System and method for maintaining stability of a motor vehicle

Abstract

A method of maintaining stability of a motor vehicle having a first axle, a second axle, and a steering actuator configured to steer the first axle, the method comprising determining a position and heading of the motor vehicle. The method further comprises determining a current side slip angle of the second axle and setting a maximum side slip angle of the second axle using a coefficient of friction at an interface of the vehicle and a road surface. The method further comprises predicting when the maximum side slip angle will be exceeded using the position and heading and the determined current side slip angle as inputs to a linear computational model. The method further comprises updating the model using the prediction of when the maximum side slip angle will be exceeded to determine an impending instability of the vehicle. Further, the method comprises correcting the impending instability via modifying a steering angle of the first axle using the updated model and the maximum side slip angle.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to systems and methods for maintaining stability of a motor vehicle. BACKGROUND

[0002] Autonomous vehicles include sensors operable to detect vehicle operation and the environment surrounding the vehicle, and computing devices operable to control all aspects of vehicle operation. Semi-autonomous vehicles operate in a similar manner, but can require some operator input, oversight, and / or control. Autonomous and semi-autonomous vehicles typically employ a vehicle navigation system integrated with vehicle controls to identify the location of the vehicle and determine guidance of the vehicle to a selected waypoint.

[0003] Generally, vehicle navigation systems use global positioning system (GPS) satellites to acquire its position data, which is then correlated to the location of the vehicle relative to the surrounding geographic area. Based on the GPS satellite signals, when guidance to a particular waypoint is needed, a route to such destination can be calculated, thereby determining the vehicle path. Specifically, the vehicle sensors and computing devices can cooperate to identify intermediate waypoints and maneuver the vehicle between such waypoints to keep the vehicle on a selected path.

[0004] The maneuvering of a motor vehicle, especially at higher speeds, is dependent on the traction of the vehicle, which is generally a function of the coefficient of friction at the interface between the vehicle and the road surface. Similar to operator-guided vehicles, when following a predetermined path, autonomous and semi-autonomous vehicles can experience a loss of traction at one or more wheels, thereby adversely affecting the stability and control of the vehicle. While in the case of operator-guided vehicles, the driving demands of the vehicle operator can play a role in such loss of traction, in the case of autonomous and semi-autonomous vehicles, the loss of traction is primarily a result of road conditions. SUMMARY

[0005] A method of maintaining stability of a motor vehicle having a first axle, a second axle, and a steering actuator configured to steer the first axle via a steering angle (Q), the method comprising determining, via an electronic controller, a position and a heading of the motor vehicle relative to a road surface. The method further comprises determining a current side slip angle (a) of the second axle. The method further comprises setting, via the electronic controller, a maximum side slip angle (a max ) of the second axle using a coefficient of friction (m) value at the interface between the motor vehicle and the road surface. The method further comprises predicting, via the electronic controller, when the maximum side slip angle (a max). The method also includes updating, via the electronic controller, a linear computational model using the prediction of when the maximum side slip angle (a max ) of the second axle will be exceeded to determine an impending instability of the motor vehicle. The method also includes, via the electronic controller, using the updated linear computational model and the maximum side slip angle (a max ) of the second axle to correct the impending instability via a command to a steering actuator to modify a steering angle (Q).

[0006] The motor vehicle can be configured to operate in an autonomous mode directed by the electronic controller. The determination of the position and heading of the motor vehicle can include, via the electronic controller, determining a desired path and discrete waypoints of the motor vehicle via receiving data from a global positioning satellite (GPS) and data from vehicle sensors, such as radar and lidar.

[0007] With respect to the vehicle heading, the first axle can be a front axle and the second axle can be a rear axle. In such embodiments, the instability of the motor vehicle can be an over-steer condition that ultimately results in a spin.

[0008] According to the method, determining the current side slip angle (a) of the second axle can include, via the electronic controller, receiving data indicative of a dynamic state of the motor vehicle from sensors mounted to the vehicle, the sensors including a yaw rate sensor to detect a yaw rate (ψ˙) of the motor vehicle, and at least one of a wheel sensor, a GPS, and an accelerometer to detect a longitudinal velocity (V x ) and a lateral velocity (V y ) of the motor vehicle.

[0009] The linear computational model can be embedded in a model predictive control (MPC) algorithm. According to the method, the MPC algorithm can be configured to determine the impending instability of the motor vehicle by repeatedly solving an open-loop finite horizon optimal control equation with constraints on the steering actuator, such as steering rate and angle limits (as a function of vehicle speed) and the maximum side slip angle (a max ) of the second axle.

[0010] According to the method, detecting the steering angle (Q) of the steering actuator can be done via a steering position sensor.

[0011] The steering actuator can be configured as an electric power assisted steering unit.

[0012] The maximum side slip angle (a max ) can be determined according to the relationship a max = µ * a. In such embodiments, μ is a coefficient of friction at the interface between the motor vehicle and the road surface.

[0013] According to the method, if μ < 0.3, the maximum side slip angle (a max ) can be in the range of 1-2 degrees. Further, if μ > 0.3, the maximum side slip angle (a max ) can be in the range of 3-4 degrees.

[0014] According to the method, if μ is unknown, the maximum side slip angle (a max ) can be set to 1 degree.

[0015] A motor vehicle having an electronic controller configured to perform the above method is also disclosed.

[0016] Scheme 1. A method of maintaining stability of a motor vehicle having a first axle, a second axle, and a steering actuator configured to steer the first axle via a steering angle (0), the method comprising:

[0017] determining, via an electronic controller, a position and heading of the motor vehicle relative to a road surface;

[0018] determining a current side slip angle (a) of the second axle;

[0019] setting, via the electronic controller, a maximum side slip angle (a max ) of the second axle using a value of a coefficient of friction (μ) at an interface between the motor vehicle and the road surface;

[0020] predicting, via the electronic controller, when the maximum side slip angle (a max ) of the second axle will be exceeded using the position and heading of the motor vehicle and the determined current side slip angle (a) of the second axle as inputs to a linear computational model;

[0021] updating, via the electronic controller, the linear computational model using the prediction of when the maximum side slip angle (a max ) of the second axle will be exceeded to determine an impending instability of the motor vehicle; and

[0022] correcting, via the electronic controller, the impending instability using the updated linear computational model and the maximum side slip angle (a max ) of the second axle by modifying the steering angle (0) via the command steering actuator.

[0023] Scheme 2. The method of Scheme 1, wherein:

[0024] the motor vehicle is configured to operate in an autonomous mode directed by the electronic controller; and

[0025] Determining the position and heading of the motor vehicle includes determining, via the electronic controller, a desired path and discrete waypoints of the motor vehicle via receiving data from a global positioning satellite (GPS).

[0026] Scheme 3. The method according to Scheme 2, wherein the first axle is a front axle and the second axle is a rear axle with respect to the vehicle heading, the instability of the motor vehicle is an oversteer condition, ultimately resulting in a spinout.

[0027] Scheme 4. The method according to Scheme 2, wherein determining the current side slip angle (a) of the second axle includes receiving, via the electronic controller, data indicative of the dynamic state of the motor vehicle from sensors mounted to the vehicle, the sensors including a yaw rate sensor for detecting a yaw rate (ψ˙) of the motor vehicle, and at least one of a wheel sensor, a GPS, and an accelerometer for detecting a longitudinal velocity (V x ) and a lateral velocity (V y ) of the motor vehicle.

[0028] Scheme 5. The method according to Scheme 4, wherein the linear computational model is embedded in a model predictive control (MPC) algorithm configured to determine an impending instability of the motor vehicle by repeatedly solving open-loop finite horizon optimal control equations with constraints on the steering actuator and a maximum side slip angle (a max ) of the second axle.

[0029] Scheme 6. The method according to Scheme 1, further comprising detecting a steering angle (0) of the steering actuator via a steering position sensor.

[0030] Scheme 7. The method according to Scheme 1, wherein the steering actuator is configured as an electric power assisted steering unit.

[0031] Scheme 8. The method according to Scheme 1, wherein the maximum side slip angle (a max ) is determined according to the relationship a max = μ * a, and wherein μ is a friction coefficient at the interface between the motor vehicle and a road surface.

[0032] Scheme 9. The method according to Scheme 1, wherein:

[0033] if μ < 0.3, then the maximum side slip angle (a max ) is in the range of 1-2 degrees; and

[0034] if μ > 0.3, then the maximum side slip angle (a max ) is in the range of 3-4 degrees.

[0035] Scheme 10. The method according to Scheme 1, wherein the maximum side slip angle (a max ) is set to 1 degree if μ is unknown.

[0036] Scheme 11. A motor vehicle comprising:

[0037] a first axle;

[0038] a second axle;

[0039] a steering actuator configured to steer the first axle via a steering angle (0);

[0040] a powertrain configured to transmit drive torque to the first axle and / or the second axle; and

[0041] an electronic controller configured to regulate the steering actuator and programmed to:

[0042] determine a position and heading of the motor vehicle relative to a road surface;

[0043] determine a current side slip angle (a) of the second axle;

[0044] set a maximum side slip angle (a max ) of the second axle using a value of a coefficient of friction (μ) at an interface between the motor vehicle and the road surface;

[0045] predict when the maximum side slip angle (a max ) of the second axle will be exceeded using the position and heading of the motor vehicle and the determined current side slip angle (a) of the second axle as inputs to a linear computational model;

[0046] update the linear computational model using the prediction of when the maximum side slip angle (a max ) of the second axle will be exceeded to determine an impending instability of the motor vehicle; and

[0047] correct the impending instability via a command to the steering actuator to modify the steering angle (0) using the updated linear computational model and the maximum side slip angle (a max ) of the second axle.

[0048] Scheme 12. The motor vehicle according to Scheme 11, wherein:

[0049] the motor vehicle is configured to operate in an autonomous mode directed by the electronic controller; and

[0050] the electronic controller is programmed to determine the position and heading of the motor vehicle by determining a desired path and discrete waypoints of the motor vehicle via receiving data from a global positioning satellite (GPS).

[0051] Option 13. The motor vehicle according to Option 12, wherein, relative to the vehicle's heading, the first axle is the front axle, the second axle is the rear axle, and the instability of the motor vehicle is an oversteering condition that ultimately leads to rotation in place.

[0052] Option 14. The motor vehicle according to Option 12, wherein the electronic controller is programmed to determine the current sideslip angle (α) of the second axle via data indicating the dynamic state of the motor vehicle received from sensors mounted to the vehicle, the sensors including a yaw rate sensor for detecting the yaw rate (ψ˙) of the motor vehicle, and at least one of wheel sensors, GPS, and an accelerometer for detecting the longitudinal velocity (V) of the motor vehicle. x ) and lateral velocity (V y ).

[0053] Option 15. The motor vehicle according to Option 14, wherein the linear computation model is embedded in the model predictive control (MPC) algorithm, which is configured to employ the maximum sideslip angle (α) of the steering actuator and the second axle. max The constraints on the open-loop finite-range optimal control equations are repeatedly solved to determine the impending instabilities of the motor vehicle.

[0054] Option 16. The motor vehicle according to Option 11, wherein the electronic controller is programmed to detect the steering angle (θ) of the steering actuator via a steering position sensor.

[0055] Option 17. The motor vehicle according to Option 11, wherein the steering actuator is configured as an electric power steering unit.

[0056] Option 18. The motor vehicle according to Option 11, wherein the electronic controller is programmed according to relation α max =µ * α to determine the maximum sideslip angle (α) max ), where μ is the coefficient of friction at the interface between the motor vehicle and the road surface.

[0057] Option 19. The motor vehicle according to Option 11, wherein:

[0058] If μ < 0.3, then the maximum sideslip angle (α) max Within the range of 1-2 degrees; and

[0059] If μ > 0.3, then the maximum sideslip angle (α) max (Within the range of 3-4 degrees.)

[0060] Option 20. The motor vehicle according to Option 11, wherein, if μ is unknown, the maximum sideslip angle (α) is... max It is set to 1 degree.

[0061] The above-described features and advantages, as well as other features and advantages of this disclosure, will become apparent in the following detailed description of embodiments and preferred modes for carrying out the described disclosure, taken in conjunction with the accompanying drawings and appended claims. Attached Figure Description

[0062] Figure 1 It is a schematic plan view of a motor vehicle with first and second axles passing through a geographical area; the vehicle uses global positioning satellites (GPS) and vehicle sensors in communication with an electronic controller configured to maintain vehicle stability as the vehicle travels along a selected path.

[0063] Figure 2 This is a schematic partial plan view of a vehicle with experienced stability loss according to this disclosure, such as the stability loss of the second axle relative to... Figure 1 As indicated by the sideslip angle of the selected path shown.

[0064] Figure 3 It is based on the lateral force on the second axle of this disclosure as Figure 1 and Figure 2 The curve shown is a function of the sideslip angle of the second axle.

[0065] Figure 4 It is to maintain Figures 1-2 The flowchart shown illustrates a method for determining the stability of a motor vehicle, and is based on... Figure 3 The curve shown compares the lateral force with the sideslip angle of the second axle. Detailed Implementation

[0066] Those skilled in the art will recognize that terms such as “above,” “below,” “upward,” “downward,” “top,” “bottom,” “left,” and “right” are used descriptively in the accompanying drawings and do not imply a limitation on the scope of this disclosure as defined by the appended claims. Furthermore, the teachings herein can be described according to functional and / or logical block components and / or various processing steps. It should be understood that such block components may include multiple hardware, software, and / or firmware components configured to perform a specified function.

[0067] Referring to the accompanying drawings, the same reference numerals denote the same parts. Figure 1 A schematic diagram of a motor vehicle 10 positioned relative to a road surface 12 is shown. The vehicle 10 may include, but is not limited to, a mobile platform, such as, but not limited to, a car, truck, van, etc. Figure 1As shown, the vehicle 10 includes a vehicle body 14 that defines four body sides - a first body end or front end 14-1, an opposite second body end or rear end 14-2, a first side or left side body side 14-3, and a second side or right side body side 14-4. Although not specifically shown, the vehicle body 14 can also define a top body portion (which can include a vehicle roof), a bottom body portion, and a passenger cabin. The left side body side 14-3 and the right side body side 14-4 are generally parallel to each other and arranged parallel with respect to a virtual longitudinal vehicle body axis X of the motor vehicle 10, and span a distance between the front end 14-1 and the rear end 14-2.

[0068] The motor vehicle 10 also includes a first axle 16-1 and a second axle 16-2. With respect to a heading of the motor vehicle 10, the first axle 16-1 can be a front axle and the second axle 16-2 can be a rear axle. As shown, the first axle 16-1 includes a first set of wheels 18-1, while the second axle 16-2 includes a second set of wheels 18-2 (e.g., separate left and right side wheels on each axle). Each of the wheels 18-1, 18-2 employs a tire configured to provide frictional contact with the road surface 12. Although two axles, the first axle 16-1 and the second axle 16-2, are specifically shown, it is not excluded that the motor vehicle 10 has additional axles. The motor vehicle 10 also includes a steering actuator 20 configured to steer the first axle 16-1 via a steering angle (Q). The steering actuator 20 can be configured as an electric power assisted steering unit. The motor vehicle 10 also includes a powertrain 22 that includes a power source 22A configured to transmit drive torque to the first axle 16-1 and / or the second axle 16-2.

[0069] As Figure 1 shown, the motor vehicle 10 includes at least one sensor 24A and an electronic controller 26 that together cooperate to at least partially control, direct, and maneuver the vehicle 10 in autonomous mode in certain situations. Thus, the vehicle 10 can be referred to as a semi-autonomous or fully autonomous vehicle. To achieve efficient and reliable vehicle control, the electronic controller 26 can be in operative communication with the steering actuator 20 configured as an electric power assisted steering unit. The sensor 24A of the motor vehicle 10 is operable to sense the road surface 12 and monitor the surrounding geographic area and traffic conditions proximate to the host vehicle.

[0070] The sensors 24A of the vehicle 10 can include, but are not limited to, at least one of a light detection and ranging (LIDAR) sensor, a radar, and a camera positioned about the vehicle 10 to detect boundary indicators, such as edge conditions, of the roadway surface 12. The types of sensors 24A, their locations on the vehicle 10, and their operations to detect and / or sense boundary indicators of the roadway surface 12 and monitor surrounding geographic areas and traffic conditions are understood by those skilled in the art and are independent of the teachings of the present disclosure and, therefore, are not described in detail herein. The vehicle 10 can also include sensors 24B attached to the vehicle powertrain 22, such as a yaw rate sensor, an accelerometer, wheel speed sensors, longitudinal speed sensors, and lateral speed sensors.

[0071] The electronic controller 26 is arranged in communication with the sensors 24A of the vehicle 10 for receiving their respective sensing data related to the detection or sensing of the roadway surface 12 and the monitoring of surrounding geographic areas and traffic conditions. The electronic controller 26 can alternatively be referred to as a control module, control unit, controller, vehicle 10 controller, computer, etc. The electronic controller 26 can include a computer and / or processor 28 and include software, hardware, memory, algorithms, connections (e.g., to the sensors 24A and 24B), etc., for managing and controlling the operation of the vehicle 10. Thus, the method generally represented and described below in Figure 4 the method can be implemented as a program or algorithm operable on the electronic controller 26. It should be appreciated that the electronic controller 26 can include means capable of analyzing data from the sensors 24A and 24B, comparing data, making decisions required to control the operation of the vehicle 10, and performing the required tasks to control the operation of the vehicle 10.

[0072] The electronic controller 26 can be implemented as one or more digital computers or host computers each having one or more processors 28, read only memory (ROM), random access memory (RAM), electrically programmable read only memory (EPROM), optical drives, magnetic drives, etc., high speed clocks, analog-to-digital (A / D) circuits, digital-to-analog (D / A) circuits, and input / output (I / O) circuits, I / O devices and communication interfaces, and signal conditioning and buffering electronics. Computer readable memory can include non-transitory / tangible media involved with providing data or computer-readable instructions. The memory can be non-volatile or volatile. Non-volatile media can include, for example, optical or magnetic disks and other persistent memory. An example of volatile media can include dynamic random access memory (DRAM), which can constitute main memory. Other examples of memory embodiments include floppy disks, flexible disks, or hard disks, magnetic tape, or other magnetic media, CD-ROMs, DVDs, and / or other optical media, and other possible memory devices such as flash memory.

[0073] The electronic controller 26 includes a tangible, non-transient memory 30 on which computer-executable instructions, including one or more algorithms, are recorded for regulating the operation of the motor vehicle 10. Specifically, the algorithms may include a model predictive control (MPC) algorithm 32 for maintaining the stability of the motor vehicle 10, which will be described in detail below. The processor 28 of the electronic controller 26 is configured to execute algorithm 32. Algorithm 32 implements a method for maintaining the stability of the vehicle 10 as it traverses the road surface 12 along a desired or selected path, including various curves and bends. Specifically, instability of the motor vehicle 10, particularly when traversing a bend, can be defined as an oversteer condition that causes the vehicle to slip and potentially spin in place.

[0074] The motor vehicle 10 also includes a vehicle navigation system 34, which may be part of integrated vehicle controls or an additional device for finding driving guidance within the vehicle. The vehicle navigation system 34 is operatively connected to a Global Positioning Satellite (GPS) 36. The vehicle navigation system 34, connected to GPS 36 and the aforementioned sensors 24A, can be used for the automation of the vehicle 10. The vehicle navigation system 34 receives its position data from GPS 36 using a satellite navigation device (not shown) and then correlates it with the vehicle's position relative to the surrounding geographic area. Based on this information, a route to a specific waypoint can be calculated when guidance to that destination is needed. Real-time traffic information can be used to adjust the route. The current position of the vehicle 10 can be calculated via dead reckoning—advancing the position over time and distance using a previously determined position and based on known or estimated speeds. Data from sensors 24B attached to the vehicle's powertrain 22 (e.g., yaw rate sensors, accelerometers, and speed sensors) and vehicle-mounted radar and optics can be used for greater reliability and to offset GPS 36 signal loss and / or multipath interference caused by urban canyons or tunnels.

[0075] The electronic controller 26 is also configured (i.e., programmed) to determine the position 38 of the motor vehicle 10 on the road surface 12 (current position in the XY plane, such as...) by receiving data from the GPS 36 via the navigation system 34. Figure 1 (as shown), desired or anticipated path 40 and heading 42. Desired path 40 may include separate waypoints, such as... Figure 1points A, B, and C shown in FIG. 1. As described above, the motor vehicle 10 can be configured to operate in an autonomous mode directed by the electronic controller 26. In this mode, the electronic controller 26 can further obtain data from the vehicle sensors 24B to direct the vehicle along the desired path 40, for example, via adjustment of the steering actuator 20. The electronic controller 26 can also be programmed to detect and monitor the steering angle (0) of the steering actuator 20 along the desired path 40, for example, during a turn through. Specifically, the electronic controller 26 can be programmed to determine the steering angle (0) via receipt and processing of data signals from a steering position sensor 44 (as shown in FIG. 1) in communication with the steering actuator 20. Figure 1

[0076] The electronic controller 26 is further configured to determine a current side slip angle (a) of the second axle 16-2, for example, by detecting data indicative of the dynamic state of the motor vehicle 10 (as shown in FIG. 1). Figure 2 The side slip angle (a) of the second axle 16-2 defines how much the wheel 18-2 has slipped in a direction generally perpendicular to the desired path 40. Specifically, the electronic controller 26 can be programmed to determine the current side slip angle (a) of the second axle 16-2, which can occur as the vehicle 10 is making a turn through the desired path 40. Determination of the current side slip angle (a) of the second axle 16-2 can be accomplished using data indicative of the dynamic state of the motor vehicle 10 received from appropriate sensors 24B attached to the vehicle powertrain 22. For example, the data can be collected via appropriate sensors 24B and communicated to the electronic controller 26, for example, a yaw rate sensor can be used to detect the yaw rate ψ˙, while wheel speed sensors and / or accelerometers can be used to detect the longitudinal velocity V x and lateral velocity V y . The GPS 36 can similarly be used to detect or assist in detecting the longitudinal velocity V x and lateral velocity V y . Further, roll rate and pitch rate sensors can be included in the sensors 24B to assist in evaluating the side slip angle (a) of the second axle 16-2.

[0077] The electronic controller 26 is further configured to use the coefficient of friction (μ) value at the interface between the motor vehicle 10 (i.e., the wheels 18-1, 18-2) and the road surface 12 to set or establish a maximum allowable side slip angle (a max ) of the second axle 16-2. Specifically, the electronic controller 26 can be programmed to determine the maximum side slip angle (a max ) according to the following relationship:

[0078] α max = µ * α (46)

[0079] ​In the relationship 46, μ is the friction coefficient at the interface between the motor vehicle 10 and the road surface 12. The value of the side slip angle (a) is generally related to the specific tire characteristics of the vehicle and represents the point at which the lateral force on the axle saturates and the corresponding tire starts to slip. For example, the value of a on a dry road surface before the vehicle starts to slip is typically about 8 degrees. If μ < 0.3, for example on a wet road surface, the maximum side slip angle (a max ) can be set in the range of 1-2 degrees. Alternatively, if μ > 0.3, for example on a dry road surface, the maximum side slip angle (a max ) can be set in the range of 3-4 degrees. In the case where μ is unknown, the maximum side slip angle (a max ) can be set to 1 degree.

[0080] The electronic controller 26 is further configured to use the position 38 and heading 42 of the vehicle 10 and the determined current side slip angle (a max ) of the second axle as inputs to a linear computational model 48 embedded in the algorithm 32 to predict when the maximum side slip angle (a max ) of the second axle 16-2 will be exceeded or will be exceeded. The electronic controller 26 is further configured to use the prediction of when the maximum side slip angle (a max ) of the second axle 16-2 will be exceeded to update the linear computational model 48 to determine an impending instability of the motor vehicle 10. Via the command steering actuator 20 modifying the steering angle (θ), the electronic controller 26 is further configured to use the updated linear computational model 48 and the maximum side slip angle (a max ) of the second axle 16-2 to correct the impending instability.

[0081] With reference to Figure 2 , when the vehicle loses road grip or traction at the second axle 16-2, for example due to an unexpected encounter with a low friction area (e.g. a puddle or a patch of gravel or ice), the forces on the second axle 16-2 rapidly decrease while the forces on the first axle 16-1 increase. As a result, a rotational moment M will be generated on the vehicle body 14 about the center of gravity C g of the vehicle such that the vehicle 10 will have a tendency to spin on the spot. The command steering actuator 20 modifying the steering angle (θ) is intended to reduce the forces on the first axle 16-1 while increasing the forces on the second axle 16-2, thereby stabilizing the vehicle 10. The electronic controller 26 can be specifically configured to determine a target steering angle (θ T ) for the steering actuator 20 and compare the target steering angle to the detected steering angle (θ). In the case where the target steering angle (θ T ) is for example greater than the detected steering angle (θ), the electronic controller 26 can command the steering actuator 20 to reduce the steering angle (θ) to the target steering angle (θ T). The reduction of the turn angle (0) will thereby limit the side slip angle (a) of the second axle 16-2 and preempt an upcoming instability of the vehicle 10 on the desired path 40, for example when passing a curve.

[0082] With continued reference to Figure 1 , the linear computational model 48 can be part of the above-mentioned model predictive control (MPC) algorithm 32. As part of the MPC algorithm 32, the linear computational model 48 can be configured to determine an upcoming instability of the motor vehicle 10 by repeatedly solving a model-based open-loop finite horizon optimal control equation using constraints on the steering actuator 20. The constraints on the steering actuator 20 can include steering rate and angle limits (which can vary with respect to the longitudinal velocity V x and lateral velocity V y of the vehicle 10) as well as a maximum side slip angle (a max ) of the second axle 16-2. In particular, the MPC algorithm 32 can be used to find an optimal control sequence over a future horizon in a finite number of steps. At each sampling time, the vehicle state can be estimated to minimize a performance index (subject to the prediction model and constraints on the steering actuator 20). A quadratic programming (QP) can then be used to solve a resulting mathematical optimization problem involving a multivariate quadratic function (subject to linear constraints, input constraints on the steering actuator 20). The side slip angle (a) of the second axle 16-2 is defined as an output constraint of the optimization problem, i.e. a maximum side slip angle (a max ) for avoiding an instability of the vehicle 10.

[0083] The linear computational model 48 can use data of the lateral force (Sr) on the second axle 16-2 as a function of the side slip angle (a) of the second axle, as shown on the curve 50 in Figure 3 , to predict when the maximum side slip angle (a max ) of the second axle will be exceeded. In particular, the side slip angle (a) of the second axle 16-2 can be expressed as follows:

[0084] α = (-V y + lr * ψ˙) / V x (52)

[0085] In expression 52, lr (as shown in Figure 1 ) is the distance from the vehicle center of gravity C g to the second axle 16-2.

[0086] Further, the lateral force (Sr) on the second axle 16-2 can be expressed as follows:

[0087] Sr = f(α) =+ / - Cr * α (54)

[0088] In expression 54, Cr is the vehicle's sideslip stiffness. Figure 3 The slope of the linear region 56 is depicted in the middle. Typically, the sideslip angle of a vehicle axle is a linear combination of the vehicle's lateral velocity and yaw rate. However, as... Figure 3 As shown, the lateral force (Sr) is a nonlinear function that depends on the sideslip angle (α) and road conditions (i.e., the coefficient of friction µ). Typically, vehicle instability occurs when the lateral force (Sr) exceeds the coefficient of friction (μ) at the interface between the vehicle 10 and the road surface 12.

[0089] Due to the nonlinearity of the lateral force (Sr), the simple MPC linear prediction model cannot compute the output limit. To allow the linear computation model 48 to efficiently compute the output limit, the MPC algorithm 32 is first adapted to effectively predict when the vehicle will rotate in place and exceed the maximum sideslip angle (α) of the second axle 16-2. max This is used to determine the impending instability of the vehicle 10. Then, the linear calculation model 48 is updated to use the maximum sideslip angle (α) of the second axle 16-2 to determine when it will exceed this angle. max The prediction of the upcoming instability of the vehicle 10 is used to determine the instability of the vehicle 10. In other words, the updated linear calculation model 48 is used to determine the instability of the vehicle 10 by using the output constraint (i.e., the maximum sideslip angle (α) of the second axle 16-2). max This is used to predictively limit impending instability. Specifically, in the prediction, after calculating the lateral force (Sr) via Expression 54, the vehicle's sideslip stiffness (Cr) is set to zero, thus allowing the MPC model to describe a vehicle rotating in place. The MPC model then uses the maximum value of the lateral force (Sr) as input to limit the rate of vehicle rotation in place to a controllable rate.

[0090] By commanding the steering actuator 20 to modify (e.g., reduce) the steering angle (θ), the electronic controller 26 is also configured to use the updated linear calculation model 48 and the maximum sideslip angle (α) of the second axle 16-2. max The modified steering angle (θ) is designed to correct for impending instability. Specifically, it aims to counteract and / or limit potential vehicle rotation as the vehicle 10 travels along the desired path 40 between waypoints A, B, and C. For example, if the detected sideslip angle (α) of the second axle is greater than the maximum sideslip angle (α) of the second axle 16-2, the modification will correct for impending instability. max The electronic controller 26 can command the steering actuator 20 to take a target steering angle (θ). TThe electronic controller 26 steers the first axle 16-1 to counteract and limit the instability of the vehicle 10 during cornering. Therefore, the electronic controller 26 can also be programmed to adjust the target steering angle (θ). T The steering angle (θ) of the detected steering actuator 20 is compared with the steering angle of the vehicle 10, and the required incremental steering angle change (Δθ) is determined to maintain the stability and balance of the vehicle 10. Therefore, the vehicle can be kept on its intended path 40 by predictively limiting the impending instability of the vehicle 10 through controlling the steering angle (θ).

[0091] Keep motor vehicles (e.g., refer to) Figures 1-3 The method 100 for the stability of the vehicle 10) is in Figure 4 The method is described in block 100 and disclosed in detail below. Method 100 begins at block 102, whereby the movement of vehicle 10 is detected via electronic controller 26. Electronic controller 26 may detect the movement of vehicle 10 via GPS 36 and / or vehicle sensors 24A, 24B. In block 102, the method may further include detecting the steering angle (θ) of steering actuator 20 via steering position sensor 44. As described above, motor vehicle 10 may be configured to operate in an autonomous or semi-autonomous mode guided by electronic controller 26. Following block 102, the method proceeds to block 104.

[0092] In block 104, the method includes determining the position 38 and heading 42 of the motor vehicle 10 relative to the road surface 12 via electronic controller 26. Determining the position 38 and heading 42 of the motor vehicle 10 may include determining a desired path 40 and discrete waypoints, such as points A, B, and C, via navigation system 34 using data from GPS 36 and vehicle sensors 24A. Following block 104, the method proceeds to block 106. In block 106, the method includes determining the current sideslip angle (α) of the second axle 16-2, for example, during a turn along the desired path 40. Determining the current sideslip angle (α) of the second axle 16-2 may include receiving data indicating the dynamic state of the motor vehicle 10 from sensors 24B via electronic controller 26, sensors 24B including a yaw rate sensor for detecting vehicle yaw rate (ψ˙), wheel speed sensors, GPS 36, and sensors for detecting the vehicle's longitudinal speed (Vx) and lateral speed (V). y The accelerometer. From box 106, the method proceeds to box 108.

[0093] In block 108, the method includes setting the maximum sideslip angle (α) of the second axle 16-2 via an electronic controller 26 using the coefficient of friction (μ) at the interface between the second set of wheels 18-2 of the vehicle and the road surface 12. max (See reference) Figures 1-3 As described above, the maximum sideslip angle (α) max) can be determined according to the relationship a max = μ * 8 degrees. Furthermore, if μ < 0.3, the maximum side slip angle (a max ) can be set in the range of 1-2 degrees, while if μ > 0.3, the maximum side slip angle (a max ) can be set in the range of 3-4 degrees. Alternatively, if μ is unknown, the maximum side slip angle (a max ) can be set to 1 degree. After block 108, the method proceeds to block 110.

[0094] In block 110, using the position 38 and heading 42 of the motor vehicle 10 and the determined current side slip angle (a) of the second axle 16-2 as inputs to the linear computational model 48, the method predicts, via the electronic controller 26, when the maximum side slip angle (a max ) of the second axle 16-2 will be exceeded. As described above with reference to Figures 1-3 , the linear computational model 48 can be embedded in the MPC algorithm 32, which is configured to determine an impending instability of the motor vehicle 10. In particular, the MPC algorithm 32 is configured to repeatedly solve open-loop finite horizon optimal control equations with constraints on the steering actuator 20 and the maximum side slip angle (a max ) of the second axle 16-2. After block 110, the method proceeds to block 112.

[0095] In block 112, using the prediction of when the maximum side slip angle (a max ) of the second axle 16-2 will be exceeded, the method includes updating, via the electronic controller 26, the linear computational model 48 to determine an impending instability of the vehicle 10. From block 112, the method proceeds to block 114, in which the method includes modifying, via the command steering actuator 20, the steering angle (0), using the updated linear computational model 48 and the maximum side slip angle (a max ) of the second axle 16-2 to correct for the impending instability via the electronic controller 26. The method can loop from block 114 back to block 106 to further determine the current side slip angle (a) of the second axle 16-2 along the desired path 40. Alternatively, in the event that the motor vehicle 10 reaches its desired destination without loss of stability, the method can end in block 116.

[0096] The detailed description and accompanying drawings or diagrams are supportive and descriptive of the disclosure, but the scope of the disclosure is defined solely by the claims. While there have been described herein the principles of the disclosure and the best mode and other embodiments for performing the disclosure, various alternative designs and embodiments exist for practicing the disclosure which are within the scope of the claims appended hereto. In addition, features of the embodiments shown in the drawings or described in the specification can not be necessarily dependent on each other. Rather, it is possible that each feature described in one example of an embodiment can be combined with one or more other desirable features from other embodiments, resulting in other embodiments not described in words or drawings. Such other embodiments are therefore within the scope of the claims.

Claims

1. A method for maintaining the stability of a motor vehicle, the motor vehicle having a first axle, a second axle, and a steering actuator, the steering actuator being configured to steering the first axle via a steering angle, the method comprising: The position and heading of a motor vehicle relative to the road surface are determined by an electronic controller; Determine the current sideslip angle α of the second axle, relative to the heading of the motor vehicle, where the first axle is the front axle and the second axle is the rear axle; The maximum sideslip angle α of the second axle is set by using the coefficient of friction μ at the interface between the vehicle and the road surface via an electronic controller. max ; Using the vehicle's positioning and heading, along with the determined current sideslip angle α of the second axle, as input to a linear computational model via an electronic controller, it is used to predict when the maximum sideslip angle α of the second axle will be exceeded. max ; The electronic controller is used to determine when the maximum sideslip angle α of the second axle will be exceeded. max The predictions are used to update the linear computation model in order to determine the impending instabilities of motor vehicles; as well as The maximum sideslip angle α of the second axle is determined via an electronic controller using an updated linear calculation model. max The impending instability is corrected by modifying the steering angle of the first axle via a command steering actuator.

2. The method according to claim 1, wherein: The motor vehicle is configured to operate in an autonomous mode guided by an electronic controller; as well as Determining the location and heading of a motor vehicle involves determining the vehicle's desired path and independent waypoints via electronic controllers that receive data from GPS.

3. The method according to claim 2, wherein, Instability in motor vehicles is a condition of oversteering that eventually leads to spinning in place.

4. The method according to claim 2, wherein, Determining the current sideslip angle α of the second axle includes receiving data indicating the dynamic state of the vehicle from sensors mounted to the vehicle via an electronic controller. The sensors include a yaw rate sensor for detecting the yaw rate of the vehicle, and at least one of wheel sensors, GPS, and an accelerometer for detecting the longitudinal and lateral velocities of the vehicle.

5. The method according to claim 4, wherein, The linear computational model is embedded in the model predictive control algorithm, and its configuration is to utilize the maximum sideslip angle α of the steering actuator and the second axle. max The constraints are repeatedly solved to obtain the open-loop finite-range optimal control equations to determine the impending instabilities of the motor vehicle.

6. The method of claim 1, further comprising detecting the steering angle of the steering actuator via a steering position sensor.

7. The method according to claim 1, wherein, The steering actuator is configured as an electric power steering unit.

8. The method according to claim 1, wherein, Maximum sideslip angle α max According to the relation α max =μ α is determined, where μ is the coefficient of friction at the interface between the vehicle and the road surface.

9. The method according to claim 1, wherein: If μ < 0.3, then the maximum sideslip angle α max Within the range of 1-2 degrees; as well as If μ > 0.3, then the maximum sideslip angle α max Within the range of 3-4 degrees.

10. The method according to claim 1, wherein, If μ is unknown, then the maximum sideslip angle α max Set to 1 degree.

11. A motor vehicle, comprising: First axle; Second axle; A steering actuator configured to steering a first axle via a steering angle; The powertrain system is configured to transmit drive torque to a first axle and / or a second axle; and An electronic controller configured to adjust the steering actuator and programmed to: Determine the position and heading of the motor vehicle relative to the road surface; Determine the current sideslip angle α of the second axle, relative to the heading of the motor vehicle, where the first axle is the front axle and the second axle is the rear axle; The maximum sideslip angle α of the second axle is determined using the coefficient of friction μ at the interface between the vehicle and the road surface. max The linear computational model uses the vehicle's positioning and heading, along with the determined current sideslip angle α of the second axle, as input to predict when the maximum sideslip angle α of the second axle will be exceeded. max ; Use the maximum sideslip angle α of the second axle to determine when it will exceed the second axle. max The predictions are used to update the linear computation model in order to determine the impending instabilities of motor vehicles; as well as Using the updated linear calculation model, the maximum sideslip angle α of the second axle is calculated. max The impending instability is corrected by modifying the steering angle of the first axle via a command steering actuator.

12. The motor vehicle according to claim 11, wherein: The motor vehicle is configured to operate in an autonomous mode guided by an electronic controller; as well as The electronic controller is programmed to determine the vehicle's position and heading by receiving data from GPS to determine the vehicle's desired path and independent waypoints.

13. The motor vehicle according to claim 12, wherein, Instability in motor vehicles is a condition of oversteering that eventually leads to spinning in place.

14. The motor vehicle according to claim 12, wherein, The electronic controller is programmed to determine the current sideslip angle α of the second axle by receiving data indicating the dynamic state of the motor vehicle from sensors mounted on the vehicle. The sensors include a yaw rate sensor for detecting the yaw rate of the motor vehicle, and at least one of wheel sensors, GPS, and an accelerometer for detecting the longitudinal and lateral velocities of the motor vehicle.

15. The motor vehicle according to claim 14, wherein, The linear computational model is embedded in the model predictive control algorithm, and its configuration is to utilize the maximum sideslip angle α of the steering actuator and the second axle. max The constraints are repeatedly solved to obtain the open-loop finite-range optimal control equations to determine the impending instabilities of the motor vehicle.

16. The motor vehicle according to claim 11, wherein, The electronic controller is programmed to detect the steering angle of the steering actuator via a steering position sensor.

17. The motor vehicle according to claim 11, wherein, The steering actuator is configured as an electric power steering unit.

18. The motor vehicle according to claim 11, wherein, The electronic controller is programmed according to the relation α max =μ α determines the maximum sideslip angle α max , where μ is the coefficient of friction at the interface between the motor vehicle and the road surface.

19. The motor vehicle according to claim 11, wherein: If μ < 0.3, then the maximum sideslip angle α max Within the range of 1-2 degrees; as well as If μ > 0.3, then the maximum sideslip angle α max Within the range of 3-4 degrees.

20. The motor vehicle according to claim 11, wherein, If μ is unknown, then the maximum sideslip angle α max Set to 1 degree.

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