CN-122009207-A - Multi-environment engineering vehicle speed estimation method and system

CN122009207ACN 122009207 ACN122009207 ACN 122009207ACN-122009207-A

Abstract

The invention discloses a vehicle speed estimation method and system for a multi-environment engineering vehicle, and belongs to the technical field of engineering vehicle control. The method comprises the steps of obtaining a wheel speed, a vehicle body posture, a GNSS original signal and a required torque signal of a vehicle, performing kinematic correction on the wheel speed based on the vehicle body posture signal, selecting an optimal wheel speed signal according to the required torque, calculating an optimal wheel acceleration through a tracking differentiator, comparing the optimal wheel acceleration with a vehicle longitudinal acceleration, judging single-wheel and all-wheel slip states, selecting a target mode from three predefined modes according to the slip states and combining with the GNSS signal effectiveness, and performing fusion estimation on the optimal wheel speed signal, the vehicle longitudinal acceleration and the GNSS speed signal to obtain a vehicle speed estimated value. According to the invention, through self-adaptive multi-mode fusion and multi-level signal compensation, the accuracy and the robustness of vehicle speed estimation under a complex operation environment are improved, and the method is used for real-time vehicle speed estimation of the articulated distributed electric drive engineering vehicle under the complex operation environment.

Inventors

ZHANG LEI
CAI KAIRUI
DING XIAOLIN
LI SIYANG

Assignees

北京理工大学

Dates

Publication Date: 20260512
Application Date: 20260413

Claims (10)

1. The method for estimating the vehicle speed of the multi-environment engineering vehicle is characterized by comprising the following steps of: acquiring a wheel speed signal, a vehicle body posture signal, a Global Navigation Satellite System (GNSS) original signal and a required torque signal for representing the running state of a vehicle, wherein the vehicle body posture signal is obtained by measuring an Inertial Measurement Unit (IMU); the wheel speed signal is subjected to kinematic correction based on the vehicle body posture signal, and an optimal wheel speed signal is selected from the corrected wheel speed signal of each wheel according to the required torque signal; according to the optimal wheel speed signal, calculating by a tracking differentiator to obtain optimal wheel acceleration, comparing the optimal wheel acceleration with longitudinal acceleration of a vehicle body, and judging a single wheel slip state and an all wheel slip state of the vehicle according to a comparison result and a preset threshold condition, wherein the longitudinal acceleration of the vehicle body is obtained by calculating based on the vehicle body posture signal; Selecting a corresponding target mode from a plurality of predefined vehicle speed fusion estimation modes according to the judged slip state and by combining the effectiveness of the GNSS original signal, wherein the vehicle speed fusion estimation modes comprise a pure wheel speed mode, a wheel speed and IMU fusion mode and a GNSS and IMU fusion mode; And carrying out fusion estimation on the optimal wheel speed signal and the longitudinal acceleration of the vehicle body based on the target mode to obtain a longitudinal speed estimation value of the vehicle at the current moment, wherein when the target mode is the GNSS and IMU fusion mode, the fusion estimation further comprises a GNSS speed signal obtained after delay correction on the GNSS original signal.
2. The method for estimating the vehicle speed of the multi-environment engineering vehicle according to claim 1, wherein the kinematic correction is specifically to compensate the wheel speed signal of each wheel by using the yaw rate in the vehicle body posture signal, eliminate the influence of the wheel speed difference on the selection of the optimal wheel speed signal when the vehicle turns, and obtain the corrected wheel speed signal of each wheel.
3. The method for estimating vehicle speed of a multi-environment engineering vehicle according to claim 1, wherein the selecting the optimal wheel speed signal is specifically as follows: When the value of the required torque signal is positive, selecting a wheel with the minimum wheel speed signal value from the corrected wheel speed signals of each wheel as an optimal wheel, wherein the wheel speed signal is the optimal wheel speed signal; And when the value of the required torque signal is negative, selecting the wheel with the maximum wheel speed signal value from the corrected wheel speed signals of each wheel as an optimal wheel, wherein the wheel speed signal is the optimal wheel speed signal.
4. The method for estimating vehicle speed of a multi-environment engineering vehicle according to claim 1, wherein the determining of the single wheel slip state includes: If the difference value between the optimal wheel acceleration and the longitudinal acceleration of the vehicle body is larger than or equal to a first threshold value, judging that single-wheel slip occurs; And if the difference value between the optimal wheel acceleration and the longitudinal acceleration of the vehicle body is smaller than the first threshold value and the duration exceeds the second threshold value after a preset condition is met, judging that the single wheel slip state is ended, wherein the preset condition comprises that the value of the required torque signal is smaller than a third threshold value or the value of the optimal wheel speed signal is larger than a fourth threshold value.
5. The method of claim 4, wherein determining the all-wheel slip condition comprises determining that all-wheel slip is occurring if all wheels are determined to be single-wheel slip.
6. The method for estimating vehicle speed of a multi-environmental engineering vehicle according to claim 1, wherein the logic for selecting the plurality of predefined vehicle speed fusion estimation modes comprises: selecting the pure wheel speed mode when no single wheel slip occurs and no all wheel slip occurs; When single-wheel slip occurs but all-wheel slip does not occur, selecting a fusion mode of the wheel speed and the IMU; When full-wheel slip occurs and the GNSS original signal is valid, selecting the GNSS and IMU fusion mode; And when full wheel slip occurs and the GNSS original signal fails, selecting a wheel speed and IMU fusion mode, and improving the fusion weight of the IMU signal.
7. The method for estimating vehicle speed of a multi-environment engineering vehicle according to claim 1, wherein the fusion estimation is implemented by using a kalman filter algorithm.
8. The method for estimating the vehicle speed of the multi-environment engineering vehicle according to claim 1, wherein the vehicle longitudinal acceleration is obtained by resolving based on the vehicle body posture signal, specifically, based on a pitch angle in the vehicle body posture signal and combined with an installation angle error of the IMU, the gravity component compensation and the coordinate projection are performed on the original vehicle longitudinal acceleration in the vehicle body posture signal, and the resolved vehicle longitudinal acceleration is obtained.
9. The method for estimating the vehicle speed of the multi-environment engineering vehicle according to claim 1, wherein the method is characterized in that the GNSS original signal is subjected to delay correction, specifically, the GNSS original signal is subjected to time delay compensation based on the longitudinal acceleration of the vehicle body, and the delayed and corrected GNSS speed signal is obtained.
10. A multiple environmental engineering vehicle speed estimation system, wherein the system, when executed, implements a multiple environmental engineering vehicle speed estimation method as defined in claims 1-9, comprising: The signal acquisition module is configured to acquire a wheel speed signal of each wheel of the vehicle, a vehicle body posture signal, a Global Navigation Satellite System (GNSS) original signal and a required torque signal representing the running state of the vehicle, wherein the vehicle body posture signal is obtained through measurement of an Inertial Measurement Unit (IMU); The wheel speed processing module is configured to perform kinematic correction on the wheel speed signal based on the vehicle body posture signal, and select an optimal wheel speed signal from the corrected wheel speed signals of each wheel according to the required torque signal; The slip judging module is configured to calculate and obtain optimal wheel acceleration through a tracking differentiator according to the optimal wheel speed signal, compare the optimal wheel acceleration with longitudinal acceleration of a vehicle body, and judge a single-wheel slip state and an all-wheel slip state of the vehicle according to a comparison result, wherein the longitudinal acceleration of the vehicle body is obtained by calculating based on the vehicle body attitude signal; The mode selection module is configured to select a corresponding target mode from a plurality of predefined vehicle speed fusion estimation modes according to the judged slip state and in combination with the effectiveness of the GNSS original signal, wherein the vehicle speed fusion estimation modes comprise a pure wheel speed mode, a wheel speed and IMU fusion mode and a GNSS and IMU fusion mode; The speed fusion module is configured to fusion estimate the optimal wheel speed signal and the longitudinal acceleration of the vehicle body based on the target mode to obtain a longitudinal speed estimation value of the vehicle at the current moment, wherein when the target mode is the GNSS and IMU fusion mode, the speed fusion module is further configured to delay and correct the GNSS original signal to obtain a GNSS speed signal, and incorporate the GNSS speed signal into the fusion estimation.

Description

Multi-environment engineering vehicle speed estimation method and system Technical Field The invention relates to the technical field of engineering vehicle control, in particular to a method and a system for estimating the speed of a multi-environment engineering vehicle. Background The articulated distributed electrically driven engineering vehicle, such as a loader, has the advantages of flexibility, high efficiency and energy conservation, and is an important development direction of engineering machinery in the future. In various working environments such as shoveling, transferring, unloading, etc., the movement state of the vehicle is extremely complex. Particularly, in the working condition of shoveling, the interaction of the bucket and materials can cause severe changes of longitudinal acceleration, pitch angle and vertical loads of front and rear axles of the vehicle, so that slipping and traction force reduction of a driving wheel are easily caused, and the working efficiency and continuity are seriously affected. Therefore, the longitudinal vehicle speed estimation can be accurately and real-timely realized, is an important input standard for advanced control functions such as vehicle driving anti-skid control, power coordination control and the like, and is important for guaranteeing the operation performance and safety of the whole vehicle under complex and variable working conditions. Currently, a vehicle speed estimation method of an engineering vehicle mainly depends on a wheel speed sensor. For example, the prior art discloses a vehicle longitudinal reference vehicle speed estimation method and system suitable for multiple working conditions, and a vehicle (patent publication number CN119239618 a), wherein different wheel speeds are selected as reference vehicle speeds by detecting different working conditions such as low speed, braking, turning and the like. However, the reliability dependence of the method on the accuracy of the sensor signal and the working condition recognition logic is high, and when the sensor is interfered by noise or the characteristics of various working conditions are overlapped in a crossed mode, misjudgment is easy to occur, so that the vehicle speed estimation accuracy is reduced. Furthermore, the calculation of the turning condition involves more sensors, which is limited in cost-sensitive applications. Another prior art proposes a longitudinal vehicle speed estimation method and device (patent publication No. CN 117622165A) of a full-wheel distributed vehicle, which evaluates the reliability by comparing the estimated value and the measured value of the wheel speed/acceleration, and obtains the vehicle speed based on the data fusion of the trusted wheels. The method improves the data reliability to a certain extent, but the core is still based on a single kinematic frame, and when full wheel slip occurs or a sensor has short-time abnormality, a reliability assessment mechanism can be invalid, so that the vehicle speed estimation has larger fluctuation or delay. In summary, the existing engineering vehicle speed estimation method is generally characterized by unstable estimation precision and insufficient robustness when aiming at multiple environments such as uneven road surface adhesion, large load impact, frequent working condition switching and the like in actual operation, is mostly dependent on a single information source or simple rules, has poor adaptability to dynamically-changed environments and working conditions, and is difficult to balance between precision and calculation efficiency in an embedded control system with high real-time requirements. Disclosure of Invention The invention aims to provide a method and a system for estimating the speed of a multi-environment engineering vehicle, which are used for solving the problems in the prior art. In order to achieve the above purpose, the technical scheme adopted by the invention is as follows: a vehicle speed estimation method for a multi-environment engineering vehicle comprises the following steps: acquiring a wheel speed signal, a vehicle body posture signal, a Global Navigation Satellite System (GNSS) original signal and a required torque signal for representing the running state of a vehicle, wherein the vehicle body posture signal is obtained by measuring an Inertial Measurement Unit (IMU); the wheel speed signal is subjected to kinematic correction based on the vehicle body posture signal, and an optimal wheel speed signal is selected from the corrected wheel speed signal of each wheel according to the required torque signal; according to the optimal wheel speed signal, calculating by a tracking differentiator to obtain optimal wheel acceleration, comparing the optimal wheel acceleration with longitudinal acceleration of a vehicle body, and judging a single wheel slip state and an all wheel slip state of the vehicle according to a comparison result and a preset threshold condition, wherein