Correction of vehicle energy consumption estimates

Abstract

The invention relates to a method and an energy consumption correction system (100) for correcting an estimate of the energy consumption of a vehicle (306) traveling through a road section (305) of a road network. In the method, the energy consumption expected to be required for traveling a road section (305) of a driving route (300) to be traveled by the vehicle (306) in the road network is calculated for the vehicle (306). The driving route (300) and additional data related to the vehicle (306) are transmitted to a data cloud (307). An estimate of the deviation between the actual energy consumption of the vehicle (306) traveling through the road section (305) and the calculated energy consumption expected to be required by the vehicle (306) for traveling through the road section (305) is determined in the data cloud (307). The calculated energy consumption expected to be required by the vehicle (306) for traveling through the road section (305) is corrected based on the estimate.

Description

Technical Field

[0001] The present invention relates to a method and an energy consumption correction system for correcting an estimate of the energy consumption of a vehicle traveling through a road section of a road network. Background Art

[0002] Many newer vehicles have an energy management system that calculates, among other things, the vehicle's projected energy consumption along a planned driving route. This calculation is particularly useful for electric vehicles, i.e., electrically powered vehicles, since they typically have a shorter driving range than comparable vehicles with internal combustion engines. Furthermore, there are still relatively few charging stations currently available for electric vehicles, at which their energy storage devices (drive batteries) can be charged.

[0003] For example, map data of a digital map, from which, for example, the road type and gradient along the driving route are derived, the driver's behavior of the vehicle driver, the vehicle occupancy rate and / or an estimated energy requirement of electrical consumers of the vehicle, such as the audio system or the air conditioning system, are used in the calculation of the estimated energy consumption.

[0004] The driving route of a vehicle from a starting position to a destination position is usually calculated using a route planner. A route planner is a computer program that is executed, for example, by a device with navigation functionality that is arranged in a vehicle or in a data cloud. The destination position of the driving route is usually derived from the destination specified by the user of the route planner. As an alternative, the destination position can also be estimated, for example, from the driving history of the vehicle. The starting position can also be derived from the user's preset. As an alternative, the starting position can be, for example, the current position of the vehicle. The position of the vehicle is usually determined using a navigation satellite system, such as GPS, GLONASS, BeiDou or Galileo.

[0005] The driving route can also be calculated based on the expected energy consumption. For example, the driving route can be calculated to minimize the expected energy consumption. Alternatively, the driving route can be calculated to allow the vehicle's energy storage device, such as a fuel tank or a drive battery, to be topped up along the driving route, for example, if the energy storage device is insufficiently full to reach the destination.

[0006] However, the accuracy of calculating the estimated energy consumption of a vehicle traveling a route is always limited, as not all parameters required for the calculation are precisely known. Therefore, the actual energy consumption required to travel the route will always deviate to some extent from the calculated estimated energy consumption. Therefore, calculating the estimated energy consumption of a vehicle traveling a route is an estimate of energy consumption, which has limited accuracy.

[0007] DE 102018104773 A1 discloses a method for determining the range of a motor vehicle or hybrid motor vehicle based on route planning. In this method, a route is divided into a plurality of route sections, and a route-specific interval energy requirement is provided for each route section. This interval energy requirement is normalized to a predetermined distance unit and a predefined weight. A vehicle-specific total energy requirement is then calculated using vehicle-specific data of the relevant motor vehicle and the normalized interval energy requirements for the route.

[0008] DE 102018203975 A1 discloses a driver assistance method for a vehicle, which includes: creating an energy forecast for a driving route based on expected driver behavior; determining a driving behavior optimized with respect to the energy forecast; and outputting an operation recommendation based on the optimized driving behavior. Summary of the Invention

[0009] The object of the present invention is to correct the estimate of the energy consumption of a vehicle traveling through a road section so as to make the estimate closer to the actual energy consumption of the vehicle traveling through the road section.

[0010] According to the invention, this object is achieved by a method for correcting an estimate of the energy consumption of a vehicle traveling through a section of a road network, wherein:

[0011] - calculating, for the vehicle, the energy consumption expected to be required to travel the section of the route that the vehicle is to travel in the road network,

[0012] - Transmitting the driving route and additional vehicle-related data to the data cloud,

[0013] - determining in the data cloud an estimate of the deviation between the actual energy consumption of the vehicle to traverse the route segment and the calculated estimated energy consumption required by the vehicle to traverse the route segment, and

[0014] - The calculated energy consumption that the vehicle is expected to need to travel the route section is corrected according to the estimated value.

[0015] That is, unlike the prior art known, for example, from DE 102018104773 A1, the method according to the present invention does not involve the actual calculation of the estimated energy consumption of a vehicle traveling a route segment. Instead, it involves correcting this calculation, i.e., correcting the estimated energy consumption calculated for the vehicle traveling the route segment. To this end, the deviation between the actual energy consumption of the vehicle traveling the route segment and the estimated energy consumption calculated for the vehicle traveling the route segment is determined in the data cloud. This estimated value is then used as a correction value to correct the estimated energy consumption calculated for the vehicle traveling the route segment.

[0016] The method according to the present invention also differs fundamentally from the driver assistance method known from DE 10 2018 203 975 A1, which proposes determining a driving behavior optimized with respect to energy forecasting and outputting maneuvering recommendations based on this optimized driving behavior. In other words, DE 10 2018 203 975 A1 aims to optimize energy consumption through targeted driving behavior rather than revising the calculation of the vehicle's projected energy consumption.

[0017] In one embodiment of the method according to the invention, an estimate of the deviation between the actual energy consumption of a vehicle traveling the route and the calculated energy consumption that the vehicle would have required to travel the route is determined by statistically evaluating vehicle consumption data transmitted to a data cloud and additional data related to each of these vehicles. The consumption data describes the calculated energy consumption that the vehicle would have required to travel the route section and the actual energy consumption of the vehicle traveling the route section.

[0018] According to the above-mentioned embodiment of the method of the present invention, the consumption data of multiple vehicles in the data cloud are therefore statistically evaluated in order to determine an estimated value of the deviation between the actual energy consumption of the vehicles walking through the road section and the calculated energy consumption that the vehicles are expected to need for walking through the road section. For example, if the statistical evaluation shows that the actual corresponding energy consumption statistically significantly exceeds the estimated energy consumption calculated for these vehicles to walk through the road section, the estimated value is revised upward accordingly. On the contrary, if the statistical evaluation shows that the actual corresponding energy consumption is statistically significantly lower than the estimated energy consumption calculated for these vehicles to walk through the road section, the estimated value is revised downward accordingly. That is, the estimated value is statistically determined by so-called group data, which includes the consumption data of multiple vehicles.

[0019] In another embodiment of the method according to the invention, when the consumption data and additional data for each section of the road network are statistically evaluated, a probability distribution of the deviation between the actual energy consumption of a vehicle traveling through the section and the calculated energy consumption that the vehicle is expected to require to travel through the section is determined.

[0020] In other words, a frequency distribution is determined based on the energy consumption data of multiple vehicles for each road section, and a probability distribution of the deviations between the actual energy consumption of the vehicles traveling the road section and the calculated energy consumption estimated to be required to travel the road section is determined from this frequency distribution. Thus, the estimated value used to correct the calculated estimated energy consumption is determined based on a probabilistic analysis of the energy consumption data of the multiple vehicles.

[0021] In a further embodiment of the method according to the invention, the consumption data are weighted as a function of the additional data in order to determine the probability distribution of the route segments.

[0022] By weighting, each of the consumption data is assigned a weight, and the consumption data is included in the statistical analysis of the consumption data according to the weight. For example, the weight of the later consumption data can be higher than that of the older consumption data, so that the later, and therefore more recent, consumption data has a greater impact on the statistical analysis results than the older consumption data.

[0023] In a further embodiment of the method according to the invention, the consumption data are transformed as a function of the additional data in order to determine the probability distribution of the route sections.

[0024] By appropriately transforming the consumption data, it can be made more comparable or compatible. For example, vehicle consumption data can be transformed based on the vehicle's mass so that it corresponds to a vehicle with a predetermined reference mass. This allows the influence of the vehicle's mass on its energy consumption to be compensated for in the statistical analysis of the consumption data.

[0025] In another embodiment of the method according to the invention, if there is not enough consumption data and additional data for a route segment in the data cloud, the consumption data and additional data used to determine the probability distribution for this route segment are replaced or supplemented by the existing consumption data and additional data for another route segment. For example, a route segment similar to the route segment for which there is not enough consumption data and additional data in the data cloud is selected as the other route segment.

[0026] The above-described embodiment of the method according to the present invention takes into account the situation where there is not enough consumption data and additional data stored in the data cloud for a particular route segment to enable a statistically meaningful evaluation of these data. In such cases, these data are replaced or supplemented by the consumption data and additional data available for another route segment. To ensure that the borrowed data corresponds as closely as possible to the route segment actually under consideration, a route segment similar to the route segment under consideration is preferably selected as the other route segment. Of course, data from multiple other routes can also be borrowed.

[0027] In another embodiment of the method according to the invention, the probability distribution of the road section is determined based on a time period during which the road section is traversed and / or weather conditions and / or traffic conditions when the road section is traversed.

[0028] In the above-described embodiment of the method according to the present invention, multiple probability distributions can be determined and evaluated for a road segment, one for each specific time period during which the road segment is traversed and / or for specific weather and / or traffic conditions during which the road segment is traversed. For example, a probability distribution can be determined for a road segment for traversing the road segment during rush hour, and another probability distribution for traversing the road segment outside of rush hour. In this way, the impact of the time period during which the road segment is traversed and / or the weather and / or traffic conditions during which the road segment is traversed on energy consumption can be taken into account.

[0029] In a further embodiment of the method according to the invention, the estimated value is transmitted from the data cloud to the vehicle, and the energy control device corrects the calculated energy consumption that the vehicle is expected to require to travel the route section as a function of the estimated value.

[0030] In the above-described embodiment of the method according to the invention, the actual correction of the calculated energy consumption estimated to be required to cover the route section is not performed in the data cloud, but by the energy control device of the vehicle based on estimated values.

[0031] In another embodiment of the method according to the invention, the additional data relating to the vehicle describes: the vehicle type of the vehicle; the energy control device of the vehicle; the software version of the software running on the control device of the vehicle, in particular the energy control device; the load of the vehicle when it travels through the road section; and / or the time point and / or time interval at which the vehicle travels through the road section.

[0032] By taking into account such additional data, an estimate can be determined vehicle-by-vehicle and / or trip-by-trip for the deviation of the actual energy consumption of the vehicle for traversing the route section from the calculated energy consumption that the vehicle is expected to require for traversing the route section.

[0033] In another embodiment of the method according to the invention, the estimated value describes the relative deviation of the actual energy consumption of the vehicle for traveling the route section from the calculated energy consumption that the vehicle is expected to need for traveling the route section.

[0034] The relative deviation of the actual energy consumption from the calculated estimated energy consumption is the (normalized) deviation from the calculated estimated energy consumption, i.e. the deviation of the actual energy consumption from the calculated estimated energy consumption divided by the calculated estimated energy consumption. The advantage of using the relative deviation as an estimate is that it is largely independent of the specific characteristics of the road section and the vehicle, such as the length of the road section and the mass of the vehicle.

[0035] According to the invention, this object is also achieved by an energy consumption correction system for correcting an estimate of the vehicle's energy consumption when a navigation device of the vehicle travels through a section of a road network, the energy consumption correction system comprising:

[0036] a database configured to assign consumption data and additional data, which are transmitted to the data cloud, to each section of the road network, the consumption data and additional data respectively describing the estimated energy consumption calculated for the vehicle for traveling each section and the actual energy consumption of the vehicle traveling the section, as well as additional vehicle-related data;

[0037] an evaluation service configured to determine, in the data cloud, for each section of the road network, based on the consumption data and additional data stored in the database, a probability distribution of the deviation of the actual energy consumption of a vehicle traveling this section from the calculated energy consumption that the vehicle would have expected to have required to travel this section,

[0038] an estimation service configured to determine, in the data cloud, for a segment of a route to be traveled by the vehicle in the road network, an estimated value of a deviation between the actual energy consumption of the vehicle for traveling the segment and the calculated energy consumption expected to be required for the vehicle to travel the segment, based on a probability distribution determined for the segment; and

[0039] A calculation unit is configured to correct the calculated energy consumption that the vehicle is expected to require to travel the route section as a function of the estimated value.

[0040] Such an energy consumption correction system is capable of executing the method according to the invention. The advantages of the energy consumption correction system are therefore derived from the above-mentioned advantages of the method according to the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The embodiments of the present invention will be explained in more detail below with reference to the accompanying drawings, in which:

[0042] Figure 1 A block diagram showing an embodiment of an energy consumption correction system according to the present invention is shown.

[0043] Figure 2 shows a flow chart of an embodiment of the method according to the present invention,

[0044] Figure 3 The driving route of the vehicle is shown. DETAILED DESCRIPTION

[0045] Figure 1 FIG. 1 is a block diagram of an energy consumption correction system 100 according to an embodiment of the present invention, wherein the energy consumption correction system is used to correct the estimated energy consumption of a vehicle traveling along a road section of a road network. The energy consumption correction system 100 includes Figure 1 The following functional units are shown: database 101 , assessment service 102 , estimation service 103 and calculation unit 104 .

[0046] Database 101 is set up to allocate consumption data and additional data to the sections of the road network and transmit them to the data cloud. These consumption data and additional data respectively describe the energy consumption calculated for the vehicle to be required to travel through each section and the actual energy consumption of the vehicle to travel through the section, as well as additional data related to the vehicle.

[0047] Additional vehicle-related data describes, for example: the vehicle type of the vehicle; the vehicle's energy control device; the software version of the vehicle's software running on the control device, in particular the energy control device; the load of the vehicle when traveling through the road section; and / or the time point and / or time interval when the vehicle travels through the road section.

[0048] The evaluation service 102 is set up to determine in the data cloud, for each section of the road network, a probability distribution of the deviation between the actual energy consumption of a vehicle traveling through the section and the calculated energy consumption expected to be required for the vehicle to travel through the section based on the consumption data and additional data stored in the database 101.

[0049] The estimation service 103 is set up to determine in the data cloud, for a section of the route that the vehicle is to travel in the road network, an estimated value of the deviation between the actual energy consumption of the vehicle traveling through the section and the calculated energy consumption that the vehicle is expected to need to travel through the section based on the probability distribution determined for the section.

[0050] The calculation unit 104 is configured to correct the calculated energy consumption that is expected to be required for the vehicle to travel the route section according to the estimated value.

[0051] The database 101 , the evaluation service 102 , and the estimation service 103 are each implemented by a computer program executed in a data cloud, for example. The computing unit 104 is, for example, a component of an energy control device of a vehicle.

[0052] Figure 2 A flow chart 200 is shown of a method according to an embodiment of the present invention, comprising method steps 201 to 204 for correcting an estimate of the energy consumption of a vehicle travelling along a section of a road network. Figure 1 The energy consumption correction system 100 described is implemented.

[0053] Also refer to the following Figure 3 Method steps 201 to 204 are described.

[0054] Figure 3 Driving route 300, traveled by vehicle 306, is shown. Driving route 300 extends from a starting point 301 to an end point 302. Also shown is a road segment 305 of driving route 300. Road segment 305 extends from a first intermediate point 303 on driving route 300 to a second intermediate point 304 on driving route 300. Vehicle 306 communicates with a data cloud 307 via a radio connection 308, for example, a mobile radio connection.

[0055] In a first method step 201 , the energy consumption that is expected to be required for vehicle 306 to travel section 305 of driving route 300 is calculated.

[0056] In a second method step 202, driving route 300 with road section 305, the energy consumption calculated for vehicle 306 and estimated to be required for traveling road section 305, and additional data related to vehicle 306 are transmitted to a data cloud 307. The additional data may describe, for example: the vehicle type of vehicle 306; the energy control device of vehicle 306; the software version of the software running on the control device of vehicle 306, in particular the energy control device; the load of vehicle 306; and / or the times and / or time intervals at which vehicle 306 is expected to travel road section 305.

[0057] In a third method step 203, the estimation service 103 determines in the data cloud 307 an estimated value for the deviation of the actual energy consumption of the vehicle 306 for traversing the route section 305 from the calculated energy consumption that the vehicle 306 is expected to require for traversing the route section 305. This estimated value describes the estimated relative deviation of the actual energy consumption of the vehicle 306 for traversing the route section from the calculated energy consumption that the vehicle 306 is expected to require for traversing the route section.

[0058] This estimated value is determined by statistically evaluating the vehicle consumption data and additional data related to these vehicles stored in database 101. The consumption data describes the calculated estimated energy consumption required by the vehicle to travel a section of the road network and the actual energy consumption of the vehicle during the travel of the section. The additional vehicle-related data describes, for example: the vehicle type; the vehicle's energy control device; the software version of the vehicle's control device, particularly the software running on the energy control device; the vehicle's load; and / or the times and / or time intervals at which the vehicle traveled the section.

[0059] During the statistical evaluation of the consumption data and the additional data, the evaluation service 102 determines, for each section of the road network, a probability distribution of the deviations between the actual energy consumption of a vehicle traveling this section and the calculated energy consumption that the vehicle is expected to require for traveling this section.

[0060] To determine the probability distribution of the route segments, the consumption data can be weighted, for example, as a function of the additional data, with later consumption data being weighted more highly than earlier consumption data.

[0061] Furthermore, the consumption data can be transformed, for example, as a function of the additional data. For example, the consumption data of a vehicle can be transformed as a function of the vehicle's mass so that they correspond to a vehicle with a predefined reference mass.

[0062] Furthermore, if there is not enough consumption data and additional data for a route segment in the data cloud 307, the consumption data and additional data used to determine the probability distribution for this route segment are replaced or supplemented by the existing consumption data and additional data for another route segment. For example, a route segment similar to the route segment for which there is not enough consumption data and additional data in the data cloud 307 is selected as the other route segment.

[0063] In addition, the probability distribution of a road section can be determined based on the time period of the road section and / or the weather conditions and / or traffic conditions when the road section is traveled. For example, the weather conditions and / or traffic conditions are obtained from the relevant information services of the data cloud 307 or other data clouds.

[0064] In fourth method step 204 , calculation unit 104 corrects the calculated energy consumption that vehicle 306 is expected to require to travel route section 305 based on the estimated value determined in third method step 203 . For this purpose, the estimated value is transmitted from data cloud 307 to vehicle 306 and supplied to calculation unit 104 .

[0065] Reference Signs List

[0066] 100 Energy Consumption Correction System

[0067] 101 Database

[0068] 102 Assessment Services

[0069] 103 Estimation Services

[0070] 104 computing units

[0071] 200 Flowchart

[0072] Method steps 201 to 204

[0073] 300 driving routes

[0074] 301 Starting Point

[0075] 302 End

[0076] 303 First midpoint

[0077] 304 Second midpoint

[0078] Section 305

[0079] 306 vehicles

[0080] 307 Data Cloud

[0081] 308 Radio Connection

Claims

1. A method for correcting an estimate of energy consumption of a vehicle (306) traveling along a road segment (305) of a road network, wherein: - calculating, for the vehicle (306), the energy consumption expected to be required for traveling along a road segment (305) of a route (300) to be traveled by the vehicle (306) in the road network, - transmitting the travel route (300) and additional data related to the vehicle (306) to a data cloud (307), - determining in the data cloud (307) an estimate of the deviation of the actual energy consumption of the vehicle (306) for traversing the road section (305) from the calculated energy consumption that the vehicle (306) is expected to require for traversing the road section (305), and - correcting the calculated estimated energy consumption of the vehicle (306) for traveling the road section (305) according to the estimated value, When statistically evaluating the consumption data and additional data for each road section (305) of the road network, a probability distribution of the deviation between the actual energy consumption of a vehicle traveling through the road section (305) and the calculated energy consumption estimated for the vehicle to travel through the road section (305) is determined, wherein the consumption data respectively describe the calculated energy consumption estimated for the vehicle to travel through the road section (305) of the road network and the actual energy consumption of the corresponding vehicle traveling through the road section (305), wherein the estimated value is determined by group data statistics, and the group data includes consumption data of multiple vehicles.

2. The method according to claim 1, wherein The estimated value of the deviation from the actual energy consumption is determined by statistically evaluating the vehicle consumption data transmitted to the data cloud (307) and additional data respectively related to the vehicle.

3. The method according to claim 1 or 2, wherein: In order to determine the probability distribution of the route section (305), the consumption data are weighted according to the additional data.

4. The method according to claim 1 or 2, wherein: In order to determine the probability distribution of the route section (305), the consumption data are transformed according to the additional data.

5. The method according to claim 1 or 2, wherein: If there is not a sufficient amount of consumption data and additional data in the data cloud (307) for a route (305), the consumption data and additional data used to determine the probability distribution of the route (305) are replaced or supplemented by the existing consumption data and additional data of another route.

6. The method according to claim 5, wherein: A section similar to the section ( 305 ) for which there is not a sufficient amount of consumption data and additional data in the data cloud ( 307 ) is selected as another section.

7. The method according to claim 1 or 2, wherein: The probability distribution of the road section (305) is determined based on a time period during which the road section (305) is traversed and / or weather conditions and / or traffic conditions during the traversal of the road section (305).

8. The method according to claim 1 or 2, wherein: The estimated value is transmitted from the data cloud (307) to the vehicle (306), and the energy control device corrects the calculated energy consumption expected to be required by the vehicle (306) to travel the road section (305) based on the estimated value.

9. The method according to claim 1 or 2, wherein: The additional data related to the vehicle (306) describe: the vehicle type of the vehicle (306); the energy control device of the vehicle (306); the software version of the software running on the control device of the vehicle (306); the load of the vehicle (306) when passing through the road section (305); and / or the time point and / or time interval when the vehicle (306) passes through the road section (305).

10. The method according to claim 9, wherein: The additional data relating to the vehicle (306) describe the software version of the software running on the energy control device of the vehicle (306).

11. The method according to claim 1 or 2, wherein: The estimated value describes the relative deviation between the actual energy consumption of the vehicle (306) when traveling through the road section (305) and the calculated energy consumption expected to be required for the vehicle (306) to travel through the road section (305).

12. An energy consumption correction system (100) for correcting an estimate of energy consumption of a vehicle (306) traveling along a road segment (305) of a road network, the energy consumption correction system comprising: a database (101) configured to assign consumption data and additional data to each of the road sections (305) of the road network, which are transmitted to a data cloud (307), the consumption data and additional data respectively describing the estimated energy consumption of the vehicle calculated for traveling each road section (305) and the actual energy consumption of the vehicle traveling the road section (305), as well as additional data related to the vehicle, an evaluation service (102) configured to determine, in the data cloud (307), for each road section (305) of the road network, a probability distribution of the deviation of the actual energy consumption of a vehicle traveling the road section (305) from the calculated energy consumption that the vehicle is expected to require for traveling the road section (305), based on the consumption data and additional data stored in the database (101), an estimation service (103) configured to determine, in the data cloud (307), for a section (305) of the route (300) to be traveled by the vehicle (306) in the road network, an estimate of the deviation of the actual energy consumption of the vehicle (306) for traveling the section (305) from the calculated energy consumption that the vehicle (306) is expected to consume for traveling the section (305), based on a probability distribution determined for the section (305); and a calculation unit (104) configured to correct the calculated estimated energy consumption of the vehicle (306) for traveling the route section (305) based on the estimated value, When statistically evaluating the consumption data and additional data for each road section (305) of the road network, a probability distribution of the deviation between the actual energy consumption of a vehicle traveling through the road section (305) and the calculated energy consumption estimated for the vehicle to travel through the road section (305) is determined, wherein the consumption data respectively describe the calculated energy consumption estimated for the vehicle to travel through the road section (305) of the road network and the actual energy consumption of the corresponding vehicle traveling through the road section (305), wherein the estimated value is determined by group data statistics, and the group data includes consumption data of multiple vehicles.

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