Vehicle dynamic model modeling method based on simplified vehicle dynamic model

Abstract

The invention discloses a vehicle dynamic model modeling method based on a simplified vehicle dynamic model, and the method comprises the steps: S10, recognizing vehicle suspension feature points, carrying out the real-time data derivation of the geometric motion state of vehicle suspension, and obtaining an estimated suspension motion state; s20, collecting through an attitude sensor, and performing data correction by estimating the suspension motion state to generate an accurate suspension motion state; s30, synthesizing the accurate suspension motion state and other collected vehicle motion information and wheel speed information to obtain vehicle attitude data; s40, vehicle motion information collected by various sensors in the vehicle is obtained, and a more accurate tire slip angle is obtained by comparing the overall vehicle motion information with the wheel speed sensor information; and S50, synthesizing the data in the vehicle model according to the driver input information and the preset existing vehicle information, and finally forming a vehicle dynamic model. The method is simple, practical, accurate in prediction result and suitable for various different vehicle types.

Description

Technical Field

[0001] The present invention belongs to the technical field of vehicle detection, and particularly relates to a vehicle dynamic model modeling method based on a simplified vehicle dynamics model. Background Art

[0002] Vehicle dynamics modeling is a form of data derivation that restores the vehicle's dynamic performance in real-time or non-real-time on a computer based on the parameters of the vehicle in the real world. It is widely used in fields such as vehicle chassis development, autonomous driving development, racing simulation software, and vehicle dynamics engineering software. The current technical paths mainly include the following several types:

[0003] ① Simplified vehicle dynamic modeling based on a single-point tire model: This modeling method is mainly used for racing simulation software and other applications with high real-time requirements. It is mainly based on a preset simplified tire model (usually consisting of ① a tire sidewall regarded as a spring-damper system, ② a reference μ value of the tire, and ③ a tire surface stress detection point). By applying external forces to ① and ③, the change of ② under the external force is deduced according to the empirical curve. Subsequently, based on the deduced results, the system calculates the frictional force generated by the tire under the external force acting on itself. Considering factors such as the load transfer and suspension force calculated by the vehicle itself based on acceleration, the system finally outputs a relatively accurate dynamic simulation result of the vehicle itself. Since it is mainly used for racing simulation software with high real-time requirements, this simulation method mainly uses a relatively inaccurate simplified vehicle dynamic modeling that is prone to cumulative errors and lacks a way to control cumulative errors. At the same time, because it highly relies on pre-entered empirical curves and vehicle data, its simulation accuracy is also highly correlated with the input information.

[0004] ② Vehicle dynamic modeling based on a multi-point complex tire model: This modeling method is mainly used for industrial-level vehicle simulation and development modeling. It is mainly based on a complete suspension mechanical model, including an external force model and an internal stress model, which are usually provided by the manufacturer or achieved through extremely fine dynamic stress analysis of the suspension system itself. It also includes a complete tire characteristic model provided by (usually a tire company) to accurately simulate the vehicle's own dynamics. Since it is mainly used for industrial-level vehicle simulation, this simulation method consumes a huge amount of computing power. It can hardly achieve real-time simulation, requires extremely high computing power for the hardware itself, and has high cost requirements. Moreover, it still highly relies on the tire model provided by the tire manufacturer, which makes it almost impossible for ordinary users to use and is also almost impossible for the vast majority of users to use in fields such as driving subjective experience that require real-time simulation of vehicle dynamics.

[0005] ③ Vehicle dynamic modeling based on vehicle attitude and G-G diagram: This modeling method is mainly used for the vehicle to control its own motion mode. It is composed of simple longitudinal and lateral G values and angle sensors fixed on the chassis suspension components, and simply models the vehicle attitude and vehicle acceleration / deceleration states, providing an inaccurate approximation of the vehicle state. Since it is mainly used for the in-vehicle four-wheel drive system of the vehicle itself, although this simulation method has low computing power consumption and high real-time performance, its dynamic simulation method is too simplistic, and because its output judgment method highly depends on pre-tuning and empirical curves, it has no practical reference value for anything other than existing hardware such as the highly integrated and pre-tuned four-wheel drive system of this vehicle. Summary of the Invention

[0006] To solve the above problems, the present invention proposes a vehicle dynamic model modeling method based on a simplified vehicle dynamics model, which is a relatively simple and practical vehicle dynamic model modeling method with accurate prediction results and applicable to multiple different vehicle models.

[0007] To achieve the above object, the technical solution adopted by the present invention is: A vehicle dynamic model modeling method based on a simplified vehicle dynamics model, comprising the steps of:

[0008] S10, identifying the vehicle suspension characteristic points, performing real-time data derivation on the geometric motion state of the vehicle suspension to obtain an estimated suspension motion state;

[0009] S20, collecting through an attitude sensor and correcting the data through the estimated suspension motion state to generate an accurate suspension motion state;

[0010] S30, after synthesizing the accurate suspension motion state with other collected vehicle motion information and wheel speed information, obtaining vehicle attitude data;

[0011] S40, obtaining the vehicle motion information collected by various sensors in the vehicle, and obtaining a more accurate tire slip angle by comparing the overall vehicle motion information and the wheel speed sensor information;

[0012] S50, comprehensively synthesizing the above data in the vehicle model according to the driver input information and the pre-given existing vehicle information, and finally forming a vehicle dynamic model.

[0013] Furthermore, a ToF vision sensor is used to identify specific characteristic points on the suspension and perform real-time data derivation on the specific geometric motion state of the vehicle suspension.

[0014] Furthermore, the vehicle motion information collected by various sensors in the vehicle includes: the vehicle motion information and wheel speed information obtained by synthesizing the data of the wheel speed sensor and the GPS-inertial navigation sensor.

[0015] Furthermore, the process of constructing the vehicle dynamic model includes the steps:

[0016] S501: According to the suspension motion data, the geometric position of the inner wall of the wheel, and the wheel size obtained by the vehicle during movement provided by the sensor, and based on the geometric appearance of the suspension, calculate the wheel ground contact midpoint position P_CP, and obtain the instantaneous velocity center P_IC and the suspension rotation center P_RC of any suspension motion state;

[0017] S502: By synthesizing the suspension rotation center P_RC, obtain the roll rotation axis of the vehicle at any time; according to the roll rotation axis and the real-time acceleration of the vehicle, calculate the original angular momentum of the vehicle at any time;

[0018] S503: According to the suspension motion data, substitute the actual transverse and longitudinal moments of inertia into the suspension motion data; since the spring value of the suspension and the geometric position of the suspension system are known, obtain the effective damping value in any motion state of the suspension, and the suspension speed threshold for the fast and slow valve switches;

[0019] S504: Construct a vehicle suspension model: perform a real-time force analysis on the geometric structure of the vehicle suspension according to the real-time yaw and pitch data of the vehicle itself, so as to obtain the internal stress of the suspension system. Through the internal stress of the suspension and the tracking of the deformation amount of the suspension bushing realized by visual tracking, perform an independent force analysis on each bushing, and then calculate the equivalent hardness value of the suspension flexible component according to its deformation amount under different external forces;

[0020] S505: Using the measured suspension motion data, the original angular momentum, the suspension speed threshold for the fast and slow valve switches, and the equivalent hardness value, obtain all the forces acting on the tire at any time, including the forces caused by the transfer of the vehicle's center of gravity, the forces caused by the mutual traction of the rigid components inside the suspension system, and the forces caused by the deformation of the suspension flexible components;

[0021] S506: Take the first derivative of the constructed vehicle suspension model. Through the force analysis obtained by combining the suspension geometric structure, obtain the real-time tire load W transfer , substitute the accelerations of the vehicle on the X, Y, and Z axes and the vehicle sideslip angle obtained from the vehicle motion state, decompose the vehicle's overall grip vector, so as to obtain the real-time grip estimation on each wheel, and calculate the tire slip ratio κ according to the difference between the wheel speed sensor and the calculated ground speed;

[0022] S507: According to the total load W Transfer,sum acting on the tire and the y corresponding relationship with the four-wheel lateral grip F, deduce a grip equivalent quantity μ corresponding to the wheel deformation amount, where

[0023]

[0024] Form the first part of the simplified tire model, i.e., the empirical model of tire horizontal grip force;

[0025] S508. Since the suspension system load and the wheel deformation amount are known, the whole wheel is regarded as two longitudinal spring-damping structures connected by the tread. According to the external force exerted on the tire by the suspension and the actual deformation amount of the tire itself, calculate the corresponding relationship between the equivalent tire deformation amount and the tire force, and form the second part of the simplified tire model, i.e., the empirical model of tire force;

[0026] S509. Based on the suspension motion data measured in S501, the original angular momentum obtained in S50�, the suspension speed threshold of the fast and slow valves obtained in S503, the equivalent hardness value obtained in S504, the empirical model of tire horizontal grip force obtained in S507, and the empirical model of tire force obtained in S508, comprehensively obtain the vehicle dynamic model.

[0027] Furthermore, the tire model is included in the vehicle dynamic model, including the steps of: obtaining the vehicle chassis data and assumed data, and obtaining the vehicle motion state; comprehensively resolving the vehicle chassis data in these two parts to produce the G-G tire model.

[0028] Furthermore, in the vehicle dynamic model, then conduct a series of intense driving on the vehicle on a closed road to obtain the vehicle motion state in this state. Subsequently, perform G-G tire model scatter plot modeling on the four-wheel grip force through data decoupling and continuously correct it.

[0029] Beneficial effects of adopting this technical solution:

[0030] Compared with the simplified vehicle dynamic modeling based on the single-point tire model, the present invention is based on the retrospective modeling method, and it is not easy to have cumulative errors, improving the accuracy. Moreover, the tire grip force envelope model based on the G-G scatter plot does not rely on the simplified single-point tire model generated highly relying on experience or debugging duration, reducing the professional threshold and debugging duration, and can be used for the actual control and modeling of vehicles.

[0031] Compared with the vehicle dynamic modeling based on the multi-point complex tire model, the present invention is based on the simplified vehicle dynamics model, greatly reducing the computing power requirement for the model itself. Moreover, the present invention has the ability of real-time self-correction, not only simplifying the process of vehicle development, but also greatly reducing the cost.

[0032] Compared with the vehicle dynamic modeling based on vehicle attitude and G-G diagram of the four-wheel drive system, the present invention can not only be used for the actual control and modeling of vehicles, but also be more accurate and reliable than the above two models. Brief Description of the Drawings

[0033] Figure 1 Schematic diagram of the process for modeling a vehicle dynamic model based on a simplified vehicle dynamics model according to the present invention;

[0034] Figure 2 Schematic diagram for establishing a tire model in the vehicle dynamic model in an embodiment of the present invention. Detailed Embodiment

[0035] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described below with reference to the accompanying drawings.

[0036] In this embodiment, as shown in Figure 1 a vehicle dynamic model modeling method based on a simplified vehicle dynamics model is proposed according to the present invention, including the steps of:

[0037] S10. Identify the characteristic points of the vehicle suspension, perform real-time data derivation on the geometric motion state of the vehicle suspension, and obtain the estimated suspension motion state;

[0038] S20. Collect through an attitude sensor, and perform data correction through the estimated suspension motion state to generate an accurate suspension motion state;

[0039] S30. After synthesizing the accurate suspension motion state and other collected vehicle attitude information, obtain vehicle attitude data;

[0040] S40. Obtain the vehicle motion information collected by various sensors in the vehicle, and obtain a more accurate tire slip angle by comparing the overall vehicle motion information and the wheel speed sensor information;

[0041] S50. Comprehensively synthesize the above data in the vehicle model according to the driver input information and the pre-given existing vehicle information, and finally form a vehicle dynamic model.

[0042] Preferably, a ToF vision sensor is used to identify specific characteristic points on the suspension, and real-time data derivation is performed on the specific geometric motion state of the vehicle suspension.

[0043] Preferably, obtaining the vehicle motion information collected by various sensors in the vehicle includes: the vehicle motion information obtained by synthesizing the data of a wheel speed sensor and a GPS-inertial sensor. Or other sensors that can provide similar information, such as an acceleration sensor array, the vehicle motion information synthesized by a vehicle 360° camera.

[0044] As an optimized solution of the above embodiment, the construction process of the vehicle dynamic model includes the steps of:

[0045] S501. Based on the suspension motion data obtained when the vehicle is in motion provided by the sensor, the geometric position of the inner wall of the wheel, and the wheel size, and according to the geometric appearance of the suspension, calculate the wheel ground contact midpoint position P_CP, and obtain the instantaneous velocity center P_IC and the suspension rotation center P_RC of any motion state of the suspension;

[0046] S502. By synthesizing the suspension rotation center P_RC, obtain the roll rotation axis of the vehicle at any time; according to the roll rotation axis and the real-time acceleration of the vehicle, calculate the original angular momentum of the vehicle at any time;

[0047] S503. According to the suspension motion data, substitute the actual transverse and longitudinal moments of inertia into the suspension motion data; since the spring value of the suspension and the geometric position of the suspension system are known, obtain the effective damping value in any motion state of the suspension and the suspension speed threshold for the fast and slow valve switches;

[0048] S504. Construct a vehicle suspension model: perform a real-time force analysis on the geometric structure of the vehicle suspension according to the real-time yaw and pitch data of the vehicle itself, so as to obtain the internal stress of the suspension system. Through the internal stress of the suspension and the tracking of the deformation amount of the suspension bushing achieved by visual tracking, perform an independent force analysis on each bushing, and then calculate the equivalent hardness value of the suspension flexible component according to its deformation amount under different external forces;

[0049] S505. Using the measured suspension motion data, the original angular momentum, the suspension speed threshold of the fast and slow valve switches, and the equivalent hardness value, obtain all the forces acting on the tire at any time, including the forces caused by the transfer of the vehicle's center of gravity, the forces caused by the mutual traction of the rigid components inside the suspension system, and the forces caused by the deformation of the suspension flexible components;

[0050] S506. Perform a first derivative on the constructed vehicle suspension model. Through the force analysis obtained by combining the geometric structure of the suspension, obtain the real-time tire load W transfer , substitute the accelerations of the vehicle on the X, Y, and Z axes and the vehicle sideslip angle obtained from the vehicle motion state, decompose the overall vehicle grip vector, so as to obtain the real-time grip estimation on each wheel, and calculate the tire slip ratio κ according to the difference between the wheel speed sensor and the calculated ground speed;

[0051] S507. According to the total load W Transfer,sum acting on the tire and the four-wheel lateral grip F y correspondence, deduce a grip equivalent quantity μ corresponding to the wheel deformation amount, where

[0052]

[0053] Form the first part of the simplified tire model, i.e., the empirical model of tire horizontal grip force;

[0054] S508. Since the load of the suspension system and the wheel deformation are known, the whole wheel is regarded as two longitudinal spring-damper structures connected by the tread. According to the external force exerted by the suspension on the tire and the actual deformation of the tire itself, calculate the corresponding relationship between the equivalent tire deformation and the tire force, and form the second part of the simplified tire model, i.e., the empirical model of tire force;

[0055] S509. Based on the suspension motion data measured in S501, the original angular momentum obtained in S502, the suspension speed threshold of the fast and slow valve switches obtained in S503, the equivalent hardness value obtained in S504, the empirical model of tire horizontal grip force obtained in S507, and the empirical model of tire force obtained in S508, comprehensively obtain the vehicle dynamic model.

[0056] As an optimized solution of the above embodiment, as Figure 2 shown, the vehicle dynamic model includes a tire model, which includes the steps of: obtaining vehicle chassis data and assumed data, and obtaining the vehicle motion state; comprehensively resolving the vehicle chassis data from these two parts to generate a G-G tire model.

[0057] The system will first make assumptions about other unknown factors except the tire according to the data given in the vehicle model; for example: for an electric vehicle equipped with two or more motors on a single axle, the system will assume that there is a known open mechanical differential.

[0058] Subsequently, conduct a series of intense driving on the closed road for the vehicle to obtain the vehicle motion state in this state, and then perform G-G tire model scatter plot modeling on the four-wheel grip force through data decoupling and continuously correct it.

[0059] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification only illustrates the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A vehicle dynamic model modeling method based on a simplified vehicle dynamics model, characterized in that Including the steps: S10. Identify the characteristic points of the vehicle suspension, perform real-time data derivation on the geometric motion state of the vehicle suspension, and obtain the estimated suspension motion state; S20. Collect through the attitude sensor, and perform data correction through the estimated suspension motion state to generate the accurate suspension motion state; S30. After synthesizing the accurate suspension motion state and other collected vehicle motion information and wheel speed information, obtain the vehicle attitude data; S40. Obtain the vehicle motion information collected by various sensors in the vehicle, and obtain a more accurate tire slip angle by comparing the overall vehicle motion information and the wheel speed sensor information; S50. Comprehensively based on the driver input information and the pre-given existing vehicle information, synthesize the above data in the vehicle model, and finally form the vehicle dynamic model.

2. A vehicle dynamic model modeling method based on a simplified vehicle dynamics model according to claim 1, characterized in that, Use the ToF vision sensor to identify specific characteristic points on the suspension, and perform real-time data derivation on the specific geometric motion state of the vehicle suspension.

3. A method for modeling a vehicle dynamic model based on a simplified vehicle dynamics model according to claim 1, characterized in that, The vehicle motion information collected by various sensors in the vehicle includes: the vehicle motion information and wheel speed information obtained after synthesizing the data of the wheel speed sensor and the GPS-inertial sensor.

4. A vehicle dynamic model modeling method based on a simplified vehicle dynamics model according to claim 1, characterized in that The construction process of the vehicle dynamic model includes the steps: S501. According to the suspension motion data, the geometric position of the inner wall of the wheel, and the wheel size obtained by the vehicle during motion provided by the sensor, calculate the wheel ground contact midpoint position P_CP according to the geometric appearance of the suspension, and obtain the velocity instant center P_IC of any suspension motion state and the suspension rotation center P_RC; S502. Obtain the roll rotation axis of the vehicle at any time by comprehensively considering the suspension rotation center P_RC; calculate the original angular momentum of the vehicle at any time according to the roll rotation axis and the vehicle's real-time acceleration; S503. According to the suspension motion data, substitute the actual transverse and longitudinal moments of inertia into the suspension motion data; since the spring value of the suspension and the geometric position of the suspension system are known, obtain the effective damping value of any motion state of the suspension and the suspension speed threshold of the fast and slow valve switches; S504. Construct the vehicle suspension model: perform real-time force analysis on the geometric structure of the vehicle suspension according to the real-time yaw and pitch data of the vehicle itself, so as to obtain the internal stress of the suspension system. Through the internal stress of the suspension and the tracking of the deformation amount of the suspension bushing realized by visual tracking, perform independent force analysis on each bushing, and then calculate the equivalent hardness value of the suspension flexible component according to its deformation amount under different external forces; S505. Use the measured suspension motion data, original angular momentum, suspension speed threshold of the fast and slow valve switches, and equivalent hardness value to obtain all the forces acting on the tire at any time, including the forces caused by the transfer of the vehicle's center of gravity, the forces caused by the mutual traction of the rigid components inside the suspension system, and the forces caused by the deformation of the suspension flexible components; S506, perform a first derivative on the constructed vehicle suspension model, and obtain the real-time tire load W through the force analysis obtained by combining the suspension geometric structure. transfer , substitute the accelerations of the vehicle on the X, Y, and Z axes and the vehicle sideslip angle obtained from the vehicle motion state, decompose the overall vehicle grip vector, so as to obtain the real-time grip estimation on each wheel, and calculate the tire slip ratio κ according to the difference between the wheel speed sensor and the calculated ground speed. S507, based on the total load W on the tire within the scope Transfer,sum and the four-wheel lateral grip F y of the corresponding relationship, a grip equivalent μ corresponding to the wheel deformation is derived, where Form the first part of the simplified tire model, that is, the tire horizontal grip empirical model; S508. Since the load of the suspension system and the wheel deformation amount are known, the wheel is regarded as two longitudinal spring-damper structures connected by the tread as a whole, and according to the external force exerted by the suspension on the tire and the actual deformation amount of the tire itself, the corresponding relationship between the equivalent tire deformation amount and the tire force is calculated to form the second part of the simplified tire model, that is, the tire force empirical model. S509. Based on the suspension motion data measured in S501, the original angular momentum obtained in S502, the suspension speed threshold of the fast and slow valve switches obtained in S503, the equivalent hardness value obtained in S504, the tire horizontal grip empirical model obtained in S507, and the tire force empirical model obtained in S508, a vehicle dynamic model is comprehensively obtained.

5. A method for modeling a vehicle dynamic model based on a simplified vehicle dynamics model according to claim 4, characterized in that, The vehicle dynamic model includes a tire model, which includes the steps of: obtaining vehicle chassis data and assumed data, and obtaining the vehicle motion state; comprehensively resolving the vehicle chassis data for these two parts to generate a G-G tire model.

6. A vehicle dynamic model modeling method based on a simplified vehicle dynamics model according to claim 5, characterized in that, In the vehicle dynamic model, subsequently, a series of intense driving is performed on the vehicle on a closed road to obtain the vehicle motion state in this state, and then the G-G tire model scatter plot modeling of the four-wheel grip is carried out through data decoupling and continuously corrected.

Images