Method and system for verifying the energy quantity of an electrical charging process, as well as server equipment for the system

Abstract

Method for verifying an electric charging process (18), wherein the charging process (18) involves the transfer of electrical energy (19) between an electrically powered motor vehicle (13) and an electric charging station (15), and station-side measurement data (16) relating to the charging process (18) are generated by a measuring circuit of the charging station (15), and the station-side measurement data (16) are received from the charging station (15) by a server device (11), and characterized by the fact that Vehicle-side charging data (17) for the same charging process (18) are generated by a control circuit of the motor vehicle (13) and the vehicle-side charging data (17) are received from the motor vehicle (13) by the server device (11), wherein a control unit (40) in the motor vehicle (13) operates a loss model (29) to determine the charging data (17), which describes electrical losses in a coupling device connecting the charging station (15) to the motor vehicle (13) and / or within an energy network of the motor vehicle (13), and calculates the charging data (17) on the basis of measurement data (28) determined on the vehicle side and influenced by the electrical losses and on the basis of the loss model (29), and The server facility (11) operates a predetermined consensus algorithm (35) to generate a consensus value (36) based on the measurement data (16) and the charging data (17), which uniformly describes the charging process (18) for both the charging station (15) and the motor vehicle (13), by calculating a single consensus value (36) from two different measured values ​​for the same measurement quantity, which is equally binding for the motor vehicle (13) and the charging station (15), and If the consensus algorithm (35) signals a successful determination of the consensus value (36), the server facility (11) triggers and / or continues a predetermined continuation action to continue the loading process (18) and / or to further process the consensus value (36), and if the consensus algorithm (35) signals an unsuccessful determination of the consensus value (36), the server facility (11) triggers a predetermined abort action to abort the loading process (18).

Description

[0001] The invention relates to a method for verifying an electric charging process by which electrical energy is transferred between an electrically powered vehicle and an electric charging station. Furthermore, the usability of the vehicle and the electric charging station can be evaluated. The invention also includes a system by means of which the method can be carried out, as well as a server that can be used as part of the system.

[0002] In a system with electric charging stations and the vehicles they power, the verified, kWh-accurate amount of energy transferred is a crucial basis for accurate billing during charging (kWh - kilowatt-hour). A verified energy quantity measurement can often only be guaranteed by a calibrated meter at each charging station. However, this leads to the disadvantage that such a charging infrastructure system is expensive.

[0003] WO 2020 / 009 666 A1 states that payment after a charging process can be made using a cryptographic currency. It also describes how a vehicle can measure how much energy it has received from the charging station. However, the charging station and the vehicle measure the energy at different points, which can lead to discrepancies in the readings. It is unclear how this discrepancy should be handled.

[0004] It is known from DE 10 2018 112 118 A1 that a blockchain can be used to make data available to multiple users without having to prove the authenticity of the data separately, because the blockchain itself ensures the authenticity.

[0005] It is known from WO 2019 / 057 330 A1 that during a charging process a control unit of a motor vehicle can also be used as a node of an external computing network.

[0006] From EP 3 093 184 A1 it is known that during a transfer of electrical energy from a charging station to a motor vehicle, this charging process can be measured by both, and if a deviation of these measured values ​​exceeds a maximum value for a predetermined period, the charging process can be aborted.

[0007] From DE 10 2011 012 915 A1 it is known that for several charging stations and several motor vehicles for different charging processes, the difference between the amount of energy measured on the vehicle side and the amount of energy measured on the charging station side can be determined in order to calculate an average error from all the measured differences, which is then used to generate calibration data for individual measuring circuits involved.

[0008] From DE 10 2018 125 597 B3, an electricity meter is known which, when recording consumed electrical energy, takes line losses into account by determining, based on measured values, the power that is delivered but does not reach the consumer, but is instead consumed in the connecting cable. This results in a parameterization of the measured value compensation.

[0009] The invention is based on the objective of providing a cost-effective or low-effort charging infrastructure to supply motor vehicles with electrical energy.

[0010] The problem is solved by the subject matter of the independent claims. Advantageous embodiments of the invention are described by the dependent claims, the following description, and the figures.

[0011] The invention provides a method for verifying an electric charging process. During the charging process, electrical energy is transferred between an electric vehicle and an electric charging station. A measuring circuit in the charging station generates station-side measurement data about the charging process, and a server in the charging station receives this station-side measurement data. This corresponds to measuring the amount of energy transferred, for example, the amount of energy delivered. However, the measurement can also relate to the amount of energy received by the charging station, as can occur in so-called regenerative braking, where a vehicle feeds electrical energy from its electrical energy storage back into an electrical supply network or power grid via the charging station.The term "charging process" can therefore refer to both charging and discharging the electrical energy storage of the motor vehicle.

[0012] The process is characterized by the fact that, in addition, a control circuit in the vehicle generates vehicle-side charging data for the same charging process. The server receives this vehicle-side charging data from the vehicle and operates a predetermined consensus algorithm to generate a consensus value based on the measurement and charging data. This consensus value uniformly describes the charging process for both the charging station and the vehicle. In other words, the amount of energy transferred is recorded or measured by both the charging station and the vehicle, specifically using two different measurement circuits: one on the station side and one on the vehicle side.

[0013] Furthermore, the procedure includes the following: if the consensus algorithm signals a successful determination of the consensus value (i.e., if a consensus value can be found), then the server initiates and / or continues a predetermined continuation action to continue the charging process and / or to further process the consensus value. Otherwise (i.e., if the consensus algorithm signals an unsuccessful determination of the consensus value), the server initiates a predetermined termination action to abort the charging process. In other words, the vehicle and the charging station can be used as mutually monitoring devices, since the devices act as a power source and power sink for the same transferred energy, meaning their measuring circuits should generate the same measured values.This is verified by the independent server, and measurement deviations are handled or compensated for by the consensus algorithm. The consensus value can represent a binding description of the transferred energy quantity for all parties involved. Advantageously, this allows the use of measurement circuits without calibration, as neither of the measured objects (vehicle and charging station) has to rely on the other's measurement data, but can contribute its own measurement data to the consensus algorithm.

[0014] The charging station considered here can be, in particular, a charging column such as those installed at a roadside or in a parking lot. The charging station's measuring circuit can, in particular, include an energy meter at a charging port. The measured data can, in particular, describe the amount of energy and / or an electrical quantity (e.g., voltage and / or current) and / or power. The server system that operates the consensus algorithm can, in particular, include one or more server computers. The consensus algorithm can, in particular, be implemented as software with program instructions. The consensus value generated by the consensus algorithm can, in particular, describe an amount of energy transferred during the charging process. The vehicle's control circuit can, in particular, be the vehicle's control unit.The charging data generated by the motor vehicle is based on vehicle-side measurement data from a vehicle-side measuring circuit, which records electrical quantities corresponding to the station-side measurement data.

[0015] If the amount of energy received in a vehicle is measured, for example, at the electrical energy storage device, this measurement is systematically lower than the corresponding measurement at the charging station when recharging, because electrical losses in the lines are not included in the measurement. The invention provides that the control unit in the vehicle operates a loss model to determine the charging data, which describes electrical losses in a coupling device connecting the charging station to the vehicle and / or within the vehicle's power network. The coupling device can, in particular, include a charging cable and / or induction coils through which the energy is transferred. The vehicle's power network can include on-board power supply lines and / or a switching converter.In other words, the measuring circuit in the vehicle does not need to be located directly at the charging port (i.e., at the connection point to the coupling device). Instead, a measuring circuit such as one found in the energy storage device (e.g., the battery) can be used. To still determine the total energy drawn from the charging station during a recharging process, the electrical losses occurring during transmission within the vehicle and / or the coupling device can be calculated using the loss model. Thus, the charging data is calculated based on the vehicle-acquired measurement data, which is influenced by the electrical losses, and on the loss model.Advantageously, this prevents systematic discrepancies or differences between the vehicle's charging data and the charging station's measurement data, such as could arise from different measurement points or locations. The loss model can be, in particular, a mathematical and / or digital model.

[0016] The invention also includes embodiments that offer additional advantages.

[0017] The charging station and the vehicle will never be able to measure exactly the same values, but a charging process can still be carried out up to a predetermined tolerance. One embodiment provides that the consensus algorithm determines the respective difference between at least one measurand quantified by both the measurement data and the charging data. The measurand can be, in particular, electrical power and / or electrical energy and / or time and / or electrical voltage and / or electrical current. The difference can, for example, be the magnitude of the difference between the measured values ​​and this measurand. If the difference meets a predetermined tolerance criterion, the consensus value is calculated from the measurement data using a predetermined consensus value fixing rule, for example, as the mean value. If, on the other hand, the difference violates the tolerance criterion, i.e.,If the difference exceeds a predefined threshold or tolerance value, the unsuccessful determination of the consensus value is signaled. The tolerance criterion describes all cases where it is unlikely that at least one of the measured objects will accept a consensus value that deviates from its own measured data because the resulting discrepancy would be too large. The tolerance criterion can, in particular, specify a tolerance range for the value of the difference. In other words, a single consensus value is calculated from, for example, two different measured values ​​for the same quantity (e.g., energy quantity or charging time), which is intended to be equally binding for the vehicle and the charging station. Advantageously, this compensates for differences due to measurement inaccuracies. The consensus value determination procedure can, in particular, provide for the calculation of an average value.

[0018] One embodiment provides that the termination measure includes generating a request command, which, via at least one output device, issues a notification indicating an error in the charging process and / or faulty measurement data. In other words, the vehicle user and / or the charging station operator can be notified of the discrepancy between charging data and measurement data. Advantageously, a countermeasure can be initiated for future charging processes to prevent further inconsistent data. The output device can, in particular, include a screen and / or generate an email.

[0019] If the measuring circuits of the charging station and the vehicle generate different readings, the charging process should be terminated as early as possible. One embodiment provides that the consensus value is repeatedly updated during the charging process, and the termination measure includes sending a reset command to the charging station and / or a termination command to the vehicle, thereby interrupting the transfer of further energy during the charging process. In other words, the charging process is checked multiple times at different points in time during the charging process, i.e., continuously or at intervals, with respect to the consensus value. Advantageously, this avoids greater damage or disadvantage that could otherwise result from continuing the charging process. The reset command can, in particular, trigger the opening of a switch on the charging station.The abort command can, in particular, stop a voltage converter of a vehicle charger.

[0020] The measurement data from the charging station and / or the charging data from the vehicle can also be noisy or incomplete, for example, which can also be used to monitor the suitability of a measurement object (vehicle / charging station) for the system. One embodiment provides that a data evaluation algorithm is placed upstream of the consensus algorithm in the server setup. This data evaluation algorithm uses a quality criterion to determine the data quality of the measurement data (from the charging station) and the charging data (from the vehicle) and / or a predetermined number of charging dips (charging interruptions). If the quality criterion is violated, the termination measure is triggered. In other words, the continuation measure is only carried out if the quality criterion is met. The data evaluation algorithm can, in particular, be software with program instructions.The quality criterion can, in particular, describe the noise and / or volatility of a measurement signal described by the measurement or charging data. Data quality can, in particular, be described by the quality of, or deviation from, a predetermined ideal value with respect to, noise and / or volatility. Charging dips can, in particular, be an interruption of the energy flow. Usage quality can, in particular, specify a quantification of charging delays caused by charging dips. To indirectly trigger the termination action from the data evaluation algorithm, a consensus value determined by the consensus algorithm can, for example, be subsequently marked as invalid.

[0021] Should the system nevertheless contain a charging station with a calibrated meter, the measurement quality thus ensured can, of course, be used to verify or check other measurement objects (motor vehicles). One embodiment provides that, in the special case where equipment data for the charging station indicates that it has a calibrated meter, the consensus value is determined solely on the basis of the measurement data. In other words, the method can be applied to several different charging stations, and the aforementioned special case may occur with one or more of these charging stations. In another embodiment, both the charging station and the motor vehicle use their respective uncalibrated meters to generate the measurement data.In other words, only non-calibrated meters are used, which do not require official recalibration in the event of a design change (for example, in a new vehicle series). Advantageously, no costly approvals for the meters are necessary. If multiple charging stations are present in the system, a calibrated meter is used as the benchmark. The equipment data that indicates this can be stored in the server and / or provided by the charging station and / or a server operated by the station's operator. The calibrated meter can be, in particular, an officially calibrated measuring instrument.

[0022] The evaluation of the measured objects (regarding the possibility of determining consensus values ​​with them and / or obtaining unfairly noisy measurement / charging data) can be used for future charging processes. In one embodiment, the server system determines evaluation data for both the charging station and the vehicle. The consensus algorithm then determines the respective weighting of the station-side measurement data and the vehicle-side charging data when calculating the consensus value. This evaluation data describes the data quality, availability, and / or usability of the measurement data provided by the charging station and / or the charging data provided by the vehicle. In other words, it describes which predetermined quality characteristics can be expected from the charging station and / or the vehicle.Advantageously, a suitable charging station can be selected for the planning of a charging process, and / or a selection criterion for vehicles authorized to use the charging station can be provided to the operator. In other words, it can be decided which charging stations and / or which vehicles will be permitted to participate in the system in the future. The evaluation data can be stored, in particular, in a data storage system on the server. The percentage can be calculated, in particular, by weighted addition using weighting factors that are set depending on the evaluation data. Data quality can be described, in particular, by the noise and / or variance or volatility. Data availability can be described, in particular, by the measured variables described by the measurement data and / or charging data.Usage quality can, in particular, indicate the frequency or probability of a charging interruption.

[0023] To obtain reliable evaluation data, it should always consider or be based on multiple charging processes. One embodiment provides that, using a predetermined measurement-object evaluation algorithm for multiple charging processes, the evaluation data is updated with each charging process based on the respective measurement and charging data of the charging process, specific to the vehicle and charging station. In other words, the charging station and / or the vehicle is monitored over multiple charging processes to determine how reliable the charging data provided by the vehicle and / or the measurement data provided by the charging station are. Advantageously, the evaluation data can describe a statistical average and thus form a more reliable evaluation criterion.The measurement object evaluation algorithm can, in particular, use the data evaluation algorithm and / or the consensus value algorithm to determine the evaluation data in the manner described.

[0024] The evaluation data can, for example, prevent a faulty charging station from being used for a charging process or a vehicle with a faulty measuring circuit from being used at a charging station. One embodiment provides that the evaluation data is used to control the charging planning of at least one future charging process in such a way that only charging stations and / or vehicles whose respective evaluation data meet a predetermined eligibility criterion are permitted for that at least one future charging process, and / or charging stations and / or vehicles are prioritized according to their evaluation data. In other words, unsuitable vehicles whose charging data does not lead to a consensus value, and / or charging stations whose measurement data does not lead to a consensus value, are excluded from the system. Advantageously, unsuitable participants can be automatically excluded or blocked.The charging plan can, in particular for an upcoming trip for which a route has been determined, identify at least one charging station for recharging the vehicle's energy storage system. The eligibility criterion can, in particular, represent a restriction on the number of participants in the system (suitable charging stations and suitable vehicles).

[0025] One embodiment provides that the evaluation data for multiple charging stations, utilizing charging processes from several vehicles (swarm vehicle data), are aggregated into a charging station map and used in charging planning to select charging stations for future charging processes along a predefined route. In other words, swarm data (i.e., data from multiple vehicles) can be used to obtain statistically supported evaluation data. Advantageously, well-organized charging planning can be controlled based on the availability and charging capacity of the charging station. The charging station map can, in particular, be designed as a so-called heatmap, which displays the values ​​specified in the evaluation data.

[0026] One embodiment provides that the server setup comprises multiple server computers, each of which independently controls loading processes and queries the evaluation data from a distributed ledger technology (DLT) and / or makes it available to the other server computers via the DLT. In other words, the evaluation data is not stored centrally, but rather the server computers exchange the evaluation data via a DLT, thus ensuring the authenticity of the evaluation data. Advantageously, this provides a measurement data verification system that can be scaled retroactively by adding server computers and operates without central management control. A particular server computer can be a cloud computer for a computer cloud or a network computer for a virtual network. The DLT can, in particular, include a blockchain-based data storage system.

[0027] One embodiment provides that the continuation measure includes storing the consensus value using a distributed ledger technology (DLT), in particular a blockchain, and a) triggering a DLT smart contract and / or b) storing an energy quantity described by the consensus value and an associated timestamp of the charging process in a logbook of the vehicle's energy storage system and / or in a charging record data store. In other words, the consensus value is used, for example, for a payment transaction within a smart contract and / or to document wear and tear on the energy storage system. Advantageously, the measurements taken during the charging process in the charging station and / or in the vehicle are made available in a compact form as a consensus value.The smart contract can be, in particular, an evaluation program linked to or contained within the DLT, with a program flow dependent on the consensus value. The timestamp can, in particular, specify a date and / or a time. The checkbook can, in particular, be designed as a digital data record that can be managed, for example, by a manufacturer of the energy storage device. The energy storage device can, in particular, be designed as a high-voltage battery (high voltage - electrical voltage greater than 60 volts, especially greater than 100 volts).

[0028] The invention also provides a system for providing a charging infrastructure, comprising the aforementioned server equipment, multiple charging stations, and multiple motor vehicles, wherein the system is configured to carry out a method according to the invention. In other words, the motor vehicles and the charging stations can be participants in a common system in which no calibrated meters are necessary, since the charging station and the motor vehicle can mutually verify each other during each charging process. Advantageously, the system can be provided with lower material or manufacturing costs than a system that requires calibrated meters.

[0029] One embodiment provides that the server setup includes at least one server computer, each configured to perform the steps of the inventive method relating to the server setup. A server computer may include a processor configured to perform the steps of an embodiment of the inventive method relating to the server setup. The processor may include at least one microprocessor and / or at least one microcontroller and / or at least one FPGA (Field Programmable Gate Array) and / or at least one DSP (Digital Signal Processor). Furthermore, the processor may include program code configured to perform the steps of the method when executed by the processor. The program code may be stored in a data memory of the processor.

[0030] The respective motor vehicle is preferably designed as a motor vehicle, in particular as a passenger car or truck, or as a passenger bus or motorcycle.

[0031] The invention also includes implementations in which features of different described embodiments are combined, unless these embodiments are expressly presented as alternatives.

[0032] The following are exemplary embodiments of the invention described. This is illustrated by: Fig. 1 a schematic representation of an embodiment of the system according to the invention; Fig. 2 a sequence diagram to illustrate an embodiment of the method according to the invention.

[0033] The exemplary embodiments described below are preferred embodiments of the invention. In these exemplary embodiments, the described components each represent individual features of the invention, which can be considered independently of one another and each further develops the invention independently. Therefore, the disclosure is intended to include combinations of features of the embodiments other than those shown. Furthermore, the described embodiments can also be supplemented by further features of the invention already described.

[0034] In the figures, identical reference symbols denote functionally equivalent elements.

[0035] The Fig. Figure 1 shows a system 10 that can include a server 11, through which charging process verification and measurement object evaluation can be automatically started, carried out, evaluated, and completed during electric charging processes. The measurement objects 12 can be configured as power sources and power sinks. The measurement objects 12 shown are, in particular, an electrically powered vehicle 13 with battery storage 14 and an electric charging station 15.

[0036] The vehicle 13 can be a private vehicle or belong to a company or vehicle rental fleet. The system 10 can comprise several vehicles 13 and / or several charging stations 15. The charging stations 15 constitute a charging infrastructure for the vehicles 13.

[0037] The server setup 11 makes it possible to independently verify measurement data 16 of a respective charging station 15 and charging data 17 of a respective motor vehicle 13 during a charging process 18 in which energy 19 is transferred between the motor vehicle 13 and the charging station 15 with minimal effort, and also to evaluate the usability of the charging station 15 and the motor vehicle 13, as will be explained further in connection with Fig. 2 is described in more detail.

[0038] The server system 11 can comprise one or more server computers 20, each of which can operate a control module 21 to control or activate the respective charging processes 18 of the motor vehicle 13 or the charging station 15, taking into account the specifications of the motor vehicle 13 and its owner, as well as the charging station 15 and its operator. A control module 21 can be implemented based on program data or program code of a software. A storage device 22 can be operated by a control module 21 to provide a respective data storage for the motor vehicles 13 and for the respective charging stations 15. For example, such a storage device 22 can be a distributed ledger technology 23, e.g., a blockchain consisting of several blocks B1, B2, B3 linked together, for example, via checksums or hash codes 24.The three blocks B1, B2, B3 shown here as examples are only examples; n blocks can be provided, where the number n can also be greater than three.

[0039] The data stored in storage device 22 can, for example, be processed by a smart contract 25, the program code of which can be executed automatically by the respective server computer 20. The server computers 20 can exchange the storage device 22 as a data structure among themselves, so that all server computers 20 have the same data available. By immutably storing the identities, for example, using a public key of the respective vehicle 13 and the respective charging station 15 in storage device 22 of server device 11, these become a trusted or authenticated instance or participant of server device 11.

[0040] Charging process verification and measurement object evaluation begin as soon as a charging process 18 between a motor vehicle 13 and a charging station 15 of the system 10 has been started or completed and a wired or wireless physical energy exchange 19 has taken place. The calibrated or uncalibrated measuring instruments 26, 27 of the measurement objects 12 determine measurement data such as voltage, current, and power. The charging data 17 of the motor vehicle 13 are generated from measurement data 28 of the measuring instrument 26 and from data of a loss model 29. Losses occur, for example, at the charging cable or in the power grid of the motor vehicle 13 during the charging process 18. The measurement data 16 are generated by the measuring instrument 27 of the charging station 15. Communication circuits 30, 31 transmit the charging data 17 and measurement data 16, respectively, via communication channels 32, 33 to the server facility 11 to one of the control modules 21.The control module 21 of the server system 11 consists of the storage system 22, which can be implemented using distributed ledger technology 23, e.g., a blockchain, and a smart contract 25. The smart contract 25 contains the program code that processes the received data using algorithms. The loading process verification includes a data evaluation algorithm 34 and a consensus algorithm 35 for the automated fixing of a consensus value 36. A measurement object evaluation algorithm 37 is used to evaluate the measurement objects 12.

[0041] Once the consensus value 36 has been fixed, it is stored in the storage device 22. Based on this, for example, an invoice 38 can be generated during an energy quantity verification.

[0042] If no consensus value 36 is found, the charging process 18 and thus the energy transfer 19 can be interrupted at any time by the vehicle 13 and the charging station 15. For this purpose, the server 11 sends a control command 39 via communication channel 32 to a control unit 40 of the vehicle 13 and / or a reset command 41 via communication channel 33 to an enabler 42 of the charging station 15.

[0043] Fig. Figure 2 illustrates once again the active or completed charging process 18. The charging data 17 of the motor vehicle 13 are sent in step S1 and the measurement data 16 of the charging station 15 are sent in step S2 from the communication circuits 30, 31 via the communication channels 32, 33 to the smart contract 25.

[0044] In step S3, the automated algorithms 34, 35, 37 are executed in the program code of the smart contract 25.

[0045] The data evaluation algorithm 34 performs a data evaluation 43 of the loading data 17 and the measurement data 16. The goal is to meet admissibility criteria based on data quality for the consensus value determination. Admissibility criteria can include data availability and data quality.

[0046] The consensus algorithm 35 performs a consensus value determination 44. This compares the charging data 17 with the measurement data 16. If the difference in the data (e.g., voltage, current) is within a tolerance range, a common consensus value 36 is generated by the smart contract 25. Furthermore, either the charging data 17 or the measurement data 16 can be used as the reference variable for the consensus value determination 44. This can be the case if the measured object 12 has a suitable level of usability, for example, through a calibrated meter or a high measured object rating in the data storage of the distributed ledger technology 23. The verified consensus value 36 can, for example, be an energy quantity. The verified consensus value 36 (e.g., the energy quantity) can serve as the basis for billing during the charging process 18. This verified software determination procedure (e.g.,(Verified energy quantity determination) can thereby enable or replace a calibrated software determination procedure. If no consensus value is reached because the admissibility criteria are insufficient, the consensus value 36 can be marked as invalid.

[0047] The measurement object evaluation algorithm 37 evaluates the usability quality of the measurement objects 12 in a measurement object evaluation 45 based on the data evaluation 43 and the consensus value fixing 44.

[0048] Charging data differences or volatility between the measurement objects (12) or charging dips allow for statements about usage quality and corresponding ratings. A ranking of the measurement objects is created from these ratings. Negative ratings erode confidence in the accuracy of charging process measurement and thus the determination of charging data. Since the identities of the measurement objects are immutably stored in the distributed ledger technology on the server, a direct correlation between charging data and ratings is possible. The greater the number of measurement methods for a given measurement object with different measurement objects, the more meaningful the usage quality of that measurement object becomes. The rating of the measurement object determines its priority and the level of trust placed in it. Customer reviews on online retail platforms serve as a comparison, where a large number of positive customer reviews indicates greater trust.The evaluation of charging stations using swarm vehicle data can serve as the basis for charging station maps. Based on the availability and charging capacity of the charging station, well-organized charging planning can be significantly improved. Peer-to-peer charging process verification also allows verified and therefore trusted energy quantities, including timestamps, to be securely stored in an energy storage logbook or used to obtain proof of charging. Furthermore, the regulation of the vehicle's charging capacity can be documented. This is useful, for example, to prove the use of discounted or renewable electricity.

[0049] The evaluation and assessment (i.e., the data evaluation 43 and / or the consensus value fixing 44 and / or the measurement object evaluation 45) can each be carried out statically (i.e., using predefined calculation formulas and / or tables) and / or statistically and / or AI-based (AI - artificial intelligence).

[0050] In step S4, the smart contract initiates the execution of the smart contract transaction with the consensus value and the measurement object evaluation.

[0051] In step S5, the smart contract transaction is executed on the blockchain. In step S6, if the consensus value is valid, settlement data 46 can optionally be processed further and a settlement 38 initiated. In step S7, if the consensus value 36 is invalid, a request command 47 can optionally be issued. The request command 47 can notify the measurement objects and their owners of a malfunction during loading or loading data tolerance. The owner can also query the valuations of the measurement objects.

[0052] Should a malfunction occur during the charging process, the server 11 can transmit the reset command 41 to the charging station 15 in step S8 of the activation 42, or the control command 39 to the vehicle 13's control unit 40 in step S9. This stops the charging process, whereupon the energy transfer 19 is interrupted. This coordination can optionally be carried out via a backend server 50.

[0053] Overall, the examples show how methods and systems for verifying the charging process of an electric charging process and for evaluating the usability of a charging station or motor vehicle can be provided via a decentralized server device.

Claims

[1] Method for verifying an electric charging process (18), wherein the charging process (18) transfers electrical energy (19) between an electrically powered motor vehicle (13) and an electric charging station (15), and station-side measurement data (16) about the charging process (18) are generated by a measuring circuit of the charging station (15), and the station-side measurement data (16) are received from the charging station (15) by a server device (11), and characterized by , that Vehicle-side charging data (17) for the same charging process (18) are generated by a control circuit of the motor vehicle (13) and the vehicle-side charging data (17) are received from the motor vehicle (13) by the server device (11), wherein a control unit (40) in the motor vehicle (13) operates a loss model (29) to determine the charging data (17), which describes electrical losses in a coupling device connecting the charging station (15) to the motor vehicle (13) and / or within an energy network of the motor vehicle (13), and calculates the charging data (17) on the basis of measurement data (28) determined on the vehicle side and influenced by the electrical losses and on the basis of the loss model (29), and The server facility (11) operates a predetermined consensus algorithm (35) to generate a consensus value (36) based on the measurement data (16) and the charging data (17), which uniformly describes the charging process (18) for both the charging station (15) and the motor vehicle (13), by calculating a single consensus value (36) from two different measured values ​​for the same measurement quantity, which is equally binding for the motor vehicle (13) and the charging station (15), and If the consensus algorithm (35) signals a successful determination of the consensus value (36), the server facility (11) triggers and / or continues a predetermined continuation action to continue the loading process (18) and / or to further process the consensus value (36), and if the consensus algorithm (35) signals an unsuccessful determination of the consensus value (36), the server facility (11) triggers a predetermined abort action to abort the loading process (18). [2] Method according to claim 1, wherein the consensus algorithm (35) determines a difference between at least one measured quantity quantified by both the measurement data (16) and the loading data (17), and if the difference meets a predetermined tolerance criterion, the consensus value (36) is calculated from the measurement data (16) using a predetermined consensus value fixing procedure, and if the difference violates the tolerance criterion, the unsuccessful determination of the consensus value (36) is signaled. [3] Method according to claim 2, wherein the consensus value (36) is calculated as the mean value using the predetermined consensus value fixing procedure. [4] Method according to one of the preceding claims, wherein the termination measure comprises generating a request command (47) by which an indication of an error in the charging process (18) and / or of faulty measurement data (16) is output via at least one output device. [5] Method according to one of the preceding claims, wherein the consensus value (36) is repeatedly updated during the charging process (18) and the termination measure comprises sending a reset command (41) to the charging station (15) and / or a termination command (39) to the motor vehicle (13) thereby interrupting the transfer of energy (19) during the charging process (18). [6] Method according to one of the preceding claims, wherein in the server device (11) a data evaluation algorithm (34) is placed upstream of the consensus algorithm (35) and by the data evaluation algorithm (34) a data quality of the measurement data (16) and the loading data (17) and / or a usage quality dependent on loading dips is determined on the basis of a predetermined quality criterion and if the quality criterion is violated, the termination measure is triggered. [7] Method according to one of the preceding claims, wherein, in the special case that equipment data for the charging station (15) indicate that the charging station (15) has a calibrated meter, the consensus value (36) is determined exclusively on the basis of the measurement data (16) and / or wherein both the charging station (15) for generating the measurement data (16) and the motor vehicle (13) for generating the charging data (17) use a respective uncalibrated meter. [8] Method according to one of the preceding claims, wherein the server device (11) determines evaluation data for the charging station (15) and for the motor vehicle (13), and the consensus algorithm (35) determines a respective proportion of the station-side measurement data (16) and the vehicle-side charging data (17) when determining the consensus value (36) by the evaluation data, wherein the evaluation data describe a data quality and / or a data availability and / or a usability quality of the measurement data (16) provided by the charging station (15) and / or the charging data (17) provided by the motor vehicle (13). [9] Method according to claim 8, wherein, by means of a predetermined measurement object evaluation algorithm (37) for several charging processes, the evaluation data are updated with each charging process (18) on the basis of the respective measurement data (16) and charging data (17) of the charging process (18) in a vehicle-specific and / or station-specific manner. [10] Method according to claim 8 or 9, wherein the evaluation data is used to control the charging planning of at least one future charging process (18) in such a way that only charging stations (15) and / or motor vehicles (13) whose respective evaluation data meet a predetermined eligibility criterion are permitted for at least one future charging process (18) and / or charging stations (15) and / or motor vehicles (13) are prioritized according to their evaluation data. [11] Method according to one of claims 8 to 10, wherein the evaluation data for several charging stations (15) are combined to form a charging station map by utilizing charging processes of several motor vehicles (13) and are used in the charging planning to select charging stations (15) for future charging processes along a given route. [12] Method according to claims 8 to 11, wherein the server setup (11) comprises several server computers (20), each of which independently controls loading operations from the other server computers (20), and queries the evaluation data from a distributed ledger technology (23), DLT, and / or makes it available to the other server computers (20) via the DLT. [13] Method according to any of the preceding claims, wherein the continuation measure comprises storing the consensus value (36) using a distributed ledger technology (23), DLT, in particular a blockchain and a) a smart contract (25) of the DLT is triggered and / or b) an energy quantity described by the consensus value (36) and an associated timestamp of the charging process (18) is stored in a checkbook of an energy storage device of the motor vehicle (13) and / or in a charging record data storage device. [14] System (10) comprising a server facility (11) and multiple charging stations (15) and multiple motor vehicles (13), wherein the system (10) is configured to perform a method according to any of the preceding claims. [15] Server setup (11) for a system (10) according to claim 14, wherein the server setup (11) comprises at least one server computer (20) which is configured to perform the steps relating to the server setup (11) of a method according to any one of claims 1 to 13.

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