Methods for optimizing a traction control system, as well as traction control systems

Abstract

A method for optimizing a vehicle traction control system that directs power from an engine and transmission to all four wheels, or only to the front wheels, or only to the rear wheels, wherein the method comprises a controller for the traction control system receiving and evaluating different data to assist in controlling the selective engagement and disengagement of at least one disengaging device or torque transmission clutch for transmitting the drive torque from the powertrain to the secondary drivetrain, wherein the data consists of historical inventory data (I1) transmitted via an air interface, which includes the road inventory; more recent, up-to-date data (I2) transmitted via an air interface, which also includes information on the friction coefficients of the roads; and real-time data (I3) from the vehicle itself.wherein the controller's adaptation is based on the real-time data (I3) alone or on the data transmitted via an air interface (I2, I3), depending on the data situation, wherein the decision (E4) as to which data is used for optimization is made after a plausibility check between the real-time data (I3) and the data transmitted via the air interface (I2, I3).

Description

[0001] The present application relates to a traction control system that is effective in selectively connecting and / or disconnecting powertrain components of an all-wheel / four-wheel drive vehicle based on several environmental conditions or road conditions. The invention further relates to a method for optimizing a traction control system. State of the art

[0002] Many modern motor vehicles are equipped with torque transmission systems designed to normally transmit drive torque from a powertrain to a set of primary wheels, and which can selectively or automatically transmit a portion of the drive torque from the powertrain to a set of secondary wheels. Such torque transmission systems, usually referred to as four-wheel drive or all-wheel drive, can be based on either a front-wheel drive (FWD) or rear-wheel drive (RWD) vehicle architecture.In many vehicles, the torque transmission system primarily operates in two-wheel drive (2WD) mode when normally driving the primary wheels, while the secondary wheels are selectively connected to the drivetrain to form four-wheel drive (4WD) or all-wheel drive (AWD) modes only when improved traction is required. When operating in 2WD mode, the secondary wheels are typically disconnected from the drivetrain to maximize fuel economy. Various disconnection systems for selectively and / or automatically disconnecting the secondary wheels and / or connecting the secondary drivetrain components are known in both conventional front-wheel drive (FWD) and rear-wheel drive (RWD) vehicle architectures.In addition to the need to switch between 2WD and 4WD / AWD modes for improved traction and fuel economy, a challenge arises with the time required to switch from 2WD to 4WD / AWD when conditions warranting enhanced traction control are detected. For example, an undesirable time delay may be necessary to synchronize and engage the secondary drivetrain components with the powertrain while the vehicle is operating under wheel slip conditions. This stems from the fact that many modern torque transfer systems operate based on their response to wheel slip detection.Accordingly, current technology requires 4WD / AWD torque transmission systems that are designed and effective to be switched to 4WD / AWD mode preventively before wheel slip occurs.

[0003] US 2010 / 0 094 519 A1, EP 2 562 025 A1 and EP 2 353 918 A1 each show a drive system with the ability to switch between two-wheel drive and four-wheel drive as required.

[0004] In the solution according to US 2010 / 0 094 519 A1, EP 2 562 025 A1 and EP 2 353 918 A1, rotation sensors are the input information for a control unit that instructs the switching between the two driving modes.

[0005] DE 10 2008 044 791 A1 deals with the control of a switchable 2 / 4-wheel drive system that includes both an automatic component and a manual switching function operated by the driver. The system first queries the settings made by the driver before querying further conditions for automatic switching.

[0006] In automatic operation - when, after a specified time period and / or a specified distance, the system considers four-wheel drive unnecessary - the system control unit sends a signal to the vehicle operator that the four-wheel drive should be switched off in order to save fuel.

[0007] DE 101 38 168 A1 shows a control system for a 2W / 4W vehicle that uses cameras to detect the road and its condition and processes the data in several control units. Various sensor data are evaluated simultaneously.

[0008] DE 10 2014 213 663 A1 discloses a method for controlling a traction control system in a motor vehicle using information from a variety of vehicle operating conditions, road conditions and weather conditions. The method for controlling a vehicle traction control system uses optical information from a camera system, which may include an onboard camera and image processing unit, to assist in controlling torque transmission between a drive unit and the first and second drive trains. This optical information can be used to identify road surface materials, road structures, and road markings, as well as the position, speed, number, and / or distance of other vehicles. The optical information generated by the camera system is combined with other data provided via the vehicle's communication network to optimize the performance of the 2WD / 4WD / AWD shift control logic. Based on the analysis of this optical information, the drivetrain is proactively switched from 2WD to 4WD / AWD mode before wheel slippage occurs.

[0009] DE 10 2015 216 483 A1 describes a method for operating a friction coefficient database from vehicle data and making the plausible data available to requesting vehicles.

[0010] The object of the invention is to provide a method for optimizing a traction control system, which is improved by additional data and its processing. Brief description

[0011] The problem is solved by a method for optimizing a vehicle's traction control system that directs power from an engine and transmission to all four wheels, or only to the front wheels, or only to the rear wheels, wherein the method comprises a controller for the traction control system receiving and evaluating different data, wherein the data consists of historical inventory data transmitted via an air interface, more recent daily data transmitted via an air interface, and real-time data from the vehicle itself, wherein the controller adapts depending on the data situation, either based on the real-time data alone or on the basis of the data transmitted via an air interface.

[0012] By using data of varying ages, it is possible to obtain an optimized dataset that allows for the optimization of the traction control system. This enables the traction control system to make better decisions about when to engage all-wheel drive and also to disengage it more quickly. A positive match of the data is used to determine the To optimally guide vehicle assistance systems for their decision-making steps in the near future, up to the physical limits of the vehicle, in order to keep the safety area of ​​the vehicle assistance systems as small as possible and to influence the driver as little as possible.

[0013] It is an advantage that the decision as to which data is used for optimization is made after a plausibility check between the real-time data and the data transmitted via the air interface.

[0014] Another advantage is that before deciding which data to use for optimization, a decision is made regarding the vehicle's position, followed by a decision on whether inventory data and up-to-date data are available, and then a decision on whether the available data is sufficient.

[0015] Any negative decision leads to a restart of the process.

[0016] To carry out the procedure, the information flow from the vehicle to a data source in the network consists of feedback on faulty or missing data, as well as real-time data from the vehicle.

[0017] The task is also solved with a traction control system for a vehicle that directs power from an engine and transmission to all four wheels, or only to the front wheels, or only to the rear wheels, with the procedure running as software on one or more controllers in the vehicle. Description of the embodiment Fig. Figure 1 shows a flowchart of a procedure for adapting the control system of an all-wheel drive vehicle, Fig. Figure 2 shows a timeline for data.

[0018] In general, the present invention relates to a method and a separation system within the drive train of a four-wheel drive (4WD) or all-wheel drive (AWD) motor vehicle, wherein an automatic separation control strategy is used as a method for selectively connecting and disconnecting a secondary drive train with / from a drive unit.

[0019] Different data are used in the process for optimizing the traction control system to control the selective engagement and disengagement of at least one separating device or Torque transmission coupling to support the transmission of drive torque from the drive unit to the secondary drive train.

[0020] The inventive method according to Fig. 1. Runs on a suitable controller as a pure software implementation. The controller is either It can be built as a single or distributed control module, or integrated into other functions and controller hardware, or installed in the vehicle as a pure software module.

[0021] Starting from the start S1 of the procedure, the software checks in a first step Step down whether the vehicle's position, measured by GPS data, is available.

[0022] Decision E1 regarding the availability of position data results in a return to the start if the vehicle's position is not available. If the data is positive, the control system retrieves data from a network data source, pre-selecting this data based on the detected position. This involves accessing information 11, which contains the road inventory, The road quality, for example, whether the current location is on an asphalt road or a gravel path. Data about the immediate surroundings of the current location can also be transmitted here. For this purpose, a radius around defines the current position.

[0023] These inventory data (11) are data that were collected and stored a long time ago, years or months ago. They contain information from map materials that are already quite old.

[0024] The inventory data I1 is still valuable because its contents do not normally change quickly. Nevertheless, factually incorrect data can be transmitted if, for example, asphalt has been removed due to road construction work, or similar events.

[0025] In step S3, the traction control system controller retrieves additional data, specifically information I2. This data provides insights into current events, such as weather data. Information on road friction coefficients is also retrieved. This data is stored, for example, in a friction coefficient database populated by other vehicles that have passed the vehicle's current position in the preceding hours and minutes. The time of data acquisition by these other vehicles is also queried to contextualize the data.

[0026] This up-to-date data I2 is not as old as the inventory data I1, but it is also not real-time data.

[0027] Decision E2 checks whether data could be downloaded from the network. If the decision is negative, the process reverts to the start S1.

[0028] If the decision is positive, meaning that data from the data source is available via the network, the process jumps to the next decision, E3. At this point, it is checked whether the available data is sufficient for the next step.

[0029] In this context, "sufficient" means that all parameters necessary for further data processing are present. If this is not the case, decision E3 triggers a measurement step S4, which, via step S5, sends feedback to the data source in the network and initiates a request to fill the data gap. The process then returns to start S1. If all data is available after decision E3, the plausibility of the data is checked in decision E4. Real-time information I3 from the vehicle is used for this purpose. Real-time data (RTD) is data that, after being recorded, is evaluated and processed with as little delay as possible. This includes data collected in the vehicle, such as data from a camera system for measurements in the visible light spectrum, or measurements from infrared or lidar systems. This data is used for comparison, analysis, or calculations to determine specific road conditions.

[0030] The real-time data also includes measurements and the recording of current vehicle slip data. Various wheel slip measurements, as known from the state of the art, are used. Further sensor data from the vehicle are also collected and processed in real time and made available to the process for optimizing the traction control system. At the same time, the vehicle's real-time data is also sent to the data source in the network for storage in the database in step S6, so that subsequent vehicles can benefit from the data.

[0031] Plausibility checking is a method used to roughly assess whether a value or result is plausible—that is, acceptable, logical, and comprehensible. It cannot always verify the correctness of the value or result; rather, it aims to identify any obvious inaccuracies. One advantage of plausibility checks is their low complexity; a disadvantage is that they may miss less obvious inaccuracies.

[0032] Assuming the current data I2 indicates a smooth surface, but the vehicle's temperature sensors show a positive temperature, the result is implausible. In this case, the controller is adjusted in step S7 solely based on the vehicle's real-time data I3.

[0033] In step S9, the data source in the network is informed about the deviation and the result. If the plausibility check in E4 is successfully completed, the data, namely the inventory data I1 and the daily updated data I2 from the network data source, are used to optimize the controller in step S8.

[0034] In Fig. Figure 2 shows on a timeline that the inventory data I1 originates from a period around t2 that lies back from the current time t0. The daily data I2 is significantly closer in time to the current time t0 at t1. A positive comparison of the data in the plausibility check stage is used to optimally guide vehicle assistance systems for their decision steps in the near future, up to the physical limits of the vehicle, in order to keep the safety area of ​​the vehicle assistance systems as small as possible and to influence the driver as little as possible. The term "near future" refers to the period until the next data collection and comparison. A vehicle assistance system can therefore provide a preview of the future to optimize vehicle control. The analysis of various data sets from the past and present also offers advantages for autonomous driving. QUOTES INCLUDED IN THE DESCRIPTION

[0000] This list of documents cited by the applicant was automatically generated and is included solely for the reader's convenience. The list is not part of the German patent or utility model application. The DPMA accepts no liability for any errors or omissions. Cited patent literature

[0000] US 2010 / 0094519 A1 [0003, 0004] EP 2562025 A1 [0003, 0004] EP 2353918 A1 [0003, 0004] DE 102008044791 A1

[0005] DE 10138168 A1

[0007] DE 102014213663 A1

[0008] DE 102015216483 A1

[0009]

Claims

[1] Method for optimising a traction control system of a vehicle which directs power from an engine and a transmission to all four wheels or only to the front wheels or only to the rear wheels, the method comprising a controller for the traction control system receiving and evaluating different data, the data consisting of inventory data (I1) transmitted over an air interface from a long time ago, current data (I2) transmitted over an air interface which is more recent in time and is real-time data (I3) of the vehicle itself, the adaptation of the controller being carried out on the basis of the real-time data (I3) alone or on the basis of the data (I2, I3) transmitted over an air interface, depending on the data situation. [2] Method according to claim 1, characterized bythat the decision (E4) as to which data is used for optimization is made after a plausibility check between the real-time data (I3) and the data transmitted via the air interface (I2, I3). [3] Method according to claim 2, characterized by that a positive comparison of the data is used to optimally guide vehicle assistance systems for their decision-making steps in the near future up to the physical limits of the vehicle in order to keep the safety area of ​​the vehicle assistance systems as small as possible and to influence the driver as little as possible. [4] Method according to claim 1 or 2, characterized bythat before the decision (E4) as to which data is to be used for optimization, a decision (E1) is made to determine the position of the vehicle, then a decision (E2) as to whether inventory data (I1) and daily updated data (I2) are available, then a decision (E3) as to whether the available data is sufficient. [5] Method according to one of the preceding claims, characterized by that any negative decision will result in a restart of the procedure. [6] Method according to one of the preceding claims, characterized by that the information flow from the vehicle to a data source in the network consists of feedback on incorrect or missing data, as well as real-time data from the vehicle. [7] A traction control system for a vehicle which directs power from an engine and a transmission to all four wheels or only to front wheels or only to rear wheels, the method being executed as software on one or more controllers in the vehicle and the method comprising the steps of any one of claims 1 to 6.

Images