Procedure for coordinating a charging process

Abstract

The invention relates to a method (1) for coordinating a charging process of an electrically powered motor vehicle. The invention is characterized in that location-specific capacities (3) in the power grid are calculated along a planned route (2), whereby a charging stop is planned in an area with sufficient capacity.

Description

[0001] The invention relates to a method for coordinating a charging process.

[0002] With increasing renewable power generation, which largely depends on weather conditions such as wind and solar power, the power grid is subject to local fluctuations. This can lead to overcapacity or undercapacity in the power grid, which must be balanced. A so-called smart grid approach, for example, is known from the state of the art.

[0003] As the number of electric vehicles increases, so does the need for more power capacity. Therefore, it makes sense to control and coordinate the charging process of electric vehicles.

[0004] DE 10 2016 202 816 A1 discloses a method for controlling the electric charging of a group of vehicles. The group of vehicles can communicate with a network operator's server via a central control system. A charging time window, a departure time, and a target charge level can be specified in advance for one or more vehicles in the group. Likewise, a cost value for the charging time window can be specified based on a cost function.

[0005] DE 10 2017 211 148 A1 describes another method for coordinating charging processes for multiple electric vehicles. The vehicles are parked at different charging stations, with planning data relating to the respective charging process being received from each vehicle via a central control device. Based on this, an individual charging plan can be generated, and the respective site plans can be coordinated. This allows a threshold for capacity in the charging network to be maintained.

[0006] For further information on the state of the art, reference can also be made to DE 10 2018 104 577 A1, which describes a method for load control of a charging station for an electric vehicle. In this method, charging power is supplied via a charging connection power with the aim of providing the greatest possible control potential in order to achieve grid stability for the power supply network.

[0007] Furthermore, there are apps, for example, that inform users about the times of day and night when electricity is cheaper or has high capacity. Independent of electric vehicles, there are, for example, utility company lockouts for temporarily shutting down heat pumps to cushion fluctuations in the power grid or peak consumption. In connection with SmartGrid, there are approaches to creating dynamic electricity tariffs that attempt to counteract fluctuations through the electricity price and create incentives to save or consume electricity accordingly. However, with the increased capacity required by a large number of users or a large number of electric vehicles, such an approach becomes increasingly complex.

[0008] The object of the present invention is to provide a method for coordinating a charging process which overcomes the aforementioned disadvantages.

[0009] According to the invention, this object is achieved by a method having the features in claim 1, and in particular in the characterizing part of claim 1. Advantageous embodiments and further developments emerge from the dependent claims.

[0010] At the core of the method according to the invention, location-based capacities in the power grid are calculated along a planned route, with a charging stop being scheduled in an area with sufficient capacity. With such a method, intelligent charging planning can make an active contribution to stabilizing the power grid. In particular, a backend-based route planning system can be used to incorporate location-based forecasts from energy suppliers and weather models.

[0011] The method is designed to coordinate the charging process of an electrically powered motor vehicle. In addition to route calculation criteria, such as individual energy savings for an electric vehicle or the calculation of the fastest or shortest route, it also creates a further option for selecting a collective energy-saving route that contributes to the common good, allowing for intelligent mitigation of power fluctuations.

[0012] Preferably, route planning can be adjusted to accommodate excess capacity in the power grid. This allows for the advantage of a cheaper electricity tariff, which can improve customer satisfaction. For example, the route can be modified if this allows excess capacity in the power grid to be used for charging, and the arrival time does not change significantly.

[0013] A very advantageous development of the concept could involve taking traffic volume along the route into account. This could, for example, help determine a section of the route that represents the optimal location for a load along the route.

[0014] According to an advantageous embodiment, a forecast from electricity providers regarding the capacity of the power grid upon arrival at a destination can be included. This makes it possible to calculate whether a charging stop upon arrival is advisable or whether it would be better to do it en route.

[0015] A further advantageous embodiment may involve a fleet of vehicles, with the vehicles being charged at different locations and / or times. This allows for a type of traffic shaping to be considered as part of the optimization, so that not all vehicles are sent to the same location for charging.

[0016] In general, the proposed measures can stabilize the power grid, while simultaneously allowing customers to benefit from low charging prices. This is particularly possible because capacity fluctuations are generally reflected in the electricity price, thus creating an incentive for customers to use the system and save money at the same time.

[0017] Further advantageous embodiments of the method according to the invention also emerge from the exemplary embodiment which is illustrated in more detail below with reference to the figure.

[0018] It shows: Fig. 1 a schematic representation of the process.

[0019] In the presentation of the Fig. 1 shows a possible embodiment of the method 1, wherein several driving routes of vehicles are shown in comparison.

[0020] To coordinate the charging process of multiple electrically powered vehicles, a location-based capacity 3a, 3b, and 3c is first calculated in the power grid. This allows a map to be created in which the different capacities 3a, 3b, and 3c are stored. The vehicles travel the different routes 2a, 2b, and 2c, passing through several location-based capacities 3a, 3b, and 3c. A charging stop, shown by the hatched circles, is scheduled in an area where sufficient capacity is available. Furthermore, the charging stops of the different vehicles can be coordinated to take into account the local and temporal conditions of a fleet of vehicles.

[0021] In the example shown, regions 3a have an energy surplus in the power grid. Regions 3b have balanced energy capacity, and regions 3c have only a limited energy supply.

[0022] If the destination is located in a region 3c, such as for the routes 2b and 2c shown, a charging stop is scheduled before the vehicle enters this region. The charging stops are marked with hatched circles; for routes 2b and 2c, these are located in regions 3a and 3b.

[0023] Ideally, charging stops in Region 3c should be avoided, and if there are no Region 3a regions with a surplus of energy in the power grid, a charging stop should be planned in a Region 3b with balanced energy in the power grid. Furthermore, vehicles should be distributed across different charging stations wherever possible to avoid energy bottlenecks.

[0024] To classify the different capacities 3a, 3b, and 3c, a forecast for an expected transit time can be crucial. Forecasts from energy suppliers regarding the expected time of reaching the region can be used for this purpose. For the destination regions, a forecast for an arrival period, and especially for a few hours thereafter, is crucial. QUOTES CONTAINED IN THE DESCRIPTION

[0000] This list of documents submitted by the applicant was generated automatically and is included solely for the convenience of the reader. This list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions. Cited patent literature

[0000] DE 10 2016 202 816 A1

[0004] DE 10 2017 211 148 A1

[0005] DE 10 2018 104 577 A1

[0006]

Claims

[1] Method (1) for coordinating a charging process of an electrically powered motor vehicle, characterized by that along a planned route (2) location-related capacities (3) in the power grid are calculated, whereby a charging stop is planned in an area with sufficient capacity. [2] Method (1) according to claim 1, characterized by that route planning is adapted to excess capacity in the power grid. [3] Method (1) according to claim 1 or 2, characterized by that traffic volume along route (2) is taken into account. [4] Method (1) according to claim 1, 2 or 3, characterized by that a prediction by electricity suppliers about a capacity (3) in the electricity grid upon arrival in a destination area is taken into account. [5] Method (1) according to one of claims 1 to 4, characterized by that a fleet of vehicles is involved, with the vehicles being charged at different locations and / or times.

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