Control device and method for predictively operating an energy vehicle-mounted electrical system.

Abstract

To improve the operation of on-board electrical system control in motor vehicles, especially with regard to resource-optimizing prediction of expected charging flows. [Solution] A control device (10) for operating an energy on-board electrical system (15) of a motor vehicle (1), the control device having an input unit (14) configured to calculate operating parameters of the energy on-board electrical system of the motor vehicle and / or one or more ambient parameters of the motor vehicle and pass them on to a processing unit of the control device, wherein at least one ambient parameter is the probability of a third-party vehicle operating action.

Description

Technical Field

[0001] The present invention relates to a control device and method for operating an in-vehicle energy electric system (in-vehicle energy power supply system) of a vehicle with a prime mover. Furthermore, the present invention particularly relates to a central database device capable of communicating with the control device.

Background Art

[0002] In many known operating methods of in-vehicle electric systems, particularly in hybrid vehicles, the identification of operating actions necessary for further operation of the in-vehicle electric system (especially the control of traction using the electromechanics of hybrid vehicles) is performed only depending on the operating parameters of the vehicle itself.

[0003] With the spread of accompanying technologies such as a navigation system and the assignment of terrain parameters to georeference points on the map of the navigation system, it has become possible to set operating actions for controlling the drive unit depending on such conditions, for example, an inclined section in a planned route. And, for example, it is possible to configure the battery to actively discharge before an inclined section when the battery is in an initial high state of charge so that "free" energy based on regeneration can be fully received on a slope.

[0004] With the improvement of the transmission performance of mobile radio communication networks, it has gradually become possible to introduce the operating states and / or operating parameters of other vehicles into the control of one's own vehicle. A system having such functionality is described in, for example, Patent Document 1 or Patent Document 2.

[0005] However, due to the numerous operating parameters that must be considered, it is difficult to find a sufficiently accurate "example" for adjusting the control of the vehicle under consideration to serve as a basis (reference point) for the control of the vehicle being examined. This is because, in order to ensure that the vehicle in question is indeed the one to be considered as an "example," it is necessary to transmit not only the vehicle type, time, and exact location, but also the vehicle's specific state. And this specific state is obtained based on numerous operating parameters of other vehicles, all of which also need to be transmitted. Therefore, such a solution requires the exchange of a large amount of data, and furthermore, it is uncertain whether a suitable "example" with data already preserved there will always be provided for a given location criterion. [Prior art documents] [Patent Documents]

[0006] [Patent Document 1] German Patent Application Publication No. 102017214384 Specification [Patent Document 2] U.S. Patent No. 9327712 [Non-patent literature]

[0007] [Non-Patent Document 1] For information on the Reflex-Augmented Reinforcement Learning algorithm, see "International Conference on Artificial Intelligence ICAI 18," pp. 429-430, CSREA Press, ISBN: 1-60132-480-4. [Overview of the project] [Problems that the invention aims to solve]

[0008] Against this backdrop, the object of the present invention is to improve the operation of on-board electrical system control in motorized vehicles, particularly with regard to predictions that optimize the resources of the expected charging flow. [Means for solving the problem]

[0009] The problem is solved by a control device having the features of claim 1, a method having the features of claim 8, and a central database device having the features of claim 10. Dependent claims relate to advantageous developments of the present invention.

[0010] According to one embodiment, a control device is provided for operating an on-board electrical energy system of a motorized vehicle, the motorized vehicle being, in particular, a hybrid drive unit having an electromechanical and an internal combustion engine or at least one internal combustion engine and regenerative capability.

[0011] The control unit includes an input unit configured to calculate, in particular detect, and pass to a processing unit of the control unit the operating parameters (i.e., in particular operating states) and / or one or more ambient parameters (i.e., in particular ambient states) of the motorized vehicle's energy onboard electrical system, and in particular identify the operating actions of the onboard electrical system.

[0012] At least one ambient parameter is the probability of a third-party vehicle action, which could be, for example, active regenerative braking of an electromechanical system or an activated start-stop function (i.e., a temporarily turned-off internal combustion engine).

[0013] This enables improved prediction of the future operating state of the in-vehicle electrical system, for example, improved prediction of the amount of charge to be provided for the in-vehicle electrical system in the near future (e.g., within the prediction range), simultaneously, in a smaller amount with greater independence from the data to be provided or transmitted (to the input unit) and / or other operating parameters of the third-party vehicle. This results in an improved possibility of optimally adjusting the energy storage unit of the in-vehicle electrical system to the expected amount of charge, resulting in sufficient storage space being available and / or that storage space being charged to the optimal level.

[0014] In addition, by taking into account the probability of a predetermined action in other vehicles within a group of vehicles (=third-party vehicles), it becomes possible to use reliable metrics for ambient conditions that, due to their characteristics, make deterministic and physical identification difficult for predetermined predictions such as regenerative braking predictions. This is the case, for example, in regenerative braking predictions on flat terrain, whereas in the case of steeply inclined road transitions, the deterministic identification of the expected charge amount can be done with high quality depending on parameters such as vehicle weight and speed.

[0015] In addition, the control device includes a processing unit that executes an operational strategy and an output unit that outputs appropriate control commands.

[0016] The control device can be understood here as an on-board electrical system control means specifically formed beyond all embodiments of the present invention, particularly for motorized vehicles having a hybrid drive unit.

[0017] The term "control" should be interpreted broadly here, and may include "closed-loop control" in particular.

[0018] "Calculate" can be understood here as making the parameter value available or finding it, and "detect" can be understood here, in particular, as making the parameter value calculated using a sensor device available.

[0019] The term "operating state" can be understood here as the overall characteristics (characteristics and values ​​are used synonymously here) of the operating parameters relevant to the consideration. The term "ambient state" can be understood here as the overall characteristics (=values) of the ambient parameters relevant to the consideration.

[0020] In this context, an on-board electrical system operation action can be understood as an action of an on-board electrical system aimed at a particularly desired change in the operating state of a motorized vehicle.

[0021] In another embodiment, a method is provided for operating an on-board energy electrical system of a motorized vehicle, the method comprising at least the following steps, as described or in any other appropriate and professionally reasonable sequence:

[0022] (a) Calculate one particular current and / or currently available value for each of the energy onboard electrical systems and / or one or more ambient parameters of the vehicle, where at least one of the ambient parameters is the probability of a third-party vehicle action.

[0023] (b) Transmit the calculated value to the processing unit of the control device.

[0024] (c) Identifying possible in-vehicle electrical system actions, in particular, depending on the calculated values, especially the calculated probabilities of third-party vehicle actions. It has.

[0025] In particular, the values ​​of the operating parameters of the energy-in-vehicle electrical system and / or the values ​​of one or more ambient parameters of the vehicle can be calculated using the input unit of the control device.

[0026] According to one embodiment, the calculated parameter values ​​are transmitted to the processing unit of the control device.

[0027] According to one embodiment, (a1) The expected route of the vehicle under consideration is calculated here, (a2) The probability of a third-party vehicle action is calculated for all georeferenced points along the route, The probability of a third-party vehicle action being performed is calculated.

[0028] According to one embodiment, (c1) All probability values ​​that exceed the relevant limit and that the georeference point is within the prediction range are taken into consideration, and / or (c2) For each of the probability values ​​considered or for the georeference point, the expected charge contribution is identified and / or (c3) The sum of the expected charge contributions is transmitted to the input unit, and / or (c4) Based on the total, the processing unit makes decisions regarding the operation actions of the in-vehicle electrical system. The in-vehicle electrical system operation action is determined based on the calculated probability of the third-party vehicle operation action.

[0029] According to one embodiment, (c_i) The in-vehicle electrical system operation action is identified based on a learned operation strategy, particularly based on a unit having the learning capability of the processing unit of the control unit of the motor vehicle. (c_ii) The operating actions of the on-board electrical system are checked based on a predetermined check strategy, in particular the reflex unit of the processing unit of the control unit of the motor vehicle.

[0030] This allows (ambient) probability-based predictions to contribute to faster and / or better learning of efficient operating strategies for in-vehicle electrical systems, and furthermore, according to one embodiment, it is possible to set effective control by the reflex unit. In this way, the updated (i.e., current) probabilities contribute to the steady development of the operating strategy, because the safety (certainty) of the proposed in-vehicle electrical system operating actions controlled by the reflex unit allows for learning of the learning-capable unit even during regular customer service.

[0031] According to one embodiment, the processing unit includes a unit with learning capabilities, which is configured to output possible in-vehicle electrical system operation actions based on a learned operation strategy. In particular, the processing unit includes a reflex unit, which is configured to check possible operation actions based on a predetermined strategy. For example, such a processing unit and related Non-Patent Document 1 and Patent Document 1 are shown therein.

[0032] In another embodiment, a central database device is provided, in particular a server having a database and a communication device for data exchange with all other vehicles of the vehicle and vehicle group considered herein.

[0033] The device is (i) In particular via the mobile radio connection of the communication device, to receive and, if applicable, store indicator values ​​for operational actions in one of several third-party vehicles or within the range of georeference points of several third-party vehicles, and / or (ii) to calculate the probability of the presence of motion action at the georeference point based on the transmitted value of the indicator, and / or (iii) The probability thus calculated for a georeference point (i.e., the probability of belonging to a georeference point) is transmitted, in particular via a mobile radio connection, to a control device of a motorized vehicle formed in particular according to any one of claims 1 to 12. It is composed of.

[0034] This makes it possible to provide each vehicle in a group of vehicles with a predetermined operational action for each georeference point, for all third-party vehicles or all related third-party vehicles that have passed through that georeference point.

[0035] According to one embodiment, in the database of the central database device, for each georeference point on the map under consideration, the operating parameters related to all vehicles in the vehicle group under consideration at that time are stored in a georeference point dataset. Furthermore, the georeference point dataset includes, in particular, all parameters related to the area surrounding the georeference point.

[0036] In particular, based on predetermined operating parameters transmitted from individual third-party vehicles, such as indicators for regenerative braking or active start-stop automatic operation devices, it is possible to calculate the probability of the existence of an operating action for all third-party vehicles or for all relevant third-party vehicles with respect to a given combination of parameters and values.

[0037] In particular, data transmission between each third-party vehicle and a central database device that stores parameter values ​​for georeferencing points, and between the central database device and the vehicles considered herein, are performed using a data connection unit and / or mobile radio communication network to retrieve probability values ​​and, if applicable, necessary parameter values.

[0038] Whether a third-party vehicle or a dataset of third-party vehicles is considered important (relevant) to the vehicle making the response request may be determined based on, for example, the type of vehicle and / or the time and / or the type of day.

[0039] According to one embodiment, the probability in question is calculated using the ratio of the number of relevant third-party vehicles that passed through the georeferenced point for which a response was requested to be made to the number of vehicles under consideration of the third-party vehicle for which the action for which a response was requested regarding the probability of existence was present (or at least present to a relevant degree).

[0040] The present invention is based, in particular, on the idea that in artificial intelligence methods (e.g., Reinforcement Learning (RL) or Reflex-Augmented Reinforcement Learning (RARL)), (but not limited to) thereto, it is possible to use georeferenced probabilities about regeneration to control the efficiency of a control algorithm.

[0041] The prediction approach using the probability of motion actions occurring at georeferenced points can also be applied to, for example, the occurrence of start-stop situations. The present invention will be described below in the example of regenerative braking prediction, illustrating its embodiments.

[0042] According to one embodiment, a map is used which has vehicle group data in which the probability of regeneration (i.e., active regeneration of the electromechanical unit of the vehicle's drive system) at georeference points along the expected driving section of the vehicle is stored. The map stores the probability of regeneration at the georeference points.

[0043] In one embodiment, georeferencing points that the vehicle will pass through within the next few seconds (e.g., a predicted range of 10 to 30 seconds) are identified by route information based on the navigation device.

[0044] According to one embodiment, for example, in measurement activities in vehicle development, and / or in real time in response to online response requests from a central database device, a characteristic charge expected for a vehicle type is calculated for a road type and a predetermined speed interval.

[0045] For example, only reference points with a regeneration probability exceeding a relevant threshold (e.g., a 75% threshold) are considered.

[0046] The data is transmitted to the vehicle in real time or daily, updated from the backend, i.e., a central database device, or stored there in a basic version. Alternatively, according to one embodiment, if the data basis is insufficient, characteristic charges can be calculated in the vehicle using a physical model (e.g., mechanical energy, gradient, etc.).

[0047] According to one embodiment, for all georeferencing points in the prediction range that have a regenerative probability exceeding the relevant limit value, characteristic charging is aggregated with respect to the road type and expected vehicle speed (e.g., utilization of congestion prediction), making it possible to calculate the predicted charging for the prediction range.

[0048] According to one embodiment, the predicted charge within the predicted range is passed to an energy management algorithm (e.g., RARL). During the expected regenerative charging, it is possible to control, for example, the operating actions of the vehicle drive unit's energy storage unit, which involve slightly stronger charging or weaker discharging. Therefore, it is possible to pre-adjust the energy storage unit so that it can accept the entire energy based on the predicted regeneration. Without pre-adjustment, it may not be possible to accept the entire energy based on regeneration, or it may only be possible to accept it within a battery charging range with poor charge acceptance, which can lead to a slight decrease in the vehicle's efficiency.

[0049] According to one embodiment, the probability of a third-party vehicle action is calculated based on the presence, absence, or degree of third-party vehicle action in multiple third-party vehicles.

[0050] For example, by calculating the probability of a predetermined operational action based on the corresponding circumstances of multiple different third-party vehicles, each at the same location and / or at the same time and / or corresponding to the same vehicle type, it becomes possible to make improved predictions of the specific on-board electrical system operational actions for the vehicle under consideration. This applies when the vehicle under consideration is in a situation (e.g., location, time, vehicle type, etc.) for which the probability of a third-party vehicle operational action has been calculated.

[0051] Third-party vehicle operation actions can be understood in particular as operation actions of one other vehicle in a group of vehicles (e.g., drive operation actions, consumption unit and / or on-board electrical system operation actions).

[0052] According to one embodiment, the probability is linked to georeferencing, so that the probability of a third-party vehicle action for a given georeferencing point is calculated in particular.

[0053] This makes it possible to predict the operating state and / or operating parameters of a vehicle for a given location, and in particular for the expected route of a vehicle along multiple consecutive georeferencing points.

[0054] In particular, the presence, absence, or degree of third-party vehicle action for each third-party vehicle within the georeferencing point or, in some cases, the georeferencing range around the point is calculated.

[0055] A georeferencing point can be understood here as a coordinate pair (or another appropriate definition of an area-free point) in a vehicle map, particularly in a navigation system. Even when a georeferencing point is described as a coordinate pair, the values ​​of the operational parameters or operational actions calculated for that georeferencing point relate to the georeferencing range surrounding the georeferencing point. For example, two adjacent georeferencing points can each have a georeferencing range that extends to the center of the distance between the two georeferencing points.

[0056] According to one embodiment, the control device includes a processing unit configured to identify an in-vehicle electrical system operation action depending on a calculated probability. This makes it possible to incorporate the calculated probability of a third-party vehicle operation action into the identification of the in-vehicle electrical system operation action to be selected.

[0057] According to one embodiment, the control device includes an output unit, which is configured to output control commands for the operation of the energy vehicle electrical system based on identified vehicle electrical system operation actions, particularly when the check by the reflex unit is positive.

[0058] According to one embodiment, the processing unit is configured to identify an in-vehicle electrical system operation action based on multiple probabilities of third-party vehicle operation actions. This makes it possible to improve the predictive quality of probabilities used as an overall indicator for prediction.

[0059] In particular, probabilities have been calculated for different georeferencing points, and specifically for other georeferencing points.

[0060] According to one embodiment, probabilities are calculated for consecutive georeferencing points along the expected route of a motorized vehicle. This makes it possible to associate predictions of operating conditions and / or operating parameters with similar conditions based on the underlying locations.

[0061] For example, the probability of regenerative braking action occurring in other vehicles at predetermined or multiple georeference points can be considered, in some cases, in determining whether it is meaningful to adjust the vehicle's specific energy storage unit in light of the expected charge amount.

[0062] The expected route, in this context, can be understood as the route currently set by the navigation system and / or the route considered most likely for the immediate future, particularly on the order of a few seconds to a few minutes.

[0063] According to one embodiment, multiple probabilities, particularly multiple consecutive georeferencing points, each with a specified probability, are limited by the prediction range.

[0064] This makes it possible to restrict predictions, and therefore particularly necessary data transfers, to timeframes where meaningful recovery is impossible in any case afterward, because the probability of a predicted scenario occurring is increasingly reduced by an ever-growing number of factors that are different from the predicted scenario and lie between them.

[0065] In particular, the prediction range is defined by the expected time delay to the expected arrival of the relevant georeferencing points, or by the number of consecutive georeferencing points.

[0066] According to one embodiment, an in-vehicle electrical system operation action is identified, in particular, based only on a georeferencing point where the probability value calculated for a third-party vehicle operation action corresponds to at least one relevant limit value of 60%, 75%, or 90%.

[0067] This ensures that probabilities or georeferencing points are taken into account to identify onboard electrical system operating actions, which, based on clear trends, can contribute to improved predictions (particularly in physically identified calculations, such as comparisons with expected charge levels for the vehicle's energy storage units).

[0068] According to one embodiment, the processing unit is configured to calculate one expected charge for each georeference point under consideration.

[0069] This allows the processing unit to provide a reliable basis for decision-making in the form of characteristic quantities, enabling it to determine the amount of expected benefits (e.g., optimal charging) that outweigh the associated drawbacks (e.g., pre-adjustment of the vehicle's energy storage system).

[0070] The choice of georeferencing points to consider is determined by, in particular, taking into account, or depending on, the relevant limits and / or predicted range and / or the expected route of the vehicle.

[0071] The expected charge amount is calculated depending on the surrounding parameters and / or at least one operating parameter of a third-party vehicle, particularly those set for the georeference point.

[0072] The expected charge amount can be understood as the charge amount obtained by considering the probability calculated based on the vehicle's surrounding parameters and operating parameters at a predetermined georeferencing point or predetermined adjacent georeferencing points.

[0073] According to one embodiment, the processing unit is configured to identify an on-board electrical system operation action based on a characteristic indicator of a georeference point, depending on (I) the probability of a third-party vehicle operation action, or (II) one or more other known ambient parameters of the georeference point.

[0074] The processing unit can determine, based on characteristic indicators, whether the prediction is promising based on the physical relationship between the vehicle's operating parameters and surrounding parameters, or based on probability values ​​for the considered operating actions of a third-party vehicle. This makes it possible to always select an improved prediction basis for each georeferencing point.

[0075] In this case, by taking into account the probability of a predetermined action in other vehicles, it becomes possible to use reliable metrics for such ambient conditions that, due to their characteristics, make deterministic and physical identification difficult for predetermined predictions, such as regenerative braking predictions.

[0076] This is the case, for example, in regenerative braking prediction on flat terrain, whereas in steeply inclined road conditions, the deterministic determination of the expected charge amount is possible with good probability, depending on parameters such as vehicle weight and speed. In the last example given, instead of probability, physical relationships can be taken into account to identify the on-board electrical system operation action that should be selected.

[0077] Therefore, the selectability of the basis for prediction makes it possible to achieve improved efficiency in electric energy systems in vehicles. In particular, characteristic indicators can take values, for example, "deterministically" or "stochastically".

[0078] For example, a "deterministic" value can be obtained if the regenerative potential for a georeference point can be calculated quasi-deterministically as a function of gradient, vehicle weight, and speed, or if the presence of start-stop-off of the internal combustion engine at the georeference point can be calculated quasi-deterministically as a function of time or the type of ratio (e.g., workday, holiday, weekend, travel day, holiday on the commute route, etc.).

[0079] For example, a value that is "probabilistic" can be obtained if, at a georeference point, there is a flat road that has a different effect on the regenerative potential that does not follow any regularity, or if there is an internal combustion engine start-stop-off.

[0080] According to one embodiment, the control device, in particular the input unit, is configured to obtain the values ​​of surrounding parameters for a georeference point (i) online and / or up-to-date from a central database device, and / or (ii) from the memory of the control device, in particular the processing unit.

[0081] By obtaining data from a central database system, particularly from backend servers, it becomes possible to continuously update probability values.

[0082] In particular, by obtaining the probability values ​​from the memory device of the control device, which can be set or updated during installation or factory maintenance of the vehicle, it becomes possible to utilize the present invention without a data connection unit and / or a mobile wireless communication network.

[0083] According to one embodiment, a combined operation is also set up in which, rather than in real time, the probability dataset stored in the control device's local memory device is brought to the latest state along with the data updated during that time (update operation). This operation is performed periodically, at freely selectable, or freely set intervals.

[0084] According to one embodiment, the third-party vehicle operation action for which a probability is calculated is at least one action from the following group: (1) regenerative operation of the electric drive unit of the third-party vehicle, and / or (2) Temporarily turning off the internal combustion engine of a third-party vehicle, and / or restarting it. (3) The power output of the power consumption unit required to respond in an energy vehicle-mounted electrical system, which is above the high power limit or below the low power limit.

[0085] Therefore, according to one embodiment, for each georeference point, values ​​for various parameters for passing vehicles can be calculated / transmitted and stored in a database device, particularly a central database device, in particular:

[0086] (1) Positional definition of georeference point: P ref (For example, a description of the surrounding area such as the x-axis, y-axis, and possibly the radius.)

[0087] (2) Examples of parameters related to operation: - Vehicle type and / or vehicle weight type - Vehicle speed -Time of day (e.g., morning, daytime, evening, night) -Type of day (e.g., workday, holiday, weekend, travel day, holiday on the commute route, etc.) - Direction of travel - Regeneration on / off / degree in some cases - Automatic start-stop device for internal combustion engines, which may involve turning the engine on / off or, in some cases, for a set duration. -Current power consumption - and so on.

[0088] (3) Examples of parameters related to the surrounding environment: - Probability of regenerative action in a moving vehicle passing through a georeferenced point - Probability of activated start-stop device in a moving vehicle passing a georeference point - Probability of abnormal power output of at least one power unit connected to the vehicle's electrical system in a vehicle that is in motion and passing through a georeferenced point. - Characteristic indicators: "deterministic" or "stochastic" -Time of day (e.g., morning, daytime, evening, night) -Type of day (e.g., workday, holiday, weekend, travel day, holiday on the commute route, etc.) - Direction of travel - Road type (e.g., urban area, intercity, highway) - Road gradient G (e.g., percentage value) - and so on.

[0089] According to one embodiment, vehicle-related parameters are calculated by both a third-party vehicle and the vehicle considered herein, used internally, and, if applicable (if the appropriate function is activated), transmitted to a central database device for each georeferencing point it passes through.

[0090] Another advantage and applicability of the present invention will become apparent from the following description related to the drawings. [Brief explanation of the drawing]

[0091] [Figure 1] This figure shows the interaction between a control device according to one embodiment of the present invention, which has a central database device according to one embodiment of the present invention and a group of vehicles 30 of third-party vehicles. [Figure 2] This figure schematically shows a control device based on Figure 1 in the execution of a method according to one embodiment of the present invention. [Figure 3] This figure schematically shows a map with multiple georeferencing points where the control device and database device based on Figure 1 are integrated, and the parameter values ​​for the method in Figure 6 are used. [Figure 4] This figure schematically shows the central database device based on Figure 1 in the implementation of the method shown in Figure 6. [Figure 5]This figure schematically shows how the probability of an action occurring in a related third-party vehicle is calculated when the method described in Figure 6 is implemented. [Figure 6] This figure shows a flowchart illustrating the implementation of the method according to an exemplary embodiment of the present invention in the configuration shown in Figure 1. [Modes for carrying out the invention]

[0092] Figure 1 shows a diagram illustrating the interaction between a central database device 20 according to an exemplary configuration of the present invention and a vehicle control device 10 according to an exemplary configuration of the present invention, which has a vehicle group 30 of third-party vehicles comprising numerous third-party vehicles. The figure further illustrates a map 2, which is the basis of the navigation dataset, particularly the georeferencing points P set on the map. ref This can be used for vehicle 1 and its control device 10, as well as for the central database device 20.

[0093] Vehicle 1 is equipped with a communication device 11, which is connected to the control device 10 of vehicle 1 and is configured to exchange data with the communication device 21 of the central database device 20. In particular, this data exchange is performed via the mobile radio communication network 3. At this time, vehicle 1 communicates with each georeference point P it passes through. ref The values ​​of the operating parameters (and therefore the operating state BZ) in the in-vehicle electrical system are supplied to the central database device 20, and then the georeference point P that is passed through is supplied. ref The values ​​of the surrounding parameters and the probability of a predetermined third-party vehicle operation action, such as the regenerative operation REKU (or possibly the start-stop operation SSA) (in this embodiment, the probability W for the regenerative operation). REKU In some cases, the probability W of the start-stop operation SSA Obtain the value for ).

[0094] The control device 10 comprises an input unit 12, a processing unit 13, and an output unit 14, and is configured to control the on-board electrical system 15 of the motor vehicle 1 with this topology.

[0095] In this embodiment, the processing unit 13 is configured as a learning system and includes a learning unit 16 for making decisions regarding possible in-vehicle electrical system operation actions B, and a reflex unit 17 for checking the decision proposals of the learning unit 16.

[0096] Each vehicle in the third-party vehicle group 30 is also equipped with a communication device, which is used to similarly transmit the actual values ​​of the operating parameters (collectively, the operating status) for each georeference point Pref that it passes through to the central database device 20, where they are stored in the database memory device 22.

[0097] The database device 20 includes a communication device 21 and a database memory device 22, as well as a computing server 23. The computing server controls the database device 20 and manages data input and output in response to response requests from vehicles.

[0098] Each georeference point P ref Regarding this, the database memory device 22 contains a georeference point dataset, which includes not only the values ​​of the surrounding parameters (surrounding conditions) of the points, but also numerous memorized operating states of third-party vehicles among the vehicle group 30 at each time each georeference point is passed through, and each operating state is defined by the sum of the values ​​of the individual operating parameters. In addition, the relevant point P refEach georeference point data set for [X] contains values that are updated either constantly or at a predetermined interval regarding the probability of one predetermined in-vehicle electrical system operation action (REKU and / or SSA in this embodiment) for the operating states during the previously memorized passages of different third-party vehicles at the georeference point.

[0099] Specifically, in this embodiment, such a georeference point data set contains values for some or all of the parameters described below: (1) Positional definition of the georeference point: P ref (2) Operating parameters of vehicles that have passed the georeference point in the past: - Vehicle type: K - Vehicle speed: v - Time: t - Type of day: d - Driving direction: R - Indicator for regenerative operation during passage: i REKU - In some cases, indicator for the start-stop device that is actuated: i SSA ; - In some cases, indicator for abnormal consumer (load) output of at least one consumer (load) connected to the in-vehicle electrical system during passage: i VL (3) Ambient parameters: - Probability of REKU during passage: W REKU - In some cases, probability of SSA during passage: W SSA - In some cases, probability of VL during passage: W VL - Characteristic indicator I C - Driving direction: R - Road type: S - Road gradient: G

[0100] Below, an exemplary implementation of the method according to the present invention for operating the in-vehicle electrical system 15 in the infrastructure depicted according to Figure 1 will be described in detail, based on Figures 2 to 6.

[0101] For this purpose, Figure 2 shows the details of information processing in the control device 10. Figure 3 illustrates the role of map 2 when specifying the in-vehicle electrical system operation action B. Figure 4 shows the details of information processing of data provided by the vehicles of the vehicle group 30 in the central database device 20, and Figure 5 shows the probability W for the third-party vehicle operation action REKU. REKU The diagram illustrates how this is calculated and how it can be used in Vehicle 1. Finally, Figure 6 shows an illustrative flowchart of the key method steps of the exemplary method.

[0102] Figure 2 shows how the input unit 12 can use the communication device 11 of the control device 10 to calculate the parameter values ​​necessary to describe the current or future relevant operating state BZ and ambient state UZ.

[0103] First, for this purpose, a route 4 (see Figure 3) is provided in which the above-mentioned vehicle control unit (not shown) may be expected, and this route is a series of georeferencing points P for the purpose of an exemplary embodiment of the present invention. ref It is determined by its orbit.

[0104] Each surrounding state UZ, with corresponding values ​​for its respective parameters, is typically related to a predetermined georeferencing point calculated using data from the left side of map 2 in the navigation system. This is because the georeferencing point lies on the expected route 4 in the near future. The expected route 4 is located on the adjacent georeferencing point P ref,n ~P ref,n+x The trajectory is shown. Figure 2 shows which georeference point P is used for the illustrated information processing. ref,nThe relationship is symbolically indicated by a dashed line. In Figure 3, the relationship to the expected Route 4 is symbolically indicated on Map 2.

[0105] In this embodiment, each operating state BZ, which has corresponding values ​​for its respective related parameters, relates to the current state of the vehicle 1 or its on-board electrical system 15.

[0106] Therefore, the operating parameters BZ and (P) are shown in Figure 2. ref,n The values ​​for each of the surrounding parameters UZ (regarding the context) are available to the input unit 12 and are also passed to the processing unit 13.

[0107] Therefore, the processing unit 13 processes each associated georeference point P ref In order to make a decision regarding possible in-vehicle electrical system operation actions B, the actual operating state BZ of the in-vehicle electrical system 15 and vehicle 1, and the georeferencing point P to be considered are necessary. ref Refers to the surrounding state UZ. In this embodiment, the latter is, in particular, the value W for the probability of the third-party vehicle action REKU. REKU It includes.

[0108] Based on the information state, the learning unit 16 of the processing unit 13 proposes an appropriate action B corresponding to a predetermined action strategy, which may be supplemented and / or replaced by a previous learning process. The reflex unit 17 of the processing unit 13 checks the proposed action B for suitability according to the predetermined strategy and transmits a reward or punishment to the learning unit 16 depending on the result of the check. If action B is rejected by the reflex unit 17, the reflex unit 17 can also pass the modified and accepted action B' to the output unit 14. The role of the output unit 14 is to control the action B (or B') determined in the in-vehicle electrical system 15 (see Figure 6, S160).

[0109] The resulting change in the operating state BZ can be directly returned to the input unit 12, or it can be extracted in the form of delayed reward / punishment and eccentrically sent to the learning unit 16.

[0110] In the embodiments described herein, a typical on-board electrical system operation action B is the adjustment of the energy storage unit of the motorized vehicle, particularly in the sense of intentional discharge in an expected charge contribution (indicator: high regeneration probability for the georeferencing point or the next georeferencing point) or intentional charge in an expected discharge contribution (indicator: high start-stop probability for the georeferencing point or the next georeferencing point).

[0111] Based on Figure 3, the relevant georeference point P ref This allows us to determine which information is stored in the database memory device 22 and, based on which logic, the control device 10 of the motor vehicle 1 will request that information in response.

[0112] Based on the navigation system's connection to the memorized map 2, the expected route 4 is known to the control device 10, and this route is connected to a series of adjacent georeferencing points P. ref It is defined by its orbit 5. Accordingly, georeference point P should be passed soon. ref To calculate information about the surrounding state UZ, the control device 10 uses the communication device 11 to retrieve the corresponding point P from the central database device 20. ref The system requests information stored in memory regarding the following: This may be parameters of the operating state of some third-party vehicles in the vehicle group 30, if necessary, but is usually always at least parameters of the ambient state UZ. In particular, this also includes the probability of regenerative action B in third-party vehicles that have already passed the corresponding georeferencing point and for this purpose left a dataset in the central database device 20.

[0113] Therefore, as can be seen from Figure 4, each georeference point P in Map 2 ref A dataset for this purpose is stored in the database memory device 22, and this dataset contains the definition of a point and its surrounding state UZ, and the georeference point P at an earlier point in time. ref This includes the numerous operating states of the 30 vehicles in the added vehicle group.

[0114] Figure 5 illustrates how, based on the data, the probability of a predetermined third-party vehicle action occurring, which in this case is the probability of the regenerative braking action REKU occurring, can be calculated.

[0115] The probability can be selectively identified and pre-calculated using the calculation server 23 of the database device 20 and transmitted to the control device 10 of the vehicle 1, or the basis stored in memory for calculation can be handed over to the control device 10 and the calculation itself can be performed there. In both cases, the calculation can be performed as illustrated in Figure 5:

[0116] Vehicle 1, using its control device 10 (not shown in Figure 5), considers the expected route 4 and identifies one or more related georeferencing points P. ref Query the dataset for this topic.

[0117] Each dataset stores the number of vehicles that have previously passed the corresponding georeferencing point. Figure 5 shows a roughly simplified illustration of 10 vehicles. The dataset includes an indicator i for the presence of the regenerative braking action (REKU) in 8 vehicles. REKU The system remembers that the (dark background icon) is set for one vehicle, while the other two vehicles do not have the (bright background icon) set for the other.

[0118] In the additional step, based on the operating state BZ of vehicle 1, "older (historischen)" third-party vehicles whose operating states are not sufficiently comparable are excluded from consideration.

[0119] In this embodiment, seven related vehicles remain, and six of them have indicator i REKU It is set.

[0120] Based on this, the georeference point P is considered. ref The probability of regeneration being 6 / 7, or 0.857, in W is 6 / 7. REKU This can be obtained.

[0121] The probability W REKU In this embodiment, the predetermined related limit value W is 0.75. rel This is further compared (see Figure 6, S130). Since the probability is greater than the relevant limit, this probability is taken into consideration when making a decision about possible in-vehicle electrical system operation action B.

[0122] In this embodiment, the decision is based on the probability W that should be calculated and considered. REKU and / or W in some cases SSA This is done based on the expected charge amount (discharge amount) or charge contribution (discharge contribution), which is calculated depending on the following:

[0123] Figure 6 illustrates the individual method steps for this process.

[0124] In step S110, first, the expected route 4 is located above georeference point P. ref It is calculated along with orbit 5.

[0125] In step S120, all georeferencing points are within the prediction range H. PRAED Whether or not it is within ("AE" is an A (umlaut), the same applies below) determines all georeference points P in orbit 5. ref This is calculated specifically according to Figure 5. Prediction range H PRAED Each P withinref For each of these, the probability W for the regenerative action is as follows: REKU and / or in some cases, start-stop action W SSA The probability W SSA This is calculated for the third-party vehicle considered in vehicle group 30.

[0126] In step S130, in order to identify cases in which it is possible to improve the prediction for calculating the physically defined charge contribution (discharge contribution), probability W REKU (or W SSA The value calculated for ) is the related limit value W rel Georeference point P that exceeds ref It is identified.

[0127] Next, in step S140, the expected charge contribution is calculated for all georeference points that have been identified.

[0128] In contrast, in step S141, for all other georeferencing points, a characteristic indicator IC is calculated based on, for example, the road type S, direction of travel, and / or especially the gradient G at the georeferencing point under consideration, and a prediction is made as to how reliably the expected charge contribution can be calculated based on the physical conditions surrounding the georeferencing point. Characteristic Indicator IC C The value for can be "deterministic" or "probabilistic," depending on whether a given motion action typically occurs for a given georeference point, or whether such a clear prediction is impossible.

[0129] Following step S141, in step S142, I C = The expected daily charge is calculated only for georeference points that are "deterministic."

[0130] In step S150, the sum of the charge contributions of the individual georeferencing points to be considered along the expected orbit 5 of route 4 is transmitted to the input unit 12 (via the communication device 11).

[0131] In step S160, the processing unit 13 determines possible operational actions B of the in-vehicle electrical system 15 based on the transmitted total.

[0132] In step S170, the processing unit 13 appropriately instructs the output unit 14, and when the output unit 14 issues a corresponding control command, operation action B is executed. In this embodiment, operation action B is, for example, the adjustment of the energy storage unit E of the vehicle 1 with respect to the expected charge amount (discharge amount).

[0133] At this time, probability W REKU If a larger charge is expected to become available soon based on this, the adjustment may include intentionally discharging the energy storage unit E.

[0134] In contrast, probability W SSA If a larger charge is expected to be provided soon based on this, the adjustment may include intentional charging of the energy storage unit E. Furthermore, the present invention may also encompass the following embodiments: 1. A control device (10) for operating the energy on-board electrical system (15) of a motor vehicle (1), wherein the operating parameters (K, v, t, d, R, i) of the energy on-board electrical system of the motor vehicle are controlled by a control device (10). REKU ,i SSA ) and / or one or more ambient parameters (t,d,R,S,G,I) of a motorized vehicle C In the control device, which includes an input unit (14) configured to calculate and pass on to the processing unit of the control device, At least one ambient parameter (W REKU ,W SSA A control device characterized in that ) is the probability of a third-party vehicle action (REKU, SSA). 2. The probability of the georeference point (P ref The control device described in 1. above, characterized in that it is associated with ). 3. The control device is equipped with a processing unit (13), and the processing unit is - Identify the in-vehicle electrical system operation action (B) based on the calculated probability, - The operation actions of the in-vehicle electrical system are identified based on multiple probabilities of third-party vehicle operation actions, and in particular, probabilities are calculated for consecutive georeferencing points along the expected route (4) of the motorized vehicle. The control device according to 1. or 2. above, characterized in that it is configured as described above. 4. Multiple probabilities, in particular, multiple consecutive georeferencing points, each with a specified probability, are used to determine the prediction range (HPRAED The control device according to item 2 or 3 above, characterized in that it is restricted by ). 5. The in-vehicle electrical system operation action is such that the calculated probability value for the third-party vehicle operation action is at least one related limit value (W rel A control device according to any one of the above 2. to 4., characterized in that it is identified only based on a georeference point corresponding to ). 6. The processing unit, - Probability of a third-party vehicle action, or - One or more other known surrounding parameters for the georeference point Depending on the characteristic indicator of the georeference point (I C A control device according to any one of 3. to 5. above, characterized in that it is configured to identify an in-vehicle electrical system operating action based on ). 7. The third-party vehicle actions for which probabilities are calculated belong to the following groups: - Regenerative operation (REKU) and / or of the electric drive unit of a third-party vehicle - Temporary shutdown (SSA) of the internal combustion engine of a third-party vehicle, which involves subsequent restarts and / or - The power consumption (VL) required for response in an energy vehicle-mounted electrical system that exceeds the high power limit or falls below the low power limit. A control device according to any one of the above 1. to 6., characterized in that it is at least one of the actions. 8. A method for operating an on-board energy electrical system (15) of a motor vehicle (1), comprising at least the following steps: - Operating parameters of the energy vehicle electrical system (K,v,t,d,R,i REKU ,i SSA ) one value each of or one or more surrounding parameters of the vehicle (t,d,R,S,G,I C Calculate the value of ) and select at least one of the surrounding parameters (W REKU ,W SSA ) represents the probability of a third-party vehicle action (REKU, SSA). - Identify the in-vehicle electrical system operation action (B) based on the calculated value. A method characterized by having the following: 9. - Automotive electrical system operation actions are identified based on learned operation strategies, and / or - The operation actions of the in-vehicle electrical system are checked based on a predetermined check strategy. The method described in 8. above, characterized by the features described above. 10. A central database device (20), in particular a server (23) having a database (22), wherein the device is - An indicator (i) for an action (REKU,SSA) at one georeferencing point or within a range of georeferencing points (Pref). REKU ,i SSA The value of ) is received from multiple third-party vehicles (30), - Based on the transmitted values ​​of the indicator, the probability (W) of the presence of motion action at the georeference point. REKU ,W SSA ) calculate, -The probability calculated in this way is transmitted to the control device (10) of the motorized vehicle (1) formed in accordance with one of the above 1. to 7. A central database device characterized by being configured in such a way. [Explanation of Symbols]

[0135] 1. Motorized vehicle 2 Maps 3. Mobile radio communication network 4. Expected Route 5 orbit 10 Control device 11. Communication equipment 12 Input Units 13 Processing Units 14 Output Units 15. In-vehicle electrical systems 16 Learning Units 17 Reflex Unit 20 Database Devices 21 Communication equipment 22 Database memory device 23 Computing Server 30. Group of third-party vehicles B. Automotive Electrical Systems - Operation Actions BZ Operating Status d. Types of days E Energy Storage Unit G Gradient / Incline H praed Prediction range I C Characteristic indicators K Vehicle type and / or vehicle weight type P ref Georeference point t time UZ Surrounding Conditions R Direction of travel REKU Regenerative Action i REKU Regenerative Indicator On / Off / Grade S Road Type SSA Start-Stop Automatic Operation Action i SSA Automatic start-stop indicator for internal combustion engine off / on v Vehicle speed W REKU Probability of regeneration W rel Related limits W SSA Start-Stop Probability

Claims

1. A control device (10) for operating the energy on-board electrical system (15) of a motor vehicle (1), wherein the operating parameters (K, v, t, d, R, i) of the energy on-board electrical system of the motor vehicle are... ＲＥＫＵ , i ＳＳＡ ) and one or more ambient parameters (t, d, R, S, G, I) of the motorized vehicle Ｃ In the control device, which includes an input unit (12) configured to calculate and pass on to the processing unit of the control device, At least one ambient parameter (W ＲＥＫＵ , W ＳＳＡ A control device characterized in that ) is the probability of a third-party vehicle operation action (REKU, SSA), including a start-stop operation (SSA) of a third-party vehicle.

2. The probability is that the georeference point (P ｒｅｆ The control device according to claim 1, characterized in that it is the probability of an action taken by a third-party vehicle that has already passed through the area in advance.

3. The control device includes a processing unit (13), and the processing unit is - Identify the in-vehicle electrical system operation action (B) based on the calculated probability, - The operation action of the in-vehicle electrical system is identified depending on multiple probabilities of the operation action of a third-party vehicle, and the probability of consecutive georeferencing points along the expected route (4) of the motorized vehicle is calculated. The control device according to claim 1 or 2, characterized in that it is configured in such a way.

4. A plurality of consecutive georeference points, each with a specified probability, are within a prediction range (H ＰＲＡＥＤ The control device according to claim 3, characterized in that it is restricted by ).

5. The calculated probability of an in-vehicle electrical system operation action for a third-party vehicle operation action is within a predetermined related limit value (W ｒｅｌ The control device according to claim 3 or 4, characterized in that it is identified based on at least one georeferencing point exceeding ).

6. The processing unit, - Probability of a third-party vehicle action, or - One or more known surrounding parameters for the georeference point The control device according to any one of claims 3 to 5, characterized in that it is configured to determine an in-vehicle electrical system operating action depending on the following.

7. The third-party vehicle action for which the probability is calculated is: - Regenerative braking operation (REKU) of the electric drive unit of a third-party vehicle or - An abnormal power consumption (VL) required for response in an energy vehicle's electric system, where the power consumption exceeds the high power limit or falls below the low power limit. The control device according to any one of claims 1 to 6, further comprising

8. A method for operating an on-board energy electrical system (15) of a motorized vehicle (1) using a control device (10) according to any one of claims 1 to 7, comprising at least the following steps: - Operating parameters (K, v, t, d, R, i ＲＥＫＵ , i ＳＳＡ ) of each one value and one or more ambient parameters (t, d, R, S, G, I Ｃ ) of the vehicle are calculated by an input unit (12) of a control device (10), and at least one (W ＲＥＫＵ , W ＳＳＡ ) of the ambient parameters is the probability of a third-party vehicle operation action (REKU, SSA), - The in-vehicle electrical system operation action (B) is determined by the control unit's processing unit (13) based on the calculated value. A method characterized by having the following:

9. - The learning unit (16) of the processing unit (13) identifies the in-vehicle electrical system operation action based on the learned operation strategy, and / or - The reflex unit (17) of the processing unit (13) checks the operation action of the in-vehicle electrical system based on a predetermined check strategy. The method according to feature 8.

10. A central database device (20), wherein the device is - Indicator (i) for motion actions (REKU, SSA) at one georeferencing point ＲＥＫＵ , i ＳＳＡ The values ​​of ) are received from multiple third-party vehicles (30), - Based on the transmitted indicator value, the probability (W) of the presence of motion action at the georeference point. ＲＥＫＵ , W ＳＳＡ ) calculate, - The probability calculated in this manner is transmitted to the control device (10) of the motorized vehicle (1) formed according to any one of claims 1 to 7. A central database device characterized by being configured in such a way.

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