阅读说明：本技术 用于各种动力总成配置的架构和可重构轮胎力估计 (Architecture and reconfigurable tire force estimation for various powertrain configurations ) 是由 E·哈希米 S·卡萨扎德马哈巴迪 A·卡杰普尔 亢雪英 J-J·陈 H·谭 J·H·霍尔 于 2019-06-12 设计创作，主要内容包括：本公开涉及用于各种动力总成配置的架构和可重构轮胎力估计。本公开公开了一种用于估计车辆轮胎力的方法,该方法包括：由车辆的控制器接收车辆的测量的车辆加速度；由控制器接收车辆的测量的车轮速度和测量的偏航率；由控制器基于车辆的旋转部件的惯性形成惯性矩阵；使用惯性矩阵计算车辆的拐角处的扭矩；基于测量的车辆加速度、测量的车轮速度和惯性矩阵来估计车辆的轮胎力；以及由控制器基于多个所估计的纵向轮胎力和侧向轮胎力来控制车辆。(The present disclosure relates to architectures and reconfigurable tire force estimation for various powertrain configurations. The present disclosure discloses a method for estimating a vehicle tire force, the method comprising: receiving, by a controller of a vehicle, a measured vehicle acceleration of the vehicle; receiving, by a controller, a measured wheel speed and a measured yaw rate of a vehicle; forming, by a controller, an inertia matrix based on inertia of a rotating component of a vehicle; calculating a torque at a corner of the vehicle using the inertia matrix; estimating a tire force of the vehicle based on the measured vehicle acceleration, the measured wheel speed, and the inertia matrix; and controlling, by the controller, the vehicle based on the plurality of estimated longitudinal tire forces and lateral tire forces.)

1. An integrated method for estimating vehicle tire forces, the integrated method comprising:

receiving, by a controller of a vehicle, a measured vehicle acceleration of the vehicle;

receiving, by the controller, a measured wheel speed of the vehicle;

receiving, by the controller, a measured yaw rate of the vehicle;

forming, by the controller, an inertia matrix based on the measured wheel speed and the measured vehicle acceleration based on inertia of rotating components of the vehicle;

calculating torques at corners of the vehicle using the inertia matrix;

estimating tire forces of the vehicle based on the measured vehicle acceleration, the measured yaw rate, the measured wheel speeds, and the inertia matrix; and

controlling, by the controller, the vehicle based on the plurality of estimated tire forces.

2. The method of claim 1, wherein the measured vehicle acceleration is a measured longitudinal acceleration of the vehicle, and further comprising receiving, by the controller, a measured lateral acceleration of the vehicle.

3. The method of claim 2, further comprising receiving, by the controller, a road bank angle and a road bank angle.

4. The method of claim 3, further comprising correcting the measured longitudinal acceleration and the measured lateral acceleration using the road bank angle and the road bank angle to determine a corrected longitudinal acceleration of the vehicle and a corrected lateral acceleration of the vehicle.

5. The method of claim 4, wherein:

the rotating component comprises a plurality of wheels of the vehicle;

the plurality of wheels includes a first wheel, a second wheel, a third wheel, and a fourth wheel;

the vehicle includes a central drive shaft coupled to a driveline and an electronic limited slip differential (eLSD) coupled to the central drive shaft;

the eLSD includes a differential case and a clutch coupled to the differential case;

the vehicle includes a first shaft interconnecting the eLSD and the fourth wheel;

the vehicle includes a second shaft interconnecting the eLSD and the third wheel;

forming, by the controller, the inertial matrix includes:

determining moments of inertia of the differential case and the clutch; and

determining moments of inertia of the third and fourth wheels from the moments of inertia of the differential case and the clutch.

6. The method of claim 5, wherein:

the vehicle includes a plurality of tires;

the plurality of tires includes a first tire, a second tire, a third tire, and a fourth tire;

the torque at the corner of the vehicle includes a first corner torque at the first tire, a second corner torque at the second tire, a third corner torque at the third tire, and a fourth corner torque at the fourth tire;

calculating the first corner torque as a function of a first braking torque at the first tire;

calculating the second corner torque as a function of a second braking torque at the second tire;

calculating the third corner torque from the inertia matrix; and is

Calculating the fourth corner torque from the inertia matrix.

7. The method of claim 6, further comprising estimating the virtual wheel speed at the corner of the vehicle from the torque at the corner of the vehicle.

8. The method of claim 7, further comprising determining longitudinal and lateral tire forces at the corner of the vehicle from the virtual wheel speed.

9. The method of claim 8, further comprising forming a reinforcement state matrix using the virtual wheel speed at the corners of the vehicle and the longitudinal and lateral tire forces at the corners of the vehicle.

10. The method of claim 9, further comprising filtering the longitudinal and lateral tire forces at the corners of the vehicle.

Background

The present disclosure relates to methods and systems for vehicle tire force estimation, and more particularly to architecture and reconfigurable tire force estimation for various powertrain configurations.

The expelled tire force estimation method is tire-based or torque-based. Due to uncertainties in tire model parameters and variations in road friction, the estimation method may provide inaccurate results. Therefore, a robust tire force estimation method is needed.

Disclosure of Invention

Tire force estimation is useful for most control and diagnostic methods. One of the challenges faced by existing algorithms is sensitivity to road conditions. Another difficulty is how to deal with different drive train configurations with disparate actuation systems. The method disclosed by the invention solves the above problems in a robust manner.

The present disclosure describes a reconfigurable algorithm for estimating tire longitudinal and lateral tire forces at each corner of a vehicle proposed and tested on different roads and under various driving conditions. The disclosed algorithm is independent of road conditions and can be used in different configurations of AWD, RWD or FWD. The estimation method can be used for various actuation/transmission types, i.e., electronic limited slip differentials (eLSDs), open differentials, electric motors, gasoline engines, etc. The disclosed method estimates longitudinal and lateral tire forces without the need for additional or unusual vehicle sensors for different AWD/FWD/RWD driveline configurations. The algorithm does not require road friction conditions. The disclosed method may also be reconfigured for different actuation/transmission types (i.e., eLSD, open differential, electric motor, gasoline engine, etc.). The disclosed method provides good estimation results in terms of drift maneuvers as well as lane changes, severe steering and more specific combined slip maneuvers. The disclosed method takes into account driving conditions in order to make a more accurate and reliable estimate on each corner. An accelerometer in a vehicle may generate noise and the signal generated by the accelerometer may fluctuate. The disclosed method is robust to accelerometer noise and fluctuations. The disclosed method is robust to tire parameter variations (variations due to wear, aging, and temperature variations have no effect on longitudinal and lateral wheel force estimation). The disclosed method employs a sliding/excitation monitoring time window to remove outliers under different driving conditions. Compared with the existing method, the method disclosed by the invention reduces the calculation complexity. By employing this method, tire force estimation can be used to significantly improve the performance of vehicle motion.

A method for estimating the tyre force of a vehicle (longitudinal and lateral) comprises: receiving, by a controller of a vehicle, a measured vehicle acceleration of the vehicle; receiving, by the controller, a measured yaw rate of the vehicle; receiving, by a controller, a measured wheel speed of a vehicle; forming, by the controller, an inertia matrix based on the inertia of rotating components of the vehicle, based on the measured wheel speeds and the measured vehicle accelerations; calculating the torque at the corners of the vehicle using the inertia matrix and torque generated by the engine (or electric motor) through various differential configurations, including open differentials and eLSD; estimating a tire force of the vehicle based on the measured vehicle acceleration, the measured wheel speed, and the inertia matrix; and controlling, by the controller, the vehicle based on the plurality of estimated tire forces.

The measured acceleration may be referred to as a measured longitudinal acceleration of the vehicle. The method may also include receiving, by the controller, a measured lateral acceleration of the vehicle. The method may also include receiving, by the controller, a road bank angle and a road bank angle. The method may further include correcting the measured longitudinal acceleration and the measured lateral acceleration using the road bank angle and the road bank angle to determine a corrected longitudinal acceleration of the vehicle and a corrected lateral acceleration of the vehicle. The rotating component may comprise a plurality of wheels of the vehicle. The plurality of wheels may include a first wheel, a second wheel, a third wheel, and a fourth wheel. The vehicle may include a central drive shaft coupled to the driveline and an electronic limited slip differential (eLSD) coupled to the central drive shaft. The eLSD may include a differential case and a clutch coupled to the differential case.

The vehicle may include a first axle interconnecting the eLSD and the fourth wheel. The vehicle may include a second shaft interconnecting the eLSD and a third wheel. The controller may form an inertia matrix by determining moments of inertia of the differential case and the clutch; and determining moments of inertia of the third and fourth wheels based on moments of inertia of the differential case and the clutch. The plurality of tires may include a first tire, a second tire, a third tire, and a fourth tire. The torque at the corners of the vehicle includes a first corner torque at the first tire, a second corner torque at the second tire, a third corner torque at the third tire, and a fourth corner torque at the fourth tire. The first corner torque may be calculated from a first braking torque at the first tire. The second corner torque may be calculated from a second braking torque at a second tire. The third corner torque may be calculated from the inertia matrix. The fourth corner torque may be calculated from the inertia matrix.

The method may further include estimating a virtual wheel speed at the corners of the vehicle from the torque at the corners of the vehicle. The method may further include determining longitudinal tire forces and lateral tire forces at corners of the vehicle from the virtual wheel speed, the corrected longitudinal/lateral acceleration (in road angle), and the measured yaw rate. The method may also include forming a reinforcement state matrix using the virtual wheel speed at the corners of the vehicle and the longitudinal tire force and the lateral tire force at the corners of the vehicle. The method may also include filtering longitudinal tire forces and lateral tire forces at corners of the vehicle.

The present disclosure also describes a vehicle. The vehicle includes a plurality of rotating members. The plurality of rotating components includes a plurality of tires. The vehicle also includes a drive train coupled to the plurality of tires and an actuator coupled to the plurality of tires. The vehicle also includes a plurality of sensors and a controller in communication with the plurality of sensors. The controller is programmed to perform the above-described method.

The above features and advantages and other features and advantages of the present teachings are readily apparent from the following detailed description of some of the best modes and other embodiments for carrying out the present teachings when taken in connection with the accompanying drawings.

Drawings

Fig. 1 is a schematic block diagram of a vehicle.

Fig. 2 is a schematic view of the vehicle of fig. 1.

FIG. 3 is a flow chart of a method for tire force estimation.

Detailed Description

The following detailed description is merely exemplary in nature and is not intended to limit the application and uses. Furthermore, there is no intention to be bound by any expressed or implied theory presented in the preceding technical field, background, brief summary or the following detailed description. As used herein, the term "module" refers to hardware, software, firmware, electronic control components, processing logic, and/or processor devices (individually or in combination), including but not limited to: an Application Specific Integrated Circuit (ASIC), an electronic circuit, a processor (shared, dedicated, or group) and memory that execute one or more software or firmware programs, a combinational logic circuit, and/or other suitable components that provide the described functionality.

Embodiments of the present disclosure may be described herein in terms of functional and/or logical block components and process steps. It should be appreciated that such block components may be realized by a number of hardware, software, and/or firmware configured to perform the specified functions. For example, embodiments of the present disclosure may employ various integrated circuit components, e.g., memory elements, digital signal processing elements, logic elements, look-up tables, or the like, which may carry out a variety of functions under the control of one or more microprocessors or other control devices. Further, those skilled in the art will recognize that embodiments of the present disclosure may be implemented in conjunction with a variety of systems, and that the systems described herein are merely exemplary embodiments of the present disclosure.

For the sake of brevity, techniques related to signal processing, data fusion, signaling, control, and other functional aspects of the systems (and the individual operating components of the systems) may not be described in detail herein. Furthermore, the connecting lines shown in the various figures contained herein are intended to represent example functional relationships and/or physical couplings between the various elements. It should be noted that alternative or additional functional relationships or physical connections may be present in an embodiment of the disclosure.

As shown in FIG. 1, the vehicle 10 generally includes a chassis, a body 14, and front and rear wheels 17. The plurality of wheels includes a first (front left) wheel 17a, a second (front right) wheel 17b, a third (rear left) wheel 17c, and a fourth (rear right) wheel 17 d. The body 14 is disposed on the chassis and substantially encloses the components of the vehicle 10. The body 14 and chassis may together form a vehicle frame. The wheels 17 are each rotationally coupled to the chassis near a respective corner of the body 14. The vehicle 10 also includes a plurality of rotating components, such as the wheels 17, the central drive shaft 12, a differential case 52 of the differential 50, a first (or right) axle 54 interconnecting the differential 50 to the fourth wheel 17d, and a second (or left) axle 56 interconnecting the differential 50 to the third wheel 17 c. The central drive shaft 12 transfers torque from the driveline 22 to the differential 50. The differential 50 may be an open differential or an electronic limited slip differential (eLSD) and may include a differential case 52 and a clutch 58 coupled to the differential case 52. The differential carrier 52 may include a rotating rear gear and therefore rotate. During rotation, the differential carrier transfers torque from the differential 50 to the first and second shafts 54, 56.

In various embodiments, the vehicle 10 may be an autonomous vehicle, and the control system 98 is incorporated into the vehicle 10. The control system 98 may be referred to simply as a system. The vehicle 10 is, for example, a vehicle that is automatically controlled to carry passengers from one location to another. Vehicle 10 is depicted in the illustrated embodiment as a sedan, but it should be understood that another vehicle may be used, including motorcycles, trucks, Sport Utility Vehicles (SUVs), Recreational Vehicles (RVs), marine vessels, aircraft, and the like. In an exemplary embodiment, the vehicle 10 may be a partially or fully automated vehicle. The four-level system represents "highly automated," meaning that the automated driving system of aspects of the dynamic driving task makes driving pattern-specific executions even if the human driver does not react appropriately to the intervention request. A five-level system represents "fully automated," meaning performed by an automated driving system of aspects of a dynamic driving task all the time, under a number of road and environmental conditions that a human driver can manage.

As shown, the vehicle 10 generally includes a propulsion system 20, a transmission system 22, a steering system 24, a braking system 26, a sensor system 28, an actuator system 30, at least one data storage device 32, at least one controller 34, and a communication system 36. In various embodiments, propulsion system 20 may include an electric machine, such as a traction motor and/or a fuel cell propulsion system. The vehicle 10 also includes a battery (or battery pack) 21 electrically connected to the propulsion system 20. Thus, battery 21 is configured to store electrical energy and provide electrical energy to propulsion system 20. Additionally, propulsion system 20 may include an internal combustion engine. The transmission 22 is configured to transmit power from the propulsion system 20 to the vehicle wheels 17 according to a selectable speed ratio. According to various embodiments, transmission system 22 may include a step ratio automatic transmission, a continuously variable transmission, or other suitable transmission. The braking system 26 is configured to provide braking torque to the wheels 17. In various embodiments, the braking system 26 may include friction brakes, brake-by-wire, a regenerative braking system such as an electric motor, and/or other suitable braking systems. The steering system 24 influences the position of the vehicle wheels 17.

The sensor system 28 includes one or more sensors 40 (i.e., sensing devices) that sense observable conditions of the external environment and/or the internal environment of the vehicle 10. The sensors 40 are in communication with the controller 34 and may include, but are not limited to, one or more radars, one or more light detection and ranging (light) sensors, one or more Global Positioning System (GPS) devices, one or more cameras (e.g., optical and/or thermal cameras), ultrasonic sensors, yaw rate sensors, gyroscopes, one or more Inertial Measurement Units (IMUs), one or more Steering Angle Sensors (SAS) for measuring steering wheel position angle and steering rate, and/or other sensors. Actuator system 30 includes one or more actuator devices 42 that control one or more vehicle features such as, but not limited to, propulsion system 20, transmission system 22, steering system 24 (including steering wheel 25), active aerodynamic devices 60 (fig. 2), and braking system 26. In various embodiments, the vehicle features may also include interior and/or exterior vehicle features such as, but not limited to, door, trunk, and compartment features such as air, music, lighting, etc. (not numbered). The sensor system 28 includes one or more Global Positioning System (GPS) devices 40g configured to detect and monitor route data (i.e., route information). The GPS device 40g is configured to communicate with a GPS to locate the position of the vehicle 10 around the globe. The GPS device 40g is in electronic communication with the controller 34. GPS device 40g includes a GPS transmitter to receive data (such as terrain data) from the GPS. The terrain data includes road grade and road bank angle of the road on which the vehicle 10 is located.

The data storage device 32 stores data for automatically controlling the vehicle 10. In various embodiments, the data storage device 32 stores a defined map of the navigable environment. In various embodiments, the defined map may be predefined by and obtained from a remote system. For example, the definition map may be assembled by a remote system and transmitted to the vehicle 10 (wirelessly and/or by wire) and stored in the data storage device 32. It is recognized that the data storage device 32 may be part of the controller 34, separate from the controller 34 and part of a separate system.

The controller 34 includes at least one processor 44 and a non-transitory computer-readable storage device or medium 46. The processor 44 may be a commercially available or custom processor, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), an auxiliary processor among several processors associated with the controller 34, a semiconductor-based microprocessor (in the form of a microchip or chip set), a macroprocessor, combinations thereof, or a device commonly used for executing instructions. The computer-readable storage device or medium 46 may include volatile and non-volatile storage such as in Read Only Memory (ROM), Random Access Memory (RAM), and keep-alive memory (KAM). The KAM is a persistent or non-volatile memory that can be used to store various operating variables when the processor 44 is powered down. The computer-readable storage device or medium 46 may be implemented using a number of memory devices, such as PROMs (programmable read Only memory), EPROMs (electrically PROM), EEPROMs (electrically erasable PROM), flash memory, or another electric, magnetic, optical, or combination memory device capable of storing data, some of which represent executable instructions used by the controller 34 to control the vehicle 10.

The instructions may comprise one or more separate programs, each of which comprises an ordered listing of executable instructions for implementing logical functions. When executed by processor 44, the instructions receive and process signals from sensor system 28, execute logic, calculations, methods, and/or algorithms for automatically controlling components of vehicle 10, and generate control signals to actuators 30 to automatically control components of vehicle 10 based on the logic, calculations, methods, and/or algorithms. Although a single controller 34 is shown in FIG. 1, embodiments of the vehicle 10 may include several controllers 34 that communicate over a suitable communication medium or combination of communication media and cooperate to process sensor signals, execute logic, calculations, methods and/or algorithms, and generate control signals to automatically control features of the vehicle 10.

In various embodiments, one or more instructions of controller 34 are embodied in control system 98. The vehicle 10 includes a user interface 23, which may be a touch screen in the dashboard. The user interface 23 is in electronic communication with the controller 34 and is configured to receive input from a user (e.g., a vehicle operator). Accordingly, the controller 34 is configured to receive input from a user via the user interface 23. The user interface 23 includes a display configured to display information to a user (e.g., a vehicle operator or passenger).

The communication system 36 is in communication with the controller 34 and is configured to wirelessly transmit information to and from other entities 48, such as, but not limited to, other vehicles ("V2V" communication), infrastructure ("V2I" communication), remote systems, and/or personal devices. In an exemplary embodiment, the communication system 36 is a wireless communication system configured to communicate via a Wireless Local Area Network (WLAN) using the IEEE 802.11 standard or by using cellular data communication. However, additional or alternative communication methods, such as Dedicated Short Range Communication (DSRC) channels, are also considered to be within the scope of the present disclosure. A DSRC channel refers to a one-way or two-way short-to-mid-range wireless communication channel specifically designed for automotive use and a set of corresponding protocols and standards. Accordingly, communication system 36 may include one or more antennas and/or transceivers for receiving and/or transmitting signals, such as Cooperative Sensing Messages (CSMs). The communication system is configured to wirelessly communicate information I between the vehicle 10 and a second vehicle.

Fig. 1 is a schematic block diagram of a control system 98 configured to control a vehicle 10. Controller 34 of control system 98 is in electronic communication with brake system 26, propulsion system 20, and sensor system 28. The braking system 26 includes one or more brake actuators (e.g., brake calipers) coupled to one or more wheels 17. When actuated, the brake actuators apply brake pressure on one or more wheels 17 to slow the vehicle 10. The propulsion system 20 includes one or more propulsion actuators for controlling the propulsion of the vehicle 10. For example, as discussed above, the propulsion system 20 may include an internal combustion engine, and in such a case, the propulsion actuator may be a throttle valve specifically configured to control airflow in the internal combustion engine. The sensor system 28 is in electronic communication with the controller 34 and may include one or more accelerometers (or one or more gyroscopes) coupled to one or more wheels 17. The accelerometer is in electronic communication with the controller 34 and is configured to measure and monitor longitudinal and lateral acceleration of the vehicle 10. The sensor system 28 may include one or more speed sensors configured to measure the speed (or velocity) of one or more wheels 17. A speed sensor (i.e., one of the sensors 40) is coupled to the controller 34 and is in electronic communication with one or more of the wheels 17.

Referring to FIG. 2, the vehicle 10 may include one or more active aerodynamic devices 60. The term "active aerodynamic device" refers to a physically tangible structure (such as spoilers, side wings, air dams, bed plates, guide vanes, vanes) that is specifically configured to disrupt existing airflow patterns around the vehicle 10 and that is movable relative to the main body 14. Each wheel 17 (fig. 1) is coupled to tires such as a first tire 19a (i.e., a left front tire), a second tire 19b (i.e., a right front tire), a third tire 19c (i.e., a left rear tire), and a fourth tire 19d (i.e., a right rear tire). The tires are located at the corners of the vehicle 10. FIG. 2 also shows tire forces (i.e., first longitudinal tire force F)_x1First lateral tire force F_y1Second longitudinal tire force F_x2Second lateral tire force F_y2A third longitudinal tire force Fx3, a third lateral tire force F_y3Fourth longitudinal tire force F_x4And a fourth lateral tire force F_y4They are also referred to as forces at the corners of the vehicle 10). Fig. 2 also shows the yaw direction ψ of the vehicle 10.

FIG. 3 is a flow chart of a method 100 for tire force estimation. The method 100 may be performed by the controller 34 and begins at a start block 102. The method 100 then proceeds to block 104. Block 104 requires parameter definition and initialization. The parameter definitions may be stored on a non-transitory computer readable storage device or medium 46 and may include vehicle mass and geometric parameters p_vInertia and effective radius matrix (including tire effective rolling radius)

) Initial state of reinforcement in state observer (tire force)Internal constants η _ i, ∈ {1,2,3,4} in the longitudinal force observer, observer gain matrix (such as longitudinal force observations at each cornerGain (related to wheel speed)

Longitudinal force observer gain matrix at each corner (associated with acceleration and yaw rate correction)

Side force observer gain matrix at each corner (associated with acceleration and yaw rate correction)

After block 104, the method 100 proceeds to block 106.

At block 106, the controller 34 receives the sensor measurements and estimates. For example, at block 106, the controller 34 receives a measured vehicle acceleration of the vehicle 10 measured by one or more sensors 40 (e.g., accelerometers and/or IMUs). Specifically, the controller 34 receives a measured longitudinal acceleration a of the vehicle 10_xAnd measured lateral acceleration a_y. The controller 34 also receives a measured steering wheel angle of the steering wheel 25 measured by one of the sensors 40 (e.g., a steering angle sensor). The controller 34 also receives a measured yaw rate r of the vehicle 10 measured by one or more sensors 40 (e.g., yaw rate sensors, gyroscopes, IMUs). The controller 34 also receives measured wheel speeds (ω) of one or more wheels 17 measured by one or more sensors 40 (e.g., speed sensors)_iI ∈ {1,2,3,4 }). The controller 34 receives the road grade angle θ of the road on which the vehicle 10 is located_rAnd an angle of inclination phi_rTo correct the measured longitudinal acceleration a, if any_xAnd measured lateral acceleration a_y. The controller 34 receives the road grade angle θ from one of the sensors 40 (e.g., a GPS device)_rAnd an angle of inclination phi_r. At block 106, the controller 34 also estimates several torques, including a braking torque T at each corner/tire_biEngine torque, electric motor torque, differential torque (such as central drive shaft to differential 50 torque T)_gAnd clutch torque T_c(e.g., eLSD control clutch torque)). In thatFollowing block 106, the method 100 proceeds to block 108.

At block 108, the controller 34 corrects the measured longitudinal acceleration a using the road bank angle and the road bank angle_xAnd measured lateral acceleration a_yTo determine a corrected longitudinal acceleration and a corrected lateral acceleration of the vehicle 10. Refining the measured longitudinal acceleration a using a time window for transition areas with high acceleration measurement fluctuations and maneuvers on the gravel surface_xAnd measured lateral acceleration a_y. The method 100 then proceeds to block 110.

At block 110, the controller 34 determines whether the corrected longitudinal acceleration, the corrected lateral acceleration, and the measured wheel speed ω at each corner/tire of the vehicle 10 are satisfied_ijThe rest condition of (2). In other words, at block 110, if the corrected longitudinal and lateral acceleration of the vehicle 10 and the measured wheel speed ω are both corrected for_iIs equal to or less than the respective predetermined threshold, the method 100 returns to block 104. On the other hand, if the corrected longitudinal acceleration, the corrected lateral acceleration and the measured wheel speed ω at each corner/tire of the vehicle 10_iiAre greater than the respective predetermined threshold, the method 100 proceeds to block 112.

At block 112, the controller 34 based on the inertia of the rotating components of the vehicle 10 (e.g., the wheels 17, the central drive shaft 12, the differential case 52 of the differential 50, the first (or right) axle 54 interconnecting the differential 50 to one of the wheels 17, and the second (or left) axle 56 interconnecting the differential 50 to one of the wheels 17) based on the measured wheel speed ω_iAnd measured or corrected vehicle acceleration of the vehicle 10 (e.g., measured longitudinal acceleration a determined at block 108)_xAnd measured lateral acceleration a_yOr corrected longitudinal acceleration and corrected lateral acceleration) to form an inertial matrix. If the differential 50 is an eLSD at the rear rail of the vehicle 10, the controller 34 may calculate the inertial component of the inertial matrix using equations (1) and (2):

for left rear tire 19c and right rear tire 19d (2)

Wherein:

I_dis the moment of inertia of the differential case;

I_inthe moment of inertia of the central drive shaft 12;

is the input shaft moment of inertia (to eLSD);

I_t3，I_t4is the moment of inertia of the rear eLSD side shaft;

is the moment of inertia of the left and right rear axles (i.e., first axle 54 and second axle 56) from the eLSD to the third wheel 17c and fourth wheel 17 d; and is

n is the eLSD gear ratio.

As described above, the inertia matrix is formed based on the inertia of the wheels 17, the differential case 52, the center drive shaft 12, and the right/left axles (i.e., the first axle 54 and the second axle 56) and the like from the differential 50 (e.g., the eLSD or the open differential) to the third wheels 17c and the fourth wheels 17 d. A gain matrix is formed and the latest high slip rate condition is incorporated for any gain update. The algorithm detects a saturation condition to assign an adaptive observer gain. The threshold value of saturation detection varies depending on the driving conditions. At block 112, the controller 34 forms a discrete system, inertia, and input matrix (with enhanced wheel speed and force states). A discrete system matrix and an enhanced state of the generalized force estimation structure are generated. The discretization is done by the step-size invariance of the exact solution. After block 112, the method 100 proceeds to block 114.

At block 114, the controller 34 uses the inertia matrix to calculate the torque at the corners of the vehicle 10. To do so, controller 34 employs equations (3), (4), and (5):

wherein:

T_gis the estimated output torque from the driveline 22 to the central drive shaft 12;

T_cis an estimated clutch torque of the differential clutch 58 (e.g., the eLSD clutch torque);

ω₃is the measured wheel speed of the third wheel 17 c;

ω₄a measured wheel speed for the fourth wheel 17 d;

n is the eLSD gear ratio;

I_t3，I_t4is the moment of inertia of the rear eLSD side shaft;

moment of inertia of the input shaft (to eLSD) inertia;

braking torques at the first tire 19a, the second tire 19b, the third tire 19c, and the fourth tire 19d, respectively;

the corner torques at the first tire 19a, the second tire 19b, the third tire 19c, and the fourth tire 19d, respectively.

As described above, the torque at the corners of the vehicle 10 includes the first corner torque at the first tire 19aSecond corner torque at second tire 19bThird corner torque at third tire 19c

And a fourth corner torque at the fourth tire 19dAccording to equations (3), (4) and (5), according to the first braking torque at the first tyre 19a

Calculating a first corner torqueAccording to a second braking torque at the second tyre 19b

Calculating a second corner torque

Moment of inertia from inertia matrix (e.g., input shaft (to eLSD)) inertia

) Calculating a third corner torqueAnd moment of inertia according to the inertia matrix (e.g., input shaft (to eLSD)) inertia) Calculating a fourth corner torquePower transmission based by torque generation module (block 114)And actuator torque to estimate the corner torque. The reconfigurable torque generating architecture facilitates the use of the tire force estimator with various powertrain configurations (FWD/RWD/AWD) and actuator types (internal combustion engine, electric motor, open differential, eLSD, etc.). The approximate output torque from the actuators and transmissions (e.g., from the driveline 22 to the central drive shaft 12, and clutch torque in the case of eLSD) is used to form the input matrix. The developed observer with modular estimators at each corner accounts for uncertainty in estimated torque from the engine, central drive shaft 12, open differential shaft, and eLSD clutch. After block 114, the method 100 proceeds to block 116.

At block 116, the controller 34 forms an augmented state matrix using the virtual wheel speed estimator and vehicle plane dynamics. To do so, controller 34 may employ equations (6), (7), and (8):

wherein:

for q ∈ {5,6 };

i∈{1,2,3,4}；

for each corner virtual wheel speed;

ω_iis each one ofMeasured wheel speeds at the corners;

total torque at each cornerAre obtained from (3) to (5);

is the moment of inertia of the wheel 17 (at each corner);

is the effective rolling radius of the tire;

η_iis an internal constant of the longitudinal force observer (one of the input observer gains);

a longitudinal force observer gain (one of the input observer gains) related to the wheel speed for each corner;

for the wheel speed at each corner;

m is the total mass of the vehicle;

is the total yaw moment at the vehicle CG;

a longitudinal force observer gain matrix for each corner (related to acceleration and yaw rate corrections);

a side-force observer gain matrix for each corner (related to acceleration and yaw-rate corrections);

for each corner/tire estimated longitudinal tire force; and is

Is the estimated lateral tire force at each corner/tire.

As described in the above equation, the virtual wheel speed at the corners of the vehicle is calculated from the torque at the corners of the vehicle 10. At block 118, controller 34 bases the virtual wheel speed on

Determining longitudinal and lateral tire forces at corners of vehicle 10The controller 34 estimates tire forces of the vehicle 10 based on the vehicle acceleration measured at block 116, the measured yaw rate, the measured wheel speeds, and the inertia matrix.

The enhanced state vector with dynamic force may be defined as:

wherein:

as a virtual wheel speed at each corner of the vehicle 10;

is the estimated longitudinal tire force at the first tire 19 a;

is the estimated longitudinal tire force at the second tire 19 b;

is the estimated longitudinal tire force at the third tire 19 c;

is the estimated longitudinal tire force at the fourth tire 19 d;

for the estimated lateral tire force at each front tire (first tire 19a and second tire 19b) of the vehicle 10;

for the estimated lateral tire force at each rear tire (first tire 19c and second tire 19d) of the vehicle 10; and is

For the estimated enhanced state vector at each time step.

The direct estimator formula with simultaneous correction/observation is defined as:

wherein:

is an enhanced state vector;

A_cis a continuous time state matrix; and is

B_cIs a continuous time input matrix.

At block 116, the new enhanced state and direct estimator equations with simultaneous correction/observation are computationally efficient, as in the form of a state matrix. Wheel speed, IMU data (acceleration and yaw rate) were observed using a disturbance observer, wheel dynamics and longitudinal/lateral dynamic models. The observer gain assignment defines the order of dependence on the model or measurement (wheel speed and acceleration). The gain variation is based on high slip rate conditions to avoid fluctuations (caused by non-linearities/disturbances) during the transition region of harsh handling. After block 116, the method 100 proceeds to block 118.

At block 118, the controller 34 employs the input and a linear observer. The vehicle plane dynamics, wheel dynamics and input observer at each corner (tire) are combined to ensure reliable estimation in the low excitation region and the high excitation region. Specifically, controller 34 forms continuous-time state matrix A using the inertia, gain, and model input matrices defined by equations (11) - (16)_cAnd a continuous time state matrix B_c：

Equations (11) - (16) are system matrices that transform the input/output form. At block 118, the continuous-time state matrix A is aligned using equation (17)_cAnd a continuous time state matrix B_cCarrying out discretization:

wherein:

A_c,A_drespectively a continuous time state matrix and a discrete time state matrix; and is

B_c,B_dRespectively a continuous time input matrix and a discrete time input matrix.

At block 118, the controller 34 then estimates the enhanced states (longitudinal and lateral forces) using the direct input observer) And virtual wheel speedAfter block 118, the method 100 proceeds to block 120.

At block 120, controller 34 determines whether a persistence criterion related to a saturation condition is satisfied. To do so, the controller 34 checks the persistence criteria (through a time window) to remove short term outliers and avoid incorrect gain assignments. In addition, the controller 34 may detect saturation conditions (obtained from wheel speeds/accelerations) and excitation levels (steering and acceleration measurements). In other words, controller 34 determines whether the tire force is less than or greater than the maximum threshold and the minimum threshold, respectively, under saturated conditions. If the persistence criteria are not satisfied, controller 34 proceeds to block 122. At block 122, the controller 34 filters the tire forces at each corner. On the other hand, if the persistence criteria are met, the method 100 proceeds to block 124. At block 124, the controller 34 passes the estimated virtual wheel speed (equation (6)) to the estimator (i.e., equations (7) and (8)). After block 124, the method 100 proceeds to block 126 and block 130.

At block 126, the enhancement state and system matrix for each corner are reinitialized. At block 130, tire force is determined using the above formulaAndafter block 126, the method 100 proceeds to block 128. The longitudinal force of each corner is estimated by a direct (discretized) estimator formula and the variable observer gain is refined to have a reliable estimate in large steering maneuvers or low excitation situations and avoid oscillations generated by harsh braking/acceleration.

At block 128, the controller 34 waits for the next sample data (i.e., the data collected at block 106) and returns to block 106. After block 130, the method 100 proceeds to block 132. At block 132, the controller 34 uses the longitudinal tire force

Or lateral tire force

The vehicle 10 is controlled (by active front/rear steering). For example, controller 34 may be based on an estimated tire force at each cornerAnd the axial lateral force of the vehicle 10

Control one or more actuator devices 42 (e.g., active pneumatic device 60, traction/stability control system, propulsion system 20, transmission system 22, steering system 24, and/or braking system 26).