Vehicle state control system for emission control, road vehicle, and method of vehicle state control

Abstract

The invention relates to an emission limited vehicle state control system comprising a state detection unit 1, a database unit 2 and a control and evaluation unit 3, the state detection unit 1 being designed to provide state data, the database unit 2 having a static database module 2.1, a dynamic database module 2.2 and a data management module 2.3, the static database module 2.1 containing static data relating to causal relationships for emissions not associated with the powertrain and the dynamic database module 2.2 containing variable data relating to emissions not associated with the powertrain, the control and evaluation unit 3 being designed to receive the state data from the state detection unit 1 and the database data from the database unit 2, to determine by means of a calculation module 3.1 an emission budget and a target emission value, to provide alternative preliminary control commands and allocate thereto a predictive emission characteristic value, and to choose a final control command from the alternative preliminary control commands based on the predictive emission characteristic value and the target emission characteristic value by means of an assessment module 3.2 and to output this final command to an actuator unit 4 in order to influence the vehicle state. The invention also relates to a road vehicle comprising a vehicle state control system of this kind and to a method for vehicle state control.

Description

Technical Field

[0001] The present invention relates to an emission restriction vehicle state control system and a method for vehicle state control for restricting emissions not associated with a drive train. Further, the present invention relates to a road vehicle in which emissions are restricted with respect to emissions not associated with a drive train.

Background Art

[0002] Traffic-related emissions can exist as engine emissions, particularly as exhaust gases of an internal combustion engine, and as non-engine emissions.

[0003] Both types of traffic-related emissions are subject to public criticism for their contribution to climate change and are classified as being dangerous to health. For more than 20 years, the European Union and the World Health Organization have accordingly worked to reduce particulate emissions by providing both guidelines and legislation. To reduce engine emissions, increasingly efficient operating systems have been developed in the past, with particular emphasis on measurements within the engine itself or on a post-treatment system.

[0004] Currently, there are no legal limit values for non-engine emissions, which has led to a continuous increase in this proportion of total emissions. Therefore, engine emissions and non-engine emissions are estimated to contribute to pollution within urban areas at comparable rates today. Since some of the wear particles can be assigned to the fine dust size class (<= 10 micrometers), the source of this fine dust is particularly relevant to human health.

[0005] In this context, UNECE has established the "Particle Measurement Programme" (PMP) to develop a standardized test procedure for the sampling and measurement of brake particles. For this reason, attention to this emission source has increased in the past.

[0006] Various approaches are currently known to reduce emissions not associated with the drivetrain, particularly those from friction brakes.

[0007] On the other hand, proposed solutions related to conventional technologies involve collecting the generated brake dust and thereby avoiding or reducing its release into the environment.

[0008] For example, German Patent Application Publication No. 102005006465 describes a solution in which discharged brake dust is bound to components of the braking system by applying an electrostatic field, a magnetic field, or a combined field. The components are cleaned by switching off the field.

[0009] Japanese Patent Publication No. 2008-115957 describes a proposal in which an electric potential is applied between the inside and outside of a rim in order to deposit brake particles inside the rim.

[0010] German Patent No. 60224858 discloses a brake wear collection device by means of increasing the electric field during braking to collect brake dust on a collection plate.

[0011] Furthermore, German Utility Model Application Publication No. 202005006844 describes a device for collecting friction block wear from the braking system of a motor vehicle, the device characterized in that brake dust is transferred via a flow guide to a filter system, where it is filtered.

[0012] German Patent Application Publication No. 102006051972 describes another brake dust collection device by means of a housing that partially encloses the area of ​​the brake caliper outlet, and as a result, thanks to the advantageous design of the housing, brake dust flows into the housing through the opening and accumulates therein.

[0013] In addition, German Patent Application Publication No. 102007009744 proposes a solution for removing brake dust, in which a suction device is connected to the vehicle's exhaust system, and the acting negative pressure transports brake dust from the wheel brakes toward the exhaust system, where it is deposited in a particle filter.

[0014] German Utility Model Application Publication No. 202005017472 also describes a concept for a brake dust absorption system, characterized in that brake dust particles are extracted by suction by a device and supported by an electrostatic field and deposited in a filter.

[0015] International Patent Application No. 2014 / 072234 describes an extraction device that sucks off brake dust through guide channels integrated into the brake lining and supplies it to a filter system.

[0016] The drawbacks of these state-of-the-art solutions are, on the one hand, the need for additional, complex, and redundant devices that tend to malfunction, and on the other hand, the remaining problem of brake dust accumulation in an environmentally friendly manner.

[0017] An approach is known that involves starting one step earlier, with the aim of reducing the formation of brake wear.

[0018] German Patent Application Publication No. 102018207298 describes a control unit and method for reducing the amount of brake dust discharged, the method describing the determination of position data relating to the position of a motor vehicle and the adaptation of the distribution of braking force to different braking devices mounted on the motor vehicle according to the position data. A drawback of this disclosure is that this solution does not actually meet the requirements of the complexity of the driving conditions.

[0019] Furthermore, German Patent Application Publication No. 102009001332 describes a solution for environmentally friendly cornering. This publication proposes a method in which the course of the curve to be traversed is determined, at least one target driving parameter is calculated to minimize emissions caused by tire wear, brake dust and carbon dioxide are generated, and the actual driving parameter is approximated to the calculated target parameter. A particular drawback here is that only solutions for specific driving conditions are shown.

[0020] German Patent Application Publication No. 102016215900 relates to a method for determining vehicle emissions and a system for carrying out the method. This solution assumes that during true driving operation, emissions are determined by means of a vehicle data processing device in a sensor-supported or model-based manner, depending on at least one vehicle parameter. The drawback of this approach is that it only provides a solution for determining emissions, and does not provide a solution for reducing them.

[0021] Furthermore, International Patent Application No. 2020 / 031103 discloses a method and device for recording and providing data for evaluating braking behavior, with particulate emissions serving as an indicator. This data is output to the vehicle driver, allowing the driver to optimize their driving style to reduce non-engine emissions. The drawback is that emission-reducing driving behaviors are merely encouraged and still depend on actual driving behavior.

[0022] Another solution for reducing brake dust emissions is described in German Patent Application Publication No. 102018207298. In particular, it is proposed to distribute braking force to different braking devices in a targeted manner based on the vehicle's position data for the purpose of reducing emissions. The drawback of braking force distribution is that only one specific technical aspect is addressed while other parameters are not considered.

Prior Art Documents

Patent Documents

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Patent Document 1

Patent Document 2

Patent Document 3

Patent Document 4

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Patent Document 13

[0024] The task of the present invention is to provide a vehicle state control system that enables emission-restricted driving of a road vehicle with respect to emissions not associated with the drivetrain, while simultaneously optimizing driving dynamics and being independent of the driving concept. Furthermore, the task is to provide a road vehicle for such emission-restricted driving operation, characterized simultaneously by optimized driving dynamics, along with a method for such emission-restricted vehicle state control and vehicle state control with optimized driving dynamics. [Means for solving the problem]

[0025] Tasks relating to a vehicle state control system are solved by the features described in claim 1. Tasks relating to a road vehicle are solved by the features described in claim 8, and tasks relating to a method are solved by the features described in claim 9. Preferred further embodiments result from the respective dependent claims.

[0026] A vehicle state control system according to the present invention, for limiting emissions not associated with the drivetrain, is based in particular on the following considerations:

[0027] For the purposes of this invention, emissions not associated with the drivetrain, also hereafter referred to as non-engine emissions, are understood to be all particulate emissions, which are generated by road vehicles and cannot be traced back to the engine combustion process. Emissions not associated with the drivetrain are particularly those from friction brakes and vehicle tires. In a broader sense, they also include road wear and resuspension caused by traffic-related turbulence.

[0028] The deceleration of road vehicles is still primarily achieved by the application of friction brakes, which convert kinetic energy into thermal energy. Eliminating friction brakes is currently not possible, even in the case of battery-electric vehicles with high recovery power, due to deceleration requirements in emergency braking situations. Systematic brake linings in combination with cast iron brake discs are considered the standard friction partner. The decisive friction effect is taken over by the contact area, which has high compressive and shear strength and is typically implemented by fiber ends or single metal chips present in the lining matrix. The particles remain primarily in the contact zone under the effects of flow forces and inertial forces. This movement occurs partially tangent to the direction of rotation, and partially they are carried circumferentially at the boundary surface to the brake disc.

[0029] In addition to initial velocity or frictional energy, surface pressure and friction zone temperature are considered to be the main variables influencing particle shape wear in friction brakes. The particle formation process and the interrelationships involved are complex and particularly dependent on the material properties of the friction mating surfaces at the frictional contact points. Therefore, in order to reduce emissions generated by vehicle wheel brakes, special attention should be paid to driving dynamics and operating conditions, in addition to materials and design approaches.

[0030] Tire and road particles can also be defined as a linking component, namely the wear of the tire tread and road surface. Wear can be described as a frictional stress, i.e., the progressive removal of material from the uppermost surface of a solid due to the contact and relative movement of the corresponding counter bodies.

[0031] The main cause of tire and road particle formation is slippage. This occurs when the instantaneous vehicle speed is greater or less than the circumferential speed of the tire. Slippage can be divided into the deformation ratio of the tire body and individual tread elements, i.e., the elastic deformation of the tire's sidewalls, and the sliding ratio, i.e., the partial relative movement between the tire surface and the road surface. In addition to wear of the tire tread and road surface due to slippage, particles can also be released due to the deposition and melting processes of the tire tread at rising temperatures. The latter can occur in cases of high sliding speed and low power transmission between the wheel and the road. Furthermore, lateral slip, which is responsible for the transmission of lateral forces during cornering, can also be classified as a cause of particulate matter emission.

[0032] The present invention is further based in part on the consideration that if the emission relevance of vehicle states to active control interventions is made situationally accessible and included in decisions for controlling motor vehicle states, then reductions in emissions not associated with the drivetrain can be achieved.

[0033] The present invention is also based on the consideration that when an emissions budget is formed for an operating unit (i.e., a total route including multiple emissions-related operating events), the allocation of emissions budget to individual emissions of operating events takes into account the effect of each operating event on the operating dynamics, and enables better operating dynamics to be achieved together with the same total emissions, rather than having only the evaluation of the emissions relevance of individual operating events performed separately.

[0034] Overall, depending on the system under consideration, distinct influencing variables for the formation of particulate abrasion can be defined, and the intensity and interaction with other influencing variables can be represented or explained using mathematical models or algorithms of machine learning. The explanation represents criteria for optimal action in terms of emission, abrasion, and driving dynamics with respect to acceleration and / or deceleration and / or lateral dynamics control.

[0035] For this purpose, the vehicle state control system includes, as its basic components, a state detection unit, a database unit, and a control and evaluation unit.

[0036] According to the present invention, the state detection unit is designed to record state data. The state data may be traffic status data, vehicle status data, or vehicle subsystem data.

[0037] The status detection unit has multiple detection units, including a traffic status detection unit, a vehicle status detection unit, and a vehicle subsystem detection unit.

[0038] A traffic situation detection unit is designed to record traffic situation data and provide it in a transmittable format. In particular, a traffic situation detection unit may be implemented as a sensor or system for recording the behavior of other road users, such as the speed of other vehicles; the behavioral requirements of traffic control devices, such as traffic lights; or the spatial relationships of a traffic area, such as lane width and distance to intersections. Furthermore, it can be data transmitted remotely, for example, in the form of navigation data, weather data, or, for example, traffic jam reports. Thus, a traffic situation detection unit detects externalities to vehicles.

[0039] A vehicle state detection unit is designed to record vehicle state data and provide it in a transmittable format. This vehicle state data specifically concerns the vehicle's driving dynamics, such as speed, acceleration in the direction of movement, or lateral acceleration. For this purpose, the vehicle state detection unit also includes appropriate sensors.

[0040] Finally, the state detection unit also has a vehicle subsystem detection unit, which is designed to record vehicle subsystem data and provide it in a transmittable format. Such vehicle subsystems can be friction brakes or vehicle tires, in particular. The state of such a vehicle subsystem is represented by at least one physical variable, but preferably several physical variables. Such physical variables could be, for example, the temperature of the brake disc or the temperature of the tire surface.

[0041] The database unit includes a static database module, a dynamic database module, and a data management module. Furthermore, the database unit can be data-connected to a state detection unit and receive state data from the state detection unit.

[0042] The static database module contains static data on causal relationships regarding emissions not associated with the drivetrain. These can be, for example, stored characteristic curves or maps. For instance, the relationship between driving speed, temperature, and friction brake particulate emissions can be stored as a characteristic curve or map. The data thus stored is based on a series of experimental tests or field data, thus ensuring a high degree of reliability. Their causal relationships are valid overall, and therefore, they can serve as a static data standard.

[0043] The vehicle state control system according to the present invention is particularly characterized by its interaction with a dynamic database module and further components. The dynamic database module has variable data relating to emissions not associated with the drivetrain. The variable data relating to emissions not associated with the drivetrain does not have overall effectiveness as a static database and is all data that can be related to emissions not associated with the drivetrain, depending on the situation. Such variable data may be, for example, dynamically acting influence values ​​or data relating to the state history.

[0044] In the case of dynamically acting influences, for example, a newly installed corrosive protective coating on brake friction may alter braking effect and discharge behavior, while simultaneously being affected by significant wear resulting from the braking action.

[0045] Data related to the condition history could be, for example, climate data. For instance, if there are high levels of humidity over a longer period, it can be assumed that corrosion on the surface of the brake disc will be enhanced, simultaneously altering the braking effect and discharge behavior. In addition, corrosion deposits are increasingly removed by the application of the brakes.

[0046] Therefore, the variable data in the dynamic data module, while having relevant influences on emission behavior, is, on the other hand, merely data that is always valid depending on the situation.

[0047] Another element of the database unit is the data management module.

[0048] This module is designed to write variable data to or delete them from the dynamic database module. In this way, the data management module ensures that current status-related data is available in the dynamic database module.

[0049] Furthermore, the data management module is designed to retrieve static data from the static database module and variable data from the dynamic database module, as well as to make them available to the control and evaluation units as transferable database data. Thus, static and dynamic data are collectively referred to as database data.

[0050] According to the present invention, the data management module ensures that the control and evaluation units also have available database data in addition to status data, and in particular ensures that, in addition to static data, the database data always includes variable data relevant to each situation.

[0051] According to the present invention, the control and evaluation unit is data-connected to both the status detection unit and the database unit. Furthermore, it is designed to receive and process status data from the status detection unit and database data from the database unit. The status data and database data are also collectively referred to as input data.

[0052] As a result of processing the input data, the control and evaluation unit provides alternative preliminary control commands, and predictive emission parameters are assigned to these alternative preliminary control commands. The predictive emission parameters represent the predicted emissions, unassociated with the drivetrain, that result from the execution of each control command. For the calculation of predictive emission parameters, causal relationships are particularly important so that they are stored as static data in a static data module. These relationships could be, for example, the relationship between brake disc temperature and particulate emissions resulting from brake wear. The calculation of predictive emission parameters also includes state data such as speed or variable data such as the total operating time of friction brakes. The alternative preliminary control commands are understood to mean, overall, that several different possible control commands are calculated for the same state and are therefore available in parallel for subsequent evaluation.

[0053] The control and evaluation unit also includes a calculation module. The calculation module is designed to calculate the emissions budget for each operating unit from state data and database data.

[0054] In this context, a driving unit is understood as the sum of multiple individual driving events performed to cover a certain distance by a vehicle from a starting point to a destination point. A driving event is understood as a driving segment of a driving unit, separated from a previous driving segment by one or more control interventions. Driving events may also be referred to as driving happenings or driving segments.

[0055] The emissions budget can be based specifically on specifications that define the acceptable emissions for each driving route. These specifications can be defined, for example, as quality characteristics by the vehicle manufacturer and stored in a database unit. Furthermore, regulatory requirements also exist in this regard and are subsequently stored in the database unit, and it is considered that the system can be adapted in the event of any changes to the regulatory requirements by modifying the database data.

[0056] Based on status data and database data, the driving route can be determined by the route planner, for example, after entering the starting point and destination of the trip to be taken, and as a result, the length of the driving route is known. Then, the emissions budget can be calculated based on the driving route. The emissions budget is the total amount of emissions that can be emitted by the vehicle during the trip along this driving route.

[0057] Furthermore, the calculation module is designed to use the calculated emission budget to determine target emission parameters for preliminary alternative control commands. This is based on the fact that data such as speed limits, traffic lights, and potential traffic jams, along with geographical data of the driving route such as curve radius and gradient, and data on the road surface, are known for the determined driving route from state data and database data.

[0058] This allows for the determination of alternative, preliminary control commands for individual operating events based on the predictive emission parameters assigned to them accordingly. The target emission parameters indicate the emission parameters available for a particular operating event, and as a result, they do not exceed the emissions budget as a whole.

[0059] Based on this, the control command can be selected from alternative, preliminary control commands, and its assigned predictive emission parameters correspond to the target emission parameters. In this way, it is achieved that the sum of the predictive emission parameters of the selected control command does not exceed the emission budget.

[0060] Advantageously, this also allows for the allocation of emission budgets to predictive emission parameters in control commands in a manner that achieves the best possible driving dynamics.

[0061] For this purpose, the control and evaluation unit according to the present invention includes an assessment module, which is designed to select a final control command from alternative preliminary control commands by means of comparing predictive emission parameters with target emission parameters.

[0062] The assessment module is based on the fact that different vehicle state control objectives, also referred to below as control objectives, may be in conflict with each other. Such control objectives may include, in particular, the minimum possible driving time, the minimum possible energy source consumption, or the lowest possible emissions from sources not produced by the drivetrain. For example, a high degree of target achievement for a short driving time control objective, also referred to below as high driving dynamics, is accompanied by a low degree of target achievement for a low emissions control objective. Selection decisions between different possible control commands usually result in compromises in the degree of target achievement for different control objectives. The assessment module is used to weight the control objectives. Based on the weighting, the assessment module can thus calculate which of the alternative preliminary control commands has the best overall optimization effect on the weighted control objectives. Depending on the weighting, the best overall optimization is achieved by different degrees of target achievement for various control objectives, and as a result, different alternative preliminary control commands are usually selected with different weightings. In particular, the weighting can be adjusted by the user, and as a result, for example, low-emission vehicle operation may be selected, with somewhat longer driving time being preferable. The control command selected through weighting is referred to as the final control command.

[0063] The assessment module is designed to determine the achievement of the target driving dynamics in cases of different derivations of predictive emission parameters from target emission parameters, where the sum of predictive emission parameters does not exceed the emission budget. This is always simply a different allocation of the emission budget. Simultaneously, different driving dynamics are achieved for individual driving events, where the individual driving dynamics related to the driving event are aggregated to produce an overall evaluation. The final control command is then selected in such a way that the sum of the individual driving dynamics results leads to an optimized overall driving dynamics result. This means that the emission budget is allocated such that, on the one hand, emissions may be higher in driving events where the relatively best driving dynamics gain is achieved by increasing emissions, and on the other hand, to compensate for this, they should be lower in driving events where emission reductions result in the relatively lowest driving dynamics loss.

[0064] After selection is made by the assessment module, the control and evaluation unit is designed to output final control commands to the actuator unit, and the vehicle state can be influenced by the actuator unit.

[0065] According to the present invention, the final control command is output to the actuator unit. Therefore, the control command is understood as any output by means of a subsequent technical unit in which a specific condition is triggered. In particular, it can be a direct switching command, or it can simply be a data output. A control command in the sense of the present invention is also understood as a non-command, i.e., a decision that does not actively intervene in the vehicle state, but for example, allows the vehicle to rotate without acceleration or deceleration.

[0066] In the sense of this invention, an actuator is understood as any technical unit whose operating conditions are modified by incoming control commands. First and foremost, an actuator is understood as any unit that directly acts on physical variables. An actuator is understood, for example, the direct action of a friction brake, the action of an eddy current brake, or the control of an electric drive unit in both driving and generator modes. Thus, for example, vehicle deceleration can be influenced by the adjustment of absorbed torque in generator mode, or, alternatively or cumulatively, by the action of a friction brake. Furthermore, an actuator in the sense of this invention is also understood as any other technical system, such as a vehicle subsystem or further control and evaluation unit, whose operating conditions are influenced by control commands and thus indirectly affect the vehicle state.

[0067] Interactions with different vehicle systems, such as the drivetrain, are considered to ensure optimal control for the driving conditions. In an example of the electric drive concept, the kinetic energy of a moving vehicle is converted into electrical energy, which can then be buffered. The required deceleration torque can be provided entirely by an electric drive unit in generator mode or by coupling with mechanical friction brakes, resulting in the benefit of reduced fine dust emission, coupled with the aforementioned reductions, along with a reduction in the number of applications of friction brakes, brake pressure, friction power, and friction zone temperature.

[0068] The inherent advantage of the solution according to the present invention is given by the fact that emission reduction by limiting means is already made possible by intelligent driving dynamics control without additional physical means.

[0069] In particular, the solutions according to the present invention are advantageous in that they allow for the consideration of causal relationships, which are higher in class of driving conditions, in order to reduce brake and / or tire and / or road wear.

[0070] For example, the solution according to the present invention is advantageous in that the data processing and decision elements do not output vehicle acceleration that is optimal for traffic flow and / or reasonable for passengers, but rather output acceleration that takes driving conditions into account, resulting in low levels of friction from the road surface, minimizing driving slip, and consequently significantly reducing tire wear.

[0071] The integration of vehicle subsystems according to the present invention, such as the use of an electric drive unit in the generator mode described above, advantageously provides a relative control concept for reducing emissions not associated with the drivetrain.

[0072] In particular, the present invention aims to address the increasing proportion of semi-autonomous and autonomous driving in the future, and situation-dependent decision-making is implemented by minimizing particulate emissions, albeit in a highly dynamic manner.

[0073] The vehicle's condition and environment are recorded and evaluated in real time by appropriate sensors, cameras, motor-vehicle-to-motor communication or motor-vehicle-infrastructure communication, or other means of condition recording. A computational structure that calculates appropriately adapted output data based on the input data is provided for fully automated guidance.

[0074] Under considerations such as friction braking due to the formation of particulate matter as a result of brake, tire, or road wear, the vehicle's acceleration and / or deceleration and / or lateral guidance (steering) actions are evaluated, taking into account the causal relationship between the vehicle subsystem's instantaneous actions and its predicted operating conditions, and control intervention and / or digital value return are implemented. In the case of autonomous or semi-autonomous driving of the vehicle, traffic conditions, driving conditions, vehicle subsystem data, and causal relationship data are also recorded and / or provided in real time to determine the action that is optimal in terms of wear and driving dynamics.

[0075] Based on traffic conditions, driving conditions, and vehicle subsystem data, the optimal action in terms of emissions, wear, and driving dynamics, which is calculated by the control and evaluation unit as a data processing and decision-making element in causal relationships and affects the vehicle's further state under consideration, can be defined as a control intervention or a digital value return for the control of the vehicle system, for example, for deceleration control by means of an electric motor in generator mode, with respect to acceleration, deceleration, and lateral dynamics, and in addition to environmental data, data on the vehicle subsystem under consideration is also taken into account in determining the action that is optimal for wear and driving dynamics.

[0076] In this context, the solutions according to the present invention are not limited to the objective of completely preventing the emission of particulate matter, but are also not limited to the objective of ensuring optimal operating conditions, such as friction brakes, by temporary action to maintain an optimal operating range for emergency braking events, and consequently describing driving decisions as actions that are optimal in terms of emission, wear, and driving dynamics.

[0077] In particular, it is advantageous that, without increasing emissions, higher driving dynamics can be provided by forming an emission budget and optimizing its allocation to individual driving events, taking into account the effects on driving dynamics.

[0078] Furthermore, an advantage of the vehicle state control system according to the present invention is that it is possible to reduce the amount of particulate matter emitted by friction brakes, while also ensuring optimal operating conditions for friction brakes, for example, by temporary operation to maintain the optimal operating range for emergency braking events.

[0079] The vehicle state control system according to the present invention can advantageously result in emission reductions for both semi-autonomous and autonomous driving.

[0080] Semi-autonomous and autonomous driving of vehicles are distinguished depending on the vehicle and the tasks of the driver or passenger.

[0081] Even in assisted driving, individual assistance systems can control speed, acceleration, and deceleration in accordance with the vehicle in front.

[0082] In the case of autonomous driving, the driving dynamics are controlled autonomously.

[0083] A vehicle condition control system, advantageously provided by an electric motor which is an integrated component to ensure reversible braking, can result in emissions-optimized operation for vehicles of any design or driving concept. The vehicle may be equipped with various sensors for detecting driving conditions, such as at least ultrasonic sensors, radar, cameras, or sensors of other physical measurement principles for recording environmental conditions.

[0084] To reduce particulate wear on vehicle tires or friction brakes by altering the driving dynamics through means of acceleration or deceleration, the acceleration intensity and braking torque can be particularly limited, depending on causally determined control, by using vehicle systems such as the drivetrain for deceleration in generator mode without engaging the friction brakes.

[0085] The solution according to the present invention aims to compromise between driving dynamics / driving comfort and the acceleration, deceleration, or lateral acceleration performance required to accomplish driving tasks, with the lateral acceleration performance being directly coupled to the particle formation process.

[0086] In addition, the vehicle state control system according to the present invention is characterized by the advantage of providing control through emission reduction effects without the need to measure the true emissions of the vehicle.

[0087] Furthermore, there is a specific advantage in that emissions not associated with the drivetrain can be restricted in a pre-definable manner. Depending on the restriction as the primary default, this restriction is maintained while achieving the optimal possible driving dynamics.

[0088] As a first advantage, further developments will result in the vehicle condition control system being designed as a system compliant with SAE levels 2-5.

[0089] In this further development, the SAE level will be considered as a standard, as follows:

[0090] SAE Level 2 is a particularly automated level. Using information about the driving environment, one or more driver assistance systems anticipate that the human driver will perform all remaining aspects of the dynamic driving task, and driving mode-specific steering and acceleration or braking processes are performed.

[0091] SAE Level 3 is a conditional automation level in which the automated driving system performs all mode-specific executions of dynamic driving tasks, anticipating that the human driver will respond appropriately to requests from the driving system.

[0092] SAE Level 4 represents a high level of automation. Here, all aspects of the dynamic driving task are performed by the automated driving system, even when the human driver does not respond to requests from the driving system.

[0093] SAE Level 5 is a fully automated level, where all aspects of dynamic driving tasks are performed by the automated driving system. This applies to all driving and environmental conditions that can be operated by a human driver.

[0094] Further developments include vehicle subsystems such as braking systems and / or tire systems.

[0095] Vehicle braking and tire systems are major sources of emissions not associated with the drivetrain.

[0096] With this further development, at least one physical variable of the braking system and / or tire system is recorded by the vehicle subsystem detection unit of the state detection unit and included as part of the state data in the evaluation and generation of control commands. Since the operating conditions of the braking system and tire system are particularly related to emission behavior, the further development will achieve potentially particularly high reductions. In particular, it is possible to monitor the temperature of the brake friction mating surface and proactively regulate the reduced driving speed after dangerous braking due to excessive overheating of the friction mating surface, and as a result, the critical temperature of the friction mating surface is also prevented in newly concentrated braking events.

[0097] Further developments allow the vehicle's condition to be affected as deceleration by the braking system.

[0098] This further development is based on the fact that braking systems are one of the main sources of emissions, particularly when the brakes are applied to slow down a vehicle.

[0099] A particular advantage here is that control commands can be provided in a manner in which deceleration occurs completely or partially by the generator operation of the electric drive unit. Furthermore, the control commands can be advantageously generated in a manner that avoids high brake disc temperatures, which would lead to increased particulate emissions.

[0100] Further developments may involve control and evaluation units and database units forming a structural unit. This unit is preferably a computer system having an integrated data memory for recording static and variable data. This structural unit may preferably be part of a vehicle control system.

[0101] Further advancements allow data related to status history to be written to a dynamic database.

[0102] Data related to status history can include, for example, data on brake operation over the most recent period. For instance, if the brakes were applied particularly hard due to the high temperature of the friction partner, it can be inferred that there was a thermally induced surface change in the brake lining. This change has an effect on both braking and emission behavior. Since their causal relationships are stored as further data in the database, this can be included in the generation of control commands along with the effect of emission reduction.

[0103] Further advantages and advancements allow the control and evaluation unit to evaluate the dependency relevance of previous final control commands by means of status data and update variable data by means of a data management module.

[0104] Advantageously, this further development allows for the design of vehicle state control systems as self-learning systems. In this design, when a control command is issued, status data, particularly vehicle status data and vehicle subsystem data, are recorded as they change. In this way, emissions, and thus the emission correlation, can be indirectly evaluated by taking data and causal relationships into account. The data management module then writes the additional data thus acquired as variable data to a dynamic database. Thus, the database of variable data is continuously optimized, and control interventions are executed by control commands so that emissions are further reduced as a result.

[0105] For example, this could be the case where vehicle tires with optimized rotational resistance are mounted to increase the range of, for instance, autonomous battery electric vehicles, and maintaining frictional contact due to increased lateral acceleration can lead to increased tire wear, especially when cornering. Advantageously, driving dynamics control can thus be optimized using a neural network, taking into account driving conditions and vehicle system data for cases such as changes in tires and / or brakes and / or road conditions, based on updates of variable data in a dynamic database in the sense of learning elements. Vehicle subsystem data such as ABS or ESP can also be used for training to evaluate specific driving situations. Thus, vehicle dynamics control is trained to new conditions.

[0106] To make decisions regarding the final selection of control commands, information on emission-related benefits is required as a reward to enable evaluation of the actions resulting from the control commands. This information is provided by a database unit, which in particular has a dynamic database module as a learning element for this purpose. Information on emission-related benefits can be used as a mathematical model to predict particle release resulting from actions such as friction brakes, tires, or wear on the road surface. For example, a machine learning algorithm can be applied that takes into account branched correlations between tribological properties, lining configuration, and environmental and test conditions. It is also conceivable that information be input through a learning process.

[0107] The control and evaluation unit can evaluate the actions resulting from control commands and calculate which process is most likely to lead to success. This makes it possible to achieve long-term improvements in the actions. Furthermore, advantageous further progress will be carried out based on observations of the environment, making it possible to select actions that are compared and evaluated according to predefined standards.

[0108] The variable data of the dynamic database module provides memory for the vehicle state control system, enabling it to store the current state of the environment. If the environment is only partially observable, an internal model of the environment's state can be created with the aid of available information. Based on this model, the control and evaluation units can provide optimized control commands.

[0109] In a further embodiment, the present invention relates to a road vehicle having a friction brake and including a vehicle state control system as described in any of the preceding claims. Regarding the vehicle state control system as a feature of such a road vehicle, references are made to the relevant chapters of the description relating to the preceding claims.

[0110] Such road vehicles according to the present invention have the particular advantage that particulate emissions can already be reduced by controlling the vehicle state during the operation of the road vehicle without the need for additional structural measurements.

[0111] A method for controlling the state of a vehicle, using means of a vehicle state control system according to any one of claims 1 to 7, comprising the following steps: a) Writing static data as parameterized data to a static database module, b) Recording state data by a state detection unit and providing them for transmission, c) The control and evaluation unit acquires state data from the state detection unit and database data from the database unit. d) The control and evaluation unit provides alternative preliminary control commands and assigns predictive emission parameters to the alternative preliminary control commands, e) Calculate the emission budget for each operating unit from the status data and the database data, f) Calculate the target emission parameters from the emission budget, g) Selecting the final control command from alternative preliminary control commands by comparing the predictive emission parameters with the target emission parameters, h) Outputting the final control command to the actuator unit and affecting the vehicle state, i) The data management unit writes and / or deletes variable data of the dynamic database module, Includes.

[0112] The description of the operating modes of the vehicle state control system also applies to the method according to the present invention in the corresponding system. The textual marking of the process steps is used for identification and designation purposes and does not specify any particular order. The order of the process steps arises as a result of the accompanying description.

[0113] The process steps are described in detail below.

[0114] a) Write static data as parameterized data to a static database module. In step a), static data is stored in a static database module. This step occurs before the regular operation and needs to be executed only once. The regular operation then begins with step b) below.

[0115] b) Record state data using a state detection unit and provide it for transmission. In this process step, the state detection unit, formed by the traffic condition detection unit, the vehicle state detection unit, and the vehicle subsystem detection unit, records state data such as the location of other road users, vehicle speed, or tire pressure.

[0116] c) The control and evaluation unit acquires state data from the state detection unit and database data from the database unit. In this process step, status data from the status detection unit and database data from the database unit are transmitted to and received by the control and evaluation unit. Therefore, all data is available for evaluation.

[0117] d) The control and evaluation unit provides alternative preliminary control commands and assigns predictive emission parameters to these alternative preliminary control commands. In process step d), the data is evaluated and alternative preliminary control commands are provided. In addition, the emission effects of the control commands in question and the predictive emission parameters derived from them are assigned to those control commands.

[0118] e) Calculate the emission budget for each operating unit from the status data and database data. In this process step, the calculation module of the control and evaluation unit calculates the emissions budget. The emissions budget is the total amount of emissions that are permitted to be emitted for each operating unit. The amount of the emissions budget results from a default value stored in the database unit. This default value can be given, for example, as emissions per kilometer, or it can be optionally adjustable by the driver.

[0119] f) Calculate the target emission parameters from the emission budget. In this step, the emissions budget is allocated to each individual driving event, resulting in the creation of target emissions parameters for each driving event. The target emissions parameters define the maximum emissions for each driving event so that the total emissions do not exceed the emissions budget.

[0120] g) Selecting the final control command from alternative preliminary control commands by comparing the predictive emission parameters with the target emission parameters. Subsequently, in process step g), a control command is selected as the final control command from several alternative preliminary control commands, and the selection is also made based on a comparison of the predicted emission parameters with the target emission parameters. Thus, for example, a control command can be selected as the final command from several possible control commands, and its associated predicted emission parameters, when considered for itself, do not exceed the corresponding target emission parameters. Furthermore, if this is compensated for by one or more other control commands due to their associated emission parameters, and in the case of selecting a control command solely based on an evaluation of each operating event with respect to itself, optimization can also be performed by the comparison means in this process step in such an acceptable manner if the sum of the individual operating dynamics results thus achieved is greater than the sum of the individual operating dynamics results, and its associated predicted emission parameters, when considered for itself, exceed the corresponding target emission parameters.

[0121] h) Outputting the final control command to the actuator unit and affecting the vehicle state. In process step h), the final control command generated by the previous process step is output to the actuator unit. The actuator unit, for example, an electric drive unit in generator mode, here influences changes in the vehicle state, such as deceleration to reduce speed.

[0122] i) The data management unit writes and / or deletes variable data of the dynamic database module. In process step i), variable data is written and / or deleted. This process step provides a particular advantage of the method according to the present invention, as situation-related variable data is also available in addition to static data, and is included in the generation and selection of control commands, which helps to further optimize their emission effects. At the same time, a static database can be eliminated because it is not necessary to store particularly complex characteristic diagrams of emission-related causal relationships, which require a lot of memory capacity and are associated with high data collection costs.

[0123] The textual marking of process steps serves the purpose of designation and does not impose a mandatory order. Regarding order, process steps a) through f) are executed in the order they are displayed, while process step g) is not affected by any specified order.

[0124] In an advantageous further development of the method, process steps a) to i) are first repeatedly performed. Furthermore, this further development includes the following additional process steps: j) Record the actual emission parameters from the final control command already issued in the operating unit, k) Include the actual emission parameters in the emission budget and calculate the remaining emission budget for the remaining operating units, l) Calculate the updated target emissions parameters from the remaining emissions budget, m) Selecting the final control command from alternative preliminary control commands by comparing the predicted emission parameters with the updated target emission parameters, Includes.

[0125] A further advantageous development of the method is characterized by the fact that the newly calculated emissions budget is performed by subtracting the emissions budget already consumed from the initially calculated emissions budget and allocating the resulting remaining emissions budget to the driving events of the remaining driving units. This is based on the fact that control commands should also be selected along with the correspondingly allocated actual emissions parameters, which are not included during the first execution of process steps d) to h) because they are derived from unpredictable state data, particularly unpredictable traffic situation data. Such unpredictable data could be, for example, emergency braking caused by a pedestrian beginning to move onto the road. Conversely, in special cases, for example, when traffic-related slow driving occurs, lower emissions parameters may also be given. In this case, there are emissions credits that can be used for the driving events of the remaining driving units in favor of higher individual driving dynamics results.

[0126] The prescribed additional process steps for further advantageous developments are described in more detail below.

[0127] j) Record the actual emission parameters of the final control command already issued in the operating unit. In process step j), emissions already generated during the operating unit are recorded. According to the present invention, this is done as a particular advantage, not based on true measurements, but on predictive emission parameters assigned to the final control command issued. Thus, the actual emission parameters in the sense of the present invention are understood to be the predictive emission parameters of the control command already executed.

[0128] k) Include the actual emission parameters in the emissions budget and calculate the remaining emissions budget for the remaining operating units. According to process step k), the actual emission parameters are subtracted from the emission budget, resulting in the remaining emission budget available for the remaining operating units. The remaining operating units are the sum of operating events remaining after subtracting the operating events already performed by the operating units. The remaining emission budget is therefore the basis for planned updates, which enables adjustment for unforeseen emission deviations of already performed operating events.

[0129] l) Calculate updated target emissions parameters from the remaining emissions budget. Process step l) primarily corresponds to process step f), but the basis for calculating the target emission parameters here is simply the remaining emission budget. The updated target emission parameters are understood to be those emission parameters, and the basis for their calculation is the remaining emission budget. In all other respects, the content of the description for process step f) applies here in the corresponding manner.

[0130] m) Selecting the final control command from alternative preliminary control commands by comparing the predicted emission parameters with the updated target emission parameters. Process step m) primarily corresponds to process step g), but the comparison performed here is referred to as the predictive emission parameters of the control commands for the remaining operating units, and the updated target emission parameters. In all other respects, the content of the description of process step g) applies here in the corresponding manner.

[0131] Process step h) is described below:

[0132] The present invention is illustrated by the means shown in the following drawings as an exemplary embodiment. [Brief explanation of the drawing]

[0133] [Figure 1] This is a block diagram of the vehicle control system. [Figure 2]This is a block diagram of a vehicle control system that includes a braking system as a vehicle subsystem. [Modes for carrying out the invention]

[0134] The use of reference numerals in the drawings and related explanatory chapters is consistent below, even when not all reference numerals are provided for all drawings.

[0135] Figure 1 shows an exemplary embodiment of the vehicle control system according to the present invention in a block diagram.

[0136] The evaluation unit 3 and the database unit 2 are combined into a single structural unit as the electronic circuitry of a computer having a processor and data memory. Here, static data is stored in the static database module 2.1. Furthermore, the database unit 2 includes a dynamic data management module 2.2. The data management module 2.3 controls both the writing of variable data to the dynamic database module 2.2 and the reading of static data from the static database module 2.1 and variable data from the dynamic database module 2.2, so that the static data and variable data are available as database data for the control and evaluation unit 3.

[0137] In addition, there is a structurally distributed state detection unit 1, which comprises a traffic situation detection unit 1.1, a vehicle state detection unit 1.2, and a vehicle subsystem detection unit 1.3. The state detection unit records other data, such as location or navigation data, as state data, in particular, data on the distance and relative speed to other road users, data on the vehicle's own speed, and data on tire and brake temperatures. The control and evaluation unit 3 receives this state data via a data link.

[0138] Therefore, the control and evaluation unit 3 has both database data and status data in its array for evaluation, for determining the driving events of the driving unit, i.e., the driving route, and providing possible preliminary control commands.

[0139] The control and evaluation unit 3 determines preliminary alternative control commands and assigns to them predictive emission parameters the emission indications that are expected when each control command is executed.

[0140] The control and evaluation unit 3 includes a calculation module 3.1 as a key component. In an exemplary embodiment, the calculation module 3.1 calculates the driving route and the driving events associated with this driving route, starting from a predefined start point and a predefined destination point, based on state data and database data. Furthermore, in the exemplary embodiment, the permissible kilometer-related emissions are stored. Based on the driving route, the emissions budget is calculated and assigned to the driving events, resulting in target emissions parameters that lead to preliminary alternative control commands.

[0141] The control and evaluation unit 3 also includes an assessment module 3.2, which, in comparing predictive emission parameters with target emission parameters, weights the target achievement level with respect to emissions and driving dynamics in an overall assessment of operating events for the operating unit as a whole, so that a final control command can be selected from preliminary control commands and then output. The final control command optimizes different target achievement levels and ensures that the sum of individual emissions for operating events does not exceed the emission budget, and emissions are allocated so that the best possible overall driving dynamics result is achieved.

[0142] The final control command acts on actuator unit 4.

[0143] In addition to the control and evaluation unit 3, the data management module 2.3 is also data-connected to the state detection unit 1, thereby enabling the writing of variables, particularly temporary relevant data from state data, to the dynamic database module 2.2. In this way, data management ensures that an up-to-date stock of such variable data is always available, which may be relevant to providing control commands and output parameters.

[0144] Figure 2 shows a modified exemplary embodiment of the vehicle state control system.

[0145] This primarily corresponds to the exemplary embodiment in Figure 1, as references are made to the content of this explanation.

[0146] The final control command acts on the actuator unit 4, which is designed as part of the braking system 5 in the exemplary embodiment shown in Figure 2. The braking system 5 also represents a vehicle subsystem, and vehicle subsystem status data is recorded from the vehicle subsystem by the vehicle subsystem detection unit 1.3.

[0147] A first exemplary embodiment of the method according to the present invention relates to a cornering driving unit, the cornering driving unit having, for simplicity, straight driving, cornering driving, and then straight driving again as driving events.

[0148] The decisive factor in tire wear is the force acting on it, and this force arises depending on the driving conditions.

[0149] In the case of straight-line driving, the force transmitted between the tires and the road is substantially generated exclusively by acceleration, and acceleration can be acceleration in the narrow sense, or it can be deceleration.

[0150] In the case of cornering, lateral forces are generated by acceleration toward the center, and this acceleration toward the center is influenced by vehicle speed, curve radius, and vehicle mass. Inertial forces are opposite to vehicle acceleration. Depending on the speed specified by the driver, or in the case of automatic or autonomous driving specified by the vehicle, in order for the vehicle to be able to pass through the curve radius, lateral guiding forces should be transmitted through the front and rear wheels, which are then influenced by slip angle, wheel load, friction value, and wheel camber. Increases in tire-related emissions and tire wear ratios are associated with force transmission.

[0151] This clearly shows that as a vehicle accelerates and decelerates more, and as a vehicle takes a curve faster, the force transmitted by the tires and the corresponding wear ratio increase. Exhaust also occurs during hard deceleration, not in the case of acceleration, due to the friction braking action required for this action.

[0152] In process step a), the causal relationships described above are written to the static database module 2.1 of database unit 2 along with other data before the start of the operation, and so they are available for evaluation.

[0153] Further information required for evaluation and decision-making is recorded and made available as state data by the state detection unit 1 in step b). In exemplary embodiments, this is particularly data relating to the characteristics of the curve to be traversed, and the data is obtained as navigation data from map material or route information. In particular, this is information such as the radius of the curve, the maximum permissible speed, and information about the road surface. The vehicle position can be determined via GPS. Information about the tires as a vehicle subsystem is provided, for example, by tire pressure, which is determined by appropriate sensor means in the associated vehicle subsystem detection unit 1.3. Furthermore, information about what is ahead of the vehicle detected by radar can be provided as traffic situation data.

[0154] In process step c), the control and evaluation unit 3 thus receives both database data, particularly causal relationship data, from the database unit 2, and state data from the state detection unit 1.

[0155] Based on this, the control and evaluation unit 3 evaluates and provides alternative preliminary control commands by assigning predictive discharge parameters in process step d). The alternative preliminary control commands are determined in an exemplary embodiment as follows:

[0156] For straight-line driving, moderate acceleration to a moderate speed, maintaining a constant moderate speed, and then moderate deceleration by applying the friction brakes before reaching a curved section are determined as the first possible set of control commands. Higher acceleration to a higher speed, followed by a slight deceleration without friction brake application and without the subsequent stage of maintaining a constant speed, are determined as the second possible set of control commands. Based on database data, estimated emissions are assigned to each of the possible control commands as predictive emission parameters.

[0157] For cornering, the first possible control command is determined to be friction brake application before reaching the curve to reduce speed. The second possible control command is determined to be cornering without a reduction in the previous speed. In the case of the first control command, the predicted particle emissions caused by friction brake and the predicted emissions caused by tire wear at the reduced cornering speed are calculated based on stored causal relationships and assigned to the first control command as predicted emission parameters. In the case of the second control command, particle emissions due to friction brake are omitted, and instead, emissions increase due to tire wear because of the higher cornering speed. This is assigned to the second control command as an emission parameter.

[0158] Furthermore, calculation module 3.1 calculates the emissions budget for the entire operating unit in process step e), which in this exemplary embodiment results in a simplified formula derived from the route length and stored emissions per kilometer. Based on the emissions budget available for all operating events, the allocation to operating events is performed in process step f), and as a result, the target emissions parameters are available.

[0159] The comparison between the determined target emission parameters and the determined predictive emission parameters of the alternative, preliminary control commands results in a determination in step g) of which control commands have relevant predictive emission parameters that do not exceed the target emission parameters.

[0160] In process step g), depending on the results of the comparison of emission parameters, the control and evaluation unit also selects the final control command for both straight driving and cornering from the possible control commands shown.

[0161] Furthermore, in the exemplary embodiment, the driving dynamics parameters are assigned to preliminary alternative control commands during the comparison. Comparisons based on the ratio of emission parameters to driving dynamics parameters are also performed here. The final selection of control commands takes into account which control commands achieve the best overall driving dynamics parameters, and their total predictive emission parameters simultaneously meet the emission budget. Here, individual predictive emission parameters can exceed the corresponding target emission parameter if other predictive emission parameters compensate for this by producing fewer emissions compared to the relevant target emission parameter. For example, higher emissions resulting from high acceleration leading to high driving dynamics can be compensated for by less deceleration over a longer distance without additional braking intervention, and subsequently less emissions resulting from slower cornering, leading to a better overall driving dynamics outcome.

[0162] Furthermore, the final control command selection takes into account, for example, whether the generation of particle emissions due to friction braking is partially, completely, or excessively compensated by lower tire wear emissions. For example, if excessive compensation is realistic, a control command for friction braking to reduce speed is selected as the final control command. Conversely, in the case of partial compensation, the final control command is a control command with no brake application. In the case of full compensation, there is a realistic emissions neutrality among the possible control commands, and therefore the control and evaluation unit also selects a control command with no brake application as the final control command in favor of achieving a better level of target with respect to shorter driving times, i.e., in favor of high driving dynamics. In a modified example of this evaluation, thresholds or characteristic curves are also stored in the assessment module 3.2 to indicate to what extent a slightly increased emissions are acceptable in favor of significantly good driving dynamics when selecting the final control command.

[0163] The final control command is then transmitted to the braking system as a control command in process step h), so that the brake activation event causes a change in the vehicle state through deceleration.

[0164] In this exemplary embodiment, the vehicle speed at which lateral acceleration and tire-related emission rates are correlated is determined in an optimized manner in terms of wear, emissions, and driving dynamics, taking into account the available information. [Explanation of Symbols]

[0165] 1. State detection unit 1.1 Traffic Status Detection Unit 1.2 Vehicle Status Detection Unit 1.3 Vehicle Subsystem Detection Unit 2 Database Units 2.1 Static Database Module 2.2 Dynamic Database Module 2.3 Data Management Module 3. Control and Evaluation Unit 3.1 Computation Module 3.2 Assessment Module 4. Actuator Unit 5. Braking System

Claims

1. A vehicle state control system, It comprises a state detection unit (1), a database unit (2), and a control and evaluation unit (3), The state detection unit (1) is designed to provide state data, which is traffic status data, vehicle status data, or vehicle subsystem data. The state detection unit is, A traffic status detection unit (1.1) designed to record the aforementioned traffic status data and provide it in a manner that can be transmitted, A vehicle state detection unit (1.2) designed to record the aforementioned vehicle state data and provide it in a transmittable format, Includes a vehicle subsystem detection unit (1.3) designed to record and provide the vehicle subsystem data in a manner that allows transmission, The database unit (2) is data-linked to the state detection unit (1) and includes a static database module (2.1), a dynamic database module (2.2), and a data management module (2.3). The static database module (2.1) includes static data relating to causal relationships for emissions not associated with the drivetrain, The dynamic database module (2.2) includes variable data relating to emissions that are not associated with the drivetrain, The data management module (2.3) is designed to write the variable data to or delete the variable data from the dynamic database module (2.2), and in addition, to retrieve the static data from the static database module (2.1) and the variable data from the dynamic database module (2.2), and provide them as database data in a transferable format. The control and evaluation unit (3) is data-linked to the state detection unit (1) and the database unit (2), and is designed to receive state data from the state detection unit (1) and database data from the database unit (2), and to provide alternative preliminary control commands from the state data and the database data, with predictive emission parameters assigned to the alternative preliminary control commands, and the predictive emission parameters representing the predicted emissions resulting from the execution of the alternative preliminary control commands. The control and evaluation unit includes a calculation module (3.1) designed to calculate the emissions budget for an operating unit from the state data and the database data, and to use the emissions budget to determine the target emissions parameters for the alternative preliminary control command. The control and evaluation unit includes an assessment module (3.2) designed to select a final control command from the alternative preliminary control commands by means of comparing the predictive emission parameters with the target emission parameters, the control and evaluation unit is designed to output the final control command to an actuator unit (4), and the vehicle state may be influenced by the actuator unit (4). Vehicle condition control system.

2. The vehicle state control system according to claim 1, characterized in that it is designed as a system in accordance with SAE levels 2 to 5.

3. The vehicle state control system according to any one of claims 1 and 2, characterized in that the vehicle subsystem is a braking system (5) and / or a tire system.

4. The vehicle state control system according to claim 3, characterized in that the vehicle state can be affected as deceleration by the braking system (5).

5. The vehicle state control system according to any one of claims 1 to 4, characterized in that the control and evaluation unit (3) and the database unit (2) form a structural unit.

6. The vehicle status control system according to any one of claims 1 to 5, characterized in that it can write status history data to the dynamic database module (2.2).

7. The vehicle state control system according to any one of claims 1 to 6, wherein the control and evaluation unit (3) is designed to assess the degree of emission relevance of the satisfaction of a previous final control command and to use the state data to update the variable data by means of the data management module (2.3).

8. A road vehicle comprising a vehicle state control system according to any one of claims 1 to 7, and equipped with a friction brake.

9. A method for controlling the state of a vehicle using means of a vehicle state control system according to any one of claims 1 to 7, comprising the following steps: a) Writing static data as parameterization to the static database module (2.1), b) Recording state data by the state detection unit (1) and providing them for transmission, c) The control and evaluation unit (3) acquires state data from the state detection unit (1) and database data from the database unit (2), d) The control and evaluation unit (3) provides alternative preliminary control commands and assigns predictive emission parameters to the alternative preliminary control commands, e) Calculating the emission budget for the operating unit from the state data and the database data, f) Calculating the target emission parameters from the emission budget, g) Selecting a final control command from the alternative preliminary control commands by comparing the predictive emission parameters with the target emission parameters, h) Outputting the final control command to the actuator unit (4) and affecting the vehicle state, i) The data management module (2.3) writes and / or deletes variable data of the dynamic database module (2.2), A vehicle state control method, including the following.

10. This includes repeating the execution of the above process steps a) to i), The following are additional process steps: j) Recording the actual discharge parameters from the final control command already issued in the aforementioned operating unit, k) Calculate the remaining emission budget for the remaining operating units, including the actual emission parameters in the emission budget. l) Calculate the updated target emission parameters from the remaining emission budget, m) Selecting the final control command from the alternative preliminary control command by comparing the predicted emission parameters with the updated target emission parameters, The vehicle state control method according to claim 9, including the method described in claim 9.

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