Method and system for estimating a waiting time for a free charging place at a charging station for electric vehicles

Abstract

The invention relates to a method and a system for determining an estimated waiting time for at least one free charging place (120) of at least one charging station (100) for an electric vehicle (50) approaching the at least one charging station (100), the method comprising the steps of: detecting electric vehicles (50) in a vicinity of a geolocation of the at least one charging station (100), which comprises one or more charging places (120) for charging an energy storage device of electric vehicles (50), in order to determine a number of electric vehicles in said vicinity; determining the occupancy level of the at least one charging station (100); outputting a waiting time of less than or equal to zero if the one charging place, or at least one of the several charging places (120), is currently unoccupied; and otherwise: determining charging request probabilities and estimated charging durations for the electric vehicles located in the vicinity of the at least one charging place (120), deriving the estimated waiting time for the at least one free charging place (120) for an electric vehicle (50) newly approaching the vicinity (130) based on the determined number of electric vehicles (50) in the vicinity (130), their charging request probabilities, and estimated charging durations; and outputting the estimated waiting time.

Description

[0001] Description

[0002] Method and system for estimating a waiting time for a free charging space at a charging point for electric vehicles

[0003] The invention relates to a method for determining the probability of a charging request from approaching electric vehicles for at least one charging point. Furthermore, the invention relates to a method for predicting a waiting time for an electric vehicle to charge electrical energy into a storage device at a charging point.

[0004] For electric vehicle owners who need to charge their electric vehicle's storage unit before starting a journey and / or during breaks, it is advantageous to be able to determine the utilization of publicly accessible charging points as accurately as possible. In particular, it is interesting to know how long the waiting time is at a particular charging point before their electric vehicle can be charged.

[0005] A charging point is defined here as charging infrastructure at a specific geolocation. A charging point can comprise multiple charging stations for electric vehicles, where electrical energy can be simultaneously charged into an electric vehicle's storage unit. The infrastructure unit that supplies a charging station is also referred to as a charging station. A charging point can therefore comprise multiple charging stations.

[0006] CN 114954129 discloses a method and apparatus for recommending charging station information. The method includes the steps of: responding to a recommendation request input by a user and determining the first time and the first remaining electric power of a current vehicle traveling to each charging station that matches a travel route; acquiring charging queue information of each charging station at the first time from a cloud server; and sorting the charging stations according to the first remaining electric power and the charging queue information and recommending charging station information according to a sorting result. According to the technical scheme of the described embodiment, reasonable travel charging suggestions can be provided by integrating various factors, and a user's charging experience can be improved.DE10 2022 101 736 A1 describes a method for operating at least one charging point for charging electric vehicles, in which (a) information is provided about an expected start of a charging option that is next available at the at least one charging point, wherein the expected time is estimated depending on a number of electric vehicles registered in a queue for charging at this at least one charging point; (b) an offer is made to purchase a ticket for a place in the queue; (c) if a ticket is purchased, the ticket holder is assigned a ticket ID that corresponds to the current place in the queue; (d) the ticket holder is provided with updated information about an expected start of a charging option that corresponds to his place in the queue.

[0007] DE10 2022 115 122 A1 describes a method for determining the number of electric vehicles waiting for a free charging point at a charging infrastructure with at least one charging point, wherein the charging infrastructure is located within a geofence area delimited by a geofence. In the method, an electric vehicle with a geofencing function is automatically classified as waiting for a charging point if all charging points are occupied, at least one charge state of a drive battery of this electric vehicle fulfills an associated charge state criterion, and at least one movement parameter of this electric vehicle fulfills an associated movement criterion. Furthermore, a charging infrastructure with at least one charging point for charging electric vehicles, which is located within a geofence area delimited by a geofence, is described, wherein the charging infrastructure is configured to carry out the described method.

[0008] US 20170276503 A1 relates to a big data-based method or system for recommending charging stations for electric vehicles with the shortest charging waiting time, comprising a travel information receiving unit for receiving a charging station search request and information about the estimated discharge time and a current location of an electric vehicle; a charging station information receiving unit for receiving power consumption data from charging stations in real time; a charging waiting time calculating unit for receiving the power consumption data from the charging station information receiving unit and calculating the charging waiting time of the charging stations in response to a charging station search request based on their power consumption;and an optimal charging station providing unit for receiving the information about the estimated discharge time and the current location from the travel information receiving unit and for receiving the charging waiting time from the charging waiting time calculating unit, and for providing information about at least one optimal charging station that can be reached within the estimated discharge time based on the current location and can recharge the vehicle in the shortest time.;

[0009] KR 20190102589 A discloses a mobile terminal and a method for guiding a charging station of the mobile terminal. According to one embodiment, the method for guiding a charging station of the mobile terminal comprises the steps of: detecting a connection with a vehicle in response to boarding the vehicle; detecting a charging station guide request; receiving information about chargeable charging stations from a server in response to a charging station guide request; and displaying at least one filtered and searched charging station information item on a navigation screen based on a learned user behavior pattern and information related to the vehicle.

[0010] The existing methods do not allow for a reliable prediction of charging point utilization and / or waiting time in every situation. Charging points are generally not installed remotely from other infrastructure. For example, charging points are located in the parking lots of retail stores or restaurants, etc. In order to be able to make statements about the potential utilization of charging points, it is desirable to know how likely it is that an approaching electric vehicle will want to charge at the charging point.

[0011] The invention is based on the object of improving a prediction of an expected waiting time for a free charging space at a charging point for an approaching electric vehicle using as little information as possible for at least one, preferably a plurality of, charging points.

[0012] The invention is achieved by a method for determining an estimated waiting time for at least one free charging space of at least one charging point with the features of patent claim 1 and a system with the features of patent claim 10. Advantageous embodiments emerge from the subclaims.

[0013] Basic idea of ​​the invention

[0014] The invention is based on the idea that not only the current utilization of the charging point is evaluated, but also the number of electric vehicles located in the immediate vicinity of a geolocation of the charging point is taken into account. However, since not every electric vehicle in the immediate vicinity is actually waiting for a free charging slot at the charging point, a charging request probability is taken into account for each electric vehicle, which indicates how likely a charging request is for each electric vehicle.

[0015] Definitions

[0016] As already stated above, a charging point is considered to be the entirety of a charging infrastructure at a geolocation.

[0017] A charging point is defined as the physical parking space for an electric vehicle where the parked electric vehicle can be charged with electrical energy. If a charging point has multiple physical parking spaces for electric vehicles where an electric vehicle can charge its electrical storage device, but only a portion of these can be used for charging at the same time, the number of physical parking spaces where an electric vehicle can be charged simultaneously indicates the number of charging spaces at the charging point.

[0018] An infrastructure unit between which an energy transmission connection, such as a cable connection or an inductive connection, is established for charging the electric vehicle is referred to as a charging station. Those skilled in the art will be aware that there are infrastructure units to which, for example, several charging cables can be connected simultaneously. If charging processes can be carried out simultaneously via these multiple cables, the infrastructure represents a plurality of charging stations, the number of which corresponds to the number of charging processes that can be carried out simultaneously. For the sake of simplicity, the following description assumes that each charging location is assigned exactly one infrastructure unit, referred to as a charging station.

[0019] An electric vehicle is considered to be a vehicle that has an electrical, externally rechargeable storage device in which electrical energy can be stored, with which an electric drive motor of the vehicle can be operated.

[0020] In particular, passenger cars with at least one electric drive motor that is supplied with electrical energy by an externally rechargeable electrical storage device installed in the passenger car are considered electric vehicles. Electric vehicles also include hybrid vehicles with an electric drive motor and an externally rechargeable electrical storage device, which additionally have at least one non-electrically operated machine that is either used directly to drive the hybrid vehicle or drives a generator that generates electrical power for the electric drive motor.

[0021] A proximity zone around a geolocation is a defined, i.e., fixed, area in which the geolocation is located. The zone is defined or specified in such a way that electric vehicles waiting to charge at the charging point are located in the proximity zone around the geolocation of the charging point. For example, if the charging point is located at the edge of a large parking lot, the proximity zone includes at least part of or even the entire parking lot.

[0022] Preferred embodiments

[0023] In particular, a method is provided for determining an estimated waiting time for at least one free charging space of at least one charging point for an electric vehicle approaching the at least one charging point, which method comprises the steps:

[0024] Detecting electric vehicles in a close range around a geoposition of the at least one charging point, which comprises one or more charging stations for charging a storage unit of electric vehicles, in order to determine a number of electric vehicles in the one close range,

[0025] Determining the utilization of at least one charging point;

[0026] Outputting a waiting time of less than or equal to zero if one or at least one of the several charging locations is currently unoccupied; and otherwise

[0027] Determining charging request probabilities and estimated charging times for the electric vehicles located in the vicinity of at least one charging point,

[0028] Deriving the estimated waiting time for at least one free charging point for an electric vehicle newly approaching the local area based on the determined number of electric vehicles in the local area, their charging request probabilities and estimated charging times; and

[0029] Display the estimated waiting time.

[0030] The electric vehicles in the vicinity of the charging point are taken into account when determining the estimated waiting time. Since not every electric vehicle in the vicinity actually wants to charge its storage at the charging point, a charging request probability is used for the electric vehicles in the vicinity to determine the number of electric vehicles that are likely to want to charge their storage at the charging point. The charging request probability for an individual electric vehicle takes values ​​between 0 and 1. 0 indicates that the electric vehicle does not want to charge under any circumstances. 1 indicates that the electric vehicle definitely wants to charge at the charging point.A sum of the charging request probabilities of the electric vehicles in the local area thus results in a dedicated number of electric vehicles in the local area of ​​the charging point that want to charge at the charging point according to the calculated probability.

[0031] If one assumes an equal charging request probability for all electric vehicles in the local area, which is a good assumption if one does not have further information about the individual electric vehicles regarding their energy management, the number of electric vehicles that are in the local area of ​​the charging point and are there to charge their energy storage at the charging point is the product of the charging request probability that applies to an electric vehicle and the number of electric vehicles in the local area.

[0032] In order to estimate the waiting time, it is also necessary to take into account the time that these electric vehicles will need to charge at the charging points.

[0033] Again, if no further information is available regarding the energy management of individual electric vehicles, an assumed average charging time for all electric vehicles can be used. The product of the number of estimated electric vehicles that want to charge their energy storage at the charging point and the assumed average charging time thus determines the time required to charge the electric vehicles that are already in the vicinity of the charging point. For a charging point with multiple charging stations, it is useful to divide this calculated time by the number of available charging stations to determine the estimated waiting time.

[0034] This estimate can be further improved if information is available about the electric vehicles currently charging at the charging station(s) or charging processes. A conservative estimate suggests increasing the specified waiting time by an average charging time. This assumes the worst-case scenario that charging processes begin at the available charging station(s) at the time the estimate is made. Thus, an average charging time elapses until the charging station(s) become free and one of the electric vehicles already waiting in the vicinity, which are crucial for the waiting time estimate, can begin charging.

[0035] To determine the estimated waiting time, the number of electric vehicles already "waiting" at the charging point and the expected charging time of those electric vehicles already "waiting" are of interest. In order to be able to make useful statements without knowing a specific charging request for each electric vehicle in the immediate vicinity and / or without knowing the amount of energy to be charged and / or without knowing the charging power available during the charging process, previously determined information, namely an assumed charging request probability and / or an average charging time, is retrieved, for example, from a storage device or database.

[0036] This data can be determined by observing and evaluating electric vehicles approaching or in the vicinity of the charging point and their charging behavior at the charging point and stored in a memory or database.

[0037] This information can therefore be determined by the entity that also determines the estimated waiting time, or it can be provided by another entity, such as a vehicle manufacturer or similar.

[0038] For both the collection of this data and the determination of the estimated waiting time, the local area is defined around the geolocation of the charging points. To determine the number of electric vehicles in the local area, the entry and exit of electric vehicles into and out of the local area is preferably recorded.

[0039] The electric vehicles are preferably designed such that a control unit of the electric vehicle monitors whether a position determined by the electric vehicle indicates entry into the near field and / or exit from the near field. The geoposition of the at least one charging point required for this purpose, as well as the information for determining the near field, are transmitted to the electric vehicles, for example, and / or stored in their memory during manufacture and / or maintenance. The control unit in the electric vehicle is preferably coupled to a navigation device in the electric vehicle, which generally comprises a satellite navigation device, in order to determine its own position. If entry into the near field and / or exiting the near field is detected, the electric vehicle transmits this information, preferably via a wireless communication device.By recording this information from the electric vehicles, it is possible in one embodiment to determine the number of electric vehicles in the vicinity of the charging point.

[0040] One embodiment provides that the number of electric vehicles in the vicinity is determined by evaluating information transmitted by the electric vehicles when entering and exiting the vicinity, and the number of electric vehicles in the vicinity is determined from the difference between the information indicating entry and the information indicating exit.

[0041] Other embodiments may determine the presence and number of electric vehicles in the vicinity in other ways. For example, camera images may be evaluated, induction sensors may be evaluated, and / or other sensors may be used to determine this information.

[0042] Based on the information transmitted by the electric vehicles, the facility that estimates waiting times can determine the number of electric vehicles in the vicinity of the charging point.

[0043] If the electric vehicles also transmit information indicating the start and end of charging, the number of charging processes and the charging durations can be determined. The charging durations can be averaged over a large number of charging processes to determine an average charging duration. As mentioned above, this is preferably stored in a memory or database. This average charging duration can be continuously updated.

[0044] The charging request probability can be derived from the number of electric vehicles in the vicinity at the start of each charging process. Thus, if the start of charging is known, the charging request probability can also be determined. In one embodiment, the previously determined charging request probabilities were determined and are (currently further updated) by determining, at the start of a charging process, a reciprocal of the electric vehicles in the vicinity of the charging point less the electric vehicles already charging. This means that the electric vehicles in the vicinity whose charging process has already begun or is completed are preferably not included in the number of electric vehicles in the vicinity that potentially want to charge at the charging point.

[0045] The values ​​thus determined for a charging request probability can be averaged.

[0046] In this case, averaging preferably takes place over time periods.

[0047] In one embodiment, the average charging time for an electric vehicle is determined based on a plurality of charging processes from the sum of charging times divided by the number of the plurality of charging processes.

[0048] Preferably, the charging request probability and / or the average charging duration are determined and stored depending on the time of day and day of the week. This means that a charging request probability and / or average charging duration is and / or is determined for specific time periods of the day. Preferably, values ​​for different days of the week, for example, for weekdays, Saturdays, Sundays and public holidays, are also determined and stored for the different time periods of the day. Thus, a set of charging request probabilities and / or average charging durations is preferably determined for different time periods of the day and different days of the week or weekday groups (e.g., weekdays). This allows the charging request probability of the electric vehicles in the vicinity of the charging point and / or their average charging duration to be better estimated.At night, after the shops in the vicinity of the charging point have closed and / or after the leisure facilities and / or restaurants in the vicinity have closed, the probability of an electric vehicle entering the vicinity of the charging point requesting charging is much higher than during the shops' or restaurants' business hours. While during business hours, electric vehicles are often accessed by people visiting the shops, leisure facilities, and / or restaurants, at night, the area is visited almost exclusively by electric vehicles that actually want to charge their energy storage devices at the charging point.

[0049] In one embodiment, time-of-day information and / or day-of-week information are recorded for the desired charging probabilities and / or the average charging times and stored together with the desired charging probabilities and / or the average charging times, so that the desired charging probability and / or the average charging time can be retrieved depending on the time of day and day of the week. When retrieving the desired charging probability and / or the average charging time, the current time of day and the current day of the week or a current day type are used to retrieve the corresponding values. Possible day types include, for example: working days, Sundays, public holidays, Saturdays, school days, vacation days, rainy days, summer days, etc. The day type can therefore depend on other parameters such as the weather, the time of year, etc.

[0050] If the device for determining the estimated waiting time has access to information from the charging point, the average charging time can also be determined based on the information generated in the charging infrastructure and stored in the memory or database.

[0051] The prediction of the estimated waiting time can be improved if electric vehicles entering the local area transmit information about their energy management. Information about energy management is understood to be all information relating to the consumption and charging of the stored electrical energy. This includes, for example, the current state of charge, the desired state of charge, the energy storage capacity, possible charging power, but also the planned route, in particular its length, planned charging breaks along the planned route, and also a specific charging intention or a conditional charging intention. A specific charging intention is understood to be an explicit desire to charge the energy storage device at a specific charging point. A conditional charging intention is a charging request that is dependent on one or more conditions.For example, the desire to charge electrical energy may only exist if the electrical energy at the charging point is offered at an energy price that is less than or equal to a specified energy price threshold. The condition would then be that the energy price is less than or equal to the specified energy price threshold. Another possible condition could be the expected waiting time for a free charging space. For example, the desire to charge could only exist if a charging space is available immediately without waiting. A variety of other, even complex, linked conditions are possible.

[0052] In one embodiment, energy management information of the electric vehicle transmitted by at least one of the electric vehicles when entering the nearby area is recorded and used to adjust the retrieved charging request probability and / or the average charging time. The information can include one or more pieces of information about the energy management of the electric vehicle. For this electric vehicle, the charging request probability and / or its charging time can then be improved compared to the retrieved values. If, for example, information is available for some of the electric vehicles about the current charge state of the energy storage device, the charging power with which the energy storage device can be charged, and the capacity of the energy storage device, a charging time at the charging point can be calculated if its available charging power is known.A potential charging time can therefore be determined for these vehicles. Summing the charging times determined in this way and dividing them by the number of electric vehicles for which the charging time can be determined based on the energy management information yields an average charging time for these electric vehicles. When determining the average charging time, the desired charging probability determined based on the energy management information and / or the average charging time determined based on the energy management information can be used for some electric vehicles, and the retrieved desired charging probability and / or the retrieved average charging time can be used for the remaining vehicles.

[0053] Alternatively or additionally, in some embodiments, it is possible that for electric vehicles in the local area for which a charging request probability can be derived from the energy management information, this individual charging request probability is used instead of the retrieved previously determined charging request probability when deriving the waiting time.

[0054] Alternatively or additionally, it is possible that for an electric vehicle in the local area for which an individual charging request probability above a threshold value has been determined on the basis of its recorded energy management information and an expected charging time can be derived on the basis of the energy management information, this individual charging time is used instead of the previously determined average charging time for this vehicle when deriving the waiting time.

[0055] Furthermore, a system for predicting the waiting time for an electric vehicle approaching a charging point is provided, comprising a vehicle detection device configured to detect electric vehicles in a vicinity of the charging point, a retrieval device configured to retrieve at least one charging request probability for electric vehicles located in the vicinity of the charging point and at least one average charging time for electric vehicles at the charging point, which are determined in advance; a charging point utilization detection device for detecting a current utilization of the charging point;and a prediction device which, if the charging point utilization detection device detects that at least one charging location of the charging point is free, is designed to predict a waiting time of less than or equal to zero, and otherwise to calculate a waiting time based on the number of electric vehicles in the vicinity detected by the vehicle detection device and the at least one charging request probability and the at least one average charging time of the charging point supplied by the retrieval device, by calculating the number of vehicles intending to charge and multiplying this by the at least one average charging time.

[0056] Preferably, the vehicle detection device comprises a communication device by means of which information is detected from electric vehicles entering and leaving the vicinity of the charging point.

[0057] Further preferably, the vehicle detection device is designed

[0058] to record energy management information of the vehicles, and the prediction device is designed to use the energy management information to specify the charging request probability and / or a predicted charging duration at least for individual or some of the vehicles and to take these into account when determining the waiting time.

[0059] The invention is explained in more detail below with reference to a drawing. Herein:

[0060] Fig.1 is a schematic of the environment of a charging point for electric vehicles.

[0061] Fig. 1 schematically illustrates an environment 150 of a charging point 100. In the illustrated embodiment, the charging point 100 comprises three charging bays 120, each of which is assigned a charging column 110. In the situation illustrated in Fig. 1, all three charging bays 120 of the charging point 100 are each occupied by an electric vehicle 50. The electric vehicles 50 at the charging bays 120 are each connected to their corresponding charging column 110 via a charging cable 115 in order to charge electrical energy into their respective storage devices (not shown).

[0062] In a local area 130 defined around the charging point 100, there are parking spaces 240 in which additional electric vehicles 50 are parked. The local area 130 encompasses an area around the geoposition of the charging point 100 in which the electric vehicles 50 are potentially located, waiting for a charging process at the charging point 100.

[0063] It is interesting to be able to estimate how long an electric vehicle 50 approaching the proximity area 130 has to wait until it can charge its electrical storage unit (not shown) at the charging point 100.

[0064] This depends, on the one hand, on how long the remaining charging times are for the electric vehicles 50 located at the charging stations 120. A control device 180 of the charging point 100 can often estimate the individual remaining charging times of the electric vehicles 50 at the charging stations 120. For this purpose, information exchanged between the electric vehicles 50 and the charging stations 110, current curves of the charging current, etc., can be evaluated. If no such information is available, an average charging time can be assumed as the best estimate, which is recorded based on previously completed charging processes for electric vehicles 50 at the charging point 100 and stored in a database 170.

[0065] However, since there are other electric vehicles 50 in the parking spaces 240 in the local area 130 in the situation shown, there may also be a charging request from these electric vehicles 50. The waiting time of an electric vehicle 50 approaching the local area 130 for a free charging space therefore also depends on how many of the electric vehicles 50 in the local area 130 have a charging request.

[0066] In the illustrated embodiment, other infrastructure facilities are located in an environment 150 of the charging point 100, for example, a retail store 210, a restaurant 220, a leisure facility 230, and a service provider 250. This list is merely exemplary. Therefore, the electric vehicles 50 parked in the parking spaces 240 do not necessarily all have to wait for a charging space 120 to become available. Rather, it is quite possible that the users of these electric vehicles 50 are visiting one of the aforementioned infrastructure facilities and there is no desire to charge the corresponding electric vehicle 50.

[0067] In order to be able to estimate the waiting time, it is helpful to determine a charging request probability for the 50 electric vehicles in the immediate vicinity.

[0068] Without further specific knowledge about the energy management of the individual electric vehicles 50, a charging request probability can be assumed for the electric vehicles 50, which has been determined for past periods. For such a determination, the electric vehicles 50 in the local area 130 are recorded. In addition, the number of charging processes taking place at the charging point is evaluated. From this, the charging request probability of individual electric vehicles 50 in the local area 130 can be derived. For many charging points, especially those that have other infrastructure facilities in the vicinity, such as a retail store 210, a restaurant 220, a leisure facility 230, and / or a service provider, the charging request probability for electric vehicles 50 located in the local area 130 of the charging point 100 can vary greatly depending on the time of day and / or day of the week.At times of day, for example at night, when the infrastructure facilities in the area are closed, a.

[0069] The probability that an electric vehicle 50 approaching the charging point 100 will also want to charge its energy storage device at the charging point is significantly higher than, for example, during peak business hours of the retail store 210 located in the vicinity 150.

[0070] The charging request probability is therefore preferably recorded based on the time of day and / or day of the week. Day types such as weekdays, Saturdays, Sundays, and public holidays can also be grouped together, and charging request probabilities can be recorded and stored separately for the different weekday groups, preferably also based on the time of day. Depending on the current day of the week and the current time of day, a charging request probability can thus be retrieved from the database 170 and used to assess the charging request of the electric vehicles 50 located in the local area 130.

[0071] In order to estimate the number of electric vehicles 50 waiting to charge the energy storage device, it is first necessary to determine the number of electric vehicles 50 located in the vicinity 130. This can be done either via sensors 140 that monitor the entry and exit of electric vehicles 50 into and out of the vicinity 130 and determine the number of electric vehicles 50 located in the vicinity 130. Suitable sensors 140 can be light barriers, induction thresholds, camera systems, etc. Since modern electric vehicles are also equipped with electronic communication means 58, one embodiment provides for the electric vehicles 50 to wirelessly transmit information when entering the vicinity 130 around the charging point 100 and when exiting the vicinity 130 of the charging point 100. This transmission takes place, for example, to a communication device 160 of the charging point 100.For this purpose, the near area 130 defined around the geoposition of the charging point 100 is transmitted, for example, to the electric vehicles 50, which then store it in a data memory 56 of a control unit 54. The control unit 54 is coupled, for example, to a navigation device 52 of the electric vehicle 50, which is capable of determining the electric vehicle 50's own position at any time. This can be implemented, for example, using a satellite navigation receiver (not shown). If the control unit 54 determines that the own position has entered the near area 130 of the charging point 100, information about this is transmitted to the communication device 160. Similarly, upon leaving the near area 130, corresponding information is transmitted to the communication device 160 of the charging point 100. The charging point 100 is thus able to determine the number of electric vehicles 50 located in the near area 130.Furthermore, the control device 180 of the charging point 100 determines an average charging time, for example based on the charging processes that have taken place in the past. This evaluation can also be carried out depending on the day of the week, by weekday groups, and additionally depending on the time of day. Corresponding average charging times are also stored in the database 170. If a waiting time is to be predicted for an electric vehicle 50 approaching the local area 130, the control unit 180 of the charging point 100 first checks whether one of the charging stations 120 is occupied. If this is the case, the estimated waiting time for an electric vehicle approaching the local area 130 is zero. If several charging stations are unused, a waiting time less than zero can also be output to indicate this.The size of the output negative number can, for example, be selected depending on the average charging time and can be specified as the product of the number of free charging spaces multiplied by the average charging time. For example, if the average charging time at the charging point is 30 minutes and two charging spaces 120 are currently unoccupied, the estimated waiting time could be "-1 hour." Other embodiments can specify a negative value corresponding to the number of free charging spaces. In this embodiment, a value of "-2 spaces" would be output as the estimated waiting time.

[0072] If, however, all charging stations at the charging point are currently occupied, the estimated waiting time for an electric vehicle 50 approaching the local area 130 is determined based on the number of electric vehicles 50 located in the local area 130. The electric vehicles 50 located at charging stations 120 are preferably disregarded, as they are no longer waiting for the charging process but have already begun their charging process. The number of remaining electric vehicles 50 in the local area 130 is used to determine the number of electric vehicles 50 that have a charging request. For this purpose, the charging request probability retrieved from the database 170 is used for each electric vehicle, without precise knowledge of the energy management of the individual electric vehicles.The number of waiting electric vehicles can thus be determined based on the product of the number of electric vehicles in the local area (minus the electric vehicles already charging) and the charging request probability. Furthermore, the waiting time is determined by how long these electric vehicles will require for their respective charging process. Without further knowledge about the energy management of the individual electric vehicles 50, an average charging time is assumed, which is also determined based on past charging processes and stored in the memory of the database 170. Multiplying the number of electric vehicles 50 determined waiting for a charging station 120 by the average charging time yields a time that indicates how long the charging processes of the electric vehicles already waiting with the determined charging request will take.If multiple charging stations 120 are available at a charging point 100, this estimated total charging time is divided by the number of available charging stations 120 to obtain a good estimate of the waiting time for a free landing station 120 for an electric vehicle 50 approaching the proximity area 130. In the example shown, a division by 3 takes place.

[0073] This estimate can be improved with additional information. In particular, information about the remaining duration(s) of the charging processes at charging point 100 can be used and added to the previously determined total waiting time in the calculation. Otherwise, it is advantageous to add an average charging time for the currently charged electric vehicles to the predicted waiting time.

[0074] The estimation can also be significantly improved if the electric vehicles 50 wirelessly transmit additional information concerning the energy management of the individual electric vehicle 50 when entering the near field 130. This information can include a current charge level of the energy storage device, a target charge level of the energy storage device, a capacity of the energy storage device, possible charging power, but also information about a planned route and / or planned charging stops along the planned route.

[0075] Based on this transmitted data, the charging request and, if applicable, also the charging duration of individual electric vehicles 50 can be more precisely estimated. For example, the route information may indicate that charging point 100 is intended as a stopping point for charging the energy storage device. From this, it can be deduced that this electric vehicle 50 has an unconditional charging request, so that the charging request probability for this electric vehicle is one. This assumes that the charging request probabilities lie between zero and one. Based on the current charge state of the energy storage device and a possibly specified desired target charge state, as well as the capacity of the energy storage device, together with the available charging power with which the energy storage device of the electric vehicle 50 can be charged, the charging duration for this electric vehicle 50 can also be precisely estimated.

[0076] In a further development, it is thus provided that for electric vehicles 50 from which energy management information is transmitted, this energy management information is used to, if necessary, specify the desired charging probability and / or the charging duration compared to the values ​​stored in the memory of the database 170. Electric vehicles 50 whose energy storage is charged to more than a threshold value, for example 70% or 80%, have a very low desired charging probability. Electric vehicles 50 whose energy storage is charged to only 20% or less, on the other hand, have a much higher desired charging probability than the average desired charging probability. Depending on the state of charge and a possibly specified desired state of charge, the desired charging probability retrieved from the memory of the database 170 can thus be increased or decreased for these electric vehicles.If necessary, the charging request probability can also be determined independently of the stored charging request probability for these electric vehicles using the energy management information.

[0077] It will be understood by those skilled in the art that only an exemplary embodiment has been described here. Further embodiments of the invention are possible. In the embodiment described here, both the charging request probabilities and the average charging times are determined by the charging point 100 or its control unit 180. The charging point also determines the expected waiting time for an electric vehicle 50 approaching the proximity area 130. In other embodiments, the data such as the average charging time and the charging request probability can also be determined and provided by another entity. For example, this data can be determined by an entity that operates a fleet management system.Assuming that users' charging behavior is independent of the specific manufacturer of the electric vehicle, a vehicle manufacturer can at least determine the probability of a charging request based on information obtained from the electric vehicles it has manufactured. If the distribution of electric vehicles sold by a vehicle manufacturer is representative of all electric vehicles on the market with regard to the various energy storage sizes and charging times, an average charging time at a specific charging point can also be determined based on the vehicle manufacturer's data. However, adjustments to such data are also possible, taking into account deviations between the manufacturer's vehicle fleet and the total number of electric vehicles on the market, for example with regard to storage sizes and possible charging capacities.

[0078] The waiting time determined by the charging point 100 for an electric vehicle 50 approaching within the vicinity 130 can be provided by the charging point 100, for example, transmitted to electric vehicles 50 in the vicinity or to services available as navigation aids that are accessible via the Internet. Electric vehicles that have access to these services can thus estimate at any time how long the waiting time at the corresponding charging point 100 is likely to be. In the illustrated embodiment, the charging point also simultaneously forms a system 400 for predicting the waiting time for an electric vehicle 50 approaching a charging point 100. The control unit 180, together with the sensors 140 and / or the communication device 160, comprises a vehicle detection device 410.It further provides a retrieval device 420 that retrieves charging request probabilities and average charging times from the database 170, preferably depending on the time of day and day of the week. Furthermore, the charging point comprises a charging point utilization detection device 430, which is implemented in the controller of the charging point 100. A prediction device 440 is also implemented in the control unit 180. The estimated waiting time is output, for example, transmitted via the communication device 160 to electric vehicles or internet services (not shown). The charging point 100 can also have an output device 450, for example in the form of a screen, on which the determined waiting time is displayed.

[0079] - I9

[0080] List of reference symbols

[0081] Electric vehicles

[0082] Navigation device

[0083] control unit

[0084] memory

[0085] means of communication

[0086] Charging point

[0087] Charging station

[0088] Loading bays

[0089] Close range

[0090] Sensors

[0091] Vicinity

[0092] Communication device

[0093] database

[0094] control unit

[0095] trading business

[0096] catering business

[0097] Leisure facility

[0098] Parking spaces

[0099] Service companies

[0100] Waiting time estimation system

[0101] Vehicle detection device

[0102] Retrieval facility

[0103] Charging point utilization detection device

[0104] Prediction device

[0105] Output device

Claims

Patent claims 1. A method for determining an estimated waiting time for at least one free charging space (120) of at least one charging point (100) for an electric vehicle (50) approaching the at least one charging point (100), comprising the steps: Detecting electric vehicles (50) in a close range around a geoposition of the at least one charging point (100), which comprises one or more charging stations (120) for charging an energy storage device of electric vehicles (50), in order to determine a number of electric vehicles in the one close range, Determining the utilization of at least one charging point (100), Outputting a waiting time of less than or equal to zero if the one charging location (120) or at least one of the plurality of charging locations (120) is currently unoccupied; and otherwise Determining charging request probabilities and estimated charging times for the electric vehicles located in the vicinity of the at least one charging station (120), deriving the estimated waiting time for the at least one charging station (120) or at least one of the plurality of charging stations to be free for an electric vehicle (50) newly approaching the vicinity (130) based on the determined number of electric vehicles (50) in the vicinity (130), their charging request probabilities and estimated charging times; and Display the estimated waiting time.

2. Method according to claim 1, characterized in that the number of electric vehicles (50) located in the near area (130) is determined by evaluating information transmitted by the electric vehicles (50) when entering the near area (130) and exiting the near area (130), and the number of electric vehicles (50) located in the near area (130) is determined from the difference between the information indicating entry and the information indicating exit.

3. Method according to claim 1 or 2, characterized in that the charging request probabilities for at least some of the electric vehicles (50) are retrieved from a database or a memory in which charging request probabilities determined previously for the at least one charging point (120) are stored.

4. Method according to one of the preceding claims, characterized in that the charging request probabilities for at least some of the electric vehicles (50) are retrieved from a database or a memory in which previously determined charging request probabilities for the at least one charging point (120) are stored.

5. Method according to one of the preceding claims, characterized in that the estimated charging time for at least some of the electric vehicles (50) is retrieved from a database (170) or a memory in which previously determined average charging times for the at least one charging station (120) are stored. 6 Method according to one of claims 3 to 5, characterized in that energy management information of the electric vehicle (50) transmitted by at least one of the electric vehicles (50) when entering the near area (130) is detected, and this information is used to adapt the retrieved charging request probability and / or adapt the average charging time.

7. The method according to claim 6, characterized in that for electric vehicles (50) in the local area (130) for which a charging request probability can be derived from the energy management information, this individual charging request probability is used instead of the retrieved previously determined charging request probability when deriving the waiting time.

8. The method according to claim 6 or 7, characterized in that for an electric vehicle (50) in the local area, for which an individual charging request probability above a threshold value is determined on the basis of its recorded energy management information, and an expected charging time can be derived on the basis of the energy management information, this individual charging time is used instead of the retrieved previously determined average charging time for this when deriving the waiting time.

9. Method according to one of the preceding claims, characterized in that the previously determined charging request probabilities were and / or are determined by, at the start of a charging process, a reciprocal of the in the vicinity (130) of the charging point (100) minus the electric vehicles (50) already charging.System (400) for predicting the waiting time for an electric vehicle (50) approaching a charging point (100), comprising: a vehicle detection device (410) which is designed to detect electric vehicles (50) in a close range around the one charging point, a retrieval device (420) which is designed to retrieve at least one charging request probability for electric vehicles (50) located in the close range of the charging point and at least one average charging time for electric vehicles (50) at the charging point, which are determined in advance in time; a charging point utilization detection device (430) for detecting a current utilization of the charging point; and a prediction device (440) which is designed to predict a waiting time of less than or equal to zero if the charging point utilization detection device (420) detects that at least one charging space (120) of the charging point (100) is free, and otherwise, based on the... Vehicle detection device (410) detected number of electric vehicles (50) in the vicinity and the at least one charging request probability supplied by the retrieval device (420) and the at least one average charging time of the charging point, to calculate a waiting time by calculating the number of electric vehicles (50) intending to charge and multiplying it by the at least one average charging time, and an output device (450) for outputting the estimated waiting time.

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