Storing battery impact information in a distributed registry

Abstract

The invention relates to a data processing method, comprising receiving (200) information relating to at least one electric battery, said information comprising at least one battery identifier and at least one impact information representative of an environmental impact associated with the identified battery. The method further comprises determining (201) at least one data point derived from the received information and storing (202) said at least one data point derived in a distributed ledger. FIG. 2

Description

Title of the invention: Storing battery impact information in a distributed ledger

[0001] The present invention belongs to the field of information management, in particular to the creation and provision of information concerning the environmental impact of batteries for electric motor vehicles. The invention applies in particular to the certification of the environmental impact of batteries for motor vehicles, in particular for land vehicles with electric motors such as cars.

[0002] It is known that products marketed in certain territories are subject to compliance with standards, particularly from the point of view of their environmental impact. Historically, consumers have been informed about compliance with these standards by means of certificates which took the form of labels affixed to the products. This is particularly the case for household appliances marketed in the European Union, which are now classified according to several energy classes ranging from A to G, on which energy labels are affixed which inform consumers in a simple and intuitive manner about the electricity consumption of these products.On the other hand, when it comes to motor vehicles and their components, the only information that is generally provided to consumers concerns their CO2 emissions, but it is generally not possible to easily access other information relating to their environmental impact.

[0003] Concerning batteries for electric vehicles, we observe in particular a lack of traceability of the type of energy used in the factories, concerning the method of extraction of the metals making up the battery and their refining as well as concerning the assembly of the electric battery.

[0004] Such monitoring should preferably be enabled throughout the battery life cycle, in particular to enable decisions to be made regarding the revaluation of used batteries which can be recycled or preferably reconditioned.

[0005] In addition, equipment manufacturers, suppliers of the equipment manufacturer, authorities or certification bodies may also wish to have access to such information on electric vehicle batteries, in a manner that ensures its authenticity.

[0006] There is thus a need to enable the collection and provision of information relating to batteries for motor vehicles, in particular information relating to the environmental impact of such batteries.

[0007] The present invention improves the situation.

[0008] To this end, a first aspect of the invention relates to a data processing method, comprising the following steps: - receiving information relating to at least one battery for an electric vehicle, said information comprising at least one battery identifier and at least one piece of impact information representative of an environmental impact associated with the identified battery; - determination of at least one data item derived from the information received; - storage of said at least one derived data in a distributed register.

[0009] Storing impact information relating to batteries in a distributed ledger enables the provision of reliable information on the environmental impact of electric batteries. The invention thus improves the ease of access and authentication of information made available concerning the environmental impact of batteries for electric vehicles.

[0010] According to embodiments, the distributed ledger may be a blockchain distributed ledger.

[0011] Such a distributed ledger ensures data authenticity, prevents any subsequent modification of the data and allows the addition of each derived data to be precisely dated, which makes it possible to collect information relating to batteries throughout their life cycle.

[0012] According to embodiments, said at least one data item derived from the received information may comprise: - battery information; - some of the battery information, including at least the battery identifier and at least one impact information; - a certificate including information relating to the battery; and / or - derived data obtained by transforming at least some of the information relating to the battery.

[0013] Thus, the method makes it possible to filter or process information relating to batteries before their storage, in the form of derived data, in the distributed register, in particular by a device responsible for this storage, which reinforces the relevance of the stored data.

[0014] According to embodiments, the method may further comprise: - receiving a request, the request identifying a battery or set of batteries, from a user terminal; - obtaining data derived from information relating to the identified battery or set of batteries, stored in the distributed ledger; - making the derived data obtained available to the user terminal.

[0015] It is thus possible to make the data stored in the register available distributed to third parties, which allows for great transparency in information on the environmental impact of batteries.

[0016] According to embodiments, the method may further comprise collecting a data set derived from information relating to a battery or set of batteries and stored in the distributed ledger, and determining a summary relating to said battery or set of batteries based on the collected derived data set.

[0017] Thus, the method according to the invention makes it possible to collect impact information and store it in the distributed register, making it possible to feed analyses / summaries of the environmental impacts of batteries, and thus better decision-making, in the choice of batteries in particular.

[0018] According to embodiments, the method may further comprise collecting a dataset derived from information relating to a battery or a set of batteries and stored in the distributed ledger, and determining a model from the collected derived dataset, the model being capable of predicting output data from input data.

[0019] Thus, the derived data which are stored in the distributed register allow the construction of predictive models which in particular make it possible to facilitate choices on the type of battery, on the technical characteristics of a battery, or on the method of revalorizing a battery.

[0020] Additionally, the model can be determined by machine learning from the collected derived data set.

[0021] Thus, the reliability of the model is improved, and is all the more important as the derived data collected are numerous and varied.

[0022] In addition or as a variant, the method may further comprise the following steps: - receiving a request from a user terminal, the request including input data from the model; - applying the model to the query input data to obtain output data; - transmitting a response to the user terminal, the response including the output data.

[0023] Thus, the model can be made available to third-party user terminals.

[0024] A second aspect of the invention relates to a computer program comprising instructions for implementing the method according to the first aspect of the invention, when these instructions are executed by a processor.

[0025] A third aspect of the invention relates to a device comprising: - an interface capable of receiving information relating to at least one battery for electric vehicle, said information comprising at least one battery identifier and at least one impact information representative of an environmental impact associated with the identified battery; - a processor capable of determining at least one piece of data derived from the information received and capable of storing said at least one piece of derived data in a distributed register.

[0026] Other characteristics and advantages of the invention will appear on examining the detailed description below, and the appended drawings in which:

[0027] [Fig-1] illustrates a system according to embodiments of the invention;

[0028] [Fig.2] is a diagram illustrating the steps of a data processing method according to embodiments of the invention;

[0029] [Fig.3] illustrates the structure of a device according to embodiments of the invention.

[0030] [Fig.l] illustrates a system 10 for collecting and making available information relating to at least one battery for an electric vehicle, according to embodiments of the invention.

[0031] The system comprises a device 100 according to the invention, capable of accessing a network 110, by which the device 100 can communicate with other entities accessing the network 110. The network 110 may in particular be an extended network of the IP type, for “Internet Protocol” in English.

[0032] No restriction is attached to the access point through which the device 100, as well as the other network entities shown in [Fig.l], accesses. For example, each entity can access the network via a wired access point, a Wi-Fi gateway, or an access point of a cellular network, such as a 3G, 4G, 5G, or any subsequent generation network.

[0033] The device 100 is a device for constituting and making available information concerning the environmental impact of a motor vehicle within the meaning of the present invention, which advantageously interacts with a distributed register 120, such as a blockchain distributed register, and which implements a method for constituting and making available information concerning the environmental impact of a motor vehicle within the meaning of the present invention, as described below.

[0034] The device 100 according to the invention is a computing device such as a server. The device 100 may be hosted within a cloud computing infrastructure.

[0035] No restrictions are attached to the distributed ledger 120, whether to its structure, to a hash function on which it is based and / or to the rules for adding a new block to the distributed ledger. Such distributed ledgers are well known and are not described further in the present description. The ledger is distributed because it is simultaneously stored on a plurality of entities of the network 110, terminals or servers.

[0036] Distributed blockchain ledgers have the advantage of allowing the storage of information that is time-stamped, and whose modification after the fact is impossible, due to both the distributed nature of the storage, but also due to the hash key associated with the stored information. It is thus made possible to store data in a traceable and transparent manner, while ensuring the authenticity of the data. It therefore makes it possible to do away with a trusted third party.

[0037] The system 10 may comprise at least one entity capable of transmitting information relating to at least one battery to the device 100 via the network 110, the information relating to each battery comprising: - a battery identifier; and - at least one piece of impact information relating to the environmental impact of the identified battery.

[0038] No restrictions are attached to the impact information which may include one or more of the following information: - amount of green energy used for the manufacture of the battery. The amount may be a proportion of the total energy used for the manufacture of the battery; - amount of green energy used for battery recycling. The amount may be a proportion of the total energy used for battery recycling; - any information relating to the material(s) used in the manufacture of the battery, such as the name of the material, the extraction method, the place of extraction, etc. For example, the battery, including its cathode, may include any of the following materials: lithium, nickel and cobalt, which may be derived from mining stages followed by purification. More complex combinations involving rarer metals are sometimes used.

[0039] Green energy is understood to mean any energy from a renewable and / or decarbonized energy source.

[0040] Optionally, the information relating to said at least one battery further comprises the following additional information: - a battery manufacturing location; - a place for marketing the battery; - a battery type, the battery type being able to indicate the material(s) used in the battery; - a vehicle identifier and / or a vehicle type including the battery; - any other technical characteristics of the battery, such as its format, weight, storage capacity, etc.

[0041] The aforementioned battery information may be transmitted, for a same battery, at different times in the battery life cycle, and the device 100 is capable of storing, upon each reception of information relating to the battery, data derived from the information relating to the battery, in the distributed register 120. The data derived from the information relating to the battery may comprise: - the information relating to the battery itself; - some of the battery information, including at least the battery identifier and at least one impact information; - a certificate including information relating to the battery, in particular the battery identifier and at least one piece of impact information; and / or - data obtained by transforming at least some of the information relating to the battery (result of the application of a given function for example).

[0042] Data derived from information relating to batteries can thus be stored in the distributed ledger 120, throughout the respective life cycles of the electric vehicle batteries.

[0043] The entity capable of transmitting the information relating to a battery to the device 100 may be a terminal 130 of a battery manufacturing site, or of an electric vehicle assembly site, in which batteries are installed in respective electric vehicles.

[0044] Thus, an operator of the manufacturing or assembly site can transmit, via the terminal 130, information relating to a battery before it is placed on the market, the information being able to include the identifier of the battery, at least one piece of impact information such as the impact of the manufacturing of the battery or information on the material or materials used in the battery, or one or more of the aforementioned additional information.

[0045] A terminal 150 of a battery reclamation site may also be capable of transmitting information relating to at least one battery to the device 100. The reclamation site may be responsible for the reclamation of batteries, either by recycling or by reuse in a vehicle different from that in which the battery was previously installed.

[0046] An operator of the reclamation site can thus transmit, via the terminal 150, information relating to the battery which may include the identifier of the battery, at least one piece of impact information such as the environmental impact associated with the reclamation of the battery, and optionally one or more of the aforementioned additional information. The information relating to the battery can further indicate a reclamation strategy adopted, among recycling or reuse for example.

[0047] The system 10 may further comprise a user terminal 140 capable of accessing the device 100 via the network 110. The user terminal 140 may be a computer, a smartphone, a touchscreen tablet, or any terminal including means for displaying / visualizing data and browsing this data, such as a user interface allowing browsing of the data.

[0048] The navigation terminal 140 may in particular request access to data derived from information relating to at least one given battery, which are stored in the distributed register 120.

[0049] The request may in particular identify: - a given battery, indicated by a battery identifier. In this case, the device 100 accesses the data derived from the information relating to the given battery which is stored in the distributed register 120, and makes this data available on a graphical interface accessible to the navigation terminal 140; - a set of batteries, indicated either by a set of battery identifiers or by a given type of battery. In this case, the device 100 accesses the data derived from the information relating to the set of batteries indicated in the request, and makes this data available on a graphical interface accessible to the navigation terminal 140.

[0050] Alternatively, the request transmitted by the user terminal 140 may require access to an analysis determined by the device 100 from at least some of the derived data stored in the distributed ledger 120.

[0051] No restriction is attached to such an analysis which can be: - a synthesis obtained from data derived from information relating to a given battery; - a summary for a given drum set, obtained from data derived from information relating to the drums in the set.

[0052] As a further variant, the device may store at least one model capable of receiving input data and determining output data, the model being determined by the device 100 based on at least some of the derived data stored in the distributed ledger 120.

[0053] For example, the model may be a machine learning model, with the derived data stored in the distributed ledger 120 thus constituting training data for building the model. The model may, for example, be a convolutional neural network.

[0054] Alternatively, the model may be a set of rules that is not obtained by machine learning, but by analyzing derived data stored in the distributed ledger 120.

[0055] No restrictions are attached to the input data or the output data of the model. The model may be able to predict a situation described by the output data based on the input data, or may be able to provide a recommendation mandate described by the output data, based on a situation identified by the input data.

[0056] In the case of storage of a model by the device 100, the user terminal can transmit a request comprising input data of the model, and the device 100 applies the model in order to determine the output data. The device 100 can thus send a response to the user terminal 140, the response comprising the output data.

[0057] Two examples of models resulting from machine learning are given below, for illustrative purposes only.

[0058] In a first example, a first model is capable of determining a recommendation, for a battery described by input data, to recycle a battery or to reuse a battery. The output data can thus take two distinct values: recycle or reuse, and the battery can be described by several input data such as a battery type, a country of battery installation and an age of the battery.

[0059] Such a first model may have been previously trained to predict the decision to recycle or reuse a battery, from training data which is the derived data stored in the distributed ledger 120, and which is descriptive of real cases. The prediction can then be compared with a decision actually made to recycle or reuse the battery, a decision which is also stored as derived data in the distributed ledger. It is thus made possible to train the first model by supervised learning.

[0060] In a second example, a second model is capable of determining a battery type, as output data, from input data identifying a situation. The input data may, for example, be a motor vehicle model, a country of circulation of the motor vehicle, a place of manufacture of the motor vehicle. The second model may be trained to, from this input data, indicate a battery type, which may include one or more materials used in the battery.

[0061] The second model may be trained or determined such that the indicated battery type minimizes the environmental impact associated with the battery, in a situation corresponding to the input data. The derived data stored in the distributed ledger may be used to train the second model by machine learning, for example by supervised learning.

[0062] Note that the device 100 can determine several models, for example the two models described above, from the data derived from the information relating to the batteries stored in the distributed register 120.

[0063] The user terminal 140 may be a terminal of a partner of the manufacturer of the battery, or the manufacturer of the electric vehicle, such as a supplier for example. It is thus made possible according to the invention to allow transparent access to authentic data on the impact and life cycle of batteries, which makes it possible to overcome the drawbacks of the prior art.

[0064] The user terminal 140 may also be a terminal of an operator of a reclamation site, who may request the application of the first predefined model, by sending a request comprising input data describing a battery to be reclaimed, in order to receive a response comprising the output data from the first model, namely the decision to recycle or reuse the battery in a new electric vehicle or for a new application.

[0065] The user terminal 140 may also alternatively be a terminal of an electric vehicle manufacturer, wishing to determine a type of battery minimizing an environmental impact, depending on an electric vehicle in which the battery is intended to be installed, depending on the place of manufacture / assembly of the vehicle and / or depending on the country of circulation of the electric vehicle. In this case, the user terminal 140 can transmit to the device 100 a request identifying a type of electric vehicle, a place of manufacture / assembly and / or a country of circulation, and the device 100 can apply the second model described previously to this data, in order to determine the type of battery minimizing the environmental impact.

[0066] [Fig.2] is a diagram illustrating the steps of a method according to embodiments of the invention.

[0067] In a step 200, the device 100 obtains information relating to at least one battery from another entity of the network, such as the terminal 130 or the terminal 150, the information relating to at least one battery comprising at least one battery identifier and at least one piece of impact information, and optionally additional information, as described previously.

[0068] In a step 201, the device 100 determines data derived from the information relating to said at least one received battery, the derived data possibly being as described previously.

[0069] In a step 202, the device 100 stores the derived data thus determined, in the distributed register 120.

[0070] Steps 200 to 202 can be iterated each time the device 100 receives information relating to at least one battery. The device 100 can thus centralize a large amount of information relating to various countries, various types of battery, installed in vehicles of different types. A distributed register is thus formed comprising information relating to a large number of batteries, in particular impact information, which is more reliable and allows monitoring of the impact of the batteries throughout their life cycle.

[0071] At a step 210, the device 100 may receive a request from the user terminal 140, the request requesting information relating to a battery identified in the request or to a set of batteries identified in the request.

[0072] In a step 211, the device 100 obtains the derived data associated with the battery identified in the request, or with the set of batteries identified in the request, from the distributed ledger 120.

[0073] In a step 212, the device 100 makes available to the user terminal 140 the derived data obtained in step 211, for example via a graphical interface.

[0074] Thus, by steps 210 to 212, the invention allows the data stored in the distributed register to be made available to third parties, which allows great transparency in the manufacture and marketing of electric batteries.

[0075] At a step 220, the device 100 can collect a set of derived data stored in the distributed ledger 120, with a view to analyzing it or building a model, as previously described.

[0076] In a step 221, the device 100 can analyze the collected derived data and determine a synthesis / analysis of the data derived from information relating to a battery, a battery type or a set of batteries. Alternatively or additionally, the device 100 can determine a model capable of determining output data from input data, from the collected derived data. The model can be determined by machine learning, for example by supervised learning.

[0077] At a step 222, the device 100 can store the determined synthesis / analysis and / or the determined model in an internal memory of the device 100, or in an external memory accessible to the device 100, or in a server accessible to the device 100.

[0078] At a step 230, the device 100 may receive a request from the terminal 140, the request requesting a synthesis for a given battery, or for a set of batteries, or submitting input data for the device 100 to apply one of the stored models to it. In accordance with the examples previously given, the submitted data may include: - descriptive data of a battery, such as a battery type, a country of battery installation and a battery age; - data identifying a situation, which may include a motor vehicle model, a country in which the motor vehicle is circulated, a place of manufacture of the motor vehicle. Such data may be submitted for application of the second model and determination of a battery type that minimizes environmental impact.

[0079] In a step 231, the device 100 obtains the required synthesis in a memory which it accesses, or obtains output data by applying a model to the input data received in the request of step 230.

[0080] In response to the request received in step 230, the device 100 transmits the synthesis and / or the output data from the model to the user terminal 140.

[0081] [Fig.3] shows the structure of a device 100 according to embodiments of the invention.

[0082] The device 100 comprises a processor 301 configured to communicate unidirectionally or bidirectionally, via one or more buses or via a direct wired connection, with a memory 302 such as a memory of the “Random Access Memory” type, RAM, or a memory of the “Read Only Memory” type, ROM, or any other type of memory (Flash, EEPROM, etc.). Alternatively, the memory 302 comprises several memories of the aforementioned types.

[0083] The memory 302 is capable of storing, permanently or temporarily, at least some of the data used and / or resulting from the implementation of the method described with reference to [Fig.2].

[0084] In particular, the memory 302 can store the synthesis(s) determined in step 221, and / or the model(s) determined in step 221.

[0085] The processor 301 is capable of executing instructions, stored in the memory 302, for implementing the steps of the method according to the invention, described with reference to [Fig. 2]. Alternatively, the processor 301 can be replaced by a microcontroller designed and configured to carry out the steps of the method according to the invention, described with reference to [Fig. 2].

[0086] The device 100 comprises a network interface 303 capable of accessing the network 110, thus making it possible to communicate with the entities 120, 130, 140 and 150 previously described.

[0087] The device 100 may further comprise another interface, not shown, capable of accessing an external memory storing one or more syntheses determined in step 221, and / or the model(s) determined in step 221.

[0088] The present invention is not limited to the embodiments described above as examples; it extends to other variants.

Claims

Claims

1. Data processing method, comprising the following steps: - receiving (200) information relating to at least one battery for an electric vehicle, said information comprising at least one battery identifier and at least one impact information representative of an environmental impact associated with the identified battery; - determining (201) at least one data item derived from the received information; - storing (202) said at least one derived data item in a distributed register (120).

2. The method of claim 1, wherein the distributed ledger is a blockchain distributed ledger (120).

3. Method according to claim 1 or 2, wherein said at least one data item derived from the received information comprises: - the information relating to the battery; - some of the information relating to the battery, comprising at least the identifier of the battery and at least one impact information item; - a certificate comprising the information relating to the battery; and / or - a derived data item obtained by transformation of at least some of the information relating to the battery.

4. Method according to one of the preceding claims, further comprising: - receiving (210) a request, the request identifying a battery or a set of batteries, from a user terminal (140); - obtaining (211) data derived from information relating to the identified battery or the identified set of batteries, stored in the distributed ledger; - making available (212) the derived data obtained, to the user terminal.

5. A method according to one of the preceding claims, further comprising collecting (220) a data set derived from information relating to a battery or set of batteries and stored in the distributed ledger (120), and determining (221) a summary relating to said battery or set of batteries based on the collected derived data set.

6. A method according to one of the preceding claims, further comprising collecting (220) a set of derived data information relating to a battery or set of batteries and stored in the distributed ledger (120), and determining (221) a model from the collected derived data set, the model being capable of predicting output data from input data.

7. The method of claim 6, wherein the model is determined by machine learning from the collected derived data set.

8. A method according to claim 6 or 7, further comprising: - receiving (230) a query from a user terminal (140), the query comprising input data; - applying (221) the model to the input data of the query to obtain output data; - transmitting (222) a response to the user terminal, the response comprising the output data.

9. Computer program comprising instructions for implementing the method according to one of the preceding claims, when these instructions are executed by a processor (301).

10. Device (100) comprising: - an interface (303) capable of receiving information relating to at least one battery for an electric vehicle, said information comprising at least one battery identifier and at least one impact information representative of an environmental impact associated with the identified battery; - a processor (301) capable of determining at least one data item derived from the information received and capable of storing said at least one derived data item in a distributed register (120).

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