Method and apparatus for facilitating tire force estimation

Abstract

The present disclosure provides "Methods and devices for facilitating tire force estimation". Methods and devices for facilitating TPMS broadcast mode selection are disclosed. An exemplary vehicle includes a sensor, a processor, and a memory. The sensor is used to generate vehicle dynamics information (VDI). The processor communicates with the memory and the sensor. The processor is configured to: estimate relative pitch angle and roll angle using the VDI, estimate tire normal force using the relative pitch angle and roll angle and the VDI, estimate tire rolling resistance using the tire normal force, and estimate tire longitudinal force and tire lateral force based on the tire rolling resistance and the VDI.

Description

Technical Field

[0001] The present disclosure relates generally to vehicle dynamics measurement and analysis, and more particularly, to methods and apparatus that facilitate tire force estimation. Background Art

[0002] In recent years, vehicles have been equipped with on-board computing platforms (OBCPs) and sensors including inertial measurement units (IMUs) to measure how the vehicle moves in space, which is called vehicle dynamics. The IMU and OBCP are typically located within the body of the vehicle. The IMU measures vehicle acceleration along three axes: x (forward / reverse), y (lateral), and z (up / down). The IMU additionally measures how fast the vehicle rotates around three axes, called: pitch rate (around the y-axis), yaw rate (around the z-axis), and roll rate (around the x-axis). The OBCP uses the measurement data to estimate the forces acting on the vehicle. Summary of the invention

[0003] The appended claims define the present application. This disclosure summarizes aspects of the embodiments and should not be used to limit the claims. Other embodiments are contemplated based on the techniques described herein, which will be apparent to one of ordinary skill in the art having studied the following drawings and detailed description, and these embodiments are intended to fall within the scope of the present application.

[0004] An exemplary vehicle is disclosed. The vehicle includes a sensor, a processor, and a memory. The sensor is used to generate vehicle dynamics information (VDI). The processor communicates with the memory and the sensor. The processor is configured to: estimate relative pitch angle and roll angle using the VDI; estimate tire normal force using the relative pitch angle and roll angle and the VDI; and estimate tire rolling resistance using the tire normal force.

[0005] An exemplary method is disclosed. The method includes: using a processor to estimate relative pitch angle and roll angle using VDI from a sensor; using a processor to estimate tire normal force using the relative pitch angle and roll angle and the VDI; and using a processor to estimate tire rolling resistance using the tire normal force.

[0006] An exemplary system is disclosed. The system includes an inertial measurement unit (IMU) and a processor. The IMU is disposed in a vehicle. The processor communicates with the IMU. The processor is configured to: receive a VDI from the IMU; estimate a relative pitch angle and a relative roll angle based on the VDI; estimate a front effective mass and a rear effective mass based on the relative pitch angle; estimate a tire normal force based on the relative roll angle and the front effective mass and the rear effective mass; estimate a tire rolling resistance based on the tire normal force and the VDI; and estimate a tire longitudinal force and a tire lateral force based on the tire rolling resistance and the VDI. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] For a better understanding of the present invention, reference may be made to the embodiments shown in the following drawings. The components in the drawings are not necessarily drawn to scale, and related elements may be omitted, or in some cases the proportions may be exaggerated in order to emphasize and clearly illustrate the novel features described herein. In addition, as is known in the art, the system components may be arranged in various ways. Moreover, in the drawings, the same reference numerals represent corresponding parts in several views.

[0008] Figure 1 is a schematic top view of a vehicle operating in accordance with the teachings of the present disclosure.

[0009] Figure 2 yes Figure 1 Schematic side view of a vehicle.

[0010] Figure 3 yes Figure 1 Schematic front view of a vehicle.

[0011] Figure 4 yes Figure 1 Another schematic side view of a vehicle.

[0012] Figure 5 yes Figure 1 Another schematic front view of a vehicle.

[0013] Figure 6 yes Figure 1 A perspective view of a wheel and tire assembly of a vehicle.

[0014] Figure 7 yes Figure 1 Block diagram of the electronic components of a vehicle.

[0015] Figure 8 yes Figure 7 A more detailed block diagram of the Tire Dynamics Analyzer.

[0016] Fig. 9 is a flow chart of a method for estimating tire forces, which can be obtained by Figure 3 The electronic components are implemented. DETAILED DESCRIPTION

[0017] While the present invention may be embodied in various forms, some exemplary and non-limiting embodiments are shown in the drawings and will be described below, but it should be understood that this disclosure is considered as examples of the invention and is not intended to limit the invention to the particular embodiments shown.

[0018] The forces on a vehicle's tires at the tire-road contact point are important for vehicle dynamics but are difficult to measure directly. Therefore, tire forces are usually estimated based on vehicle motion measured by vehicle sensors (e.g., vehicle acceleration and rotation rate). Real-time estimated tire force values ​​can be used in a variety of applications, including safety-related vehicle control design, tire wear monitoring, and indirect driving behavior analysis.

[0019] Traditionally, there are two methods for estimating tire forces based on vehicle motion: using a predetermined tire force-slip model and not using a tire force-slip model. Using a tire force-slip model, vehicle dynamics information is input into the tire force-slip model to produce tire force estimates. Using a tire force-slip model approach requires fewer sensors, but the resulting estimates are often inaccurate due to inaccuracies in the force-slip model caused by tire nonlinear characteristics and other factors such as temperature and humidity. Without using a tire force-slip model, tire forces are estimated using only vehicle dynamics information. However, when using some existing estimation methods without the aid of a tire force-slip model, achieving accurate results can be challenging under certain operating conditions, especially when the vehicle is operating in a steady state and tire forces are relatively small.

[0020] The present disclosure provides a method and apparatus for estimating tire forces (including driven wheel longitudinal forces during constant speed cruising) in real time under all driving conditions using vehicle dynamics information without resorting to tire force-slip models. By estimating tire forces under all driving conditions, driving habits and long-term tire wear can be monitored.

[0021] Figure 1 is a schematic top view of a vehicle 110 operating in accordance with the teachings of the present disclosure. Figure 2 yes Figure 1 Schematic side view of a vehicle 110 . Figure 3 yes Figure 1 A schematic front view of a vehicle 110 is shown. Figure 1 , Figure 2 and Figure 3 As shown, vehicle 110 includes wheel and tire assembly 112, center of gravity (CoG) 114, roll center 116, sensors 120, on-board computing platform (OBCP) 130, infotainment head unit (IHU) 140, and body 150. Body 150 includes suspension elements 152 such as links, struts, springs, dampers, bushings, etc.

[0022] The wheel and tire assembly 112 includes a corresponding axle. The wheel and tire assembly 112 is rotatably connected to the body 150 via the axle and the suspension element 152. The wheel and tire assembly includes a left front wheel and tire assembly 112Fl, a right front wheel and tire assembly 112Fr, a left rear wheel and tire assembly 112Rl, and a right rear wheel and tire assembly 112Rr. In the example shown, the wheel and tire assembly 112 is substantially the same. In some examples, the front wheel and tire assembly 112 is different from the rear wheel and tire assembly 112 (not shown) (e.g., a larger wheel and tire on a rear wheel drive sports vehicle). The wheel and tire assembly 112, CoG114, and roll center 116 define a plurality of distances between each other, referred to as the geometry of the vehicle 110. The geometry of the vehicle 110 includes:

[0023] H c , the height of CoG114;

[0024] H r , the height of the roll center 116;

[0025] e F , a front track between the left front wheel and tire assembly 112Fl and the right front wheel and tire assembly 112Fr;

[0026] e R , the rear track between the left rear wheel and tire assembly 112Rl and the left rear wheel and tire assembly 112Rr;

[0027] L R , the longitudinal distance from CoG114 to the rear axle;

[0028] L F , the longitudinal distance from the center of gravity to the front axle; and

[0029] L, longitudinal distance between front and rear axles.

[0030] The sensors 120 may be arranged in and around the vehicle 110 in any suitable manner. The sensors 120 may be installed to measure characteristics of the exterior surroundings of the vehicle 110. Additionally, some sensors 120 may be installed within the cabin of the vehicle 110 or in the body of the vehicle 110 (such as the engine compartment, wheel well, etc.) to measure characteristics of the interior of the vehicle 110. For example, such sensors 120 may include accelerometers, odometers, tachometers, pitch and yaw rate sensors, wheel speed sensors, microphones, tire pressure sensors, and biometric sensors, among others. In the example shown, the sensors 120 are wheel speed sensors, powertrain monitoring sensors, and inertial measurement units (IMUs). The sensors 120 generate wheel speeds ω, propulsion torques T ω, and the like, which are processed by the OBCP 130 into each of the wheel and tire assemblies 112. P and braking torque TB It should be understood and recognized that the propulsion torque T P and braking torque T B may be values ​​derived by the OBCP 130 based on data from the sensors 120. More specifically, for the left front wheel and tire assembly 112F1, these wheel speeds, propulsion torques, and braking torques may be referred to as ω Fl 、T PFl and T BFl ; For the right front wheel and tire assembly 112Fr, it can be called ω Fr 、T PFr and T BFr For the left rear wheel and tire assembly 112Rl, it can be called ω Rl 、T PRl and T BRl ; and for the right rear wheel and tire assembly 112Rr, may be referred to as ω Rr 、T PRr and T BRr The sensor 120 also senses the vehicle speed v, the pitch rate θ · , yaw rate Roll rate φ · , front wheel steering angle δ F , longitudinal acceleration a x , lateral acceleration a y and the normal acceleration a z In other words, the sensor 120 generates vehicle dynamics information (VDI) of the vehicle 110 .

[0031] The onboard computing platform 130 uses the vehicle dynamics information provided by the sensors 120 to estimate the forces on each of the wheel and tire assemblies 112 and the wind resistance F 风 In addition, the OBCP 130 generates messages related to the forces on the wheel and tire assembly 112 for display via the IHU 140. For example, the OBCP 130 generates messages related to tire wear, driving behavior, tire dynamics, etc.

[0032] The infotainment head unit 140 provides interaction between the vehicle 140 and the user. The infotainment head unit 140 includes digital and / or analog interfaces (e.g., input devices and output devices) to receive input from the user and display information. The input devices may include, for example, control knobs, instrument panels, digital cameras for image capture and / or visual command recognition, touch screens, audio input devices (e.g., cabin microphones), buttons, or touch pads. The output devices may include instrument cluster outputs (e.g., dials, lighting devices), actuators, heads-up displays, center console displays (e.g., liquid crystal displays (“LCDs”), organic light emitting diode (OLED) displays, flat panel displays, solid-state displays, etc.), and / or speakers. In the illustrated example, the infotainment head unit 170 includes hardware (e.g., a processor or controller, memory, storage devices, etc.) and components for an infotainment system (such as a display). of and MyFord of of In addition, the infotainment head unit 140 displays the infotainment system on, for example, a center console display.

[0033] Figure 4 yes Figure 1 Another schematic side view of a vehicle 110 is shown. Figure 4 As shown, the relative pitch angle θ r is defined by a longitudinal line along the body of the vehicle 110 and the road surface 402. In operation, the OBCP 130 estimates the relative pitch angle θ based on vehicle dynamics information from the sensors 120. r , as will be described in more detail below.

[0034] Figure 5 yes Figure 1 Another schematic front view of a vehicle 110 is shown. Figure 5 As shown, the relative roll angle φ r is defined by a side line passing through the body of the vehicle 110 and the road surface 402. In operation, the OBCP 130 estimates the relative roll angle φ based on vehicle dynamics information from the sensors 120. r , as will be described in more detail below.

[0035] Figure 6 yes Figure 1 A perspective view of one of the wheel and tire assemblies 112 of the vehicle 110 is shown. Figure 6 As shown, as the wheel and tire assembly rotates at the wheel speed ω, the longitudinal tire force F x , lateral tire force F y and the normal tire force F z , Tire rolling resistance Tr , propulsion torque T P and braking torque T B Acting on the wheel and tire assembly 112. It should be understood that for undriven wheels (e.g., rear wheels of a front-wheel drive vehicle), T P It should also be understood that the tire rolling resistance T r is the reaction torque applied to the wheel and tire assembly 112 by the road surface 402. It should also be understood that each wheel and tire assembly 112 is subject to longitudinal, lateral and normal tire forces and tire rolling resistance. More specifically, for the left front wheel and tire assembly 112F1, these forces and reaction torques may be referred to as F xFl 、F yFl 、F zFl and T rFl ; For the right front wheel and tire assembly 112Fr, it can be referred to as F xFr 、F yFr 、F zFr and T rFr For the left rear wheel and tire assembly 112R1, it can be referred to as F xRl 、F yRl 、F zRl and T rRl ; and for the right rear wheel and tire assembly 112Rr, may be referred to as F xRr 、F yRr 、F zRr and T rRr In operation, the OBCP 130 estimates the longitudinal and normal tire forces F for each of the wheel and tire assemblies 112 based on the vehicle dynamics information from the sensors 120 . x 、F z and tire rolling resistance T r , as will be described in more detail below. In addition, in operation, the OBCP 130 estimates the front lateral force F along the front axle of the front wheel and tire assembly 112Fl, 112Fr based on the vehicle dynamics information from the sensor 120. yFa , and the rear lateral force F of the rear wheel and tire assembly 112Rl, 112Rr along the rear axle yRa , as will be described in more detail below.

[0036] Figure 7 yes Figure 11. A block diagram of an electronic component 700 of a vehicle 110 of FIG. 1. A first vehicle data bus 702 communicatively couples a sensor 120, an OBCP 130, and other devices connected to the first vehicle data bus 702. In some instances, the first vehicle data bus 702 is implemented according to a controller area network (CAN) bus protocol defined by the International Organization for Standardization (ISO) 11898-1. Alternatively, in some instances, the first vehicle data bus 702 may be a media oriented system transport (MOST) bus, or a CAN flexible data (CAN-FD) bus (ISO 11898-7). A second vehicle data bus 704 communicatively couples the OBCP 130 and the infotainment head unit 140. The second vehicle data bus 704 may be a MOST bus, a CAN-FD bus, or an Ethernet bus. In some instances, the OBCP 130 communicatively isolates the first vehicle data bus 702 and the second vehicle data bus 704 (e.g., via a firewall, a message agent, etc.). Alternatively, in some examples, the first vehicle data bus 702 and the second vehicle data bus 704 are the same data bus.

[0037] The OBCP 130 includes a processor or controller 710 and a memory 720. In the illustrated example, the OBCP 130 is configured to include a tire dynamics analyzer 730. Alternatively, in some examples, the tire dynamics analyzer 730 may be incorporated into another electronic control unit (ECU) having its own processor 710 and memory 720. The processor or controller 710 may be any suitable processing device or collection of processing devices, such as, but not limited to: a microprocessor, a microcontroller-based platform, a suitable integrated circuit, one or more field programmable gate arrays (FPGAs), and / or one or more application specific integrated circuits (ASICs). The memory 720 may be a volatile memory (e.g., RAM, which may include non-volatile RAM, magnetic RAM, ferroelectric RAM, and any other suitable form); a non-volatile memory (e.g., disk memory, flash memory, electrically programmable read-only memory, electrically erasable programmable read-only memory, non-volatile solid-state memory, etc.), an unchangeable memory (e.g., electrically programmable read-only memory), a read-only memory, and / or a high-capacity storage device (e.g., a hard disk drive, a solid-state drive, etc.). In some examples, memory 720 includes multiple types of memory, particularly volatile memory and non-volatile memory.

[0038] The memory 720 is a computer readable medium on which one or more sets of instructions, such as software for operating the methods of the present disclosure, may be embedded. The instructions may embody one or more of the methods or logic as described herein. In certain embodiments, the instructions may reside completely or at least partially within any one or more of the memory 720, the computer readable medium, and / or the processor 710 during execution of the instructions. The memory 720 stores a vehicle dynamics threshold database 722. The vehicle dynamics threshold database 722 includes predetermined tire force thresholds associated with tire wear monitoring and / or vehicle dynamics monitoring.

[0039] The terms "non-transitory computer-readable medium" and "tangible computer-readable medium" should be understood to include a single medium or multiple media, such as a centralized database or distributed database and / or associated caches and servers storing one or more instruction sets. The terms "non-transitory computer-readable medium" and "tangible computer-readable medium" also include any tangible medium that can store, encode, or carry an instruction set for execution by a processor or cause a system to perform any one or more of the methods or operations disclosed herein. As used herein, the term "tangible computer-readable medium" is expressly defined to include any type of computer-readable storage device and / or storage disk, and does not include propagating signals.

[0040] Figure 8 yes Figure 7 8. The tire dynamics analyzer 730 includes a data receiver 810, a relative angle estimator 820, an effective mass estimator 830, a tire normal force estimator 840, a rolling resistance estimator 850, a wind force estimator 860, a tire longitudinal and lateral force estimator 870, and a feedback generator 880. The tire longitudinal and lateral force estimator 870 includes an extended Kalman filter 872.

[0041] In operation, the data receiver 810 receives vehicle dynamics information transmitted by the sensors 120 .

[0042] In operation, the relative angle estimator 820 estimates the relative pitch angle θ r and the relative roll angle φ r More specifically, the relative angle estimator 820 is based on the longitudinal acceleration a x , forward propulsion torque T PF and rear propulsion torque T PR , and the first, second and third predetermined constants c1, c2, c3, the relative pitch angle θ is estimated using the following formula 1 r In addition, the relative angle estimator is based on the lateral acceleration a y and a fourth predetermined constant c4, the relative roll angle φ is estimated using the following formula 2: r.

[0043] θ r ≈c1a x +c2T PF +c3T PR

[0044] Formula 1

[0045] φ r ≈c4a y

[0046] Formula 2

[0047] More specifically, the first constant c1, the second constant c2, the third constant c3, and the fourth constant c4 are linear regression weights that depend on the geometry of the vehicle 110 and the physical parameters of the suspension element 152 (spring constants, damping rates, joint friction, etc.). The first constant c1 is the longitudinal acceleration regression coefficient. The second constant c2 is the front propulsion torque regression coefficient. The third constant c3 is the rear propulsion torque regression coefficient. The fourth constant c4 is the lateral acceleration regression coefficient. The constants c1, c2, c3, and c4 are stored in the memory 720. The constants c1, c2, c3, and c4 are experimentally determined for each vehicle production line during vehicle production line testing and / or in real time via measurements from the sensor 120.

[0048] In operation, the effective mass estimator 830 estimates the effective mass m shared by the front and rear axles. F 、m R More specifically, the effective mass estimator 830 is based on the total mass m of the vehicle 110, the height H of the CoG 114, and the c , relative pitch angle θ r , longitudinal distance L from CoG114 to rear axle R and the longitudinal distance L between the front and rear axles, the vertical force F shared by the front axles of the vehicle 110 is estimated using the following formula 3: zF In addition, the effective mass estimator 830 is based on the total mass m of the vehicle 110, the height H of the CoG 114, and the c , relative pitch angle θ r , longitudinal distance L from CoG114 to the front axle F and the longitudinal distance L between the front and rear axles, the vertical force F shared by the rear axle of the vehicle 110 is estimated using the following formula 4: zR .

[0049]

[0050] Formula 3

[0051]

[0052] Formula 4

[0053] Furthermore, in operation, the effective mass estimator 830 is based on the vertical force F shared by the front axle of the vehicle 110. zF and the standard acceleration g due to gravity (about 9.8 m / s 2 ), the effective mass m shared by the front axle of the vehicle 110 is estimated using the following formula 5 F In addition, the effective mass estimator 830 is based on the vertical force F shared by the rear axle of the vehicle 110 zR and the standard acceleration g due to gravity, the effective mass m shared by the rear axle of the vehicle 110 is estimated using the following formula 6: R .

[0054]

[0055] Formula 5

[0056]

[0057] Formula 6

[0058] In operation, the tire normal force estimator 840 is based on the relative roll angle φ r , lateral acceleration a y , normal acceleration a z , front effective mass m F and the effective mass m R 、Height H of CoG114 c , the height H of the roll center 116 r 、Front wheel track e F and rear track e R , estimate the normal force on each of the wheel and tire assemblies 112 using the following equations 7, 8, 9, 10:

[0059]

[0060] Formula 7

[0061]

[0062] Formula 8

[0063]

[0064] Formula 9

[0065]

[0066] Formula 10

[0067] In operation, the rolling resistance estimator 850 calculates the rolling resistance based on the respective normal forces F z, the corresponding wheel speed ω of each wheel and tire assembly 112, and the fifth constant c5 and the sixth constant c6, the rolling resistance T of each of the wheel and tire assemblies 112 is estimated using the following formula 11 r .

[0068] T r ≈F z (c5+c6ω)

[0069] Formula 11

[0070] More specifically, the fifth constant c5 and the sixth constant c6 are linear regression weights that depend on tire geometry and material composition. The fifth constant c5 is the tire normal force regression coefficient. The sixth constant c6 is the tire normal force-velocity regression coefficient. The constants c5 and c6 are stored in the memory 720. The constants c5 and c6 are experimentally determined for each vehicle production line during vehicle production line testing and / or in real time via measurements from the sensor 120.

[0071] In operation, the wind force estimator 860 estimates the wind resistance F based on the vehicle speed v and the seventh constant c7 using the following formula 12: 风 .

[0072] F 风 =c7v 2

[0073] Formula 12

[0074] More specifically, the seventh constant c7 is a linear regression weight that depends on the geometry of the vehicle 110. The seventh constant c7 is a wind resistance regression coefficient. The constant c7 is stored in the memory 720. The constant c7 is experimentally determined for each vehicle production line during vehicle production line testing and / or in real time via measurements from the sensor 120.

[0075] In operation, the tire longitudinal and lateral tire force estimator 870 estimates the longitudinal tire force F of each of the wheel and tire assembly 112 using an extended Kalman filter 872 based on the dynamic system model described by the following matrix equations 13 and 14: x and the lateral tire forces F on the wheel and tire assembly 112 front and rear ya .

[0076] x k =f(x k-1 ,u k-1 )+w k-1

[0077] Formula 13

[0078] y k =h(x k )+vk-1

[0079] Formula 14

[0080] As shown in Formula 13, f is the input of two vectors x k-1 and u k-1 The function of w k-1 is the unmodeled error, sometimes called the disturbance, and x k is the resultant vector. This perturbation w k-1 This may be due to, for example, changes in the load of the vehicle 110, errors in the determined wind forces (e.g., a luggage rack tied to the vehicle), etc. Furthermore, as shown in Equation 14, h is a function whose input is the vector x, v k-1 is the electronic noise of the electronic component 700, and y is the resultant vector.

[0081] More specifically, tire longitudinal and lateral force estimator 870 includes an extended Kalman filter 872. To estimate the longitudinal tire force F x and the lateral tire force F ya , the tire longitudinal and lateral tire force estimator 870 assumes that w k-1 and v k-1 is a normally distributed random variable with a mean of zero, and the extended Kalman filter 872 is implemented based on the following quantities and using the following matrix equations 15 to 57: propulsion torque T PFl 、T PFr ; Braking torque T BFl 、T BFr 、T BRl 、T BRr ; Wind resistance F 风 , rolling resistance T rFl 、T rFr 、T rRl 、T rRr ; Steering angle δ F , yaw rate Wheel speedω Fl ,ω Fr ,ω Rl ,ω Rr , longitudinal acceleration a x , lateral acceleration a y , the sampling rate Δt of the sensor 120 , the radius r of the wheel and tire assembly 112 , and the moment of inertia I of the wheel and tire assembly 112 ω .

[0082]

[0083] Formula 15, where

[0084] At step k-1

[0085]

[0086] Formula 16

[0087] At step k-1

[0088] u k-1 =[T PFl -T BFl -T rFl , T PFr -T BFr -T rFr , T PRl -T BRl -T rRl , T PRr -T BRr -T rRr , δ F ] T

[0089] Formula 17

[0090] f(x k-1 ,u k-1 )=[f1(x k-1 ,u k-1 ), f2(x k-1 ,u k-1 ), ..., f 17 (x k-1 ,u k-1 )] T

[0091] Formula 18, where

[0092]

[0093] Formula 19

[0094]

[0095] Formula 20

[0096]

[0097] Formula 21

[0098]

[0099] Formula 22

[0100]

[0101] Formula 23, where

[0102] F yF =-(F xFl sinδ F+F xFr sinδ F )+F yFa cosδ F

[0103] Official 24

[0104] F yR ≈F yRa

[0105] Formula 25

[0106]

[0107] Formula 26

[0108]

[0109] Formula 27

[0110]

[0111] Formula 28

[0112]

[0113] Formula 29

[0114]

[0115] Formula 30

[0116]

[0117] Formula 31

[0118]

[0119] Formula 32

[0120]

[0121] Formula 33

[0122]

[0123] Formula 34

[0124]

[0125] Formula 35

[0126]

[0127] Formula 36

[0128]

[0129] Formula 37

[0130]

[0131] Formula 38, where

[0132] At step k

[0133]

[0134] Formula 39

[0135] h(x k )=[h1(x k ), h2(x k ), ..., h7(x k )] T

[0136] Formula 40, where

[0137]

[0138] Formula 41

[0139] h2(x k )=ω Fl，k

[0140] Formula 42

[0141] h3(x k )=ω Fr，k

[0142] Formula 43

[0143] h4(x k )=ω Rl，k

[0144] Formula 44

[0145] h5(x k )=ω Rr，k

[0146] Formula 45

[0147]

[0148] Formula 46, where

[0149] F xF =-(F xFl cosδ F +F xFr cosδ F )-F yFa sinδ F

[0150] Formula 47

[0151] F xR ≈-F xRl -F xRr

[0152] Formula 48

[0153]

[0154] Formula 49, where

[0155] F yF =-(F xFl sinδ F +F xFr sinδ F )+F yFa cosδ F

[0156] Formula 50

[0157] F yR ≈F yRa

[0158] Formula 51

[0159]

[0160] Formula 52, where

[0161]

[0162] Formula 53

[0163]

[0164] Formula 54, where

[0165]

[0166] Formula 55

[0167]

[0168] Formula 56

[0169]

[0170] Formula 57

[0171] It should be understood and appreciated that the vector y shown in equations 38, 39 and 56 above k The measurements generated by sensor 120 in the physical system described by equations 13 and 14 above are described, where the measurement noise comes from electronic component 700.

[0172] In some instances, P1 - The initial value of is equal to Q in equation 12 above. It should be understood that Q and R are parameters that can be tuned in the extended Kalman filter 872. In addition, in some examples, Q and R in equations 52 and 54 above are described by the following matrix equations 58 and 59, respectively.

[0173] Q=diag(1e-4, 0.4, 0.4, 0.4, 0.4, 25, 2.5e5, 25, 2.5e5, 25, 2.5e5, 25, 2.5e5, 25, 2.5e5, 10, 1e5, 10, 1e5)

[0174] Formula 58

[0175] R=diag(0.01, 0.1, 0.1, 0.1, 0.1, 0.3, 0.02)

[0176] Formula 59

[0177] Thus, once the tire longitudinal and lateral tire force estimator 870 has executed the extended Kalman filter 872, the tire dynamics analyzer has estimated ten tire forces: four longitudinal tire forces (F xFl 、F xFr 、F xRl 、F xRr ), two lateral tire forces on each axle (F yFa 、F yRa ) and four normal tire forces (F zFl 、F zFr 、F zRl 、F zRr ).

[0178] In operation, the feedback generator 880 generates a message related to the estimated value of the estimated tire force. More specifically, the feedback generator 880 accesses the vehicle dynamics force threshold database 722 stored in the memory 720 to compare the estimated tire force with the stored vehicle dynamics thresholds. If one or more of the estimated tire forces exceed one or more of the vehicle dynamics thresholds, the feedback generator 880 generates a warning message for display on the IHU 140. In some examples, the warning message reminds the driver of the vehicle 110 that improved driving habits (e.g., less aggressive acceleration, smoother cornering, etc.) can extend the useful life of the tires of the wheel and tire assembly 112. In some examples, the warning message indicates to the driver of the vehicle 110 that the tires of the wheel and tire assembly 112 have reached the end of their recommended useful life. In some examples, the warning message indicates to the driver of the vehicle 110 that the tires of the wheel and tire assembly 112 are under excessive (e.g., exceeding recommended) tire forces. Additionally, if the estimated tire forces are within (e.g., not exceeded) the vehicle dynamics threshold, the feedback generator 880 generates a congratulatory message for display on the IHU 140. In some examples, the congratulatory message compliments the driver of the vehicle 110 for driving habits that may extend the tire life of the wheel and tire assembly 112. In some examples, the congratulatory message compliments the driver of the vehicle 110 for driving habits that may improve the fuel economy of the vehicle 110.

[0179] Fig. 9 is a flow chart of a method 900 for analyzing tire dynamics, which may be performed by Figure 7 The electronic component 700 is implemented. Fig. 9 A flowchart representing a memory device (such as Figure 7 The machine-readable instructions in the memory 720 of the processor include one or more programs, which are executed by the processor (such as Figure 7 When executed by the processor 710, the vehicle 110 implements Figure 7 and Figure 8 Example tire dynamics analyzer 730. In addition, although reference Fig. 9 The flowchart shown in describes an exemplary procedure, but many other methods of the exemplary tire dynamics analyzer 730 may be used instead. For example, the order of execution of the blocks may be changed, and / or some of the blocks described may be changed, eliminated, or combined.

[0180] Initially, at block 902 , the data receiver 810 collects input from the sensors 120 .

[0181] At block 904, the relative angle estimator 820 estimates the relative pitch angle θ based on the sensor input and the first constant c1, the second constant c2, the third constant c3, and the fourth constant c4. rand the relative roll angle φ r .

[0182] At block 906, the effective mass estimator 830 calculates the relative pitch angle θ based on the relative pitch angle θ. r , the geometry of the vehicle 110 , the sensor input, and the mass m of the vehicle 110 before estimating the effective mass m F and the effective mass m R .

[0183] At block 908 , the tire normal force estimator 840 calculates the relative roll angle φ based on the relative roll angle φ. r , the geometry of the vehicle 110, sensor inputs, and the front effective mass m F and the effective mass m R Estimate the tire normal force F of each of the wheel and tire assemblies 112 z .

[0184] At block 910 , the rolling resistance estimator 850 calculates the rolling resistance based on the tire normal force F z , sensor inputs, and fifth constants c5 and sixth constants c6 to estimate the tire rolling resistance T of each of the wheel and tire assemblies 112 r .

[0185] At block 912, the wind force estimator 860 estimates the wind force F based on the sensor input and the seventh constant c7. 风 .

[0186] At box 914 , the tire longitudinal and lateral force estimator 870 executes the extended Kalman filter 872 to calculate the tire longitudinal and lateral force based on the sensor input and the rolling resistance T r Estimated tire longitudinal force F x and the lateral force F y .

[0187] At block 916, feedback generator 880 determines tire force F x 、F y 、F z Whether it is within the vehicle dynamics threshold stored in memory 720.

[0188] If at block 916, the feedback generator 880 determines that the tire force F x 、F y 、F z Not within the vehicle dynamics threshold, method 900 proceeds to box 918.

[0189] At block 918, the feedback generator 880 generates a warning message to be displayed on the IHU 140. The method 900 then returns to block 902.

[0190] If at block 916, the feedback generator 880 determines that the tire force Fx 、F y 、F z Within the vehicle dynamics threshold, method 900 proceeds to box 920.

[0191] At block 920, the feedback generator 880 generates a congratulatory message to be displayed on the IHU 140. The method 900 then returns to block 902.

[0192] In the present application, the use of transitional conjunctions is intended to include conjunctions. The use of definite or indefinite articles is not intended to indicate cardinality. Specifically, reference to "the" object or "one" and "a" object is intended to also represent one of a possible plurality of such objects. In addition, the conjunction "or" can be used to convey simultaneous features rather than mutually exclusive alternatives. In other words, the conjunction "or" should be understood to include "and / or". The terms "include", "comprise", "cover" are inclusive and have the same scope as "comprises", "includes" and "contains".

[0193] From the above, it can be appreciated that the above disclosed apparatus and method can more accurately estimate the forces applied to the vehicle tires in real time and under all driving conditions. Further displaying messages related to long-term tire wear and / or driving habit improvement can assist the driver in operating the vehicle, and / or reduce vehicle maintenance costs. In addition, more accurate estimation of tire forces can improve vehicle dynamics control performance. It should also be understood that the disclosed apparatus and method provide a specific solution to a specific problem, namely, to estimate tire forces in real time based on relative pitch angle and roll angle and tire rolling resistance for inaccurate tire force estimates under all types of vehicle operating conditions. In addition, the disclosed apparatus and method provide improvements to computer-related technology by increasing the functionality of the processor to estimate relative pitch angle and roll angle, estimate the front and rear effective masses of the vehicle, estimate tire normal forces, estimate tire rolling resistance, estimate vehicle wind forces, estimate tire longitudinal and lateral forces, and generate information based on the estimated tire forces.

[0194] As used herein, the terms "module" and "unit" refer to hardware having circuitry that is typically combined with a sensor to provide communication, control, and / or monitoring capabilities. "Module" and "unit" may also include firmware executed on the circuitry.

[0195] The above embodiments, particularly any "preferred" embodiments, are examples of possible implementations and are presented merely for a clear understanding of the principles of the present invention. Many changes and modifications may be made to the above embodiments without substantially departing from the spirit and principles of the technology described herein. All modifications are intended to be included within the scope of this disclosure and to be protected by the appended claims.

[0196] According to the present invention, a vehicle is provided, which has: a sensor for generating vehicle dynamics information (VDI); and a processor and a memory, which communicate with the sensor and are configured to: estimate relative pitch angle and roll angle using the VDI; estimate tire normal force using the relative pitch angle and roll angle and the VDI; and estimate tire rolling resistance using the tire normal force.

[0197] According to one embodiment, the processor is further configured to estimate the tire longitudinal force and the tire lateral force using the tire rolling resistance and the VDI.

[0198] According to one embodiment, the above invention is further characterized by an infotainment head unit (IHU), wherein if one or more of the normal tire forces, longitudinal tire forces, or lateral tire forces exceed the vehicle dynamics threshold, the processor is further configured to display a warning message via the IHU.

[0199] According to one embodiment, the processor is further configured to estimate the front effective mass and the rear effective mass; and the processor estimates the tire normal force using the front effective mass and the rear effective mass.

[0200] According to one embodiment, the processor is configured to estimate the relative pitch and roll angles using a plurality of predetermined constants.

[0201] According to one embodiment, the plurality of predetermined constants are related to one or more of vehicle geometry, spring constants, damping rates, or suspension linkage joint friction.

[0202] According to one embodiment, the processor is configured to estimate the tire rolling resistance using a plurality of predetermined constants.

[0203] According to one embodiment, the plurality of predetermined constants are related to one or more of tire geometry or tire material composition.

[0204] The method according to the present invention includes: using a processor to estimate relative pitch angle and roll angle using vehicle dynamics information (VDI) from a sensor; using a processor to estimate tire normal force using the relative pitch angle and roll angle and VDI; and using a processor to estimate tire rolling resistance using the tire normal force.

[0205] According to one embodiment, the above invention is further characterized by using the tire rolling resistance and the input to estimate the tire longitudinal force and the tire lateral force with a processor.

[0206] According to one embodiment, the above invention is further characterized by displaying a warning message using a processor if one or more of the normal tire forces, the longitudinal tire forces, or the lateral tire forces exceed a vehicle dynamics threshold.

[0207] According to one embodiment, the above invention is further characterized by estimating the front effective mass and the rear effective mass using a processor, and estimating the tire normal force is performed using the front effective mass and the rear effective mass.

[0208] According to one embodiment, estimating the relative pitch and roll angles is performed using a plurality of predetermined constants.

[0209] According to one embodiment, the plurality of predetermined constants are related to one or more of vehicle geometry, spring constants, damping rates, or suspension linkage joint friction.

[0210] According to one embodiment, estimating tire rolling resistance is performed using a plurality of predetermined constants related to one or more of tire geometry or tire material composition.

[0211] According to the present invention, a system is provided, which has an inertial measurement unit (IMU) arranged in a vehicle; and a processor, which communicates with the IMU and is configured to: receive vehicle dynamics information (VDI) from the IMU; estimate the relative pitch angle and the relative roll angle based on the VDI; estimate the front effective mass and the rear effective mass based on the relative pitch angle; estimate the tire normal force based on the relative roll angle and the front effective mass and the rear effective mass; estimate the tire rolling resistance based on the tire normal force and the VDI; and estimate the tire longitudinal force and the tire lateral force based on the tire rolling resistance and the VDI.

[0212] According to one embodiment, the processor is further configured to estimate wind resistance; and the tire longitudinal force and the tire lateral force are further based on the wind resistance.

[0213] According to one embodiment, the relative pitch angle and the relative roll angle are also based on a plurality of predetermined constants.

[0214] According to one embodiment, the above invention is also characterized by a memory in communication with a processor for storing vehicle dynamics thresholds; and a display in communication with the processor; wherein if one or more of the normal tire force, the longitudinal tire force, or the lateral tire force exceeds the vehicle dynamics threshold, the processor is also configured to display a warning message via the display.

[0215] According to one embodiment, the relative pitch angle, relative roll angle and tire rolling resistance are also based on a plurality of predetermined constants.

Claims

1. A vehicle comprising: Sensors that generate information about vehicle dynamics; and a processor and a memory in communication with the sensor and configured to: estimating relative pitch and roll angles using the vehicle dynamics information; estimating tire normal forces using the relative pitch angle and roll angle and the vehicle dynamics information; estimating tire rolling resistance using the tire normal force; estimating tire longitudinal force and tire lateral force using at least the tire rolling resistance; generating a warning message when one or more of the tire longitudinal force and the tire lateral force exceeds a vehicle dynamics threshold; as well as A display in communication with the processor, the display configured to display the warning message. 2 . The vehicle of claim 1 , wherein the processor is further configured to estimate tire longitudinal force and tire lateral force using the vehicle dynamics information.

3. The vehicle of claim 2, further comprising an infotainment head unit (IHU), wherein the processor is further configured to display a warning message via the IHU if one or more of the normal tire forces, the longitudinal tire forces, or the lateral tire forces exceed a vehicle dynamics threshold.

4. The vehicle of claim 1, wherein: The processor is further configured to estimate a front effective mass and a rear effective mass; and The processor estimates the tire normal force using the front effective mass and the rear effective mass. 5 . The vehicle of claim 1 , wherein the processor is configured to estimate the relative pitch and roll angles using a plurality of predetermined constants.

6. The vehicle of claim 5, wherein the plurality of predetermined constants are related to one or more of vehicle geometry, spring constants, damping rates, or suspension linkage joint friction. 7 . The vehicle of claim 1 , wherein the processor is configured to estimate the tire rolling resistance using a plurality of predetermined constants.

8. The vehicle of claim 7, wherein the plurality of predetermined constants are related to one or more of tire geometry or tire material composition.

9. A method for a vehicle, comprising: using vehicle dynamics information from sensors to estimate relative pitch and roll angles using a processor; estimating, with the processor, a tire normal force using the relative pitch and roll angles and the vehicle dynamics information; estimating tire rolling resistance using the tire normal force with the processor; estimating, with the processor, a tire longitudinal force and a tire lateral force using at least the tire rolling resistance; When one or more of the tire longitudinal force and the tire lateral force exceeds a vehicle dynamics threshold, a warning message is displayed using a display. 10 . The method of claim 9 , further comprising estimating tire longitudinal forces and tire lateral forces using the vehicle dynamics information with the processor.

11. The method of claim 9, further comprising estimating, with the processor, a front effective mass and a rear effective mass, and performing the estimating the tire normal force using the front effective mass and the rear effective mass.

12. The method of claim 9, wherein estimating the relative pitch and roll angles is performed using a plurality of predetermined constants.

13. The method of claim 12, wherein the plurality of predetermined constants are related to one or more of vehicle geometry, spring constants, damping rates, or suspension linkage joint friction.

14. The method of claim 9, wherein estimating the tire rolling resistance is performed using a plurality of predetermined constants related to one or more of tire geometry or tire material composition.

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