Planning routes for an electric vehicle

Abstract

The invention relates to a method (S1-S9) for planning routes (A, B) for an electric vehicle (BEV), in which the routes (A, B) are evaluated based on at least one predicted ecological property of the charging current available along the routes (A, B) for charging the electric vehicle (BEV). A data processing device (IT, SP, BS) is configured to carry out the method (S1-S9). A system (IT, SP, BS, EV) comprises a data processing device (IT, SP, BS) and at least one external instance (EV) that provides information (D3) about the at least one ecological property of the charging current, wherein the information (D3) is transferable from the at least one external instance (EV) to the data processing device (IT, SP, BS). A computer program product comprises code that, when executed on the data processing device and / or on the system, carries out the method (S1-S9).The invention is particularly advantageously applicable to the route planning of fully electric vehicles.

Description

[0001] The invention relates to a method for planning routes for an electric vehicle, in which the routes are evaluated based on at least one ecological property of the charging current available along the routes for charging the electric vehicle. The invention also relates to a data processing device configured to carry out the method. The invention further relates to a system comprising a data processing device and at least one external instance that provides information about the at least one ecological property of the charging current, wherein the information is transferable from the at least one external instance to the data processing device. The invention also relates to a corresponding computer program product. The invention is particularly advantageously applicable to the route planning of fully electric vehicles.

[0002] Route planning for vehicles to establish routes between a specific (original or updated during the journey) starting position and a specific destination position is generally known. Different routes can be evaluated based on target criteria, e.g., how well they fulfill one or more target criteria. Such target criteria can, for example, - the duration (“fastest route to the destination”), - the route length (“shortest route to the destination”), - include travel costs ("most cost-effective route to the destination"), etc. Users can often specify in advance the target criterion by which routes should be evaluated, e.g., to establish a corresponding ranking. Route planning can typically also take traffic events such as traffic jams, road closures, etc. into account. Route planning is typically updated regularly after it has been started. For vehicles with combustion engines, the target criterion is also known to be the lowest pollutant emissions during the journey. For purely electric vehicles, which can also be referred to as battery-electric vehicles (BEVs), the pollutant emissions during the journey ("tank-to-wheel") are set at zero or 0 g / km.

[0003] For electric vehicles, charging stops at charging stations can be included in route planning, especially if the destination cannot be reached without recharging the battery. It is known to take into account the pollutant emissions generated by generating the charging current (“well-to-wheel”).

[0004] For example, DE 10 2020 001 782 A1 discloses a method for charging a traction battery of a battery-electric motor vehicle. The method comprises receiving greenhouse gas information relating to a quantity of greenhouse gas emissions that has occurred when generating electrical energy that is made available at a stationary charging device. A target charge level of the traction battery is received based on the received greenhouse gas information. The traction battery is charged to the target charge level by the stationary charging device. In one embodiment, the step(s) of receiving and / or the step of determining is / are carried out as part of route planning (e.g., by means of a navigation system) of the motor vehicle. In a further development, the route planning is carried out with an objective function for minimizing a travel time, for minimizing a cumulative total energy consumption (comprising, for example,Energy transport in the grid and energy consumption in the motor vehicle), preferably total exergy consumption, and / or to minimize greenhouse gas emissions.

[0005] DE 10 2022 201 646 A1 discloses a method for determining actual emission values for a vehicle, comprising receiving a certificate file containing information about production-related emissions of an energy source or an electrical current charged during a charging or refueling process in a vehicle from a supply point that provides the energy source or the electricity; and storing the certificate file together with at least one item of information about the amount of electricity or energy source charged. Actual emissions for a journey can then be calculated using the information in the certificate file.

[0006] It is the object of the present invention to at least partially overcome the disadvantages of the prior art and in particular to provide an improved possibility for the ecologically advantageous charging of electric vehicles, in particular purely electrically operated electric vehicles.

[0007] This object is achieved according to the features of the independent claims. Preferred embodiments can be found in particular in the dependent claims.

[0008] The problem is solved by a method for planning routes for an electric vehicle, in which the routes are evaluated based on at least one predicted ecological property of the charging current available along the routes for charging the electric vehicle.

[0009] This method has the advantage that the pollutant emissions required to generate the charging current offered to the electric vehicle along its route can be determined particularly precisely, thus allowing the goal of reducing pollutants generated by charging the electric vehicle to be achieved particularly effectively. This approach takes advantage of the fact that energy producers, electricity suppliers, grid operators, energy markets, etc., provide one-day, multi-day, or even weekly forecasts on the composition of the electrical energy mix they supply. The emission quantities of pollutants (e.g. CO2, methane, etc.) required to generate the individual energy types contained in the energy mix, as well as the shares of each energy type in the overall energy mix, are known, at least in terms of estimates, and can be broken down into the charging current offered to the electric vehicle along its route and thus forecast.These forecasts can, for example, take into account changes in the shares of individual energy types in the energy mix due to deployment planning of power plants and storage facilities, generation forecasts from renewable energies based on weather forecasts, likely changes in demand, etc., and thus enable far more precise route optimization for an ecologically advantageous characteristic than considering only current emission quantities. Using this method, a different evaluation of the routes can then be obtained at different times, assuming otherwise identical boundary conditions.

[0010] In one embodiment, the electric vehicle is a fully electric or battery-powered vehicle. The method is particularly advantageous for this. However, the method can also be used for plug-in hybrid vehicles (PHEVs).

[0011] In one embodiment, the charging current available along the route(s) for charging the electric vehicle is provided by at least one public charging station. However, the charging current can alternatively or additionally be provided by at least one private charging station, e.g., via a wallbox.

[0012] The fact that the routes are evaluated based on at least one predicted ecological property of the charging current comprises, in particular, that possible routes are evaluated using at least one target criterion (e.g., how well or poorly they correspond to the at least one target criterion), whereby the at least one predicted ecological property of the charging current at possible charging points is or can be included as input variable(s) in the evaluation. The at least one target criterion therefore includes or takes into account the at least one ecological property of the charging current (e.g., the share of renewable energies or the amount of CO2 generated), but can also take into account other properties of the charging current (e.g., its price) and / or properties of the route (e.g., its length, travel time, etc.) between a specific starting position and a specific destination position.

[0013] The result of the evaluation can, in particular, include a degree of agreement between the considered routes and the at least one target criterion. The degree of agreement can then be ranked, resulting in an order or ranking of the routes that reflects the degree of agreement.

[0014] The at least one target criterion can be exactly one target criterion or comprise several target criteria. If there are multiple target criteria, these can be incorporated as individual criteria into a formulaically formulated overall criterion. One or more target criteria – even those not relating to an ecological property – can be formulated as percentage scales, in particular. Thus, a target criterion can correspond to a percentage degree of agreement with a predicted ecological property, e.g., between 0% (no agreement) and 100% (full agreement). One or more target criteria can be formulated as boundary conditions, e.g., that a specific route must not exceed or fall below a threshold value for an ecological or non-ecological property.

[0015] An ecological characteristic of the charging current corresponds in particular to the characteristic of the charging current at the time or for the period of time at which the electric vehicle is expected to be connected to the corresponding charging point when traveling the route.

[0016] A selected route can be updated, especially if the minimum ecological characteristics of the available charging current (especially including the charging current available at the destination) change over time, e.g., due to travel delays, a change in the weather forecast, etc. The update can be performed before and / or during a trip. In one further development, the same route will continue to be suggested or used; in another further development, an alternative route may be suggested or used.

[0017] The route optimization can also include charging points available at the start position and / or the destination position, e.g. wall boxes, public charging stations, etc.

[0018] An "ecological property" of the charging current can be understood in particular as a property in the generation, transport, etc. of the charging current that can have a noticeable impact on the environment, in particular on the Earth's climate. Ecological properties can, for example, be at least one property from the group - a quantity of at least one environmentally harmful substance emitted to generate the charging current, - a proportion of the charging current provided for charging must be comprised of environmentally friendly energy sources. If the amount of CO2 required to generate the charging current is taken into account, nuclear energy, wind energy, solar energy, hydropower, and / or geothermal energy generation can be classified as environmentally friendly energy sources. The at least one environmentally harmful substance can be, for example, particulate matter, heavy metals, CO2, methane, etc.

[0019] A type of energy can be understood, in particular, as a method of generating electrical energy. Energy types can include, for example: - Energy generation from hard coal, - Energy generation from lignite, - Energy generation from natural gas, - Energy generation from biomass or bioenergy (e.g. from wood and / or waste), - nuclear energy, - Wind energy (on-shore and off-shore), - solar energy, - Energy generation from geothermal energy, - Water energy (hydropower and / or ocean energy) - etc.

[0020] An “ecological energy type” is understood in particular to be a type of energy that is classified as ecologically beneficial or environmentally friendly. It is a design that renewable energy types are classified as ecological energy types. Renewable energy types can include, for example, bioenergy, geothermal energy, hydropower, ocean energy, solar energy, and wind energy. It is a further development that only renewable energy types are classified as ecological energy types, alternatively or additionally also other energy types. For example, it is a further development that energy types that require a small amount of at least one environmentally harmful substance to be generated are classified as ecological energy types. For example, depending on the point of view, nuclear energy can be classified as environmentally friendly because no CO2 is produced during the operation of a nuclear power plant. Also, for example,A renewable energy source such as wood cannot be classified as an ecological energy source because its combustion can generate particulate matter. In general, the pollutant emissions required for the manufacture and / or construction of an energy generation facility can also be taken into account, for example, the amount of CO2 required for the manufacture and / or construction of a wind turbine, a solar panel, etc.

[0021] It is a further development that the energy types considered as green energy types in the context of this procedure are determined by a higher authority with regard to the electric vehicle, for example, by energy suppliers, fleet operators, government authorities, etc. It is a further development that the energy types considered as green energy types in the context of this procedure are determined by a user or owner of the electric vehicle. For example, one user may consider nuclear energy to be a green energy type, while another may not.

[0022] A further development allows a user of the method to set preferences that are or can be used to evaluate routes. In a further development, this can concern the target criteria by which routes are evaluated, in particular ranked. The user can thus select one or more target criteria and / or boundary conditions. A further development allows a user of the method to set preferences regarding whether and which at least one ecological characteristic is or should be used to evaluate routes.

[0023] In one embodiment, the routes are optimized with regard to at least one ecological characteristic. This particularly includes optimizing the routes with regard to at least one ecological or ecologically advantageous characteristic or additionally with regard to at least one other characteristic, e.g. travel time, travel costs, etc. For example, an optimization or route selection can be carried out with regard to low CO2 production or a high proportion of renewable energy types. Alternatively, an optimization or route selection can be carried out with regard to low CO2 production / a high proportion of renewable energy types under the boundary condition that the additional costs compared to the cheapest route do not exceed a certain absolute or percentage amount of money. In another variant, an optimization orRoute selection can be based on the most cost-effective or fastest route under the boundary condition that the amount of CO2 generated to generate the charging current and / or the proportion of renewable energy types in the charging current does not exceed a certain absolute or percentage threshold compared to the most environmentally friendly route. In particular, when optimizing for the fastest route, the charging power of the charging points providing the charging current can be taken into account. The state of charge of the drive battery at the beginning of the journey at the starting position (“start SoC”) and / or the desired target state of charge of the drive battery at the end of the journey at the destination position (“destination SoC”) can also be taken into account for route selection / optimization. In particular, the charging time can be calculated or at least estimated based on the achievable charging power(s) at the charging points and the amount of energy required for the drive battery.

[0024] One embodiment allows the electric vehicle to feed discharge current from its drive battery back into the charging point along at least one of the routes, and the routes are additionally evaluated based on a potential saving of an environmentally harmful substance required for electrical energy generation and / or an increase in the proportion of environmentally friendly energy sources due to the feed-in. This achieves the advantage that the feed-in can reduce the generation of more environmentally harmful energy sources in the area of at least one energy supplier, grid operator, etc. along the route. Furthermore, this advantageously stabilizes electrical energy grids.For this configuration to be feasible, at least one charging point along the route must have both the charging point providing the charge and the electric vehicle configured for regeneration (often referred to as "vehicle-to-grid" (V2G)), and regeneration must be enabled / permitted. This configuration is particularly advantageous if the proportion of green energy stored in the electric vehicle's drive battery is higher than the proportion of green energy in the charging current at the charging point.

[0025] With regard to feed-in, the scenario in particular that can be relevant is that an electric vehicle is charged at a charging point along the route with comparatively environmentally friendly electrical energy and discharged at a charging point reached later along the route, especially if discharging can avoid the generation of less environmentally friendly electrical energy. An example of this could include an electric vehicle being charged at its starting point with environmentally friendly and possibly also inexpensively generated electrical energy, e.g. with solar power from a home photovoltaic system, and then, further along the route, feeding electrical energy back at least once to a charging point where electrical energy with a lower proportion of environmentally friendly energy types is used.This is particularly advantageous if the destination can be reached with discharging and without further charging, if the time required for discharging is not or not significantly negative for a user (e.g., because the discharging / charging point is located at a shopping center or restaurant), and / or if the user is compensated for feeding back energy. The feed-in tariff can also be taken into account when optimizing route costs. However, electric vehicles can in principle also be charged between the start and destination positions at "green" charging points using charging current with more favorable ecological characteristics and discharged at "gray" charging points using charging current with less favorable ecological characteristics.

[0026] In general, a specific charging point, including a charging point at the start and / or destination location, can exhibit more or less favorable ecological characteristics at different times or durations, depending on weather, time of day, base load, etc., and can then be considered either a green or a gray charging point. This can be estimated by predicting the ecological characteristic(s), and a route can be set up and updated accordingly.

[0027] One design takes into account the predicted charging power or energy availability of the charging current when planning routes. This allows routes to be planned even more precisely and optimized more effectively. This takes advantage of the knowledge that the available charging power at charging points can fluctuate over time and, in particular, can be lower than the technically maximum transferable charging power. One reason for this may be that an energy supplier supplying the charging point must first supply other consumers / customers with electrical energy before electrical energy can be made available to the charging point to charge the electric vehicle. This "surplus supply" can fluctuate over time. The lower the throttled charging power for charging, the less favorable the charging process generally becomes due to the longer charging time.On the other hand, it can be particularly advantageous to discharge at such a charging point, as this allows the energy supplier's supply situation to be stabilized, advantageously without the need to start up additional - usually ecologically harmful - energy generation facilities.

[0028] In one embodiment, an electric vehicle is connected to a particularly suggested charging point along the route and is charged and / or discharged according to a charging plan suggested or specified by the route planning. The method for planning routes for an electric vehicle can therefore also be viewed as a method for charging (charging and / or discharging) electric vehicles. The method can further be understood as a method for guiding electric vehicles along a route. The method can also be understood as a method for avoiding the generation of charging energy with ecologically detrimental properties.

[0029] It is a further development that, during actual charging (charging and / or discharging), the ecological property actually assigned to the charging current is recorded. This can be advantageous, for example, for conducting an economic and / or ecological assessment.

[0030] The object is also achieved by a data processing device configured to carry out the method according to one of the preceding claims. The data processing device can be designed analogously to the method, and vice versa, and has the same advantages.

[0031] In one embodiment, the data processing device is an on-board system of the electric vehicle and / or a user terminal. The on-board system of the electric vehicle can, for example, comprise an on-board computer and / or an entertainment system. The user terminal can, for example, be a mobile user terminal such as a smartphone or a tablet PC. However, the data processing device can also be an external entity such as a network computer, a backend, e.g., of a manufacturer of the electric vehicle, etc.

[0032] The object is also achieved by a system comprising a data processing device as described above and at least one external instance which provides information about the at least one ecological property of the charging current, wherein the information can be transferred from the at least one external instance to the data processing device.

[0033] The system can be designed analogously to the method and / or the data processing device, and vice versa, and has the same advantages.

[0034] The object is further achieved by a computer program product comprising code which, when executed on the data processing device as described above and / or (e.g. distributed) on the system as described above, executes the method as described above.

[0035] The above-described properties, features and advantages of this invention, as well as the manner in which they are achieved, will become clearer and more clearly understood in connection with the following schematic description of an embodiment, which is explained in more detail in connection with the drawings. Fig. 1 shows a sketch of possible routes for route planning; Fig. 2 shows a possible sequence of the method for planning routes for an electric vehicle and for charging the electric vehicle.

[0036] Fig. Figure 1 shows a sketch of two possible routes A and B for route planning between a starting position P1 and a destination position P2. The starting position P1 is located at a home H belonging to a user of a fully electric vehicle (BEV). Home H has a photovoltaic system, which can generally be used to charge the BEV in excess via a charging point LP1, e.g., in the form of a so-called wallbox. For the charging energy at the wallbox, a renewable energy share of 95% is assumed here, as well as a price of €0.20 / kWh and a CO2 generation quantity of 40 g / kWh. The price can include, for example, the procurement costs of the photovoltaic system, the CO2 quantity can include the proportion of electrical energy not charged in excess, the amount of CO2 required to manufacture the photovoltaic system, etc.

[0037] At the target location P2, there may be a charging point LP2, such as a private or public charging station, provided at the hotel, etc. This charging point LP2 is supplied, for example, by a local energy supplier with charging current available at a price of €0.30 / kWh, a CO2 emission of 80 g / kWh, and a renewable energy share of 90%, for example, because it is primarily generated by wind power.

[0038] The user of the electric vehicle (BEV) now wants to determine a route from their home H to the destination P2. For purely exemplary and simplified purposes, the two routes A and B are available for selection. According to the user's wishes, the electric vehicle (BEV) should have a charging capacity of 80 kWh at the starting position P1 and a charging capacity of 30 kWh at the destination P2. For example, the starting time is specified as 11:00 a.m., and the latest arrival time is 4:30 p.m. Furthermore, it is assumed that the electric vehicle (BEV) consumes 20 kWh per 100 km on both routes A and B.

[0039] Route A is 500 km long, with a charging point LP3, e.g., a public charging station, located at the intermediate location P3. This charging station is forecast to provide charging energy at a price of €0.40 / kWh, with a CO2 emission of 200 g / kWh, and a renewable energy share of 75%. This high renewable energy share can be achieved, for example, through the use of solar farms. At the charging station LP3, the electric vehicle (BEV) is forecast to charge 50 kWh to achieve the desired charging capacity of 30 kWh at the destination location P2. This would result in an absolute CO2 emission on Route A of 50 kWh × 200 g / kWh = 1000 g. The user would have to pay 50 kWh × €0.40 / kWh = €20 for this.

[0040] Route B is 400 km long, with another charging point LP4, e.g., a public charging station, located approximately halfway along the route at intermediate position P4. This charging point LP4 is forecast to provide charging energy at a price of €0.80 / kWh, with a CO2 emission of 800 g / kWh, and a renewable energy share of 0%. The virtually nonexistent renewable energy share could be due, for example, to the exclusive use of coal-fired and / or gas-fired power plants. At charging station LP4, the electric vehicle BEV is forecast to only need to charge 30 kWh to achieve the desired charging capacity of 30 kWh at destination position P2. This would result in an absolute CO2 emission of 30 kWh × 800 g / kWh = 2400 g on Route B. The user would have to pay 30 kWh × €0.80 / kWh = €24 for this.

[0041] Through appropriate route planning, route A or route B can now be selected depending on the desired optimization, for example in the case of a - Target criterion “shortest route” route B; - Target criterion “fastest route” also route B, unless traffic volume, speed limits, etc. indicate otherwise; - Target criterion “cheapest charging” route A; - Target criterion ‘lowest CO2 emissions’ route A; and - Target criterion “highest share of renewable energy” route A.

[0042] However, under the same traffic conditions, the selected route may change if, for example, the corresponding forecast values for the target criteria "cheapest charging," "lowest CO2 emissions," and "highest renewable energy share" change. For example, a comparable price, CO2 emissions, and renewable energy share can be forecast for charging point LP3 compared to charging point LP4 if the trip is postponed to the evening or night, because solar power is no longer generated at that time, and the local energy supplier must rely on "grey" energy, as is the case at charging point LP4.

[0043] The "fastest route" target criterion also takes into account the expected time spent at charging points LP3 and LP4, particularly the charging time. This may depend, for example, on the predicted available charging power of the charging current.

[0044] However, feed-in at charging points LP3 or LP4 can also be considered, particularly at charging point LP4 under the forecast boundary conditions shown. This can, for example, help avoid generating charging energy with a 0% renewable energy share. In one scenario, for example, the maximum (standard) battery capacity of the drive battery of the electric vehicle BEV is so large that, even after partial discharge at intermediate position P4, it is still charged with 30 kWh upon arrival at the destination position. If, for example, the maximum (standard) battery capacity is 200 kWh and it is fully charged via home H, the electric vehicle BEV could feed back 90 kWh of electrical energy with a renewable energy share of 95% at intermediate position P4 without requiring further charging between P1 and P2. This can be remunerated accordingly in further training.

[0045] The route planning can be carried out or set up by means of at least one data processing device, for example by means of an on-board system BS of the electric vehicle, a user terminal SP and / or by means of another external data processing instance IT such as a route service provider, a backend of a manufacturer of the electric vehicle BEV.

[0046] Fig. 2 shows a possible flow of the method for planning routes for an electric vehicle BEV, including charging of the electric vehicle BEV.

[0047] In step S1 the route planning is started.

[0048] In step S2, at least a starting position and a destination position, as well as advantageously a starting time or an arrival time, are specified. If neither a starting time nor an arrival time is specified, an immediate starting time is assumed. Furthermore, in step S2, information about the type of vehicle (e.g., a fully electric vehicle, its energy consumption values, etc.) can optionally be specified, or corresponding default settings can be left as they are. Furthermore, a desired charge level of the drive battery at the destination position can optionally be entered.In addition, in step S2, user preferences can be specified or left as they are, such as selecting the route(s) with the lowest CO2 emissions or the highest share of renewable energy, or with the lowest CO2 emissions or the highest share of renewable energy, if this does not result in more than X € additional costs compared to the cheapest route, no more than Y additional kilometers compared to the shortest route and / or no more than Z minutes time loss compared to the fastest route, etc.

[0049] In step S3, data D1 to D4 required for route calculation are provided, e.g., from an internal data storage or from external sources. This data can, for example, include, as before, data D1 on an existing road network with associated information such as speed limits, construction sites, etc., as well as available charging points LP1 to LP4, and also data D2 on a traffic forecast. Furthermore, required data D1 to D4 here include forecast data D3 regarding the forecast price, CO2 generation volume, and renewable energy share at the charging points LP1 to LP4 for the predicted reaching of such a charging point. Furthermore, forecast data D4 regarding energy availability / available charging capacity or charging demand at the charging points and the associated power grids can also be requested. Data D3 and D4 are typically provided by external EV entities such as energy suppliers, energy traders, grid operators, etc.of the charging points P1 to P4 located in their supply areas.

[0050] In step S4, based on the information provided in steps S2 and S3, the available routes are evaluated or optimized for the desired target criterion. From this, the optimal route or several routes that best match the target criterion (e.g., the optimal route and the two subsequent routes) are determined. For relevant charging points LP1 to LP4, for example, the amount of energy to be charged / feeded back into the grid, the price, the amount of CO2 generated, and / or the share of renewable energy at a probable charging time, as well as the charging duration, can be calculated.

[0051] In step S5, the user is shown the most suitable route(s) with charging stops at charging points P1 to P4 for selection / driving instructions.

[0052] In step S6, a check is made to determine whether the trip has begun. If this has not yet been done ("N"), the system automatically or by the user returns to step S2 (as shown) or to step S3, particularly at regular intervals.

[0053] However, if the journey has been initiated ("Y"), route guidance is performed in step S7 as is generally known, in particular by updating at least data D2 to D4. The update may also include suggestions for changing a route, e.g., if information regarding price, CO2 emissions, and / or the renewable energy share of charging points LP2 to LP4 has changed.

[0054] Step S7 may include that when a specific charging point is approached and the electric vehicle BEV is connected to it, a currently suitable charging quantity (i.e., amount of energy for charging or discharging) is automatically transmitted from the route planning to the charging point, which then carries out a corresponding charging process, possibly after approval or modification by a user.

[0055] As part of the route guidance, a check is carried out in step S8 to determine whether the target position P2 has been reached. If this is not yet the case ("N"), the route guidance continues in step S7.

[0056] However, if the target position P4 is reached (“J”), the process is terminated.

[0057] Of course, the present invention is not limited to the embodiment shown.

[0058] In general, “a”, “an”, etc. can be understood as a singular or a plural, in particular in the sense of “at least one” or “one or more”, etc., as long as this is not explicitly excluded, e.g. by the expression “exactly one”, etc.

[0059] A numerical value may also include the exact number stated as well as a usual tolerance range, as long as this is not explicitly excluded. List of reference symbols A Route B Route BEV electric vehicle BS on-board system D1-D4 data EV External Instance H Home IT External data processing instance P1-P4 route positions LP1-LP4 charging points at the route positions SP user terminal S1-S9 process steps 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 2020 001 782 A1

[0004] DE 10 2022 201 646 A1

[0005]

Claims

[1] Method (S1-S9) for planning routes (A, B) for an electric vehicle (BEV), in which the routes (A, B) are evaluated based on at least one predicted ecological property of the charging current available along the routes (A, B) for charging the electric vehicle (BEV). [2] Method (S1-S9) according to claim 1, wherein the at least one ecological property comprises at least one property from the group - a quantity of at least one environmentally harmful substance, in particular gas, in particular CO2, emitted to generate the charging current, - a share of ecological energy sources, in particular renewable energy sources, in the charging current. [3] Method (S1-S9) according to one of the preceding claims, in which at least part of the charging current available along the route (A, B) is provided by at least one public charging station (P2-P4). [4] Method (S1-S9) according to one of the preceding claims, in which the electric vehicle (BEV) can feed back discharge current along the at least one route (A, B) and the at least one route (A, B) is additionally evaluated based on a possible saving of an environmentally harmful substance required for generating electrical energy and / or based on an increase in the proportion of ecological energy types due to a feed-in. [5] Method (S1-S9) according to one of the preceding claims, in which the routes (A, B) are evaluated for the at least one ecological property (S4). [6] Method (S1-S9) according to one of the preceding claims, in which preferences can be set by a user of the method as to whether the at least one ecological property is used to evaluate the routes (A, B) (S2). [7] Method (S1-S9) according to one of the preceding claims, in which a predicted charging power of the charging current is taken into account when planning the routes (S3). [8] Method (S1-S9) according to one of the preceding claims, in which an electric vehicle (BEV) is connected to a particularly proposed charging point (P1-P4) of the route (A, B) and is charged and / or discharged (S7) according to a charging plan predetermined by the route planning. [9] Method (S1-S9) according to one of the preceding claims, wherein the electric vehicle (BEV) is a fully electrically powered vehicle. [10] Data processing device (IT, SP, BS) which is designed to carry out the method (S1-S9) according to one of the preceding claims. [11] Data processing device (SP, BS) according to claim 8, wherein the data processing device is an on-board system (BS) of the electric vehicle (BEV) and / or a user terminal (SP). [12] System (IT, SP, BS, EV), comprising a data processing device (IT, SP, BS) according to one of claims 10 to 11 and at least one external instance (EV) which provides information (D3) about the at least one ecological property of the charging current, wherein the information (D3) is transferable from the at least one external instance (EV) to the data processing device (IT, SP, BS). [13] Computer program product comprising code which, when executed on the data processing device (IT, SP, BS) according to any one of claims 10 to 11 and / or on the system (IT, SP, BS, EV) according to claim 12, carries out the method (S1-S9) according to any one of claims 1 to 9.

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