CN115973064A - Method and system for systematically monitoring vehicle motion state - Google Patents
Method and system for systematically monitoring vehicle motion state Download PDFInfo
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Abstract
The invention provides a systematic monitoring method for a vehicle motion state, which can systematically monitor the slippage state, the transverse speed, the longitudinal speed, the course angle, the yaw angle and the roll angle of a vehicle, the transverse acceleration measurement deviation, the longitudinal acceleration measurement deviation and the angular speed measurement deviation of an inertial navigation system and the gradient of a running road surface.
Description
Technical Field
The invention relates to the field of information acquisition, in particular to a method and a system for systematically monitoring the motion state of a vehicle.
Background
The human society has already advanced into the era of artificial intelligence, and the value and significance of the automatic driving technology as one of the hot research fields of artificial intelligence have gradually appeared, so that the automatic driving automobile can liberate both hands of human beings, reduce the frequency of traffic accidents, improve the traffic efficiency, ensure the safety of people, and the research and application of the automatic driving technology become the advantage of upgrading the vehicle industry. The automatic driving control system is an important component of automatic driving technology and is an important factor influencing the performance of the automatic driving technology.
The vehicle system state is the input of the automatic driving control system, but is limited by the problems that some state quantities of the system are not easy to directly measure, the measurement error of the sensor is not easy to be measured, and the like. Specifically, some state quantities of the system cannot be directly measured during the movement of the vehicle, for example, when the vehicle runs on a curve, the centroid slip angle information of the vehicle cannot be obtained through the sensor. Meanwhile, the road surface slope angle and the inclination angle of the running vehicle also affect the motion state of the vehicle, but the vehicle-mounted sensor cannot directly measure the road surface slope angle and the inclination angle. The absence of a vehicle motion status signal can result in reduced accuracy or failure of the autopilot control system. In addition, the measurement equipment is limited by economical efficiency and usability, and is difficult to engineer; the measuring equipment is limited by the performance of the measuring equipment, and measuring information has errors. For example, the high-precision GPS system is expensive, and is difficult to be applied to mass production of automatic driving vehicles in order to reduce the vehicle cost. The vehicle-mounted sensor of the mass-production automatic driving vehicle has the advantages of low cost, limited measurement precision and limited signal precision input into a control system, so that high-precision control cannot be realized.
In view of the above problems, the solutions in the prior art generally only design a monitoring method for a single vehicle signal, and do not design a system monitoring method for a vehicle state. Accordingly, there is a need for methods and systems that ameliorate the deficiencies of the prior art.
Disclosure of Invention
This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.
Aiming at the problems in the prior art, the invention provides a systematic monitoring method for the vehicle motion state, which can systematically monitor the slip state, the transverse speed, the longitudinal speed, the course angle, the yaw angle and the roll angle of a vehicle, the transverse acceleration measurement deviation, the longitudinal acceleration measurement deviation and the angular speed measurement deviation of an inertial navigation system and the gradient of a running road surface, enrich the state quantity signals of the vehicle motion system, and acquire the system state quantity signals which can not be measured by using a sensor, so that the system state quantity signal requirements of most automatic driving control algorithms can be met under the condition of only using the inertial navigation system and a wheel speed meter sensor, and the accuracy of the vehicle state quantity signals is improved.
In one embodiment of the present invention, a method for systematically monitoring the state of motion of a vehicle is disclosed, the method comprising:
acquiring an input signal comprising sensor measurements;
detecting a tire slip state based on the tire rotational speed, the tire surface speed, and the tire rotational angular acceleration included in the input signal;
judging a vehicle transverse running state and a vehicle longitudinal running state according to the tire rotating speed, the engine torque, the braking signal and the gear signal which are included in the input signals, wherein the vehicle transverse running state is divided into a lateral deviation state and a non-lateral deviation state, and the vehicle longitudinal running state is divided into a static state, a non-braking running state and a braking running state;
monitoring a vehicle longitudinal running speed based on the tire slip state and the vehicle longitudinal running state;
performing inertial measurement unit bias monitoring system enabling by comparing yaw rate, wheel angle and vehicle longitudinal acceleration included in the input signal with calibrated thresholds;
processing the measurement deviations of the longitudinal acceleration, the lateral acceleration and the yaw angular velocity monitored by the inertial measurement unit offset monitoring system to obtain measurement offset monitoring values of the three measurement deviations and obtain an unbiased measurement value of the three measurement values based on the measurement offset monitoring values;
monitoring the transverse running speed of the vehicle according to the unbiased measurement value;
monitoring the slope angle of the running road surface of the vehicle according to the unbiased measurement value, the transverse running speed of the vehicle and the longitudinal running speed of the vehicle; and
and outputting each monitored monitoring value.
In one embodiment of the invention, the tire slip condition is determined according to one of the following: longitudinal comparison of individual wheel speeds; a lateral comparison between a plurality of wheel speeds; and direct comparison of wheel speed differential to IMU-ax.
In one embodiment of the present invention, monitoring a vehicle longitudinal running speed based on the tire slip condition and the vehicle longitudinal running condition further comprises:
selecting an optimal state tire according to the tire slip state and the longitudinal running state of the vehicle to acquire the tire surface speed of the optimal state tire;
calculating a predicted value of the longitudinal running speed of the vehicle through geometric relation and coordinate transformation based on the surface speed of the tire; and
and acquiring a vehicle longitudinal running speed monitoring value through Kalman filtering by using the vehicle longitudinal running speed predicted value and the vehicle longitudinal running speed information calculated through the sensor information.
In one embodiment of the invention, performing the inertial measurement unit offset monitoring system enabling by comparing the yaw rate, the wheel angle and the vehicle longitudinal acceleration included in the input signal with calibrated thresholds further comprises:
when the vehicle keeps constant-speed straight line running, respectively judging whether the obtained yaw angular speed signal, the obtained wheel corner signal and the obtained vehicle longitudinal acceleration signal are at 0 position; and
and starting the inertial measurement unit offset monitoring system when the distance from the 0 position is larger than a threshold value.
In one embodiment of the present invention, processing the measured deviations of the longitudinal acceleration, the lateral acceleration and the yaw rate monitored by the inertial measurement unit offset monitoring system to obtain measured offset monitoring values of the three measured deviations further comprises:
and respectively processing the three measurement deviations through low-pass filtering and amplitude filtering, and taking the filtered state value as the measurement bias monitoring value.
In one embodiment of the invention, the method further comprises monitoring a vehicle yaw angle based on the unbiased measurement, including the operations of:
establishing a vehicle combined model containing three freedom degrees of motion, namely vertical motion, lateral motion and pitching motion; and
and substituting the unbiased measured value into the vehicle combined model to obtain a vehicle yaw monitoring value.
In one embodiment of the invention, the method further comprises monitoring a vehicle centroid slip angle from the unbiased measurement, wherein the vehicle centroid slip angle and the vehicle lateral running speed are further monitored by:
and (3) acquiring a vehicle mass center slip angle and a vehicle transverse running speed monitoring value by using a vehicle kinematic model and a Luenberger observer.
In one embodiment of the present invention, monitoring a vehicle operating road surface grade angle based on the unbiased measurement and the vehicle lateral and longitudinal operating speeds further comprises:
and acquiring a vehicle running road surface slope angle monitoring value through Kalman filtering.
In one embodiment of the invention, the vehicle longitudinal running speed and the vehicle centroid slip angle and the vehicle lateral running speed are further monitored based on the vehicle running road surface gradient angle.
In another embodiment of the present invention, a system for systematic monitoring of vehicle motion states is disclosed, the system comprising:
a signal input module configured to acquire an input signal comprising sensor measurements;
a measurement bias monitoring module configured to:
performing inertial measurement unit bias monitoring system enabling by comparing yaw rate, wheel angle and vehicle longitudinal acceleration included in the input signal with calibrated thresholds; and
processing the measurement deviations of the longitudinal acceleration, the lateral acceleration and the yaw angular velocity monitored by the inertial measurement unit offset monitoring system to obtain measurement offset monitoring values of the three measurement deviations and obtain an unbiased measurement value of the three measurement values based on the measurement offset monitoring values;
a longitudinal speed monitoring module configured to:
detecting a tire slip state based on the tire rotational speed, the tire surface speed, and the tire rotational angular acceleration included in the input signal;
judging a vehicle transverse running state and a vehicle longitudinal running state according to the tire rotating speed, the engine torque, the braking signal and the gear signal which are included in the input signals, wherein the vehicle transverse running state is divided into a lateral deviation state and a non-lateral deviation state, and the vehicle longitudinal running state is divided into a static state, a non-braking running state and a braking running state; and
monitoring a vehicle longitudinal running speed based on the tire slip state and the vehicle longitudinal running state;
a lateral speed monitoring module configured to monitor a vehicle lateral travel speed based on the unbiased measurement;
a road surface gradient monitoring module configured to monitor a vehicle operating road surface gradient angle based on the unbiased measurement and the vehicle lateral and longitudinal operating speeds; and
a signal output module configured to output the monitored values.
In one embodiment of the invention, the longitudinal speed monitoring module is further configured to determine the tire slip status according to one of the following: longitudinal comparison of individual wheel speeds; a lateral comparison between a plurality of wheel speeds; and direct comparison of wheel speed differential to IMU-ax.
In one embodiment of the invention, the longitudinal speed monitoring module is further configured to monitor the vehicle longitudinal running speed by:
selecting an optimal state tire according to the tire slip state and the longitudinal running state of the vehicle to acquire the tire surface speed of the optimal state tire;
calculating a predicted value of the longitudinal running speed of the vehicle through geometric relation and coordinate transformation based on the surface speed of the tire; and
and acquiring a vehicle longitudinal running speed monitoring value through Kalman filtering by using the vehicle longitudinal running speed predicted value and the vehicle longitudinal running speed information calculated through the sensor information.
In one embodiment of the invention, the measurement bias monitoring module is further configured to perform inertial measurement unit bias monitoring system enabling by:
when the vehicle keeps constant-speed straight line running, respectively judging whether the obtained yaw angular speed signal, the obtained wheel corner signal and the obtained vehicle longitudinal acceleration signal are at 0 position; and
and starting the inertial measurement unit offset monitoring system when the distance from the 0 position is larger than a threshold value.
In one embodiment of the invention, the measurement bias monitoring module is further configured to obtain the measurement bias monitoring value by:
and respectively processing the three measurement deviations through low-pass filtering and amplitude filtering, and taking the filtered state value as the measurement bias monitoring value.
In one embodiment of the invention, the apparatus further comprises a body angle monitoring module configured to monitor a vehicle yaw angle based on an unbiased measurement of the three measurements, and the body angle monitoring module is further configured to monitor the vehicle yaw angle by:
establishing a vehicle combined model containing three freedom degrees of motion, namely vertical motion, lateral motion and pitching motion; and
and substituting the unbiased measured value into the vehicle combined model to obtain a vehicle yaw monitoring value.
In one embodiment of the invention, the lateral speed monitoring module is further configured to monitor vehicle centroid slip angle from the unbiased measurements and monitor the vehicle centroid slip angle and the vehicle lateral running speed by:
and (3) acquiring a vehicle mass center slip angle and a vehicle transverse running speed monitoring value by using a vehicle kinematic model and a Luenberger observer.
In one embodiment of the invention, the road slope monitoring module is further configured to monitor the vehicle operating road slope angle by:
and acquiring a vehicle running road surface slope angle monitoring value through Kalman filtering.
In yet another embodiment of the present invention, a computer-readable storage medium storing instructions for systematically monitoring vehicle motion states is disclosed, comprising:
instructions for obtaining an input signal comprising sensor measurements;
instructions for detecting a tire slip state based on the tire rotational speed, the tire surface speed, and the tire rotational angular acceleration included in the input signal;
instructions for determining a vehicle lateral running state and a vehicle longitudinal running state from the tire rotational speed, the engine torque, the brake signal, and the gear signal included in the input signal, wherein the vehicle lateral running state is divided into a yaw and a yaw, and the vehicle longitudinal running state is divided into a standstill, a running non-brake, and a running brake;
instructions for monitoring a vehicle longitudinal running speed based on the tire slip condition and the vehicle longitudinal running condition;
instructions for performing inertial measurement unit bias monitoring system enablement by comparing yaw rate, wheel angle, and vehicle longitudinal acceleration included in the input signal to calibrated thresholds;
instructions for processing the measured deviations of the longitudinal acceleration, the lateral acceleration, and the yaw angular velocity monitored by the inertial measurement unit offset monitoring system to obtain measured offset monitoring values of the three measured deviations and obtaining an unbiased measurement of the three measurements based on the measured offset monitoring values;
instructions for monitoring a lateral vehicle travel speed based on the unbiased measurement;
instructions for monitoring a vehicle operating road slope angle based on the unbiased measurement and the lateral and longitudinal vehicle operating speeds; and
instructions for outputting the monitored values.
Other aspects, features and embodiments of the present invention will become apparent to those ordinarily skilled in the art upon review of the following description of specific exemplary embodiments of the invention in conjunction with the accompanying figures. While features of the invention may be discussed below with respect to certain embodiments and figures, all embodiments of the invention can include one or more of the advantageous features discussed herein. In other words, while one or more embodiments may have been discussed as having certain advantageous features, one or more of such features may also be used in accordance with the various embodiments of the invention discussed herein. In a similar manner, although example embodiments may be discussed below as device, system, or method embodiments, it should be appreciated that such example embodiments may be implemented in a variety of devices, systems, and methods.
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So that the manner in which the above recited features of the present disclosure can be understood in detail, a more particular description of the disclosure, briefly summarized above, may be had by reference to aspects, some of which are illustrated in the appended drawings. It is to be noted, however, that the appended drawings illustrate only certain typical aspects of this disclosure and are therefore not to be considered limiting of its scope, for the description may admit to other equally effective aspects.
FIG. 1 shows a block diagram of a system for systematic monitoring of vehicle motion states according to one embodiment of the present disclosure.
FIG. 2 shows a signal flow diagram in a system for systematic monitoring of vehicle motion states according to one embodiment of the present disclosure.
FIG. 3 shows a flow diagram of a method for systematic monitoring of vehicle motion states according to one embodiment of the present disclosure.
Detailed Description
Various embodiments will now be described more fully hereinafter with reference to the accompanying drawings, which form a part hereof, and which show specific exemplary embodiments. Embodiments may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of these embodiments to those skilled in the art. Embodiments may be implemented as a method, system or device. Accordingly, embodiments may take the form of a hardware implementation, an entirely software implementation, or an implementation combining software and hardware aspects. The following detailed description is, therefore, not to be taken in a limiting sense.
The steps in the various flowcharts may be performed by hardware (e.g., processors, engines, memory, circuitry), software (e.g., operating systems, applications, drivers, machine/processor-executable instructions), or a combination thereof. As one of ordinary skill in the art will appreciate, methods involved in various embodiments may include more or fewer steps than those shown.
The system monitoring method for the vehicle motion state is characterized in that the existing mature monitors and filter methods, such as a Luenberger monitor, a Kalman filter, a low-pass filter and other system combinations, are utilized to systematically monitor the slip state, the transverse speed, the longitudinal speed, the course angle, the yaw angle, the roll angle of a vehicle, the transverse acceleration measurement deviation, the longitudinal acceleration measurement deviation and the angular speed measurement deviation of an inertial navigation system and the gradient of a running road surface, so that the state quantity signals of a vehicle motion system are increased, and the accuracy of the vehicle state quantity signals is improved.
Aspects of the present disclosure are described more fully hereinafter in terms of block diagrams and method flow diagrams.
Fig. 1 shows a block diagram of a system 100 for systematic monitoring of vehicle motion states according to one embodiment of the present disclosure.
As shown in FIG. 1, in one embodiment of the present invention, a system 100 for systematically monitoring vehicle motion includes a signal input module 102, a measurement bias monitoring module 104, a longitudinal speed monitoring module 106, an (optional) body angle monitoring module 108 (shown in phantom in FIG. 1), a lateral speed monitoring module 110, a road grade monitoring module 112, and a signal output module 114.
In one embodiment of the invention, the signal input module 102 may be configured to acquire an input signal comprising sensor measurements. In this embodiment, the sensor measurements may include, but are not limited to, tire speed, tire surface speed, tire cornering acceleration, engine torque, brake signals, gear signals, longitudinal acceleration, lateral acceleration, and yaw rate, among others. The various measurements/signals acquired are fed to various monitoring modules/monitors of the present invention for processing and analysis.
In one embodiment of the invention, the measurement bias monitoring module 104 may be configured to perform inertial measurement unit bias monitoring system enablement by comparing yaw rate, wheel angle, and vehicle longitudinal acceleration included in the input signal to calibrated thresholds; and processing the measured deviations of the longitudinal acceleration, the lateral acceleration and the yaw angular velocity monitored by the inertial measurement unit offset monitoring system to obtain measured offset monitoring values of the three measured deviations and obtain unbiased measured values of the longitudinal acceleration, the lateral acceleration and the yaw angular velocity based on the measured offset monitoring values. In one embodiment of the present invention, it may also be determined whether the inertial measurement unit offset monitoring system (specifically, the inertial measurement unit lateral acceleration offset, longitudinal acceleration offset, and yaw rate offset monitoring system) is on by comparing the yaw rate, wheel angle, and vehicle longitudinal acceleration included in the input signal with calibrated thresholds.
In another embodiment of the present invention, the measurement bias monitoring module 104 may be further configured to respectively determine whether the acquired yaw rate signal, wheel angle signal and vehicle longitudinal acceleration signal are at 0 position when the vehicle keeps straight running at a constant speed, and to turn on the inertial measurement unit bias monitoring system if the distance from 0 position is greater than a threshold value. As will be appreciated by those skilled in the art, the threshold may be any suitable threshold, not limited to a particular threshold, and the calibration threshold (bit 0) may also be any other suitable calibration threshold, not limited to the bit 0 calibration threshold.
With the inertial measurement unit bias monitoring system turned on, when the lateral acceleration bias, the longitudinal acceleration bias, and the yaw rate bias are monitored, the measured bias monitoring module 104 may be further configured to obtain measured bias monitoring values for the three measured biases by: the three measurement deviations are respectively processed through low-pass filtering and amplitude filtering, and the filtered state value is used as the measurement bias monitoring value, and the calculation principle is as follows:
wherein, the first and the second end of the pipe are connected with each other,
for the filtered state values, namely the longitudinal acceleration measurement deviation, the transverse acceleration measurement deviation and the yaw angular velocity measurement deviation of the inertial navigation system, x (k) is the measured value at the moment k, wherein x (k) can be understood as a matrix formed by three signal offsets, each signal offset needs to be filtered, and p is a filtering factor. As can be appreciated by those skilled in the art, the above calculation principle [1 ]]Without limitation, any other suitable calculation principle may be employed in other embodiments of the invention to calculate the measurement bias monitor value.
In one embodiment of the invention, first, the longitudinal speed monitoring module 106 may be configured to detect a tire slip condition based on the tire rotational speed, the tire surface speed, and the tire cornering acceleration included in the input signals. In this embodiment, the longitudinal speed monitoring module 106 may be further configured to determine the tire slip status according to one of the following: longitudinal comparison of individual wheel speeds; a lateral comparison between a plurality of wheel speeds; and direct comparison of wheel speed differential to IMU-ax. Specifically, the method comprises the following steps:
1) Longitudinal comparison of individual wheel speeds: the current speed is compared with the historical speed, and if the change is too large, the slip is prone to happen. The calculation principle is as follows:
where w (k) is the angular velocity value of the current tire measured the kth time, m is the number of recorded samples, Δ ω thrshld If the rotation speed exceeds the threshold value, the tire is judged to be slipped.
2) Lateral comparison between a plurality of wheel speeds: when the electric vehicle is driven, the rotating speed of a driving wheel is higher than that of a driven wheel, and the slip tendency is larger; during braking, the wheel with high slip rate generally has higher locking probability and has no representativeness of the vehicle speed. The calculation principle is as follows:
wherein w (k) is the angular velocity value of the current tire measured at the kth time, R r In order to be the current radius of the tire,
longitudinal velocity, Δ v, obtained for the kth monitoring thrshld If the speed threshold is exceeded, it is determined that the tire is slipping. As can be appreciated by those skilled in the art, the above calculation principle [2 ]]And [3]Without limitation, any other suitable calculation principle may be employed in other embodiments of the invention to determine whether a tire is slipping.
3) Direct comparison of wheel speed differential to IMU-ax: the vehicle speed of the vehicle can be converted from the wheel speed of the wheel, when the tire slips, the rotation speed of the wheel will rapidly rise, and then the vehicle speed converted from the wheel speed of the wheel will also rapidly rise, so the wheel speed differential, that is, the change rate of the rotation speed of the tire and the change rate of the vehicle speed converted from the wheel speed are the same. The IMU-ax is the acceleration of the vehicle measured by the sensor IMU in a physical manner, i.e., the acceleration throughout the movement of the vehicle body. When the wheel does not slip, the wheel speed is actually the speed of the entire vehicle body movement, which is the same, and the differential of the wheel speed is consistent with the IMU-ax value. When the wheel slips, the wheel speed rapidly rises, but the movement speed of the whole vehicle body is the same as that of the wheel speed, so that the differential value of the wheel speed is larger than the value of IMU-ax, and the wheel slip can be judged.
In one embodiment of the invention, the longitudinal speed monitoring module 106 may be further configured to determine the vehicle lateral running state and the vehicle longitudinal running state based on the tire speed, the engine torque, the brake signal, and the gear signal included in the input signal. The determination of the running state of the vehicle may be performed before, after, or simultaneously with the above-described determination of the tire slip state. In this embodiment, the vehicle lateral running state can be divided into a cornering bias and a non-cornering bias, and the vehicle longitudinal running state can be divided into a stationary, running non-braking, and running braking.
Subsequently, the longitudinal speed monitoring module 106 may be configured to monitor the vehicle longitudinal running speed based on the tire slip status and the vehicle longitudinal running status. Specifically, the longitudinal speed monitoring module is further configured to monitor the vehicle longitudinal running speed by:
1) And selecting the best-state tire according to the tire slip state and the longitudinal running state of the vehicle to acquire the tire surface speed of the best-state tire. In one embodiment of the present invention, the best-case tire is selected based on the wheel having the lowest wheel slip as the best-case wheel and the tire surface speed of the best-case tire is obtained.
2) Calculating a predicted value of the longitudinal running speed of the vehicle through geometric relation and coordinate transformation based on the surface speed of the tire; and
3) And acquiring a vehicle longitudinal running speed monitoring value through Kalman filtering by using the vehicle longitudinal running speed predicted value and the vehicle longitudinal running speed information calculated through the sensor information.
The calculation principle of the steps 1) to 3) is as follows:
P - (k)＝AP(k-1)A T +Q [5]
K(k)＝P - (k)H T (HP - (k)H T +R) -1 [6]
P(k)＝(I-K(k)H)P - (k) [8]
wherein the content of the first and second substances,
the method is characterized in that a predicted state value calculated by a model at the moment k, namely longitudinal speed, u (k) is an input quantity of the model at the moment k, namely longitudinal acceleration, A and B are system parameter matrixes obtained by a kinematic model and coordinate transformation, Z (k) is a measured value at the moment k, and H is a parameter of a measuring system. Q and R are covariance matrices of process noise and measurement noise, and K (K) is the Kalman gain at time K. P (k) is the vehicle longitudinal running speed at time k. As can be appreciated by those skilled in the art, the above-described calculation principle [4]]-[8]Without limitation, any other suitable calculation principle may be employed in other embodiments of the invention to calculate the vehicle longitudinal running speed monitoring value.
In one embodiment of the present invention, the optional body angle monitoring module 108 may be configured to monitor vehicle yaw angle based on an unbiased measurement of the three measurements (i.e., longitudinal acceleration, lateral acceleration, and yaw angular velocity) provided by the measured offset monitoring module 104. In this embodiment, the body angle monitoring module 108 may be further configured to monitor the vehicle yaw angle by: establishing a vehicle combined model containing three motion degrees of freedom of vertical, lateral and pitching (the suspension at the four wheels is equivalent to a spring damping element, and the vertical degree of freedom is equivalent to the spring damping element); and substituting the unbiased measurement value into the vehicle combination model to obtain a vehicle yaw angle monitoring value.
In one embodiment of the invention, the lateral speed monitoring module 110 may be configured to monitor the vehicle lateral operating speed based on these unbiased measurements. The unbiased measurement may be obtained in the same manner as described above for body angle monitoring module 108, i.e., unbiased measurements of longitudinal acceleration, lateral acceleration, and yaw rate provided by measurement bias monitoring module 104. In another embodiment of the invention, the lateral speed monitoring module 110 may be further configured to monitor the vehicle centroid slip angle from the unbiased measurements and obtain a vehicle centroid slip angle monitoring value and a vehicle lateral operating speed monitoring value using a vehicle kinematic model and a Luenberger observer. As will be appreciated by those skilled in the art, any suitable vehicle kinematics model may be employed without limitation to a particular vehicle kinematics model, and any other suitable observer may be employed to obtain vehicle centroid slip angle and vehicle lateral operating speed monitoring values without limitation to a particular Luenberger observer.
In one embodiment of the invention, the road slope monitoring module 112 may be configured to monitor the vehicle operating road slope angle based on these unbiased measurements as well as the vehicle lateral operating speed provided by the lateral speed monitoring module 110 and the vehicle longitudinal operating speed provided by the longitudinal speed monitoring module 106. In this embodiment, the road surface gradient monitoring module 112 may obtain the vehicle running road surface gradient angle monitoring value through kalman filtering, and the calculation principle is the same as the above equations [4] to [8].
In another embodiment of the invention, the vehicle longitudinal running speed and the vehicle centroid slip angle and the vehicle transverse running speed can be further monitored based on the vehicle running road surface gradient angle to further improve monitoring accuracy.
Fig. 2 shows a signal flow diagram in a system 100 for systematic monitoring of vehicle motion states according to one embodiment of the present disclosure. The various monitors in fig. 2 correspond to the various monitoring modules in fig. 1.
As shown in FIG. 2, various sensors on the vehicle may collect various sensor measurement signals including, but not limited to, tire speed, tire surface speed, tire cornering acceleration, engine torque, braking signals, gear signals, longitudinal acceleration, lateral acceleration, and yaw rate, among others. The various measurements/signals acquired are fed to various monitoring modules/monitors of the present invention for processing and analysis. For example, the tire rotational speed, tire surface speed, tire cornering acceleration, engine torque, brake signals, and gear signals collected by the sensors may be fed to a longitudinal speed monitor for processing and analysis and generation of vehicle longitudinal speed monitor values as signal monitoring results, and the generated longitudinal speed monitor values may be used by other monitors, such as an inertial measurement unit measurement bias monitor and a road grade monitor, as shown in fig. 2.
Further, as shown in fig. 2, the longitudinal acceleration, lateral acceleration, and yaw rate of the vehicle, as collected by the sensors, may be fed to an inertial measurement unit measurement bias monitor, an optional body angle monitor, a lateral speed monitor, and a road slope monitor, respectively, for processing and analysis, and generate a measurement bias monitor value, a vehicle yaw angle (such as pitch angle and roll angle) monitor value, a center of mass yaw angle and vehicle lateral speed monitor value, and a road slope angle monitor value, respectively, as signal monitoring results. Additionally, in one embodiment of the present invention, the measured offset monitor value may in turn be used by the body angle monitor, the lateral speed monitor, and the road slope monitor to correct the longitudinal acceleration, the lateral acceleration, and the yaw rate to produce unbiased measurements of these measurements, the vehicle longitudinal speed and the vehicle lateral speed monitor values may in turn be used by the inertial measurement unit measured offset monitor and the road slope monitor to generate the measured offset monitor value and the road slope angle monitor value, respectively, with greater accuracy, and the road slope angle monitor value may in turn be used by the longitudinal speed monitor and the lateral speed monitor to generate the corresponding monitor values with greater accuracy.
FIG. 3 shows a flow diagram of a method 300 for systematic monitoring of vehicle motion states according to one embodiment of the present disclosure.
As shown in FIG. 3, the method 300 begins at step 302 by acquiring an input signal comprising sensor measurements. In one embodiment of the present invention, the sensor measurements may include, but are not limited to, tire speed, tire surface speed, tire cornering acceleration, engine torque, brake signals, gear signals, longitudinal acceleration, lateral acceleration, and yaw rate, among others. The various measurements/signals acquired are fed to various monitoring modules/monitors of the present invention for processing and analysis.
The method 300 then continues to step 304, where a tire slip condition is detected based on the tire rotational speed, the tire surface speed, and the tire cornering acceleration included in the input signal. In one embodiment of the invention, the tire slip condition is determined according to one of the following: longitudinal comparison of individual wheel speeds; a lateral comparison between a plurality of wheel speeds; and direct comparison of wheel speed differential to IMU-ax.
The method 300 then continues to step 306, where the vehicle lateral running state is divided into yaw and yaw, and the vehicle longitudinal running state is divided into stationary, service non-braking, and service braking, based on the tire speed, engine torque, brake signal, and gear signal included in the input signal.
Subsequently, the method 300 continues to step 308 where the vehicle longitudinal running speed is monitored based on the tire slip condition and the vehicle longitudinal running condition. In one embodiment of the present invention, monitoring a vehicle longitudinal running speed based on the tire slip condition and the vehicle longitudinal running condition further comprises: selecting an optimal state tire according to the tire slip state and the longitudinal running state of the vehicle to acquire the tire surface speed of the optimal state tire; calculating a predicted value of the longitudinal running speed of the vehicle through geometric relation and coordinate transformation based on the surface speed of the tire; and acquiring a vehicle longitudinal running speed monitoring value through Kalman filtering by using the vehicle longitudinal running speed predicted value and the vehicle longitudinal running speed information calculated through the sensor information.
Next, method 300 continues to step 310 with performing inertial measurement unit bias monitoring system enablement by comparing yaw rate, wheel angle, and vehicle longitudinal acceleration included in the input signal to calibrated thresholds. In one embodiment of the invention, the steps further comprise: when the vehicle keeps constant-speed straight line running, respectively judging whether the obtained yaw angular speed signal, the obtained wheel corner signal and the obtained vehicle longitudinal acceleration signal are at 0 position; and turning on the inertial measurement unit bias monitoring system if the difference from 0 is greater than a threshold.
The method 300 then continues to step 312 where the measured biases for the longitudinal acceleration, the lateral acceleration, and the yaw rate monitored by the inertial measurement unit bias monitoring system are processed to obtain measured bias monitored values for the three measured biases and to obtain unbiased measurements for the three measurements (i.e., the longitudinal acceleration, the lateral acceleration, and the yaw rate) based on the measured bias monitored values. In one embodiment of the invention, the steps further comprise: the three measurement deviations are processed by low pass filtering and amplitude filtering and the filtered state value is taken as the measurement bias monitor value. In another embodiment of the present invention, these unbiased measurements may be used to monitor vehicle yaw angle, and in this embodiment of the present invention, monitoring vehicle yaw angle may further comprise: establishing a vehicle combination model containing three freedom degrees of motion, namely vertical motion, lateral motion and pitching motion; and substituting the unbiased measurement value into the vehicle combined model to obtain a vehicle yaw angle monitoring value.
The method 300 then continues to step 314 where the vehicle lateral operating speed is monitored based on the unbiased measurement. In another embodiment of the invention, the method can further comprise monitoring the vehicle mass center slip angle according to the unbiased measurement value, and acquiring the vehicle mass center slip angle and the vehicle transverse running speed monitoring value by utilizing a vehicle kinematic model and a Luenberger observer.
Next, the method 300 continues to step 316 where the vehicle operating road grade angle is monitored based on the unbiased measurement and the vehicle lateral operating speed and the vehicle longitudinal operating speed. In one embodiment of the invention, the steps further comprise: and acquiring a vehicle running road surface slope angle monitoring value through Kalman filtering.
Finally, the method 300 continues to step 318 where the monitored values are output. In one embodiment of the present invention, the output monitoring values may be further used by the respective monitoring module/monitor to generate more accurate monitoring values.
After step 318, the method 300 ends.
In conclusion, the technical scheme of the invention utilizes the existing mature monitor and filter method to carry out systematic monitoring on the slip state, the transverse speed, the longitudinal speed, the course angle, the yaw angle and the roll angle of the vehicle, the transverse acceleration measurement deviation, the longitudinal acceleration measurement deviation and the angular speed measurement deviation of the inertial navigation system and the gradient of the running road surface, increases the state quantity signals of the vehicle motion system and improves the signal precision of the vehicle state quantity.
Embodiments of the present invention are described above with reference to block diagrams and/or operational illustrations of methods, systems, and computer program products according to embodiments of the invention. The functions/acts noted in the blocks may occur out of the order noted in any flowchart. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A method for systematically monitoring the state of motion of a vehicle, the method comprising:
acquiring an input signal comprising sensor measurements;
detecting a tire slip state based on the tire rotational speed, the tire surface speed, and the tire rotational angular acceleration included in the input signal;
judging a vehicle transverse running state and a vehicle longitudinal running state according to the tire rotating speed, the engine torque, the brake signal and the gear signal which are included in the input signals, wherein the vehicle transverse running state is divided into a lateral deviation and a non-lateral deviation, and the vehicle longitudinal running state is divided into a static state, a running non-brake state and a running brake state;
monitoring a vehicle longitudinal running speed based on the tire slip condition and the vehicle longitudinal running condition;
performing inertial measurement unit bias monitoring system enabling by comparing yaw rate, wheel angle, and vehicle longitudinal acceleration included in the input signal to calibrated thresholds;
processing the measurement deviations of the longitudinal acceleration, the lateral acceleration and the yaw angular velocity monitored by the inertial measurement unit offset monitoring system to obtain measurement offset monitoring values of the three measurement deviations and obtain an unbiased measurement value of the three measurement values based on the measurement offset monitoring values;
monitoring the transverse running speed of the vehicle according to the unbiased measurement value;
monitoring a vehicle running road surface gradient angle according to the unbiased measurement value, the vehicle transverse running speed and the vehicle longitudinal running speed; and
and outputting each monitored monitoring value.
2. The method of claim 1, wherein said tire slip condition is determined according to one of the following: longitudinal comparison of individual wheel speeds; a lateral comparison between a plurality of wheel speeds; and direct comparison of wheel speed differential to IMU-ax.
3. The method of claim 1, wherein monitoring a vehicle longitudinal travel speed based on the tire slip condition and the vehicle longitudinal travel condition further comprises:
selecting an optimal state tire according to the tire slip state and the longitudinal running state of the vehicle to obtain the tire surface speed of the optimal state tire;
calculating a predicted value of the longitudinal running speed of the vehicle through geometric relation and coordinate transformation based on the surface speed of the tire; and
and acquiring a vehicle longitudinal running speed monitoring value through Kalman filtering by using the vehicle longitudinal running speed predicted value and the vehicle longitudinal running speed information calculated through the sensor information.
4. The method of claim 1, wherein performing inertial measurement unit bias monitoring system enabling by comparing yaw rate, wheel angle, and vehicle longitudinal acceleration included in the input signal to calibrated thresholds further comprises:
when the vehicle keeps running straight at a constant speed, respectively judging whether the obtained yaw angle speed signal, the obtained wheel angle signal and the obtained vehicle longitudinal acceleration signal are at 0 position; and
and starting the inertial measurement unit bias monitoring system when the distance from the 0 position is larger than a threshold value.
5. The method of claim 1, wherein processing the measured deviations of the longitudinal acceleration, the lateral acceleration, and the yaw rate monitored by the inertial measurement unit offset monitoring system to obtain measured offset monitoring values for the three measured deviations further comprises:
and respectively processing the three measurement deviations through low-pass filtering and amplitude filtering, and taking the filtered state value as the measurement bias monitoring value.
6. The method of claim 1, further comprising monitoring a vehicle yaw angle based on the unbiased measurement, including the operations of:
establishing a vehicle combined model containing three freedom degrees of motion, namely vertical motion, lateral motion and pitching motion; and
and substituting the unbiased measurement value into the vehicle combined model to obtain a vehicle yaw angle monitoring value.
7. The method of claim 1, further comprising monitoring a vehicle center of mass slip angle from the unbiased measurement, wherein the vehicle center of mass slip angle and the vehicle lateral running speed are further monitored by:
and (3) acquiring a vehicle mass center slip angle and a vehicle transverse running speed monitoring value by using a vehicle kinematic model and a Luenberger observer.
8. The method of claim 1, wherein monitoring a vehicle operating road grade angle based on the unbiased measurement and the vehicle lateral operating speed and the vehicle longitudinal operating speed further comprises:
and acquiring a vehicle running road surface slope angle monitoring value through Kalman filtering.
9. The method of claim 7, wherein the vehicle longitudinal running speed and the vehicle centroid slip angle and the vehicle lateral running speed are monitored further based on the vehicle running road surface grade angle.
10. A system for systematically monitoring the state of motion of a vehicle, the system comprising:
a signal input module configured to acquire an input signal comprising sensor measurements;
a measurement bias monitoring module configured to:
performing inertial measurement unit bias monitoring system enablement by comparing yaw angular velocity, wheel turning angle, and vehicle longitudinal acceleration included in the input signal to calibrated thresholds; and
processing the measurement deviations of the longitudinal acceleration, the lateral acceleration and the yaw angular velocity monitored by the inertial measurement unit offset monitoring system to obtain measurement offset monitoring values of the three measurement deviations and obtain an unbiased measurement value of the three measurement values based on the measurement offset monitoring values;
a longitudinal speed monitoring module configured to:
detecting a tire slip state based on a tire rotational speed, a tire surface speed, and a tire rotational angular acceleration included in the input signal;
judging a vehicle transverse running state and a vehicle longitudinal running state according to the tire rotating speed, the engine torque, the brake signal and the gear signal which are included in the input signals, wherein the vehicle transverse running state is divided into a lateral deviation and a non-lateral deviation, and the vehicle longitudinal running state is divided into a static state, a running non-brake state and a running brake state; and
monitoring a vehicle longitudinal running speed based on the tire slip condition and the vehicle longitudinal running condition;
a lateral speed monitoring module configured to monitor a vehicle lateral travel speed based on the unbiased measurement;
a road grade monitoring module configured to monitor a vehicle operating road grade angle based on the unbiased measurement and the vehicle lateral and longitudinal operating speeds; and
a signal output module configured to output the monitored values.
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