are presented as a time course of an electrical condition, such as e.g. a voltage or a current, and may include state transitions or state histories.
  • a control signal model block 5 the one or more original control signals S provided by the control unit 4 are modified with a control signal model and provided as corresponding modified control signals S′.
  • FIGS. 2b and 2c show signal curves of a voltage or a current of a resulting signal in the electromechanical device 2 based on a curve of a provided control signal S shown in FIG Flank and / or have a current peak.
  • the actuation with the one or more control signals S in the electromechanical device 2 can generate power losses due to the switching energy consumed, which depend on the course of the control signals S over time.
  • the electronic converter 3 or the electronic system 1 can also be subject to loads depending on the shape of the curve of the control signal S, which can impair the service life of the electronic system 1 . This can be caused, for example, by temporary overvoltages or overcurrents and high temperatures.
  • the behavior of the electronic system 1 can be evaluated according to various criteria and mapped to a behavior variable. By varying the course and/or form of the control signals S, the various behavior variables can be varied in order to improve the behavior of the electronic system 1 .
  • the one or more behavior variables can be determined by a circuit simulation, such as in the SPICE programming language, with which the reaction of the electromechanical device 2 to the course of any control signals can be determined.
  • response signals to the control signals S are modeled and evaluated using one or more behavior variables according to one of the criteria mentioned above (power loss, switching losses, overshoot, load, etc.).
  • the one or more behavior variables can be combined using a (differentiable) cost function in order to determine a behavior measure that characterizes a behavior of the electronic system 1 .
  • the measure of behavior can be calculated by a sum of the weighted measures of behavior.
  • the weightings can be specified according to an optimization criterion.
  • Limit values can be used as criteria, e.g. B. be defined for temperatures, voltages or the like, so that the behavior measure is determined depending on a distance of the respective behavior variable from the respective limit value.
  • control signal S in the control signal model block 5 In order to process the control signal S in the control signal model block 5, it must be parameterized in a suitable manner. This can take place in the control unit 4 or on the input side in the control signal model block 5 . In the latter case, a provided analog control signal can be sampled and parameterized in a suitable manner.
  • the control unit 4 can specify the one or more original control signals by time segments and the values of an electrical variable, in particular a voltage or a current, assigned to the time segments.
  • control signal S can be defined in several time intervals/time steps with different durations t1, t2, . . . , tn and with respective amplitudes A1, A2, .
  • the modified or optimized control signal S' to be determined by the control signal model can be parameterized in the same way or in a different way.
  • control unit 4 can also indicate the one or more control signals by one or more parameters of a periodic activation, such as e.g. B. a cycle frequency of a periodic control, in particular a frequency and / or pulse width modulation, a degree of modulation, a duty cycle, a pulse duration and / or a pulse shape.
  • a periodic activation such as e.g. B. a cycle frequency of a periodic control, in particular a frequency and / or pulse width modulation, a degree of modulation, a duty cycle, a pulse duration and / or a pulse shape.
  • the control signal model can be a data-based, trainable model, in particular an artificial neural network, or a regression model.
  • an artificial neural network is assumed as a model, since this can be trained in a simple manner by differentiation.
  • the control signal model can be implemented in different variants.
  • the control signal model can be implemented as hardware or software in the control unit 4 as part of the electronic system 1 or separately thereto.
  • the control signal model can be implemented in the control unit 4 with an adaptation function, in which the control signal model is retrained accordingly at predetermined points in time or regularly in order to correct aging effects in the electronic system 1 . An implementation in the latter variant is described in more detail below with reference to a flowchart in FIG.
  • control unit 4 The method presented there can be implemented in a control unit 4 using hardware and/or software.
  • step S1 the control unit 4 of the electronic system provides parameters for a suitable parameterization of the time profile of the one or more control signals S that are to be applied to the electronic converter 3 in sequence.
  • the original control signal S is provided in parameterized form by the control unit 4 or provided as a progression of the state of an electrical variable (current or voltage).
  • the parameterization can be carried out in the control signal model block 5 .
  • the parameterization can provide, for example, for the control signal to be divided into a number of time steps and for a corresponding amplitude value to be assigned. In this way, an amplitude can be specified for a number of upcoming magazines.
  • step S2 the one or more parameterized, original control signals S are transmitted to the control signal model together with the operating conditions of the electronic converter 3 to be controlled and operating properties and/or system properties.
  • the operating conditions relate to the operation of the electronic converter 3 and can include one or more of the following variables: a voltage present at the electronic converter 3 and a current flowing through the electronic converter 3 at the current time, and a current Temperature of the electronic converter 3.
  • the operating characteristics can relate to general characteristics of the type of electronic converter 3 and concern one or more of the following parameters: threshold voltage, leakage current at the gate terminal, on-state resistance as well as their variances, which are caused either by scattering due to Manufacturing tolerances or due to aging effects.
  • the system properties can relate to other components of the electronic circuit that can affect the operation of the electronic converter 3 .
  • the system properties can include one or more of the following parameters of other system components of the electronic circuit: a thermal resistance of the overall structure, which is decisive for the temperature of the electronic converter 3 to be controlled, the capacitance of a back-up capacitor, which is coupled to the electronic converter 3 , and the same.
  • variances in these variables which result either from manufacturing tolerances or from aging, can also be taken into account as such parameters.
  • control signal model determines a modified control signal that can be used to control the electromechanical device 2 .
  • the electronic converter 3 is controlled in accordance with the profile specified by the modified control signal parameters of the modified control signal S'.
  • the conversion of the modified control signal parameters, which define the modified control signal S', into the analog control signal S' can preferably take place in the control signal model block 5 or in a separate device.
  • step S4 An adaptation criterion can be checked in step S4. If the adaptation criterion provides for a further adaptation or update of the control signal model (alternative: yes), the method continues with step S5, otherwise (alternative: no) the process jumps back to step S1.
  • Adaptation criteria can depend, for example, on a predetermined period of time since the last adaptation, on the course of the original control signal, or on an external adaptation signal.
  • an update of the control signal model can be triggered if system properties such. B. a temperature, voltage values, measurement signal and the like, deviate from corresponding predetermined reference values by more than a predetermined amount of deviation.
  • the adaptation criteria should be used to check whether the control signal model needs to be retrained due to component aging, wear or other systematic changes in the operating conditions.
  • step S5 the control signal model is retrained.
  • the retraining of the control signal model serves to correct inaccuracies in the circuit simulation and the component models on which it is based in the control signal model, e.g. B. due to component aging, wear or other systematic changes in the operating conditions, the learned control signal (adjustments) are no longer optimal.
  • the retraining of the control signal model aims to generate modified control signals from given control signals, for which the behavior measure is optimized.
  • the cost function of the behavior measure and the system of equations of the circuit simulation can be used in connection with a gradient descent method in order to further train the model parameters of the control signal model.
  • the control signal model is initially created using a training data set made up of control signals and associated modified control signals.
  • the modified control signals are each determined based on a specified control signal and depending on a behavior measure that is determined from one or more behavior variables that are determined for the modified control signal using a circuit simulation and the specified cost function.
  • control signals are specified with as many variants as possible within the scope of the possible control signals for driving the transistor 3 .
  • the circuit simulations can determine the one or more corresponding behavior variables or the resulting behavior measure (depending on a predetermined cost function) based on the parameterization of the modified control signal S'.
  • a training data record for the control signal model can be performed by optimizing (minimizing) the behavior measure with respect to a relevant control signal, in particular by backpropagation. This is possible because, as a rule, the functions underlying a circuit simulation can be differentiated, so that the optimized performance measure can be determined by differentiating the cost function and the function of the circuit simulation for updating the model parameters of the control signal model.
  • the optimization can be carried out with suitable secondary conditions.
  • a parameter can also be taken into account in the cost function for calculating the behavior measure, which parameter evaluates how the function brought about by the control signal is achieved by the modified control signal.
  • control signal model in the form of a neural network, such as. B. a recurrent neural network (LSTM, GRU), a multi-layer perceptron or the like.
  • LSTM recurrent neural network
  • GRU multi-layer perceptron
  • control signal model can also be retrained externally to the electronic system 1 .
  • the parameterized original and modified control signals S, S' as well as the operating conditions and the component parameters and system parameters are transmitted to an external computing unit, which carries out the circuit simulations in the knowledge of the electromechanical device 3 in order to calculate the behavioral variables or the behavioral measure.
  • the model parameters of the neural network can thus be retrained externally and the model parameters can be transmitted back to the electronic system 1 so that they can be used in sequence.
  • control signal model can also be implemented as a lookup table in the electronic system, so that the control signal parameters of the original control signal are assigned according to the lookup table to modified control signal parameters which represent the modified control signal S'.
  • the lookup table is created based on a control signal model that can be implemented externally to the electronic system 1 . In this way, the computing effort in the electronic system 1 can be significantly reduced.

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Dc-Dc Converters (AREA)

Abstract

L'invention concerne un procédé de fonctionnement d'un système électronique (1) présentant un convertisseur électronique (3) commandé par au moins un signal de commande d'origine (S) pour un dispositif électromécanique ou un convertisseur de puissance, ledit procédé comprenant les étapes suivantes : - la fourniture (S1) d'un profil du signal de commande d'origine (S) destiné à commander le convertisseur électronique (3), - la modification (S2) du profil d'origine dudit signal de commande en fonction d'un modèle de signal de commande basé sur des données apte à l'apprentissage afin d'obtenir un profil d'au moins un signal de commande modifié (S'), ledit modèle de signal de commande étant conçu pour déterminer le profil dudit signal de commande modifié (S') en fonction du profil dudit signal de commande d'origine (S) et en particulier de conditions de fonctionnement du convertisseur électronique (3) et/ou de propriétés de fonctionnement et/ou de propriétés du système ; - la commande (S3) du convertisseur électronique (3) à l'aide dudit signal de commande modifié (S').
PCT/EP2021/072646 2020-08-27 2021-08-13 Procédé et appareil de commande d'un convertisseur électronique au moyen de procédés d'apprentissage automatique WO2022043105A1 (fr)

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DE102020210825.0 2020-08-27
DE102020210825.0A DE102020210825A1 (de) 2020-08-27 2020-08-27 Verfahren und Vorrichtung zum Steuern eines elektronischen Wandlers mithilfe maschineller Lernverfahren

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Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102017128123A1 (de) * 2017-11-28 2019-05-29 Deutsches Zentrum für Luft- und Raumfahrt e.V. Verfahren zur Selbstoptimierung des Wirkungsgrads eines in einem Arbeitspunkt betriebenen Schaltreglers

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102017128123A1 (de) * 2017-11-28 2019-05-29 Deutsches Zentrum für Luft- und Raumfahrt e.V. Verfahren zur Selbstoptimierung des Wirkungsgrads eines in einem Arbeitspunkt betriebenen Schaltreglers

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Title
STENDER MARIUS ET AL: "Development of a Black-Box Two-Level IGBT Three-Phase Inverter Compensation Scheme for Electrical Drives", 2019 IEEE 28TH INTERNATIONAL SYMPOSIUM ON INDUSTRIAL ELECTRONICS (ISIE), IEEE, 12 June 2019 (2019-06-12), pages 296 - 301, XP033586135, DOI: 10.1109/ISIE.2019.8781543 *
TAMRAKAR UJJWOL ET AL: "Design of online supplementary adaptive dynamic programming for current control in power electronic systems", 2017 IEEE ENERGY CONVERSION CONGRESS AND EXPOSITION (ECCE), IEEE, 1 October 2017 (2017-10-01), pages 3038 - 3043, XP033247251, DOI: 10.1109/ECCE.2017.8096556 *

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