ADAPTIVE DRIVE CONTROL LOW TRACTION DETECTION AND OPERATING MODE SELECTION

Abstract

System, comprehensive: a control device (106) programmed to indicate a low-traction operating mode (220) of a vehicle (102) when a longitudinal tracking accumulation exceeds a first threshold and a lateral reaction accumulation exceeds a second threshold, wherein the longitudinal tracking accumulation measures an activation count of a traction control system over time, and the lateral reaction accumulation measures a comparison of the vehicle yaw rate with a model-based prediction of the vehicle yaw rate desired by the driver.

Description

TECHNICAL AREA

[0001] Aspects of the disclosure generally concern adaptive vehicle control surface state detection and operating mode selection. STATE OF THE ART

[0002] Various vehicle subsystems are known to operate in different configuration modes to adapt to varying conditions that change over time. Automatic transmissions, for example, can be controlled in sport, winter, economy, and manual configuration modes, in which the ratios of gears and other subsystem control parameters are modified to match prevailing conditions or driver preferences. Electric active and adaptive suspension systems are known to have on-road and off-road configuration modes. Power steering systems can operate in different configuration modes, varying the level of assistance provided.

[0003] Traditionally, the operation of each vehicle subsystem is manually controlled by the driver based on preference and experience. As the number of controllable subsystems increases, the driver may be faced with a growing number of choices regarding which configuration modes to select for each subsystem based on context and situation. In addition to the increasing number of available choices, this situation also increases the potential for unexpected system interactions. Unless the driver is highly experienced, this complex situation can result in unintended vehicle behavior.

[0004] Various methods and vehicle systems for taking different conditions into account are known from DE 10 2015 109 270 A1, US 2012 / 0 203 424 A1, DE 10 2007 055 421 A1, US 2003 / 0 200 016 A1 and DE 10 2015 118 565 A1. SUMMARY

[0005] In one or more illustrative embodiments, a system includes a control device programmed to indicate a low-traction operating mode of a vehicle when a longitudinal tracking accumulation exceeds a first threshold and a lateral reaction accumulation exceeds a second threshold, wherein the longitudinal tracking accumulation measures an activation count of a traction control system over time, and the lateral reaction accumulation measures a comparison of the vehicle yaw rate with a model-based prediction of the vehicle yaw rate desired by the driver.

[0006] In one or more illustrative embodiments, a method includes calculating a Longitudinal Tracking Accumulation (LTA) for a vehicle, which measures a traction control system activation count over time, and a Lateral Response Accumulation (LRA), which measures a comparison of the vehicle's yaw rate with a driver-desired model-based yaw rate prediction, and specifying a low-traction operating mode to be applied to the vehicle based on an analysis of the LTA and LRA and weather condition information.

[0007] In one or more illustrative embodiments, a non-volatile, computer-readable medium embodying instructions which, when executed by one or more processors of a vehicle control device, cause the control device to compute a longitudinal tracking accumulation (LTA) that measures a number of activations of a traction control system over time; to compute a side reaction accumulation (LRA) that measures a comparison of the vehicle yaw rate with a prediction of the vehicle yaw rate;to analyze the LTA and LRA to determine whether a low traction operating mode is indicated and, based on system settings, to provide a recommendation on a human-machine interface screen display of the vehicle to switch to low traction mode or to automatically set an operating mode of at least one electronic control unit of the vehicle to implement the low traction operating mode. BRIEF DESCRIPTION OF THE DRAWINGS Fig. Figure 1 illustrates an exemplary system for implementing adaptive drive control (ADC) low traction detection and operating mode selection (ADC-LT) in a vehicle; Fig. Figure 2 illustrates an exemplary block diagram of a data flow for the ADC control device; Fig. Figure 3 illustrates an example user interface of the vehicle for configuring the ADC control device; Fig. Figure 4 illustrates an example user interface of the vehicle for displaying an ADC control device recommendation; and Fig. Figure 5 illustrates an exemplary process for ADC acquisition and operating mode selection in a vehicle 102. DETAILED DESCRIPTION

[0008] Detailed embodiments of the present invention are disclosed herein as required; however, it is understood that the disclosed embodiments are purely exemplary of the invention, which can be embodied in various and alternative forms. The figures are not necessarily to scale; some features may be exaggerated or minimized to show details of certain components. Specific structural and functional details disclosed herein are therefore not to be interpreted as limiting, but solely as a representative basis for instructing a person skilled in the art in the diverse applications of the present invention.

[0009] Systems that automatically adjust the operating modes of vehicle control devices can be called adaptive vehicle control (ADC) systems. For example, a vehicle might use a suspension-adjusting ADC to automatically select from sport, normal, and comfort suspension modes to adapt to uneven road gradients and facilitate cornering. In another example, the vehicle might use a performance / economy ADC to automatically activate an economy mode that reduces fuel consumption and power output.

[0010] An ADC Low Traction (ADC-LT) system and procedure can be configured to automatically detect a slippery surface and activate an operating mode for it when current driving conditions require it. In addition to ADC decision-making, which automatically selects Sport, Normal, and Comfort modes to adapt to challenging road conditions, cornering, and winding curves, the LT mode can be conditionally automatically selected. ADC-LT detects slippery conditions based on a multidimensional computational approach according to lateral and longitudinal anomaly detection and accumulation, as well as associated telematics information. ADC-LT can be configured to automatically switch traction modes or to provide the driver with recommendations for switching traction modes. Further aspects of ADC-LT are described in detail here.

[0011] Fig. Figure 1 illustrates an exemplary system 100 for implementing adaptive drive control (ADC) low traction detection and operating mode selection in a vehicle 102. The system 100 comprises a vehicle 102 that has a plurality of electronic control units (ECUs) 104, which communicate with each other and with an ADC control device 106 via one or more vehicle buses 108. The vehicle 102 can also communicate with a weather service 116 via a network 114. Although an exemplary system 100 in Fig. As shown in Figure 1, the exemplary components as illustrated are not intended to be limiting. System 100 can have more or fewer components, and additional or alternative components and / or implementations can be used.

[0012] Vehicle 102 can be a diverse range of motor vehicle types, including crossover vehicles (CUVs), off-road vehicles (SUVs), trucks, recreational vehicles (RVs), boats, aircraft, or other mobile machinery for transporting people and goods. In many cases, Vehicle 102 can be powered by an internal combustion engine. Alternatively, Vehicle 102 can be a hybrid electric vehicle (HEV), powered by both an internal combustion engine and one or more electric motors, such as a series hybrid electric vehicle (SHEV), a parallel hybrid electric vehicle (PHEV), or a parallel / series hybrid electric vehicle (PSHEV). Because the type and configuration of Vehicle 102 can vary, its capabilities can also vary accordingly.Among other possibilities, the vehicle can have 102 different capabilities related to passenger capacity, towing capability and capacity, and storage space.

[0013] The vehicle 102 can have a multitude of ECUs 104 configured to perform and manage various functions of the vehicle 102 using the power of the vehicle battery and / or the powertrain. The ECUs 104 can be computing devices containing hardware processors configured to run software and / or firmware to implement the operations of the ECUs 104 discussed here. As illustrated in the example, the vehicle ECUs 104 are represented as individual ECUs 104-A through 104-G. However, the vehicle ECUs 104 can share physical hardware, firmware, and / or software, allowing the functionality of multiple ECUs 104 to be integrated into a single ECU 104, and the functionality of several such ECUs 104 to be distributed across a plurality of ECUs 104.

[0014] The vehicle ECUs 104 may include components of the vehicle 102 that provide assistance while driving. As some non-restrictive examples of the vehicle ECU 104, the vehicle 102 may include an electronic power steering module (EPASM) 104-A, a powertrain control module (PCM) 104-B, an adaptive cruise control module (ACCM) 104-C (or in other vehicles a cooperative adaptive cruise control system (CACC)), a transmission control module (TCM) 104-D, a suspension control module (SUM) 104-E, and a brake control module (BCM) 104-F.

[0015] The EPASM 104-A can be configured to use an electric motor to provide mechanical power steering for the driver, thereby reducing the effort required to steer the vehicle 102. The PCM 104-B can be configured to facilitate control coordination between the engine and / or transmission and / or driveshaft and / or axle drive of the vehicle 102. The ACCM 104-C can be configured to automatically control the speed of the vehicle 102. The TCM 104-D can be configured to use engine load and vehicle speed information to determine a gear position to be engaged in the transmission.The SUM 104-E can be configured to control suspension aspects of the vehicle 102, such as controlling the damping of the vehicle 102's suspension, and the BCM 104-F can be configured to control braking aspects of the vehicle 102 (for example, anti-lock braking systems (ABS), etc.). It should be noted that the present disclosure illustrates only an exemplary set of ECUs 104, and that vehicles 102 may have more, fewer, or different ECUs 104 than those described herein.

[0016] The ECUs 104 can be configured to operate in various modes, allowing the behavior of the ECU 104 to be optimized for different conditions in each mode. For example, one or more ECUs 104 can be configured to operate in settings such as Comfort, Normal, or Sport. When driving at a generally low speed (that is, slower than 25 mph), the EPASM 112, for instance, can be configured to operate in Comfort settings to reduce the driver's steering effort. At higher speeds (for example, up to 55 mph), the EPASM 112 can be configured to switch to Normal settings. At even higher speeds, the EPASM 112 can be configured to switch to the Sport setting.As another example, the ECUs 104 can be configured to switch between different operating modes based on driving conditions. For instance, the SUM 104-E can be configured to switch to a comfort mode when driving on bumpy roads and to a normal mode when driving on smooth surfaces.

[0017] The ADC control device 106 can be configured to determine the operating modes into which one or more vehicle ECUs 104 are to be placed. The ADC control device 106 can have any number of processors 110, ASICs, ICs, memory 112 (for example, FLASH, ROM, RAM, EPROM, and / or EEPROM), and software code to work together with any other to perform a series of operations. The memory 112 can, for example, contain ADC logic code 118 which, when executed by the one or more processors 110 of the ADC control device 106, causes the ADC control device 106 to perform one or more of the operations described in detail herein. The memory 112 can also contain ADC options 120 that configure aspects of the operation of the ADC logic 118.

[0018] The ADC control device 106 communicates with other vehicle systems, sensors, and control devices to coordinate their function. For example, the ADC control device 106 communicates with other vehicle ECUs, sensors, and / or systems (for example, the PCM 104-B, the TCM 104-D, etc.) via one or more wired or wireless vehicle bus connections 108 using common bus protocols (for example, CAN, LIN, etc.). These input signals can include, but are not limited to, a brake pedal state S. bp exhibiting a brake pressure signal P that corresponds to a brake pedal position (for example, pressed or released). brk , which corresponds to an actual brake pressure value within the brake system (for example, brake line pressure or master cylinder pressure, brake torque), engine speed (N e ), vehicle speed (V eh), steering wheel position, turn signal activation and / or accelerator pedal position (APP) that corresponds to a driver request for propulsion, or whether a traction control system (TCS) warning is provided.

[0019] Furthermore, the ADC control device 106 can also be configured to receive additional information from sources outside the vehicle 102 via the telematics control unit (TCU) 104-G (and / or via the Ford SYNC control unit). This additional information can include, for example, information about infrastructure (e.g., vehicle-to-vehicle (V2V) / vehicle-to-infrastructure (V2I) communication using dedicated short-range communications (DSRC) or other protocols), vehicle sensors (e.g., cameras, light detection and ranging radar (LIDAR), sonar, GNSS, HD map, solar pyrometer, rain sensor, ambient temperature, pressure, and humidity, etc.).For example, the TCU 104-G can be configured to allow the vehicle 102 to receive information via a network 114 from a weather service 116.

[0020] Weather service 116 can be configured to provide information related to current and forecast weather conditions. Weather condition information can include, for example, temperature (e.g., current, forecast low, forecast high, etc.), precipitation type (e.g., rain, snow, sleet, hail, etc.), precipitation probability (e.g., as a percentage), allergen status (e.g., pollen level, smog level, etc.), among other options. In some cases, forecast weather conditions can be specified over a daily timescale, while in others, forecast weather conditions can be specified over a shorter timescale, such as hourly.The weather service 116 can be configured to receive requests for current and / or predicted weather conditions for a specified geographical location and date / place and to answer the requests with the requested information.

[0021] Based on the received information, the ADC control device 106 can communicate with the ECUs 104 to configure which of the various operating modes the ECUs 104 should operate in. Although shown as a single, separate control device, the ADC control device 106 can be integrated into one or more other control devices of the vehicle 102, and / or can have multiple control devices that can be used to control several vehicle systems according to an overall vehicle control logic or software.

[0022] Fig. Figure 2 illustrates an exemplary block diagram of a data flow 200 for the ADC control device 106. In this example, the data flow 200 can be implemented, at least in part, by the ADC logic 118 of the ADC control device 106, which is described above. A data collector 202 receives vehicle driver data 204, environmental data 206, and telematics connectivity data 208. A condition assessor 210 receives the data from the data collector 202 and uses a longitudinal tracking collection (LTA) 212, a side reaction collection (LRA) 214, and an analysis of associated seasonal and weather information (weather condition) 216 to determine current states of the vehicle 102.A decision-maker 218 receives the current state information of the vehicle 102 from the state assessor 210 and, based on this information, determines an operating mode 220 into which the various vehicle systems 222 (which may include one or more of the vehicle ECUs 104, described in detail above) are to be placed. Based on options selected by the driver via a driver interface 224, the decision-maker 218 either automatically applies a change of operating mode 220 to the vehicle systems 222 (for example, ECUs 104) or provides the driver with a recommendation to change operating mode 220 to another operating mode suitable for the states experienced by the vehicle 102. Although an exemplary data flow 200 is shown in... Fig. As shown in Figure 2, the exemplary elements illustrated in the figure are not intended to be limiting. Data flow 200 may actually contain more or fewer elements, and additional or alternative processes, aspects, and / or implementations may be used.

[0023] The driver data 204 can contain various control inputs from the driver of the vehicle 102. These inputs can, for example, include inputs on the controls of the human-machine interface (HMI) related to the control of the vehicle, such as S bp , P brk, APP, steering wheel position or turn signal operation. These inputs can also include user inputs on a touch-sensitive screen or other MMS of the vehicle 102 for receiving settings or other inputs not directly related to the driving task, such as climate control settings, infotainment settings and selection of other vehicle 102 settings.

[0024] The vehicle and environmental data 206 may contain information related to environmental conditions measured by the vehicle 102. For example, the environmental data 206 may contain pitch, yaw, yaw rate, model-based predicted yaw rate, or other remote sensing information obtained from a vehicle stability control system or other sensor systems. For another example, the environmental data 206 may contain rain sensor and solar exposure sensor information related to weather conditions measured by the vehicle 102.

[0025] The telematics / connectivity data 208 can contain information related to environmental conditions measured outside the vehicle 102. For example, the telematics / connectivity data 208 can contain information related to current and predicted weather conditions obtained from the weather service 116.

[0026] The condition assessor 210 can be configured to receive driver data 204, environmental data 206 and telematics connectivity data 208 from the data collector 202 and to calculate the LTA 212, LRA 214 and the weather condition 216.

[0027] The value of LTA 212 can be determined based on analysis and accumulation of vehicle traction control activations. LTA 212 can be provided to the decision-maker 218 as a value ranging from 0 to 1, where values ​​closer to 1 represent a higher probability of slippery longitudinal states, and values ​​closer to 0 represent a relatively lower probability of slippery longitudinal states. To calculate LTA 212, the condition assessor 210 can include collectors for tracking the activation of the traction control system (TCS) warning. TCS activation can be obtained from one or more vehicle buses 108 (for example, a CAN bus). If the TCS is activated, the condition assessor 210 generates a digital flag value and increments a TCS counter. In one example, this is done by creating an intermediate flag that checks the TCS state as follows: (1) If TCS is active → flag=1 If TCS is inactive → flag=0

[0028] If the TCS is activated (for example, flag 1), the LTA 212 can be calculated as follows: LTA(k)=LTA(k−1)+e where k is the number of cycles of executing accumulation, and e is an increment value (for example, e = 0.25, as mentioned above).

[0029] The LTA 212 can be reset to zero after a scheduled period of time. For example, the reset period could be one to three minutes of TCS inactivity.

[0030] In another embodiment, the LTA 212 can be calculated and implemented as an exponential filter for TCS activations: LTAk=α*TCSstatus+(1−α)*LTAk−1 where the LTA value is between 0 and 1, and where α is an experimentally determined time constant (between 0 and 1, for example 0.15) that determines how quickly the counter can change in n intervals.

[0031] The LRA 214 value can be determined to provide analysis and accumulation of lateral anomalies and deviations from the lateral movement requested by the driver. The LRA 214 can be provided to the decision-maker 218 as a value ranging from 0 to 1, where values ​​closer to 1 represent a greater probability of lateral slippage, and values ​​closer to 0 represent a lesser probability of slippage.

[0032] For example, the LRA 214 can be calculated as follows: LRA=abs(Ldes−Lpred)γ where L des The real-time measurement of the vehicle's yaw rate is a result of steering inputs and control actions requested by the driver; L preda model-based prediction of the yaw rate, which, as is known from the prior art, is calculated from the steering and control inputs requested by the driver and vehicle parameters and is obtained from the vehicle network (for example, from the vehicle's electronic stability control system 102), and γ is a scaling factor of a tunable maximum yaw rate deviation (for example, a scaling factor of 3 to 5 degrees per second).

[0033] The weather information 216 can be determined using one or more weather rules based on the environmental data 206 and the telematics connectivity data 208. A rule can, for example, define a weather Zustand Specify 1 to assign a snowfall environmental condition identified by the vehicle's sensors 102 via data from the weather service 116, or otherwise 0. Alternatively, a rule can specify a weather ZustandSpecify a value of 1 to assign a state with a temperature below freezing, or 0 otherwise. As yet another example, a rule can specify a weather Zustand Specify from 1 to assign a black ice condition when the ambient temperature (as measured, for example, by a sensor on vehicle 102) is between 0 °C and -3 °C and the dew point is above 0 °C. It should be noted that these are merely examples, and more, fewer, and other weather rules may be used.

[0034] Alternatively, the weather could Zustand as a continuous function based on other information reported by the weather data provider, such as snow (or precipitation rate), are determined as WeatherCondition(k)={0, if snowfall rate 0 cm / hr; 1, if snowfall rate≥5 cm / hr

[0035] Then a linearly increasing function between 0 and 1 is obtained.

[0036] Or the weather condition could be based on estimated snow depth accumulation (or rainwater accumulation) on the road surface, as determined by GPS or other means at the location, or by the vehicle on the route ahead in a similar manner.

[0037] In these cases: WeatherState(k) = (1−α) * WeatherState(k−1)+α * WeatherState(k)

[0038] where α is a number between 0 and 1 (for example, 0,1).

[0039] Regardless of the approach, the assignment of weather conditions to determine the weather Zustand -Values ​​can be used to improve the identification of slippery situations by the decision-maker 218.

[0040] The decision controller 218 can be configured to determine the operating mode 220 into which the vehicle 102 is to be placed, based on the LTA 212, LRA 214, and the weather condition 216, which is obtained from the condition assessor 210. The operating modes 220 can include, for example, Sport mode 220, Normal mode 220, and Comfort mode 220. The decision controller 218 can therefore cause the vehicle 102 to adapt to road conditions, cornering, and conditions with winding curves along the roadway.

[0041] More specifically, the decision controller 218 can be configured to automatically select either a low traction (LT) or a normal traction (220) operating mode. For example, the decision controller 218 can be configured to select the LT operating mode 220 based on a collection of anomalies from the LTA 212, the LRA 214, and the weather condition 216. As an example, the decision to select either an LT operating mode 220 or a normal traction (220) operating mode can be calculated as follows. ADCLT={1 if{LTA>λWeatherState=1LRA>θotherwise 0

[0042] As indicated in equation (4), determining the ADC LT -Values ​​based on LTA 212, LRA 214 and weather condition 216. An ADC LT A value of 1 results in an instruction to activate LT operating mode 220, and an ADC LTA value of 0 results in a setting for deactivation from LT operating mode 220. Examples of the tunable threshold values ​​of the constants λ and θ are 0.75 and 0.7 respectively.

[0043] Variations of equation (4) are possible. If the weather Zustand For example, if the weather element is defined as a continuous signal between 0 and 1 instead of a binary 0 or 1, a threshold could also be introduced for it. Another possible variation could be the calculation of ADC. LT This can also be changed by introducing weighting factors, for example, numbers between 0 and 1, which allow the developer to determine how much weight should be assigned to each element. These weighting factors could also be determined dynamically based on confidence in the individual signals at any given time.

[0044] The driver interface 224 can be configured to provide the ADC control unit 106 with the ability to configure information related to ADC options 118 for automatic mode selection or mode recommendation. Using the driver interface 224, the driver can select for the ADC control unit 106 to place the vehicle 102 in power mode 220, in which low-traction settings are not used, or in a low-traction (LT) mode, in which low-traction settings are used. As an alternative selection, the driver interface 224 can allow the driver to select an Auto-ADC mode 220, requiring the decision-maker 218 to automatically adjust the mode selection for specific driving contexts.

[0045] In some examples, the driver interface 224 can also present ADC options 118 for operating the Auto-ADC mode 220. For example, the driver interface 224 can allow the driver to choose between a first ADC option 118, in which the ADC control device 106 learns the LT mode 220 and automatically activates it when the decision-maker 218 detects slippery conditions, and a second ADC option 118, in which the ADC control device 106 provides a driver recommendation to activate the LT mode 220 when the decision-maker 218 detects slippery conditions, without automatically applying the LT mode 220.

[0046] In the first option's operating mode, for example, the command to activate LT operating mode 220 can result in automatic activation of LT operating mode 220, whereas in the second option, the command to activate LT operating mode 220 can result in a recommendation to the driver to activate LT operating mode 220. As another example, in the first option's operating mode, the command to deactivate LT operating mode 220 can result in deactivation of LT operating mode 220, whereas in the second mode, the command to deactivate LT operating mode 220 can result in a recommendation to return to normal traction operating mode 220. The decision point 218 of the ADC control device 106 can therefore be used to automatically select from recommendations or to make recommendations to select from operating modes 220 of the vehicle systems 222.

[0047] Fig. Figure 3 illustrates an example user interface 300 of the vehicle 102 for configuring the ADC control device 106. In one example, the user interface 300 can be displayed on a main unit or another display 302 of the vehicle 102. The main unit display 302 can, for example, be controlled by a video connection from a video controller for the vehicle 102 in communication with the ADC control device 106 via the vehicle bus 108. The user interface 300 can allow the user to configure the ADC options 120 of the ADC control device 106 in connection with automatic or manual application of the recommended ADC settings. In some examples, the user interface 300 can be displayed in response to the user selecting an ADC configuration option.To facilitate the configuration of the ADC control device 106, driver selections made on the user interface 300 can be provided to the driver interface 224 of the ADC control device 106 via the vehicle bus 108, which in turn can update the outdated ADC options 120 in the memory 112 of the ADC control device 106.

[0048] As shown, the user interface 300 has a category list 304 consisting of one or more screen displays with content that can be shown on the main screen area 304 of the main unit display 302. As some examples, the category list 304 may include an audio screen display from which the configuration of the vehicle 102's audio settings can be performed, a climate control screen display from which the climate control settings of the vehicle 102 can be configured, a telephone screen display from which call services can be used, a navigation screen display from which maps and routing can be performed, an application screen display from which installed applications can be accessed, and a settings screen display from which backlighting or other general settings of the main unit display 302 can be accessed.The user interface 300 may also include a general information area 308 where the time, current temperature and other information may remain visible to the user regardless of the specific screen display or application active on the main screen area 306.

[0049] The main screen area 306 may have a user interface 300 with a descriptive label 310 indicating that the user interface 300 is intended for configuring the ADC options 120 of the ADC control device 106. The main screen area 306 also has a configuration panel 312 containing the configurable options.These options may include, for example, an ADC activation option 314, which allows the driver to select whether the ADC is activated or deactivated; an automatic traction mode selection option 316, which allows the driver to select whether the ADC control unit 106 automatically sets the traction mode 220 of the vehicle 102 or provides recommendations to the driver on how to set the traction mode 220; and an automatic suspension mode selection option 318, which allows the driver to select whether the ADC control unit 106 automatically sets the suspension mode 220 for the vehicle 102 or provides recommendations to the driver on how to set the suspension mode 220.

[0050] Fig. Figure 4 illustrates an example user interface 400 of the vehicle 102 for displaying a recommendation 402 from the ADC control unit 106. The recommendation 402 can be displayed by the ADC control unit 106 in response to a message received by the head unit via the vehicle bus 108, recommending a change in operating mode 220. As shown, the recommendation 402 has a title 404 to indicate to the driver that the recommendation 402 is generated by the ADC control unit 106. The recommendation 402 can also have a description label 406 that describes the recommended change in operating mode 220 (for example, that operating mode 220 with low traction is recommended).Recommendation 402 may also include an operating mode change button 408 which, when selected by the driver, is configured to cause the ADC control device 106 to receive permission to apply the proposed operating mode 220 to the vehicle systems 222. Warning 402 may also include a rejection button 410 which, when selected by the driver, is configured to reject Recommendation 402 without adapting operating mode 220.

[0051] Fig. Figure 5 illustrates an exemplary process 500 for ADC-LT acquisition and operating mode selection in a vehicle 102. In an example, the process 500 can be executed by using the ADC control device 106 in accordance with the data flow 200, which is discussed in detail above.

[0052] In process 502, the ADC control device 106 performs data collection. In one example, the data collector 202 of the ADC control device 106 receives the driver data 204, the environment data 206, and the connectivity data 208.

[0053] At operation 504, the ADC control device 106 performs LTA 212 calculations, and at operation 506, the ADC control device 106 performs LRA 214 calculations. For example, the LTA 212 and LRA 214 anomaly detection and accumulation can be performed by the condition assessor 210 of the ADC control device 106, as discussed above.

[0054] In process 508, the ADC control device 106 determines which conditional states of the ADC determination are fulfilled. In one example, the decision-maker 218 of the ADC control device 106 analyzes the LTA 212, LRA 214 and the weather condition 216 to determine the ADC LT -value to be determined using equation (1).

[0055] At 510, the ADC control device 106 determines the LT operating mode 220 for the vehicle 102. In one example, the decision point 218 of the ADC control device 106 determines the operating mode 220 into which the vehicle 102 is placed based on the ADC. LT and to place the driver options specified via the driver interface 224.

[0056] In operation 512, the ADC control device 106 applies the specified LT operating mode 220 to the vehicle systems 222. In one example, the ADC control device 106 can automatically set the operating mode 220 of the vehicle systems 222. In another example, the ADC control device 106 can display recommendation 402 to the user, allowing the user to manually accept or reject the recommended operating mode 220. After operation 512, process 500 returns to operation 502.

[0057] Computing devices described herein, such as the ECUs 104 and the ADC control device 106, generally contain computer-executable instructions, the instructions being executable by one or more computing devices such as those listed above. Computer-executable instructions can be compiled or interpreted from computer programs created using a variety of programming languages ​​and / or technologies, including, without limitation and either alone or in combination, Java™, C, C++, C#, Visual Basic, JavaScript, Perl, etc. Generally, a processor (for example, a microprocessor) receives instructions, for example, from memory, a computer-readable medium, etc., and executes them, thereby running one or more processes, including one or more of the processes described herein.Such instructions and other data can be stored and transmitted using a variety of computer-readable media.

[0058] Regarding the processes, systems, procedures, heuristics, etc., described herein, it should be understood that, although the steps of such processes, etc., are described as occurring in a specific, ordered sequence, such processes could also be implemented using the described steps in a different order than that described here. Furthermore, it should be understood that certain steps could be performed simultaneously, that other steps could be added, or that certain steps described herein could be omitted. In other words, the descriptions of processes provided here are for the purpose of illustrating certain embodiments and should in no way be interpreted as limiting the claims.

Claims

[1] System, encompassing: a control device (106) programmed to indicate a low-traction operating mode (220) of a vehicle (102) when a longitudinal tracking accumulation exceeds a first threshold and a lateral reaction accumulation exceeds a second threshold, wherein the longitudinal tracking accumulation measures an activation count of a traction control system over time, and the lateral reaction accumulation measures a comparison of the vehicle yaw rate with a model-based prediction of the vehicle yaw rate desired by the driver. [2] System according to claim 1, wherein the control device (106) is further programmed to use weather information (216) to confirm the low traction operating mode (220). [3] System according to claim 1, wherein the control device (106) is further programmed to indicate the low traction operating mode (220) by providing a recommendation to switch to the low traction operating mode (220) on a human-machine interface screen (306) of the vehicle (102). [4] System according to claim 1, wherein the control device (106) is further programmed to specify the low traction operating mode (220) by automatically setting an operating mode (220) of at least one electronic control unit (ECU) (104) of the vehicle (102) to implement the low traction operating mode (220). [5] System according to claim 1, wherein a current cycle of longitudinal tracking accumulation is calculated by determining a value based on a set of traction control system warnings issued during a predetermined time period and by adding the value to a previous cycle value of longitudinal tracking accumulation. [6] System according to claim 5, wherein the predetermined time interval is one minute. [7] System according to claim 1, wherein the side reaction accumulation is calculated according to an absolute difference between the vehicle yaw rate and the model-based prediction of the vehicle yaw rate desired by the driver, divided by a tunable maximum yaw rate deviation constant. [8] Procedure comprising the following: Computation of a longitudinal tracking accumulation (LTA), which measures a number of activations of a traction control system over time, and a side reaction accumulation (LRA), which measures a comparison of the vehicle yaw rate with a model-based prediction of the yaw rate, for a vehicle (102), and Specifying a low traction operating mode (220) to be applied to the vehicle (102) based on analyzing the LTA and LRA as well as weather condition information (216). [9] Method according to claim 8, further comprising indicating the low traction operating mode (220) by providing a recommendation to switch to the low traction operating mode (220) on a human-machine interface screen display (306) of the vehicle (102). [10] Method according to claim 8, which further comprises specifying the low traction operating mode (220) by automatically setting an operating mode (220) of at least one electronic control unit (104) of the vehicle (102) in order to implement the low traction operating mode (220). [11] Method according to claim 8, further comprising calculating a current LTA cycle by determining a value based on a set of traction control system warnings issued during a predetermined time period and by adding the value to a previous LTA cycle value. [12] Method according to claim 11, wherein the predetermined time interval is one to three minutes. [13] Method according to claim 8, further comprising calculating the side reaction accumulation according to an absolute difference of the vehicle yaw rate and a selected model-based prediction of the vehicle yaw rate divided by a tunable constant representing a maximum yaw rate deviation.

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