CN111114547B - Distributed driving electric motor coach adaptive cruise curve control method - Google Patents
Distributed driving electric motor coach adaptive cruise curve control method Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/14—Adaptive cruise control
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
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Abstract
The invention discloses a distributed driving electric motor coach adaptive cruise curve control method, which comprises the following specific steps: locking following target vehicle- > target motion attitude sensing- > curve region detection- > estimation of curve curvature- > estimation of yaw velocity- > judgment of vehicle control power- > control of adaptive cruise of a curve of the vehicle. The invention has obvious advancement and innovation in the aspects of target identification accuracy and curve driving safety, provides a new control method for the loss and locking of the cruise target and the vehicle body sideslip control in the curve process, effectively solves the defects of the traditional self-adaptive cruise system, and improves the driving safety.
Description
Technical Field
The invention relates to the technical field of adaptive control of new energy buses, in particular to a distributed driving electric bus adaptive cruise curve control method.
Background
An Adaptive Cruise Control (ACC) system is taken as a research hotspot of an automobile active safety and intelligent traffic system, can effectively reduce the operation burden of a driver in the driving process, improves the traffic flow of roads and improves the driving comfort of vehicles. However, the existing self-adaptive cruise system of the electric motor coach has defects and defects in design, particularly under the condition of a curve, a following target can be lost after the electric motor coach enters the curve, vehicles of adjacent lanes can be misjudged as the target of the lane, the curvature of the curve is misjudged without early deceleration, or the self-adaptive cruise function is directly exited during the curve, so that potential safety hazards are brought to a driver.
Chinese patent: a method and apparatus for controlling a hybrid adaptive cruise curve (Japanese patent application laid-open No. 108189838B, No. 201711481266.2, applicant: Jili institute of automotive research (Ningbo) Co., Ltd.) propose to acquire road information and curve information ahead of a vehicle using a GPS and an electronic map, calculate a safe vehicle speed when passing through a curve from the curve information in advance, detect whether the vehicle enters the curve in real time, and control the vehicle speed based on steering information of the vehicle, steering wheel angle information of the vehicle, and lane line detection information.
Chinese patent: a curve control system and method (publication No. 105667509A, application patent No. 201511024574.3, applicant: Suzhou Anzhi automobile parts Co., Ltd.) for an automobile adaptive cruise control system comprises a data acquisition module, a front automobile state judgment module, a road curvature calculation module, an effective target screening module and a vehicle speed calculation module, and is used for reasonably controlling a vehicle according to the running condition of the vehicle.
Chinese patent: a vehicle adaptive cruise control system (publication No. 103754221B, application No. 201410033748.1, applicant: Qinghua university) includes an information acquisition unit, a lane change warning unit, an adaptive cruise control unit, and a vehicle dynamics unit that converts a desired longitudinal acceleration into a desired throttle opening or brake pressure and transmits it to a vehicle object, completing longitudinal control of the vehicle object.
Chinese patent: a target extraction method for a vehicle adaptive cruise control system (publication No. 108944929A, application patent No. 201810552699.0, applicant: Hefei Zhongke automatic control systems, Inc.) uses an ESR radar sensor to identify a front target, extracts target data, and judges whether the target is a target vehicle or a target object; and (4) performing curve recognition when the vehicle is at a curve, and judging whether a target in front of the main vehicle is a valid target.
The adaptive cruise system of the electric motor coach in the prior art has the defects and shortcomings in design, and particularly has potential safety hazards in the process of curve following cruise. The invention aims to solve the problems, and the scheme provides that: the system is based on the self-adaptive cruise curve control method, and has obvious advancement and innovation in the aspects of target identification accuracy and curve running safety.
Disclosure of Invention
The invention discloses a distributed driving electric motor coach adaptive cruise curve control method, which mainly aims to overcome the defects and shortcomings in the prior art.
The technical scheme adopted by the invention is as follows:
a distributed driving electric motor coach adaptive cruise curve control method comprises the following specific steps:
step 1: locking a following target vehicle, starting an adaptive cruise function when the vehicle normally runs without faults, and locking a vehicle in front of a lane as the following target vehicle;
step 2: sensing the moving posture of the target, receiving the camera video and the millimeter wave radar information by the vehicle fusion sensor module to perform data fusion, integrating a target screening algorithm, and completing the detection of the state of the front vehicle and the lane line information;
and step 3: detecting a curve area: after the front vehicle starts to enter a curve, the vehicle fusion sensor module detects the deviation angle theta information, and the vehicle millimeter wave radar automatically compensates a dynamic detection area ROI (region of interest);
and 4, step 4: estimation of the curvature of the curve: the vehicle curve curvature estimation module receives the information of the fusion sensor module, estimates the curvature of the curve, the reciprocal of the curvature of the curve is the radius of the curvature of the curve, and then sends the estimation result to the vehicle adaptive cruise control module;
and 5: estimation of yaw rate: the vehicle self-adaptive cruise controller module receives information of the fusion sensor module and the curve curvature radius estimation module, and estimates a value of a yaw velocity according to the vehicle speed and the curve curvature radius;
step 6: judging the control right of the vehicle: the vehicle self-adaptive cruise controller module compares the estimated yaw velocity with a set threshold value, and exits from the self-adaptive cruise function when the value of the yaw velocity is larger than the threshold value, and the vehicle control right is given to the driver for control; when the value of the yaw rate is not greater than the threshold value, calculating the torque required by the current vehicle running state, and sending control information to the vehicle drive-by-wire chassis;
and 7: controlling the adaptive cruise of a curve of a vehicle: the vehicle drive-by-wire chassis executes the instruction information sent by the vehicle adaptive cruise controller module, controls the motion state of the vehicle and completes the adaptive cruise of the curve.
Further, the preceding vehicle state in step 2 includes: and detecting and judging the relative distance, the relative speed and the deviation angle of the front vehicle and the vehicle.
Further, the lane line information in step 2 includes detecting whether the leading vehicle is on the lane.
Further, the drive-by-wire chassis of step 7 is a distributed drive-by-wire chassis.
As can be seen from the above description of the present invention, compared with the prior art, the present invention has the following advantages:
the fusion sensor module receives camera video and millimeter wave radar information to perform data fusion, and an integrated target screening algorithm accurately detects the state of a front vehicle and lane line information; the curve curvature estimation module is used for receiving the information of the fusion sensor module, estimating the curvature of the curve and sending an estimation result to the self-adaptive cruise controller module; the adaptive cruise controller module is used for calculating the torque required by the current vehicle running state of the vehicle according to the information of the fusion sensor module and the curve curvature estimation module and sending control information to the wire-controlled chassis; the drive-by-wire chassis driven in a distributed mode executes instruction information from the adaptive cruise controller module, controls the motion state of the vehicle and finally achieves the adaptive cruise function of a curve.
The scheme provides a new system and a control mode, integrates a sensor fusion module, a curve curvature estimation module, an adaptive cruise controller and a distributed drive-by-wire chassis, provides a self-adaptive cruise curve control method based on the system, has obvious advancement and innovation in the aspects of target identification accuracy and curve running safety, provides a new control method for loss and locking of a cruise target and vehicle body sideslip control in the curve process, effectively solves the defects of the traditional self-adaptive cruise system, and improves the driving safety.
Drawings
FIG. 1 is a flow chart of an adaptive cruise control method of the present invention.
Detailed Description
Embodiments of the present invention will be further described with reference to the accompanying drawings.
A distributed driving electric motor coach adaptive cruise curve control method comprises the following specific steps:
step 1: locking a following target vehicle, starting an adaptive cruise function when the vehicle normally runs without faults, and locking a vehicle in front of a lane as the following target vehicle;
step 2: sensing the moving posture of the target, receiving the camera video and the millimeter wave radar information by the vehicle fusion sensor module to perform data fusion, integrating a target screening algorithm, and completing the detection of the state of the front vehicle and the lane line information;
and step 3: detecting a curve area: after the front vehicle starts to enter a curve, the vehicle fusion sensor module detects the deviation angle theta information, and the vehicle millimeter wave radar automatically compensates a dynamic detection area ROI (region of interest);
and 4, step 4: estimation of the curvature of the curve: the vehicle curve curvature estimation module receives the information of the fusion sensor module, estimates the curvature of the curve, the reciprocal of the curvature of the curve is the radius of the curvature of the curve, and then sends the estimation result to the vehicle adaptive cruise control module;
and 5: estimation of yaw rate: the vehicle self-adaptive cruise controller module receives information of the fusion sensor module and the curve curvature radius estimation module, and estimates a value of a yaw velocity according to the vehicle speed and the curve curvature radius;
step 6: judging the control right of the vehicle: the vehicle self-adaptive cruise controller module compares the estimated yaw velocity with a set threshold value, and exits from the self-adaptive cruise function when the value of the yaw velocity is larger than the threshold value, and the vehicle control right is given to the driver for control; when the value of the yaw rate is not greater than the threshold value, calculating the torque required by the current vehicle running state, and sending control information to the vehicle drive-by-wire chassis;
and 7: controlling the adaptive cruise of a curve of a vehicle: the vehicle drive-by-wire chassis executes the instruction information sent by the vehicle adaptive cruise controller module, controls the motion state of the vehicle and completes the adaptive cruise of the curve.
Further, the preceding vehicle state in step 2 includes: and detecting and judging the relative distance, the relative speed and the deviation angle of the front vehicle and the vehicle.
Further, the lane line information in step 2 includes detecting whether the leading vehicle is on the lane.
Further, the drive-by-wire chassis of step 7 is a distributed drive-by-wire chassis.
Due to the common use of yaw-rate sensors, the yaw-rate can generally be obtained directly by means of the yaw-rate sensor. Besides, the yaw rate observation can be performed by using the kinematic relationship of the wheel speed and the yaw rate. The related art also gives a method of estimating the yaw rate using the rear wheel speed. For a vehicle with non-driven wheels, a set of non-driven wheel speed signals is often used for estimation, a yaw rate is obtained by using a wheel speed difference and a wheel track regression of the non-driven wheels, and when the non-driven wheels are steering wheels, a front wheel steering angle signal is also introduced, as shown in the following formula.
In the formula (I), the compound is shown in the specification,
as an estimate of the yaw-rate,
，
the wheel speeds of the left and right wheels of the front axle or the rear axle,
the wheel track of the left wheel and the right wheel of the front axle or the rear axle,
for the front wheel steering angle, if the estimation is made for the rear (non-steered) left and right wheels,
the items may be omitted.
There is also a related art that extends the algorithm to estimate the yaw rate using the four wheel speeds. As shown in the following formula.
Theoretically, the yaw rate can be obtained by regression through the method as long as one group of front wheels or rear wheels of the vehicle does not slip. However, in the case of a large yaw acceleration, the wheel radius is changed due to the shift of the load of the inner and outer wheels, and the estimation accuracy is affected. At this time, the estimated value may be corrected by the lateral acceleration and the longitudinal vehicle speed, as shown below.
Is composed of
Can obtain the product
Can be approximately considered as
The two methods were combined for estimation as shown in the following formula.
In general, the yaw rate is the easiest to estimate in the vehicle motion state parameters, and better observation effect can be achieved by fusing the information of the yaw rate sensor with the wheel speed.
As can be seen from the above description of the present invention, compared with the prior art, the present invention has the following advantages:
the fusion sensor module receives camera video and millimeter wave radar information to perform data fusion, and an integrated target screening algorithm accurately detects the state of a front vehicle and lane line information; the curve curvature estimation module is used for receiving the information of the fusion sensor module, estimating the curvature of the curve and sending an estimation result to the self-adaptive cruise controller module; the adaptive cruise controller module is used for calculating the torque required by the current vehicle running state of the vehicle according to the information of the fusion sensor module and the curve curvature estimation module and sending control information to the wire-controlled chassis; the drive-by-wire chassis driven in a distributed mode executes instruction information from the adaptive cruise controller module, controls the motion state of the vehicle and finally achieves the adaptive cruise function of a curve.
The scheme provides a new system and a control mode, integrates a sensor fusion module, a curve curvature estimation module, an adaptive cruise controller and a distributed drive-by-wire chassis, provides a self-adaptive cruise curve control method based on the system, has obvious advancement and innovation in the aspects of target identification accuracy and curve running safety, provides a new control method for loss and locking of a cruise target and vehicle body sideslip control in the curve process, effectively solves the defects of the traditional self-adaptive cruise system, and improves the driving safety.
The above description is only an embodiment of the present invention, but the design concept of the present invention is not limited thereto, and any insubstantial modifications of the present invention using this concept shall fall within the scope of infringing the present invention.
Claims (4)
1. A distributed driving electric motor coach adaptive cruise curve control method is characterized by comprising the following steps: the control method comprises the following specific steps:
step 1: locking a following target vehicle, starting an adaptive cruise function when the vehicle normally runs without faults, and locking a vehicle in front of a lane as the following target vehicle;
step 2: sensing the moving posture of the target, receiving the camera video and the millimeter wave radar information by the vehicle fusion sensor module to perform data fusion, integrating a target screening algorithm, and completing the detection of the state of the front vehicle and the lane line information;
and step 3: detecting a curve area: after a front vehicle starts to enter a curve, a vehicle fusion sensor module detects deviation angle theta information, and a vehicle millimeter wave radar automatically compensates a dynamic detection area ROI;
and 4, step 4: estimation of the curvature of the curve: the vehicle curve curvature estimation module receives the information of the fusion sensor module, estimates the curvature of the curve, the reciprocal of the curvature of the curve is the radius of the curvature of the curve, and then sends the estimation result to the vehicle adaptive cruise control module;
and 5: estimation of yaw rate: the vehicle self-adaptive cruise controller module receives information of the fusion sensor module and the curve curvature radius estimation module, and estimates a value of a yaw velocity according to the vehicle speed and the acceleration of the vehicle;
step 6: judging the control right of the vehicle: the vehicle self-adaptive cruise controller module compares the estimated yaw velocity with a set threshold value, and exits from the self-adaptive cruise function when the value of the yaw velocity is larger than the threshold value, and the vehicle control right is given to the driver for control; when the value of the yaw rate is not greater than the threshold value, calculating the torque required by the current vehicle running state, and sending control information to the vehicle drive-by-wire chassis;
and 7: controlling the adaptive cruise of a curve of a vehicle: the vehicle drive-by-wire chassis executes the instruction information sent by the vehicle adaptive cruise controller module, controls the motion state of the vehicle and completes the adaptive cruise of the curve.
2. The adaptive cruise curve control method for the distributed-drive electric motor coach as claimed in claim 1, wherein: the preceding vehicle state in the step 2 comprises: and detecting and judging the relative distance, the relative speed and the deviation angle of the front vehicle and the vehicle.
3. The adaptive cruise curve control method for the distributed-drive electric motor coach as claimed in claim 1, wherein: the lane line information in the step 2 includes detecting and judging whether the front vehicle is on a lane.
4. The adaptive cruise curve control method for the distributed-drive electric motor coach as claimed in claim 1, wherein: the drive-by-wire chassis of the step 7 is a distributed drive-by-wire chassis.
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