Method and device for determining and carrying out a charging strategy for electric vehicles, and computer method

Abstract

The invention relates to a method, to a device, and to a computer-implemented method and a corresponding computer method for determining the charging strategy for an electric battery of at least one electrically drivable vehicle. For this purpose, a battery variable is detected which represents the charge state of the battery of at least one vehicle. Furthermore, a route variable is detected which represents the route to be travelled by the vehicle to be charged. In order to determine the energy available for the charging process, an expected energy variable is generated or detected that represents a predicted future amount of energy which can be generated or which is available. After the corresponding variables have been detected, the charging strategy is determined on the basis of the at least one battery variable, the route variable and the expected energy variable.

Description

[0001] Description

[0002] Method and device for determining and implementing a charging strategy for electric vehicles and computer method

[0003] The invention relates to a method and a device for determining and implementing a charging strategy for an electric vehicle at a charging station as well as a computer-implemented method and a corresponding computer program.

[0004] State of the art

[0005] Methods for predicting the energy requirements of an electric vehicle to determine the required charging quantity of the energy storage device are well known. In addition to the planned distance to be covered, the elevation profile or the expected headwind can also be taken into account in the known methods.

[0006] From DE 20 2021 103 932 U1 a method for controlling the charging of an electric vehicle is known, in which the charging process is additionally controlled by the availability of a renewable energy source.

[0007] Disclosure of the invention

[0008] The present invention claims a method and a device as well as a computer-implemented method or a corresponding computer method for determining the charging strategy of an electric battery of at least one electrically driven vehicle. Furthermore, a method and a device are also claimed which controls the supply of a vehicle with electrical energy using the method according to the invention. For this purpose, a battery variable is recorded which represents the charge state of the battery of at least one vehicle. Furthermore, a distance variable is recorded which represents the distance to be traveled by the vehicle to be charged. In the simplest case, the pure distance traveled between the departure point or charging point and the destination can be recorded as the distance variable.In addition, other boundary conditions can also be taken into account when determining the route size, such as the traffic situation, detour routes, the elevation profile, driving behavior, and / or the vehicle's payload. To determine the energy available for loading, an expected energy value is generated or recorded that represents a forecast future amount of energy that can be generated or is available at the destination. In particular, the expected amount of energy that can be generated and / or is available should come from renewable and / or regenerative energy sources. These could be weather-dependent energy sources such as solar energy or wind energy, or even energy from biogas plants. Alternatively or additionally, the state of charge of an energy storage device at the departure or loading location, as well as at the destination, can also be taken into account in the expected energy value.After recording the relevant variables, the charging strategy is determined depending on at least one battery size, the route size and the expected energy value.

[0009] The advantage of the present invention is that the charging of the electric vehicle or the battery located in the vehicle depends on the energy available, particularly the energy generated at the time of charging, thus avoiding energy transport and / or energy storage, which leads to energy losses. By taking into account the battery size and the distance traveled by multiple vehicles, prioritization can also be achieved, which can, for example, lead to fleet operators optimizing the charging process, specifically selecting vehicles within the fleet, and increasing cost-effectiveness.

[0010] In a further development of the invention, it is provided that the expected quantity, which represents an expected amount of energy that can be generated and / or is available, is determined as a function of weather information. In particular, the aim is for the expected amount of energy to be generated by a renewable energy source whose generation and / or energy quantity depends on the weather. Alternatively, the amount of energy stored in an energy storage device and available for charging the battery can also have been generated by a renewable energy source. For example, solar radiation can be taken into account when generating solar power and / or wind conditions can be taken into account when generating wind energy. In a biogas plant, the available organic material that can be utilized in the biogas plant can be taken into account.Optionally, the quality of the organic material can also be used as a measure of the renewable energy that can be generated.

[0011] Furthermore, it is planned to determine and / or record a separate energy expectation value for both the departure location or the intended charging location, as well as for the destination. This makes it possible to determine the amount of energy available or capable of being produced at the departure location or charging location, as well as at the destination, so that the return journey can be completed using the energy from the departure location if necessary. This will reduce the charging time at the departure location. Furthermore, the necessary storage of the energy generated at the destination will also be reduced, resulting in fewer energy losses during storage and withdrawal from an energy storage system.

[0012] Advantageously, energy storage devices are available at the departure / charging location and / or the destination, in which the energy generated, in particular, by renewable energy sources is stored. In order to also take the already stored energy into account when determining the charging strategy, at least one state of charge variable of an energy storage device can be recorded at the departure / charging location and / or the destination.

[0013] In one embodiment of the invention, the charging strategy is determined not just for a single vehicle but for at least two vehicles, for example within a vehicle fleet. For this purpose, at least two battery variables are recorded, each representing the state of charge of the electric battery of another vehicle. The charging strategy can additionally be determined as a function of at least one time variable. In this case, the time variable can represent a predetermined period of time, for example for reaching a minimum state of charge of the battery in the vehicle, and / or a predetermined arrival time at the destination. In one embodiment of the invention, the minimum state of charge can correspond to the minimum amount of energy required to cover the distance between the departure location / charging location and the destination, optionally taking into account alternative routes based on recorded traffic data or other boundary conditions.

[0014] In general, the charging strategy can also be determined based on traffic data. For this purpose, the process can determine various routes and their expected energy requirements based on the distance. By taking this into account, a longer route can be planned, for example, which, based on traffic data or route information, can be covered faster or more energy-efficiently than a shorter route.

[0015] When determining the charging strategy, the costs of charging the electric battery can also be considered. For this purpose, the expected costs for energy consumption at both the departure / charging location and the destination can be determined to derive an energy- and cost-optimized charging strategy. For example, it is conceivable that it makes more energy-efficient sense not to set off with a fully charged battery if cheaper energy can be charged at the destination. Furthermore, storage efficiency can also be considered in the charging strategy if it is known that sufficient energy will be available at the destination for the return journey.

[0016] The method can, for example, run in a processing unit so that the charging strategy can be transmitted to the driver, the operator of a charging station, or the charging station itself. Of course, the charging station itself can also have such a processing unit so that the charging process can be automatically controlled by the method after the charging strategy has been determined. Optionally, the information about the charging strategy and the amount of energy to be charged can also be transmitted to other charging stations, for example to the destination, in order to reserve this amount of energy there if necessary. When the invention is used in a fleet network, several charging stations at the charging location or destination can thus be coordinated and controlled jointly for a number of vehicles.It is also possible to determine or derive the charging strategy according to the invention using a computer program, for example on a central server or in a (mobile) app.

[0017] Short description of the drawings

[0018] Figure 1 illustrates the principle of determining the charging strategy according to the invention using a block diagram. The flowchart in Figure 2 shows the underlying method according to the invention. Figure 3 shows an extension of the method from Figure 2.

[0019] Embodiments of the invention

[0020] If electrical energy is not used directly at the point of generation, energy losses occur during transport and / or storage. For this reason, it makes sense to utilize generated electrical energy directly as much as possible. This is where the present invention addresses this issue by predicting how much energy can be generated and then storing it directly in the battery of an electric vehicle, thus avoiding transport and storage losses.

[0021] The energy generation from conventional energy sources such as nuclear fission, coal, and gas-fired power plants is highly predictable due to their controllable energy production. However, with renewable energy sources such as solar cells or wind turbines, the energy generated depends on the corresponding weather conditions. If weather conditions are additionally included in the determination of a charging strategy, as in the present invention, energy losses due to transport or storage in additional energy storage devices can be reduced or even avoided. Figure 1 shows a device with a processing unit 100 that carries out a method according to the invention, as described, for example, with reference to Figures 2 and 3.

[0022] To determine or derive the charging strategy, the method in the processing unit 100 records at least one battery state in the vehicle to be charged, a distance variable representing the distance between the departure point or the charging point and the destination, and an expected energy variable representing the amount of energy that can be generated by an energy source, in particular a renewable one. From these variables, the method determines the amount of energy that can and must be fed into the battery from the energy source in order to be able to travel at least to the destination and back. If less energy is generated by the energy source, in particular a renewable one, at the departure point / charging point, a check can be made to determine whether further energy is available at the destination for the return journey or whether the remaining energy can be obtained from another source, for example an external energy storage device.

[0023] To implement the method according to the invention, the device can retrieve at least the battery status 110 of the vehicle to be charged via a wired or wireless connection. Optionally, however, the method can also be used in a fleet association, for example, in a company or a rental car service. In this case, the device can query the battery statuses 110 of a plurality of vehicles to determine their potential charging needs.

[0024] The route length can be entered, for example, in the form of an input 115 by the vehicle user into the processing unit 100. Alternatively, route planning can be used to determine the route length based on the destination, historical movement profiles, or by a dispatcher. If the charging strategy is to be derived for a plurality of vehicles, a route length can be recorded and considered for each vehicle. Due to the temporarily limited predictability of the expected energy consumption, the recording and consideration of the route length can be limited to journeys within a specified period of time.

[0025] To derive the expected energy quantity, weather information from a corresponding weather service 120 or from the energy source provider can be read in and taken into account. Both the weather information at the departure location or intended charging location and the destination location can be taken into account to determine a suitable charging strategy. For example, it can be planned that only the amount of energy required for the journey to the destination is drawn at the departure location or charging location, since sufficient energy is available at the destination for the return journey.

[0026] If the renewable energy source at the departure location, charging location, or destination does not generate a sufficient amount of energy to cover at least one distance, a check can be made to determine whether an energy storage device 125 or another energy source is available for charging. To enable the driver to continue the journey despite the insufficient amount of renewable energy generated, the method can record the charge level of at least one energy storage device at the departure location, charging location, or destination to determine whether this energy storage device provides a sufficient amount of energy for the journey. The same applies, of course, to other, non-renewable energy sources.

[0027] The process can also take traffic data from a control center 130 on the intended routes or during route planning into account when determining the charging strategy, so that even detours caused by traffic jams or difficult-to-navigate route sections can be covered with a sufficient amount of energy. Here, too, when applying charging strategy planning within a fleet, the energy requirement can be considered individually for each vehicle based on the traffic situation.

[0028] Additionally, a time variable can also be considered when determining the charging strategy. For example, it is conceivable for the vehicle user to specify the departure time, arrival time, and / or charging duration via input 140, so that the method determines the charging depending on the potential amount of energy to be transferred. In a fleet, the time variables can be considered for each individual vehicle, regardless of whether they are entered by individual users or a central dispatcher.

[0029] When purchasing the energy quantity, the energy costs can also be taken into account. The process can collect corresponding price information from the provider 145 of the energy source or the various energy sources.

[0030] A memory 105 can be provided in the processing unit 100, in which, for example, historical usage data, boundary conditions for determining the charging strategy, price information, or other data relevant for deriving the charging strategy can be stored. Furthermore, the determined charging strategy can be stored in the memory 105 for later use. It is also possible to link the charging strategy with associated control commands stored in the memory 105 for operating a charging station.

[0031] The charging strategy determined in processing unit 100 can be displayed to the user via a corresponding display 160. Alternatively or additionally, the charging strategy can be output to suitable additional processing units 150. The charging strategy can also be used to control a charging station 170 so that the charging process can be carried out automatically. It is also conceivable that both the charging station at the departure location and the destination are informed of the charging strategy, so that the user at the destination does not have to further control the charging or reserve an amount of energy to be drawn. In a fleet association, the charging strategy can be sent to a central server 180, which controls the charging stations for the various vehicles accordingly.

[0032] The method according to Figure 2 describes a rudimentary version of the method according to the invention. The acquisition of the battery size in step 210, the distance size in step 220, and the expected energy size 230 can be performed in parallel or separately, as they are independent of one another. Alternatively, these values ​​can also be acquired sequentially by a method. The values ​​acquired in this way are linked in a step 240 to derive and determine a charging strategy. The charging strategy acquired in this way can be output in a subsequent step 250, forwarded to a charging process controller, or used directly to control the charging process.

[0033] The determination of the battery size in step 210 may include a standalone process in which the state of charge of the battery in one or more vehicles is determined and made available to the method for determining the charging strategy.

[0034] The determination of the route size in step 220 can also be carried out and made available independently. It is conceivable that the route, route, or distance on which the route size is based is determined based on a route plan or the planning of a dispatcher, in particular for a large number of vehicles, i.e., at least two vehicles. If the charging strategy is to be determined for a large number of vehicles, the route size can be a matrix or a data field in order to consider both the routes or distances as well as possible detours, for example, based on the underlying traffic data.

[0035] The expected energy quantity in step 230 can be provided, for example, by the energy supplier. The forecast can take into account both current and future weather conditions, particularly if the expected energy quantity at the destination is to be considered for determining the charging strategy.

[0036] The methods for determining the battery size, the route size, and the expected energy value can be executed individually or in any combination, separately, or as part of the method for determining the charging strategy. Optionally, the method according to Figure 2 can be started by detecting a charging request by the user or initiating the determination by a dispatcher in step 200.

[0037] The flowchart of a method according to Figure 3 describes an expanded embodiment for determining a charging strategy, particularly taking into account renewable and / or intermittently available energy sources, for example, due to weather conditions. Additional parameters and / or boundary conditions are taken into account, enabling optimization of the charging process and the use of the energy generated or available at the time of charging.

[0038] After the method has started, for example, due to a user request or initiation based on a fleet calculation, at least one battery variable, one route variable, and one expected energy variable at the departure location and / or the intended (first) charging location are recorded in a first step 300. If the method is to determine a charging strategy for a large number of vehicles, either for each individual vehicle or for the power output control of a shared charging infrastructure or a (renewable) energy source, a plurality of the individual variables can also be recorded. Of course, it can also be provided to record the respective variable in the form of a multidimensional variable in order to take into account corresponding assignments to the vehicles or alternative characteristics. Based on the variables thus recorded, a check is carried out in step 330 as to whether a charging strategy can be determined that meets the requirements.If a corresponding charging strategy can be determined, the charging strategy can be communicated to the user in step 340, transmitted to a charging station, or used directly to control charging before the method is terminated. However, if it is detected in step 330 that charging according to the specifications for determining the charging strategy is not possible, the user is informed in step 360 that no suitable charging strategy can be determined in this case. Alternatively, the method can also be restarted or run through again with the acquisition of further parameters after step 300. For example, in step 300, the expected energy value at the destination can be acquired or determined in order to check whether a sufficient amount of energy is or will be available there from a (renewable) energy source to enable the return journey.In this case, the charging strategy can specify in step 330 that the battery is only charged with the energy required for the outward journey. Accordingly, in step 340, a charging station or a certain amount of energy can be reserved at the destination.

[0039] Possible additional parameters can be recorded in optional steps 310 and / or 320 after the recording of the variables in step 300 and taken into account when determining the charging strategy. For example, in step 310, the available energy from existing energy storage devices and / or other energy sources at the departure location or (first) charging location as well as at the destination can be taken into account. Recording the energy costs, in particular of the various energy sources or from energy storage devices at the departure location / charging location and at the destination in step 310 can also play a role in determining the charging strategy in step 330. Since the required amount of energy depends essentially on the distance to the destination, the traffic situation can be recorded in step 310 and taken into account when calculating the route and determining the route size.

[0040] In optional step 320, a time variable can be recorded, which can also be taken into account when determining the charging strategy in step 330. For example, it is conceivable that the journey must have started by a certain time or that the vehicle must have arrived at the destination by a certain time at the latest. Since this may limit the charging time at the departure point or charging point, such an indication can also lead to a changed charging strategy, for example by requiring the battery to be at least partially charged at the destination for the return journey. The same applies to specifying a maximum charging time at the departure point and / or at the destination, for example in the context of freight transport, taking into account loading and unloading times as well as driver rest periods. As already explained, the method according to the invention can also be used to determine the charging strategy for a large number of vehicles.This could, for example, be a transport company, a taxi company, a freight forwarding company, a rental car service, a car sharing service, and / or a bus company. Thus, at least some of the vehicles could be charged from a shared renewable energy source, for example, on a company premises, so that the generated energy can be used efficiently, in particular without the need for storage, for economic reasons. In such a case, the determined charging strategy for at least two vehicles can be sent to the vehicles themselves, to the charging station, to the vehicle drivers, and / or to a dispatcher in a further optional step 350.

[0041] The method according to the invention can be applied and trained within the context of the application of artificial intelligence. The method can run on a central server and control not only a large number of vehicles but also a plurality of charging stations. This plurality of charging stations can be assigned to a single (renewable) energy source. Alternatively or additionally, the charging stations can also be assigned to different (renewable) energy sources, so that the user or vehicle can be assigned a charging station that provides the amount of energy required for the journey.

Claims

Claims 1 . Method for determining a charging strategy of an electric battery of at least one vehicle, the method comprising at least • a battery size is recorded (210, 300) which represents the state of charge of the electric battery of at least one vehicle, and • a route variable (220, 300) is recorded, which represents the route to be travelled by the vehicle between a departure point and a destination, and • an energy expectation value (230, 300) is recorded, which represents a future amount of energy that can be generated and / or is available at the destination, and • the charging strategy is determined depending at least on the battery size, the route size and the energy expectation size (240, 330).

2. Method according to claim 1, characterized in that the energy expectation value represents an expected amount of energy that can be generated and / or is available, and the method determines the expected value as a function of weather information, wherein it is particularly provided that the weather information represents wind information, sun information and / or the quality of the availability of organic material that can be used in biogas plants 3. Method according to claim 1 or 2, characterized in that the method • a first energy expectation value (230, 300) is recorded, which represents the expected amount of energy that can be generated and / or is available at the departure location, and / or • a second energy expectation value (230, 300) is recorded, which represents the expected amount of energy that can be generated and / or is available at the destination.

4. Method according to one of the preceding claims, characterized in that the method additionally determines the charging strategy as a function of at least one state of charge variable (240, 330), wherein it is provided in particular that the state of charge variable determines a state of charge of at least one energy storage device • at the departure point, and / or • represented at the destination.

5. Method according to one of the preceding claims, characterized in that the method comprises at least • a first battery value is recorded, which represents the state of charge of the electric battery of the vehicle to be charged at the departure point, and • a second battery size is detected, which represents the state of charge of another vehicle, in particular at the departure location, wherein the charging strategy is additionally determined as a function of at least the first and second battery size (240, 330).

6. Method according to one of the preceding claims, characterized in that the method additionally determines the charging strategy as a function of at least one time variable (240, 330), wherein it is provided in particular that the time variable • an arrival time at the destination, and / or • represents a duration for the expected charging process until a minimum charge level of the vehicle's battery is reached, wherein it is particularly provided that the minimum charge level corresponds at least to the amount of energy that the vehicle requires to bridge the distance between the departure point and the destination.

7. Method according to one of the preceding claims, characterized in that the method determines the loading strategy as a function of traffic data (240, 330), wherein in particular traffic data on one of the possible routes from the departure point to the destination are taken into account.

8. Method according to one of the preceding claims, characterized in that the method, when determining (240, 330) the charging strategy, takes into account an energy and / or cost optimization with regard to the power loss during transport and / or storage of the amount of energy generated in the future 9. Device with a processing unit for determining a charging strategy of an electric battery of at least one vehicle, with a processing unit (100), wherein the processing unit (100) carries out in particular one of the methods according to claims 1 to 8, wherein the processing unit (100) at least • a battery size is recorded (210, 300) which represents the state of charge of the electric battery of at least one vehicle, and • a route size is recorded (220, 300), which represents the route to be travelled between a departure point and a destination, and • an energy expectation value is recorded (230, 300), which represents a future amount of energy that can be generated and / or is available at the destination, and • the charging strategy is determined depending at least on the battery size, the route size and the energy expectation size (240, 330).

10. Device which controls the electrical energy for supplying a vehicle according to one of the steps of one of the methods according to claims 1 to 8 (170).

11. A computer-implemented method which performs the steps of any of methods 1 to 8.

12. A computer program which carries out the steps of any of the methods 1 to 8.

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