Method and device for determining the wear rate of a vehicle computer

Abstract

The present invention relates to a method and device for determining the wear rate of a vehicle control unit (101). To this end, values ​​of a set of parameters representative of wear factors are measured for each electronic component of at least some of the electronic components included in the control unit (101). These values ​​are further stored in a memory (1010) associated with the control unit (101). The parameter set includes at least one parameter specific to each electronic component. A wear rate of the control unit (101) is predicted by feeding a wear rate prediction model with the set of parameter values. Figure 1 (for the abstract)

Description

Title of the invention: Method and device for determining the wear rate of a vehicle computer Technical field

[0001] The present invention relates to methods and devices for determining a wear rate of one or more vehicle computers, for example of a motor vehicle. The invention also relates to a method and device for predictive maintenance of a vehicle. The invention also relates to a method and device for identifying components to be replaced in a vehicle as a function of the determined wear rate. The invention also relates to a method and device for qualifying the condition of the components of a vehicle as a function of the determined wear rate. The invention also relates to a method and device for detecting a design and / or manufacturing defect in a vehicle component from feedback on the wear rates determined for this component. The invention also relates to a method and device for modeling a vehicle component as a function of wear rates determined for components of the same type. Technological background

[0002] Contemporary vehicles are made up of a large number of calculators or ECUs (from the English "Electronic Control Unit" or in French "Unité de contrôle électronique") each made up of a set of electronic components. Each of these electronic components is susceptible to failure or defect, depending in particular on the conditions of use of the calculators.

[0003] When the driver of a vehicle is faced with a fault or breakdown in a computer in his vehicle, the latter must then contact a specialized center to determine whether the fault or breakdown observed requires corrective maintenance to correct the fault or breakdown after its occurrence. Such corrective maintenance is most often accompanied by an intervention or repair in a garage, for example. Such corrective maintenance is synonymous with costs incurred by the corrective maintenance and inconvenience caused by the immobilization of the vehicle for a period sometimes lasting up to several days or even several weeks.

[0004] Furthermore, when the computer failure is associated with a defective electronic component of the computer, the maintenance operation sometimes consists of a simple replacement of the defective electronic component without taking into consideration the state of the other electronic components of the computer. However, replacing the defective electronic component does not prevent the occurrence of a fault. at the level of another electronic component of the computer, which can be particularly inconvenient for the driver who may then have to deal with repeated breakdowns or faults in the electronic systems on board the vehicle. Summary of the present invention

[0005] An object of the present invention is to solve at least one of the problems of the technological background described above.

[0006] Another object of the present invention is to improve the prediction of breakdowns or faults in a vehicle's computer(s).

[0007] According to a first aspect, the present invention relates to a method for determining a wear rate of a vehicle computer, the computer comprising a plurality of electronic components, the method comprising the following steps: - for each electronic component of at least part of the plurality of electronic components, measurement of values ​​of a set of parameters representative of wear factors and recording in a memory associated with the calculator of the set of parameter values, the set of parameters comprising at least one parameter which is a function of each electronic component; - prediction of the wear rate of the calculator by feeding a wear rate prediction model with the set of parameter values, the wear rate prediction model having been learned in a learning phase according to determined usage constraints of the calculator

[0008] The use of values ​​measured and recorded in the memory of the computer, which values ​​correspond to wear factor parameters specific to each electronic component making up the computer, makes it possible to determine a wear rate of the computer via a model taking into consideration constraints of use of the computer, for example defined during the design of the computer. This makes it possible to determine the state of the computer according to its actual use in the vehicle, via the measurements of the parameters specific to each electronic component, according to objectives set for example at the design (for example the service life).

[0009] Thus, when an electronic component of the computer is detected as being defective, knowing the wear rate of the computer makes it possible to determine whether replacement of the defective electronic component is sufficient (for example if the wear rate of the computer suggests a sufficiently long remaining operating time) or whether replacement of the entire computer is necessary (for example if the wear rate of the computer is high).

[0010] Furthermore, predicting the wear rate of a computer based on measured wear factors of each of its electronic components makes it possible to plan preventive maintenance operations before a failure of the computer. does not appear, which avoids unexpected immobilization of the vehicle for example.

[0011] According to a variant, the method further comprises a step of receiving first data representative of a distance traveled by the vehicle since the vehicle was put into circulation and second data representative of an operating time of the computer, the prediction of the wear rate of the computer furthermore being a function of the first and second data by further feeding the wear rate prediction model with the first and second data.

[0012] According to another variant, the method further comprises the steps of: - generation, by the wear rate prediction model, of at least one fault code representative of a wear rate of at least one electronic component of the plurality; - display control of at least one graphic object representative of at least one fault code for display of at least one graphic object on a display device of the vehicle.

[0013] According to another variant, the at least one parameter corresponds to: - a tension; and / or - a power; and / or - a current intensity; and / or - a temperature; and / or - a cycle counter.

[0014] According to an additional variant, the wear rate prediction model is learned based on a set of intrinsic failure modes of each electronic component of the plurality.

[0015] According to another variant, the wear rate prediction model is implemented via an artificial intelligence system and / or a neural network.

[0016] According to a second aspect, the present invention relates to a device for determining a wear rate of a vehicle computer, the device comprising a memory associated with a processor configured for implementing the steps of the method according to the first aspect of the present invention.

[0017] According to a third aspect, the present invention relates to a vehicle, for example of the automobile type, comprising a device as described above according to the second aspect of the present invention.

[0018] According to a fourth aspect, the present invention relates to a computer program which comprises instructions adapted for executing the steps of the method according to the first aspect of the present invention, in particular when the computer program is executed by at least one processor.

[0019] Such a computer program may use any programming language, and be in the form of source code, object code, or intermediate code between source code and object code, such as in a partially compiled, or in any other desirable form.

[0020] According to a fifth aspect, the present invention relates to a computer-readable recording medium on which is recorded a computer program comprising instructions for carrying out the steps of the method according to the first aspect of the present invention.

[0021] On the one hand, the recording medium may be any entity or device capable of storing the program. For example, the medium may comprise a storage means, such as a ROM memory, a CD-ROM or a microelectronic circuit type ROM memory, or a magnetic recording means or a hard disk.

[0022] Furthermore, this recording medium may also be a transmissible medium such as an electrical or optical signal, such a signal being able to be conveyed via an electrical or optical cable, by conventional or hertzian radio or by self-directed laser beam or by other means. The computer program according to the present invention may in particular be downloaded from an Internet-type network.

[0023] Alternatively, the recording medium may be an integrated circuit in which the computer program is incorporated, the integrated circuit being adapted to perform or to be used in performing the method in question. Brief description of the figures

[0024] Other characteristics and advantages of the present invention will emerge from the description of the particular and non-limiting exemplary embodiments of the present invention below, with reference to the appended figures 1 to 3, in which:

[0025] [Fig-1] schematically illustrates a vehicle, according to an exemplary embodiment by particular of the present invention;

[0026] [Fig.2] illustrates a device configured to determine a wear rate of one or several calculators of the vehicle of [Fig.l], according to a particular and non-limiting exemplary embodiment of the present invention.

[0027] [Fig.3] illustrates a flowchart of the different stages of a determination process mination of a wear rate of one or more computers of the vehicle of [Fig.l], according to a particular and non-limiting exemplary embodiment of the present invention. Description of the exemplary embodiments

[0028] A method and a device for determining a wear rate of a vehicle computer will now be described in what follows with joint reference to Figures 1 to 3. The same elements are identified with the same reference signs throughout the description which follows.

[0029] The terms “first(s)”, “second(s)” (or “first(s)”, “second(s)”), etc. are used in this document by arbitrary convention to allow identification and to distinguish different elements (such as operations, means, etc.) implemented in the embodiments described below. Such elements may be distinct or correspond to a single element, depending on the embodiment.

[0030] According to a particular and non-limiting example of embodiment of the present invention, the determination of a wear rate of a computer of a vehicle comprising a plurality of electronic components is for example implemented by a computer of the vehicle or by a data processing device connected in communication to the vehicle. For this purpose, the method comprises the measurement of values ​​of a set of parameters each representative of a wear factor for each electronic component of at least a portion of the electronic components forming the computer. The parameters (or associated wear factors) monitored or measured are advantageously a function of each electronic component, that is to say that the monitored parameters can vary from one electronic component to another, at least for a portion of the electronic components for which the parameters or wear factors are monitored.The measured values ​​for this or these parameters are recorded in a memory associated with the calculator, for example an internal memory of the calculator.

[0031] The values ​​of this or these parameters recorded in memory are used to feed a wear rate prediction model to determine the wear rate of the computer. The parameters of such a model have been previously learned, for example during the design of the computer from data representative of the failure modes associated with each electronic component or each type of electronic component.

[0032] [Fig. 1] schematically illustrates a vehicle 10, according to a particular and non-limiting example of implementation of the present invention.

[0033] [Fig.l] illustrates a vehicle 10, for example a motor vehicle, carrying one or more computers 101.

[0034] The vehicle 10 corresponds for example to a vehicle with a thermal engine, with electric motor(s) or even a hybrid vehicle with a thermal engine and one or more electric motors. The vehicle 10 thus corresponds for example to a land vehicle, for example an automobile, a truck, a bus, a motorcycle.

[0035] For reasons of clarity, a single computer 101 is shown in [Fig. 1]. Of course, the present invention is not limited to such an example but relates to a vehicle carrying a plurality of computers, the operations and steps of the different processes or methods implemented in relation to the computer 101 applying in a similar or identical manner to all or part of the computers carried in the vehicle 10.

[0036] The calculator 101 corresponds for example to a set of calculators (or ECUs) forming the on-board system of the first vehicle 10. Such a set of computers forms for example a multiplexed architecture for the realization of different services or functions useful for the proper functioning of the vehicle 10 and to assist the driver of the vehicle 10 in the control of the vehicle 10 and / or to establish a diagnosis on the operation of one or more computers of the vehicle 10. The computers are in particular configured to communicate and exchange data between them via one or more computer buses, for example a communication bus of the CAN data bus type (from the English "Controller Area Network" or in French "Network of controllers"), CAN FD (from the English "Controller Area Network Flexible Data-Rate" or in French "Network of controllers with flexible data rate"), FlexRay (according to the ISO 17458 standard) or Ethernet (according to the ISO / IEC 802-3 standard).According to an alternative embodiment, the computers are configured to communicate and exchange data between them using a wireless communication mode, for example using a wireless connection of the Bluetooth® or Wifi® type for example.

[0037] The computer 101 is formed or comprises a set of electronic components, the type and number of electronic components depending for example on the type of computer and the functions provided by the computer.

[0038] The electronic components forming a calculator correspond for example to one or more of the following components, the list below being provided as an example and not being exhaustive: - one or more processors or microcontrollers; and / or - one or more resistors; and / or - one or more capacitors; and / or - one or more diodes; and / or - one or more transistors, for example of the MOSFET, FET or bipolar type; and / or - one or more memories 1010; and / or - one or more electronic relays; and / or - one or more induction coils.

[0039] A process for determining a wear rate of a computer, for example the computer 101, of the vehicle 10 is advantageously implemented by the vehicle 10, for example by the computer 101 or by a combination of computers of the on-board system of the vehicle 10.

[0040] According to an alternative embodiment, the process is implemented by a system comprising the vehicle 10 and a data processing device 11 such as a computer, a tablet, a diagnostic device. In such a system, the vehicle 10 and the data processing device are connected by wired or wireless communication, for example of the Bluetooth®, wifi® or 5G type.

[0041] In a phase prior to the implementation of the process of determining the wear rate as such, a wear rate prediction model is determined, generated or learned.

[0042] The preliminary phase corresponds for example to a design phase of the computer according to a specification or specifications listing a set of determined usage constraints of the computer 101 (for example including the functions that the computer must provide, the manufacturing and design cost constraints, the usage constraints of the computer (for example environmental constraints (temperatures, humidity, etc.), the minimum lifetime of the computer, a minimum performance level as a function of time, etc.).

[0043] The prediction model is thus learned as a function of determined usage constraints of the computer during a so-called learning phase, corresponding for example to the design phase of the computer 101.

[0044] The prediction model comprises, for example, a set of parametric rules making it possible to determine the wear rate of the computer based on data or parameter values ​​provided as input to the model.

[0045] According to a variant, the prediction model is implemented in the form of an artificial intelligence system, for example by a neural network, such a prediction model being defined by the parameters of the neural network establishing in particular the links between the neurons of the network. Such a prediction model implements for example one or more operations of classification of the data or parameter values ​​provided as input to the model to determine a wear rate (corresponding for example to the wear rate associated with the most probable class obtained as a result of the classification(s)).

[0046] The generation or learning of the prediction model is for example implemented by the data processing device 11, the parameters of the prediction model then generated or learned being recorded in memory 1010 of the computer 101 so that this prediction model can be implemented or executed by one or more processors of the computer 101, if applicable.

[0047] The model for predicting the wear rate of the computer 101 is generated or learned by taking into account the electronic components forming this computer 101, or at least part of these electronic components.

[0048] The prediction model is advantageously generated by considering the intrinsic failure modes of each of the electronic components forming the computer, or at least of each electronic component of a part of the electronic components forming the computer 101. The failure modes of the electronic components are for example obtained from a reference document 12 such as the normative document referenced IEC 61709:2017. This document describes, by type of technology, the failure modes by type of electronic component and technology with indication of failure mechanisms by type of electronic component.

[0049] A failure mode corresponds to an observable form of malfunction of an electronic component and belongs to a set of determined modes including, for example, loss of function, untimely operation, impossible start-up, impossible stop-down and degraded operation. The failure modes may vary from one electronic component to another depending on the type of electronic component. A failure criticality index or indicator is, for example, associated with each failure mode.

[0050] This document IEC 61709:2017 describes in particular the parameters associated with the wear factors (or lifetime factors) to be taken into account to determine the wear rate of each electronic component during the life of each electronic component.

[0051] For example, a wear factor of a Mosfet type power transistor corresponds to the number of cycles, the lifetime of such a transistor being associated with a maximum number of cycles (for example 500000 or 750000 cycles). It is thus possible to determine a wear rate of the transistor as a function of the number of cycles performed, a determined wear rate being associated with the maximum number of cycles (for example a wear rate of 0.8 or 0.9 or 1 is associated with the maximum number of cycles).

[0052] According to another example, for a light-emitting diode, a parameter representative of a wear factor corresponds to the temperature of the diode and another parameter representative of another wear factor corresponds to the current measured in the diode. The wear rate of a diode is thus, for example, determined by a law or rule having the temperature and the current as parameters.

[0053] According to yet another example, for a capacitor, the parameters to be considered to determine a wear rate are the temperature, the applied voltage and the ripple current (i.e. the variations in intensity over a portion of a direct current). The wear rate of a capacitor is thus, for example, determined by a law or rule having as parameters the temperature, the voltage and the ripple current.

[0054] Table 1 below provides by way of example one or more wear factor parameters associated with each electronic component of a non-exhaustive set of electronic components.

[0055] [Tableauxl] Electronic component type Wear factor parameters Resistor Voltage (in V) and power (in W) Capacitor Voltage (in V) Connector Current (in A) Fuse Current (in A) Inductor Current (in A) and hotspot temperature (in °C) Transformer Voltage (in V), current (in A) and hotspot temperature (in °C) Diode Reverse voltage (in V) and junction temperature (in °C) Optocoupler Vce voltage (in V), reverse voltage (in V) and junction temperature (in °C) Bipolar transistor Junction temperature (in °C), Vce voltage (in V) and Vbe voltage (in V) FET transistor Junction temperature (in °C), Vgs voltage (in V) and Vds voltage (in V)

[0056] Once the wear rate prediction model is generated or learned, the wear rate prediction model is ready for use in a production phase or mode, for example in the vehicle 10 or in the data processing device 11.

[0057] In a first operation of the process, the computer 101 measures, via one or more sensors associated or integrated with the computer 101, for each electronic component forming the computer 101 or for each electronic component of a part of the electronic components forming the computer, one or more values ​​for each of the parameters representative of the risk factor(s) identified for each electronic component during the generation of the wear rate prediction model.

[0058] According to an alternative embodiment, when a group of several components of the computer 101 has one or more common risk factor parameters (for example the temperature for a microcontroller, a diode, an integrated circuit), then the computer 101 measures this parameter for the entire group of components rather than measuring this parameter individually for each component.

[0059] The measured values ​​are advantageously recorded in an associated memory to the computer (i.e. a memory connected in communication to the computer 101), for example the internal memory 1010 of the computer 101.

[0060] Depending on the type of parameter / wear factor measured (or monitored), the history of measured values ​​is kept in memory or each new measured value overwrites the previous measured value.

[0061] For example, if the measured parameter / wear factor corresponds to a number of cycles performed, the value stored in memory corresponds to an integer corresponding to an increment (the increment being increased by the value 1 for each new cycle detected).

[0062] If the measured parameter / wear factor corresponds to a current (an intensity in A), a history of the different measured intensities is for example stored in memory. According to an alternative embodiment, the intensity of the measured current is compared to a threshold and the value associated with this parameter corresponds to the number of times the measured intensity has exceeded the threshold (the increment being increased by the value 1 each time the threshold is exceeded).

[0063] When the measured parameter / wear factor corresponds to a parameter common to a group of components, the history of the measurements carried out for this group of components is stored in memory for all the components of the group of components.

[0064] For each electronic component, a set of one or more specific parameters is monitored or measured in accordance with the parameter(s) identified during the generation or training of the wear rate prediction model, the different values ​​obtained during the monitoring or control of this or these parameters being stored in memory.

[0065] In a second operation of the process, a wear rate of the computer 101 is determined by the wear rate prediction model by providing as input to the prediction model the value(s) stored in memory for each of the wear factor parameters identified for each electronic component forming the computer 101 (or for each electronic component of a portion of the electronic components forming the computer 101).

[0066] When the prediction model is implemented or executed by the computer 101, the prediction of the wear rate is for example determined regularly, for example at regular intervals or at each occurrence of a determined event (for example at each start of the vehicle 10 during a diagnostic operation or each day, each week, each month).

[0067] When the prediction model is implemented or executed by the processing device 11 (for example during a diagnosis of the vehicle 10, during a revision or maintenance of the vehicle in a garage or car dealership or during of a remote diagnosis according to a remote connection of the OTA type (from the English "Over The Air" or in French "by air"), the processing device 11 is connected to the vehicle 10 (for example via a wired or wireless connection via ad hoc communication interfaces of the vehicle 10 and the device 11) so that the device 11 recovers the values ​​of the different parameters stored in the memory of the vehicle 10, for example in the memory 1010. The device 11 then determines the wear rate of the vehicle 10 by feeding the wear rate prediction model with the latest values ​​stored in the memory of the vehicle 10. The wear rate then determined is representative of the wear rate at the time instant of recovery of the data representative of the values ​​stored in the memory 1010.

[0068] According to a particular variant embodiment, the distance traveled by the vehicle 10 and / or the operating time of the computer 101 are further taken into account by the prediction model to determine the wear rate of the computer 101.

[0069] According to this embodiment variant, the prediction model has been learned as a function of these additional parameters with, for example, the objective of ensuring operation without guaranteed critical failure mode for a determined mileage of the vehicle 10 and / or a determined duration of use (for example defined in operating hours).

[0070] According to this variant, first data representative of the distance (in km) traveled by the vehicle since its first entry into circulation are for example received by the computer 101 (or by the data processing device 11) from a memory associated with the computer controlling the odometer of the vehicle 10. Second data representative of the operating time of the computer 101 are for example recorded in the memory 101. These second data are for example representative of the number of operating cycles of the computer 101, an operating cycle being defined by a pair of events corresponding to the powering up (ON) followed by a powering down (OFF) of the computer 101. According to another example, the second data are representative of the cumulative duration (in hours, minutes and / or seconds) measured between each powering up (ON) and powering down (OFF) of the computer 10.

[0071] According to this variant, the distance parameter and / or the operating time parameter are taken into account to determine the wear rate of the computer 101, in addition to the parameters representative of the wear factors specific to each electronic component.

[0072] According to a particular embodiment, the wear rate prediction model is further determined or learned to generate a set of fault codes according to the wear rate of each electronic component determined according to the wear factor parameter(s) controlled for each electronic component.

[0073] According to one variant, the fault codes are associated with different operating states or wear rates determined for the computer 101 by the prediction model.

[0074] According to this embodiment, when a fault code is generated by the prediction model, the process comprises a display control of a graphical object representative of the determined fault code.

[0075] The control of the display of the graphic object is for example implemented by another computer of the vehicle 10 connected to the computer 101, for example the IVI computer (from the English “In-Vehicle Infotainment” or in French “Infodivertissement embargo”), the display control comprising the display of the graphic object (corresponding for example to a warning light or an icon) on a screen of the vehicle 10 (for example the dashboard of the vehicle 10).

[0076] The display of such a graphic object makes it possible to alert the driver of the vehicle 10 of a failure or a probable future failure of the computer 101 (or of one or more of its electronic components).

[0077] The wear rates determined for a component or group of components are for example used to assess the need to replace or not the component or group of components, for example during a preventive maintenance operation of the vehicle.

[0078] The wear rate determined for a component or a group of components also makes it possible to qualify the condition of the component or group of components.

[0079] A design and / or manufacturing defect of a component or group of components is furthermore, for example, identified from the wear rates determined on a set of vehicles carrying this type of component or group of components. Monitoring the wear rates makes it possible to assess whether the wear of a component throughout its life cycle complies with the specifications of its design / manufacture.

[0080] The wear rates determined for a set of components are, for example, further used in mission profile calculations for the design, sizing and development of new components, which makes it possible to benefit from field feedback from the components on board vehicles in circulation under real conditions.

[0081] [Fig. 2] schematically illustrates a device 2 configured to determine the wear rate of a vehicle computer, for example the computer 101 of the vehicle 10, according to a particular and non-limiting exemplary embodiment of the present invention. The device 2 corresponds for example to a device on board the vehicle 10, for example a computer. According to a variant, the device 2 corresponds to the data processing device 11.

[0082] The device 2 is for example configured for the implementation of the operations described with respect to [Fig.l] and / or the steps of the method described with respect to [Fig.3]. Examples of such a device 2 include, but are not limited to, on-board electronic equipment such as an on-board computer of a vehicle, an electronic calculator such as an ECU (“Electronic Control Unit”), a smartphone, a tablet, a laptop, a server. The elements of the device 2, individually or in combination, may be integrated into a single integrated circuit, into several integrated circuits, and / or into discrete components. The device 2 may be implemented in the form of electronic circuits or software (or computer) modules or even a combination of electronic circuits and software modules.

[0083] The device 2 comprises one (or more) processor(s) 20 configured to execute instructions for carrying out the steps of the method and / or for executing the instructions of the software(s) embedded in the device 2. The processor 20 may include integrated memory, an input / output interface, and various circuits known to those skilled in the art. The device 2 further comprises at least one memory 21 corresponding for example to a volatile and / or non-volatile memory and / or comprises a memory storage device which may comprise volatile and / or non-volatile memory, such as EEPROM, ROM, PROM, RAM, DRAM, SRAM, flash, magnetic or optical disk.

[0084] The computer code of the embedded software(s) comprising the instructions to be loaded and executed by the processor is for example stored in the memory 21.

[0085] According to various particular and non-limiting embodiments, the device 2 is coupled in communication with other similar devices or systems and / or with communication devices, for example a TCU (from the English “Telematic Control Unit” or in French “Telematic Control Unit”), for example via a communication bus or through dedicated input / output ports.

[0086] According to a particular and non-limiting exemplary embodiment, the device 2 comprises a block 22 of interface elements for communicating with external devices. The interface elements of the block 22 comprise one or more of the following interfaces: - RF radio frequency interface, for example Wi-Fi® type (according to IEEE 802.11), for example in the 2.4 or 5 GHz frequency bands, or Bluetooth® type (according to IEEE 802.15.1), in the 2.4 GHz frequency band, or Sigfox type using UBN (Ultra Narrow Band) radio technology, or LoRa in the 868 MHz frequency band, LTE (LTE) "Long-Term Evolution", LTE-Advanced or 5G, for example in the 700 GHz frequency band MHz, at 800 MHz, at 900 MHz, at 1.5 GHz, at 1.8 GHz, at 1.9 GHz, at 1.9 - 2.1 GHz, at 2.6 GHz, at 3.5 GHz or at 26 GHz; - USB interface (from the English “Universal Serial Bus” or “Universal Serial Bus” in French); - HDMI interface (from the English “High Definition Multimedia Interface” or “High Definition Multimedia Interface” in French); - LIN interface (from the English “Local Interconnect Network”).

[0087] According to another particular and non-limiting embodiment, the device 2 comprises a communication interface 23 which makes it possible to establish communication with other devices (such as other computers of the on-board system) via a communication channel 230. The communication interface 23 corresponds for example to a transmitter configured to transmit and receive information and / or data via the communication channel 230. The communication interface 23 corresponds for example to a wired network of the CAN (Controller Area Network) type, CAN FD (Controller Area Network Flexible Data-Rate) type, FlexRay (standardized by the ISO 17458 standard) or Ethernet (standardized by the ISO / IEC 802-3 standard), or to a wireless network of the Bluetooth® or wifi® type for example.

[0088] According to a particular and non-limiting exemplary embodiment, the device 2 can provide output signals to one or more external devices, such as a display screen 240, touch-sensitive or not, one or more speakers 250 and / or other peripherals 260 (projection system) via output interfaces 24, 25 and 26 respectively. According to a variant, one or other of the external devices is integrated into the device 2.

[0089] [Fig. 3] illustrates a flowchart of the different steps of a method for determining a wear rate of a vehicle computer, for example the computer 101 of the vehicle 10, according to a particular and non-limiting exemplary embodiment of the present invention. The method is for example implemented by a device on board the vehicle 10 or by the device 2 of [Fig. 2].

[0090] In a first step 31, values ​​of a set of parameters representative of wear factors are measured for each electronic component of at least part of the plurality of electronic components included in the computer, these values ​​being further recorded in a memory associated with the computer, the set of parameters comprising at least one parameter which is a function of each electronic component.

[0091] In a second step 32, a wear rate of the calculator is predicted by supplying a wear rate prediction model with the set of parameter values, the wear rate prediction model having been learned in a learning phase according to determined usage constraints of the calculator.

[0092] According to a variant, the variants and examples of the operations described in relation to [Fig.l] apply to the steps of the method of [Fig.3].

[0093] Of course, the present invention is not limited to the exemplary embodiments described above but extends to a method for controlling the operation of a vehicle computer which would include secondary steps without thereby departing from the scope of the present invention. The same would apply to a device configured for implementing such a method.

[0094] The present invention also relates to a vehicle, for example an automobile or more generally an autonomous land-based motor vehicle, comprising the device 2 of [Fig.2].

Claims

Claims

1. Method for determining a wear rate of a computer (101) of a vehicle (10), said computer (101) comprising a plurality of electronic components, said method comprising the following steps: - for each electronic component of at least a portion of said plurality of electronic components, measuring (31) values ​​of a set of parameters representative of wear factors and recording in a memory (1010) associated with said computer (101) said set of parameter values, said set of parameters comprising at least one parameter depending on said each electronic component; - predicting the wear rate of said computer (101) by feeding a wear rate prediction model with said set of parameter values, said wear rate prediction model having been learned in a learning phase as a function of determined usage constraints of said computer (101).

2. Method according to claim 1, further comprising a step of receiving first data representative of a distance traveled by said vehicle (10) since said vehicle was put into circulation and second data representative of an operating time of said computer, the prediction of the wear rate of said computer (101) being furthermore a function of said first and second data by further feeding the wear rate prediction model with said first and second data.

3. Method according to claim 1 or 2, further comprising the steps of: - generating, by said wear rate prediction model, at least one fault code representative of a wear rate of at least one electronic component of said plurality; - controlling the display of at least one graphical object representative of said at least one fault code for display of said at least one graphical object on a display device of said vehicle (10).

4. Method according to one of claims 1 to 3, for which said at least one parameter corresponds to: - a voltage; and / or - a power; and / or - a current intensity; and / or - a temperature; and / or - a cycle counter.

5. A method according to any one of claims 1 to 4, wherein said wear rate prediction model is learned based on a set of intrinsic failure modes of each electronic component of said plurality.

6. Method according to one of claims 1 to 5, for which said wear rate prediction model is implemented via a neural network.

7. Computer program comprising instructions for implementing the method according to any one of the preceding claims, when these instructions are executed by a processor.

8. A computer-readable recording medium on which is recorded a computer program comprising instructions for carrying out the steps of the method according to one of claims 1 to 6.

9. Device (2) for determining a wear rate of a vehicle computer (10), said device (2) comprising a memory (21) associated with at least one processor (20) configured for implementing the steps of the method according to any one of claims 1 to 6.

10. Vehicle (10) comprising the device (2) according to claim 9.

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