CONTROL UNIT FOR A VEHICLE SYSTEM

Abstract

Control unit for estimating the traction of a vehicle, comprising the following: a monitoring module that monitors wheel torque values; a determination module for determining maximum torque values ​​by obtaining and storing empirical data while driving on a surface, wherein the maximum torque values ​​are the wheel torque values ​​immediately before wheel slippage; a prediction module that predicts a traction threshold based on the maximum torque values, where the traction threshold is based on a stochastic model of the maximum torque values; and a control module that outputs a signal indicating the traction threshold.

Description

TECHNICAL AREA

[0001] The present disclosure relates to a control unit for a vehicle system and a method for operating the same, in particular, but not exclusively, a control unit and a method for estimating the traction of a vehicle. Another aspect of the invention relates to a vehicle comprising the control unit and methods. STATE OF THE ART

[0002] A vehicle comprises an engine coupled to a transmission system, which in turn is coupled via a driveshaft to two or four driven wheels. Power and torque from the engine are transmitted to each of the driven wheels via the transmission system and the driveshaft. In the case of an electric vehicle (EV), motors are located at the wheels for propulsion.

[0003] Depending on the terrain, the high torque of the driven wheels can exceed the surface's capacity. In such cases, the driven wheels spin on the surface. A particular problem arises on low-friction surfaces, such as wet grass, where wheel slippage can damage the surface and cause the wheel to lose traction.

[0004] Generally, when wheel slip events are detected, a vehicle reacts by implementing one or more strategies, such as applying braking force, reducing throttle, or changing the engine response profile. These control reactions are reactive and occur for a limited time. These reactions may need to be repeated. Repeating wheel slip events and vehicle reaction patterns does not yield satisfactory results, as further wheel slip events and damage to the surface on which the vehicle is driven are inevitable.

[0005] DE 10 2010 015 953 A1 relates to a system and a method for detecting the possible presence of slippage between a vehicle tire and a road surface. JP 2009 - 80 659 A relates to a driving assistance system.

[0006] It is an object of the present invention to further improve this state of the art. BRIEF SUMMARY OF THE INVENTION

[0007] According to one aspect of the present invention, a control unit for estimating the traction of a vehicle is provided, comprising: a monitoring module that monitors wheel torque values; a determination module for determining maximum torque values ​​by obtaining and storing empirical data while driving on a surface, wherein the maximum torque values ​​are the wheel torque values ​​immediately before wheel slip; a prediction module that predicts a traction threshold based on the maximum torque values; and a control module that outputs a signal indicating the traction threshold.

[0008] In this way, the vehicle is able to detect impending wheel slip by monitoring the maximum torque values ​​collected on a surface while driving and predicting a traction threshold. It can then issue a traction control signal before wheel slip occurs, thus communicating traction and / or torque requirements accordingly, rather than communicating a request for traction and / or torque after wheel slip has already occurred. This proactive approach to preventing wheel slip is a better solution than a reactive approach after a wheel slip event, as it prevents damage to the surface on which the vehicle is operating, which is likely to occur once wheel slip has already taken place.A completely intact driving surface would mean that further wheel slip events are less likely to occur, thus preventing damage to the surface and a vehicle from getting into more extreme conditions.

[0009] The prediction module that forecasts the traction threshold can include calculating the probability of wheel slip using a parameter model of this empirical data. This approach incorporates historical data and a past record of torque detection and monitoring for improved accuracy. A probabilistic model can also use parameters depending on available data, making the model more robust.

[0010] The control module can issue a signal indicating a traction request in response to a current torque value exceeding the traction threshold. This allows the vehicle to detect impending wheel slip by monitoring whether the current torque value exceeds a predicted traction threshold and request traction and / or torque accordingly, rather than requesting traction and / or torque after wheel slip has occurred. This proactive approach to preventing wheel slip is superior to a reactive approach after a wheel slip event, as it prevents damage to the surface on which the vehicle operates, which is likely to occur once wheel slip has taken place.A completely intact driving surface would mean that further wheel slip events are less likely to occur, thus preventing damage to the surface and a vehicle from getting into more extreme conditions.

[0011] The traction request can be issued to a traction control system (TCS).

[0012] The control unit can include a vehicle display.

[0013] The vehicle display allows the driver to receive a warning that the predicted traction threshold has been exceeded, enabling them to react to excessive vehicle torque and prevent wheel slip events.

[0014] The monitoring module can monitor one or more vehicle conditions. The determination module can determine one or more maximum torque values ​​associated with each vehicle condition.

[0015] The vehicle condition can be selected from the following list: time, date, weather, distance traveled, vehicle position, dynamic or static state of the vehicle, vehicle altitude, vehicle speed, and duration of time spent at a current position. The vehicle condition can also be a vehicle configuration, such as a current vehicle setting, a vehicle state, or any factors that could influence the vehicle configuration and / or state, such as environmental conditions.

[0016] The vehicle itself, and the surface on which it operates, can change due to any of the aforementioned conditions. For example, the surface on which the vehicle operates changes depending on the vehicle's position. The vehicle may be in one position on different terrain with different surface types than in another position. For example, the vehicle may be in one position on grass and then move to another on asphalt (road). Terrain can be identified as grass, gravel, snow, ice, sand, rock, mud, or dirt track. The vehicle may be on the same terrain but in positions with varying degrees of slip resistance. In another example, the time of day, the date, or the weather can affect the surface on which the vehicle operates and consequently change the vehicle's condition.By predicting the traction threshold for a specific condition, the vehicle can be designed to reduce or prevent wheel slip. In this way, wheel slip is less likely to occur than if a single traction threshold were applied to all vehicle conditions.

[0017] The prediction module can predict the traction threshold based on one or more maximum torque values ​​corresponding to a predefined range of vehicle conditions. For example, where the vehicle condition is position, the traction threshold is based on one or more maximum torque values ​​corresponding to a predefined range of positions.

[0018] The specified range of each vehicle condition can be determined based on the current vehicle condition.

[0019] Basing the traction threshold on a range of vehicle conditions based on the current vehicle condition is more advantageous than basing the traction threshold on every possible vehicle condition, including anomalies such as extreme conditions that could distort the traction threshold. Determining the traction threshold in this way further improves the system's reliability in preventing wheel slip events. For example, where the vehicle condition is a distance the vehicle has traveled or the time it takes to reach the current vehicle position, having a range of traction thresholds eliminates or minimizes anomalies resulting from distance-based surface changes.

[0020] The prediction module can update the traction threshold in response to monitoring maximum torque values ​​of the system during its use.

[0021] Updating the traction threshold while the system is in use provides a degree of feedback to optimize the traction threshold generated by the system, thus making the traction request more reliable.

[0022] The traction threshold can be based on a stochastic model of the maximum torque values.

[0023] The traction threshold can be less than or equal to a predetermined percentage of maximum torque values.

[0024] Setting the transaction threshold to less than or equal to a predefined percentage of a vehicle's maximum torque values ​​allows the system to filter out anomalies. These anomalies can be generated by one or more sensors while they are in operation. The predefined percentage can be set according to any desired confidence level specified by the vehicle's designer. A higher percentage results in increased confidence that no wheel slip is occurring.

[0025] The specified percentage of maximum torque values ​​can be 95%.

[0026] The fact that the specified percentage of maximum torque values ​​is 95% means that all but the most extreme anomalies have been taken into account when predicting the traction threshold.

[0027] The prediction module can generate a prediction band based on a regression model. The prediction band can have a minimum and a maximum prediction value for each condition. The traction threshold can be less than or equal to the minimum threshold.

[0028] If the traction threshold is lower than the minimum threshold, this results, based on past occurrences of wheel slip, in a specifically chosen degree of certainty that no wheel slip will occur.

[0029] The regression model can be set up to extrapolate the prediction band to conditions outside the range of recorded conditions.

[0030] Extrapolating the prediction bands means that the model can be used for vehicle conditions outside the range of conditions in which the vehicle has operated in the past. For example, maximum torque values ​​of a vehicle operating in relatively light rain when wheel slip occurs can be used to predict the traction threshold for heavier rain at the same location.

[0031] The signal indicating the traction threshold can be sent to a human-machine interface (HMI), and the feedback includes one or more of the following: visual output, audible output, and / or haptic output. In this way, the vehicle provides feedback to its operator, a driver, enabling the driver to make an informed decision about how to operate the vehicle to avoid wheel slip and ensure smooth operation.

[0032] The signal indicating the traction threshold can be sent to a vehicle control unit, and the feedback includes a reduction in engine power and / or a modification of the accelerator pedal map. In this way, the signal indicating the traction threshold and / or the traction requirement can be communicated directly to the relevant vehicle system(s), causing the vehicle to automatically change its settings.

[0033] The control unit can send and / or receive data; the data can be selected from the following list: torque, maximum torque value and vehicle condition.

[0034] The communication module allows the control unit to receive data from other locations, such as a central storage device, or to send data to other locations, thus creating a more robust model. The communication module can be configured to send and / or receive data to other vehicles and / or a storage device.

[0035] In cases where data is sent to and received from other vehicles, such an arrangement enables better modeling, as vehicles can learn from the received data analyzed by the control units of a fleet of vehicles. Alternatively, it may be advantageous for the memory to depend on the available hardware and the communication protocol used by the control unit and / or the communication module.

[0036] According to another aspect of the present invention, a vehicle is provided which includes the control unit according to a preceding claim.

[0037] According to a further aspect of the present invention, a method for estimating the traction of a vehicle is provided, comprising: monitoring torque values; determining a maximum torque value by obtaining and storing empirical data while driving on a surface, wherein the maximum torque values ​​are the wheel torque values ​​immediately before wheel slip; predicting a traction threshold value based on the maximum torque value; and outputting a signal indicating the traction threshold value.

[0038] The procedure may include predicting the traction threshold by calculating the probability of wheel slip using a parameter model of the empirical data.

[0039] The procedure may include outputting a signal indicating the traction requirement in response to a current torque value exceeding the traction threshold.

[0040] The procedure may involve monitoring one or more vehicle conditions and determining one or more maximum torque values ​​associated with each vehicle condition.

[0041] The vehicle condition can be selected from the following list: time, date, weather, distance traveled by the vehicle, vehicle position, dynamic or static state of the vehicle, vehicle altitude, vehicle speed, and duration for which the vehicle is at the current position.

[0042] The procedure may include predicting the traction threshold based on one or more maximum torque values ​​corresponding to a predetermined range of the vehicle condition.

[0043] The specified range of each vehicle condition can be determined based on the current vehicle condition.

[0044] The procedure may include updating the traction threshold in response to monitoring maximum torque values ​​of the system during its use.

[0045] Predicting the traction threshold can involve calculating the traction threshold such that it is less than or equal to a given percentage of maximum torque values.

[0046] The specified percentage can be adjusted. The specified percentage can be 95%.

[0047] The procedure may include: generating a prediction band based on a regression model, wherein the prediction band has a minimum prediction value and a maximum prediction value for each condition; and determining the traction threshold such that it is less than or equal to the minimum threshold(s).

[0048] The procedure may involve extrapolating the prediction band to conditions outside the range of conditions used to build the regression model.

[0049] The procedure may involve sending and / or receiving data to / from other vehicle(s) and / or a memory device. The data may be selected from the following list: torque, maximum torque value, and vehicle condition.

[0050] According to a further aspect of the present invention, a control unit for the above-described purpose is provided, wherein: the means for receiving one or more signals, each indicating a wheel torque value, comprises: an electronic processor having an electrical input for receiving the one or more signals, each indicating a wheel torque value; and an electronic storage device electrically coupled to the electronic processor and containing instructions, the means for determining—based on the wheel torque value(s)—that the vehicle is in a state immediately before wheel slippage, and the means for estimating traction by monitoring wheel torque values;Determining maximum torque values ​​by acquiring and storing empirical data during driving on a surface, wherein the maximum torque values ​​are the wheel torque values ​​immediately before wheel slip; and including predictions of a traction threshold based on the maximum torque values, the processor being configured to access the memory device and execute the instructions stored therein, so that it is operational to detect, based on the wheel torque value(s), that the vehicle is in a state immediately before wheel slip; and to command the output of a signal indicating the traction threshold.

[0051] According to a further aspect of the present invention, a non-volatile, computer-readable medium is provided which tangibly embodies computer-executable instructions for operating a motor vehicle control unit, wherein the instructions are executable by a vehicle processor to provide operations that include: monitoring torque values; determining a maximum torque value by obtaining and storing empirical data while driving on a surface, wherein the maximum torque values ​​are the wheel torque values ​​immediately before wheel slip; predicting a traction threshold value based on the maximum torque value; and outputting a signal indicating the traction threshold value.

[0052] Within the scope of this application, it is expressly intended that the various aspects, embodiments, examples, and alternatives set forth in the preceding paragraphs, in the claims, and / or in the following description and drawings, and in particular their individual features, may be considered independently of one another or in any combination. Features described in connection with one embodiment apply to all embodiments, unless these features are incompatible. This means that all embodiments and / or features of any embodiment may be combined in any way and / or in any combination, provided that these features are not incompatible.The applicant reserves the right to amend any originally filed patent claim or to file any new patent claim accordingly, including the right to amend any originally filed patent claim to depend on and / or incorporate any feature of any other claim, even if it has not previously been claimed in this manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] One or more embodiments of the invention are now described by way of example only, with reference to the accompanying drawings, wherein: Fig. 1A shows a schematic representation of a vehicle comprising a control unit according to an embodiment of the present invention; Fig. 1B shows a schematic representation of a vehicle comprising a control unit according to another embodiment of the invention; Fig. 1C a very schematic diagram of a vehicle's speed control system Fig. 1A is; Fig. 2 a block diagram of the control unit of Fig. 1A and / or Fig. 1B shows; Fig. 3 a block diagram of an alternative embodiment of the system of Fig. 2 shows; Fig. 4 a graphical representation of a method for predicting a transaction threshold using the control unit of Fig. 2 shows; Fig. 5 a graphical representation of an alternative method for determining the transaction threshold using the control unit of Fig. 2 shows; Fig. 6 a graphical representation of a procedure for updating the transaction threshold of Fig. 4, while the control unit is in use; Fig. 7 shows a flowchart of a procedure that is carried out by the control unit of the Fig. 1A and Fig. 1B is used; and Fig. Figure 8 shows a graphic representation of a vehicle which has the control unit of Fig. 1A or Fig. 1B includes. DETAILED DESCRIPTION

[0054] With reference to Fig. 1A comprises a vehicle 10 and a chassis 12 for carrying various components. The vehicle 10 is designed for off-road use, i.e., use on terrain other than normal asphalt roads, as well as on paved roads. The various components mounted on the chassis 12 include an engine 14, a transmission 16, a transfer case 18, a driveshaft 22, a front drive unit (FDU) 24, a front drive shaft 26, a rear drive unit (RDU) 30, and a rear drive shaft 28. The front drive shaft 26 and the rear drive shaft 28 are subdivided into a front driver-side drive shaft 32, a front passenger-side drive shaft 34, a rear driver-side drive shaft 36, and a rear passenger-side drive shaft 38. Each of the aforementioned drive shafts 32, 34, 36, 38 is connected to a wheel.Accordingly, there are four wheels, specifically a front driver's side wheel 40, a front passenger's side wheel 42, a rear driver's side wheel 44 and a rear passenger's side wheel 46.

[0055] Wheels 40, 42, 44, and 46 each have a corresponding brake 40B, 42B, 44B, and 46B, respectively. Each wheel 40, 42, 44, and 46 of vehicle 10 is assigned a corresponding speed sensor 40S, 42S, 44S, and 46S. The sensors 40S, 42S, 44S, and 46S are mounted on a chassis 12 of vehicle 10 and are configured to measure the rotational speed of the corresponding wheel.

[0056] A control system for the vehicle includes a central control unit 610 ( Fig. 1B), which is referred to as the vehicle control unit (VCU) 610, the powertrain control unit 611 and a brake control unit 613 ( Fig. 1C). The brake control unit is an anti-lock braking system (ABS) control unit 613 and forms part of a brake system 622 ( Fig. 1B). The VCU 610 receives and outputs several signals from various sensors and subsystems provided on the vehicle 10 (not shown). The VCU 610 includes a low-speed progress (LSP) control system 612, which is located in Fig. Figure 1C shows a stability control system (SCS) 614S, a traction control system (TCS) 78, an adaptive cruise control system (ACC) 616, and a hill descent control (HDC) system 612HD. The SCS 614S improves the stability of the vehicle 10 by detecting and counteracting a loss of traction. If excessive wheel rotation is detected, the TCS 78 is designed to reduce the wheel rotation by applying a braking force in combination with a reduction in the drivetrain torque. In the embodiment shown, the SCS 614S and the TCS 78 are implemented by the VCU 610. In some alternative embodiments, the SCS 614S and / or the TCS 78 may be implemented by the brake control unit 613. Alternatively, the SCS 614S and / or the TCS 78 can be implemented by separate control units.

[0057] With reference to Fig. 2 The traction estimation control unit 60 comprises a monitoring module 66, a determination module 68, a prediction module 70, and a control module 72, all of which are provided as electronic data on a non-volatile memory component of a computer unit. The computer unit also includes a processor for executing each of the aforementioned modules 66, 68, 70, and 72. In one embodiment, these modules are arranged in series such that the monitoring module 66 is connected to the determination module 68, which is connected to the prediction module 70, which is connected to the control module 72.

[0058] In the event of a wheel slip event, the SCS 614S, the TCS 78, the ABS control unit 613, and the HDC system 612HD provide outputs indicating, for example, SCS activity, TCS activity, ABS activity, individual wheel brake interventions, and engine torque requests from the VCU 610 to the motor 14. Each of these events indicates that a wheel slip event has occurred. Other vehicle subsystems, such as a roll stability control system, may also be present.

[0059] In the present embodiment, the wheel speed signals are generated by the wheel speed sensors 40S, 42S, 44S, 46S assigned to the respective wheels of the vehicle 10. The wheel speed signals received by the ABS control unit 613 are compared with a vehicle reference speed value, which corresponds to the actual speed of the vehicle 10 over the ground. Thus, the degree of slip of a given wheel is defined as the difference between the speed of a given wheel 40, 42, 44, 46 and the vehicle reference speed value. The ABS control unit 613 is configured to estimate the value of the surface friction, at least partially, based on measurements of the wheel slip for a given amount of torque applied to a wheel.

[0060] In response to the surface friction signal, the engine control unit is configured to determine the amount of torque that can be applied to a drive wheel of the vehicle 10 before the drive wheel slip exceeds a prescribed slip value. In the present embodiment, the prescribed slip value is determined taking into account a vehicle reference speed value. That is, the prescribed slip value is dependent on the vehicle speed and typically increases with vehicle speed, although other arrangements are also suitable.

[0061] The amount of torque is determined by the engine control unit (ECU) by referring to a look-up table (LUT) that provides torque values ​​related to the prescribed slip. In some embodiments, the ECU also obtains the prescribed slip value taking into account the driving mode in which the vehicle is operated. In some driving modes, greater amounts of slip are permitted for a given vehicle speed than in other driving modes, and the ECU is designed to consider this when determining the prescribed slip value.In some embodiments, the engine control unit also takes into account a measure of weight acting on each drive wheel or on each axle supplying drive torque for propelling the vehicle 10 when calculating the measure of torque with which a given wheel or axle 26, 28 must be applied to produce the prescribed measure of slip for that wheel or axle. This is because the measure of torque that can be applied to a wheel typically increases with increasing weight on a wheel for a given value of a surface μ. The weight acting on each wheel or axle 26, 28 can be determined by using information specifying a weight distribution between the front and rear axles 26, 28.After determining an estimated value of the amount of torque required to cause a given drive wheel 40, 42, 44, 46 to have the prescribed amount of slip, the engine control unit calculates a specific amount of torque that the engine 14 must generate to deliver the calculated amount of torque at a given drive wheel 40, 42, 44, 46 or axle 26, 28 in the current configuration of the power transmission system. Therefore, the amount of torque at a given drive wheel is calculated by the engine control unit or by a brake control unit, such as an ABS control unit.

[0062] In another embodiment, the transmission can obtain an accurate torque prediction for internal components by taking the predicted incoming motor torque and then considering the gear ratio and transmission loss to predict the transmission output. It is then possible to calculate the torque at the wheel using this output and a differential ratio.

[0063] In yet another embodiment, each of the front driver-side, front passenger-side, rear driver-side and rear passenger-side drive shafts 32, 34, 36, 38 comprises a torque sensor, as shown in Fig. Figure 1B shows the following: Specifically, there is a front driver-side torque sensor 50, a front passenger-side torque sensor 52, a rear driver-side torque sensor 54, and a rear passenger-side torque sensor 56. Each of the torque sensors 50, 52, 54, and 56 is connected to a control unit, in the form of a traction estimator 60. The traction control unit 60 is connected via a network, such as CAN or FlexRay, to a human-machine interface (HMI) 64, which includes a display. The HMI 64 is installed on a dashboard (not shown) of the vehicle 10. These torque sensors 50, 52, 54, and 56 measure the amount of torque at each wheel 40, 42, 44, and 46, respectively.

[0064] The monitoring module 66 includes an input function for receiving signals from the engine control unit and / or brake control unit, such as the ABS control unit 613. In another embodiment, the monitoring module 66 receives signals from the torque sensor(s) 50, 52, 54, 56. In this way, the monitoring module 66 is configured to monitor torque values, specifically torque values ​​assigned to the wheels 40, 42, 44, 46.

[0065] The input function of the monitoring module 66 is also configured to receive various inputs relating to vehicle conditions from other sensors 74 and modules. These vehicle conditions include time, date, weather, distance traveled by the vehicle, vehicle position, dynamic or static state of the vehicle, vehicle altitude, vehicle speed, and time spent at the current position. The monitoring module 66 is thus configured to monitor one or more of these vehicle conditions.

[0066] The functionality of the determination module 68, the prediction module 70, and the control module 72 are described in more detail below. In summary, however, the determination module 68 is configured to determine a "maximum torque value." The maximum torque value corresponds to the torque value calculated for each wheel immediately before wheel slip occurs. In another embodiment, the maximum torque value corresponds to the torque value detected by a given torque sensor 50, 52, 54, 56 immediately before wheel slip occurs. The torque value immediately before wheel slip is therefore used as the "maximum torque value" because the occurrence of wheel slip is inherently accompanied by a reduction in torque.

[0067] Prediction module 70 is then configured to predict a traction threshold based on the maximum torque value. The traction threshold involves calculating the probability of wheel slip using a parameter model of the empirical data. The traction threshold is a torque value below which there is an inherent degree of confidence that no wheel slip will occur.

[0068] In statistics, a parametric model is a family of distributions that can be described using a finite number of parameters. These parameters are usually collected to form a single k-dimensional parameter vector θ = (θ1, θ2, ..., θk). The "traction threshold" could be based on the maximum value collected in such a parametric model collection.

[0069] The control module 72 then outputs a signal indicating the traction threshold and / or a "traction request" 76 in response to a current torque value estimated by an engine control unit and / or a brake control unit, such as the ABS control unit 613. In another embodiment, a sensor 50, 52, 54, 56 detects that the current torque value exceeds the "traction threshold." The signal indicating the "traction request" 76 is output to a vehicle communication network, such as CAN or FlexRay.

[0070] The traction control system 78 is not included in the definition of the traction system 60, but rather is a different system within the same vehicle 10. This invention is part of the VCU 610 and could be separate from or part of subsystems of the VCU. For example, the control unit 60 can be part of the TCS 78, the ABS 613, or the SCS 614S.

[0071] The signal indicating the traction request is sent to a specific system within the vehicle to provide direct feedback to the driver. This feedback can be haptic, audible, or visual. For example, at least one of the following may be present: an audible tone, a visual indication on an HMI 64 display, or haptic feedback via a pedal or steering wheel. This is not an exhaustive list, and other types or combinations of feedback may be provided to the driver.

[0072] In one embodiment, the HMI 64 is configured to display a warning to the driver with a visual cue, indicating "Reduce acceleration" or "Reduce speed," based on the signal indicating the traction request. A driver can thus take action to avoid wheel slip, for example by reducing throttle, when the "Reduce acceleration" or "Reduce speed" warning appears.

[0073] Alternatively or additionally, the signal indicating the traction requirement is sent to a system that could allow the driver finer control. For example, a throttle map could be modified so that the pedal input would be smoother if the driver's input needs to be less aggressive to avoid breaking the surface.

[0074] In one embodiment, the control unit 60 also includes a communication module 80, which sends and receives data via a telematics unit within the vehicle to and from an address outside the vehicle 10. The transmitter-receiver can send and receive data to and from the external address via an electromagnetic medium 82, such as 3G, 4G, or even Wi-Fi.

[0075] In an alternative embodiment, the control unit 60 also includes a communication module 80, wherein the communication module 80 is a hardware component in the form of a transceiver configured to send and receive data to and from an address outside the vehicle 10. The transceiver can send and receive data to and from the external address via an electromagnetic medium 82, such as 3G, 4G, or even Wi-Fi.

[0076] The communication module 80 is also connected to the determination module 68, the prediction module 70, and the control module 72. Communication between the communication module 80 and each of these other modules 68, 70, and 72 is bidirectional. All data received by the communication module 80 from an external address is thus directly forwarded to each module 68, 70, and 72. Similarly, all outputs from these three modules 68, 70, and 72 can be detected by the communication module 80 and sent to the external address. This data can include: torque, maximum torque value, direction of vehicle movement, vehicle condition, vehicle location data, and other factors that can provide information about the surface condition.

[0077] In this embodiment, the communication module 80 communicates with a central memory 84 located at an address outside the vehicle 10. The memory 84 comprises one or more databases for storing data including: torque, maximum torque value, direction of travel, vehicle condition, vehicle location data, and other factors that can provide information about the surface condition. In this way, these parameters can be sent directly from the vehicle 10 to the memory 84, since the communication module 80 can read the outputs from each module 68, 70, 72. Other vehicles can then use this raw data stored in the memory 84 to share information and build a more accurate model for predicting the traction threshold and the subsequent traction request 76.In addition to the fact that different control units share 60 data points, data such as current weather conditions can be loaded into the vehicle's memory from other sources by a central operator. Vehicles in a fleet can thus communicate indirectly with each other via the central memory 84 to share information and build more accurate models of maximum torque values ​​and traction thresholds.

[0078] In Fig. Figure 3 shows an alternative embodiment. Those features that this embodiment shares with the first embodiment are indicated as being 100 times larger. For the sake of brevity, not all features common to both embodiments are shown and described.

[0079] With reference to Fig. 3. The control unit 160 does not communicate with a central memory 84 ( Fig. 2) Instead, the control unit 160 is configured to communicate directly with other control units 160 located on other vehicles by communicating via a cloud server 185.

[0080] Each of the first or second embodiments can operate in the same way to determine a “maximum torque value” and to generate signals indicating the “traction threshold” and the “traction requirement.” The main difference between the first and second embodiments is the way in which data is shared between multiple control units 60, 160. Accordingly, the following descriptions of operating procedures apply to both embodiments, but for the sake of brevity, they are described only with reference to the first embodiment.

[0081] A method for operating the control unit 60, 160 to estimate the traction for a vehicle 60 is best described with reference to Fig. 4 described. Torque values ​​are determined by the monitoring module 766 ( Fig. 7) monitored. When wheel slip, i.e., a sudden loss of torque at a wheel, is detected, the torque value immediately preceding the wheel slip is recorded as a maximum torque value of 100. The maximum torque value of 100 is recorded for a specific vehicle condition. The vehicle condition is also continuously monitored by the monitoring module 66. In this case, the vehicle condition is the distance, as shown on the X-axis. The distance corresponds to the distance from a starting position of the vehicle, and the distance can be replaced by a current vehicle position provided as GPS coordinates. In this way, the maximum torque value for a vehicle condition, specifically the position, is determined. It is possible to record another vehicle condition, such as weather type, time of day, or vehicle speed, associated with the maximum torque value.A more comprehensive list of potential vehicle conditions includes the following: time, date, weather, vehicle position, dynamic (i.e., the vehicle is moving) or static (i.e., the vehicle is stationary) state of the vehicle, distance traveled, vehicle altitude, vehicle speed, and time the vehicle has been at its current position. For illustrative purposes, however, this procedure for operating control unit 60, 160 is described only with reference to the vehicle position.

[0082] The "traction threshold" is then predicted. To determine the "traction threshold" 768, a compilation of maximum torque values ​​for a wide range of positions must first be recorded. The control unit 60, 160 receives and stores empirical data of these maximum torque values ​​while driving on a surface, where these maximum torque values ​​are the wheel torque values ​​immediately before wheel slip occurs. These maximum torque values ​​100 are then filtered to obtain a range, R, of maximum torque values ​​100. The filtering process considers the current vehicle position and then selects those maximum torque values ​​100 that are representative of the current position. For example, within the range, R, maximum torque values ​​for vehicle positions within +20 m of the current position are considered.The maximum torque values ​​100 outside the range, R, of +20 m are ignored. In this way, the prediction of the "traction threshold" 770 is based on maximum torque values ​​corresponding to a predefined range of vehicle positions, where the range of vehicle positions is based on the current vehicle position.

[0083] Instantaneous axle torque values ​​can be calculated by taking a real-time engine torque output provided by the engine control unit (accurate estimates compiled into a map) and multiplying it by the gear ratio and differential ratios to predict the axle torques. It can be assumed that the torque distribution to the axles is equal for a standard open differential; therefore, the axle torque could be divided by 2 to predict the wheel torque, which is the empirical data element that can be collected, for example, for a maximum torque of 100 Nm. Other methods for calculating wheel torque can be used.

[0084] The maximum empirical torque values ​​of 100 would be collected and assigned to a given vehicle position, which the control unit could use to set the traction threshold for that position when the vehicle returns to the same position.

[0085] The maximum torque values ​​(100) within the range, R, are then assigned to a distribution curve. In this way, the "traction threshold" is based on a stochastic model of the maximum torque values ​​(100). The prediction module 70 predicts a traction threshold, which involves calculating the probability of wheel slip using a parameter model of the obtained empirical data. The "traction threshold" (102) is calculated as being less than a predefined percentage of the maximum torque values ​​(100) within the range, R. The predefined percentage is also called the confidence band. A confidence band of 95% would provide a high level of confidence that future wheel slip would not occur, since 95% of previous maximum torque values ​​for similar vehicle positions are magnitude larger than the current torque value. The control module 72 can output the signal indicating the "traction threshold".This can be used for further processing by the control unit 60, 160 or by any other subsystem of the vehicle 10. In this way, the “traction request” is based on the “maximum torque value” determined by the monitoring module 68 (. Fig. 2) is monitored.

[0086] When the vehicle is powered 10, the monitoring module 66 monitors ( Fig. 2) from an engine control unit and / or brake control unit, such as the ABS control unit 613, torque values ​​of each wheel are also received. In another embodiment, the torque values ​​from each of the torque sensors 50, 52, 54, 56 are monitored. The control module 72 includes a comparator that compares the current torque values ​​with the "traction threshold". If the current torque value is greater than or equal to the "traction threshold", the control module 72 outputs the signal indicating the "traction request" 76 to a communication network, such as CAN or FlexRay, or to a communication module.

[0087] The output signal is then sent to a high-level display front (HLDF) unit, and the HLDF unit signals the HMI 64 to display the "traction request" as a warning, for example, "do not accelerate." Alternatively, the warning may indicate that a wheel slip limit is about to be reached or has been exceeded. The warning can be one or more of the following: visual, audible, or haptic feedback. In this way, a driver understands that a potential problem exists and reduces the accelerator pedal input. This is likely to prevent wheel slip, while the driver is responsible for operating the vehicle in response to the received signal output by the control unit. Preventing wheel slip is better than reacting to a wheel slip event because it avoids damage to the ground beneath the vehicle.

[0088] In another embodiment, the output signal is sent to the vehicle control unit (VCU) so that the accelerator pedal map can be modified to provide increased sensitivity. The driver can then use the accelerator pedal in the normal way, while the vehicle handles the difference in traction requirements. This avoids breaking up the ground under the vehicle, while the driver does not need to react in any other way to counter the wheel slip event.

[0089] In yet another embodiment, the output signal is sent to the vehicle control unit (VCU), the engine control unit, and the powertrain control unit, so that the engine power is reduced and / or the transmission ensures that the required differential gear is changed, thus preventing the breaking up of the ground surface.

[0090] An alternative method for operating the control unit 60, 160 is best described with reference to Fig. 5 described. Torque values ​​are determined by the monitoring module 766 ( Fig. 7) monitored. If wheel slip, i.e., a sudden loss of torque at a wheel, is detected, the torque value immediately preceding the wheel slip is recorded as a maximum torque value of 200. The maximum torque value of 200 is recorded for a specific vehicle condition and is also continuously monitored by the monitoring module 66 ( Fig. 2) monitored. The vehicle condition in this case is the distance, as plotted on the X-axis. The distance is the distance from a starting position of the vehicle, and the distance can be replaced by a current vehicle position provided as GPS coordinates. In this way, the maximum torque value for a vehicle condition, specifically the position, is determined. It is possible to record another vehicle condition, such as weather type, time of day, or vehicle speed, associated with the maximum torque value. A more comprehensive list of potential vehicle conditions includes the following: time, date, weather, vehicle position, dynamic or static state of the vehicle (moving or stationary), vehicle altitude, vehicle speed, and time the vehicle has been at the current position.For illustrative purposes, however, this procedure for handling the vehicle condition is described only with reference to the vehicle position.

[0091] The "traction threshold" is then predicted. Determining the "traction threshold" requires first recording a compilation of maximum torque values ​​for a wide range of positions. A regression model is then implemented to generate a minimum predicted value 210 and a maximum predicted value 212. The torque difference between the minimum predicted value 210 and the maximum predicted value 212 is a prediction band. The minimum and maximum predicted values ​​210 and 212 of the prediction band are extrapolated to distances smaller and larger than those previously monitored positions. The "traction threshold" 202 is then calculated to be lower than the minimum predicted value 212. The minimum predicted value 212 is not constant over a full range of position values ​​because the maximum torque value 200 is sensitive to distance.This is because the type of terrain at one location differs from the type of terrain at another. The type of terrain affects the maximum torque value of 200, as wheel slippage occurs more easily on some types of terrain than on others.

[0092] When the vehicle is powered 10, the monitoring module 66 monitors ( Fig. 2) from an engine control unit and / or brake control unit, such as the ABS control unit 613, also torque values ​​of each wheel. In another embodiment, monitored torque values ​​are obtained from each of the torque sensors 50, 52, 54, 56. The control module 72 ( Fig. 2) includes a comparator that compares the current torque value with the "traction threshold." The current torque value is compared with the "traction threshold" at the current position 214 of the vehicle. For a current torque value that is greater than or equal to the "traction threshold," the control module 72 outputs the signal indicating the "traction request" 76 to a network, such as CAN or FlexRay, or to the communication module 80. The output signal is then sent to an HLDF unit. The HLDF unit signals the HMI 64 to display the "traction request" as a warning, for example, "do not accelerate." In this way, a driver understands that a potential problem exists and reduces the accelerator pedal input. This is likely to prevent wheel slip.Preventing wheel slippage is better than reacting to a wheel slippage event, because this way the ground under the vehicle is not damaged.

[0093] Another alternative method for operating the control unit 60 is best described with reference to Fig. 6 described. This further alternative method either builds on the first method of Fig. 4 or the second method of Fig. 5. In particular, the “traction threshold” 302 was already predicted based on a compilation of maximum torque values ​​300.

[0094] Then vehicle 10 will be operated as usual. The monitoring module 66 ( Fig. 2) continues to monitor other maximum torque values ​​300' that the control unit 60 encounters during its operation. Since the "traction threshold" 302 is predicted to be smaller than the majority of maximum torque values ​​300, other maximum torque values ​​300' are typically only recorded where other conditions, such as weather, affect the terrain at a given location. One scenario where another maximum torque value 300' occurs would be one where a vehicle comes to a stop at a particular location. The vehicle is then left stationary for a period of time. The vehicle is then driven away from rest, at which point other conditions may have changed, such as heavy rain while the vehicle was stationary. These other recorded maximum torque values ​​300' are processed by the prediction module 70 ( Fig.2) used to update the "traction threshold" 302.

[0095] Further alternative methods and modifications of the system are considered to fall within the scope of the present invention without leaving the scope of protection as specified by the following claims.

Claims

[1] Control unit for estimating the traction of a vehicle, comprising the following: a monitoring module that monitors wheel torque values; a determination module for determining maximum torque values ​​by obtaining and storing empirical data while driving on a surface, wherein the maximum torque values ​​are the wheel torque values ​​immediately before wheel slippage; a prediction module that predicts a traction threshold based on the maximum torque values, where the traction threshold is based on a stochastic model of the maximum torque values; and a control module that outputs a signal indicating the traction threshold. [2] Control unit for a vehicle according to claim 1, wherein the prediction of the traction threshold by the prediction module comprises calculating the probability of wheel slip using a parameter model of the empirical data. [3] Control unit for a vehicle according to claim 1 or 2, wherein the control module outputs a signal indicating a traction request in response to a current torque value that exceeds the traction threshold. [4] Control unit according to a preceding claim, wherein the monitoring module monitors one or more vehicle conditions and the determination module determines one or more maximum torque values ​​that are associated with the or each vehicle condition. [5] Control unit according to claim 4, wherein the vehicle condition is selected from the following list: time, date, weather, distance traveled by the vehicle, position of the vehicle, dynamic or static state of the vehicle, altitude of the vehicle, vehicle speed and duration that the vehicle is at a current position. [6] Control unit according to claim 4 or 5, wherein the prediction module predicts the traction threshold value based on one or more maximum torque values ​​corresponding to a predetermined range of the or each vehicle condition. [7] Control unit according to claim 6, wherein the predetermined range of the or each vehicle condition is determined based on the or each current vehicle condition. [8] Control unit according to a preceding claim, wherein the prediction module updates the traction threshold in response to monitoring maximum torque values ​​of the system during its use. [9] Control unit according to a preceding claim, wherein the traction threshold is less than or equal to a predetermined percentage of maximum torque values. [10] Control unit according to one of claims 4 to 8, wherein the prediction module generates a prediction band based on a regression model, wherein the prediction band has a minimum prediction value and a maximum prediction value for each condition, and the traction threshold is set to be less than or equal to the minimum threshold(s). [11] Control unit according to claim 10, wherein the regression model is configured to extrapolate the prediction band to conditions outside the range of conditions used to build the regression model. [12] Control unit according to a preceding claim, wherein the signal indicating the traction threshold is sent to a human machine interface (HMI) and the feedback includes one or more of the following: visual output, audible output and / or haptic output. [13] Control unit according to a preceding claim, wherein the signal indicating the traction threshold is sent to a vehicle control unit and the feedback includes a reduction of engine power and / or modification of the accelerator pedal map. [14] Control unit according to a preceding claim, wherein the control unit sends and / or receives data to or from other vehicle(s) and / or a memory, wherein the data is selected from the following list: Torque, maximum torque value and vehicle conditions. [15] Vehicle comprising the control unit according to a preceding claim. [16] Methods for estimating the traction of a vehicle, comprising the following: Monitoring torque values; Determining maximum torque values ​​by obtaining and storing empirical data while driving on a surface, where the maximum torque values ​​are the wheel torque values ​​immediately before wheel slip; predicting a traction threshold based on the maximum torque values, where the traction threshold is based on a stochastic model of the maximum torque values; and Output of a signal indicating the traction threshold. [17] The method of claim 16, comprising the following: Predictions of the traction threshold, including a calculation of the probability of wheel slip using a parameter model of the empirical data. [18] The method of claim 16 or 17, comprising the following: Outputting a signal indicating a traction request in response to a current torque value that exceeds the traction threshold. [19] A method according to any of the preceding claims, comprising: Monitoring one or more vehicle conditions; and Determine one or more maximum torque values ​​that are associated with the vehicle condition or conditions. [20] Method according to any preceding claim, comprising: Traction threshold predictions based on one or more maximum torque values ​​corresponding to a predefined range of vehicle conditions. [21] Method according to claim 20, wherein the predetermined range of the or each vehicle condition is determined based on the or each current vehicle condition. [22] A method according to any one of claims 16 to 21, comprising the following: Updating the traction threshold in response to monitoring maximum torque values ​​of the system during its use. [23] Method according to any one of claims 16 to 22, wherein predicting the traction threshold comprises calculating the traction threshold such that it is less than or equal to a predetermined percentage of maximum torque values. [24] A method according to any one of claims 16 to 23, comprising the following: Generating a prediction band based on a regression model, wherein the prediction band has a minimum prediction value and a maximum prediction value for each condition; and Determine the traction threshold so that it is less than or equal to the minimum threshold(s). [25] The method of claim 24, comprising the following: Extrapolating the prediction band to conditions outside the range of conditions used to build the regression model. [26] Method according to any one of claims 16 to 25, comprising sending and / or receiving data to / from another vehicle and / or a storage device.

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