Method for determining optimised operating settings for drivetrain components of a utility vehicle

Abstract

The invention relates to a method for determining optimised operating settings for drivetrain components of a utility vehicle. The method comprises transmitting (S20) vehicle state data (5) of the utility vehicle arising during a journey along a route (4) and vehicle surroundings data (6) to a computing unit (7) external to the utility vehicle. The method further comprises the computing unit (7) using (S40) the transmitted vehicle state data (5) and vehicle surroundings data (6) to simulate the journey along the route (4) using a stored vehicle model (8) in order to determine current operating settings (1) for drivetrain components (2) of the utility vehicle (3). The method further comprises the computing unit (7) carrying out (S60) further simulations of the journey along the route (4) using the stored vehicle model (8) on the basis of alterations of determined current operating settings (1) and determining (S80) optimised operating settings (1) for drivetrain components (2) of the utility vehicle (3) on the basis of an assessment of the simulations carried out and the altered operating settings (1) in terms of definable target criteria. The optimised operating settings (1) are then transmitted (S100) to the utility vehicle (3), for example by means of wireless data transfer (9) and / or during a workshop visit. The method according to the invention allows operating settings to be centrally optimised for utility vehicles already being used on the road by end customers.

Description

[0001] Method for determining optimized operating settings for drive train components of a commercial vehicle

[0002] Description

[0003] The invention relates to a method for determining optimized operating settings for drive train components of a commercial vehicle.

[0004] Operating settings for a commercial vehicle's powertrain components are determined during the development process. Such operating settings can include, for example, operating settings for the control and / or regulation of powertrain systems and components, such as the corresponding operating settings for the combustion engine, the activation of an electric motor, the cooling system, the transmission and its gearshift application, or the power distribution between the tractor unit and the semitrailer / trailer in combination vehicles, etc.

[0005] It is known from practice that corresponding operating settings can be optimized during vehicle development with the aid of test drives. In this process, vehicle condition data and vehicle environment data obtained during a test drive along a route are recorded and collected. Development engineers then recreate the test drive in a simulation using a computer-based vehicle model of the commercial vehicle, based on the collected vehicle condition data and vehicle environment data, in order to determine and optimize the operating settings for the drivetrain components.

[0006] The disadvantage of this is that the operating settings determined in this way are optimal for the test track and the driving behavior during the test drive, but are not necessarily optimal for later actual use of the commercial vehicle.

[0007] It is conceivable that a user might actually use the vehicle for different route profiles and / or under different environmental conditions than those assumed for the original optimization. Furthermore, it is conceivable that the subsequent driver's driving behavior differs significantly from the driving behavior assumed for the original optimization, e.g., during the test drive. Furthermore, it is possible that different commercial vehicle fleet operators pursue different goals with their vehicle fleets and therefore have different preferences and requirements regarding the operating settings for powertrain components.For example, fleet operators' preferences and requirements may differ with regard to the relative weighting of energy efficiency, average driving speed, tolerance of component wear, and driving comfort, which would lead to different optimized operating settings, e.g., a different shift application for an automated transmission. Accordingly, an initial definition of the operating settings may not be optimal for different requirements.

[0008] It is therefore an object of the invention to provide an improved technique for determining optimized operating settings for drive train components of a commercial vehicle, with which disadvantages of conventional techniques can be avoided.

[0009] This object is achieved by the method having the features of independent claim 1. Advantageous further developments are specified in the dependent claims and the description.

[0010] According to a general aspect of the invention, a method is provided for determining optimized operating settings for drive train components of a motor vehicle. The motor vehicle is particularly preferably a commercial vehicle, for example a truck or bus. In other words, the vehicle can be a vehicle which, due to its design and equipment, is designed for transporting people, transporting goods or towing trailers. The vehicle is preferably a tractor unit, i.e. a vehicle for towing a semi-trailer or trailer. The vehicle is particularly preferably a tractor unit without a coupled semi-trailer. The motor vehicle can be powered by an internal combustion engine. Alternatively or additionally, the motor vehicle can be powered by an electric motor, e.g., by a battery-electric or fuel cell-based powertrain.

[0011] The method is preferably a computer-implemented method. The individual method steps can be performed by different computing units (computers) that communicate with one another. The method is described below using a highlighted exemplary embodiment of a commercial vehicle. Instead of the described commercial vehicle, the method is also applicable to a motor vehicle, at least with regard to the non-commercial vehicle-specific aspects. The method comprises the step of transmitting vehicle status data of the commercial vehicle (hereinafter also referred to as the vehicle) and vehicle environment data resulting from a journey along a route to a computing unit external to the commercial vehicle.

[0012] The vehicle status data and vehicle environment data are determined by the commercial vehicle during the journey and transmitted to the processing unit external to the commercial vehicle, e.g., wirelessly ("over-the-air"). Vehicle status data is data that identifies and / or characterizes the condition of the vehicle during the journey and can include values ​​for powertrain-specific operating parameters, which will be described below. The vehicle status data can be used to reconstruct the vehicle's condition during the journey in detail, while the vehicle environment data indicates where and under which ambient conditions (outside temperature, etc.) the journey took place. The processing unit external to the commercial vehicle can be a computer (central computer) of the commercial vehicle manufacturer.

[0013] The method further comprises the step of using the transmitted vehicle status data and vehicle environment data by the computing unit to simulate the journey along the route based on a stored vehicle model in order to determine and / or evaluate current operating settings for drivetrain components of the commercial vehicle. In other words, based on relevant vehicle status data and environmental data (vehicle environment data), the current operating settings of the commercial vehicle, if not yet known, can be determined by means of a computer-aided simulation using a corresponding vehicle model stored in the computing unit. Furthermore, the current operating settings can be evaluated with regard to definable target criteria.

[0014] The method further comprises the step of conducting further simulations of the journey along the route by the computing unit using the stored vehicle model, based on variations of the determined current operating settings. This is followed by the step of determining optimized operating settings for drivetrain components of the commercial vehicle based on an evaluation of the performed simulations with regard to definable target criteria. The evaluation of the simulations comprises an evaluation of the varied operating settings, preferably also in comparison with one another and with the current operating settings, in order to select those operating settings that are optimal with regard to the target criteria. This step is also preferably carried out by the computing unit.In other words, based on the current operating settings, these are changed in order to carry out further simulations, which can then be evaluated in order to determine optimal or at least improved operating settings for the commercial vehicle.

[0015] The method further comprises the step of transmitting the optimized operating settings to the commercial vehicle. The transmission can be carried out, for example, via wireless data transmission. The transmission can be carried out directly to the commercial vehicle in operation or only after a workshop visit. The method steps according to the invention are preferably carried out for a commercial vehicle already in operation and / or operated by the end customer.

[0016] The method according to the invention enables centralized optimization of operating settings for commercial vehicles already in practical use by the end customer. This enables the use of powerful central computers outside the commercial vehicle to carry out and evaluate the simulations, preferably supported by machine learning methods, in order to determine the optimized operating settings. The vehicle manufacturer's combined knowledge (know-how) on the vehicle can advantageously be incorporated here. Furthermore, data from other vehicles can also advantageously be incorporated into the analysis and determination of optimized operating settings. Operating settings made at the factory can advantageously be subsequently reviewed and optimized for vehicles already in operation by the end customer based on vehicle condition and vehicle environment data obtained in practical use.

[0017] Since the optimization of operating settings is based on definable target criteria, the target criteria and thus the optimization can be flexibly defined (adapted) according to the end customer's preferences. This provides a technical solution that enables a commercial vehicle to automatically optimize its operating settings for drivetrain components in a needs-based and situation-adapted manner, even during subsequent practical use.

[0018] In an advantageous embodiment of the invention, the step of determining optimized operating settings for the drive train components of the commercial vehicle may comprise:

[0019] - a selection of several options for optimized operating settings based on different variations of the operating settings, wherein the selection is preferably carried out automatically by the computing unit;

[0020] - providing information regarding the selected multiple options together with a decision option to a fleet operator operating the commercial vehicle to select an option preferred by the fleet operator for optimised operating settings; and

[0021] - receiving the preferred option selected by the fleet operator using the decision option to determine the optimized operating settings.

[0022] Advantageously, a technical solution is provided that allows a fleet operator to be involved in optimizing the operating settings of one or more of its vehicles. The aforementioned provision of information on the multiple options and the receipt of the selected options can be supported by a communication system for communication between a vehicle manufacturer and the fleet operator and / or automated.

[0023] In a further preferred embodiment, the method further comprises the steps of identifying commercial vehicles within a fleet of commercial vehicles that have an identical or at least similar drivetrain configuration, and transmitting the optimized operating settings to the identified commercial vehicles of the fleet. Advantageously, the determined optimized operating settings can also be used to optimize the operating settings for other commercial vehicles in the fleet, in particular for commercial vehicles that are identical or similar in terms of their drivetrain configuration, without having to perform separate simulation chains for each of the vehicles.

[0024] It was stated above that the optimized operating settings are determined based on definable target criteria. The definable target criteria can include at least one of the following target criteria: travel time, energy and / or fuel consumption, operational wear of at least one component of the drivetrain, ride comfort, range, and average speed of the commercial vehicle. The target criteria are linked to at least one multi-criteria objective function using a preferably definable weighting.

[0025] Such target criteria and multi-criteria objective functions are known from the state of the art. Here, the optimization of the operating settings of powertrain components is understood as a multidimensional optimization problem described by an objective function that can include not only physical variables such as fuel consumption, but also other requirements such as operational wear of components, etc.

[0026] According to an advantageous embodiment, the definition of the target criteria and / or their weighting or the selection of a target function from the at least one target function can be performed by user input and / or by querying a database. A customer preference for defining the target criteria and / or their weighting and / or for selecting the target function can be stored in a corresponding database. The user input can be performed via a suitably designed website, an application program, or generally a communications system that captures the user input and transmits it to the computing unit for executing the simulations.

[0027] This variant offers the advantage that an end customer, especially a fleet operator, can influence the optimization of the operating settings in a simple and transparent manner and change the specifications for this. For example, it is conceivable that a fleet operator observes an increasing number of wear-related vehicle failures of certain drivetrain components. In response, the fleet operator could give greater weight to a corresponding target criterion that minimizes operational wear of the corresponding drivetrain component.

[0028] In a further embodiment, the above-described implementation of further simulations and the determination of the optimized operating settings are carried out using and / or supported by machine learning methods. These are preferably artificial intelligence, AI-based methods, e.g., using an artificial neural network. Such methods are particularly suitable for processing large amounts of data. The use of such methods also facilitates the application of the method for the most automated determination of optimized operating settings for a large number of vehicles, processing large amounts of data, e.g., in the form of vehicle status data and vehicle environment data.

[0029] In one embodiment of the invention, further simulations can be carried out and the optimized operating settings can be determined for selected operating settings, which preferably correspond to at least one vehicle function. The selected operating settings and / or the at least one vehicle function are selected by user input and / or by querying a database. A customer preference for determining the selection of operating settings and / or vehicle functions to be optimized is preferably stored in the database. An advantage of this embodiment is that optimized operating settings can be carried out specifically for certain vehicle functions, e.g. those that can be selected by a customer. By way of example only, such a vehicle function can be a cooling function or a cooling system of the drive train. In this case, only operating settings that correspond to the cooling function oraffect the cooling system.

[0030] It was stated above that the vehicle state data and vehicle environment data are used to simulate the journey along the route using a stored vehicle model. The vehicle model can include a longitudinal dynamics model to represent the vehicle's longitudinal dynamics and / or a thermodynamic powertrain model to represent thermal effects. Such vehicle models are vehicle-specific with regard to the specific powertrain configuration and are well known in various forms from the prior art and are therefore not described in detail here. Vehicle manufacturers typically use such vehicle models to perform corresponding simulations as part of vehicle development, as already mentioned at the beginning.

[0031] The vehicle environment data preferably comprises location data and / or GPS data, i.e., data on the current location and / or the current route, such as, for example, elevation / gradient data of the route. The vehicle environment data may further comprise weather data, preferably weather data on the ambient temperature and / or wind speed that occur while driving along the route. Weather data such as the ambient temperature influences, for example, the switching points for optimized fan activation and / or the optimal speed selection during uphill driving with regard to the cooling performance of a powertrain cooling system. The more precisely the vehicle environment data is known, the more reliably the current operating settings can be simulated and subsequently optimized.

[0032] In one embodiment, the operating settings can comprise a profile, preferably a controlled or regulated profile, of at least one state variable of at least one drive train component. The optimized operating settings comprise an optimal profile, preferably optimal control or regulation, of the at least one state variable with respect to the definable target criteria.The at least one state variable can comprise at least one of the following state variables: a vehicle speed selection, a gear selection, shift times and / or shift speeds for an automated transmission, a charge state of an energy storage device for providing electrical drive energy in a hybrid or electric drive train, a coolant temperature of a primary or secondary cooling circuit of a drive train, switch-on and switch-off times of a fan for engine cooling and / or a pump of a primary or secondary cooling circuit of the drive train, switch-on times for a retarder, switch-on times of an electric auxiliary drive, and a power distribution between a tractor unit and a semitrailer and / or trailer. Optimizing the operating settings for these state variables enables particularly advantageous optimization of drive train operation.

[0033] In one embodiment, the variation of the determined current operating settings comprises a variation of operating parameters and / or state variables of the drivetrain components that can be automatically adjusted within the framework of closed-loop and / or open-loop control processes. The corresponding closed-loop and / or open-loop control processes can thus be optimized. A state variable, in this case, refers to a variable that describes the state of a drivetrain component. This can be, for example, a coolant temperature or a selected gear.

[0034] Alternatively or additionally, the variation of the determined current operating settings can include at least one of the following vehicle-specific modification options: a tire diameter and a total weight, preferably a gross combination weight of a commercial vehicle designed as a tractor unit. For example, within the scope of the optimization according to the method, it can be determined that different tires would be advantageous for the commercial vehicle, e.g., to improve fuel efficiency or reduce tire wear.

[0035] Alternatively or additionally, carrying out further simulations of the journey along the route can further comprise a variation of at least one of the following environmental parameters: an ambient temperature and road gradient. Both variations are parameters that cannot themselves be influenced within the framework of the operating settings of a vehicle. However, they can influence the optimal setting of other operating settings of the drivetrain components, so that in this way, for example, improved operating settings of the vehicle can be made depending on the ambient temperature and / or road gradient. According to a further aspect, the described commercial vehicle can be a tractor unit with a semi-trailer, wherein the vehicle data preferably comprise load data of the semi-trailer. The load data preferably comprise data on the weight and / or volume of the load.This allows for the fact that optimal operating settings can change depending on the load. For example, a heavily loaded vehicle may require a different gear selection during an uphill climb than a vehicle with a light load.

[0036] The previously described preferred embodiments and features of the invention can be combined with one another as desired. Further details and advantages of the invention are described below with reference to the accompanying drawings.

[0037] They show:

[0038] Figure 1 is a schematic flow diagram illustrating a method according to an embodiment of the invention;

[0039] Figure 2 is a schematic flow diagram illustrating a method according to a further embodiment of the invention;

[0040] Figure 3 shows a schematic representation of a data communication within the scope of the method according to an embodiment; and

[0041] Figure 4 shows a schematic representation of a transmission of vehicle status data and vehicle environment data within the scope of the method according to one embodiment.

[0042] Identical or functionally equivalent elements are designated by the same reference numerals in all figures and are partly not described separately.

[0043] Figure 1 shows a schematic flow diagram to illustrate a method for determining optimized operating settings for drive train components of a commercial vehicle according to one embodiment of the invention. In the following description of the method steps of Figure 1 (and Figure 2), reference is also made to Figures 3 and 4. The method comprises step S20 of recording and transmitting vehicle status data 5 of a commercial vehicle and vehicle environment data 6 resulting during a journey along a route to a computing unit external to the commercial vehicle. This vehicle status data 5 is data that identifies and / or characterizes the state of the vehicle during this journey. In this case, values ​​for drive train-specific operating parameters can be recorded, i.e., operating data from systems and components can be recorded that are used to control or regulate drive train components, e.g.Operating data of an internal combustion engine, an automated manual transmission and its shift application, and / or an electric motor (depending on the vehicle's drive type), operating data on the cooling system of the drivetrain components, on a retarder, and on the power distribution between the tractor unit and semi-trailer. For example only, vehicle status data 5 can include the recorded vehicle speed and, in the case of internal combustion engine-powered vehicles, the gearshift history along the route, operating data on the cooling system of the drivetrain components, e.g., coolant temperatures, as well as data on the energy consumption of individual drivetrain components.

[0044] Such vehicle status data 5 can be collected by the commercial vehicle 3 along the route 4 in a conventional manner using the control units and sensors installed in the commercial vehicle. Based on the collected vehicle status data, the vehicle status during the journey along the route 4 can be reconstructed in detail.

[0045] The collected vehicle environment data 6 indicate where and under which ambient conditions (outside temperature, etc.) the journey along the route 4 took place. The vehicle environment data 6 preferably comprises location data and / or GPS data, i.e. data on the current location and / or the current route 4, such as elevation / gradient data or speed limits of the route 4. The vehicle environment data can further comprise weather data, preferably weather data on the ambient temperature, the time of year and / or wind speed that occur during the journey along the route, or data resulting therefrom on the rolling resistance of the vehicle. The vehicle environment data for the route itself can be obtained from the vehicle navigation system; environmental data for the surroundings, such as weather data, can be queried from a weather database and / or recorded using corresponding environmental sensors of the vehicle.

[0046] Which vehicle status data 5 and vehicle environment data 6 are recorded and transmitted depends, among other things, on the specific drive train configuration of the vehicle, furthermore on which drive train component(s) 2 the operating settings are to be optimized, as well as on the specific execution of the optimization calculation, ie, which data is required for this purpose.

[0047] The vehicle status data 5 and vehicle environment data 6 determined by the commercial vehicle 3 are transmitted wirelessly 9 to a computing unit 7 external to the commercial vehicle, e.g., by means of a data communication unit of the commercial vehicle 3, which can use, for example, a mobile data connection for this purpose. The computing unit external to the commercial vehicle can be a high-performance computer (central computer) 7 of the commercial vehicle manufacturer (see Figure 3).

[0048] The computer 7 uses the transmitted vehicle status data 5 and vehicle environment data 6 to simulate the journey along the route using a stored vehicle model 8, i.e., to recreate it through simulation (step S40). This simulation can be used to determine the current operating settings for the drivetrain components of the commercial vehicle (if not already known). Furthermore, the current operating settings can be evaluated with regard to definable target criteria.

[0049] Subsequently, the computing unit performs further simulations of the journey along the route using the stored vehicle model (step S60). However, for these simulations, the current operating settings are modified (varied). Step S80 then determines optimized operating settings for drivetrain components 2 of the commercial vehicle based on an evaluation of the performed simulations with respect to definable target criteria.

[0050] The evaluation of the simulations includes an evaluation of the varied operating settings, preferably also in comparison with one another and with the current operating settings, in order to select those operating settings that are optimal with regard to the target criteria. This step is also carried out by the computing unit 7. In other words, based on the current operating settings, these are changed in order to carry out further simulations, which can then be evaluated in order to be able to determine optimal or at least improved operating settings for the commercial vehicle. The result can be, for example, changed limit temperatures for controlling components of the drive train cooling system, or changed shift speeds for an automated manual transmission. Depending on which operating settings, ieTo determine and / or evaluate the specific component or subsystem of the powertrain for which the thermal effects are to be determined and / or evaluated, it is advisable to use a suitable vehicle (partial) model and the required vehicle condition data and vehicle environment data. By way of example only, a thermodynamic powertrain model can be used in a known manner to represent thermal effects as the vehicle model for the operating settings of the commercial vehicle's cooling system, and data such as the temperature and pressure in the cooling circuit, etc., can be used as vehicle condition data, and environmental influencing parameters such as the ambient temperature can be used as vehicle environment data.

[0051] In this case, it is advantageous to conduct the simulations and determine the optimized operating settings using and / or supported by machine learning methods. Due to the large amounts of data to be processed and the complex models involved, it is advantageous to use artificial intelligence, AI-based methods using an artificial neural network.

[0052] For the simulations in steps S40 and S60 and the evaluation of the simulations in step S80, known vehicle models 8 can be used. These models include a longitudinal dynamics model for simulating the vehicle's longitudinal dynamics and a thermodynamic powertrain model for simulating thermal effects. The simulation of vehicle behavior using such models in vehicle development is well known in practice. Commercial software packages for multi-physical modeling of the powertrain can also be used for this purpose, such as Matlab® and Simulink® from MathWorks and GT-SUITE® from Gamma Technologies. Such commercial software packages for vehicle development now also contain so-called artificial intelligence (AI) modules that support corresponding AI-based simulations using vehicle models.Initially, the vehicle environment data and vehicle condition data obtained during test drives of the commercial vehicle during its development can be used as training data. Over time, however, the new vehicle condition data and vehicle environment data continuously acquired through the application of the method can be used to continuously train the AI-based method and / or the artificial neural network used, etc.

[0053] For a possible implementation, reference is made merely as an example to the publication: "A multiphysical simulation model for the evaluation of drive and thermal management concepts in motor vehicles," by Christian Haupt, Technical University of Munich, published at: http: / / nbn-resolving.de / urn / resolver.pl?urn:nbn:de:bvb:91 - diss-20130307-1 1 14641 -0-4. The publication describes a possible vehicle model for modeling vehicle longitudinal dynamics and for modeling the thermal processes of the powertrain, which have a significant influence on fuel consumption. The publication also describes the determination of operating settings for powertrain components, supported by AI-based simulation and evaluation using artificial neural networks.Furthermore, the publication provides examples of commercial software packages suitable for performing corresponding simulations for the operating settings of powertrain components based on a vehicle model and evaluating them based on a class-based approach. Steps S40 to S80 can optionally be implemented based on the vehicle model of this publication and with the aid of the simulations and software packages described therein. The relevant aspects of this publication are hereby incorporated by reference.

[0054] It was stated above that in step S80, optimized operating settings for drivetrain components of the commercial vehicle are determined based on an evaluation of the simulations performed with regard to definable target criteria. The target criteria comprise several of the following target criteria: a travel time, energy and / or fuel consumption, operational wear of at least one component of the drivetrain, and possibly further target criteria. The target criteria are linked to at least one multi-criteria objective function using a definable weighting. The optimization of the operating settings of drivetrain components is understood as a multi-dimensional optimization problem that is described by such an objective function. Here, partial cost functions corresponding to the individual objective criteria are combined to form an overall cost function (quality functional) by means of summation.

[0055] Using this total cost function or the quality function, the individual simulations, each of which is based on different operating settings, can now be evaluated. The result can be those varied operating settings that are optimal in this regard. These can then be defined as optimized operating settings. The target criteria, weightings of target criteria, and the multi-criteria target functions can be stored in the computing unit 7 or in a database 12 to which the computing unit 7 can access. Furthermore, customer preferences for defining the target criteria and / or their weighting, as well as preferences for selecting target functions and vehicle functions to be optimized, can be stored in the database 12.

[0056] During steps S40 to S80, optimization-capable, as well as implausible or faulty, application processes in the vehicle can be identified. These include, for example, brief retarder activations, brief fan activations, implausible gearshifts, or gearshift oscillations. Based on predefined thresholds such as the duration of the activation or the number of gearshifts within a defined period, it can be determined whether a condition exists that can be improved.

[0057] These optimized operating settings 1 can then be transmitted back to the commercial vehicle 3 (step S100) in order to adapt the operating settings there according to the optimized operating settings. Transmission can be made directly wirelessly ("over-the-air") to the commercial vehicle 3 in operation or delayed until a future workshop visit. Alternatively, it is also possible to transmit the optimized operating settings to a fleet operator 10 of the commercial vehicle 3, who then transfers the optimized operating settings to the commercial vehicle 3.

[0058] Figure 2 shows a schematic flow diagram to illustrate a method according to a further embodiment of the invention.

[0059] A special feature of this design variant is that an end customer of the commercial vehicle, in particular a fleet operator, can be involved in the optimization of the operating settings.

[0060] According to this embodiment, the determination S80 of the optimized operating settings first comprises, in step S82, selecting a plurality of options for optimized operating settings 1 based on different variations of the operating settings.

[0061] The plurality of options can, for example, be provided in the form of different driving scenarios. The plurality of driving scenarios can, merely by way of example, comprise a first driving scenario (“consumption-optimized ferry operation”) which, of all driving scenarios, is the most optimized in terms of energy consumption efficiency, e.g., fuel efficiency. This means that this first driving scenario corresponds to operating settings for drive train components which enable the lowest possible energy consumption, e.g., fuel consumption, of the commercial vehicle. The plurality of driving scenarios can further comprise, for example, a second driving scenario (“time-optimized ferry operation”) which is the most optimized in terms of the shortest possible travel time and / or the highest possible average travel speed (and is less optimized for fuel efficiency). This means thatThis second driving scenario corresponds to operating settings that enable the fastest possible ferry operation, even if this comes at the expense of fuel efficiency.

[0062] The selection of options or driving scenarios can be performed, for example, by computer 7, in which a different total cost function is used for each option or driving scenario to evaluate the simulations and varied operating settings. For the first driving scenario ("consumption-optimized ferry operation"), energy consumption is weighted particularly heavily as a target criterion compared to other target criteria, while for the second driving scenario ("time-optimized ferry operation"), travel time is weighted particularly heavily as a target criterion compared to other target criteria.

[0063] In step S84, the information 11 concerning the selected multiple options can then be provided, together with a decision option, to a fleet operator 10 operating the commercial vehicle 3 for selecting an option for optimized operating settings 1 preferred by the fleet operator 10. The fleet operator can then decide on one of the options and select it.

[0064] According to this embodiment, a commercial vehicle operator can thus select a driving scenario that is advantageous for them or, in general, an option for optimized operating settings that is advantageous for them. For a first vehicle fleet whose operating costs should be as low as possible, the first driving scenario may be advantageous, whereas for a second vehicle fleet used for rapid goods deliveries, the second driving scenario may be advantageous. Depending on the preferred option, determining the optimized operating settings results in a more consumption-optimized or more time-optimized driving style of the commercial vehicle, e.g., through different gearshift applications with an automated transmission or different acceleration behavior in an operating mode with automated longitudinal guidance of the vehicle.

[0065] The preferred option selected by the fleet operator 10 using the decision option 11 for determining the optimized operating settings 1 can then be transmitted back to the computer 7 and received by the latter. The provision of information regarding the selected multiple options together with a decision option to a fleet operator operating the commercial vehicle can be done via a website, an application program ("app") or the like in order to inform the fleet operator about the selectable options. For this purpose, information about the options can be provided to explain them, e.g., how they differ in terms of fuel efficiency, average time savings per route, etc. The decision option can be implemented by making one of the options selectable by the fleet operator, e.g., by being clickable via a displayed selection menu.The result of this user input 13 is transmitted to the computing unit 7 in order to determine the optimized operating settings based on the selected option, which are transmitted to the commercial vehicle.

[0066] Figure 2 below illustrates a further embodiment variant relating to step S100 using steps S102 and S104. The special feature of this embodiment variant is that the determined optimized operating settings are also used to update or optimize the operating settings for other, particularly identical or similar, commercial vehicles in the fleet, without having to perform separate simulation chains for each vehicle.

[0067] For this purpose, in step S102, commercial vehicles 3 within a fleet of commercial vehicles are identified that have an identical or at least a similar drivetrain configuration. For example, based on the optimized operating setting or the resulting changed parameters, it can be checked to what extent the optimization can be transferred to vehicles with a similar configuration, e.g. because they are equipped with the same or a similar drivetrain configuration, for which the changed parameters are also applicable. The optimized operating settings 1 are then transmitted S104 to the commercial vehicles 3 of the fleet thus identified. The transmission can be made as quickly as possible wirelessly "over the air" directly to the corresponding commercial vehicles or, if vehicles cannot be reached "over the air", also with a time delay, as soon as a data connection is possible again or during the next workshop visit.When changing operating settings that are classified as safety-critical, the fastest possible data transfer should generally be ensured.

[0068] This allows the optimized operating settings to be first transmitted to the fleet operator, who then has them applied to the relevant vehicles in their fleet. Accordingly, this technology enables a fleet operator to quickly optimize operating settings for entire segments of their vehicle fleet.

[0069] Although the invention has been described with reference to specific embodiments, it will be apparent to one skilled in the art that various changes may be made and equivalents may be substituted without departing from the scope of the

[0070] Even if the method has been described specifically for the highlighted case of a commercial vehicle, the method is also generally applicable for determining optimized operating settings of a motor vehicle and shall be deemed disclosed in this regard. Insofar as examples of fleet operators of commercial vehicles are described, these examples shall also apply to operators of motor vehicle fleets. Consequently, the

[0071] The invention is not limited to the disclosed embodiments, but is intended to encompass all embodiments falling within the scope of the appended claims. In particular, the invention also claims protection for the subject matter and features of the dependent claims, independent of the claims referred to.

[0072] List of reference symbols

[0073] 1 Optimized operating settings

[0074] 2 drivetrain components

[0075] 3 Commercial vehicle 4 Driving distance

[0076] 5 Vehicle status data

[0077] 6 Vehicle environment data

[0078] 7 Commercial vehicle external computing unit

[0079] 8 Stored vehicle model 9 Wireless data transmission

[0080] 10 fleet operators

[0081] 11 Information and decision-making options

[0082] 12 Database

[0083] 13 User input

Claims

Patent claims 1. A method, preferably a computer-implemented method, for determining optimized operating settings (1) for powertrain components (2) of a commercial vehicle (3), comprising the steps of: a) transmitting (S20) vehicle state data (5) of the commercial vehicle and vehicle environment data (6) obtained during a journey along a route (4) to a computing unit (7) external to the commercial vehicle; b) using (S40) the transmitted vehicle state data (5) and vehicle environment data (6) by the computing unit (7) to simulate the journey along the route (4) using a stored vehicle model (8) in order to determine current operating settings for powertrain components (2) of the commercial vehicle (3); c) performing (S60) further simulations of the journey along the route (4) by the computing unit (7) using the stored vehicle model (8), based on variations of the determined current operating settings;d) Determination (S80) of optimized operating settings (1) for powertrain components (2) of the commercial vehicle (3) based on an evaluation of the simulations performed and the varied operating settings with regard to definable target criteria, and e) transmission (S100) of the optimized operating settings (1) to the commercial vehicle (3), for example by means of wireless data transmission (9) and / or during a workshop visit.; 2. The method of claim 1, wherein the determination (S80) of the optimized operating settings comprises: a) selecting (S82) several options for optimized operating settings (1), for example in the form of several driving scenarios, based on different variations of the operating settings; b) providing (S84) information (11) concerning the selected several options, together with a decision option (11) to a fleet operator (10) operating the commercial vehicle (3) for selecting an option for optimized operating settings (1) preferred by the fleet operator (10); and c) receiving (S86) the preferred option selected by the fleet operator (10) by means of the decision option (11) for determining the optimized operating settings (1). A method according to any one of the preceding claims, further comprising the steps: identifying (S102) commercial vehicles (3) within a fleet of commercial vehicles that have an identical or at least similar powertrain configuration, and transmitting (S104) the optimized operating settings (1) to the identified commercial vehicles (3) of the fleet. A method according to any one of the preceding claims, a) wherein the target criteria comprise at least one of the following: driving time, energy and / or fuel consumption, operational wear of at least one component (2) of the powertrain, driving comfort, range, and average speed of the commercial vehicle (3), and b) wherein the target criteria are linked to at least one multi-criteria objective function by means of a weighting, preferably definable. A method according to claim 4, further comprising the step: Determining the target criteria and / or their weighting or selecting an objective function from the at least one objective function by user input (13) and / or by querying a database (11), in which preferably a customer preference for determining the target criteria and / or their weighting and / or for selecting the objective function is stored. A method according to one of the preceding claims, wherein the execution (S60) of further simulations and the determination (S80) of the optimized operating settings (1) are carried out by means of and / or supported by machine learning methods, preferably AI-based methods using an artificial neural network.Method according to one of the preceding claims, wherein the execution (S60) of further simulations and the determination (S80) of the optimized operating settings (1) is carried out for selected operating settings (1) corresponding to at least one vehicle function, wherein the at least one vehicle function was selected by a user input (13) and / or by querying a database (12) in which preferably a customer preference for determining the vehicle functions to be optimized is stored.

8. Method according to any of the preceding claims, wherein the vehicle model (8) comprises a longitudinal dynamics model for representing the vehicle longitudinal dynamics and / or a thermodynamic powertrain model for representing thermal effects.

9. Method according to any of the preceding claims, wherein the vehicle environment data (6) comprise: location data and / or GPS data, weather data, preferably weather data relating to ambient temperature and / or wind speed for the route (4).

10. Method according to one of the preceding claims, wherein the variation of the determined current operating settings (1) comprises a) a variation of operating parameters and / or state variables of the powertrain components (2) that can be automatically adjusted within the framework of control and / or regulation processes; and / or b) a variation of at least one of the following vehicle-related modification possibilities: a tire diameter and a total weight, preferably a gross train weight of a commercial vehicle designed as a semi-trailer tractor (3).

11. Method according to one of the preceding claims, wherein the performance (S60) of further simulations further comprises: a variation of at least one of the following environmental parameters: an ambient temperature and road gradient.

12. Method according to one of the preceding claims, wherein a) the operating settings (1) comprise a profile, preferably a controlled or regulated profile, of at least one state variable of at least one drive train component (2) for the journey distance (4); and b) the optimized operating settings (1) comprise a profile optimal with respect to the definable target criteria, preferably optimal control or regulation, comprising at least one state variable.

13. The method of claim 12, wherein the at least one state variable comprises at least one of the following state variables: a) a speed selection of the vehicle (3); b) a gear selection, shift points and / or shift speeds for an automated transmission; c) a state of charge of an energy storage device for providing electrical drive energy in a hybrid or electric powertrain. d) a coolant temperature of a primary or secondary cooling circuit of a powertrain, e) switching-on and switching-off times of a fan for engine cooling and / or a pump of a primary or secondary cooling circuit of the powertrain, f) switching times for a retarder, g) switching-on times of an electric auxiliary drive, h) a power distribution between a tractor unit and a semi-trailer and / or trailer. Method according to one of the preceding claims, wherein the commercial vehicle (3) is a tractor unit with a semi-trailer, wherein the vehicle state data (5) preferably comprise load data of the semi-trailer, preferably data on the weight and / or volume of the load.

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