WO2018059906A1 - Procédé permettant de faire fonctionner un réseau de bord électrique - Google Patents

Procédé permettant de faire fonctionner un réseau de bord électrique Download PDF

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Publication number
WO2018059906A1
WO2018059906A1 PCT/EP2017/072539 EP2017072539W WO2018059906A1 WO 2018059906 A1 WO2018059906 A1 WO 2018059906A1 EP 2017072539 W EP2017072539 W EP 2017072539W WO 2018059906 A1 WO2018059906 A1 WO 2018059906A1
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WIPO (PCT)
Prior art keywords
components
component
energy
state
motor vehicle
Prior art date
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PCT/EP2017/072539
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German (de)
English (en)
Inventor
Hans-Peter Seebich
Tuelin Baysal
Armin Ruehle
Juergen Barthlott
Patrick MUENZING
Oliver Dieter Koller
Christian Bohne
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
Priority to CN201780059205.9A priority Critical patent/CN109789843A/zh
Priority to EP17764393.9A priority patent/EP3519251A1/fr
Priority to JP2019516514A priority patent/JP6768152B2/ja
Publication of WO2018059906A1 publication Critical patent/WO2018059906A1/fr

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Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R16/00—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for
    • B60R16/02—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements
    • B60R16/03—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements for supply of electrical power to vehicle subsystems or for
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/005—Testing of electric installations on transport means
    • G01R31/006—Testing of electric installations on transport means on road vehicles, e.g. automobiles or trucks
    • G01R31/007—Testing of electric installations on transport means on road vehicles, e.g. automobiles or trucks using microprocessors or computers

Definitions

  • the invention relates to a method and an arrangement for operating an energy supply system of a motor vehicle.
  • An energy supply system of a motor vehicle has the task of supplying electrical consumers with energy. If an energy supply fails due to a fault or aging of at least one component of the energy system, important functions, such as, for example, the power steering, are eliminated. Since the steering ability of the motor vehicle is not impaired, but only becomes difficult, the failure of the power plant network is generally accepted in today in series vehicles.
  • Two-channel energy network are u. a. in the publication WO 2015/135729 AI or in the publication DE 10 2011 011 800 AI described.
  • a monitoring arrangement for monitoring an energy system of a motor vehicle is known from the document DE 10 2013 201 060 AI.
  • the power cord network has a high-voltage electrical system and a low-voltage electrical system, which are connected to each other via a DC-DC converter, wherein the low-voltage electrical system several safety-critical consumers are connected.
  • the monitoring arrangement has a monitoring control unit and as further components for each safety-critical consumer an associated sensor for detecting a value of an electrical operating parameter of the consumer, wherein the monitoring control unit is adapted to monitor at least one consumer taking into account the detected value for the electrical operating parameter.
  • a monitoring unit for all the components of the energy used with all components with regard to their current and possible future state for example, taking into account wear and / or aging, be monitored preventively.
  • a prediction of the future state can be based on these two aspects, ie wear and aging. However, other aspects may alternatively or additionally be taken into account.
  • PCM Powernet Condition Management
  • a monitoring of a current state and a prognosis for the wear of components of the power plant network is carried out, with which the state of the power system on a system level of
  • the monitoring unit comprises as modules a diagnostic module and a prognosis module.
  • a diagnosis of an actual state can be carried out for each component as a possible state analysis.
  • a diagnosis of an actual state and thus of the current state can also be carried out for the entire energy on-board network, usually with comprehensive consideration of all the components of the energy on-board network, as a possible state analysis.
  • a prediction of a future state can be performed for each component as a possible state analysis.
  • a prediction of a future state can also be carried out for the entire energy on-board network, usually with comprehensive consideration of all the components of the energy on-board network, as a possible state analysis.
  • this monitoring unit taking into account at least one diagnosis and / or prognosis for at least one component and / or at least one vehicle electrical system channel and / or the entire energy grid, it is generally automatically decided whether a driving function, for example an automated driving function, may be released or has to be stopped. For this is the
  • Monitoring unit which combines the components of the energy comprehensively and comprehensively monitored, with which an overall state of the energy supply, which is dependent on at least one physical operating variable, is assessed by the energy on-board network, since individual components of the energy on-board network generally can not assess this for lack of information about the entire energy supply network.
  • the driving function is supported by at least one component of the energy on-board network.
  • individual components of the power system supply current values of at least one, as a rule, physical operating variable, for example current, voltage or temperature, to the monitoring unit.
  • the current state of the energy on-board network is monitored by merging a diagnosis of individual components and of the entire power system.
  • the diagnosis of the power system on the system level serves to validate the plausibility of the individual components at the component level.
  • an analysis of a reliability of the entire energy onboard network and individual components of the power plant network can be performed.
  • critical states of the energy supply are predicted depending on a topology of the energy grid, depending on causes of failure and / or dependent on an operating mode which is set, for example, for carrying out a respective driving operation of the motor vehicle.
  • values of the at least one operating variable are detected and monitored in real time, whereby a load of the at least one component is determined on the basis of a state and reliability monitoring.
  • values of a state analysis of individual components which, for example, also include failure probabilities, are transmitted to the monitoring unit and used for a status analysis of the entire on-board network.
  • the state of all relevant components of the motor vehicle can be monitored in its entirety (status monitoring).
  • the arrangement is suitable from the point of view of product safety for safety-critical new ones
  • Automated driving function is supported in an embodiment. In this case, aging effects of at least one component in the energy supply system are taken into account, which are important at least for such a driving function.
  • the release of the driving function can be suppressed and / or revoked. If the driving function is currently being carried out and a safety-relevant state of the at least one component is detected, it may be prompted for the driving function to be ended and left. This concerns, for example, also a sailing as
  • driving strategies are applied preventively, by means of which driving situations are avoided which lead to a severe aging of the at least one component of the energy on-board network, thereby increasing the reliability of the energy on-board network.
  • the method also includes performing at least one preventive maintenance action on the at least one component, which may be e.g. B. in a regular maintenance interval is feasible, whereby an availability of at least one component is increased.
  • Carrying out a driving function for example in an automated driving operation, For example, a change and / or a transfer of control of the motor vehicle to a driving function that can be controlled more easily by the driver can be carried out in a manual driving operation.
  • a driving function for example in an automated driving operation
  • a change and / or a transfer of control of the motor vehicle to a driving function that can be controlled more easily by the driver can be carried out in a manual driving operation.
  • the motor vehicle also at
  • This also relates to the measure to prevent a release of the driving function, if a critical condition, eg. Due to deterioration of the at least one component of the power transmission system with high importance for the motor vehicle, should be predicted with the monitoring unit for the power onboard. Thus, it is possible to warn ahead of the critical state at an early stage, which saves time in the initiation of a fallback strategy.
  • a critical condition eg. Due to deterioration of the at least one component of the power transmission system with high importance for the motor vehicle
  • the reliability and safety of the motor vehicle can be increased even in manual, non-automated driving, whereby a lingering, for example. On a lane of a motorway, avoided can.
  • a performance of a future automated and autonomous driving operation and thus a corresponding driving function of the motor vehicle can be controlled and / or supported, taking into account that the driver in such a driving operation no longer than sensory, regulatory, mechanical and energy fallback
  • the motor vehicle now has functions or has to be available, since now the motor vehicle assumes functions of the driver, such as an environment recognition, a trajectory planning and a trajectory conversion, which, for example, also includes the steering and braking.
  • a load and / or a load capacity of components of the power system are determined with the monitoring unit, wherein the load during operation is determined in real time.
  • Resilience models for the components are determined in advance, for example in tests, for specific conditions.
  • the load is converted to the conditions of resilience.
  • the load capacity models are usually stored component-dependent in the monitoring unit (PCM). If, during operation, at least one component should fail, which is avoided with the monitoring unit, it is possible to adapt and / or generate loadability models by evaluating a number of failures of the same components of the same design. From the load capacity is concluded on a future state of the power plant network.
  • an aging and / or wear is identified for a component, at least its relevance for the energy on-board network, as a rule for the entire motor vehicle as a system level, is taken into account as part of an importance or import analysis.
  • An importance of a component depends on a topology of the power rail network that may be single-channel or multi-channel, and may or may not include an additional battery.
  • the topology of the power cord system installed in the motor vehicle is usually determined after its production.
  • the structure of the energy onboard network is analyzed at least once or only once during the development of the energy grid, taking into account, if necessary, operating modes and causes of failure.
  • the structure is then stored as at least one algorithm in the monitoring unit.
  • the determination of the state of the energy onboard network with the monitoring unit comprises a systemic diagnosis as a state analysis on the basis of the values of the physical operating variables as input variables, based on which an actual state of the power plant network is analyzed, and a forecast for predicting the future state of the power plant network based on
  • Components for example.
  • a use of a component usually has no influence on the load capacity.
  • the load on the component results from their use in motor vehicles.
  • a previous total load of the at least one component can likewise be determined from values of these operating parameters which are determined and collected over a relatively long period of time, for example during the entire previous operation of the at least one component.
  • a current load of the at least one component can be determined from current values of these operating parameters. Values of the operating variables are provided to the monitoring unit with sensors that are assigned to the components. In this case, the load is determined on the basis of values of the at least one physical operating variable that has hitherto resulted during operation of the at least one component. From load-relevant operating variables and a previous load in combination with the load capacity, the failure probability is calculated as at least one reliability parameter of the at least one component, for example.
  • field data can be recorded, which can be taken into account for the design and / or design of future components.
  • physical and / or systemic diagnoses of the individual components are combined in the monitoring unit and thus at a central location. It is also possible to perform the method software-based, since the monitoring unit has at least one arithmetic unit or as a computing unit for monitoring the
  • Components of the power take-off network is formed. It is conceivable that a driving function is forbidden and therefore not released, although a current actual state of the electrical power system determined on the basis of the diagnosis made as a diagnosis may be in order, but due to the state analysis also carried out as a prognosis, a future critical state is forecasted.
  • Possible faults and / or possible aging of components of the power plant network are or are detected by the method, it being possible to provide that an operating mode for carrying out a driving function is terminated or disabled and a transition to a safe operating mode is initiated, wherein a check of the Driving function can be passed to the driver, which is also possible under consideration of the prognosis of the future critical state, although a single component, even taking into account the diagnosis no error or no aging reports.
  • a state analysis that includes multiple components and thus possibly performed for the entire energy on-board network is classified higher than a state analysis for only one component or a few components.
  • a driving function is specifically released depending on an operating mode, a failure cause and / or a topology of the energy on-board network. In an embodiment, it is taken into account which components support a respective driving function and are therefore necessary for their implementation.
  • a decision on a release of a driving function can be made for each driving function, in an embodiment for an automated driving function.
  • a driving function can z. B. be designed as a sailing operation in a manual drive but also as a sailing operation in an automated ride.
  • a condition analysis that considers multiple components together can be used to validate a condition analysis that takes a smaller number of components into account together. This plausibility check whether results of a state analysis, the components to a higher-level control unit and / or the monitoring unit report, to results of a state analysis, resulting from a system-related consideration of the complete energy grid fit.
  • the energy supply network can be mapped by means of node and mesh rules, whereby any implausibilities can be detected.
  • an energy on-board network can have components of only one manufacturer or of different manufacturers.
  • a component of a first manufacturer can be supplemented and / or replaced by a component of another manufacturer. It is possible that there is no loadability model and / or aging model for such a foreign component, which may be the case, for example, if this component is not specifically intended for use in a motor vehicle. However, this component may also be monitored in one embodiment of the method and its
  • Condition diagnosed as well as the future condition can be predicted. If the energy on-board network consists of components from different manufacturers, it is envisaged that different power handling models of the respective manufacturers can be implemented in the monitoring unit. It is conceivable z. B. that in each component the load capacity model and the required
  • Components are used for which load-bearing models are available.
  • cloud-based changes in an operating mode or operating strategy can be derived by exchanging data with the database over the Internet to detect failures of the database
  • Field data development of the components can be improved by Capture of field data due to a large number of components monitored in the field, load models, e.g. B. by deep learning can be improved. It is also possible that known loadability models are adjusted and / or updated taking into account known, real loads on the components.
  • the method can be used for any motor vehicle in which a release of certain driving functions in response to a previous load, stress and / or aging of components of the power plant network and the current state of the components to be granted.
  • the method can be used in any motor vehicle whose power cord system has a high safety relevance, which relates, for example, a motor vehicle, with a sailing or recuperation can be performed, and / or an automated motor vehicle for performing a highly automated, fully automated or autonomous driving operation.
  • modules for example an engine, a drive unit, a steering, a brake and / or an electric brake booster of the motor vehicle, which influence a trajectory of the motor vehicle in the respective driving operation, are automatically controlled and thus controlled and / or or regulated.
  • At least some steps of the presented method can be performed by the monitoring unit and / or the control unit software-supported.
  • FIG. 1 shows a schematic representation of an example of an energy on-board network of a motor vehicle for which an embodiment of the method according to the invention can be carried out with an embodiment of the arrangement according to the invention.
  • Figure 2 shows a schematic representation of the embodiment of the arrangement according to the invention.
  • FIG. 3 shows a diagram of an embodiment of the method according to the invention with the embodiment of the arrangement according to the invention from FIG. 2.
  • FIG. 4 shows details of operating modes which can be realized in the context of the embodiment of the method with the power cord system.
  • the example shown schematically in Figure 1 of the power plant network 2 for a motor vehicle comprises a first channel 4, which is also referred to as the base unit network, and a second channel 6. Both channels 4, 6 are connected here via a DC-DC converter 8.
  • the first channel 4 of the power cord network 2 comprises as components a starter 10, a generator 12, a first battery 14, at least one non-safety-relevant consumer 16, and at least one first safety-relevant consumer 18.
  • the second channel 6 comprises a second battery 20 and at least one second safety-relevant consumer 22 as components. In this case, at least one function which is executed by the at least one first safety-relevant consumer 18 can be carried out redundantly by the at least one second safety-relevant consumer 22.
  • the safety-relevant th consumers 18, 22 may also be referred to as safety-critical consumers.
  • both channels 4, 6 here have an electrical voltage as an operating variable, values for this voltage being identical for both channels 4, 6 here and, for example, each being 12 volts.
  • the two channels 4, 6 of this power cord network 2 is constructed redundantly. With the mentioned components of the power cord system 2, it is possible to realize functions for an automated driving of the motor vehicle. However, it is also conceivable that the two channels 4, 6 have different voltages.
  • the embodiment of the arrangement 24 according to the invention schematically illustrated with reference to FIG. 2 comprises an energy on-board network 25 for a motor vehicle, this energy on-board network 25 including several consumers as components 28, 30, 32. Details of this energy onboard network 25 are shown in FIG. 4. These components 28, 30, 32 form a component level 26 of the power system 25.
  • the energy board network 25 is assigned to a system level 34, a monitoring unit 36 as a module designed as a diagnostic module 38 module for performing a systemic diagnosis here as state analysis, as a forecasting module 40 trained module for performing a prognosis as a state analysis and trained as a load capacity module 42 in the resilience models are deposited or z. B. be deposited by reading.
  • the prediction module is used to determine a load of the components 28, 30, 32, taking into account the loadability models from the load capacity module 42, wherein characteristics for a reliability of the components 28, 30, 32 are determined. These reliability characteristics are used by the prognosis module 40 for analyzing and forecasting the state of the power plant network 2, 25.
  • the loadability module 42 comprises the loadability models of the components of the energy on-board network 28, 30, 32.
  • the system level 34 comprises a module designed as an energy management module 44, which is connected to the monitoring unit 36 and to the components 28, 30, 32.
  • a vehicle level 45 of the motor vehicle comprises a control unit 46.
  • the monitoring unit 36 receives from the components 28, 30, 32 of the energy on-board network 25 values of physical operating variables, for example of physical state variables, of the components 28, 30 , 32 provided by sensors in-service.
  • each component 28, 30, 32 of the monitoring unit 36 transmit information about their state, such information is supplemented by values of the physical state variables that are measured in the power plant network 25 in important places.
  • the monitoring unit 36 is also provided with information on a previous load, which is based on previously determined values of the physical operating variables, of at least one respective component 28, 30, 32.
  • the monitoring unit 36 makes decisions regarding an operating mode, a failure cause of a component 28, 30, 32 and a topology-specific release for an automated driving function. For each failure cause and each mode of operation possible with the motor vehicle, authorizations and relinquish requests for operating modes and, if necessary, further functions, eg, for the topology installed in the motor vehicle, are made. For example, a forecast for a replacement of a component and planning for a next regular workshop visit, z. For a main inspection (HU).
  • HU main inspection
  • a normal travel 48, a recuperation 50 and a sailing operation 52 are given by way of example as operating modes and / or driving functions of the motor vehicle.
  • the sailing operation 52 can be carried out in an automated journey.
  • the monitoring unit 36 determines whether an automated driving function of the motor vehicle must be released or has to be stopped, or if a respective operating mode must be exited or can be carried on.
  • a respective information about this is provided to the control unit 46 of the motor vehicle.
  • information that is detected in the embodiment of the method are transmitted by radio via the Internet to a central, fixed unit 54, wherein this unit 54 may be formed as a database and / or workshop.
  • the central unit 54 communicates with the monitoring unit 36 information.
  • FIG. 3 shows a possible division and a flow of information in the monitoring unit 36 when performing an embodiment of the method according to the invention.
  • a prognosis is carried out by the monitoring unit 36 with the prognosis module 40 and a diagnosis is made with the diagnosis module 38.
  • the prognosis module 40 via an interface 56 external load models for the components 28, 30, 32 are provided.
  • the resilience models are stored in the forecasting module 40. It is also conceivable that each component 28, 30, 32 carries an identification number, with which an associated resilience models can be obtained from the Internet.
  • a first input 58 is provided, via which the monitoring unit 36, in this case the prediction module 40, load data of the components 28, 30, 32 are provided during an ongoing operation of the power system 25.
  • the load data are derived from time-dependent courses of physical state variables, for example the current, the voltage and the temperature. To determine such curves, values of the physical state variables are collected during operation.
  • the diagnostic module 38 is provided by the components 28, 30, 32 via a second input 60 information on possible errors of components 28, 30, 32. Via a third input 62, the diagnostic module 38 and thus also the monitoring unit 36 receive information, in this case values for physical state variables, for example current values for current, voltage and / or temperature, which for the components 28, 30, 32 during operation of the Energybordnetzes 25, provided.
  • the input 62 can be used to transmit additional physical state variables, for example instantaneous current, voltage and / or temperature values, which are measured at selected locations in the energy on-board network 25, to the diagnosis module 38 and thus also to the monitoring unit 36.
  • the prediction module 40 can use load-bearing models 64 of the components 28, 30, 32 generated and deposited in the forecasting module 40.
  • 64 reliability characteristics of the components 28, 30, 32 are determined from the load data of the components 28, 30, 32 and the load capacity models, z. B. a momentary probability of failure of a component 28, 30, 32 due to aging and / or wear.
  • Other load capacity models from other manufacturers may be provided via the interface 56. From this, a probability 66 of an error of a component 28, 30, 32 due to wear is calculated. Furthermore, a second probability 68 for an unsafe state of the entire power system 25 is calculated taking into account aspects 70 which represent an operating mode of the
  • a cause of failure and a topology of the power plant network 25 relate.
  • at least one reliability characteristic of the energy on-board network 25 is calculated for the further aspects 70 and thus for each operating mode and every possible cause of failure.
  • the further aspects 70 also determine a topology of the components 28, 30, 32 installed in the motor vehicle, which has an influence on the at least one reliability characteristic of the power system 25.
  • Values for the determined probabilities 66, 68 are compared in a comparison 74 with respective limit values 72, wherein a risk for a failure of the energy on-board network 25 is determined.
  • statements about imminent changes of components 28, 30, 32 are possible, which ideally can be carried out during a regular workshop visit. From the diagnostic module 38 76 states of the
  • Components 28, 30, 32 based on the diagnosis of the components 28, 30, 32, which have been transmitted via the input 60 checked. Based on this, a system diagnosis 78 is carried out, with which a plausibility check of the diagnoses of the components 28, 30, 32 and a recognition of undetected errors of these components 28, 30, 32 is possible.
  • the values of physical state variables of the components 28, 30, 32 and the optionally selected physical state variables in the energy on-board network 25 transmitted via the input 62 are used to carry out a system diagnosis 78 with which the states of the components 28, 30, 32 are recognized and unrecognized Error in the power cord 25 is possible. In addition, an identification of the faulty components 28, 30, 32 is possible.
  • a message 80 via a current actual state of the power plant network 25 is provided, this actual state is determined by superimposing the diagnosis of the components 28, 30, 32 and the system diagnosis 78 of the power plant network 25.
  • the monitoring unit 36 performs calculations 82.
  • loadability models 84 are stored for the components 28, 30, 32 and the power system 25 or can be supplied via an interface 56.
  • a first use 86 results for the system level 34 and thus for one level of the energy on-board network 25, which includes an influence on a load management to protect the components 28, 30, 32 by communication with the energy management 44.
  • a second benefit 88 is provided for the motor vehicle level 45 here.
  • a third benefit 90 is provided here for future developments. This includes an improvement of load-bearing models 84 due to a large number of components 28, 30, 32 and an improvement of the load-bearing models 84 due to known, real loads of the components 28, 30, 32.
  • the at least one component 28, 30, 32 which in this example is an energy source, for example the generator 10 (FIG. 1), an electrical memory, for example a battery 14, 20, the DC-DC converter 8 ( Figure 1), an energy Distributor or to a consumer 16, 18, 22 ( Figure 1), transmitted values of physical operating variables as parameters to the monitoring unit 36, from which a diagnosis of the at least one component 28, 30, 32 is derived as state analysis.
  • an energy source for example the generator 10 (FIG. 1)
  • an electrical memory for example a battery 14, 20
  • the DC-DC converter 8 Figure 1
  • an energy Distributor or to a consumer 16, 18, 22 Figure 1
  • a physical plausibility check of the diagnoses of the components 28, 30, 32 is carried out, which are also transmitted to the monitoring unit 36 and on the other hand predicts a reliability of the components 28, 30, 32 and the power plant network 25.
  • the operating variables determined in this case are of the operating modes that are possible in the motor vehicle, of causes of failure, of the topology of the power system 25 used, of an operating time of the
  • the monitoring unit 36 transmits a recommendation to the control unit 46, which states whether an automated driving function must be enabled or has to be prevented.
  • the monitoring unit 36 transmits parameters to the control unit 46, which include statements about the status of the components 28, 30, 32 and / or the entire power system 25 and or parts thereof depending on the operating mode.
  • parameters which indicate changes of components 28, 30, 32 or include a permissible release time of the various operating modes can be taken into account.
  • the monitoring unit 36 comprises two modules, namely the diagnostic module 38 and the prognosis module 40, wherein the monitoring unit 36 is subdivided into these modules.
  • the energy supply system 25 is checked with the diagnostic module 38 for the presence of errors.
  • the values of the operating variables are mutually plausible and evaluated for the execution of device-internal diagnoses and for providing messages about the current state.
  • information about a topology of the energy gate network 2, 25 including the components 28, 30, 32 and their configuration are taken into account.
  • a respective currently active operating mode of the motor vehicle and thus also of the power plant network 2, 25 is taken into account. It is possible, individual, z. B. currently active operating modes to monitor, in addition, it can also be checked whether other modes of operation in a current state work.
  • an operating mode is, for example, designed as a start-stop phase, as a normal drive 48, as a recuperation 50 or as a sailing operation 52 with the internal combustion engine switched off. From information about the respective operating mode, the state of the power system 2, 25 can be determined.
  • the sailing operation 52 is carried out with the engine switched off for the motor vehicle, provision is made in a first example for at least one battery 14, 20 (FIG. 1) to be discharged as component 28, 30, 32 within a certain limit, since the generator 12 ( Figure 1) as a further component 28,
  • the generator 12 reports a fault-free operation with medium utilization, wherein, however, an energy content of the first battery 14 (FIG. 1) continuously drops, which is, for example, a fault of the energy management 44, a controller of the generator 12 (FIG. 1) or the first battery 14 (FIG. 1) and / or a battery sensor of this battery 14.
  • the described with the second example error can not be recognized in the prior art today, since each of the above Components 28, 30, 34 on their own reports error-free operation.
  • a set of status messages which individually are alone in themselves, indicates an error and / or an aging.
  • a safety-relevant fault and / or a safety-relevant aging are detected by the monitoring unit 36, which violate a potential safety target, it is provided that a transition to an automated driving function and / or an operating mode, eg. B. the sailing operation 52 or the recuperation 50 is not released in an automated driving. If the motor vehicle is in a manual driving mode and is to be changed into the sailing mode 52, but the battery 14, 20 has too little energy to restart a motor, the motor vehicle may not change to the sailing mode 52.
  • Results of the diagnosis are thus used to block or release automatic driving functions, wherein a digital value, for example a zero or one, is transmitted to the control unit 46, which states whether a respective automated driving function is now locked or released.
  • a state variable which, for example, may have values between 0% and 100% and may have intermediate steps as defined.
  • control unit 46 requests from the monitoring unit 36 certain automated driving functions, for example a motorway pilot. Based on a history of previous values of physical operating variables, which is also based on models 84 determined the monitoring unit 36 loads the components 28, 30, 32, which are to be expected at the respective driving function. On the basis of this, a respective driving function can be released or prohibited if the expected load is too high. If a driving function causes a lower load, this can continue to be enabled and therefore released.
  • certain automated driving functions for example a motorway pilot.
  • a prognosis is also provided for a future state of at least one component 28, 30, 32 and / or the power system 25.
  • loading data is transmitted from the components 28, 30, 32 to the prognosis module 40.
  • load data and load capacity models of the components 28, 30, 32 are reliability characteristics, such. B. failure probabilities of the components 28, 30, 32 determined.
  • the loadability models are integrated in the forecasting module 40. Via the interface 56 it is also possible to implement load-bearing models of components from other manufacturers.
  • the prognosis module 40 calculates the probability that the energy supply of the safety-relevant components 28, 30, 32 could be limited and / or unavailable due to wear effects.
  • several causes of failure can be the reason for the insufficiently available energy supply. These are determined accordingly reliability. Examples of these failure causes are an overvoltage or an undervoltage on the safety-relevant components 28, 30, 32, which are taken into account in their own reliability models, since different reliability-related combinations lead to failure of the safety-relevant components 28, 30, 32. Consequently, a calculation of the probabilities depends on the topology of the power plant network 25, on the operating modes considered and the causes of the failure. To calculate this probability, for each operating mode, eg.
  • a reliability block diagram for example, a fault tree, a Markov model or the like deposited with currently calculated Failure rates of the components 28, 30, 32 is fed and calculated.
  • the reliability block diagram or a comparable one Methodology for modeling system reliability provides for the criticality of failure, aging, and / or wear of the components 28, 30, 32 of the entire power plant network 25.
  • the method is taken into account that their structure is not based on the electrical diagram of the energy on-board network 25, but on a combination of errors or aging, which lead due to the failure cause to a power supply with values for the voltage that is less than a predetermined minimum value or greater as a predetermined maximum value and lead outside of a predetermined voltage interval by the safety-relevant consumer.
  • the DC converter 8 (FIG. 1) to fail as component 28, 30, 32 of the power system 25, which is a critical state because of the failure of the DC converter 8 forcibly discharges the battery 20, resulting in an undervoltage in the second channel 6 as a cause of failure. This failure is taken into account by modeling a reliability.
  • the first battery 14 fails in the first channel 4 (FIG. 1). If, in addition, the sailing mode 52 is set as the driving function for the motor vehicle, in which the generator 12 (FIG. 1) is turned off and thus a smaller amount of electrical energy is generated, an undervoltage may result as the cause of the failure. This is also taken into account in the reliability block diagram.
  • the determined conditional probabilities 74 are compared with limit values 72. In this case, a safety-critical driving function is only released by the systemic diagnosis of the actual state of the power system 25, if the actual state of the power system 25 is in order.
  • conditional probability can be determined, which includes a probability of a safety-critical state of the energy on-board network 25 assuming a functional actual state.
  • the monitoring unit 36 notifies the control unit 46 which operating modes may be released when an automated driving function is performed and which are not, wherein an automated driving function can also be completely prevented and thus prevented.
  • the arrangement 24 is designed as a self-learning system, it is possible to adapt a respective operating strategy to a load behavior, whereby the components 28, 30, 32 can be optimally utilized.
  • the monitoring unit 36 may communicate with the central unit 54.
  • Component 28, 30, 32 is predicted to have a limited life, it is u. a. possible to replace the respective affected component 28, 30, 32 in a timely manner. It is also possible to predict the load taking into account a route profile based on navigation data.
  • the energy on-board network 25 shown schematically in detail in FIG. 4a likewise comprises a first channel 100 and a second channel 102, which are connected by a DC converter 101 as a possible component 28, 30, 32 (FIG. 2) of the energy on-board network 25.
  • the first channel 100 comprises as components 28, 30, 32 (FIG. 2) a generator 104 and a first battery 106.
  • the second channel 102 comprises as components 28, 30, 32 (FIG. 2) a second battery 108, a starter 110, a first safety-relevant consumer 112 and a second non-safety-relevant consumer 114.
  • FIG. 4 shows a first ground potential point 116, a second ground potential point 118, a third ground potential point 120, a fourth ground potential point 122, a fifth ground potential point 124 and a sixth ground potential point 126 of the power system 25.
  • Some of these components 28, 30, 32, 100, 101, 102, 104, 106, 108, 110, 112, 114, 116, 118, 120, 122, 124, 126 of the power system 25 are further shown in flowcharts 4b, 4c, 4d, the components 28, 30, 32, 100, 101, 102, 104, 106, 108, 110, 112, 114, 116, 118, 120, 122, 124, 126 are here logically connected in series and / or in parallel.
  • the normal drive 48, the recuperation 50 and the sail operation 52 can be carried out for the energy on-board network 25 and thus also for its component 28, 30, 32 (FIG. 2) as driving function and / or operating mode.
  • the generator 104 converts mechanical energy, which is produced when the motor of the motor vehicle is running, into electrical energy, which is provided to the two batteries 106, 108, and these are charged. In addition, energy is also provided to the safety-relevant consumer 112 and the non-safety-relevant consumer 114 in the normal drive 48. As shown in the flow chart of Figure 4b, electrical energy is from at least one ground potential point 116, 118, 120, from the generator 104 or the first battery 106, via the first channel 100, the DC converter 101, the second channel 102 to the safety relevant Consumers 112 and the mass potential point 124 transported.
  • the mechanical energy from a movement of the motor vehicle is converted by the generator 104 into electrical energy, which is also provided here to the two batteries 106, 108 and the safety-relevant consumer 112 and the non-safety-relevant consumer.
  • the flowchart from FIG. 4 c shows for this purpose that electrical energy is transported at least starting from the ground potential point 120, from the generator 104 via the first channel 100, the DC-DC converter 101, the second channel 102 to the safety-relevant load 112 and the ground potential point 124.
  • the method for state analysis and thus for the diagnosis of the current state and / or for the prognosis of the future state can be carried out for all components 28, 30, 32 of the energy on-board network 2, 25, which are designed to provide electrical energy.
  • this interval is defined by a minimum value and thus an upper limit and a maximum value and thus a lower limit. This applies in each case to an upper and a lower limit for a voltage and / or a current as a physical operating variable.
  • limits and / or non-safety-relevant consumers 114 can optionally be taken into account in the respective state analysis if required.
  • a diagnosis of at least one component 28, 30, 32 by a diagnosis of all components 28, 30, 32 and thus the entire power system 25 as a system plausibility, with previously unrecognized errors of individual components 28, 30, 32 can be recognized, since the components 28, 30, 32 are not diagnosed individually but across systems, with a mutual interaction of the components 28, 30, 32 can be considered.
  • the diagnostics at the component level 26 are made plausible by the system level 34 diagnostics.
  • a single faulty component 28, 30, 32 may possibly not be identified as faulty when performing an individual diagnosis, whereas an effect of this faulty component 28, 30, 32 on at least one further component 28, 30, 32 can be detected during cross-system diagnostics.
  • results of individual diagnoses wherein for each component 28, 30, 32 a diagnosis is performed individually on the component level 26, are summarized centrally in the monitoring unit 36.
  • the characteristic quantities of the components 28, 30, 32 are at least the at least one physical operating variable and possibly parameters, and at least the at least one physical operating variable of the entire power system 25 is determined and / or measured.
  • load-relevant parameters that are relevant for the operation u. a. load-relevant physical operating variables, recorded and stored and thus in a memory of the monitoring unit 36, which is designed to store data, recorded.
  • the recorded values are converted to a defined level of the load.
  • failure probabilities of the components 28, 30, 32 are determined. From this, a mode of operation mode and / or failure cause-dependent failure probability of the energy on-board network 25, for example, also taking into account a topology of the power system 25, are calculated, with the topology u. a.
  • the prognosis-formed state analysis at the component level 26 for individual components 28, 30, 32 can be made plausible by the prognosis of the entire energy on-board network 25 at the system level 34, as in the case of the state analysis designed as a diagnosis.
  • the recorded data are processed into the load-relevant parameters and recorded with load-relevant parameters, including load-relevant physical operating variables, and stored and thus in a memory of the monitoring unit 36, the Save data is formed, written.
  • These data are compared with loadability models of components 28, 30, 32, from which instantaneous reliability characteristics can be determined.
  • the reliability characteristics are determined by mapping the reliability structure of the operating modes as a function of relevant failure mechanisms. By extrapolating the previous load, a reliability prediction can be performed at the component level 26 and at the system level 34, which can be mutually plausible. From the previous load and the stored loadability model, a prognosis of the future condition can be carried out.
  • At least one condition analysis designed as a diagnosis ie. H. a system level 34 diagnosis and / or component level 26 diagnosis
  • at least one conditional analysis designed as a prognosis d. H. a prognosis on system level 34 and / or a prognosis on component level 26, plausibility and vice versa.
  • an automated driving function could be performed on the basis of the at least one diagnosis for the current actual state of the at least one component 28, 30, 32, this may be due to the at least one prognosis for the future state of the at least one component 28, 30, 32 are prevented, as in the at least one prognosis usually a larger number of values for operating variables is considered as in the case of at least one diagnosis.
  • the state analyzes for the diagnosis and the prognosis can be carried out online and / or during ongoing operation of the energy on-board network 2, 25 and of the motor vehicle.

Landscapes

  • Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Computer Hardware Design (AREA)
  • Microelectronics & Electronic Packaging (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Electric Propulsion And Braking For Vehicles (AREA)
  • Direct Current Feeding And Distribution (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)
  • Secondary Cells (AREA)

Abstract

L'invention concerne un procédé pour faire fonctionner un réseau de bord électrique (25) d'un véhicule à moteur, le réseau de bord électrique (25) comprenant plusieurs composants (28, 30, 32). Selon ce procédé, un diagnostic d'un état réel est effectué à partir de valeurs de caractéristiques de fonctionnement physiques de tous les composants (28, 30, 32) en tant qu'une première analyse d'état pour tous les composants (28, 30, 32) du réseau de bord électrique (25), et seulement un diagnostic d'un état réel est effectué à partir de valeurs de caractéristiques de fonctionnement physiques respectivement d'un composant (28, 30, 32) en tant qu'au moins une deuxième analyse d'état pour respectivement un composant (28, 30, 32), ladite au moins une deuxième analyse d'état pour respectivement un composant (28, 30, 32) étant validée par la première analyse d'état pour tous les composants (28, 30, 32).
PCT/EP2017/072539 2016-09-27 2017-09-08 Procédé permettant de faire fonctionner un réseau de bord électrique WO2018059906A1 (fr)

Priority Applications (3)

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CN201780059205.9A CN109789843A (zh) 2016-09-27 2017-09-08 用于运行车载能量网的方法
EP17764393.9A EP3519251A1 (fr) 2016-09-27 2017-09-08 Procédé permettant de faire fonctionner un réseau de bord électrique
JP2019516514A JP6768152B2 (ja) 2016-09-27 2017-09-08 車載電源システムを動作させる方法

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DE102016218567.5A DE102016218567A1 (de) 2016-09-27 2016-09-27 Verfahren zum Betreiben eines Energiebordnetzes
DE102016218567.5 2016-09-27

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DE102020212277A1 (de) 2020-09-29 2022-03-31 Robert Bosch Gesellschaft mit beschränkter Haftung Verfahren und Vorrichtung zum Bestimmen einer Restnutzungsdauer basierend auf einer prädiktiven Diagnose von Komponenten eines elektrischen Antriebssystems mithilfe Verfahren künstlicher Intelligenz
JPWO2023095342A1 (fr) * 2021-11-29 2023-06-01

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CN109789843A (zh) 2019-05-21
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DE102016218567A1 (de) 2018-03-29
EP3519251A1 (fr) 2019-08-07

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