Vehicle subsystem control method and apparatus

Abstract

Aspects of the invention relate to a control system, a vehicle and a control method. The control system is for controlling selection of one of a plurality of subsystem control modes to control operation of at least one vehicle subsystem of the vehicle. The subsystem control modes each correspond to one or more different terrain types, including a first terrain type corresponding to sand. The subsystem control modes include a first subsystem control mode corresponding to the first terrain type. The control system includes one or more processors collectively configured to determine a rolling resistance of the vehicle and a moving average of the rolling resistance, select one of a plurality of mode selection probability profiles each defining a first terrain indication probability component associated with the first terrain indication parameter based on the determined moving average, determine a first mode selection probability associated with the first terrain type based on the first terrain indication probability component from the selected mode selection probability profile, and select one of the subsystem control modes based on the first mode selection probability.

Description

Technical Field

[0001] This disclosure relates to methods and apparatus for controlling vehicle subsystems. Various aspects of the invention relate to control systems, methods, vehicles, and computer-readable instructions. Background Technology

[0002] It is known that the operation of one or more vehicle subsystems can be controlled based on the terrain type in which the vehicle is operating. Multiple subsystem control modes can be defined, for example, corresponding to different terrain types. One or more vehicle subsystems are controlled based on the mode selected from these multiple subsystem control modes. Changes in terrain, such as if the vehicle is operating off-road, may lead to the selection of different subsystem control modes. If the change in terrain type is localized, selecting a different subsystem control mode may be inappropriate.

[0003] The purpose of this invention is to address one or more of the disadvantages associated with the prior art. Summary of the Invention

[0004] The various aspects and embodiments of the present invention provide control systems, vehicles, methods, and computer-readable instructions as claimed in the appended claims.

[0005] According to an aspect of the invention, a control system is provided for controlling the selection of one of a plurality of subsystem control modes to control the operation of at least one vehicle subsystem of a vehicle, each subsystem control mode corresponding to one or more different terrain types; one or more different terrain types include a first terrain type corresponding to sand, and the subsystem control mode includes a first subsystem control mode corresponding to the first terrain type; the control system includes one or more processors, which are collectively configured to:

[0006] Determine the rolling resistance of the vehicle;

[0007] Determine the moving average value of rolling resistance;

[0008] One of multiple mode selection probability maps is selected based on the determined moving average, and each of the multiple mode selection probability maps has a first terrain indication probability component that is associated with the first terrain indication parameter.

[0009] Determine a first mode selection probability associated with a first terrain type, the first mode selection probability being determined based on a first terrain indication probability component derived from a mode selection probability map selected from a plurality of mode selection probability maps; and

[0010] One of the multiple subsystem control modes is selected based on the determined first mode selection probability.

[0011] A first mode selection probability is determined based on one of a plurality of mode selection probability maps. In at least some embodiments, the mode selection probability maps are different from each other. The first mode selection probability can be indirectly modified by defining different mode selection probability maps. The selection of one of the plurality of mode selection probabilities can be used to refine the selection of the subsystem control mode.

[0012] Rolling resistance of a vehicle is a time-varying parameter, meaning it is a dynamic parameter that changes with respect to time. The determined rolling resistance can represent its real-time value. A moving average (also known as a sliding average) of the rolling resistance can be calculated based on a predetermined time period.

[0013] The control system includes one or more controllers, which collectively include: at least one electronic processor having an electrical input for receiving input signals; and at least one memory device electrically coupled to the at least one electronic processor and having instructions stored therein; and wherein the at least one electronic processor is configured to access the at least one memory device and execute the instructions thereon to determine the rolling resistance of a vehicle; and to determine a moving average of the rolling resistance. The at least one electronic processor is configured to select one of a plurality of mode selection probability maps based on the determined moving average, each of the plurality of mode selection probability maps defining a first terrain indication probability component associated with a first terrain indication parameter. The at least one electronic processor is configured to determine a first mode selection probability associated with a first terrain type, the first mode selection probability being determined based on the first terrain indication probability component derived from a mode selection probability map selected from the plurality of mode selection probability maps. The at least one electronic processor is configured to select one of a plurality of subsystem control modes based on the determined first mode selection probability.

[0014] The first terrain indicator parameter can be a time-varying parameter, that is, a dynamic parameter that changes with respect to time.

[0015] The first terrain indication parameter may include or be composed of the vehicle's rolling resistance. Multiple mode selection probability maps can each define a first terrain indication probability component associated with the vehicle's rolling resistance. One of the multiple mode selection probability maps is selected based on the determined moving average of the rolling resistance. The first mode selection probability can be determined based on the determined rolling resistance. The determined rolling resistance can represent a real-time value of the rolling resistance.

[0016] Selecting one of multiple pattern selection probability maps may include comparing a determined moving average of rolling resistance with a rolling resistance threshold. The rolling resistance threshold may be predefined. In a variant, the rolling resistance threshold may be calculated dynamically. The multiple pattern selection probability maps may include at least a first pattern selection probability map and a second pattern selection probability map. The first pattern selection probability map may be selected based on the determination that the moving average of rolling resistance is greater than the rolling resistance threshold. The second pattern selection probability map may be selected based on the determination that the moving average of rolling resistance is less than the rolling resistance threshold.

[0017] One or more processors may be configured to collectively determine a second terrain indication probability component based on a second terrain indication parameter. The second terrain indication parameter may be a time-varying parameter, i.e., a dynamic parameter that changes with time. The first mode selection probability may be determined based on the second terrain indication probability component. The first mode selection probability may be determined based on at least the first and second terrain indication probability components. The first and second terrain indication parameters may be different from each other.

[0018] The second terrain indication parameter may include or consist of the vehicle's yaw angle. The one or more processors may be collectively configured to receive a yaw angle signal indicating the vehicle's yaw angle. The second terrain indication parameter can be determined based on the yaw angle indicated by the yaw angle signal. One or more processors may apply a hold-and-step-descent function to the yaw angle signal to generate a modulated yaw angle signal. The hold-and-step-descent function may be configured to hold the peak value of the yaw angle for a calibrable time period and then control the decay of the yaw angle (i.e., the reduction of the yaw angle). The decay of the yaw angle may be performed at a calibrable rate. The decay rate may be constant or non-constant. The decay of the yaw angle may continue until the value exceeds the yaw angle indicated by the yaw angle signal. The second terrain indication probability component can be determined based on the modulated yaw angle signal.

[0019] One or more processors may be configured to collectively determine a third terrain indication probability component based on a third terrain indication parameter. The third terrain indication parameter may be a time-varying parameter, i.e., a dynamic parameter that changes with time. The first mode selection probability may be determined based on the third terrain indication probability component. The first mode selection probability may be determined based on at least the first and third terrain indication probability components. A second terrain indicator may also be optionally used to determine the first mode selection probability. The first and third terrain indication parameters may be different from each other.

[0020] The third terrain indication parameter may include the vehicle's pitch angle. One or more processors may be configured to collectively receive a pitch angle signal indicating the vehicle's pitch angle. The third terrain indication parameter can be determined based on the pitch angle indicated by the pitch angle signal. The one or more processors may be collectively configured to apply a hold-and-step descent function to the pitch angle signal to generate a modulated pitch angle signal. The hold-and-step descent function may be configured to hold the peak of the pitch angle for a calibrable time period and then control the decay of the pitch angle (i.e., the reduction of the pitch angle). The pitch angle decay can be performed at a calibrable rate. The decay rate can be constant or non-constant. The pitch angle decay can continue until the value exceeds the pitch angle indicated by the pitch angle signal. The third terrain indication parameter can be determined based on the modulated pitch angle signal.

[0021] The one or more processors may be collectively configured to control the selection of a first subsystem control mode based on one or more entry conditions. The one or more processors may be collectively configured to selectively enable and disable the selection of the first subsystem control mode based on the entry conditions or each entry condition. The selection of the first subsystem control mode may be enabled based on determining that the entry conditions or each entry condition are met. The selection of the first subsystem control mode may be disabled (or suppressed) based on determining that the entry conditions are not met. The one or more entry conditions may include one or more of the following: ambient temperature, vehicle speed, and terrain roughness.

[0022] The one or more entry conditions may include one or more of the following:

[0023] 1. Ambient temperature, which is greater than or equal to a predetermined temperature threshold.

[0024] 2. Vehicle reference speed (VREF), which is less than or equal to a predetermined speed threshold.

[0025] 3. The measured terrain roughness is less than or equal to a predetermined terrain roughness threshold.

[0026] According to another aspect of the invention, a control system is provided for controlling the selection of one of a plurality of subsystem control modes to control the operation of at least one vehicle subsystem of a vehicle, each subsystem control mode corresponding to one or more different terrain types; one or more different terrain types include a first terrain type corresponding to sand, and the subsystem control mode includes a first subsystem control mode corresponding to the first terrain type; the vehicle control system includes one or more processors, said one or more processors being collectively configured to:

[0027] Determine a first mode selection probability associated with a first terrain type, the first mode selection probability being determined based on at least one of a first terrain indication probability component and a second terrain indication probability component; and

[0028] One of the multiple subsystem control modes is selected based on the determined first mode selection probability;

[0029] in:

[0030] The first terrain indication probability component is determined based on a modulated yaw angle signal, which is generated by applying a hold-and-step descent function to the yaw angle signal received from a yaw angle sensor; and

[0031] The second terrain indication probability component is determined based on a modulated pitch angle signal, which is generated by applying a hold-and-step descent function to the pitch angle signal received from a pitch angle sensor.

[0032] The hold-and-step descent function can be configured to maintain the peak value of the yaw angle for a calibrable time period and then control the decay of the yaw angle (i.e., the reduction of the yaw angle). The decay of the yaw angle can be performed at a calibrable rate. The decay rate can be constant or non-constant. The decay of the yaw angle can continue until the value exceeds the yaw angle indicated by the yaw angle signal.

[0033] The hold-and-step descent function can be configured to maintain the peak pitch angle for a calibrable time period and then control the decay of the pitch angle (i.e., the reduction of the pitch angle). The pitch angle decay can be performed at a calibrable rate. The decay rate can be constant or non-constant. The pitch angle decay can continue until the value exceeds the pitch angle indicated by the pitch angle signal.

[0034] According to another aspect of the invention, a control system is provided for controlling the selection of one of a plurality of subsystem control modes to control the operation of at least one vehicle subsystem of a vehicle, each subsystem control mode corresponding to one or more different terrain types; wherein the one or more different terrain types include a first terrain type, and the subsystem control mode includes a first subsystem control mode corresponding to the first terrain type; the vehicle control system includes one or more processors, the one or more processors being configured collectively to:

[0035] Based on the first terrain indication parameter, one of multiple mode selection probability maps is selected, and each of the multiple mode selection probability maps has a first terrain indication probability component associated with the first terrain indication parameter.

[0036] Determine a first mode selection probability associated with a first terrain type, the first mode selection probability being determined based on a first terrain indication probability component derived from a mode selection probability map selected from a plurality of mode selection probability maps; and

[0037] One of the multiple subsystem control modes is selected based on the determined first mode selection probability.

[0038] Selecting one of multiple pattern selection probability maps may include comparing a first terrain indication parameter with a threshold. The threshold may be predefined. In a variant, the threshold may be dynamically calculated. The multiple pattern selection probability maps may include at least a first pattern selection probability map and a second pattern selection probability map. The first pattern selection probability map may be selected based on determining that the first terrain indication parameter is greater than the threshold. The second pattern selection probability map may be selected based on determining that the first terrain indication parameter is less than the threshold. The one or more processors may be configured to determine a moving average of the first terrain indication parameter. The moving average of the first terrain indication parameter may be compared with the threshold to select one of the first and second pattern selection probability maps.

[0039] The first terrain indication parameter may include the vehicle's rolling resistance. Alternatively or additionally, the first terrain indication parameter may include one or more of the following: road surface friction and road surface roughness.

[0040] According to another aspect of the invention, a vehicle comprising a control system as described herein is provided.

[0041] According to another aspect of the invention, a method is provided for controlling the selection of one of a plurality of subsystem control modes for controlling the operation of at least one subsystem of a vehicle, each subsystem control mode corresponding to one or more different terrain types; one or more different terrain types including a first terrain type corresponding to sand, and the subsystem control mode including a first subsystem control mode corresponding to the first terrain type; wherein the method includes:

[0042] Determine the rolling resistance of the vehicle;

[0043] Determine the moving average value of rolling resistance;

[0044] One of multiple mode selection probability maps is selected based on the determined moving average, and each of the multiple mode selection probability maps has a first terrain indication probability component that is associated with the first terrain indication parameter.

[0045] Determine a first mode selection probability associated with a first terrain type, the first mode selection probability being determined based on a first terrain indication probability component derived from a mode selection probability map selected from a plurality of mode selection probability maps; and

[0046] One of the multiple subsystem control modes is selected based on the determined first mode selection probability.

[0047] According to another aspect of the invention, computer-readable instructions are provided that, when executed by one or more processors, cause the one or more processors to perform the methods described herein.

[0048] According to another aspect of the invention, a control system is provided for controlling the selection of one of a plurality of subsystem control modes to control the operation of at least one vehicle subsystem of a vehicle, each of the subsystem control modes corresponding to one or more different terrain types; wherein the one or more different terrain types include a first terrain type, and the subsystem control mode includes a first subsystem control mode corresponding to the first terrain type; the vehicle control system includes one or more processors, the one or more processors being configured to:

[0049] Determine the vehicle's initial operating parameters;

[0050] One of multiple mode selection probability maps is selected based on the determined first operating parameter, and each of the multiple mode selection probability maps is customized with a first terrain indication probability component associated with the first terrain indication parameter;

[0051] Determine a first mode selection probability associated with a first terrain type, the first mode selection probability being determined based on a first terrain indication probability component derived from a selection of multiple mode selection probability maps; and

[0052] One of the multiple subsystem control modes is selected based on the determined first mode selection probability.

[0053] The first operating parameter may include the vehicle's rolling resistance. Alternatively, or additionally, the first operating parameter may include one or more of the following: road surface roughness and road surface friction. Other operating parameters may be used. The mode selection probability map can be selected based on the vehicle's rolling resistance. The first terrain type may be sandy terrain, such as terrain including deep sand or terrain composed of deep sand. The first terrain type may include one of the following: grass / gravel / snow; mud and ruts; and rock.

[0054] Within the scope of this application, it is expressly intended that all aspects, embodiments, examples, and alternatives set forth in the foregoing paragraphs, claims, and / or the following description and drawings, and in particular their various features, may be adopted individually or in any combination. That is, all embodiments and / or features of any embodiment may be combined in any manner and / or combination, unless such features are incompatible. The applicant reserves the right to amend any originally filed claim or accordingly file any new claim, including the right to modify any originally filed claim to any feature subordinate to and / or incorporated into any other claim, even though it was not initially claimed in this manner. Attached Figure Description

[0055] One or more embodiments of the invention will now be described by way of example only with reference to the accompanying drawings, in which:

[0056] Figure 1 A schematic representation of a vehicle including a control system according to an embodiment of the present invention is shown;

[0057] Figure 2 It shows Figure 1 The diagram shows a schematic representation of the vehicle's control system, drive unit, and subsystems.

[0058] Figure 3 It shows Figure 1 and Figure 2 The diagram shows a schematic representation of the controller of the control system.

[0059] Figure 4 It is a graph showing the first probability spectrum and the second probability spectrum of the first rolling resistance probability component and the second rolling resistance probability component defined relative to the determined rolling resistance.

[0060] Figure 5 The first graph shows the rolling resistance of a vehicle traversing deep sand.

[0061] Figure 6A The diagram shows the first curve illustrating the modulation of the vehicle pitch angle signal by applying a hold-and-step descent function;

[0062] Figure 6B The second graph illustrating the modulation of the yaw angle signal by applying a hold-and-step descent function is shown.

[0063] Figure 7 The illustration is shown according to Figure 5 The second curve representing the probability of sand pattern selection generated by rolling resistance; and

[0064] Figure 8This is a block diagram illustrating the method for determining the probability of selecting a sand mode based on the rolling resistance of a vehicle. Detailed Implementation

[0065] This document describes, with reference to the accompanying drawings, a vehicle control system 1 and a method 400 for controlling the operation of at least one vehicle subsystem 3(n) of a vehicle 5 according to an embodiment of the present invention. As described herein, the vehicle control system 1 includes a vehicle control unit 7 for controlling the operation of at least one vehicle subsystem 3(n).

[0066] Vehicle 5 is described herein with reference to a frame of reference including the longitudinal axis X, the transverse axis Y, and the vertical axis Z. Reference numerals in this document include suffixes of integer form to distinguish multiple similar parts on vehicle 5. The same suffix applies to parts that are related to each other, such as parts that form part of the same sub-assembly of vehicle 5. The integer n is used herein to identify a signal or event associated with a corresponding feature among multiple features of vehicle 5.

[0067] like Figure 1 As shown, the control system 1 is installed in a vehicle 5 comprising four (4) wheels 9 (1) to 9 (4). The wheels 9 (1) to 9 (4) include a first front wheel 9 (1) and a second front wheel 9 (2) mounted on the front axle, and a first rear wheel 9 (3) and a second rear wheel 9 (4) mounted on the rear axle. The vehicle 5 is a road vehicle, such as an automobile, a sport utility vehicle (SUV), or a multi-purpose vehicle. Figure 1 and Figure 2 As shown, the vehicle 5 in this embodiment is an automobile. Vehicle 5 includes one or more torque-generating machines 11, such as an internal combustion engine (ICE) and / or an electric drive unit. Vehicle 5 may be a battery electric vehicle (BEV), a hybrid electric vehicle (HEV), a plug-in hybrid electric vehicle (PHEV), or an internal combustion engine (ICE) vehicle. The front wheels 9(1), 9(2) and / or the rear wheels 9(3), 9(4) may be driven by one or more torque-generating machines 11. In this embodiment, vehicle 5 is two-wheel drive and only the front wheels 9(1) to 9(2) are driven. The torque-generating machine 11 includes an electric drive unit (EDU) 11 for driving the front wheels 9(1), 9(2) of vehicle 5. Alternatively or additionally, the rear wheels 9(1), 9(2) of vehicle 5 may be driven by the electric drive unit 11. Vehicle 5 may include more than one electric drive unit 11.

[0068] Figure 1 and Figure 2A vehicle control system 1 for vehicle 5 is shown. Vehicle 5 is suitable for off-road use, i.e., suitable for use on terrain other than conventional paved roads. The vehicle control system 1 controls one or more of the vehicle subsystems 3(n), including but not limited to the propulsion (or engine) management system 3(1), transmission system 3(2), steering system 3(3), braking system 3(4), suspension system 3(5), and differential system 3(6). Although five subsystems are shown as being under the control of the vehicle control system 1, in reality, a greater number of vehicle subsystems 3(n) may be included on the vehicle and may be under the control of the vehicle control system 1. Vehicle 5 includes multiple vehicle sensors 13(n), and these sensors reflect various different parameters associated with the vehicle's motion and state.

[0069] like Figure 2 As shown, the transmission system 3 (2) includes a transmission 21 that can be selectively operated to engage one of a plurality of gear ratios. Gear ratios typically include a plurality of forward gear ratios, a reverse gear ratio, and a neutral (or disengaged) gear ratio. The transmission system 3 (2) in this embodiment also includes a transfer case 23 that can be selectively operated to engage a low gear ratio. The transfer case 23 can be omitted from the transmission system 3 (2). The suspension system 3 (5) in this embodiment is a height-adjustable suspension. The suspension system 3 (5) can be, for example, an air suspension or a mechanically adjustable suspension. The suspension system 3 (5) includes a plurality of height-adjustable suspension units 15 (1) to 15 (4) associated with corresponding wheels 9 (1) to 9 (4) of the vehicle 5. The height of the suspension system 3 (5) can be controlled, for example, by controllably inflating and deflating one or more airbags disposed in suspension units 15 (1) to 15 (4) to raise or lower the vehicle body. The differential system 3 (6) includes one or more lockable differentials, such as a center differential, a rear differential, and a front differential. The differential system 3 (6) in this embodiment includes a center differential (in...) Figure 2 (Indicated by reference numeral 17 in the attached figure).

[0070] The vehicle control system 1 includes a vehicle control unit 7. For example... Figure 3The vehicle control unit 7 shown includes a controller 110, but it should be understood that this is merely illustrative. The controller 110 includes a processing unit 120 and a memory unit 130. The processing unit 120 may be one or more electronic processing units 120 operably executing computer-readable instructions. The memory unit 130 may be one or more memory units 130. The memory unit 130 is electrically coupled to the processing unit 120. The memory unit 130 is configured to store instructions, and the processing unit 120 is configured to access the memory unit 130 and execute the instructions stored thereon. The controller 110 includes an input unit 140 and an output unit 150. The input unit 140 may include an electrical input 140 of the controller 110. The output unit 150 may include an electrical output 150 of the controller 110.

[0071] The vehicle control unit 7 is configured to output control signals 155 to control one or more of the subsystems 3. The control signals 155 configure the subsystems 3(n) in a manner suitable for the driving conditions of the vehicle 5. The control signals 155 may, for example, configure the subsystems to control the vehicle 5 based on a determination of the type or category of terrain on which the vehicle is operating (referred to as terrain condition). The control signals 155 include electrical signals 155 output from electrical output 150.

[0072] The vehicle control unit 7 receives multiple input signals 160 from vehicle sensors 13(n) disposed on the vehicle 5. The input signals 160 represent various parameters associated with vehicle motion and state. The input signals 160 provide or are used to calculate multiple terrain indication parameters 165(n), which indicate the type or category of terrain on which the vehicle 5 operates. The vehicle control unit 7 is configured to determine a suitable control strategy for one or more of the vehicle subsystems 3 based on the terrain indication parameters 165(n). In this embodiment, the vehicle control unit 7 is configured to classify the terrain into one of the following terrain types: road; grass / gravel / snow; mud and ruts; sand; and rock. The terrain classification can be modified, for example, to include fewer terrain types or additional terrain types.

[0073] Multiple subsystem control modes 170(n) are predefined. Each of the multiple subsystem control modes 170(n) corresponds to one of the terrain types. The vehicle control unit 7 is configured to select one of the multiple subsystem control modes 170(n) based on one or more of the multiple terrain indication parameters 165(n). A mode selection probability (weighted) 31(n) is calculated for each of the subsystem control modes 170(n) based on the terrain indication parameter 165(n). The vehicle control unit 7 selects one of the subsystem control modes 170(n) based on the calculated mode selection probability. The mode selection probabilities of the subsystem control modes 170(n) are compared with each other to determine which of the multiple subsystem control modes 170(n) is suitable for the current operating condition. The vehicle control unit 7 may, for example, integrate the mode selection probability 31(n) of each of the subsystem control modes 170(n). The integral determines the "positive difference" between the calculated mode selection probability 31(n) of the currently selected subsystem control mode 170(n) and the calculated mode selection probability 31(n) of each of the other subsystem control modes 170(n). When the integral value exceeds a predetermined threshold, or when the current subsystem control mode selection probability 31(n) is equal to zero or lower than the predetermined threshold, the vehicle control unit 7 can change the selected subsystem control mode 170(n).

[0074] Each of the multiple subsystem control modes 170(n) is associated with a corresponding terrain classification in the terrain classification. The subsystem control modes 170(n) include the following: general driving control mode 170(1); grass / gravel / snow (GGS) control mode 170(2); mud and ruts control mode 170(3); sand control mode 170(4); and rock crawling control mode 170(5). General driving control mode 170(1) is suitable for highway driving and can, for example, configure the suspension to prioritize comfort. Grass / gravel / snow (GGS) control mode 170(2) can adapt the throttle response and configure the transmission to prioritize traction. Mud and ruts control mode 170(3) can allow increased wheel rotation to enable passage through muddy terrain. Sand control mode 170(4) can map the throttle response to help maintain momentum through sand. Rock crawl control mode 170 (5) may include configuring the throttle or torque graph of the electric drive unit 11 to perform rock crawl maneuvers. In the case of a vehicle 5 including an internal combustion engine, rock crawl control mode may include selecting a low gear ratio (e.g., by engaging the transfer case).

[0075] Sensor 13(n) is configured to measure operating parameters of vehicle 5 and output sensor signal 25(n) providing an indication of the measured operating parameters. Sensor signal 25(n) is supplied to vehicle control unit 7 as input signal 160. Sensor signal 25(n) is an electrical signal. In this embodiment, sensor 13(n) is configured to provide a continuous (i.e., uninterrupted) indication of the operating parameters. Sensor signal 25(n) can provide a quantified representation of the measured operating parameters.

[0076] The sensors 13(n) in this embodiment include: a wheel speed sensor 13(1) for measuring the speed of each of the wheels 9(1) to 9(4); a vehicle pitch angle sensor 13(2); a yaw angle sensor 13(3); a longitudinal acceleration sensor 13(4); an ambient temperature sensor 13(5); a torque sensor (or torque estimator) 13(6); a slope sensor (or slope estimator) 13(7); a brake pedal position sensor 13(8); an accelerator pedal position sensor 13(9); and longitudinal, lateral, and vertical motion sensors 13(10). The wheel speed sensor 13(1) outputs a wheel speed signal 25(1) indicating the measured wheel speed of each wheel 9(1) to 9(4). The vehicle pitch angle sensor 13(2) outputs a vehicle pitch angle signal 25(2) indicating the measured vehicle pitch angle of the vehicle 5 (i.e., the measured rotation of the vehicle 5 about the lateral axis Y). Yaw angle sensor 13 (3) outputs yaw angle signal 25 (3), which indicates the measured yaw angle of vehicle 5 (i.e., the measured rotation of vehicle 5 about the vertical axis Z). Longitudinal acceleration sensor 13 (4) outputs longitudinal acceleration signal 25 (4), which indicates the measured longitudinal acceleration of vehicle 5 (i.e., the acceleration of vehicle 5 along the longitudinal axis X). Ambient temperature sensor 13 (5) outputs ambient temperature signal 25 (4), which indicates the measured temperature of vehicle 5. Torque sensor 13 (6) outputs torque signal 25 (6), which indicates the torque (Nm) generated by electric drive unit 11 (and / or internal combustion engine). Slope sensor 13 (7) outputs slope signal 25 (7), which indicates the measured or estimated slope of the road surface on which vehicle 5 is operating. Brake pedal sensor 13 (8) outputs brake pedal signal 25 (8), which indicates the position of the brake pedal (not shown), for example, the degree to which the brake pedal is depressed. Accelerator pedal sensor 13 (9) outputs accelerator pedal signal 25 (9), which indicates the position of the accelerator pedal (not shown), for example, the degree to which the accelerator pedal is depressed. Longitudinal, lateral, and vertical motion sensors 13 (10) output motion signals indicating the motion of vehicle 5 along each reference axis X, Y, and Z. Vehicle 5 may include an inertial measurement unit (not shown). The inertial measurement unit may, for example, include one or more accelerometers. One or more of pitch angle sensor 13 (2), yaw angle sensor 13 (3), longitudinal acceleration sensor 13 (4), and longitudinal, lateral, and vertical motion sensors 13 (10) may be incorporated into the inertial measurement unit.

[0077] As outlined above, the vehicle control unit 7 is configured to select one of a plurality of subsystem control modes 170(n) corresponding to the current type or classification of terrain. A mode selection probability (weighted) 31(n) is determined for each of the subsystem control modes 170(n). The mode selection probability 31(n) provides an indication of the likelihood that the associated subsystem control mode 170(n) is suitable for the type or category of terrain on which the vehicle 5 operates. The mode selection probability 31(n) may include, for example, one or more of the following:

[0078] 1. General driving mode selection probability 31 (1) associated with general driving control mode 170 (1).

[0079] 2. Grassland / Gravel / Snow (GGS) control pattern selection probability 31 (2) associated with Grassland / Gravel / Snow (GGS) control pattern 170 (2).

[0080] 3. Mud and rut pattern selection probabilities 31 (3) associated with mud and rut control pattern 170 (3).

[0081] 4. Sandy pattern selection probability 31(4) associated with sandy control pattern 170(4).

[0082] 5. Rock crawling mode selection probability 31 (5) associated with rock crawling control mode 170 (5).

[0083] The mode selection probability 31(n) is determined based on one or more of the terrain indication parameters 165(n). As described herein, the terrain indication parameters 165(n) can be derived from operating parameters measured by the sensor 13(n). Alternatively or additionally, the mode selection probability 31(n) can be determined based on one or more probability maps 29(n). The probability maps 29(n), or each probability map 29(n), can define a terrain indication probability component 33(A) to 33(E) associated with one of the terrain indication parameters 165(n). The mode selection probability 31(n) is determined relative to one or more terrain indication probability components 33(A) to 33(E).

[0084] The operation of vehicle control unit 7 is described herein with particular reference to sand control mode 170 (4). Sand control mode 170 (4) is selected to configure one or more of subsystems 3 (n) for vehicle operation on terrain classified as sand (e.g., on sand dunes). It should be understood that the methods and systems described herein can be used to select one of other control modes 170 (n). As described herein, the sand mode selection probability 31 (4) is determined based on the rolling resistance (Nm) 90 of vehicle 5. Rolling resistance 90 represents the force resisting the movement of vehicle 5 on the terrain. Rolling resistance 90 on a flat surface (i.e., without slope) can be calculated using the following equation:

[0085] [1]

[0086] Where: Frr is the rolling resistance (Nm);

[0087] f is the rolling resistance coefficient;

[0088] m is the vehicle mass (kg); and

[0089] g is the acceleration due to gravity (9.81 m / s²). 2 ).

[0090] The rolling resistance 90 on an inclined road surface (with a slope α) can be calculated using the following equation:

[0091] [2]

[0092] Where: Frr is the rolling resistance (Nm);

[0093] f is the rolling resistance coefficient;

[0094] m is the vehicle mass (kg);

[0095] g is the acceleration due to gravity (9.81 m / s²). 2 );as well as

[0096] α is the slope (°).

[0097] For deformable surfaces such as sand, the rolling resistance coefficient f is relatively large. When vehicle 5 traverses terrain with deformable surfaces (e.g., terrain including or composed of sand), the rolling resistance 90 increases. In this example, the terrain is in the form of dunes. Dunes are typically composed of relatively deep sand. Dunes can be composed of sand with a depth greater than or equal to 150 mm. Sand with a depth greater than 150 mm is referred to as “deep sand” in this document. It should be understood that sand can have a depth less than or greater than 150 mm. The probability of selecting the sand mode 31 (4) can be increased based on the determination that the rolling resistance 90 is above a threshold to facilitate the selection of the sand control mode 170 (4).

[0098] When traversing terrain primarily composed of sand, it has been recognized that variations in road surface conditions affect rolling resistance 90. These variations may include localized areas with different mechanical properties than the surrounding areas. Localized areas may, for example, be less deformable than the surrounding areas. Localized areas may include hard-packed pavement that is less deformable than the surrounding sand. Alternatively or additionally, localized areas may consist of sand with a different depth than the surrounding areas (e.g., a reduced depth compared to the surrounding areas). Variations in road surface conditions result in variations in the rolling resistance 90 of vehicle 5. For example, rolling resistance 90 may decrease as vehicle 5 traverses localized areas with relatively hard pavement and / or reduced depth. The reduction in rolling resistance 90 may reduce the sand mode selection probability 31 (4). For example, the sand mode selection probability 31 (4) may be reduced based on the determination that rolling resistance 90 is below a rolling resistance threshold. The reduction in the sand mode selection probability 31 (4) may cause vehicle control unit 7 to deselect sand control mode 170 (4) and select one of other subsystem control modes 170 (n). The vehicle control unit 7 can, for example, change from sand control mode 170 (4) to general driving control mode 170 (1). For example, if the change in the selected subsystem control mode 170 (n) is caused by a local change in road conditions, the change may be inappropriate. In the example above, if the vehicle 5 passes through a local area of ​​the terrain with a less deformable road surface and then returns to sand, which can deform more easily, the general driving mode 170 (1) may be inappropriate.

[0099] In some cases, selecting or deselecting the subsystem control mode 170(n) due to local changes in road conditions may be inappropriate. To reduce or prevent inappropriate selection and / or deselection of the subsystem control mode 170(n), multiple probability maps 29(n) are defined. The multiple probability maps 29(n) are stored in the memory device 130 and accessed by the controller 110. Each of the probability maps 29(n) defines the relationship between terrain indication probability components 33(A) to 33(E) and associated terrain indication parameters 165(n). The subsystem mode selection probability 31 can be determined based on one or more of the terrain indication probability components 33(A) to 33(E). In this embodiment, each of the multiple probability maps 29(n) defines a rolling resistance probability component 33(A) associated with the rolling resistance 90 of the vehicle 5. As described herein, the sand mode selection probability 31 (4) is determined based on the rolling resistance probability component 33(A) defined by the probability map 29(n).

[0100] In this embodiment, the plurality of probability maps 29(n) include at least a first probability map 29(1) and a second probability map 29(2). Each of the first probability map 29(1) and the second probability map 29(2) defines a rolling resistance probability component 33(A) relative to the rolling resistance 90. The first probability map 29(1) and the second probability map 29(2) are different from each other. As described herein, the rolling resistance probability component 33(A) is determined based on one of the first probability map 29(1) and the second probability map 29(2). The first probability map 29(1) and the second probability map 29(2) are illustrated by way of example. Figure 4 The first probability plot 29(1) defines a first relationship between the rolling resistance probability component 33(A) and the rolling resistance 90. The first probability plot 29(1) represents a standard (or default) probability plot used to determine the sand mode selection probability 31(4). The second probability plot 29(2) defines a second relationship between the rolling resistance probability component 33(A) and the rolling resistance 90. The second probability plot 29(2) represents a modified probability plot used to determine the sand mode selection probability 31(4) when the vehicle 5 is operating in deep sand. One of the first probability plot and the second probability plot 29(2) is selected based on the determined rolling resistance 90 of the vehicle 5. As described herein, one of the first probability plot 29(1) and the second probability plot 29(2) is selected based on the moving average of the determined rolling resistance 90.

[0101] The first probability plot 29(1) represents the default rolling resistance probability component 33(A) used to determine the sand mode selection probability 31(4). The second probability plot 29(2) represents the non-standard rolling probability component 33(A) used to determine the sand mode selection probability 31(4) when the vehicle is operating in deep sand (e.g., when vehicle 5 is crossing a sand dune). Figure 4 As shown, the first probability plot 29(1) and the second probability plot 29(2) include corresponding first and second functions, which define the relationship between the rolling resistance probability component 33(A) and the rolling resistance 90 of the vehicle 5. The rolling resistance probability component 33(A), defined by the first probability plot 29(1) and the second probability plot 29(2), increases with the increase of the rolling resistance 90. In this embodiment, the relationship between the rolling resistance probability component 33(A) and the rolling resistance 90 is non-linear. Figure 4 As shown, the first probability plot 29(1) and the second probability plot 29(2) each include an S-curve. Each S-curve includes a convex portion and a concave portion connected by a central (transition) portion. The slope (gradient) of the central portion of the second probability plot 29(2) is greater than the slope (gradient) of the corresponding central portion of the first probability plot 29(1). The rolling resistance probability component 33(A) defined by the second probability plot 29(2) increases faster than the rolling resistance probability component 33(A) defined by the first probability plot 29(1) relative to the rolling resistance 90. By comparison, in Figure 4 The third probability plot 29(3) is shown. The third probability plot 29(3) represents the rolling resistance probability component 33(B) used to determine the grass / gravel / snow (GGS) mode selection probability 31(2) relative to the rolling resistance 90. The grass / gravel / snow (GGS) mode selection probability 31(2) is determined based on the rolling resistance probability component 33(B). The rolling resistance probability component 33(B), as defined by the third probability plot 29(3), decreases as the rolling resistance 90 increases. The third probability plot 29(3) includes an inverted S-shaped curve (inverted S-curve). It should be understood that an additional probability plot 29(n) may be defined.

[0102] The vehicle control unit 7 is configured to select one of a plurality of probability maps 29(n) to determine the terrain indication probability component 33 (AE). The selection of one of the plurality of probability maps 29(n) is performed based on one or more of the terrain indication parameters 165(n). In this embodiment, one of the first probability map 29(1) and the second probability map 29(2) is selected based on the moving average 95 of the rolling resistance 90 (referred to herein as the rolling resistance moving average 95). The vehicle control unit 7 is configured to calculate the rolling resistance moving average 95 over a predetermined time period (e.g., 2 seconds, 3 seconds, 5 seconds, or 10 seconds). The time period can be calibrated, for example, based on empirical data. The rolling resistance moving average 95 is compared with a rolling resistance threshold TH1. In this embodiment, the rolling resistance threshold TH1 is defined as 2000 Nm. The rolling resistance threshold TH1 can be greater than or less than 2000 Nm. The determination of an appropriate rolling resistance threshold TH1 is described herein with reference to sample data acquired when the vehicle 5 operates on terrain including or composed of sand. The first probability plot 29(1) is selected based on the determination that the moving average of rolling resistance 95 is less than the rolling resistance threshold TH1. The second probability plot 29(2) is selected based on the determination that the moving average of rolling resistance 95 is greater than the rolling resistance threshold TH1.

[0103] Figure 5 The diagram shows a first graph 300 illustrating a set of sample data. The sample data represents the rolling resistance 90 when vehicle 5 traverses terrain including or composed of deep sand (e.g., when vehicle 5 traverses sand dunes). The first plotted line 305 represents the instantaneous value of the rolling resistance 90 of vehicle 5. The second plotted line 310 represents the moving average of the rolling resistance 95. Figure 5As shown, rolling resistance 90 includes short-term fluctuations when vehicle 5 traverses deep sand. Short-term fluctuations of rolling resistance 90 include peaks and troughs that may be caused by local changes in terrain. A trough in the first trajectory 305 indicates a short-term decrease in rolling resistance 90, for example, caused by vehicle 5 traversing a compacted sandy area. Conversely, a peak in the first trajectory 305 indicates a short-term increase in rolling resistance 90, for example, caused by vehicle 5 traversing a sandy area with greater depth. Even if the type of terrain does not change, short-term fluctuations of rolling resistance 90 may reduce the sand mode selection probability 31 (4). The reduced sand mode selection probability 31 (4) increases the likelihood that one of the other subsystem control modes 170 (n) will be selected. In the example shown, it has been determined that when the rolling resistance drops below 4000 Nm, the likelihood of selecting general driving control mode 170 (1) instead of sand control mode 170 (4) increases. The regions t1 to t5 highlighted in the first graph 300 represent the operating windows in the sample data where the general driving control mode 170(1) can be selected instead of the sand control mode 170(4). If the mode selection probability 31(n) changes due to changes in terrain (e.g., a change in terrain type from sand to road), then a change to the general driving control mode 170(1) would be appropriate. However, in this example, since the terrain type does not change, the selection of the general driving control mode 170(1) is inappropriate. Instead, the reduced sand mode selection probability 31(4) is at least partly caused by short-term fluctuations in the rolling resistance 90.

[0104] like Figure 5 As shown, a rolling resistance moving average 95 is calculated to reduce or eliminate short-term fluctuations. The calculation of the rolling resistance moving average 95 effectively filters out the rolling resistance 90. Then, the rolling resistance moving average 95 is compared with a rolling resistance threshold TH1 to select one of several probability profiles 29(n). The rolling resistance threshold TH1 is defined as reducing the impact of short-term variations in rolling resistance 90 on the sand pattern selection probability 31(4). In this embodiment, the rolling resistance threshold TH1 is defined as 2000 Nm. Figure 5 As shown, short-term fluctuations in rolling resistance 90 decrease to below the rolling resistance threshold TH1 within the sample data. However, for most of the sample data, the moving average of rolling resistance 95 remains above the rolling resistance threshold TH1.

[0105] The vehicle control unit 7 is configured to select one of a first probability map 29 (1) and a second probability map 29 (2) based on the rolling resistance moving average 95. The rolling resistance moving average 95 is compared with a rolling resistance threshold TH1 to select one of the first probability map 29 (1) and the second probability map 29 (2). The first probability map 29 (1) is selected based on the determination that the rolling resistance moving average 95 is less than the rolling resistance threshold TH1. The second probability map 29 (2) is selected based on the determination that the rolling resistance moving average 95 is greater than the rolling resistance threshold TH1. Then, the rolling resistance 90 is compared with one of the selected first probability map 29 (1) and the second probability map 29 (2) to determine the rolling resistance probability component 33 (A). Thus, the rolling resistance probability component 33 (A) is determined based on the instantaneous (i.e., current) rolling resistance 90 of the vehicle 5. The sand mode selection probability 31 (4) is determined based on the rolling resistance probability component 33 (A) derived from one of the selected first probability map 29 (1) and the second probability map 29 (2).

[0106] The determined sand mode selection probability 31(4) is compared with the determined mode selection probability 31(n) for each of the other subsystem control modes 170(n). The vehicle control unit 7 is configured to select one of the multiple subsystem control modes 170(n) based on the determined mode selection probability 31(n). As described herein, the vehicle control unit 7 integrates the determined mode selection probability 31(n) for each of the subsystem control modes 170(n). The integration determines a positive difference between the selected subsystem control mode 170(n) mode selection probability 31(n) and the mode selection probability 31(n) for each of the other subsystem control modes 170(n). The subsystem control mode 170(n) with the largest positive difference is selected. The vehicle control unit 7 is configured to output a control signal 155 to control one or more of the subsystems 3. The control signal 155 indicates the selected subsystem control mode 170(n). The subsystem 3 is controlled according to the control signal 155.

[0107] It should be understood that different terrain indication parameters 165(n) can be used for the selection of the probability map 29(n) and the determination of the terrain indication probability component 33(AE). A first terrain indication parameter 165(n) can be used to select the probability map 29(n); and a second terrain indication parameter 165(n) can be used to iterate through the selected probability map 29(n) to determine the terrain indication probability component 33(AE). The first terrain indication parameter 165(n) and the second terrain indication parameter 165(n) are different from each other. However, regarding the determination of the rolling resistance probability component 33(A), the rolling resistance 90 (and the rolling resistance moving average 95) are suitable for determining the rolling resistance probability component 33(A).

[0108] The rolling resistance probability component 33(A) can be directly derived from one of the first probability plots 29(1) and the second probability plot 29(2). The sandy terrain selection probability 31(4) is determined based on the rolling resistance probability component 33(A). The sandy terrain selection probability 31(4) can be determined based on one or more terrain indication parameters 165(n). One or more terrain indication parameters 165(n) can include rolling resistance 90. The sandy terrain selection probability 31(4) can correspond to the rolling resistance probability component 33(A). Alternatively, the sandy terrain selection probability 31(4) can be determined based on multiple terrain indication parameters 165(n). The sandy terrain selection probability 31(4) can be determined based on multiple rolling resistance probability components 33(A). The rolling resistance probability component 33(A), or each rolling resistance probability component 33(A), can be determined based on one or more of multiple terrain indication parameters 165(n). The sandy terrain selection probability 31(4) can be determined by summing multiple rolling resistance probability components 33(A).

[0109] The determination of the sand mode selection probability 31 (4) is described above with reference to the rolling resistance probability component 33 (A) determined based on the rolling resistance 90 of vehicle 5. Alternatively or additionally, the sand mode selection probability 31 (4) can be determined based on other terrain indication parameters 165 (n) (e.g., the vehicle body pitch angle and / or yaw angle of vehicle 5). As mentioned above, the vehicle body pitch angle signal 25 (2) indicates the measured vehicle body pitch angle α; and the yaw angle signal 25 (3) indicates the measured yaw angle γ. The pitch angle probability component 33 (B) can be determined based on the vehicle body pitch angle of vehicle 5. The pitch angle probability component 33 (B) can be proportional to the magnitude of the pitch angle or the rate of change of the pitch angle. Alternatively or additionally, the yaw angle probability component 33 (C) can be determined based on the yaw angle of vehicle 5. The yaw angle probability component 33 (C) can be proportional to the magnitude of the yaw angle or the rate of change of the yaw angle. The sand mode selection probability 31(4) can be determined based on one or more of the following: rolling resistance probability component 33(A); pitch probability component 33(B); and yaw probability component 33(C). For example, the sand mode selection probability 31(4) can include the sum of the following: rolling resistance probability component 33(A); pitch probability component 33(B); and yaw probability component 33(C).

[0110] The measured vehicle pitch angle and the measured yaw angle typically include short-term fluctuations. These short-term fluctuations may cause changes in one or more of the mode selection probabilities 31(n). It has been determined that these changes may lead to inappropriate selection or deselection of one or more of the subsystem control modes 170(n). In particular, it has been determined that the sand control mode 170(4) can be selected or deselected due to short-term fluctuations in the measured vehicle pitch angle and the measured yaw angle.

[0111] In this embodiment, the vehicle control unit 7 is configured to modulate one or more of the sensor signals 25(n) to generate terrain indication parameters 165(n). In this embodiment, the vehicle control unit 7 is configured to perform hold-and-step-down signal modulation on one or more of the sensor signals 25(n). Hold-and-step-down signal modulation involves holding a peak in the sensor signal 25(n) for a calibrable time period, and then controlling the attenuation of the sensor signal 25(n) at a calibrable rate until the input sensor signal 25(n) exceeds the peak again. Hold-and-step-down signal modulation is performed for each peak in the operating parameters. The reduction in the amplitude of the sensor signal 25(2) is interrupted by a peak having a larger amplitude than the modulated signal. A mode selection probability associated with each of the plurality of subsystem control modes 170(n) is calculated based on the modulated sensor signal 25(n). Hold-and-step-down signal modulation is effective in extending the duration of peaks in the operating parameters. This can help reduce short-term fluctuations in the calculated mode selection probabilities of each of the subsystem control modes 170(n). This can reduce or suppress changes in the subsystem control mode 170(n). The vehicle control unit 7 is configured to apply a hold-and-step descent function to the vehicle pitch angle signal 25(2) to generate a modulated vehicle pitch angle signal 25'(2). Alternatively or additionally, the vehicle control unit 7 is configured to apply a hold-and-step descent function to the yaw angle signal 25(3) to generate a modulated yaw angle signal 25'(3).

[0112] Figure 6A and Figure 6B The pitch angle signal 25 (2) and yaw angle signal 25 (3) of the vehicle body are used to illustrate the hold and stepped descent signal modulation. Figure 6A The first graph 50 is shown as an example. The first graph 50 includes a first vehicle pitch trajectory 55 representing the raw vehicle pitch angle signal 25 (2) received from the vehicle pitch angle sensor 13 (2); and a second vehicle pitch trajectory 60 representing the modulated vehicle pitch angle signal 25′ (2). Figure 6BThe second graph 70 is shown as an example. The second graph 70 includes a first yaw angle trajectory 75 representing the yaw angle signal 25 (3) received from the yaw angle sensor 13 (3); and a second yaw angle trajectory 80 representing the modulated yaw angle signal 25′ (3). The vehicle control unit 7 is configured to determine the pitch angle probability component 33 (B) based on the modulated vehicle pitch angle signal 25′ (2); and to determine the yaw angle probability component 33 (C) based on the modulated yaw angle signal 25′ (3).

[0113] Figure 7 The second plot 350, which shows the sand mode selection probability 31 (4), is shown in the diagram. The second plot 350 is compiled using the sample data represented in the first plot 300. As described herein, sample data is captured when the vehicle 5 is operating on deep sand, for example, when the vehicle 5 is crossing a sand dune. The first trajectory 360 represents the sand mode selection probability 31 (4) generated based on the pitch probability component 33 (B) and the yaw probability component 33 (C) generated using the modulated vehicle pitch angle signal 25' (2) and the modulated yaw angle signal 25' (3). For comparison, the second trajectory 370 represents the reference sand mode selection probability 31 (4) generated based on the original vehicle pitch angle signal 25 (2) and the original yaw angle signal 25' (3). The second trajectory 370 includes three regions t1 to t3, in which the reference sand mode selection probability 31 (4) decreases due to road conditions. In each of the regions t1 to t3, the reference sand mode selection probability 31 (4) is less than 0.5. The reduction in the sand mode selection probability 31(4) increases the likelihood that the sand control mode 170(3) will be deselected and one of the other subsystem control modes 170(n) will be selected. In contrast, the first trajectory 370 represents a sand mode selection probability 31(4) that is always greater than 0.5. Furthermore, the sand mode selection probability 31(4) generated based on the modulated vehicle pitch angle signal 25'(2) and the modulated yaw angle signal 25'(3) includes fewer short-term fluctuations. This can reduce the likelihood of inappropriate (or improper) selection or deselection of the sand control mode 170(4).

[0114] At least in some embodiments, the techniques described herein can be combined to control the selection of sand control mode 170 (4). The sand mode selection probability 31 (4) can be determined based on a plurality of terrain indication parameters 165 (n). The plurality of terrain indication parameters 165 (n) can include one or more of the following: rolling resistance 90, vehicle pitch angle, and vehicle yaw angle. Driving on sand produces unique driving events that can be identified to indicate terrain type. For example, high yaw gain and / or regular vehicle pitch are indications that vehicle 5 is operating on sand. A separate terrain indication probability component 33 (AE) can be determined for each of the plurality of terrain indication parameters 165 (n). The sand mode selection probability 31 (4) is determined based on each of the terrain indication probability components 33 (AE). For example, the sand mode selection probability 31 (4) can be determined by summing the individual terrain indication probability components 33 (AE). The sand mode selection probability 31 (4) is then compared with other mode selection probabilities 31 (n) to select subsystem control mode 170 (n). Figure 8 A block diagram is shown representing a method 400 for implementing these functions. In the arrangement shown, the sand mode selection probability 31 (4) is determined based on the rolling resistance 90 and at least one of the vehicle pitch angle and the vehicle yaw angle.

[0115] Method 400 includes determining the rolling resistance 90 of vehicle 5 (box 405). A rolling resistance moving average 95 is determined based on the rolling resistance 90 (box 410). One of a plurality of probability maps 29(n) is selected (box 415). The plurality of probability maps 29(n) are predefined, and each probability map defines the relationship between a terrain indication probability component 33 (AE) and one or more terrain indication parameters 165(n). In the arrangement shown, the probability map 29(n) is selected from one of three (3) predefined probability maps 29(1) to 29(3). The rolling resistance moving average 95 can be compared with one or more rolling resistance thresholds TH1 to select the probability map 29(n). It should be understood that fewer or more than three (3) probability maps 29(1) to 29(3) can be defined. The probability map 29(n) is selected based on the rolling resistance moving average 95. The rolling resistance probability component 33(A) is determined based on the selected probability map 29(n) (box 420). Based on the (instantaneous) rolling resistance 90 of vehicle 5, the rolling resistance probability component 33 (A) is derived from the selected probability spectrum 29 (n). The rolling resistance probability component 33 (A) is output (box 425).

[0116] The vehicle pitch angle signal 25(2) is received from the vehicle pitch angle sensor 13(2) (box 430). The vehicle pitch angle signal 25(2) is an unfiltered electrical signal representing the vehicle pitch angle. The vehicle pitch angle signal 25(2) is modulated by applying a hold-and-step descent function (box 435). The pitch angle probability component 33(B) is determined based on the modulated vehicle pitch angle signal 25′(2) (box 440). The pitch angle probability component 33(B) can be increased based on the detection of a pitch angle event indicating passage through a dune. The pitch angle event can be detected by identifying a characteristic pattern in the vehicle pitch angle. The characteristic pattern can, for example, have a predefined frequency and / or amplitude. The characteristic pattern can be defined relative to a frequency range and / or amplitude range. The pitch angle probability component 33(B) is output (box 445).

[0117] Yaw angle signal 25(3) is received from yaw angle sensor 13(3) (box 450). Yaw angle signal 25(3) is an unfiltered electrical signal representing the yaw angle. Yaw angle signal 25(3) is modulated by applying a hold-and-step descent function (box 455). Yaw angle probability component 33(C) is determined based on the modulated vehicle pitch angle signal 25′(3) (box 460). Yaw angle probability component 33(C) can be increased based on the detection of a yaw angle event indicating crossing a dune. Yaw angle events can be detected by identifying a characteristic pattern in the yaw angle. The characteristic pattern can, for example, have a predefined frequency and / or amplitude. The characteristic pattern can be defined relative to a frequency range and / or amplitude range. Yaw angle probability component 33(C) is output (box 465).

[0118] The sandy terrain selection probability 31(4) is determined based on the rolling resistance probability component 33(A), the pitch angle probability component 33(B), and the yaw angle probability component 33(C) (box 470). The sandy terrain selection probability 31(4) is output (box 475). The selection probabilities 31(n) are compared with each other (box 480). The control pattern 170(n) corresponding to the terrain with the highest selection probability 31(n) is selected (box 485).

[0119] It should be understood that the mode selection probability 31(n) can be determined based on other terrain indication parameters 165(n). The mode selection probability 31(n) can be determined based on road surface roughness. The road surface roughness probability component 33(D) can be determined based on the measured road surface roughness. The road surface roughness probability component 33(D) can decrease as the road surface roughness increases. The mode selection probability 31(n) can be determined based on road surface friction. The road surface friction probability component can be determined based on the estimated road surface friction. In alternative or additional locations, the mode selection probability 31(n) can be determined based on vehicle speed. The vehicle speed probability component 33(E) can be determined based on vehicle speed. The vehicle speed probability component 33(D) can decrease as the vehicle speed increases. The sand mode selection probability 31(4) can be determined, for example, based on one or more of the following: rolling resistance probability component 33(A), pitch angle probability component 33(B), yaw angle probability component 33(C) (box 470), road surface roughness probability component 33(D), and vehicle speed probability component 33(E).

[0120] One or more entry conditions can be defined for selecting subsystem control mode 170(n). For example, one or more of vehicle speed, ambient temperature, and road surface roughness can be used as entry conditions. The selection of sand control mode 170(4) can be controlled based on whether the entry conditions are met. For example, the selection of sand control mode 170(4) can be disabled (suppressed) based on determining that the vehicle speed is greater than a speed threshold. The selection of sand control mode 170(4) can be enabled based on determining that the vehicle speed is less than a speed threshold. Alternatively or additionally, the selection of sand control mode 170(4) can be disabled (suppressed) based on determining that the ambient temperature is less than a predefined temperature threshold (e.g., 15°C). The selection of sand control mode 170(4) can be enabled based on determining that the ambient temperature is greater than a predefined temperature threshold. Alternatively or additionally, the selection of sand control mode 170(4) can be disabled (suppressed) based on determining that the road surface roughness is greater than a predefined road surface roughness threshold. The selection of sand control mode 170(4) can be enabled based on determining that the road surface roughness is less than a predefined road surface roughness threshold.

[0121] It should be understood that various changes and modifications can be made to this invention without departing from the scope of this application.

Claims

1. A control system for controlling the selection of one of a plurality of subsystem control modes to control the operation of at least one vehicle subsystem of a vehicle, wherein each of the subsystem control modes corresponds to one or more different terrain types; wherein, The one or more different terrain types include a first terrain type corresponding to sandy land, and the subsystem control mode includes a first subsystem control mode corresponding to the first terrain type; the control system includes one or more processors, which are collectively configured to: Determine the rolling resistance of the vehicle; Determine the moving average value of the rolling resistance; One of multiple mode selection probability maps is selected based on a determined moving average, each of the multiple mode selection probability maps having a first terrain indication probability component associated with a first terrain indication parameter. A first mode selection probability associated with the first terrain type is determined, the first mode selection probability being determined based on a first terrain indication probability component derived from a mode selection probability map selected from the plurality of mode selection probability maps. as well as One of the multiple subsystem control modes is selected based on the determined first mode selection probability.

2. The control system according to claim 1, wherein, The first terrain indication parameter includes the rolling resistance of the vehicle, and each of the plurality of mode selection probability maps has a first terrain indication probability component that is associated with the rolling resistance of the vehicle.

3. The control system according to claim 1 or 2, wherein, Selecting one of the plurality of pattern selection probability maps involves comparing the determined moving average of the rolling resistance with a rolling resistance threshold.

4. The control system according to claim 3, wherein, The plurality of mode selection probability maps include a first mode selection probability map and a second mode selection probability map; the first mode selection probability map is selected based on determining that the moving average of the rolling resistance is greater than the rolling resistance threshold; the second mode selection probability map is selected based on determining that the moving average of the rolling resistance is less than the rolling resistance threshold.

5. The control system according to any one of claims 1 to 4, wherein, The one or more processors are collectively configured to: The second terrain indication probability component is determined based on the second terrain indication parameter; The first mode selection probability is determined based on the second terrain indication probability component.

6. The control system according to claim 5, wherein, The second terrain indication parameter includes the vehicle's yaw angle, and the one or more processors are collectively configured to: Receive a yaw angle signal indicating the yaw angle of the vehicle; A hold-and-step descent function is applied to the yaw angle signal to generate a modulated yaw angle signal; and The second terrain indication probability component is determined based on the modulated yaw angle signal.

7. The control system according to any one of the preceding claims, wherein, The one or more processors are collectively configured to: The probability component of the third terrain indication is determined based on the third terrain indication parameters; The first mode selection probability is determined based on the third terrain indication probability component.

8. The control system according to claim 7, wherein, The third terrain indication parameter includes the vehicle's pitch angle, and the one or more processors are collectively configured to: Receive a pitch angle signal indicating the vehicle's body pitch angle; A hold-and-step descent function is applied to the pitch angle signal to generate a modulated pitch angle signal; and The third terrain indication probability component is determined based on the modulated pitch angle signal.

9. The control system according to any one of the preceding claims, wherein, The one or more processors are collectively configured to: The selection of the control mode for the first subsystem is controlled based on one or more entry conditions; The one or more entry conditions include one or more of the following: ambient temperature, vehicle speed, and terrain roughness.

10. A vehicle comprising a control system according to any one of the preceding claims.

11. A control method for selecting one subsystem control mode from a plurality of subsystem control modes to control the operation of at least one subsystem of a vehicle, wherein each of the subsystem control modes corresponds to one or more different terrain types; wherein, The one or more different terrain types include a first terrain type corresponding to sandy land, and the subsystem control mode includes a first subsystem control mode corresponding to the first terrain type; wherein, the method includes: Determine the rolling resistance of the vehicle; Determine the moving average value of the rolling resistance; One of multiple mode selection probability maps is selected based on a determined moving average, each of the multiple mode selection probability maps having a first terrain indication probability component associated with a first terrain indication parameter. A first mode selection probability associated with the first terrain type is determined, the first mode selection probability being determined based on a first terrain indication probability component derived from a mode selection probability map selected from the plurality of mode selection probability maps; and One of the multiple subsystem control modes is selected based on the determined first mode selection probability.

12. A computer-readable instruction that, when executed by one or more processors, causes the one or more processors to perform the method according to claim 11.

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