DE102020200490A1 - Method for influencing an operating state of a drive train of a hybrid vehicle, as well as a drive train management system - Google Patents

Abstract

The invention relates to a method for influencing an operating state of a drive train (2) of a hybrid vehicle (3), comprising:
- Controlling the drive train (2) of the hybrid vehicle (3),
- Acquisition of environmental information in an environment of the hybrid vehicle (3) and / or of vehicle-specific data of the hybrid vehicle (3) and / or of external traffic data and / or a driving behavior of a user (7) of the hybrid vehicle (3) as actual information in a real driving operation of the hybrid vehicle (3),
- Generating prediction information in relation to a driving mode in which the hybrid vehicle (3) will be, on the basis of the actual information, and
- Switching the hybrid vehicle (3) into a first driving mode with an internal combustion engine (11) of the drive train (2) or into a second driving mode with an electric motor (12) of the drive train (2) depending on the prediction information. The invention also relates to a drive train management system (1).

Description

The invention relates to a method for influencing an operating state of a drive train of a hybrid vehicle. The method comprises controlling the drive train of the hybrid vehicle and capturing environmental information in the surroundings of the hybrid vehicle and / or vehicle-specific data of the hybrid vehicle and / or external traffic data and / or driving behavior of a user of the hybrid vehicle as actual information during real driving of the hybrid vehicle. The invention also relates to a drive train management system for influencing an operating state of a drive train of a hybrid vehicle. The drive train management system has a control unit for controlling the drive train of the hybrid vehicle and a detection unit for recording environmental information in an environment of the hybrid vehicle and / or vehicle-specific data of the hybrid vehicle or external traffic data and / or a driving behavior of a user of the hybrid vehicle as actual information in a real driving operation of the hybrid vehicle.

the DE 10 2015 224 114 A1 relates to a transmission control for controlling and / or regulating the operation of an automatic or automated gearbox of a motor vehicle, with a shift strategy of the transmission control device controlling and / or regulating the operation of the transmission on the basis of driving status data and / or driver request data and with the shift strategy of the transmission control device on A gear change from a current actual gear to a target gear is influenced on the basis of existing environmental information data.

the DE 10 2006 042 419 A1 Contains a method for influencing the gear selection of a following vehicle, in particular a motor vehicle with an automated shift system, with an ACC system of the following vehicle using a data bus, for example a CAN bus, including the distance to a vehicle ahead and the speed of the vehicle ahead makes available and the speed of the vehicle ahead is compared with the speed of the following vehicle and a differential speed is determined.

the DE 10 2011 080 712 A1 relates to a method for influencing a gear shift strategy of a motor vehicle, for example a commercial vehicle, the operation of the transmission being controlled with the aid of driving status data and / or driver request data.

Full hybrid vehicles or plug-in hybrid vehicles can be driven either by combustion engine, electrically or in combination. The current operating mode, and thus the connection or disconnection of the internal combustion engine, can be controlled by a comprehensive operating strategy. For example, the current state of charge of the battery is taken into account and whether current driving is possible in electric mode.

The object of the present invention is to provide a method and a drive train management system for determining, generating, processing and interpreting environmental information with which the drive train of the hybrid vehicle can be adapted more efficiently to a current and / or future situation of the hybrid vehicle.

This object is achieved by a method and a drive train management system according to the independent patent claims. Meaningful further developments result from the subclaims.

One aspect of the invention relates to a method for influencing an operating state of a drive train of a hybrid vehicle. The drive train of the hybrid vehicle is controlled and information on the surroundings in the surroundings of the hybrid vehicle and / or vehicle-specific data of the hybrid vehicle and / or external traffic data and / or driving behavior of a user of the hybrid vehicle is recorded as actual information in a real driving operation of the hybrid vehicle carried out. What is essential to the invention is the generation of prediction information relating to a driving mode in which the hybrid vehicle will be located on the basis of the actual information. Furthermore, the hybrid vehicle is switched into a first driving mode with an internal combustion engine of the drive train or into a second driving mode with an electric motor of the drive train as a function of the prediction information. As a result, the drive train of the hybrid vehicle can be adapted to the current and / or future situation or to the future driving operation of the hybrid vehicle. In this way, in particular, efficient operation of the drive train of the hybrid vehicle can be carried out.

For example, large amounts of information on the vehicle environment can be generated using ADAS sensors in the hybrid vehicle and also using usable swarm data. It is thus possible to combine this information into a consistent image of the vehicle environment. This information is specifically for Driver assistance systems, such as lane keeping assistants, distance assistants, emergency braking assistants, etc. used. On the basis of this information, it is also possible to identify the intention and predict future behavior of the ego driver and other road users. One advantage of this invention is, for example, that the metrologically acquired information on the vehicle environment is processed into intention and prediction information and then used to control drive components such as a hybrid operating strategy and a gear selection strategy.

For example, the control and adaptation of the operating modes can be carried out on the basis of predicted data and data of the intention recognition.

The term drive train here refers to all drive control units, i.e. hybrid operating strategy, gear shift strategy, etc.

Furthermore, for example, the driving modes or the operating modes are selected between hybrid or electric driving, taking into account the prediction information.

In particular, the prediction information can be used to shift the load point in the internal combustion engine of the drive train and / or the electric motor of the drive train. In particular, the internal combustion engine and / or the electric motor can be operated optimally with the aid of the prediction information. In particular, more intelligent and efficient operation of a hybrid vehicle can be provided with the proposed method. As a result of the driving mode adapted to the prediction information, in particular lower energy consumption and thus lower pollutant emissions of the hybrid vehicle can be achieved. A significantly increased range of the hybrid vehicle can also be achieved due to the lower energy consumption of the hybrid vehicle. In particular, the electric range can be significantly increased during the second driving mode.

The hybrid vehicle can be, for example, a hybrid electric motor vehicle without an external charging facility or a plug-in hybrid vehicle. In particular, the hybrid vehicle has a drive train which comprises an internal combustion engine as an internal combustion engine and an electric motor. The hybrid vehicle can be designed with an operating medium container for a fuel of the internal combustion engine and with an electrical energy storage unit for storing electrical energy for the electric motor.

The information about the surroundings in the vicinity of the hybrid vehicle means all of the information that can be recorded in the immediate vicinity of the hybrid vehicle. For example, information on the lane occupancy of a lane in the vicinity of the hybrid vehicle or adjacent lane objects in a lane in the vicinity of the hybrid vehicle and / or other road users such as other motor vehicles or pedestrians or cyclists can be displayed with the information about the surroundings. Likewise, route-related information about the surroundings, such as, for example, buildings in the vicinity of the roadway or an upcoming tunnel or a roadway route ahead with a gradient or a turning road, can be taken into account. Likewise, traffic lights and / or traffic signs and / or a road quality of the roadway in the vicinity of the hybrid vehicle can be recorded with the information about the surroundings in the surroundings of the hybrid vehicle. In particular, the information about the surroundings can be recorded using sensor units and / or camera systems and / or swarm data and / or online map data from the hybrid vehicle.

As actual information, for example, vehicle-specific data such as vehicle trajectory, a current fill level of the operating fluid container of the motor vehicle, a current state of charge of the electrical energy store of the hybrid vehicle, a current average consumption of the drive train or information from a driver assistance system of the hybrid vehicle can be recorded. The external traffic data can be used to represent, in particular, traffic light phases of the traffic lights ahead and / or current traffic jam information and / or a current and / or future traffic situation on a route of the hybrid vehicle. With the driving behavior of the user of the hybrid vehicle, pedal values can be displayed during an acceleration process of the hybrid vehicle. For example, acceleration intervals of the user can be recorded with the driving behavior of the user.

These examples for the recorded information are not to be understood as conclusive, but are only intended to represent the multitude of possible information for the actual information. With the aid of this diverse amount of information, the actual information can be provided extensively and efficiently during the real driving operation of the hybrid vehicle. The real driving operation is, in particular, operation of the hybrid vehicle in a real traffic situation when driving on a road, such as for example a motorway and / or an intersection in a real traffic situation.

With the aid of the actual information, the hybrid vehicle can generate the prediction information itself. In particular, the prediction information is used to predict a future driving operation or a future driving situation of the hybrid vehicle. In particular, with a vehicle system of the hybrid vehicle, the prediction information can be generated and provided automatically and independently as a function of the actual information. For example, the vehicle system can be a software component, a computing unit or a processing unit. Under certain circumstances, all the recorded actual information is taken into account when generating the prediction information in order to be able to provide as exact and precise a determination as possible of a driving situation or driving mode in which the hybrid vehicle will be. In particular, after the prediction information has been generated, the drive train of the hybrid vehicle is correspondingly switched depending on the prediction information generated. As a result, the drive train can be adapted to the predicted situation of the hybrid vehicle. In particular, depending on the prediction information generated, either the drive train is switched to the first driving mode with the internal combustion engine or the second driving mode with the electric motor. As a result, an efficient and energy-saving and pollutant-reduced operation of the drive train of the hybrid vehicle can be achieved and provided.

In an advantageous embodiment of the invention it is provided that the generated prediction information and / or the actual information is stored in a database, with past prediction information and / or past actual information stored in the database being taken into account when generating the current prediction information. By taking into account the past prediction information and actual information stored in the database, current prediction information can be better generated. In particular, the current prediction information can thereby be determined more precisely and precisely. By taking past information into account, when generating the current prediction information, specific situations and / or circumstances, which in particular were already recorded and / or generated in the past, can be entered into and taken into account. This results in more extensive options for generating the prediction information. In particular, the most varied of situations, such as traffic situations, for example, can be taken into account when generating the current prediction information.

For example, the database can be an external server and / or an external service provider for storing data. Likewise, the database can be part of a system of the hybrid vehicle which stores the generated prediction information and / or the recorded actual information immediately after the generation or recording.

In a further advantageous exemplary embodiment, it is provided that the past prediction information stored in the database and / or the actual information are made available to at least one further hybrid vehicle, in particular via a communication link. By providing the stored data in the database, other road users and other hybrid vehicles can use the information in order to be able to generate the best possible prediction information for the other hybrid vehicle themselves. This results in a traffic situation in the future, with the hybrid vehicle and the further hybrid vehicle being able to carry out the best possible and exact prediction of the traffic situation or understanding of the situation. A minimization of the risk of an accident can be ensured, since the hybrid vehicle and the at least one further hybrid vehicle can estimate and assess the impending traffic situation as precisely as possible on the basis of the stored data. This results in a better understanding of the situation or an improved interpretation of the situation for driving the hybrid vehicle and / or the further hybrid vehicle for the hybrid vehicle and the at least one further hybrid vehicle.

It is preferably provided that, depending on the actual information and / or the prediction information, a current or future driving behavior of the hybrid vehicle and / or another road user is predicted and a corresponding control signal is generated for the drive train of the hybrid vehicle. By predicting the current and / or future driving behavior of the hybrid vehicle and / or the other road user, the drive train of the hybrid vehicle can be controlled with the help of the generated control signal in such a way that safe and efficient driving behavior of the hybrid vehicle can be carried out. In particular, the risk of an accident with regard to other road users and the hybrid vehicle can be significantly reduced or minimized. In particular, the prediction of the driving behavior of the hybrid vehicle and / or of the other road user takes place in the hybrid vehicle itself. By predicting the future or current driving behavior of the hybrid vehicle and / or further Road user, the driving behavior of the hybrid vehicle and in particular the operating state of the drive train of the hybrid vehicle can be adapted to the respective driving behavior or situations and controlled accordingly. In particular, the generated control signal is transmitted to a control unit of the drive train so that, for example, the first driving mode and / or the second driving mode of the drive train can be switched or controlled accordingly.

For example, based on the current and / or future driving behavior of the hybrid vehicle and / or the other road user, a further control signal for, for example, a braking device and / or a driver assistance system can be generated in order to be able to respond in particular to the driving behavior of the other road user. In this way, accidents in particular can be avoided.

In an advantageous embodiment of the invention it is provided that a future traffic situation of the hybrid vehicle is predicted in the prediction information and the respective driving mode of the drive train of the hybrid vehicle is adapted to the future traffic situation. As a result, in particular an energy-saving and pollutant-minimized driving mode of the drive train of the hybrid vehicle can be selected and implemented as a function of the predicted traffic situation. As a result, the hybrid vehicle and in particular the drive train of the hybrid vehicle can be operated efficiently. In particular, the future traffic situation can be predicted on the basis of the prediction information and / or, for example, from past information. When predicting the traffic situation, for example, navigation data and / or mobile online data can be used. In particular, with the help of the predicted future traffic situation, the drive train of the hybrid vehicle is switched accordingly and the predicted future traffic situation of the hybrid vehicle can be transmitted to other hybrid vehicles and / or other road users in the vicinity of the hybrid vehicle and / or on a route of the hybrid vehicle and / or to the database become. By taking into account the future traffic situation of the hybrid vehicle, in particular a fluid and smooth driving operation of the hybrid vehicle can be provided. In particular, with the prediction of the future traffic situation, an efficient and above all more comfortable driving operation of the hybrid vehicle can be carried out on a future route.

In a further advantageous embodiment of the invention it is provided that at least one control signal for the drive train is generated depending on the prediction information, the drive train being switched to a first driving mode or to the second driving mode with the generated control signal. As a result, the appropriate driving mode of the drive train can be adapted to a driving mode in which the hybrid vehicle will be located. In this way, in particular, the hybrid vehicle can be operated in an efficient and energy-saving manner. In particular, the control signal is generated with a system of the hybrid vehicle itself and transmitted to the corresponding components or control systems of the drive train. With the aid of the at least one generated control signal, either the drive train can be switched and operated in the first driving mode or in the second driving mode. For example, a control signal for the first driving mode and a further control signal for the second driving mode can be generated. Then, depending on which mode is currently required, the corresponding control signal, which has already been generated, can be transmitted to the drive train.

It is preferably provided that, depending on the actual information and the prediction information, a first point in time at which the first driving mode of the drive train of the hybrid vehicle is executed and a second point in time at which the second driving mode of the drive train of the hybrid vehicle is executed are determined, and the first and the second point in time for the switching of the hybrid vehicle in the first driving mode or in the second driving mode are taken into account. With the aid of the first point in time and the second point in time, a respective operation of the drive train, in which the drive train is in the first driving mode or in the second driving mode, can be provided. As a result, the drive train can be efficiently shifted and operated in the first driving mode and / or in the second driving mode.

It is preferably provided that the actual information and the prediction information are provided to a machine learning unit of the drive train, with automatic machine training of the drive train being carried out as a function of the actual information and the prediction information. As a result, it can be achieved, for example, that the drive train intelligently and independently carries out a corresponding driving mode or operating mode of the drive train and / or can independently assess whether the desired driving mode can be carried out sensibly or whether another driving mode would currently not be more efficient. In particular, this enables improved use of the drive train of the hybrid vehicle because the drive train can independently select and implement the currently most efficient and better driving mode with the help of the machine learning unit.

For example, a machine learning process such as deep learning can be carried out with the machine learning unit. For example, the machine learning unit can be linked to the database and take into account the previously stored prediction information and actual information in the automatic machine training of the drive train.

In a further advantageous exemplary embodiment, provision is made for traffic data from an external server to be taken into account in addition to the actual information for generating the prediction information. As a result, specific information can also be taken into account when generating the prediction information in order to carry out an even more precise and improved generation of the prediction information. As a result, in particular a future traffic situation or a future driving behavior of the hybrid vehicle can be better taken into account and the drive train can thus be switched or operated in the respectively required and better driving mode. For example, the external server can be a traffic service provider that can transmit current and future traffic events to the hybrid vehicle. In particular, the hybrid vehicle can be linked to a portable communication terminal, such as a smartphone or tablet, of the user of the hybrid vehicle, and this means that upcoming appointments and / or upcoming routes and / or upcoming trips by the user of the hybrid vehicle can be taken into account when generating the prediction information. This results in an improved application of the respective driving modes of the drive train of the hybrid vehicle.

Another aspect of the invention relates to a drive train management system for influencing an operating state of a drive train of a hybrid vehicle. The drive train management system comprises a control unit for controlling the drive train of the hybrid vehicle. Furthermore, the drive train management system has a recording unit for recording environmental information in the surroundings of the vehicle and / or vehicle-specific data of the hybrid vehicle and / or external traffic data and / or driving behavior of a user of the hybrid vehicle as actual information during real driving of the hybrid vehicle . With a computing device, prediction information relating to a driving mode in which the hybrid vehicle will be located can be generated on the basis of the actual information. Furthermore, the drive train management system comprises a switching unit of the control unit for switching the hybrid vehicle in a first driving mode with an internal combustion engine of the drive train or a second driving mode with an electric motor of the drive train as a function of the detection information. With the drive train management system just proposed, in particular a method according to one of the previously described embodiments is carried out. In particular, the previously described method is carried out with the drive train management system.

The invention also includes further developments of the drive train management system according to the invention which have features as they have already been described in connection with the further developments of the method according to the invention. For this reason, the corresponding developments of the drive train management system according to the invention are not described again here.

The invention also includes the combinations of the features of the described embodiments.

An exemplary embodiment of the invention is described below. For this purpose, the single figure shows an exemplary embodiment of a drive train management system.

The exemplary embodiment explained below is a preferred embodiment of the invention. In the exemplary embodiment, the described components of the embodiment each represent individual features of the invention that are to be considered independently of one another, which also develop the invention independently of one another and are therefore also to be regarded as part of the invention individually or in a combination other than the one shown. Furthermore, the described embodiment can also be supplemented by further features of the invention that have already been described.

The figure shows a drive train management system 1 with which an operating state of a drive train 2 of a hybrid vehicle 3 can be influenced. With the drive train 2 it is, in particular, the drive unit for carrying out a locomotion trip of the hybrid vehicle 3 . With a control unit 4th can the powertrain 2 of the hybrid vehicle 3 to be controlled. At the control unit 4th it is in particular a control device or a control system of the hybrid vehicle 3 . The powertrain management system 1 also includes a registration unit 5 . At the registration unit 5 it can be, for example, a sensor system or a camera system of the hybrid vehicle 3 act. In particular, the acquisition unit 5 at the most varied and diverse positions of the hybrid vehicle 3 be arranged. With the registration unit 5 can provide environmental information in an environment 6th of the hybrid vehicle 3 and / or vehicle-specific data of the hybrid vehicle 3 and / or external traffic data and / or a driving behavior of a user 7th of the hybrid vehicle 3 as actual information during real driving of the hybrid vehicle 3 are recorded. For example, all of this information can be obtained using the hybrid vehicle's on-board sensors 3 are recorded. So can traffic incidents in the area 6th of the hybrid vehicle 3 and / or another hybrid vehicle 8th in the vicinity of the hybrid vehicle 3 are recorded. Vehicle-specific system information of a vehicle system of the hybrid vehicle can also be used 3 are recorded. Likewise, the person-specific driving behavior of the user 7th recorded and provided as actual information. In particular, the detection takes place during the real driving operation of the hybrid vehicle 3 in real traffic or in a real street situation.

The powertrain management system 1 has a computing device 9 with which prediction information relating to a driving mode in which the hybrid vehicle is 3 will be located, can be generated on the basis of the recorded actual information. If necessary, all recorded actual information is taken into account when generating the prediction information. With the aid of the prediction information, in particular, evaluated knowledge and / or context information about a future driving maneuver and / or a traffic situation can be provided. In particular, the drive train can use the prediction information 2 of the hybrid vehicle 3 operated more efficiently. In particular, the prediction information provides an improved understanding of the situation or an improved interpretation of a future traffic situation or the future driving mode in which the hybrid vehicle is operating 3 is provided. With a switching unit 10 the control unit 4th can use the hybrid vehicle 3 and especially the powertrain 2 of the hybrid vehicle 3 can be switched depending on the generated prediction information. In particular, with the help of the generated prediction information, the hybrid vehicle 3 in a first driving mode with an internal combustion engine 11 of the powertrain 2 or a second driving mode with an electric motor 12th of the powertrain 2 be switched or operated depending on the prediction information. This enables, in particular, an energy-saving and emission-efficient operation of the hybrid vehicle 3 can be achieved.

For example, the generated prediction information and / or the actual information can be in a database 13th get saved. In particular, this is done with the aid of the computing device 9 . At the computing device 9 it is in particular a computing unit or a backend or a software application. For example, those in the database 13th stored past prediction information and / or past actual information can be used in the generation of current prediction information. In particular, the database 13th be an external server unit or a cloud, e.g. is the database 13th in the hybrid vehicle 3 integrated.

The ones in the database 13th stored past prediction information or the actual information can at least be transferred to the further hybrid vehicle 8th are provided so that the further hybrid vehicle 8th when generating prediction information, the stored information of the hybrid vehicle 3 can take into account. In particular, the data is transferred or retrieved from the database 13th via a communication link. For example, the data can be transmitted and accessed via Bluetooth or another wireless network.

For example, is the control unit 4th designed in such a way that, depending on the actual information and / or the prediction information, a current and / or a future driving behavior of the hybrid vehicle 3 and / or another road user 14th predicted and a corresponding control signal for the drive train 2 of the hybrid vehicle 3 can be generated. At the other road user 14th it can be, for example, a pedestrian or a cyclist or a motor vehicle in traffic. The generated control signal of the control unit 4th is generated in such a way that the drive train 2 of the hybrid vehicle 3 can be adjusted according to the current or future driving behavior and adjusted accordingly. For example, the control signal from the control unit 4th via a communication bus of the hybrid vehicle 3 the drive train 2 be transmitted.

For example, with the computing device 9 a future traffic situation of the hybrid vehicle 3 can be predicted depending on the prediction information. With the predicted traffic situation, the drive train can use the generated control signal 2 of the hybrid vehicle 3 switched or controlled in such a way that the drive train 2 either in the first Driving mode or is operated in the second driving mode. In particular, the prediction information is used to generate at least one control signal, for example a control signal for a first driving mode and a control signal for a second driving mode, for the drive train, with the control signal generated by the control unit 4th the powertrain 2 using the switching unit 10 is switched to either the first driving mode or the second driving mode.

In particular, the control unit 4th depending on the actual information and the prediction information, a first point in time at which the first driving mode of the drive train 2 of the hybrid vehicle 3 is executed, and a second point in time in which the second drive mode of the drive train 2 of the hybrid vehicle 3 is trained, determine. With the help of the times, the control unit can 4th generate the control signals so that when switching the hybrid vehicle 3 the corresponding desired driving mode can be operated. In particular, the first and the second point in time when shifting the drive train 2 considered.

The powertrain management system 1 can for example be a machine learning unit 15th have, the machine learning unit 15th an automatic machine training of the drive train with the help of the actual information and the prediction information 2 can perform. This enables the drive train to be taught in independently 2 and in particular the control unit 4th be taken into account with regard to the appropriate and more efficient driving modes. In particular, the machine learning unit 15th as an external unit in the hybrid vehicle 3 or for example in the drive train or in a drive train system of the hybrid vehicle 3 be integrated.

For example, traffic data from an external server and / or calendar data from an electronic calendar of the user can also be used to generate the prediction information 7th of the hybrid vehicle 3 must be taken into account. In particular, the calendar data can be used with a portable communication terminal 16 of the user 7th the hybrid vehicle 3 and in particular the powertrain management system 1 to be provided. The traffic data can in particular be provided by online services.

For example, the powertrain management system 1 for the generation of the prediction information, the current fill level of the resource container 17th of the hybrid vehicle 3 consider. The current state of charge of an electrical energy store can also be used 18th of the hybrid vehicle 3 must be taken into account. For example, a start-stop strategy for the first driving mode with the internal combustion engine can be made with the generated prediction information 11 be improved. A sailing function of the hybrid vehicle can also be performed with the generated prediction information 3 be taken into account in the first driving mode. The coasting function can be used to decouple the combustion engine 11 can be carried out more efficiently when driving in pushing situations.

For example, with the aid of the prediction information, a corresponding frictional connection in the transmission of the hybrid vehicle can be achieved 3 can be set and adjusted.

One advantage in generating and using the prediction information is that the internal combustion engine can be decoupled in a targeted manner 11 from the drive train 2 of the hybrid vehicle 3 can be performed when electric driving of the hybrid vehicle 3 is desired or more efficient.

For example, swarm data from external locations can be sent to the hybrid vehicle as actual information 3 and / or the database 13th to provide.

In the following, individual application examples and application situations are described in which the prediction information can be used.

In an exemplary application, it can be that the hybrid vehicle 3 enter an expressway or motorway and especially want to merge into the existing traffic flow. It is important that a road classification and the traffic flow are recorded as actual information. With the prediction information, the hybrid vehicle knows 3 that in this situation a quick process of merging into the flowing traffic is necessary. The hybrid vehicle knows 3 that there is a large speed delta in the driving speed of the hybrid vehicle 3 is required. This can be predicted with the help of the prediction information and with the drive train 2 and the control unit 4th are provided accordingly, so that the corresponding time intervals can be provided for the respective driving modes.

In a further exemplary application, the user 7th a turning maneuver is desired. Turning processes can in particular be recorded as vehicle-specific data. In this case, the activated blinker can be recorded as actual information. As a result, the prediction information can be used to give the user a tendency to turn 7th be taken into account at, for example, a road intersection. The Powertrain 2 be switched so that the internal combustion engine 11 parked early and the hybrid vehicle 3 slowly with the help of the electric motor 12th rolls up to the intersection. For example, in addition to saving energy, a higher recuperation torque of the hybrid vehicle can be achieved 3 adjusted and taken into account.

For example, if the blinker is set, the user can 7th and by simultaneously recording the information on the surroundings in which the hybrid vehicle is 3 is on a motorway, with the aid of the prediction information an intention to overtake or an impending overtaking maneuver can be determined. The powertrain can do this 2 can be operated in particular in the first driving mode, and in particular the drive train knows 2 that the internal combustion engine 11 must be started early in order to provide a corresponding speed delta. The transmission of the hybrid vehicle can 3 be switched back to avoid hesitations.

In a further exemplary application, the hybrid vehicle can recognize a stop request 3 can be provided with the aid of the prediction information. When a red traffic light is detected, the prediction information can be generated to the effect that the second drive mode of the drive train is used to approach the red traffic light 2 is used. A parked vehicle at a traffic light can also be detected by the detection unit, so that the second driving mode can also be set. Likewise, the parked car can be a parked car in the second row on a street, then the first operating mode can be provided to the user with the aid of the prediction information 7th of the hybrid vehicle 3 wants to avoid the vehicle parked in the second row.

In a further exemplary application, the driving behavior of the user can be identified 7th and a distance between two passing vehicles to the hybrid vehicle 3 be determined. In particular, for example, if the user is sporty driving 7th and a sufficient time gap between two moving vehicles, prediction information is generated, according to which a cut-in maneuver of the hybrid vehicle 3 will be imminent. As a result, the drive train can use the prediction information 2 be switched to the effect that the first driving mode is to be used in the cut-in maneuver.

In a further exemplary application, the hybrid vehicle 3 are in a traffic jam on an expressway or a motorway. This can be taken into account when generating the prediction information, so that the second driving mode is efficient for the upcoming driving mode, since it is very likely that constant stop-and-go driving behavior will be carried out. This can save fuel. In a further exemplary embodiment, the hybrid vehicle 3 Carry out driving operations using an adaptive cruise control. With the help of the registration unit 5 one in front of the hybrid vehicle 3 another driving hybrid vehicle 8th are detected, and in particular when the other hybrid vehicle is turning 8th generate the prediction information to the effect that the driving operation is transferred to the further hybrid vehicle traveling ahead 8th should be adjusted. In particular, the prediction information can be used to provide an understanding of the situation as to when the vehicle in front that is turning will leave its own lane or whether, for example, a cyclist has to be taken into account when turning right. This can be used for shifting the drivetrain 2 must be taken into account. The hybrid vehicle can then 3 for example, be operated in a first time window in a first driving mode and in a second time window in a second driving mode.

List of reference symbols

1

Powertrain management system

2

Powertrain

3

Hybrid vehicle

4th

Control unit

5

Registration unit

6th

vicinity

7th

Users

8th

another hybrid vehicle

9

Computing device

10

Switching unit

11

Internal combustion engine

12th

Electric motor

13th

Database

14th

Road users

15th

Machine learning unit

16

portable communication terminal

17th

Equipment container

18th

electrical energy storage

QUOTES INCLUDED IN THE DESCRIPTION

This list of the documents listed by the applicant was generated automatically and is included solely for the better information of the reader. The list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions.

Patent literature cited

• DE 102015224114 A1 [0002]
• DE 102006042419 A1 [0003]
• DE 102011080712 A1 [0004]

Claims (10)

Method for influencing an operating state of a drive train (2) of a hybrid vehicle (3), comprising: - Controlling the drive train (2) of the hybrid vehicle (3), - Acquisition of environmental information in an environment (6) of the hybrid vehicle (3) and / or of vehicle-specific data of the hybrid vehicle (3) and / or of external traffic data and / or a driving behavior of a user (7) of the hybrid vehicle (3) as actual Information during a real driving operation of the hybrid vehicle (3), characterized by - Generating prediction information in relation to a driving mode in which the hybrid vehicle (3) will be, on the basis of the actual information, and - Switching the hybrid vehicle (3) into a first driving mode with an internal combustion engine (11) of the drive train (2) or into a second driving mode with an electric motor (12) of the drive train (2) as a function of the prediction information. Procedure according to Claim 1 , characterized in that the generated prediction information and / or the actual information is stored in a database (13), with past prediction information and / or past actual information stored in the database (13) being taken into account when generating the current prediction information . Procedure according to Claim 2 , characterized in that the past prediction information stored in the database (13) and / or the actual information is made available to at least one further hybrid vehicle (8), in particular via a communication link. Method according to one of the preceding claims, characterized in that, depending on the actual information and / or the prediction information, a current or future driving behavior of the hybrid vehicle (3) and / or another road user (14) is predicted and a corresponding control signal for the drive train (2) of the hybrid vehicle (3) is generated. Method according to one of the preceding claims, characterized in that a future traffic situation of the hybrid vehicle (3) is predicted with the prediction information, and the respective driving mode of the drive train (2) of the hybrid vehicle (3) is adapted to the future traffic situation. Method according to one of the preceding claims, characterized in that depending on the prediction information, at least one control signal for the drive train (2) is generated, the drive train (2) being switched to the first driving mode or the second driving mode with the generated control signal. Method according to one of the preceding claims, characterized in that, depending on the actual information and the prediction information, a first point in time at which the first driving mode of the drive train (2) of the hybrid vehicle (3) is executed and a second point in time at which the second Driving mode of the drive train (2) of the hybrid vehicle (3) is executed, are determined, and the first and second points in time for switching the hybrid vehicle (3) into the first driving mode or into the second driving mode are taken into account. Method according to one of the preceding claims, characterized in that the actual information and the prediction information of a machine learning unit (15) of the drive train (2) are provided, with an automatic machine training of the drive train (2) depending on the actual information and the prediction information. is carried out. Method according to one of the preceding claims, characterized in that, in addition to the actual information, traffic data from an external server are taken into account for generating the prediction information. Drive train management system (1) for influencing an operating state of a drive train (2) of a hybrid vehicle (3), with - A control unit (4) for controlling the drive train (2) of the hybrid vehicle (3), - A detection unit (5) for detecting environmental information in an environment (6) of the hybrid vehicle (3) and / or of vehicle-specific data of the hybrid vehicle (3) and / or of external traffic data and / or a driving behavior of a user (7) of the hybrid vehicle (3) as actual information during a real driving operation of the hybrid vehicle (3), characterized by - A computing device (9) for generating prediction information relating to a driving mode in which the hybrid vehicle (3) will be, on the basis of the actual information, and - A switching unit (10) of the control unit (4) for switching the hybrid vehicle (3) in a first driving mode with an internal combustion engine (11) of the drive train (2) or in a second driving mode with an electric motor (12) of the drive train (2) in Dependence on the prediction information.

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