EP3883811A1

EP3883811A1 - Charging system for electric vehicles

Info

Publication number: EP3883811A1
Application number: EP19805270.6A
Authority: EP
Inventors: Stephan CATER
Original assignee: Innogy SE
Current assignee: CCS Abwicklungs AG
Priority date: 2018-11-21
Filing date: 2019-11-15
Publication date: 2021-09-29
Also published as: WO2020104326A1; DE102018129335A1; US20210268929A1

Abstract

The application relates to a charging system (200) for electric vehicles (224, 226), comprising a plurality of charging stations (216, 218) each configured to exchange electrical power with at least one electric vehicle (224, 226), at least one charging profile determination module (234) configured: to receive a charging station identifier assigned to a first charging station (216, 218) of the plurality of charging stations (216, 218) and a user identifier of an electric vehicle (224, 226) to be charged at the first charging station (216, 218) during a charging operation, which user identifier is assigned to a user, to determine, on the basis of the received user identifier and the received charging station identifier, at least one historical charging operation data set relating to the user identifier and the charging station identifier, to estimate at least one charging parameter for the charging operation on the basis of the at least one historical charging operation data set, and to determine the charging curve profile for the charging operation at least on the basis of the at least one estimated charging parameter.

Description

Charging system for electric vehicles

The application relates to a charging system for electric vehicles, comprising a

A plurality of charging stations, each set up to exchange electrical power with at least one electric vehicle. In addition, the

Registration a method for operating a charging system.

Charging systems for charging electric vehicles are known from the prior art. Known charging systems have one or more charging stations that can be communicatively coupled to a back-end system. A

Charging station can have at least one charging point to which an electric vehicle to be charged can be electrically connected. For example, the charging point can be a charging cable attached to the charging station, which can be connected to a charging port of the electric vehicle. Alternatively, the charging point can be a charging port on the charging station that can be connected to a charging cable. As a rule, before the start of a charging process between a charging station and an electric vehicle, a charging curve profile for the charging process to be carried out is established. The charging curve profile to be determined is based at least on the maximum power P _L-max available at the charging station. The maximum available power P _L-max is in particular the maximum permissible, deliverable (total) power at the

Charging station.

FIG. 1 shows a schematic view of exemplary charging curve profiles at a charging station from practice. In particular, the power curve P is plotted against time t. In the present case, it is initially assumed that the charging station has at least two charging points. It is also possible for a charging station arrangement to be provided with two or more charging stations which are arranged adjacent to one another, that is to say are coupled to the same power network section.

With a first charging curve profile 102 between the time to and the time t2, a power Pi is reserved for this period for a first charging process of a first electric vehicle at the charging station. In particular

Basically, the power Pi is reserved or held for the first electric vehicle for the charging process up to a point in time t2. The power Pi can

for example, the maximum permissible charging power of the electric vehicle.

At time ti, a second charging process is requested by a second electric vehicle at the charging station. A second power is reserved for this by a second charging curve profile 104. As can be seen, the second is

Electric vehicle output power limited by the maximum output power P L_max and the power Pi already reserved for the first charging process.

Furthermore, it can be seen that no power can be made available for a further charging point of the charging station (or a further neighboring charging station) at least between the time ti and the time t2.

As already described, by defining a charging curve profile, the corresponding power for the charging process of an electric vehicle is permanently reserved for a certain period of time, regardless of the actual one

Demand / desire for electrical power or energy. This can lead to the fact that the power available for charging another electric vehicle at a charging station is limited in certain time periods.

In order to optimize the operation and in particular the efficiency of a charging station, it is known from the prior art to determine the state of charge of the electrical item to be charged Storage, especially the traction battery, of the electric vehicle. Furthermore, in known charging systems, there is usually

User interface (e.g. at the charging station and / or on a user terminal (e.g. smartphone, tablet etc.)) provided by the user to enter the

desired amount of energy and / or the desired charging time can be used. As a result, the power reserved by the charging curve profile can be adapted more precisely to the need / desire for electrical power or energy.

Based on the state of charge and the desired amount of energy and / or the desired charging time, for example, the power Pi to be reserved from the above example can be reduced, but the amount of energy can be the same by extending the charging process duration, so that more power is available for the second electric vehicle and / or power is still available for a third electric vehicle. In practice, however, it has been shown in the operation of known charging systems that users only rarely use the option of using the desired amount of energy and / or the desired charging duration or charging process duration

Specify user interface.

One reason for this is that entering the information leads to increased effort for the user. In addition, it is necessary for the user to have the desired amount of energy and / or the desired amount before starting a charging process

Determine and determine charging duration.

It is therefore the object of the application to provide a charging system for charging electric vehicles which optimizes the operation of the charging stations, in particular the efficiency of the charging stations, and at the same time increases the user-friendliness. According to a first aspect of the application, the object is achieved by a charging system for electric vehicles according to claim 1. The charging system comprises a plurality of charging stations. A charging station is set up to exchange electrical power with at least one electric vehicle. The charging system comprises at least one charging profile determination module. The charging profile determination module is set up to:

Obtaining a charging station identifier assigned to a first charging station of the plurality of charging stations and a user identifier assigned to a user of an electric vehicle to be charged at the first charging station during a charging process,

Determining, based on the received user identification and the received charging station identification, at least one historical charging process data record relating to the user identification and the charging station identification,

Estimating at least one charging parameter for the charging process, based on the at least one historical charging process data record, and

Determining the charging curve profile for the charging process, at least based on the at least one estimated charging parameter.

In contrast to the prior art, according to the application, a charging system with a plurality of charging stations is provided, which enables the operation of the

Charging stations, especially the efficiency of the charging stations, optimized and

at the same time increases user friendliness by determining the

Loading curve profile on historical, especially user-specific and

loading position-specific, loading process records based. The one

Charging curve profile to be reserved charging power can be optimized.

User input via a user interface module can be omitted.

The charging system according to the application comprises a plurality of charging stations. A charging station according to the application is to be understood as a stationary device that exchanges electrical energy between an electric vehicle or the electrical storage device of the electric vehicle and the stationary device enables. In particular, a charging station has at least one charging point, preferably a plurality of charging points, around an electric vehicle

For example, to couple with the charging station via a charging cable, so that electrical energy can be exchanged via the charging cable. As a charging point, a charging station can have, for example, at least one permanently attached charging cable and / or at least one charging connection, which can be coupled to a charging cable.

Furthermore, the charging station can comprise charging technology in order to control the charging process.

The charging stations are located in different locations or positions, especially in public and partially public spaces. Two or more charging stations at the same location (for example, the same parking area) can be referred to as a charging station arrangement.

In the present case, an electric vehicle is to be understood as a vehicle, in particular a car, which can be operated at least partially electrically and comprises at least one rechargeable electrical store, in particular a traction battery.

In addition, the charging system includes at least one

Load profile determination module. The charging profile determination module can be in a charging station, a back-end system of the charging system and / or one

Computing device, which is controlled, for example, by the back-end system, can be arranged or implemented.

The charging profile determination module is in particular set up to optimize a charging curve profile for a charging process, based on historical charging processes of the user at the charging station at which the charging process is to be carried out. For optimization purposes, the registration in particular suggests first evaluating a user identification and a charging station identification. In particular, the charging station identifier of the charging station and the user identifier of the user can be obtained before a charging process of an electric vehicle of a specific user at a specific (first) charging station. At least system-wide, a charging station identifier can be uniquely assigned to one charging station and one

User identification can be uniquely assigned to a user.

Based on the user ID received and the one received

Charging station identifier can determine at least one historical charging process data record that has at least one recorded charging parameter (value) of a historical, that is to say previous, charging process. Preferably, a plurality of historical ones can be stored in at least one memory module

Charging process records are stored, which are charging station ID-dependent and user ID-dependent. This is to be understood in particular to mean that the memory module with the stored charging process data records can be searched for user identification and charging station identification, so that they can be found, that is to say

are determinable.

Based on the historical charging process data records, at least one charging parameter, in particular a plurality of charging parameters for the

charging process to be performed. A loading parameter or value is to be understood as a parameter (value) that influences the loading curve profile to be created.

Based on the estimated at least one loading parameter, this can

Charging curve profile for the charging process to be carried out determined, in particular generated. Then the charging process at the charging station

be performed. It is understood that when determining the

Charging curve profile the charging curve profiles already available at the charging station or the charging curve profiles present on the charging station arrangement of a charging station can be taken into account.

The charging system can preferably comprise an authentication module. The authentication module can be in a charging station, a back-end system of the charging system and / or a computing device, for example, by the

Backend system is controlled, arranged or implemented. The

Authentication module can be set up to carry out a

Authentication process, especially before starting the charging process at the first charging station. In particular, at least based on the

User identification, it is checked whether the user is authorized to charge at the charging station (which can be identified based on the charging station identifier) or not.

The charging profile determination module can preferably be used for the

Authentication process used user ID (e.g. a contract ID, user name, user address etc.) is provided. Furthermore, the charging station identifier used in an authentication process (e.g. signature, unique address, unique geographic coordinates or the like)

Position information, unique code, etc.) of the charging station, at which the user authenticates himself for a charging process, is provided.

As has already been described, the charging system can comprise at least one memory module, set up for storing user identification-dependent and

Charging station ID-dependent historical charging process records. The storage module can be arranged or implemented in a charging station, a back-end system of the charging system and / or a storage arrangement which is controlled, for example, by the back-end system.

The charging profile determination module can particularly preferably be designed as a control module. The control module can receive at least the user identifier and the charging station identifier as input variables for a control algorithm. Output size can be the optimized charging curve profile in particular. The control module can perform the control algorithm according to the above

Executions, preferably access the memory module in which the historical loading data records are stored. The memory module can be an integral part of the control module.

The control module can preferably be formed by a control module selected from the group comprising:

Extreme value controller,

Fuzzy controller,

a control model based on a machine learning algorithm, a neural network, or

Combinations of these.

In this way, in particular, a self-learning charging system for an electric vehicle can be provided.

In addition, the charging profile determination module can be set up for

Determine the charging curve profile based on at least one

Real-time information, especially an instantaneous power grid parameter. A power grid parameter can be, for example, a grid frequency, a harmonic, a voltage and / or a current. The at least one power grid parameter can be recorded by a further measuring device

be made available to the charging profile determination module. It is possible that the further measuring device is located in a charging station. By one

Grid parameters are taken into account, the current grid status

are taken into account and the network to which the charging station is coupled can thereby be stabilized, for example. The charging system preferably has a back-end system communicatively connected to the plurality of charging stations. At least the charging profile determination module can preferably be implemented in the back-end system.

The charging profile determination module can preferably be set up to estimate the at least one charging parameter based on at least one historical load distribution of the power grid to which the first charging station is connected.

In particular, the charging profile determination module can call up the historical load distribution from the (first) charging station at which the charging process is to be carried out. The historical load distribution can be used to estimate what the average load on the supply network is at the time of the desired charging process. Such an average workload can be time-resolved, so that, for example, a time-dependent and / or weekday-dependent

average occupancy. A time of day

average occupancy can be a so-called

Be load forecast / load forecast.

According to a further embodiment of the charging system according to the application, the charging system can comprise at least one recording module. The

Recording module can in the charging station, a back-end system of the charging system and / or a separate computing device, for example, by the

Backend system is controlled to be arranged.

The recording module can be configured to record charging processes carried out at the plurality of charging stations. In particular, the at least one recording module can record (almost) every charging process, for example with the aid of suitable measuring sensors. Thus, the recording module can be set up to record the charging processes that have been carried out

at least one charging station, in particular for detecting the at least one actually measured during a charging process

Load parameters or load parameter value. In particular, the memory module can be set up for storing the recorded charging process, in particular the at least one charging parameter actually measured during a charging process, in the form of a user charging-dependent and charging station identifier-dependent historical charging data record, for storing the recorded charging process, in particular dependent on the charging station identifier.

According to a particularly preferred embodiment, the

Charging profile determination module can be set up to estimate the maximum permissible charging power of the charging process to be carried out during the

to be carried out to be transferred amount of energy and / or the duration of the charging process.

In other words, a charging parameter according to the application can, in particular, the (maximum or average) charging power of the charging process to be carried out (or the historical charging process), the charge to be transferred (or transferred)

Amount of energy of the charging process to be carried out (or of the historical

Charging process) or the charging process duration of the charging process to be carried out (or the historical charging process).

By estimating, in particular, a plurality of these parameters, the charging curve profile can then be created with a higher accuracy for the expected charging process.

Furthermore, according to a further embodiment of the charging system according to the application, the at least one estimated charging parameter can be one

Probability of occurrence must be assigned. In particular, it can

Charging profile determination module one for each estimated charging parameter

Determine and assign probability of occurrence or an expected value. An example is shown in Table 1 below:

Table 1

Here P _{max is} the estimated maximum (reserve) charging power, E _men the estimated (transferred) amount of energy and the charging process the estimated time during which the electric vehicle will be coupled to the charging station.

The charging profile determination module can be set up to determine the charging curve profile for the charging process, at least based on the at least one estimated charging parameter and the assigned probability of occurrence. If, for example, the charging process duration is estimated to be 6 hours with an expected value of 100%, the charging process profile can have a duration of 6 hours (possibly with a predefinable safety tolerance) and the estimated amount of energy (with an expected value of 100%) can be distributed over these 6 hours will. However, if the charging process duration of 6 hours is only estimated with an expected value of 50%, the charging process profile can have a duration of 3 hours (possibly with a predefinable safety tolerance) and the estimated amount of energy (with an expected value of 100%) can be distributed over these 3 hours be (if it is possible).

In addition, the charging profile determination module can be set up for

Determining the at least one historical charging process record based on a charging start time (e.g. a time of day and / or a day of the week) of the charging process. In this way, the determination of the charging curve profile can be further optimized.

For example, on a certain day of the week, the user may regularly use his vehicle at a specific charging station for a first (approximate) Charging duration then follows, while the user regularly connects his vehicle at the specific charging station on another weekday for another (approximate) charging duration, which can differ, for example significantly, from the first charging duration.

The charging profile determination module can preferably be set up to estimate the at least one charging parameter based on the (current)

State of charge (in particular the charging capacity) of the battery to be charged

Electric vehicle. In particular, before the start of the charging process, the state of charge, in particular the current charging capacity of the battery to be charged

Electric vehicle. Depending on the state of charge, the at least one charging parameter can be estimated with greater accuracy. It goes without saying that, optionally, information on the charging process duration and / or the desired amount of energy can also be obtained via a user interface and can be taken into account in the estimation.

According to a further preferred embodiment of the charging system according to the application, the charging profile determination module can be designed to estimate the distance to be traveled by the electric vehicle after the charging process, based on at least one user data record assigned to the user identification. The user data record can be location information, in particular a place of residence and / or work address. The location information can be determined, for example, from a user account. In this embodiment, it is advantageously possible to estimate how far a user may or may want to drive with his electric vehicle. For example, if a user charges their electric vehicle at a charging station at their work place during their working hours, it is

It is particularly important that the battery of the electric vehicle has at least enough energy at the end of its working day that the user can drive from his workplace to his home without having to stop again. A charging curve profile can be determined, for example, in such a way that the battery of the electric vehicle is at least as much after a specific charging process duration Energy means that a user can drive from the charging station at the workplace where the electric vehicle is charging to his home without another stopover. For this purpose, location information (for example geographical information) of the charging station and information about the place of residence (for example geographical information) can advantageously be used to determine the charging curve profile.

As an alternative or in addition, other available user data can preferably be taken into account by the charging profile determination module, such as working time data of the user. In particular, user-specific data (which can be stored in a user account) can contain a user group of the user. For example, it is conceivable that such a user group is assigned to a specific shift work (shift work). This advantageously makes it possible to

Estimated time of departure of a user and thus the duration of the charging process with an increased probability or accuracy. Example: A user is a worker and wants to charge his electric vehicle during his working hours. The shift of the worker extends, for example, from 6:00 a.m. to 2:00 p.m. The worker can thus belong to the "early shift" user group, for example. It is very unlikely that the worker will be using his

Electric vehicle will drive home. The predicted time at which the

In the example, the charging process must be successfully completed, i.e. the estimated charging time, is around 2:00 p.m. Such information can be obtained from

Determination of a charging curve profile can be used.

As has already been described, the charging system can comprise at least one storage module. According to a further embodiment of the charging system according to the application, a plurality of charging station identifiers can be stored in the storage module. At least one charging station identifier, preferably (almost) each charging station identifier, can (in each case) be assigned at least one functional attribute to the parking area assigned to the charging station. For example, the function attribute can indicate the purpose for which the parking space is used (for example for parking an electric vehicle while at work, or the Shopping etc.). The charging profile determination module can be set up to estimate the at least one charging parameter based on the at least one function attribute. The creation of the loading curve profile can be further optimized.

It is understood that two or more memory modules can be provided.

According to a further embodiment of the charging system according to the application, the charging profile determination module can be set up to determine the further charging station used by the user (within a specific predeterminable time period) in at least one previous charging process. The

Charging profile determination module can be set up to determine a distance between the further charging station used in the previous charging process and the first charging station. The charging profile determination module can be set up to estimate the at least one charging parameter based on the determined route. In particular, based on the determined route, it can be estimated how much energy the electric vehicle has used to complete the route. As a result, the energy requirement or the amount of energy of the electric vehicle can be estimated with a higher accuracy during the charging process to be carried out. The creation of the loading curve profile can be further optimized.

A particular charging curve profile can particularly preferably have a plurality of charging curve intervals. The charging system can have at least one

Load curve profile adjustment module include. The

Charging curve profile adaptation module can be arranged or implemented in a charging station, a back-end system of the charging system and / or a computing device which is controlled, for example, by the back-end system. The

Charging curve profile adaptation module can be configured to adapt at least one of the charging curve intervals during the execution of the charging process, based on at least one real-time information. A charging curve interval may preferably have a period of 15 minutes. At the beginning of a As already described above, a charging curve profile is determined during the charging process. For example, after each charging curve interval (or at other times) during the charging process, the previously determined charging curve profile can take into account current real-time information, in particular at least one

Mains network parameters (e.g. mains frequency, harmonic, voltage and / or current) (and possibly further historical data) can be adjusted.

If, for example, after a certain number of charging curve intervals, a difference in the forecast average utilization of the

Supply network and the current load is determined, the charging curve profile determined at the beginning of the charging process can be adapted with regard to the difference found. For example, it is unlikely that a

Workers still come to work after three hours of actually starting work. If, for example, it is determined after three hours that the employee mentioned does not charge his electric vehicle at work (as is usually the case), then those based on the further historical data can be scheduled

Resources are released.

By using the charging curve intervals and in particular the possible adaptation of the charging curve profile, optimal utilization can advantageously be achieved. Advantageously, by using

Charging curve intervals the degree of complexity of the control module are limited, since in one embodiment (always) only a part (the period of a few charging curve intervals) of the charging curve profile can be calculated.

Furthermore, dynamic prioritization of a user during the

Charging process can be used to determine the charging curve profile. A dynamic prioritization of a user can be used if the charging process has several charging curve intervals and, as mentioned above, the charging curve profile of the charging process can be adapted. A dynamic Prioritization can be based on the user-specific data and / or the further historical data and / or the current real-time information.

Example: If, based on user-specific data, it is determined by computer-aided evaluation (e.g. by the loading profile determination module) that a user with a very high probability at 3:00 p.m. the one to be loaded

Wants to use an electric vehicle and at 14:00 the current state of charge of the electric vehicle (or the battery) is not yet sufficient for a desired mobility, then the charging curve profile of the charging process, in particular the charging power, can be changed between 14:00 and 15:00 that the desired mobility can be ensured at 15:00. The user thus receives a high dynamic prioritization value in the example at 2:00 p.m., which can lead to a high proportion of the maximum available power at the charging station being able to be supplied to the electric vehicle of the user in the course of the charging curve profile determination.

Another aspect of the application is a method of operating a

Charging system, especially a previously described charging system. The process includes:

Obtaining a charging station identifier assigned to a first charging station and a user identifier assigned to a user of an electric vehicle to be charged at the first charging station during a charging process, determining, based on the received user identifier and the charging station identifier received, at least one historical charging process data record relating to the user identifier and the charging station identifier,

Determining the charging curve profile for the charging process, at least based on the at least one estimated charging parameter. It goes without saying that the modules and units described above can each be at least partially formed by hardware elements and / or software elements and may be arranged or implemented in a distributed manner.

The characteristics of the charging systems and processes can be freely combined with one another. In particular, features of the description and / or the dependent ones

Claims, even with complete or partial circumvention of features of the independent claims, alone or freely combined with one another, be inventive.

There are now a multitude of possibilities for designing and developing the charging system and the method according to the application. For this purpose, reference is made on the one hand to the claims subordinate to the independent claims, and on the other hand to the description of exemplary embodiments in conjunction with the drawing, in which:

1 shows a diagram with exemplary charging curve profiles according to the prior art,

Fig. 2 is a schematic view of an embodiment of a

Charging system according to the present application,

Fig. 3 is a diagram with exemplary charging curve profiles according to the

present application, and

4 shows a diagram of an exemplary embodiment of a method according to the present application.

The same reference numerals are used below for the same elements. FIG. 2 shows a schematic view of an exemplary embodiment of a

Charging system 200 according to the present application. The charging system 200 includes a plurality of charging stations 216, 218 and at least one

Charging profile determination module 234, for example in the form of a control module, such as a neural network or one based on a machine learning algorithm

Rule model.

In the present case, in particular two charging stations 216, each with a charging point 220, are grouped to form a charging arrangement 212. The loading arrangement 212 and the

Charging stations 216 of the charging arrangement 212 are connected to a first supply power network 228, for example a first local network 228, and are set up at a first location.

A further charging station 218 with three charging points 220 is also arranged as an example. In the present case, the charging station 218 is connected to a further supply network 230, for example a further local network 230, and is set up at a further location.

A charging point 220 can be formed, for example, in the form of a stripped charging cable. Furthermore, a charging station 216, 218 may have a (not shown)

Have charging control or charging technology. In the case of a charging arrangement 212, a common charging control can also be provided.

Each charging station 216, 218 is set up to exchange electrical power with a connected electric vehicle 224, 226 as part of a charging process. In particular, a charging station 216, 218 can deliver electrical power to an electric vehicle 224, 226 for charging a vehicle battery. Each charging station 216, 218 obtains the deliverable electrical energy or power from the respective power network 228, 230. A charging control (not shown), in particular comprising a rectifier, can also be arranged in an electric vehicle 224, 226. In the present case, the charging profile determination module 234 is arranged or implemented in a back-end system 244. It goes without saying that, in other variants of the application, at least this module can also be arranged or implemented (at least partially) in a charging station.

As can be seen, the charging stations 216, 218 are connected to the back-end system 244 (e.g. one or more servers) via a (wireless and / or wired) communication network 232. The respective

Elements 216, 218, 234 have suitable communication modules 222, 240.

Optionally, the charging system 200 can include at least one memory module 236

Authentication module 238 and a charge curve profile adaptation module 242 include. In the present exemplary embodiment, these optional modules 236, 238 and 242 are also implemented in the back-end system 244. Here, too, it goes without saying that with other variants of the registration, at least some of these modules are also (at least partially) in a charging station (or another one)

Computing device) can be arranged or implemented.

Furthermore, it can be seen that at the charging station arrangement 212 or

Charging stations 216 parking areas 246 are provided for electric vehicles 224, 226 to be charged. The further charging station 218 also has parking spaces 248. The charging station 218 can be arranged, for example, in a parking lot 248 of a supermarket and the charging station arrangement 212 in a company parking lot 246.

Each charging station 216, 218 can have a unique, in particular system-wide,

Charging identifier must be assigned. In addition, users can be registered in the charging system and, for example, have a user account in which user data, such as a user identification that uniquely identifies the user, payment data, address data etc. can be stored. The charge identifiers and the registered ones

User IDs can be stored in the memory module 236, for example. Function attributes can be assigned to the charging station identifiers.

For example, the charging station identifiers of the charging stations 216 can (in each case) be assigned the functional attribute “company parking lot” or long-term parking lot and the charging station 218 “supermarket” or short-term parking lot. It goes without saying that other names can be chosen.

In addition, in the memory module 236, a variety of historical user ID dependent and charging station ID dependent

Loading records have been stored. For example, using a recording module (not shown), the actual charging parameters, such as the (maximum or average) charging power of a charging process carried out, the amount of energy transferred during the charging process and / or the charging process duration of the charging process carried out, can be recorded and stored, for example, in a searchable database in the storage module 236 will. In particular, the database can be searchable for user identification and charging station identification.

The functioning and operation of the charging system 200 is described in more detail below with the aid of FIG. 4. FIG. 4 shows a diagram of a

Embodiment of a method according to the present application. In a first step 401, the charging profile determination module 234 can obtain a charging station identifier assigned to a first charging station 216 and a user identifier assigned to a user of an electric vehicle 224, 226 to be charged at the first charging station 216 during a charging process.

For example, this can be done as part of an authorization process before the start of a charging process. During the authorization process or

Authorization process can in particular the charging station 216 with the

Backend system 244 communicate and in particular the authentication module 238 and preferably the charging profile determination module 234 at least that

User identification of the user of the electric vehicle 224 to be charged and the

Provide the charging station identifier of the charging station 216 at which the electric vehicle 224 is being charged. It goes without saying that the user identification and the

Charging station identifier can also be made available to the charging profile determination module 234 in another way. In a next step 402, which may be part of a control algorithm, may be performed by the load profile determination module 234 based on the received one

User ID and the charging station ID received, at least one

historical, concerning the user identification and the charging station identification

Loading process record can be determined. A multiplicity of loading process data records can preferably be determined.

In particular, the loading profile determination module 234 can access the loading operation records stored in the database and those of the received ones

Historical user identification and charging station identification

Load records, particularly the historical records contained therein

Determine loading parameters.

The charging start time of the (requested) charging process can preferably be determined and taken into account when determining the historical charging process data records. In step 403, which may also be part of the control algorithm

at least one loading parameter for the charging process to be carried out, based on the at least one historical charging process data record, in particular the

Variety of historical loading parameters can be estimated. For example, the loading parameters can be estimated according to Table 1. In particular, each historical loading parameter can be assigned a probability of occurrence, which can be taken into account in the estimation. Furthermore, optionally in step 403, the charging profile determination module 234

be configured to estimate the at least one charging parameter based on the state of charge of the battery of the electric vehicle 224 to be charged and / or the at least one functional attribute of the charging station 216.

For example, the charging station 216 can request the state of charge of the battery of the electric vehicle 224 to be charged from the electric vehicle 224 and forward the received state of charge to the back-end system 244. This can also optionally be taken into account in the estimation in step 403.

A previous distance traveled between a charging station that was previously used and the charging station 216 at which charging is to be carried out and / or a distance to be covered after the charging process, for example from the company car park to the user's place of residence, can be taken into account in step 403 .

Then in step 404 the loading curve profile for the one to be carried out

Charging, at least based on the at least one estimated

Load parameters, determined, in particular generated. In particular, a plurality of charging parameters, such as maximum charging power, charging process duration and / or amount of energy to be transmitted, can be estimated and in step 404 for the

Determination of the charging curve profile are taken into account.

After the determination, in particular generation, of the charging curve profile, the charging process can be carried out, at least if the authentication result is positive.

Exemplary charging curve profiles according to the present application on a

Charging station are shown in Figure 3. For a first charging process, a charging curve profile can be based on an estimated charging process duration of at least to to ts 302 can be reserved with a maximum charging power (lower than in FIG. 1). However, due to the longer, reserved charging time

(compared to FIG. 1) the same amount of energy can be reserved for the charging process. This makes it possible for a charging curve profile 304 with a for a second charging process with an estimated shorter charging process duration from ti to t3

(compared to Figure 1 higher) maximum charging power can be reserved. In addition, a charging curve profile 306 with a further maximum charging power can be reserved for a third charging process with an estimated charging process duration from t2 to t4.

As has already been described, it is in the present application

It is advantageously possible that the location information of the charging station can be taken into account with regard to the historical data of the user when determining the charging curve profile. For example, the user can charge his electric vehicle in his employer's company parking lot. With regard to the time available for the charging process, such a charging process is another charging process which is carried out, for example, while shopping in the parking lot of a supermarket.

The historical data of the user to be used to determine the charging curve profile can in particular be filtered with location information. This means that only the historical data of the user at a specific location or at a specific charging station are used for determining the charging curve profile. In a further embodiment, the user-specific data can contain prioritization information of the user. As a result, it is advantageously possible for a charging curve profile to be determined taking into account a prioritization. For example, users who only charge at a charging station for a short period of time can be given higher priority than users who generally charge their electric vehicle at a charging station for a long period of time.

Claims

Patent claims

1. charging system (200) for electric vehicles (224, 226), comprising:

a plurality of charging stations (216, 218), each set up for

Exchanging electrical power with at least one electric vehicle (224, 226),

at least one charging profile determination module (234) set up for:

- obtaining a first charging station (216, 218) of the plurality of

Charging station identifier (216, 218) and a user identifier assigned to a user of an electric vehicle (224, 226) to be charged at the first charging station (216, 218) during a charging process,

- Estimating at least one charging parameter for the charging process, based on the at least one historical charging process data record, and

- Determining the charging curve profile for the charging process, at least based on the at least one estimated charging parameter.

2. Loading system (200) according to claim 1, characterized in that

the charging profile determination module (234) is set up to estimate the maximum permissible charging power for the charging process, the amount of energy for the charging process and / or the charging process duration.

3. Loading system (200) according to claim 1 or 2, characterized in that the at least one estimated charging parameter

Probability of occurrence is assigned, and the charging profile determination module (234) is set up to determine the charging curve profile for the charging process, at least based on the at least one estimated charging parameter and the associated one

Probability of occurrence.

4. Loading system (200) according to one of the preceding claims, characterized

characterized that

the charging profile determination module (234) is set up to determine the at least one historical charging process data record, based on a charging start time of the charging process.

5. Loading system (200) according to one of the preceding claims, characterized

characterized that

the charging profile determination module (234) is set up to estimate the at least one charging parameter based on the state of charge of the battery of the electric vehicle (224, 226) to be charged.

6. Loading system (200) according to one of the preceding claims, characterized

characterized that

the charging profile determination module (234) is set up to estimate the distance to be traveled by the electric vehicle (224, 226) after the charging process, based on at least one assigned to the user identification

User record,

wherein the user data record is location information, in particular one

Home address and / or work address.

7. Loading system (200) according to one of the preceding claims, characterized

characterized that

the charging system (200) comprises at least one storage module (236), a plurality of charging station identifiers being stored in the storage module (236), at least one charging station identifier being at least one Functional attribute of the parking area (246, 248) assigned to the charging station (216, 218) is assigned, and

the charging profile determination module (234) is set up to estimate the at least one charging parameter based on the at least one

Function attribute.

8. loading system (200) according to any one of the preceding claims, characterized

characterized that

the charging profile determination module (234) is set up to determine the further charging station used by the user in at least one previous charging process,

the charging profile determination module (234) is set up to determine a distance between the further charging station (216, 218) used in the previous charging process and the first charging station (216, 218), and

the charging profile determination module (234) is set up to estimate the at least one charging parameter based on the determined route.

9. loading system (200) according to any one of the preceding claims, characterized

characterized that

a particular charging curve profile has a plurality of charging curve intervals, and

the charging system (200) comprises at least one charging curve profile adaptation module (242), configured to adapt at least one of the charging curve intervals during the execution of the charging process, based on at least one real-time information.

10. Method for operating a charging system (200), in particular one

A charging system (200) according to any one of the preceding claims, comprising:

Receiving one assigned to a first charging station (216, 218)

Charging station identifier and a user identifier assigned to a user an electric vehicle (224, 226) to be charged at the first charging station (216, 218) during a charging process,