CN110001657B - Vehicle safety control method based on tire state information and vehicle - Google Patents
Vehicle safety control method based on tire state information and vehicle Download PDFInfo
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- CN110001657B CN110001657B CN201910315787.3A CN201910315787A CN110001657B CN 110001657 B CN110001657 B CN 110001657B CN 201910315787 A CN201910315787 A CN 201910315787A CN 110001657 B CN110001657 B CN 110001657B
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Abstract
The invention discloses a vehicle safety control method based on tire state information and a vehicle, wherein the method comprises the following steps: determining a reference straight line according to an adhesion slip curve and a slip slope between the adhesion coefficient and the slip rate of the tire under different road conditions; calculating an attachment coefficient according to the current slip slope and the tire state information of the tire, and taking the attachment coefficient and the slip slope as coordinates of a data point; selecting a predetermined number of reference points on the reference straight line, and calculating the similarity between each reference point and the data point; and calculating the maximum attachment coefficient corresponding to the data point according to the similarity between each reference point and the data point, and controlling the vehicle by taking the maximum attachment coefficient as a control parameter. According to the technical scheme, the maximum adhesion coefficient of each tire in the vehicle is accurately calculated in real time, so that the maximum effective braking force or effective driving force is obtained, the driving safety of the vehicle is improved, and the energy consumption of the vehicle is reduced.
Description
Technical Field
The invention relates to the technical field of vehicle safety, in particular to a vehicle safety control method based on tire state information and a vehicle.
Background
In the existing field of vehicle active safety, various parameter information during the vehicle running process is mainly acquired through an empirical value estimation method or through various sensors (for example, the driving direction of a driver is identified through a steering wheel angle sensor and various wheel rotation speed sensors, the actual moving direction of the vehicle is identified through a yaw angle sensor and a rotation angle of the vehicle around the direction vertical to the ground axis, a lateral acceleration sensor and the like), then parameters such as a slip rate, an adhesion coefficient and the like are calculated through the acquired various complex parameter information, and the vehicle is selectively braked or driven through the calculated parameters, so that the vehicle running stability is improved.
However, by adopting the sensor and the method for observing the adhesion coefficient by using the fuzzy neural network or the sliding mode variable structure and the like, as the condition of a vehicle running road is extremely complex, and various sensors are constantly in dynamic change, not only are large background noise and various interferences existed, but also variable parameters such as wind resistance and the like can not be obtained in real time when the load in the vertical direction of the tire (such as the gravity center of the vehicle moves forwards during braking and the gravity center deviation is large compared with the static state) and the wind resistance and the like during the running process of the vehicle can not be obtained in real time, and the obtained parameters such as the slip ratio, the adhesion coefficient and the like have large errors and are complex; by using the "optimal slip ratio" empirical value estimation method, the utilization rate of the adhesion coefficient of the vehicle cannot be always in an optimal state, and the vehicle can be locked (in a braking condition) or slipped (in a driving condition) and even cause the vehicle to be unstable. Meanwhile, when the performance of the sensor changes or fails, the sensor is difficult to find and detect in time, and serious potential safety hazards are undoubtedly brought to the driving process of the vehicle.
Disclosure of Invention
In view of the above problems, the present invention provides a vehicle safety control method based on tire condition information and a vehicle, so as to solve the disadvantages of the prior art.
According to an embodiment of the present invention, there is provided a vehicle safety control method based on tire condition information, including:
determining a reference straight line according to an adhesion slip curve and a slip slope between the adhesion coefficient and the slip rate of the tire under different road conditions;
calculating an adhesion coefficient according to the current slip rate and tire state information of the tire, and taking the adhesion coefficient and the slip rate as coordinates of data points;
selecting a predetermined number of reference points on the reference straight line, and calculating the similarity between each reference point and the data point;
and calculating the maximum attachment coefficient corresponding to the data point according to the similarity between each reference point and the data point, and controlling the vehicle by taking the maximum attachment coefficient as a control parameter.
In the above method for controlling vehicle safety based on tire condition information, the determining a reference line according to an adhesion slip curve and a slip slope between an adhesion coefficient and a slip ratio of a tire under different road conditions includes:
determining a slip slope according to the slip rate;
and when the slip slope meets a preset condition, determining the reference straight line according to the curve of the overlapped part of the adhesion slip curves of different road conditions.
In the above-described vehicle safety control method based on tire state information, both end points of the reference straight line are determined simultaneously with the determination of the reference straight line, and the method further includes:
and determining a longitudinal safety interval of the adhesion coefficient according to the coordinates of the two end points of the reference straight line, dividing the longitudinal safety interval into different risk levels according to the safety degree of the vehicle, and prompting a user at each risk level or correspondingly controlling the vehicle according to the maximum adhesion coefficient.
In the above-described vehicle safety control method based on the tire condition information, the tire condition information is acquired by:
acquiring an original wheel speed pulse signal of each tire in the vehicle;
revising or reconstructing the original wheel speed pulse signal through a preset rule to obtain wheel speed pulse data;
and determining the tire state information corresponding to the wheel speed pulse data according to a pre-learned corresponding relation.
In the above-described vehicle safety control method based on the tire condition information, the tire condition information includes load information;
the step of calculating the adhesion coefficient according to the current slip ratio and the tire state information of the tire comprises the following steps:
calculating the slip rate from the wheel speed pulse data;
and calculating the adhesion coefficient according to the slip rate and the load information.
In the above-described vehicle safety control method based on the tire-state information, the control parameter further includes an intention deviation between an actual running trajectory and a desired trajectory of the vehicle, the intention deviation being determined by:
calculating a difference between the raw wheel speed pulse signal and the wheel speed pulse data over a predetermined monitoring period, the difference being taken as the intended bias.
In the above-described vehicle safety control method based on the tire-state information, the control parameter further includes a degree of center of gravity deviation of the vehicle, the degree of center of gravity deviation being determined by:
measuring the track width of a tire in a vehicle;
calculating the barycentric coordinate of the vehicle according to the load information and the wheel track;
and determining the gravity center deviation degree of the vehicle according to the gravity center coordinates and a preset safety threshold value.
In the above-described vehicle safety control method based on the tire state information, controlling the vehicle by the control parameter includes:
judging whether the control parameter at the current moment exceeds a preset safety range;
if the control parameter exceeds the preset safety range, adjusting the driving state and the change trend of the vehicle according to the control parameter at the current moment, and recalculating the control parameter after adjustment of the vehicle, wherein the adjustment comprises adjusting the actual driving track of the vehicle according to the intention deviation and/or adjusting the barycentric coordinate of the vehicle according to the barycentric deviation degree and/or adjusting the braking force or the driving force of the vehicle according to the maximum adhesion coefficient;
and if the adjusted control parameter still exceeds the preset safety range, continuously adjusting the driving state and the variation trend of the vehicle at the next moment according to the adjusted control parameter, and repeatedly executing the steps until the control parameter after the last adjustment does not exceed the preset safety range.
In the above-described vehicle safety control method based on the tire state information, when the vehicle is controlled by the control parameter or the vehicle is controlled to decelerate in accordance with the accelerator pedal depression, an energy recovery device is involved, and energy is recovered by the energy recovery device.
A second embodiment of the present invention provides a vehicle safety control device based on tire condition information, including:
the reference straight line determining module is used for determining a reference straight line according to an adhesion slip curve and a slip slope between the adhesion coefficient and the slip rate of the tire under different road conditions;
the adhesion coefficient calculation module is used for calculating an adhesion coefficient according to the current slip rate and the tire state information of the tire, and taking the adhesion coefficient and the slip rate as coordinates of data points;
the similarity calculation module is used for selecting a preset number of reference points on the reference straight line and calculating the similarity between each reference point and the data point;
and the maximum adhesion coefficient calculation module is used for calculating the maximum adhesion coefficient corresponding to the data point according to the similarity between each reference point and the data point so as to control the vehicle by taking the maximum adhesion coefficient as a control parameter.
A third embodiment of the invention provides a vehicle including a memory for storing a computer program and a processor for executing the computer program to cause the vehicle to execute the above-described vehicle safety control method based on tire state information.
A fourth embodiment of the present invention provides a computer-readable storage medium storing the computer program used in the vehicle described above.
The invention discloses a vehicle safety control method based on tire state information and a vehicle, which at least provide the following technical effects: the current slip slope and the adhesion coefficient are used as coordinates of data points, the coordinates of the data points are fitted with reference points on a determined reference straight line, if the data points and the reference points can be fitted into a straight line, and the fitting degree meets a fitting threshold value, the maximum adhesion coefficient can be calculated according to the similarity between the fitted data points and the reference points, the maximum adhesion coefficient of each tire in the vehicle running process is calculated in real time and accurately, the maximum effective braking force or effective driving force of each tire is obtained according to the maximum adhesion coefficient, the running state of the corresponding tire of the vehicle is controlled accurately in real time according to the effective braking force or the effective driving force, the running safety of the vehicle is greatly improved, the time complexity and the space complexity of an algorithm used in the calculating process are small, and the algorithm execution efficiency is improved; when the running state of the vehicle is accurately controlled in real time through the effective braking force or the effective driving force, the vehicle runs in an efficient state, the energy consumption of the vehicle is reduced during braking or driving, and the energy-saving effect is achieved; braking or driving torque under various driving conditions (such as uphill slope, downhill slope, automatic parking, anti-locking and the like) can be estimated through the maximum adhesion coefficient, and accurate monitoring and control of the vehicle can be further realized under different driving conditions.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings required to be used in the embodiments will be briefly described below, and it should be understood that the following drawings only illustrate some embodiments of the present invention, and therefore should not be considered as limiting the scope of the present invention.
Fig. 1 is a schematic flow chart illustrating a vehicle safety control method based on tire condition information according to a first embodiment of the present invention.
Fig. 2 is a schematic diagram illustrating an adhesion slip curve under different road conditions according to a first embodiment of the present invention.
Fig. 3 shows a schematic diagram of a normalized stick-slip curve provided by the first embodiment of the present invention.
Fig. 4 is a diagram illustrating wheel speed pulse data according to a first embodiment of the present invention.
Fig. 5 is a diagram illustrating a truncation error of wheel speed pulse data according to a first embodiment of the present invention.
Fig. 6 is a flowchart illustrating a vehicle safety control method based on tire condition information according to a second embodiment of the present invention.
Fig. 7 is a flowchart illustrating a vehicle safety control method based on tire condition information according to a third embodiment of the present invention.
Fig. 8 is a flowchart illustrating a vehicle control method according to a third embodiment of the present invention.
Fig. 9 is a flowchart illustrating a vehicle safety control method based on tire condition information according to a fourth embodiment of the present invention.
Fig. 10 is a schematic structural diagram illustrating a vehicle safety control device based on tire condition information according to a fifth embodiment of the present invention.
Description of the main element symbols:
600-vehicle safety control device based on tire condition information; 610-reference line determination module; 620-attachment coefficient calculation module; 630-similarity calculation module; 640-maximum attachment coefficient calculation module.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein in the description of the multi-scale calibration plate is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
The following detailed description of embodiments of the invention refers to the accompanying drawings.
Example 1
Fig. 1 is a schematic flow chart illustrating a vehicle safety control method based on tire condition information according to a first embodiment of the present invention. The vehicle safety control method based on the tire condition information includes:
and step S110, determining a reference straight line according to an adhesion slip curve and a slip slope between the adhesion coefficient and the slip rate of the tire under different road conditions.
Specifically, the adhesion coefficient and the slip ratio of the vehicle under different road conditions can be collected, and the adhesion coefficient and the slip ratio of each road condition are fitted into an adhesion slip curve. Because the adhesion coefficients and the slip rates of different road conditions are different, the adhesion slip curves obtained by fitting different road conditions are different.
Fig. 2 shows an adhesion slip curve of a tire under different road conditions, where Φ is an adhesion coefficient and S is a slip ratio.
Further, the "determining a reference straight line according to an adhesion slip curve and a slip slope between the adhesion coefficient and the slip ratio of the tire under different road conditions" includes:
determining a slip slope according to the slip rate; and when the slip slope meets a preset condition, determining the reference straight line according to the curve of the overlapped part of the adhesion slip curves of different road conditions.
Specifically, the slip slope K is calculated from the slip ratio in the following manner:
s is 1/K + E, where E is the horizontal intercept.
When the slip ratio S is small to a certain degree, the slip slopes K corresponding to different slip ratios S are difficult to distinguish, all the adhesion slip curves are superposed together and completely accord with the trend theory between the adhesion coefficient and the slip ratio, and therefore the concepts of the normalized adhesion coefficient and the normalized slip ratio are introduced.
Wherein, phi 1 is normalized adhesion coefficient, phimaxFor maximum sticking coefficient, S1 is normalized slip ratio, CKFor the tire longitudinal stiffness, N is the tire vertical load.
After introducing the normalized adhesion coefficient and the normalized slip ratio, all the superposed adhesion slip curves can be normalized to obtain a normalized adhesion slip curve, which is shown in fig. 3 as a normalized adhesion slip curve, and it is obvious that the normalized adhesion slip curve is also the curve where the maximum adhesion coefficient is located.
The part of the straight line passing through the origin on the normalized adhesion slip curve is determined as a reference straight line, and all points between the point L1 and the point L2 on the normalized adhesion slip curve as in fig. 3 are on the straight line L, so that the straight line L can be taken as the reference straight line.
Step S120, calculating an adhesion coefficient according to the current slip rate and the tire state information of the tire, and taking the adhesion coefficient and the slip slope as coordinates of a data point.
Specifically, the slip ratio of a tire is a proportion of slip components of a wheel in the total movement by definition of the slip ratio, which can be calculated from wheel speed pulse data most reflecting the driving intention:
S＝(v-ωR)/v＝(Wx-Wy)/Wx
where v is the tire longitudinal velocity, ω is the tire angular velocity, WxFor the wheel speed pulse data of the tire, WyTo filter out wheel speed pulse data for slip components.
And determining the corresponding relation between the slip ratio and the adhesion coefficient, and further obtaining the adhesion coefficient based on the slip ratio obtained by the calculation and the determined corresponding relation between the slip ratio and the adhesion coefficient.
The correspondence between slip ratio and adhesion coefficient can be determined by:
the stick-slip curve may be determined based on tire state of motion information and vehicle dynamics equations. The tire motion state information comprises information such as load, tire pressure, longitudinal rigidity and the like.
For example, if Φ is the adhesion coefficient and S is the slip ratio, Φ is F/N. According to the vehicle dynamics equation Mμ+FR+M γ0 can be deduced:
wherein F is the ground braking force, N is the load of the tire in the vertical direction, MμFor brake moment of brake, MγIs the moment of inertia of the tire, and J is the moment of inertia of the tire, typically 0.8-1.0Kgm2，
For angular deceleration, PcFor brake pressure, KcIs the braking torque coefficient, R is the rolling radius of the tire, CkIn order to obtain the longitudinal stiffness of the tire, which is linearly related to the load N in the vertical direction of the tire, the longitudinal stiffness is significantly affected by the load N in the vertical direction of the tire, so that the longitudinal stiffness of the tire needs to be calibrated in advance according to the magnitude of the load N in the vertical direction of the tire, in this embodiment, Ck＝N/R。
Since there is a linear relationship between the ground braking force and the slip ratio, the correspondence between the adhesion coefficient and the slip ratio can also be simplified as:
Φ＝F/N＝CkS/N
therefore, the adhesion coefficient is obtained by substituting the slip ratio obtained above into the above equation.
And taking the point at the current moment as a data point, and taking the slip rate and the attachment coefficient at the current moment as coordinate values of the data point to participate in subsequent operation.
Further, the tire condition information is acquired by:
acquiring an original wheel speed pulse signal of each tire in the vehicle; revising or reconstructing the original wheel speed pulse signal through a preset rule to obtain wheel speed pulse data; and determining the tire state information corresponding to the wheel speed pulse data according to a pre-learned corresponding relation.
Specifically, an original wheel speed pulse signal of each tire in the vehicle is obtained, in a certain monitoring period, the tire with the minimum number of the original wheel speed pulse signals (with the maximum wheel radius) is selected as a standard wheel, the motion state of other tires of the standard wheel is used as a reference, and the original wheel speed pulse signals of the standard wheel are revised or reconstructed through a preset rule to obtain wheel speed pulse data. In the present embodiment, the wheel speed pulse data may include two forms, the first being wheel speed pulse data representing driving intention (the wheel speed pulse data representing driving intention is mainly used as an intention deviation calculating portion described below); the second type is wheel speed pulse data in a straight running state, and hereinafter, corresponding tire state information is mainly determined according to the wheel speed pulse data in the straight running state.
Fig. 4 shows the original wheel speed pulse signal. Although the original wheel speed pulse signal has been filtered out of high frequency components, the original wheel speed pulse signal also includes several other errors, such as correction errors of the original wheel speed pulse signal at different angles due to deviation of the central angle of the steering wheel, truncation errors caused when the original wheel speed pulse signal is collected, errors caused by magnetic declination of a magnetic gap of the wheel speed sensor and radius errors caused by resonance phenomenon of the tire, and errors caused by slip correction of the tire according to the motion characteristics of the vehicle. Therefore, the original wheel speed pulse signal needs to be revised or reconstructed according to a preset rule.
The preset rule comprises corresponding revising according to the actual central angle of the steering wheel and the tire slippage, and interference is eliminated or errors are reduced through one or more of algorithms such as a multiple period method, a frequency spectrum analysis method, a least square method, Kalman filtering and recursive averaging.
For example, when dealing with an error caused by an actual center angle deviation of a steering wheel, the steering wheel center angle read by a CAN bus of an automobile and the actual steering wheel center angle are always inconsistent due to assembly or mechanical wear, and therefore the steering wheel angle read by the CAN bus needs to be calibrated in the following manner:
since the vehicle is in a straight-line driving state for most of the time, the read steering wheel angles are in gaussian distribution, and therefore the steering wheel angles can be respectively accumulated according to all the read steering wheel angles in gaussian distribution, and when a normal test condition is met, a final actual center angle of the steering wheel can be determined, for example, a value at a peak value is taken as the final actual center angle of the steering wheel.
And determining the correction quantity or relative correction quantity of the wheel speed pulse data of each tire in the monitoring period corresponding to the actual central angle of the steering wheel according to the corresponding relation between the steering wheel angle and each tire pulse data calibrated in advance, and determining the actual wheel speed pulse data corresponding to the steering wheel angle.
For another example, when the tire slip is revised accordingly, the tire rolling radius model may be determined according to the tire mechanics model and its motion characteristics (three most important factors affecting the tire rolling radius change, air pressure, load (tire vertical direction) and speed): under the fixed load, the relationship between the air pressure and the sinking amount and the relationship between the load and the sinking amount under the fixed air pressure are approximate to a linear change relationship which can be expressed by a polynomial; under the condition of constant load and constant air pressure, the rolling radius of the tyre and the vehicle speed are approximately in linear change relationship. For a car, because the change of the load is limited, the rolling radius of the tire basically does not change (can be ignored) along with the change of the load, when the tire pressure is higher, the influence of the speed on the rolling radius of the tire is smaller, and the influence of the air pressure on the rolling radius of the tire is smaller when the vehicle speed is lower.
The concrete slip correction method can be determined in a pre-calibration mode. For example, taking a hawkok tire of a Sonata bridge car as an example, the linear fitting relation between the rolling radius R of the tire of the driving wheel and the vehicle speed V is as follows: and R is 0.0317V +297.06, and the linear fitting equation of the rolling radius of the driven wheel tire and the vehicle speed is as follows: r is 0.0347V + 296.68. Because the equivalent incidence relation exists between the vehicle speed, the radius and the calibrated tire pulse data, the calibrated tire pulse data can be used for carrying out corresponding tire slip correction on the original wheel speed pulse signal for the convenience of subsequent calculation.
Meanwhile, because the rolling radius of the tire or the variation of the pulse data in the same monitoring period is very small, and it is difficult to directly measure the small variation in the running process of the automobile, based on a certain monitoring period, the wheel speed pulse data of other tires can be packed by using a standard wheel (with the minimum pulse number) to generate an accumulated difference effect (the variation of the original wheel speed pulse signal generated by the rotation of the wheel is used to indirectly reflect the variation of the rolling radius and the variation of the state of the automobile body). And accumulating and packaging the corrected or reconstructed wheel speed pulse data of the tire in the monitoring period into a data packet respectively, calculating a wheel speed pulse data packet showing driving intention and a wheel speed pulse data packet in a straight driving state respectively, and accumulating and packaging original wheel speed pulse signals which are not corrected or reconstructed into a data packet based on the monitoring period respectively, wherein the data packet is hereinafter referred to as an original pulse data packet. Obviously, the wheel speed pulse data packet representing the driving intention, the wheel speed pulse data packet in the straight-line driving state and the original pulse data packet have mapping relation and comparability in the data sequence or the corresponding monitoring period.
Further, for further improving the accuracy of data acquisition and reducing errors caused by tire resonance phenomena, the time domain of the original wheel speed pulse signal is subjected to Fourier transform to obtain a frequency domain of the original wheel speed pulse signal, and the frequency domain of the original wheel speed pulse signal is subjected to spectrum analysis to conveniently find or filter out abnormal point data.
For another example, since the truncation error is a phenomenon that "+ 1" "or" -1 "is easily generated in the obtained pulse data of different data packets when the original wheel speed pulse signal is acquired, as shown in fig. 5, in the input signal 1, 7 original wheel speed pulse signals are acquired within the monitoring period Δ t, and in the input signal 2, 6 original wheel speed pulse signals are acquired within the same monitoring period Δ t, which causes the truncation error in the acquisition of the original wheel speed pulse signals. In this embodiment, when processing the truncation error, the truncation error may be eliminated by a multiple period method (for example, a plurality of acquisition periods are set within the monitoring period Δ t shown in fig. 5 to acquire all the original wheel speed pulse signals within Δ t).
In order to further reduce or eliminate interference and errors in the preset rule, the preset rule may be implemented by using algorithm methods such as a least square method, kalman filtering, recursive averaging, and the like, which are not described herein. Meanwhile, during correction or reconstruction, the principle that adjacent original wheel speed pulse signals cannot change suddenly is considered, overrun correction is not carried out, and graded limit correction is only carried out on an overrun part in a limit range. For example, if the first original wheel speed pulse packet is compared to the fifth original wheel speed pulse packet, the fifth original wheel speed pulse packet cannot exceed the first original wheel speed pulse packet by more than 5 pulses, if 6 packets are reached, the fifth pulse packet can be corrected by 5 pulses, if 8 packets are reached, the fifth pulse packet can be corrected by 6 pulses, and if 10 packets are reached, the fifth pulse packet can be corrected by 7 pulses, so that in practice no larger fluctuations occur in the adjacent original wheel speed pulse signals.
And after wheel speed pulse data of a certain monitoring period are obtained, determining the tire state information corresponding to the wheel speed pulse data according to a corresponding relation learned in advance.
Specifically, the tire condition information includes a wear level, a tire pressure, a load, a temperature, and the like.
For a specific vehicle type, the method can be realized by a calibration mode: the method comprises the steps of collecting multiple groups of data of tires in a certain monitoring mileage unit in advance, wherein each group of data comprises wheel speed pulse data of a vehicle and tire state information. Under the given load, the air pressure is changed, under the given air pressure, the load is changed, and the corresponding pulse data is fitted after the vehicle full working condition range is learned, so that the corresponding relation between the wheel speed pulse data and the tire state information is obtained.
In this embodiment, the correspondence relationship between the wheel speed pulse data and the tire condition information may be described by a multidimensional lookup table as described below. In some other embodiments, the correspondence relationship between the wheel speed pulse data and the tire condition information may also be a functional expression.
The table above is a multidimensional search table corresponding to a wear level of 1. When the tire wear level is 1 grade, the wheel speed pulse data corresponding to the tire pressure of P1 and the load of T1 is K11; wheel speed pulse data corresponding to the tire pressure of P2 and the load of T1 is K12; wheel speed pulse data corresponding to the tire pressure of P3 and the load of T1 is K13; wheel speed pulse data corresponding to the tire pressure of P1 and the load of T2 is K21; wheel speed pulse data corresponding to the tire pressure of P2 and the load of T2 is K22; and so on.
The table above is a multi-dimensional search table corresponding to a tire wear rating of 2. When the tire wear level is 2 grade, the wheel speed pulse data corresponding to the tire pressure of P1 and the load of T1 is Q11; wheel speed pulse data corresponding to the tire pressure of P2 and the load of T1 is Q12; wheel speed pulse data corresponding to the tire pressure of P3 and the load of T1 is Q13; wheel speed pulse data corresponding to the tire pressure of P1 and the load of T2 is Q21; wheel speed pulse data corresponding to the tire pressure of P2 and the load of T2 is Q22; and so on.
It should be noted that all the above contents are common to the same vehicle type, and parameters such as wheel speed pulse data, steering wheel angle, load, etc. corresponding to different vehicle types are different. If the temperature of the tire is to be further obtained, it can be obtained by simple conversion according to the ambient temperature of the tire, the unsteady temperature characteristic of the tire, and the charles' law.
Step S130, selecting a predetermined number of reference points on the reference straight line, and calculating the similarity between each reference point and the data point.
Specifically, the predetermined number may be 2.
As shown in fig. 3, reference points H1 and H2 are selected on the reference straight line L, the adhesion coefficient and the slip ratio of the reference point H1 are respectively used as the coordinates of the reference point H1, the adhesion coefficient and the slip ratio of the reference point H2 are used as the coordinates of the reference point H2, and if the data point is H3, in this embodiment, the fuzzy similarity between H3 and H1, H2 is calculated by a fuzzy similarity algorithm, and the fuzzy similarity is used as the similarity between H3 and H1, H2.
In some other embodiments, the hamming distance between H3 and H1, H2 or the gray association between H3 and H1, H2 may also be used as the similarity.
And step S140, calculating the maximum attachment coefficient corresponding to the data point according to the similarity between the reference points and the data point, and controlling the vehicle by taking the maximum attachment coefficient as a control parameter.
Further, the maximum adhesion coefficient Φ may be calculated by the following formulamax：
Wherein phiH1Is the adhesion coefficient corresponding to the reference coordinate point H1, phiH2Is the adhesion coefficient, ω, corresponding to the reference coordinate point H2H1Is the fuzzy similarity, ω, between the data point H3 and the reference point H1H2Is the fuzzy similarity between the data point H3 and the reference point H2.
The maximum adhesion coefficients corresponding to the four tires can be calculated respectively in the above manner, and the tires corresponding to the vehicle are controlled respectively according to the maximum adhesion coefficients corresponding to the tires.
Specifically, the respectively controlling the corresponding tires of the vehicle according to the maximum adhesion coefficients corresponding to the tires comprises:
the driving state is changed by adjusting the braking force or the driving force of the vehicle according to the maximum adhesion coefficient corresponding to each tire, the adjusted real-time adhesion coefficient is recalculated, whether the adjusted real-time adhesion coefficient exceeds the maximum adhesion coefficient and/or whether the adjusted change trend is estimated to be safe is judged, the recalculated result after adjustment is used as the basis for the next adjustment, and the real-time adhesion coefficient or the change trend after the last adjustment meets the preset safety condition in a step-by-step approximation mode.
Example 2
Fig. 6 is a flowchart illustrating a vehicle safety control method based on tire condition information according to a second embodiment of the present invention. The vehicle safety control method based on the tire condition information includes the steps of:
step S210, determining a reference straight line according to an adhesion slip curve and a slip slope between the adhesion coefficient and the slip rate of the tire under different road conditions.
This step is the same as step S110, and is not described herein again.
Step S220, calculating an adhesion coefficient according to the current slip ratio of the tire and the tire state information, and taking the adhesion coefficient and the slip ratio as coordinates of a data point.
This step is the same as step S120, and is not described herein again.
In step S230, a predetermined number of reference points are selected from the reference straight line, and the similarity between each reference point and each data point is calculated.
This step is the same as step S130, and is not described herein again.
And step S240, calculating the maximum attachment coefficient corresponding to the data point according to the similarity between the reference points and the data point, and controlling the vehicle by taking the maximum attachment coefficient as a control parameter.
This step is the same as step S140, and is not described herein again.
And step S250, determining a longitudinal safety interval of the adhesion coefficient according to the coordinates of the two end points of the reference straight line, dividing the longitudinal safety interval into different risk levels according to the safety degree of the vehicle, and prompting a user at each risk level or correspondingly controlling the vehicle according to the maximum adhesion coefficient.
Specifically, as shown in fig. 3, while the reference straight line is determined, both end points L1 and L2 of the reference straight line are also determined. Wherein the end point L1 is the lower inflection point of the reference straight line in the normalized adhesion slip curve, and the end point L2 is the upper inflection point of the reference straight line in the normalized adhesion slip curve. For example, when a reference straight line is determined in the normalized adhesion slip curve, all points in the normalized adhesion slip curve are fitted, the point which is fitted to the reference straight line at the beginning is taken as the end point L1, and the point which is fitted to the reference straight line at the last is taken as the end point L2.
For example, depending on the braking distance of the motor vehicle versus the adhesion coefficient:
SF＝V2/256Φ
wherein S isFIs the braking distance and V is the vehicle speed.
If the vehicle is braked at a speed of 60 km/h on a road surface with an adhesion coefficient phi of 0.6 and a coefficient phi of 0.3, the difference of the braking distance is 23 m, which is enough to see the importance of the adhesion coefficient when driving or braking on a road.
Therefore, the zone formed by the two end points L1 and L2 is defined as a safety zone, and the safety zone is divided into different risk levels. As set forth in the following table:
| safety zone | Risk rating |
| L1～M1 | In general |
| M1～M2 | Danger of |
| M2～L2 | Severe severity of disease |
In the above table, in the interval L1 to M1, the corresponding risk level is general, and there is a space for an increase (the adhesion coefficient increases with an increase in the vehicle speed within a certain range); in the interval of M1-M2, the corresponding risk level is dangerous, which indicates that the danger is close to serious danger immediately, and can prompt the user to cause warning; in the interval M2-L2, the corresponding risk level is a serious danger, which means that emergency measures have to be taken, for example, the driving state of the vehicle can be controlled by the maximum adhesion coefficient. Wherein, M1 and M2 are real numbers which are larger than L1 and smaller than L2, and M1< M2.
Example 3
Fig. 7 is a flowchart illustrating a vehicle safety control method based on tire condition information according to a third embodiment of the present invention. The vehicle safety control method based on the tire condition information includes the steps of:
and 310, determining a reference straight line according to an adhesion slip curve and a slip slope between the adhesion coefficient and the slip rate of the tire under different road conditions.
This step is the same as step S110, and is not described herein again.
And step 320, calculating an adhesion coefficient according to the current slip ratio of the tire and the tire state information, and taking the adhesion coefficient and the slip ratio as coordinates of a data point.
This step is the same as step S120, and is not described herein again.
Step S330, selecting a predetermined number of reference points on the reference straight line, and calculating the similarity between each reference point and each data point.
This step is the same as step S130, and is not described herein again.
Step S340, calculating a maximum adhesion coefficient corresponding to the data point according to the similarity between each reference point and the data point, so as to control the vehicle by using the maximum adhesion coefficient as a control parameter.
This step is the same as step S140, and is not described herein again.
In step S350, a difference between the original wheel speed pulse signal and the wheel speed pulse data packet is calculated in a predetermined monitoring period, and the difference is used as an intention deviation.
To further increase the degree of active safety of the vehicle, the vehicle may also be controlled from multiple dimensions, such as, for example, precise monitoring and control of the vehicle in the lateral (deviation of the intended driving), vertical (deviation of the center of gravity of the vehicle) and longitudinal (maximum sticking coefficient) dimensions.
Specifically, in the process of calculating the intention deviation, the wheel speed pulse data is wheel speed pulse data representing driving intention, the wheel speed pulse data representing driving intention represents the intention of a driver because the wheel speed pulse data representing driving intention is data after errors and interference are eliminated, and the original wheel speed pulse signal represents the actual driving state of the vehicle because the original wheel speed pulse signal is actually acquired in the driving process of the vehicle. Therefore, the difference value between the original pulse data packet and the wheel speed pulse data packet representing the driving intention in the monitoring unit is calculated, and the intention deviation between the actual running track and the expected track of the vehicle can be obtained.
And step S360, measuring the wheel track of the vehicle tires, calculating the gravity center coordinate of the vehicle according to the load information and the wheel track, and determining the gravity center deviation degree of the vehicle according to the gravity center coordinate and a preset safety threshold value.
Specifically, according to the moment balance principle of four tires in a vehicle, the gravity center is obtained by adopting a method of taking the four tires as supporting force measuring points.
For example, let the four tires in the vehicle be A, B, C and D, respectively, in the clockwise direction. The four tires form a quadrilateral ABCD, and the geometric center coordinates of the vehicle are (0, 0, 0) assuming that the track width AB is a, BC is AD, and b, which is measured in advance in this embodiment.
Let the barycentric coordinates of the vehicle be (X, Y, Z) and the value of the load of tire A be FAThe value of the load of the tire B is FBThe value of the load of the tire C is FCWheel ofThe value of the load of the tire D is FDThe total weight of the vehicle is W ═ FA+FB+Fc+Fd。
The value of X in the barycentric coordinates is calculated by:
X×W＝AB/2×(FA+FD)-AB/2×(FB+FC)
＝[(FA+FD)-(FB+FC)]×a/2×(FA+FB+FC+FD)
the value of Y in the barycentric coordinates is calculated by:
Y×W＝AD/2×(FA+FB)-AD/2×(FC+FD)
＝[(FA+FB)-(FC+FD)]×b/2×(FA+FB+FC+FD)
if necessary, a level sensor may be used or added, such as a tilt sensor, to determine the Z coordinate by taking moments from the B wheels. The influence on the radius of the tire can also be determined according to the change of the load in the vertical direction of the tire, so that the change degree of the load change in the vertical direction of the tire to the gravity center change can be calculated.
The value of Z in the barycentric coordinates is also calculated by:
after the barycentric coordinates of the vehicle are obtained, the barycentric coordinates are compared with a preset barycentric threshold value, the difference value between the barycentric coordinates and the barycentric threshold value is calculated, and the barycentric deviation degree of the vehicle is determined.
It should be noted that the step of calculating the maximum adhesion coefficient, the step of calculating the intentional deviation, and the step of calculating the degree of deviation of the center of gravity may be performed simultaneously, or may be performed in any order, and are not limited herein.
In step S370, the vehicle is controlled using the maximum adhesion coefficient, the intended deviation, and the degree of center of gravity deviation as control parameters.
Further, as shown in fig. 8, the controlling the vehicle may include the steps of:
step S410, determining whether the control parameter at the current time exceeds a preset safety range.
Step S420, if the control parameter exceeds the preset safety range, adjusting the driving state and the variation trend of the vehicle according to the control parameter at the current time, and recalculating the control parameter after the adjustment of the vehicle.
Wherein the adjusting comprises adjusting an actual driving trajectory of the vehicle according to the intended deviation and/or adjusting a barycentric coordinate of the vehicle according to the degree of barycentric deviation and/or adjusting a braking or driving force of the vehicle according to the maximum attachment coefficient. The preset safety range comprises a longitudinal safety range and/or a transverse safety range and/or a vertical safety range.
The control parameters exceeding the preset safety range are as follows: if any one of the control parameters exceeds a preset safety range (for example, the condition 1 is that the intention deviation exceeds a transverse safety range, the condition 2 is that the gravity center deviation degree exceeds a vertical safety range, the condition 3 is that the maximum adhesion coefficient exceeds a longitudinal safety range, and if one of the condition 1, the condition 2 and the condition 3 is true), the control parameter exceeds the preset safety range; if all of the control parameters satisfy the preset safety range (e.g., all of the above conditions 1, 2, and 3 do not hold), the control parameter does not exceed the preset safety range.
Specifically, when any control parameter at the current time exceeds a preset safety range, the fact that the vehicle is in a driving risk is indicated, and at the current time, the actual driving track of the vehicle is adjusted according to the intention deviation, the gravity center coordinate of the vehicle is adjusted according to the gravity center deviation degree, the braking force or the driving force of the vehicle is adjusted according to the maximum adhesion coefficient of each tire, and the intention deviation, the gravity center deviation degree and the maximum adhesion coefficient of the vehicle after adjustment are calculated.
And step S430, if the adjusted control parameter still exceeds the preset safety range, continuing to adjust the driving state and the variation trend of the vehicle at the next moment according to the adjusted control parameter, and repeatedly executing the steps until the control parameter after the last adjustment does not exceed the preset safety range.
Specifically, whether the adjusted control parameter exceeds a preset safety range or not is continuously judged, if the adjusted control parameter still exceeds the preset safety range, the driving state of the vehicle and the change trend of the future time range are readjusted through any one control parameter (which may include an intention deviation, a gravity center deviation degree or a maximum attachment coefficient) exceeding the preset safety range according to the same manner, the last adjustment result is used as the basis of the next adjustment, and the driving state of the vehicle is adjusted for multiple times according to the step-by-step approaching closed-loop control manner until the intention deviation, the gravity center deviation degree and the maximum attachment coefficient of the vehicle after the last adjustment meet preset conditions.
Example 4
Fig. 9 is a flowchart illustrating a vehicle safety control method based on tire condition information according to a fourth embodiment of the present invention. The vehicle safety control method based on the tire condition information includes the steps of:
and step 510, determining a reference straight line according to an adhesion slip curve and a slip slope between the adhesion coefficient and the slip rate of the tire under different road conditions.
This step is the same as step S110, and is not described herein again.
Step 520, calculating an adhesion coefficient according to the current slip ratio of the tire and the tire state information, and using the adhesion coefficient and the slip ratio as coordinates of a data point.
This step is the same as step S120, and is not described herein again.
In step S530, a predetermined number of reference points are selected from the reference straight line, and the similarity between each reference point and the data point is calculated.
This step is the same as step S130, and is not described herein again.
And step S540, calculating the maximum attachment coefficient corresponding to the data point according to the similarity between the reference points and the data point, and controlling the vehicle by taking the maximum attachment coefficient as a control parameter.
This step is the same as step S140, and is not described herein again.
In step S550, a difference between the original wheel speed pulse signal and the wheel speed pulse data is calculated as an intention deviation in a predetermined monitoring period.
This step is the same as step S350, and is not described herein again.
Step S560, measuring the tread of the tire in the vehicle, calculating the barycentric coordinate of the vehicle based on the load information and the tread, and determining the degree of barycentric deviation of the vehicle based on the barycentric coordinate and a predetermined safety threshold.
This step is the same as step S360, and is not described herein again.
In step S570, the vehicle is controlled using the maximum adhesion coefficient, the intended deviation, and the degree of center of gravity deviation as control parameters.
This step is the same as step S370, and is not described herein again.
Step S580, during the process of controlling the vehicle by the control parameter or during the deceleration control of the vehicle by the accelerator pedal back-off mode, the vehicle is involved in an energy recovery device, and the energy is recovered by the energy recovery device.
Specifically, in the case where the engine power is the same, when the output torque of the engine is increased, the output rotation speed is decreased, whereas when the torque is decreased, the rotation speed is increased. That is, when the engine speed is the same, the output torque of the engine is reduced, so that the output power of the engine can be reduced, and the purpose of energy saving can be achieved.
Therefore, when the vehicle is controlled by the control parameters or is subjected to deceleration control in a mode of adjusting back the accelerator pedal, under the condition of meeting the driving desire, the energy recovery device pre-installed in the vehicle can recover the energy of the redundant power in the closed-loop control process according to the magnitude of the required minimum torque, and the effects of energy conservation and energy recovery are further achieved.
It is worth noting that the electromechanical device for energy recovery can also recover through a pulse mode based on frequency, so that the control on the energy recovery device is simple, the riding comfort during energy recovery is improved, and then through the pulse recovery mode, due to the fact that the working principle of the pulse recovery device is similar to that of an ABS (anti-lock braking system), in case of failure of the vehicle active safety control device, the pulse energy recovery device can also play a function similar to that of the ABS, and on the basis of not increasing the cost, the redundant design of brake force control failure is achieved.
Example 5
Fig. 10 is a schematic structural diagram illustrating a vehicle safety control device based on tire condition information according to a fifth embodiment of the present invention. The vehicle safety control device 600 based on the tire state information corresponds to the vehicle safety control method based on the tire state information of embodiment 1. Any of the options in embodiment 1 are also applicable to this embodiment, and will not be described in detail here.
The vehicle safety control apparatus 600 based on tire state information includes a reference straight line determining module 610, an adhesion coefficient calculating module 620, a similarity calculating module 630, and a maximum adhesion coefficient calculating module 640.
And a reference straight line determining module 610, configured to determine a reference straight line according to an adhesion slip curve and a slip slope between the adhesion coefficient and the slip ratio of the tire under different road conditions.
And the adhesion coefficient calculation module 620 is configured to calculate an adhesion coefficient according to the current slip ratio of the tire and the tire state information, and use the adhesion coefficient and the slip ratio as coordinates of a data point.
A similarity calculating module 630, configured to select a predetermined number of reference points from the reference straight line, and calculate a similarity between each reference point and the data point.
And a maximum adhesion coefficient calculating module 640, configured to calculate a maximum adhesion coefficient corresponding to the data point according to the similarity between each reference point and the data point, so as to control the vehicle by using the maximum adhesion coefficient as a control parameter.
Another embodiment of the present invention also provides a vehicle including a memory for storing a computer program and a processor for executing the computer program to cause the vehicle to perform the above-described method for controlling vehicle safety based on tire state information or the above-described function of each module in the apparatus for controlling vehicle safety based on tire state information.
Still another embodiment of the present invention also proposes a computer-readable storage medium storing the computer program used in the vehicle described above.
The invention provides a vehicle safety control method based on tire state information and a vehicle, and has the following advantages: the method has the advantages that various tires of the vehicle are selectively and accurately controlled through control parameters with multiple dimensions (horizontal, longitudinal and vertical), the braking force or the driving force of the vehicle is accurately and dynamically controlled in real time in a closed-loop control mode approaching step by step, potential dangers such as vehicle head pushing, tail flicking, side turning and the like are accurately identified, the safety and comfort of the vehicle during running are obviously improved, and the experience of the tire on the vehicle control performance during the maximum ground holding force is exerted; the defect that the vehicle speed is adjusted by the energy consumption of traction through an accelerator pedal in the running process of the vehicle is overcome, the defect that the vehicle speed is adjusted by the energy consumption of the traction through the accelerator pedal is similar to the defect that the accelerator pedal is completely opened, the traction is controlled only when the opening degree of the accelerator pedal is increased again so as to improve the control performance and the energy economy of the vehicle, and meanwhile, when the vehicle is braked, the braking pressure and the electromechanical coupling braking force during energy recovery are dynamically coordinated, so that the riding comfort and the safety are guaranteed, the energy consumption is reduced, and the energy recovery efficiency is improved.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative and, for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in alternative implementations, the functions noted in the block may occur out of the order noted in the figures. 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 involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, each functional module or unit in each embodiment of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention or a part of the technical solution that contributes to the prior art in essence can be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a smart phone, a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention.
Claims (10)
1. A vehicle safety control method based on tire condition information, characterized by comprising:
determining a reference straight line and an upper inflection point of the reference straight line according to an adhesion slip curve and a slip slope between the adhesion coefficient and the slip rate of the tire under different road conditions;
calculating an adhesion coefficient according to the current slip rate and tire state information of the tire, and taking the adhesion coefficient and the slip rate as coordinates of data points;
selecting a predetermined number of reference points on the reference straight line, and calculating the similarity between each reference point and the data point;
determining the maximum adhesion coefficient corresponding to the data point according to the similarity between each reference point and the data point and/or the inflection point of the reference straight line, and controlling the vehicle by taking the maximum adhesion coefficient as a control parameter;
wherein before the step of calculating the adhesion coefficient according to the current slip ratio and the tire state information of the tire, the method comprises the following steps:
the method comprises the steps of learning the full working condition range of a vehicle under different working conditions, and fitting corresponding wheel speed pulse data to obtain the corresponding relation between the wheel speed pulse data and tire state information, wherein the corresponding relation is used for determining the corresponding tire state information according to the obtained current wheel speed pulse data.
2. The method of claim 1, wherein the determining a reference straight line according to an adhesion slip curve and a slip slope between an adhesion coefficient and a slip ratio of the tire under different road conditions comprises:
determining a slip slope according to the slip rate;
and when the slip slope meets a preset condition, determining the reference straight line according to the curve of the overlapped part of the adhesion slip curves of different road conditions.
3. The vehicle safety control method based on the tire-state information according to claim 2, wherein both end points of the reference straight line are determined simultaneously with the determination of the reference straight line, the method further comprising:
and determining a longitudinal safety interval of the adhesion coefficient according to the coordinates of the two end points of the reference straight line, dividing the longitudinal safety interval into different risk levels according to the safety degree of the vehicle, and prompting a user at each risk level or correspondingly controlling the vehicle according to the maximum adhesion coefficient.
4. The vehicle safety control method based on the tire state information according to claim 1, wherein the tire state information is acquired by:
acquiring an original wheel speed pulse signal of each tire in the vehicle;
revising or reconstructing the original wheel speed pulse signal through a preset rule to obtain wheel speed pulse data;
and determining the tire state information corresponding to the wheel speed pulse data according to a pre-learned corresponding relation.
5. The vehicle safety control method based on tire condition information according to claim 4, wherein the tire condition information includes load information;
the step of calculating the adhesion coefficient according to the current slip ratio and the tire state information of the tire comprises the following steps:
calculating the slip rate from the wheel speed pulse data;
and calculating the adhesion coefficient according to the slip rate and the load information.
6. The vehicle safety control method based on tire state information according to claim 5, wherein the control parameter further includes an intention deviation between an actual running trajectory and a desired trajectory of the vehicle, the intention deviation being determined by:
calculating a difference between the raw wheel speed pulse signal and the wheel speed pulse data over a predetermined monitoring period, the difference being taken as the intended bias.
7. The vehicle safety control method based on tire state information according to claim 6, wherein the control parameter further includes a degree of center of gravity deviation of the vehicle, the degree of center of gravity deviation being determined by:
measuring the track width of a tire in a vehicle;
calculating the barycentric coordinate of the vehicle according to the load information and the wheel track;
and determining the gravity center deviation degree of the vehicle according to the gravity center coordinates and a preset safety threshold value.
8. The vehicle safety control method based on tire condition information according to claim 7, wherein controlling the vehicle by the control parameter includes:
judging whether the control parameter at the current moment exceeds a preset safety range;
if the control parameter exceeds the preset safety range, adjusting the driving state and the change trend of the vehicle according to the control parameter at the current moment, and recalculating the control parameter after adjustment of the vehicle, wherein the adjustment comprises adjusting the actual driving track of the vehicle according to the intention deviation and/or adjusting the barycentric coordinate of the vehicle according to the barycentric deviation degree and/or adjusting the braking force or the driving force of the vehicle according to the maximum adhesion coefficient;
and if the adjusted control parameter still exceeds the preset safety range, continuously adjusting the driving state and the variation trend of the vehicle at the next moment according to the adjusted control parameter, and repeatedly executing the steps until the control parameter after the last adjustment does not exceed the preset safety range.
9. The tire-state-information-based vehicle safety control method according to claim 8, wherein energy is recovered by an energy recovery device interposed during control of the vehicle by the control parameter or deceleration control of the vehicle by accelerator pedal adjustment.
10. A vehicle, characterized by comprising a memory for storing a computer program and a processor for executing the computer program to cause the vehicle to execute the tire-state-information-based vehicle safety control method according to any one of claims 1 to 9.
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| CN113408043B (en) * | 2020-03-17 | 2024-04-05 | 宇通客车股份有限公司 | Whole vehicle tire matching method and device |
| CN111267806A (en) * | 2020-03-31 | 2020-06-12 | 桂林电子科技大学 | Optimal tracking control method for slip rate of ABS (anti-lock braking system) of vehicle |
| CN111532277B (en) * | 2020-06-01 | 2021-11-30 | 中国第一汽车股份有限公司 | Vehicle terrain recognition system and method and vehicle |
| CN111775912B (en) | 2020-06-24 | 2021-06-11 | 东南大学 | Tank car rollover relieving type control method based on electronic braking deceleration |
| CN113836737B (en) * | 2021-09-29 | 2023-10-27 | 东风汽车有限公司东风日产乘用车公司 | Tire interference risk monitoring method, device and equipment |
| CN114537346B (en) * | 2021-12-11 | 2022-12-09 | 清华大学 | Electric wheel slip rate determination method and device, computer equipment and storage medium |
| CN114347963B (en) * | 2021-12-28 | 2023-02-10 | 广州小鹏汽车科技有限公司 | Vehicle control method, vehicle control device, vehicle and storage medium |
| CN114394101B (en) * | 2022-02-17 | 2024-02-23 | 武汉路特斯汽车有限公司 | Method for determining adhesion coefficient between tire and road surface, control device and vehicle |
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