CN115402331A - Steep descent method based on dynamic ramp estimation - Google Patents
Steep descent method based on dynamic ramp estimation Download PDFInfo
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- CN115402331A CN115402331A CN202211206408.5A CN202211206408A CN115402331A CN 115402331 A CN115402331 A CN 115402331A CN 202211206408 A CN202211206408 A CN 202211206408A CN 115402331 A CN115402331 A CN 115402331A
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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
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
- B60W40/06—Road conditions
- B60W40/076—Slope angle of the road
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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
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
- B60W40/107—Longitudinal acceleration
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/72—Electric energy management in electromobility
Abstract
The invention provides a steep descent method based on dynamic slope estimation, belonging to the technical field of electric vehicle control.
Description
Technical Field
The invention belongs to the technical field of electric vehicle control, and particularly relates to a steep descent method based on dynamic ramp estimation.
Background
For the vehicle running, the real-time dynamic road surface gradient parameters are obtained, and the functions of ramp assistance, constant-speed cruising, automatic parking, steep-slope descent and the like can be better realized. The traditional road surface ramp parameters are usually obtained by measuring through a ramp sensor, the measuring mode is relatively accurate when a vehicle runs stably, but detection errors are easy to generate when the vehicle runs in a shaking mode or an acceleration and deceleration mode, and meanwhile the cost of the whole vehicle is increased. The steep descent function is beneficial to stable operation of the vehicle when the vehicle descends the steep slope, can avoid the phenomenon of high-speed out-of-control of the vehicle, and can improve the safety of the vehicle, and the function is based on accurate slope judgment.
In addition, because the road surface is often not an ideal flat road condition, the real-time gradient parameter is inevitably changed in real time, and the parameter cannot be directly used for realizing the function. The existing method provides a method for realizing steep descent by adjusting output torque through an acceleration range and an accelerator pedal opening degree, and the control method does not take control of the speed of a downhill as a control target and tends to cause unstable speed of the steep descent.
Disclosure of Invention
Aiming at the defects in the prior art, the steep descent control method based on dynamic slope estimation provided by the invention solves the problems of inaccurate slope estimation and inflexible speed adjustment of the steep descent control under the condition of no slope sensor.
In order to achieve the above purpose, the invention adopts the technical scheme that:
the scheme provides a steep descent method based on dynamic ramp estimation, which comprises the following steps:
s1, carrying out polynomial fitting on the vehicle speed within preset time through a least square method;
s2, carrying out differential processing on the polynomial fitting result, and substituting the differential processing into the current moment vehicle speed to obtain the acceleration of the current moment;
s3, obtaining a ramp parameter at the current moment by utilizing a mechanical principle according to the acceleration at the current moment;
s4, filtering ramp parameters within preset time;
s5, judging whether the fluctuation of the ramp parameter after filtering is less than or equal to 10%, if so, calculating to obtain a mean value of the gradient, and entering a step S6, otherwise, returning to the step S4;
s6, judging whether the gradient mean value is larger than or equal to a preset steep slope slow descending threshold value, if so, meeting a steep slope slow descending condition, and entering the step S7, otherwise, returning to the step S5;
and S7, looking up a table by using the gradient mean value, and obtaining the corresponding steep descent speed according to the table, thereby finishing the steep descent based on the dynamic slope estimation.
Further, the expression of the acceleration at the present time is as follows:
a(x)＝a n nx n-1 +a n-1 (n-1)x n-2 +,…,+a 1
wherein a (x) represents the acceleration at the current time, a n ,a n-1 (n-1),…,a 1 ,a 0 Representing the coefficients of a polynomial fitted to the differential, x n-1 ,x n-2 A vector, x represents the argument of the fitted differentiated polynomial.
Still further, the expression of the ramp parameter is as follows:
where θ represents a ramp parameter, T m Representing the real-time torque of the motor, f representing the vehicle sliding resistance, mu representing the vehicle speed reduction ratio, eta representing the transmission system efficiency, R representing the vehicle tire radius, m representing the weight of the vehicle when empty, a representing the vehicle real-time acceleration, and g representing the gravitational acceleration.
The invention has the beneficial effects that:
(1) The invention solves the acceleration and the gradient through vehicle speed filtering and gradient filtering, effectively inhibits the noise generated by difference, filters the estimated gradient, takes the stable value of the ramp after filtering for a period of time as the input of the steep descent, establishes a two-dimensional table of the steep descent vehicle speed and the gradient, achieves the aim of dynamically adjusting the vehicle speed of the descent aiming at different gradients, and improves the accuracy of gradient estimation.
(2) The invention takes the range of slope fluctuation for a period of time as the condition for entering the steep descent, thereby effectively avoiding the driving discomfort caused by repeated entering and exiting of the steep descent mode caused by bumpy roads or accidental uneven roads.
(3) The invention establishes a steep descent speed-gradient two-dimensional table, can dynamically adjust the speed according to the real-time gradient, avoids the inflexibility of constant speed in steep descent and improves the driving comfort.
(4) According to the invention, the acceleration and gradient parameters are solved through vehicle speed filtering and gradient filtering, so that the noise generated by difference is effectively inhibited, and the accuracy of gradient estimation is improved.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Fig. 2 is a graph showing a sliding resistance in the present embodiment.
Detailed Description
The following description of the embodiments of the present invention is provided to facilitate the understanding of the present invention by those skilled in the art, but it should be understood that the present invention is not limited to the scope of the embodiments, and it will be apparent to those skilled in the art that various changes may be made without departing from the spirit and scope of the invention as defined and defined in the appended claims, and all matters produced by the invention using the inventive concept are protected.
Examples
As shown in fig. 1, the present invention provides a steep descent method based on dynamic slope estimation, which is implemented as follows:
s1, carrying out polynomial fitting on the vehicle speed within preset time through a least square method;
s2, carrying out differential processing on a polynomial fitting result, and substituting the current time vehicle speed to obtain the acceleration of the current time;
in this embodiment, the real-time acceleration is calculated first, and by performing least square polynomial fitting on the vehicle speed over a period of time, if a period of time is set to be n times before the current time, the vehicle speed values at the n times are subjected to least square fitting, where the fitting formula is as follows:
v(x)＝a n x n +a n-1 x n-1 +,…,+a 1 x+a 0
the acceleration can be obtained by deriving the above equation as follows:
a(x)＝a n nx n-1 +a n-1 (n-1)x n-2 +,…,+a 1
wherein v (x) represents a vehicle speed value, a (x) represents an acceleration at the present time, and a n ,a n-1 (n-1),…,a 1 ,a 0 Representing the coefficients of a polynomial fitted to the differential, x n-1 ,x n-2 A.
S3, obtaining a ramp parameter at the current moment by utilizing a mechanical principle according to the acceleration at the current moment;
in this embodiment, according to the mechanical equation, if the vehicle is on a slope, the gradient is θ, the real-time torque of the motor is Tm, the reduction ratio is μ, the transmission system efficiency is η, the tire radius is R, the sliding resistance is f (obtained through a sliding test), the set mass m, the gravitational acceleration is g, and the real-time acceleration is a, the formula for estimating the real-time slope parameters is as follows:
where θ represents a ramp parameter, T m Representing the real-time torque of the motor, f representing the vehicle sliding resistance, mu representing the vehicle speed reduction ratio, eta representing the transmission system efficiency, R representing the vehicle tire radius, m representing the weight of the vehicle when empty, a representing the vehicle real-time acceleration, and g representing the gravitational acceleration.
S4, filtering ramp parameters within preset time;
in this embodiment, the least square or other filtering algorithm may be used for filtering the gradient parameter θ for a period of time, which is not suitable for too long, and is generally controlled within 1 second to ensure the real-time performance of the parameter.
S5, judging whether the fluctuation of the ramp parameters after filtering is less than or equal to 10%, if so, calculating to obtain a mean value of the gradient, and entering the step S6, otherwise, returning to the step S4;
in this embodiment, if the fluctuation of the slope parameter is less than ± 10% within a period of time (generally, 3 to 5 seconds are taken), the average value of the slope is obtained.
S6, judging whether the gradient mean value is larger than or equal to a preset steep slope slow descending threshold value, if so, meeting a steep slope slow descending condition, and entering the step S7, otherwise, returning to the step S5;
and S7, looking up a table by using the gradient mean value, obtaining the corresponding steep slope slow descent speed according to the table, and finishing the steep slope slow descent based on the dynamic slope estimation.
In this embodiment, it is determined whether the gradient mean value is greater than or equal to a set steep gradient descent threshold, and if the steep gradient descent condition is satisfied, the corresponding steep gradient descent speed is obtained by looking up a table with the gradient value according to the table.
The present invention is further described below.
The final reduction ratio of a certain electric vehicle model is 9.98, the efficiency of a transmission system is 95%, the dynamic rolling radius of a tire is 277mm, the preparation mass is 975kg, the sliding resistance curve is shown in figure 2, in the figure, y represents sliding resistance, x represents sliding vehicle speed, and R represents fitting mean square error.
The two-dimensional table of vehicle speed and steep descent grade is shown in table 1:
TABLE 1
| Slope of |
10％ | 15％ | 20％ | 25％ | 30％ | >30％ |
| |
30 | 20 | 15 | 10 | 8 | 8 |
Assuming that the vehicle speed is 30km/h at a certain moment and the motor driving torque is-26.9 Nm, the steep descent method comprises the following steps:
firstly, calculating real-time acceleration, wherein the sampling period of the vehicle speed is 10mS, sampling 7 points, and performing least square fitting by adopting a second-order polynomial, wherein the fitting formula is as follows:
v(x)＝-38.02x 2 +9.53x+58.79
the acceleration can be obtained by deriving the above equation as follows:
a(x)＝-38.02x+9.53
the acceleration at the moment is 5.728km/h 2 。
The formula for calculating the gradient parameter is as follows:
the slope data is adopted at an interval of 100mS, the slope parameter theta is filtered, 5 points are sampled, 2-order filtering is still adopted, and the filtering result is 14.62%. The slope stability judging threshold is set to be 3S, the maximum value of the slope in 3S is 14.8%, the minimum value is 14.2%, the slope fluctuation is less than +/-10%, and the average slope value is 14.5%. Because the slopes are 14.5% or more than 10%, the target vehicle speed for calculating the steep slope slow-falling control is 19km/h as a table look-up input value and a linear interpolation mode is adopted by the intermediate numerical value of the table look-up through the table look-up.
Claims (3)
1. A steep descent method based on dynamic ramp estimation is characterized by comprising the following steps:
s1, performing polynomial fitting on the vehicle speed within preset time by a least square method;
s2, carrying out differential processing on the polynomial fitting result, and substituting the differential processing into the current moment vehicle speed to obtain the acceleration of the current moment;
s3, obtaining a ramp parameter at the current moment by utilizing a mechanical principle according to the acceleration at the current moment;
s4, filtering ramp parameters within preset time;
s5, judging whether the fluctuation of the ramp parameters after filtering is less than or equal to 10%, if so, calculating to obtain a mean value of the gradient, and entering the step S6, otherwise, returning to the step S4;
s6, judging whether the gradient mean value is larger than or equal to a preset steep slope slow-falling threshold value, if so, meeting the steep slope slow-falling condition, and entering the step S7, otherwise, returning to the step S5;
and S7, looking up a table by using the gradient mean value, and obtaining the corresponding steep descent speed according to the table, thereby finishing the steep descent based on the dynamic slope estimation.
2. A steep descent method according to claim 1 and wherein the acceleration at the current time is expressed as follows:
a(x)＝a n nx n-1 +a n-1 (n-1)x n-2 +,…,+a 1
wherein a (x) represents the acceleration at the current time, a n ,a n-1 (n-1),…,a 1 ,a 0 Representing the coefficients of a polynomial fitted to the differential, x n-1 ,x n-2 A.
3. A method of steep descent based on dynamic ramp estimation according to claim 2, wherein the ramp parameters are expressed as follows:
where θ represents a ramp parameter, T m The real-time torque of the motor is shown, f is vehicle sliding resistance, mu is vehicle speed reduction ratio, eta is transmission efficiency, R is vehicle tire radius, m is vehicle weight when the vehicle is unloaded, a is vehicle real-time acceleration, and g is gravity acceleration.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116596185A (en) * | 2023-05-12 | 2023-08-15 | 北京建筑大学 | Ecological driving quantitative evaluation and track optimization method based on VSP distribution |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116596185A (en) * | 2023-05-12 | 2023-08-15 | 北京建筑大学 | Ecological driving quantitative evaluation and track optimization method based on VSP distribution |
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