METHOD AND SYSTEM FOR DETERMINING A SPIN-OUT VEHICLE CONDITION

Abstract

Computer-implemented method for determining at least one vehicle skidding condition, comprising: Receiving at least one motion parameter of a vehicle based on signals captured by at least one vehicle sensor; estimating a self-aligning torque and at least one lateral axis force based on at least one motion parameter; estimating the tire caster for at least one tire of the vehicle using the self-aligning torque and the at least one lateral axle force; Determining at least one vehicle skidding condition based on the estimated tire trail; the computer-implemented method further includes the following: a condition of decreasing tire trail is determined and an initial vehicle skidding condition is determined in response to the condition of decreasing tire trail; and / or The estimated tire caster is compared with a predetermined tire caster threshold, and a second vehicle skidding condition is determined based on the comparison.

Description

TECHNICAL AREA

[0001] The technical field generally relates to the determination of at least one vehicle skidding condition and in particular to a computer-implemented method and system for estimating tire caster for determining at least one vehicle skidding condition and for controlling a vehicle based thereon.

[0002] DE 603 ​​05 232 T2 describes a device for estimating the traction factor of a vehicle wheel. It comprises a restoring torque estimation device for estimating a restoring torque generated at least at one wheel of the vehicle due to the steering factor determined by the steering factor measuring device, and a vehicle condition measuring device for determining a state variable of the vehicle.The device further comprises a wheel factor estimating device for estimating at least one wheel factor including a lateral force and a slip angle applied to the wheel based on the state variable determined by the vehicle condition measuring device, and a grip factor estimating device for estimating a grip factor of at least one wheel tire in accordance with a relationship between the restoring torque determined by the restoring torque estimating device and the wheel factor determined by the wheel factor estimating device.

[0003] Furthermore, WO 2005 / 044 650 A1 describes a device for determining a vehicle pivot point taking into account a sideslip angle of the vehicle. BACKGROUND

[0004] Dynamic control systems are increasingly used in motor vehicles to improve vehicle safety and comply with government regulations. Examples of such systems include active vehicle safety systems such as electronic stability control (ESC), comprehensive safety vehicle (CSV) systems, and lane departure warning systems. For these safety systems to function effectively, accurate and timely knowledge of the vehicle's dynamic states is essential.

[0005] If a moving vehicle has "spun out" to such an extent that its velocity vector is pointing sideways, stability control systems can offer little benefit in steering the vehicle. In this case, the stability control system can be deactivated until the vehicle is properly aligned.

[0006] Determining the vehicle skidding conditions before the vehicle actually skids out can enable a driver and / or an active safety system of a vehicle to counteract the driving behavior that leads to the vehicle skidding.

[0007] Accordingly, there is a need for a system and a method for determining vehicle skid conditions, possibly including precursors of skid conditions and actual skidding. Additionally, it is desirable to implement such a system and method using the available acquired signal and in a processing-efficient scheme. Furthermore, other desirable functions and features will become apparent from the following detailed description and the attached claims in conjunction with the attached drawings, as well as the preceding technical field and background information. SUMMARY

[0008] According to the invention, a computer-implemented method with the features of claim 1 and a system with the features of claim 7 for determining a vehicle skidding condition are proposed. DESCRIPTION OF THE DRAWINGS

[0009] The exemplary embodiments are described below in conjunction with the following drawings, where the same reference numerals denote the same elements, and where the following applies: Fig. Figure 1 is a functional block diagram of a vehicle with modules for determining at least one vehicle skidding condition according to different embodiments; Fig. Figure 2 is a diagram of exemplary submodules for determining at least one vehicle skidding condition according to different embodiments; Fig. Figure 3 is a flowchart that represents a first part of a processing procedure for determining vehicle slip conditions according to various embodiments; and Fig. Figure 4 is a flowchart that represents a second part of a processing procedure for determining vehicle slip conditions according to different embodiments. Fig. Figure 5 is a schematic drawing illustrating the progression of the vehicle during a vehicle skid. DETAILED DESCRIPTION

[0010] The following detailed description serves only as an example. Furthermore, there is no intention to be bound by any theory explicitly or implicitly presented in the preceding technical section, background, summary, or the following detailed description. The term "module" as used here refers to an application-specific integrated circuit (ASIC), an electronic circuit, a processor (shared, dedicated, or group processor), and memory that executes one or more software or firmware programs, a combinational logic circuit, and / or other suitable components providing the described functionality.

[0011] Inventive embodiments may be described herein as functional and / or logical block components and various processing steps. It should be noted that such block components may be composed of any number of hardware, software, and / or firmware components configured to perform the required functions. For example, one embodiment of the invention may employ various integrated circuit components, such as memory elements, digital signal processing elements, logic elements, lookup tables, or the like, which can perform a multitude of functions under the control of one or more microprocessors or other control devices.Furthermore, experts will recognize that embodiments of the present invention can be implemented in conjunction with any number of directional control systems and that the described vehicle system is merely an example of an embodiment of the invention.

[0012] For the sake of brevity, conventional techniques related to signal processing, data transmission, signal generation, control, and other functional aspects of the systems (and the individual operating elements of the systems) are not described in detail herein. Furthermore, the connecting lines shown in the various figures herein are intended to illustrate exemplary functional relationships and / or physical couplings between the various elements. It should be noted that many alternative or additional functional relationships or physical connections may exist in an embodiment of the invention.

[0013] With reference to Fig. Figure 1 is an exemplary vehicle 100, which partially incorporates a control system 110, as shown in exemplary embodiments. As can be seen, the vehicle 100 can be any type of vehicle that might be subject to skidding, which is the case when the vehicle breaks away uncontrollably in a direction in which the vehicle 100 is traveling VH and a direction in which the vehicle 100 is traveling VT, which differ excessively, as schematically shown in Figure 1. Fig. Figure 5 illustrates this. An angle between the direction in which the vehicle is traveling, VH, and the direction of the vehicle's path is a vehicle skew angle. Although the figures shown herein represent an example with specific arrangements of elements, actual embodiments may include additional intermediate elements, devices, features, or components. It should be noted that Fig. 1 is for illustrative purposes only and may not be to scale.

[0014] In an exemplary embodiment, the vehicle 100 comprises a front axle 101 with front wheels 103 and a rear axle 102 with rear wheels 104. The person skilled in the art will recognize that the axles 101, 102 are shown in an exaggerated, protruding form for illustrative purposes.

[0015] The control system 110 further includes a control module 120, which receives inputs from one or more sensors 130 of the vehicle 100. The sensors 130 detect observable states of the vehicle 100 and generate corresponding sensor signals. For example, the sensors 130 can detect the conditions of an electric power steering (EPS) system 140 of the vehicle 100, an inertial measurement unit 150 of the vehicle 100, and / or other systems of the vehicle 100 and generate corresponding sensor signals. The sensors 130 can detect one or more of the following vehicle motion parameters and generate corresponding control signals: lateral acceleration, yaw rate, EPS torque, steering angle, longitudinal speed, vehicle roll angle, etc.In various embodiments, the sensors 130 communicate the signals directly to the control module 120 and / or can transmit the signals to other control modules (not shown), which in turn transmit data from the signals to the control module 120 via a communication bus (not shown) or other communication means.

[0016] In exemplary embodiments, the control system 110 further comprises a non-volatile memory 250 that stores various lookup parameters, as described in more detail herein. The control system 110 includes an instrument panel 252 that provides an interface with a driver to receive inputs from the driver and provide outputs to the driver. The instrument panel 252 may include a display, such as indicator lights and / or a graphical user interface, through which outputs can be made.

[0017] The control module 120 receives the signals and / or the data acquired by the sensors and, using the acquired signals, estimates a tire caster for one or more tires of the vehicle. The control module 120 determines at least one vehicle skid condition based on the estimated tire caster. The control module 120 then uses the vehicle skid condition to control one or more features of the vehicle 100, as described below. The control module 120 of Fig. 1 (and the various sub-modules contained therein, as below with reference to Fig. 2 described), can be implemented by a combination of at least one computer program 121 that is executed on at least one processor 122 of the vehicle 100.

[0018] The estimated tire caster can provide an early indication of the sideslip angle β and thus potential vehicle skidding conditions. In particular, if the sideslip angle β exceeds a predetermined threshold, it can be determined that a skid has occurred. The estimated tire caster correlates the tire restoring torque (SAT) and the tire lateral force and is capable of providing a preventive warning of tire force saturation, which is a likely precursor to a skid.

[0019] When tire force is saturated, the limits of the tire / road capacity have likely been reached. Any force demanded beyond this limit may lead to vehicle instability and potentially to a skid, or at least to conditions that could lead to a skid, unless corrective action is taken. Tire force saturation is indicated by tire SAT and tire lateral force, and thus also by tire caster. An interesting feature of SAT is that it indicates tire force saturation before the lateral forces are saturated.The control module 120 is able to utilize these SAT characteristics through the estimated tire caster to provide an early indication of a vehicle skidding condition, enabling subsequent steps to be taken by a feature control module 520, such as warning a driver, taking automated EPS countermeasures, and starting the calculation of the vehicle's sideslip angle before a skid has actually occurred.

[0020] With reference to Fig. 2 and with continued reference to Fig. Figure 1 illustrates a diagram of submodules contained in the control module 120 according to various exemplary embodiments. As can be seen, different embodiments of the control module 120 according to the present disclosure are possible. In different embodiments, the components shown in Fig. The two submodules shown are combined and / or further partitioned to determine at least one vehicle slip condition and to control one or more components of the vehicle 100 based thereon. In various embodiments, the control module 120 comprises a sensor module 500, a SAT estimator module 502, a first vehicle slip condition module 504, a front axle lateral force estimator module 506, a central processing module 508, a second vehicle slip condition module 510, a tire caster estimator module 512, a sideslip angle estimator module 514, a third vehicle slip condition module 516, a rear axle slip angle estimator module 518, and a feature control module 520.

[0021] The central processing module 508 provides effective control and communication between the various modules. In particular, it facilitates the collaboration of results from the different modules, as summarized in the flowcharts. Fig. 3 and Fig. As shown in Figure 4, it can be executed using the central processing module 508.

[0022] The sensor module 500 receives parameters as input from the EPS or the IMU sensors 130. These parameters can include, for example: torque and steering angle provided by the EPS, which can be directly detected by the EPS system 140 or indirectly determined from other detected values; yaw rate, lateral velocity, longitudinal velocity, and vehicle roll angle, which can be directly detected by the vehicle IMU 150 or indirectly determined from other detected values; but are not limited to these.

[0023] The 512 tire caster estimation module estimates tire caster based on the detected lateral acceleration, yaw rate, and EPS torque. These detected values ​​are readily available from the IMU and EPS sensors. Tire or axle lateral force can be determined based on lateral acceleration and yaw rate, and SAT can be determined in a known manner based on the electronic power steering torque. SAT and axle lateral force can be combined to estimate tire caster based on a known relationship (described below) between tire caster, tire lateral force, and SAT.

[0024] The front axle lateral force estimation module 506 estimates at least one lateral axle force, for example, based on detected lateral acceleration and yaw rates from sensors 130. The minimum lateral axle force for a front axle 101 of vehicle 100 can be [value missing in original text]. The tire caster estimation module 512 estimates tire caster using at least the estimated lateral force. The axle lateral force for a front axle 101 can be calculated based on the following equation: Fyf=May−LfMay−Ir˙L

[0025] In Equation 1, Fyf represents the front axle lateral force, Lf represents the distance from the vehicle's center of gravity to the front axle 101, I is the yaw moment of inertia, M is the vehicle mass, ṙ is the estimated rate of change of the yaw rate with respect to time, and L is the wheelbase length (the distance between the front and rear axles 101, 102). The parameters of Equation 1 include values ​​that can be obtained from the sensor 130 integrated into the IMU, in particular the estimated yaw rate and axle lateral force, or are otherwise vehicle constants stored in memory 250. Since the detected yaw rate is usually a nearly clean signal, ṙ can be estimated with sufficient accuracy based on r from the IMU's sensors 130. Other algorithms and equations besides Equation 1 for determining the axle lateral forces are possible.

[0026] The SAT estimation module 502 estimates the tire SAT, for example, based on the detected EPS torque from sensors 130 (via sensor module 500). The tire caster estimation module 512 estimates tire caster using at least the SAT from the SAT estimation module 502. The SAT can be estimated using known algorithms such as those disclosed in US 8,634,986, the document, in particular the part relating to the estimation of SAT based on the detected EPS torque, being incorporated herein by reference.

[0027] The tire caster estimator 512 estimates tire caster using the SAT from the SAT estimator 502 and the front axle lateral force estimator 506. The tire caster estimator 512 establishes a relationship between the estimated S and the lateral axle force and estimates the tire caster using this relationship. For example, the relationship could be the rate of change of the estimated SAT with respect to the estimated lateral axle force.

[0028] In a particular embodiment, the tire caster estimation module 512 estimates a tire caster using the following equation: τa=F^y∗(tm(δ)+t^p)︸Γf

[0029] In equation 2, t̂ represents the mechanical track (which is a function of the steering angle). p represents the estimated tire trail, Γ f represents the entire track, τ a represents SAT and F̂ yThis represents an estimate of the front axle lateral force. SAT and front axle lateral force can be determined from the SAT estimation module 502 and the axle lateral force estimation module, as described above. Based on these estimates, the total toe can be determined. Since the mechanical toe does not vary significantly, the total toe can be used to estimate the tire caster. The total toe in Equation 2 can be viewed as a relationship between SAT and axle lateral force, namely the rate of change or the slope of SAT with respect to the axle forces.

[0030] In various embodiments, the tire caster estimation module 512 uses a Kalman filter, a least-squares method (e.g., a recursive least-squares method), or other averaging or filtration-based algorithms to determine the slope between estimated SAT values ​​and estimated axle lateral force values ​​in order to estimate the tire caster. An example of real-time tire caster estimation, t̂ p , is a recursive least squares method with a forgetting factor, as is known to experts.

[0031] Equation 2 shows that the tire caster is included in a total distance (which is a combination of mechanical track and tire caster) obtained from the inclination determined by the tire caster estimation module 512. Accordingly, the total track can be used by the control module 120 to determine at least one vehicle skid condition. Alternatively, the tire caster can be estimated separately from the total distance by applying a correction factor to the total track, as determined from the inclination, to compensate for (e.g., subtract) any mechanical track.

[0032] In various embodiments, the first vehicle skid condition module 504 determines a state of decreasing tire caster, which has been estimated by the tire caster estimation module 512. The first vehicle skid condition module 504 determines a first vehicle skid condition in response to the state of decreasing tire caster. The tire caster may decrease for a predetermined period of time so that the state of decreasing tire caster can be determined. Such decreasing tire caster can provide an early indication of the type of vehicle instability that may lead to skidding. The first vehicle skid condition module 504 can output a first flag 522 in response to the determination of the state of decreasing tire caster.The feature control module 520 works with the instrument panel 252 of vehicle 100 to respond to the first flag 522 by issuing a skid warning to the driver of vehicle 100.

[0033] In various embodiments, the second vehicle skid condition module 510 compares the estimated tire caster with a predetermined tire caster threshold to determine a second vehicle skid condition based on the comparison. The threshold can indicate a tire caster that has reached a low point, suggesting high slip angles corresponding to saturated SAT. After the threshold is exceeded, vehicle control becomes unstable, and skidding is possible. The predetermined tire caster threshold can be determined experimentally and stored in the vehicle memory 250. The second vehicle skid condition module 510 can determine the second vehicle skid condition based on the predetermined tire caster threshold being violated for a predetermined duration.

[0034] In various embodiments, the central processing module 508 obliges the second vehicle skid condition module 510 to run only in response to the first vehicle skid condition module 504, which determines the first vehicle skid condition.

[0035] In various embodiments, the second vehicle skid condition module 510 outputs a second flag 524 in response to the specified second vehicle skid condition. The feature control module 520 can operate with an automated vehicle control system, such as the EPS system 140, in response to the specified second vehicle condition or the second flag 524, by controlling the vehicle 100 to counteract the skid.

[0036] In various embodiments, the second vehicle skid condition module 510 can additionally or alternatively determine the second vehicle skid condition based on an estimated axle slip angle by the rear axle slip angle estimation module 518, in addition to or as an alternative to the technique described above, by which the estimated tire trail is compared with a predetermined threshold.

[0037] In various embodiments, the tire caster estimator module 512 estimates the tire caster for one of the front and rear axles, typically the front axle 101 of the vehicle 100. The rear axle slip angle estimator module 518 estimates the slip angle of the other axle, typically the rear axle. The rear axle slip angle estimator module 518 can estimate the slip angle using at least one of the steering angle, yaw rate, and longitudinal speed obtained from the sensors 130 (through the sensor module 500). The second vehicle slip condition module 510 determines the second vehicle slip condition based on the estimated slip angle of the other axle. In particular, the second vehicle slip condition module 510 compares the estimated slip angle with a predetermined slip angle threshold to determine the second vehicle slip condition.The predetermined slip angle threshold can be empirically determined to correspond to a value at which vehicle skidding is likely and in which memory 250 is stored.

[0038] In various embodiments, the central processing module 508 requires that the rear axle slip angle estimation module 518 be executed, e.g., estimating the rear axle slip angle only if it has been determined that the estimated tire caster is not above the predetermined threshold for the other axle, which may be the front axle 101. Such a restriction requires that the axle slip angle for an axle 101, 102 is estimated only if a negligibly small axle slip angle exists for the other axle.

[0039] In this example, it is assumed that the axle shear force estimator 506 operates with respect to the front axle 101 and the axle slip angle estimator 518 operates with respect to the rear axle. The following equations are known for the front axle and rear axle slip angle estimation: αf=δ−vy+aru αr=−vy−bru

[0040] By subtracting equation 4 from equation 3, the following equation can be derived: αr=αf−δ+Lru

[0041] Since, as is known, the front slip angle α f small is |α f | < α*, where af* A large rear axle slip angle α can be a calibration parameter. r can be identified if: |−δ+Lru|>|αr*| where ar* is another calibration parameter.

[0042] In equation 6, δ represents the steering angle, r is the yaw rate, and u is the longitudinal velocity, all of which can be obtained from sensors 130 (via sensor module 500). L is the wheelbase length, which is a known vehicle constant.

[0043] Using equation 6, the rear axle slip angle estimator 518 estimates the rear axle slip angle α. r The second vehicle skid condition module 510 compares the rear axle slip angle with the predetermined slip angle threshold value from memory 250 to determine the second vehicle skid condition and optionally output the second flag 524.

[0044] In various embodiments, the third vehicle skid condition module 516 estimates a third vehicle skid condition based on the estimated vehicle sideslip angle. The third vehicle skid condition module 516 estimates the vehicle sideslip angle in response to at least one of the determined first and second vehicle skid conditions, as determined by the first and second vehicle skid condition modules 504 and 510, respectively.

[0045] The vehicle swim angle is estimated by the swim angle estimation module 514, as described below. It can be processed extensively to estimate the vehicle swim angle because it involves the integration of a vehicle spin factor, as described below. Such processing can be deferred until at least one of the first and second vehicle spin conditions has been determined without affecting the ability to determine actual vehicle spin. In particular, if the first and second vehicle spin conditions have not been determined to indicate a potential spin condition, there is no need to proceed to the step of estimating the vehicle swim angle if no vehicle spin will occur. As described in Fig. Figure 5 illustrates the spin factor β̇ xand the associated sideslip angle shows a large difference between one direction of vehicle travel VH, e.g., as set by the steering angle, and another direction of vehicle travel VT. That is, the sideslip factor indicates a tendency of the vehicle to skid. The sideslip factor corresponds to a rate of change with respect to time of the vehicle sideslip angle β̇. x .

[0046] In various embodiments, the third vehicle skid condition module 516 compares the vehicle's skid angle with a predetermined vehicle skid angle threshold β* and determines the third vehicle skid condition based on the comparison. The vehicle skid angle threshold can be determined experimentally and stored in memory. The vehicle skid angle threshold is set to indicate a probability of the vehicle skidding. If the threshold is exceeded, the third vehicle skid condition can be determined. The third vehicle skid condition module 516 can output a third flag 526 in response to the third vehicle skid condition. An automated vehicle control system, such as...At least one of the safety control systems of vehicle electronic stability control (ESC), comprehensive vehicle safety systems (CSV) and vehicle lane change assist systems, a chassis control system and the EPS system 140, may be at least partially switched off in response to the specified third condition or third flag 526.

[0047] The wing angle estimation module 514 can estimate the vehicle wing angle based on lateral acceleration, longitudinal velocity, and yaw rate, as obtained from at least one sensor 130 of the IMU 150 via the sensor module 500. A vehicle roll angle can be another acquired parameter for use in determining the wing angle.

[0048] In various embodiments, the swim angle estimation module 514 estimates the vehicle swim angle by means of an integration- or summation-based calculation. The integration- or summation-based calculation can integrate or summate successively calculated slip values, e.g., the rate of change of the swim angle. Integrating the rate of change of the swim angle results in an estimated vehicle swim angle for use by the third vehicle slip condition module 516 described above.

[0049] The following equation can be integrated or iteratively summed to estimate the swim angle: β˙x=−κβx+(ay+g sin(ψ))u−r

[0050] κ is the filter gain, β x is the estimated lateral slip angle u, a yg, ψ, r are longitudinal velocity, lateral acceleration, gravitational acceleration, vehicle roll angle, and yaw rate, all of which are either available as constants (gravity) or are obtained from the acquired signal of the IMU sensor 130 via the sensor module 500. Equation 7 allows the processing requirements for determining the vehicle roll angle to be reduced while protecting the vehicle slip angle estimation from divergence. Pseudo-integration, e.g., a low-pass filter, can be used to integrate Equation 7.

[0051] It has been found that the estimation of the sideslip angle tends to fail when pure integration is used for estimation due to the presence of noise and bias in real-world measurements. The error usually manifests as an accumulated error when integration is performed over a relatively long period. The present algorithm combats such error accumulation problems by performing a rough estimate of the sideslip angle using integration only over a relatively short period. This relatively short period is determined by the third vehicle slip condition module 516 and the sideslip angle estimation module 514, which work together to perform integration only when the second vehicle slip condition has been determined by the second vehicle slip condition module 510, optionally based on the second flag 524.The third vehicle skid condition module 516 resets the integration in response to the second vehicle skid condition, which is no longer determined by the second vehicle skid condition module 510, as described in more detail below.

[0052] The integration or summation-based calculation performed by the Sideslip Angle Estimator module 514 can be initiated based on the estimated tire caster from the Tire Caster Estimator module 512. For example, the integration or summation-based calculation can be initiated in response to a comparison of the estimated tire caster and the predetermined tire caster threshold, as performed by the second vehicle skid condition module 510. The comparison requires that the tire caster be lower than the predetermined tire caster threshold, indicating a high slip angle and vehicle instability, as previously described. The integration or summation-based calculation performed by the Sideslip Angle Estimator module 514 can be reset based on the estimated tire caster being above the tire caster threshold.In this way, the integration or summation calculation is performed for a short period, which only persists if a comparison between tire caster and the specified tire caster threshold indicates vehicle instability, in order to reduce the processor load and allow a sufficiently accurate rough estimate of the vehicle's sideslip angle.

[0053] In various embodiments, the feature control module 520 reacts ( Fig. 1) respond to at least one specific vehicle skid condition from at least one of the first, second, and third vehicle skid condition modules 504, 510, 516 to provide a command to control an associated vehicle feature. For example, the feature control module 520 can respond to at least one of the first, second, and third flags 522, 524, 526 to provide a control command to at least one of the vehicle control systems, such as the EPS system 140 and the instrument panel 252. The vehicle control system can be configured to respond to the output signal by disabling at least one function or automated control of the vehicle steering or other automated vehicle function to counteract the skid. The instrument panel can be configured to issue a skid warning to the driver of the vehicle.The warning can be a display message and / or an audible warning.

[0054] In various embodiments, the first condition of vehicle skidding can be a preventive condition, meaning it is met before the actual skidding occurs. Sufficient seconds are provided by the feature control module 520 for a warning light or other driver indication (e.g., audible). This will allow the driver to take countermeasures to reduce the risk of the vehicle skidding.

[0055] In various embodiments, the second condition of vehicle skidding indicates a probability that vehicle skidding has either occurred or will occur. The second condition may occur too soon after a vehicle skidding event to trigger a warning. Accordingly, the feature control module 520 can issue a command to an automated vehicle control system, such as the EPS system 140, to respond to the second condition by taking corrective action to prevent the vehicle skidding, if possible.

[0056] In various embodiments, the third condition of vehicle skidding indicates that vehicle skidding has actually occurred. In such a state, certain automated vehicle control systems should be deactivated to prevent energy from being transferred to the skidding vehicle and thus potentially amplifying the skidding. The feature control module 520 therefore issues a suitable shutdown command to an automated vehicle control system such as the EPS system 140 or to vehicle safety systems such as electronic stability control (ESC), comprehensive safety vehicle (CSV) systems, and lane departure warning systems.

[0057] With reference to Fig. 3 and Fig. 4 and with further reference to Fig. Figures 1-2 show flowcharts of methods 600 and 700 for determining at least one vehicle skidding condition and for controlling a vehicle 100 based thereon according to various embodiments. Methods 600 and 700 can be used in conjunction with the vehicle 100. Fig. 1 implemented and through the control system 120 from the Fig. 1. can be carried out according to various embodiments. As can be seen from the disclosure, the sequence of operations within the method is not limited to sequential processing according to the Fig. 3 and Fig. 4 is limited; rather, any suitable sequences may be chosen in accordance with the present disclosure. It is further understood that the procedure consists of the Fig. 3 and Fig. 4 can be set to run at predetermined time intervals during the operation of vehicle 100 and / or can be set to run due to predetermined events.

[0058] Fig. Figure 3 illustrates Procedure 600 for determining the first and second vehicle slip conditions. Procedure 600 of Fig. 3 are crucial in determining whether the procedure relates to the procedures 700 of Fig. 4. More precisely, when the procedures 600 of Fig. 3. If a possible vehicle skid condition is not determined, e.g., conditions that are precursors to actual vehicle skid, the processing to determine the actual vehicle skid will be carried out in accordance with procedures 700 of Fig. 4 is avoided.

[0059] In step 602, the sensor module 500 receives signals from at least one of the sensors 130, the IMU 150, and the EPS 140. The sensor module 500 can process the signals for other modules as needed.

[0060] In step 604, the front axle lateral force is estimated by the front lateral force estimation module 604. The front axle lateral force can be estimated based on lateral acceleration and yaw rate signals from the sensor module 500 using Equation 1 above.

[0061] In step 606, SAT is estimated by the SAT estimation module 502 for at least one of the front tires using a known algorithm, which may require an EPS torque from the sensor module 500.

[0062] In step 608, the pneumatic track t pThe rate of change of the front axle lateral force with respect to SAT is estimated using the Tire Caster Estimator 512. The Tire Caster Estimator 512 can estimate the rate of change using a suitable inclination estimation algorithm, such as a recursive least squares with a forgetting factor, as described above. The tire caster can be determined separately and used in subsequent steps to determine vehicle skid conditions, or it can be included in the total track, which is used in subsequent steps as representative of the tire caster, or a tire caster can be isolated based on a correction applied to the total track, as described above.

[0063] In step 610, a determination is carried out by the first vehicle skid control module 504 to determine whether the tire trail t pfor at least a predetermined period t1* decreases, determining whether a sustained decrease occurs. Step 610 can be implemented by requiring a continuous decrease in tire caster over the period, or a decrease in tire caster at each of a number of discrete, regular sampling points over the period. If step 610 results in a positive evaluation (Y for Yes in Fig. 3) that t p If the value decreases over the period t*, then the first flag 522 is output in step 612. If step 610 results in a negative evaluation (N for No in ), then the flag 522 is output in step 612. Fig. 3), procedures 600 return to the first step 602.

[0064] In step 614, the second vehicle skid control module 510 determines whether the tire caster t pFor at least a predetermined period t2*, the speed is below a predetermined threshold tp*, indicating a high risk of impending vehicle skidding. The period t2* is selected to protect against transient or noise effects that trigger the second flag 524. Tire caster may be required continuously below the threshold for the period or at each of a specific number of regular sampling points corresponding to the period. In the case of a positive assessment (Y), that t p If the value is below the predetermined threshold tp*, the second flag 524 is output in step 616. In the case of a negative evaluation (N), procedures 600 proceed to step 618 to determine the slip angle for the rear axle 102.

[0065] In step 618, a determination is made as to whether the rear slip angle α r greater than a predetermined threshold ar* The rear slip angle can be estimated by sensor module 500 using steering angle, yaw rate, and longitudinal speed. The rear slip angle is estimated by the rear axle slip angle estimation module 518, possibly using equation 6 above. If step 618 receives a positive evaluation (Y) indicating that the rear slip angle is above the predetermined threshold, then the second flag 524 is triggered. If step 618 receives a negative evaluation (N), procedures 600 return to the initial step 602.

[0066] By using the tire caster angle tp in determining the vehicle skidding condition, an indication of an impending skidding can be determined, which may allow sufficient time to apply appropriate corrections, whether automated or initiated by the driver, to avoid an actual skidding.

[0067] Procedures 600 can cause at least one of the first and second flags 616, 620 to be output to the feature control module 520. The feature control module 520 responds to these flags by appropriately controlling a vehicle feature, as described above. Furthermore, if both flags 616, 620 have been generated, i.e., both the first and second vehicle skid conditions have been determined, the procedure continues to determine the actual vehicle skid based on the vehicle sideslip angle according to step 622 and procedure 700. Fig. 4 to determine.

[0068] The procedures 700 of Fig. Step 4 of determining the actual vehicle skid is partially performed by the third vehicle skid condition module 516 and the sideslip angle estimation module. In step 702, it is determined whether the tire caster tp for one vehicle axle 101, 102 is less than the specified tire caster threshold tp*, or it is determined whether the slip angle αr for the other vehicle axle 101, 102 is greater than the slip angle threshold αr*. Step 702 is usually already performed by steps 614 and 618 of Procedure 600. Fig. 3, as described above, as a preliminary step to calling procedure 700 of Fig. 4 performed. Step 702 is performed in Fig. 4 repeated to assist in describing the integrator reset step 704. In addition to a negative evaluation (N) of step 702, resulting in a return to the initial step 602 of procedure 600 of Fig. 3, an integrator of the swim angle estimation module 514 is reset at step 704. In this way, the integrator is always in a reset state at the beginning of the vehicle swim angle estimation according to procedure 700 of Fig. 4. Furthermore, step 702 is cyclically checked to ensure that subsequent integration steps are only performed while the potential vehicle skidding inequalities of step 702 remain satisfied, i.e., there is a sustained positive evaluation of step 702.

[0069] If a positive assessment (Y) is obtained in step 702, procedures 700 proceed to step 706. In step 706, sampled signals relating to the assessment of the vehicle's swim angle are received by the swim angle estimation module 514 from the sensor module 500. For example, u, a y, g, ψ, r, which correspond to the longitudinal velocity, the lateral acceleration, the gravitational acceleration, the vehicle roll angle and the yaw rate, each read as above.

[0070] In step 708, the vehicle slip factor β̇ is determined. x The float angle is estimated by the float angle estimation module 514. The estimation can be performed using Equation 7 described above and factoring the signals read by sensor module 500 in step 706. To evaluate Equation 7, it may be necessary to establish an initial value for the float angle β. x to replace, as it is a recurring calculation. An exemplary initial value for the float angle β x can be zero.

[0071] In step 710, an integration or summation step is performed by the sideslip angle estimation module 514, using at least one previous value of the vehicle slip factor. β˙x., which is determined by at least one previous iteration of step 708, to the vehicle slip factor β̇ x The value determined in the current iteration of step 708 is added. This provides a value for the vehicle's swim angle β. x estimated.

[0072] In step 712, an assessment is performed by the third vehicle spin-out state module 516 to determine whether the estimated vehicle swim angle β x is greater than a predetermined threshold value βx*. The predetermined threshold β x * indicates the probability of the vehicle skidding. For example, a threshold value β x * must be chosen from 500 or larger.

[0073] If step 712 returns a negative rating (N), that the threshold β x* if it has not been injured, then step 706 of receiving new recorded values ​​from sensor module 500, step 708 of calculating the vehicle slip factor will be carried out. β˙x. and the step of integrating or summing the vehicle slip coefficient β̇ x iterations are repeated, and the vehicle slip factor continues to accumulate until either at least one of the tire caster angles tp is not below the tire caster angle threshold tp*, or until the axle lateral force αr is not greater than the axle lateral force threshold αr*, or until step 712 returns a positive rating.

[0074] If step 712 returns a positive rating (Y), that the threshold β x * has been injured, then the third vehicle skid condition module 516 determines the actual vehicle skid and in step 714 the third flag 526 is set.

[0075] The feature control module 520 can respond to the third flag 526 by shutting down the EPS system 140 and / or another automated vehicle control system (e.g., a vehicle safety system such as vehicle electronic stability control (ESC), comprehensive vehicle safety systems (CSV), and vehicle lane change assist systems) as previously described.

Claims

[1] Computer-implemented method for determining at least one vehicle skidding condition, comprising: Receiving at least one motion parameter of a vehicle based on signals captured by at least one vehicle sensor; estimating a self-aligning torque and at least one lateral axis force based on at least one motion parameter; estimating the tire caster for at least one tire of the vehicle using the self-aligning torque and the at least one lateral axle force; Determining at least one vehicle skidding condition based on the estimated tire trail; the computer-implemented method further includes the following: a condition of decreasing tire trail is determined and an initial vehicle skidding condition is determined in response to the condition of decreasing tire trail; and / or The estimated tire caster is compared with a predetermined tire caster threshold, and a second vehicle skidding condition is determined based on the comparison. [2] Computer-implemented method according to claim 1, wherein the method, in response to the identified at least one vehicle skidding condition, comprises at least one of the following steps: switching off at least one function of a vehicle control system, an automatic vehicle control system, to counteract the vehicle skidding and issuing a vehicle skidding warning to a driver of the vehicle. [3] Computer-implemented method according to claim 1, comprising estimating a vehicle sideslip angle and determining a third vehicle skid condition based on the vehicle sideslip angle. [4] Computer-implemented method according to claim 3, wherein the vehicle slip angle is estimated by an integration- or summation-based calculation that integrates or summates an estimated vehicle slip factor with respect to time. [5] Computer-implemented method according to claim 1, wherein the tire caster for one of the front and rear axles of the vehicle is estimated and the method comprises estimating a sideslip angle of the other axle of the vehicle and determining a second vehicle skid condition based on the estimated sideslip angle of the other axle. [6] Computer-implemented method according to claim 1, wherein the motion parameters include at least one of the following: Longitudinal speed, electronic power steering torque, steering angle, yaw rate, lateral acceleration and vehicle roll angle based on signals acquired from at least one sensor of an electronic power steering system and an inertial measurement unit. [7] System, comprehensive: a non-volatile, computer-readable medium, comprising: a first module configured to receive at least one motion parameter of a vehicle based on signals received from at least one vehicle sensor; a second module configured to estimate a tire caster for at least one tire of the vehicle using a self-aligning torque and at least one lateral axis force, wherein the self-aligning torque and the at least one lateral axis force are estimated based on the at least one motion parameter; a third module configured to determine at least one vehicle skidding condition based on the estimated tire caster; the system further includes: a first vehicle skid condition module configured to detect a decreasing tire caster state and to determine a first vehicle skid condition in response to the decreasing tire caster state; and / or a second vehicle skid condition module configured to compare the estimated tire caster with a predetermined tire caster threshold and to determine a second vehicle skid condition based on the comparison.

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