Vehicle curve driving control method and device and storage medium

Abstract

The invention discloses a vehicle curve driving control method and device and a storage medium, and relates to the technical field of vehicle control, and the method comprises the steps that when a vehicle is in a curve, the current steering wheel turning angle, the current vehicle speed and the whole vehicle mass of the vehicle are obtained; querying an efficiency coefficient calibration table according to the current steering wheel angle, the current vehicle speed and the vehicle quality to obtain a calibration efficiency coefficient; controlling the vehicle to run on a curve based on the calibrated efficiency coefficient, and detecting whether the vehicle triggers an efficiency coefficient self-learning condition of curve driving force in the curve driving process; when the efficiency coefficient self-learning condition of the curve driving force is triggered, the current efficiency coefficient is determined according to the current driving data of the vehicle driving on the curve; updating a calibration efficiency coefficient in the efficiency coefficient calibration table through the current efficiency coefficient; and through the updated calibration efficiency coefficient, curve driving control is carried out on the vehicle, stable curve speed control is realized, and the control precision is improved.

Description

Technical Field

[0001] The present application relates to the field of vehicle control technology, and in particular to a vehicle curve driving control method, device and storage medium. Background Art

[0002] When the vehicle is running on a curve, the direction of the driving force is not consistent with the direction of vehicle movement. Since the tire is a plastic element with a certain elasticity, the angle between the driving force and the direction of movement is not completely equal to the front wheel angle. If the front wheel angle is calculated by the steering wheel angle, the process itself will introduce certain deviations.

[0003] The current deviation elimination method is mainly to estimate the driving force through the front wheel angle, but there is a certain deviation between the estimated driving force and the actual value, resulting in inaccurate control of the vehicle on the curve, affecting the user experience. Summary of the invention

[0004] The main purpose of the present application is to provide a vehicle curve driving control method, device and storage medium, aiming to solve the technical problem that when the vehicle is driving on a curve, there is a deviation in the driving force of the vehicle control, which affects the stability of the vehicle speed.

[0005] To achieve the above-mentioned purpose, the present application proposes a vehicle curve driving control method, the vehicle curve driving control method comprising:

[0006] When the vehicle is on a curve, obtain the vehicle's current steering wheel angle, current speed, and vehicle mass;

[0007] According to the current steering wheel angle, the current vehicle speed and the vehicle mass, an efficiency coefficient calibration table is searched to obtain a calibration efficiency coefficient;

[0008] Controlling the vehicle to drive on a curve based on the calibrated efficiency coefficient, and detecting whether a self-learning condition of the efficiency coefficient of the driving force of the curve is triggered during the vehicle's driving on the curve;

[0009] When the efficiency coefficient self-learning condition of the driving force on a curve is triggered, the current efficiency coefficient is determined according to the current driving data of the vehicle when driving on the curve;

[0010] Updating the calibrated efficiency coefficient in the efficiency coefficient calibration table by using the current efficiency coefficient;

[0011] The vehicle is controlled on curves using the updated calibrated efficiency coefficient.

[0012] In one embodiment, the step of updating the calibrated efficiency coefficient in the efficiency coefficient calibration table by using the current efficiency coefficient includes:

[0013] Calculating a current efficiency coefficient deviation according to the current efficiency coefficient and the calibrated efficiency coefficient;

[0014] Determining the angle interval of the current steering wheel angle according to the current steering wheel angle, and determining the speed interval of the current vehicle speed according to the current vehicle speed;

[0015] Get multiple steering wheel angles and multiple vehicle speeds within a cycle;

[0016] When the plurality of steering wheel angles are within the angle interval and the plurality of vehicle speeds are within the vehicle speed interval, the calibrated efficiency coefficient in the efficiency coefficient calibration table is updated according to the cycle number, the angle interval, the vehicle speed interval and the current efficiency coefficient deviation.

[0017] In one embodiment, when the plurality of steering wheel angles are all within the steering angle interval and the plurality of vehicle speeds are all within the vehicle speed interval, the step of updating the calibrated efficiency coefficient in the efficiency coefficient calibration table according to the cycle number, the steering angle interval, the vehicle speed interval and the current efficiency coefficient deviation comprises:

[0018] When the plurality of steering wheel angles are within the angle interval and the plurality of vehicle speeds are within the vehicle speed interval, calculating an average steering wheel angle within the angle interval according to the plurality of steering wheel angles and cycle numbers, and calculating an average vehicle speed within the vehicle speed interval according to the plurality of vehicle speeds and cycle numbers;

[0019] Obtaining a first angle and a second angle according to the angle interval, wherein the first angle is smaller than the second angle;

[0020] calculating a corner efficiency coefficient deviation by using the first corner angle, the average steering wheel angle, the second corner angle, and the current efficiency coefficient deviation;

[0021] The calibrated efficiency coefficient in the efficiency coefficient calibration table is updated based on the corner efficiency coefficient deviation, the vehicle speed range, and the current efficiency coefficient deviation.

[0022] In one embodiment, the step of updating the calibrated efficiency coefficient in the efficiency coefficient calibration table based on the corner efficiency coefficient deviation, the vehicle speed range and the current efficiency coefficient deviation comprises:

[0023] Based on the corner efficiency coefficient deviation, the calibrated efficiency coefficient of the corresponding corner in the efficiency coefficient calibration table is updated by using an inverse proportional distribution deviation method to obtain a reference efficiency coefficient calibration table;

[0024] Obtaining a first vehicle speed and a second vehicle speed according to the vehicle speed interval, wherein the first vehicle speed is less than the second vehicle speed;

[0025] Calculating a vehicle speed efficiency coefficient deviation by using the first vehicle speed, the second vehicle speed, the average vehicle speed, the first turning angle, the second turning angle, and the current efficiency coefficient deviation;

[0026] The calibrated efficiency coefficient of the corresponding vehicle speed in the reference efficiency coefficient calibration table is updated by using the vehicle speed efficiency coefficient deviation to complete the updating of the efficiency coefficient calibration table.

[0027] In one embodiment, when the efficiency coefficient self-learning condition of the driving force on a curve is triggered, the step of determining the current efficiency coefficient according to the current driving data of the vehicle when driving on the curve includes:

[0028] When the self-learning condition of the efficiency coefficient of the curve driving force is triggered, the driving driving force, the driving wind resistance, the driving rolling resistance, the driving slope resistance and the driving acceleration resistance are obtained according to the current driving data of the vehicle when driving on the curve;

[0029] Obtain the relationship between the calibrated efficiency coefficient and the longitudinal dynamics of the vehicle;

[0030] A current efficiency coefficient is calculated based on the relationship, the running drive force, the running wind resistance, the running rolling resistance, the running slope resistance, and the running acceleration resistance.

[0031] In one embodiment, the step of constructing the efficiency coefficient calibration table includes:

[0032] Define the relationship between the efficiency coefficient and the longitudinal dynamics of the vehicle;

[0033] Collect historical driving data of vehicles when driving on different curves;

[0034] Obtaining historical efficiency coefficient data of the vehicle when traveling on different curves according to the historical driving data and the relationship;

[0035] Fitting the historical efficiency coefficient data, and obtaining influencing factors affecting the efficiency coefficient according to the fitting results, wherein the influencing factors include steering wheel angle, vehicle speed and vehicle mass;

[0036] A mapping relationship between the efficiency coefficient and the steering wheel angle, the vehicle speed and the vehicle mass is established based on the historical steering wheel angle, the historical vehicle speed, the vehicle mass and the historical efficiency coefficient data in the historical driving data to obtain an efficiency coefficient calibration table.

[0037] In one embodiment, the step of controlling the vehicle to drive on a curve based on the calibrated efficiency coefficient includes:

[0038] Obtain the relationship between the calibrated efficiency coefficient and the longitudinal dynamics of the vehicle;

[0039] Get the current wind resistance, current rolling resistance, current ramp resistance and current acceleration resistance;

[0040] calculating a control driving force of the vehicle according to the calibrated efficiency coefficient, the relationship, the current wind resistance, the current rolling resistance, the current ramp resistance, and the current acceleration resistance;

[0041] The vehicle is controlled to travel on a curve according to the controlled driving force.

[0042] In one embodiment, the step of detecting whether the efficiency coefficient self-learning condition of the driving force of a curve is triggered during the vehicle's driving on a curve includes:

[0043] When the vehicle is driving on a curve, the steering wheel angle change rate is obtained;

[0044] When the current steering wheel angle is greater than a preset angle threshold and the steering wheel angle change rate is less than a preset change rate threshold, a self-learning condition for triggering the efficiency coefficient of the curve driving force is determined.

[0045] In addition, to achieve the above-mentioned purpose, the present application also proposes a vehicle curve driving control device, the vehicle curve driving control device comprising:

[0046] An acquisition module is used to acquire the current steering wheel angle, current vehicle speed and vehicle mass of the vehicle when the vehicle is in a curve;

[0047] A query module, configured to query an efficiency coefficient calibration table according to the current steering wheel angle, the current vehicle speed and the vehicle mass to obtain a calibrated efficiency coefficient;

[0048] a control module, configured to control the vehicle to drive on a curve based on the calibrated efficiency coefficient, and detect whether a self-learning condition of the efficiency coefficient of the driving force of the curve is triggered during the vehicle's driving on the curve;

[0049] A determination module, for determining a current efficiency coefficient according to current driving data of the vehicle when driving on the curve when a self-learning condition for the efficiency coefficient of the driving force on the curve is triggered;

[0050] An updating module, configured to update the calibrated efficiency coefficient in the efficiency coefficient calibration table by using the current efficiency coefficient;

[0051] The control module is also used to control the vehicle's cornering driving through the updated calibrated efficiency coefficient.

[0052] In addition, to achieve the above-mentioned purpose, the present application also proposes a vehicle curve driving control device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, and the computer program is configured to implement the steps of the vehicle curve driving control method as described above.

[0053] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the vehicle curve driving control method described above are implemented.

[0054] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the vehicle curve driving control method described above are implemented.

[0055] One or more technical solutions proposed in the present application are as follows: when the vehicle is in a curve, the current steering wheel angle, the current vehicle speed and the vehicle mass of the vehicle are obtained; according to the current steering wheel angle, the current vehicle speed and the vehicle mass, an efficiency coefficient calibration table is queried to obtain a calibrated efficiency coefficient; based on the calibrated efficiency coefficient, the vehicle is controlled to drive on the curve, and it is detected whether a self-learning condition of the efficiency coefficient of the driving force of the curve is triggered during the vehicle's driving on the curve; when the self-learning condition of the efficiency coefficient of the driving force of the curve is triggered, the current efficiency coefficient is determined according to the current driving data of the vehicle when driving on the curve; the calibrated efficiency coefficient in the efficiency coefficient calibration table is updated by the current efficiency coefficient; and the vehicle is controlled to drive on the curve by the updated calibrated efficiency coefficient. By querying the efficiency coefficient calibration table based on the acquired driving data to obtain the best driving force, the stability of the vehicle when driving on curves can be ensured, thereby significantly improving driving safety. The efficiency coefficient self-learning condition for the driving force on curves is introduced. When specific conditions are met, the data in the efficiency coefficient calibration table is automatically updated to better adapt to different road conditions and changes in personal driving habits, providing a more personalized and efficient driving experience, thereby achieving smooth vehicle speed control on curves and improving control accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0057] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0058] Figure 1 A schematic diagram of a flow chart provided for the first embodiment of the vehicle curve driving control method of the present application;

[0059] Figure 2 This is a schematic diagram of the relationship between driving force and speed in an embodiment of the vehicle curve driving control method of the present application;

[0060] Figure 3 This is a schematic diagram showing that the traditional feedforward + PID control method may lead to inaccurate vehicle speed control on a curve;

[0061] Figure 4 This is a schematic diagram of constructing an efficiency coefficient calibration MAP in an embodiment of the vehicle curve driving control method of the present application;

[0062] Figure 5 A schematic diagram of a flow chart provided for the second embodiment of the vehicle curve driving control method of the present application;

[0063] Figure 6 This is a schematic diagram of the module structure of the vehicle curve driving control device according to an embodiment of the present application;

[0064] Figure 7 Schematic diagram of the device structure of the hardware operating environment involved in the vehicle curve driving control method in the embodiment of the present application.

[0065] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0066] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0067] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0068] The main solution of the embodiment of the present application is: when the vehicle is in a curve, obtain the vehicle's current steering wheel angle, current vehicle speed and vehicle mass; query the efficiency coefficient calibration table according to the current steering wheel angle, the current vehicle speed and the vehicle mass to obtain the calibrated efficiency coefficient; control the vehicle to drive on the curve based on the calibrated efficiency coefficient, and detect whether the vehicle triggers the efficiency coefficient self-learning condition of the curve driving force during the curve driving process; when the efficiency coefficient self-learning condition of the curve driving force is triggered, determine the current efficiency coefficient according to the current driving data of the vehicle when driving on the curve; update the calibrated efficiency coefficient in the efficiency coefficient calibration table according to the current efficiency coefficient; and control the vehicle to drive on the curve according to the updated calibrated efficiency coefficient.

[0069] At present, more and more vehicles are equipped with intelligent driving functions. As an important part of the intelligent driving system, longitudinal control is responsible for converting the planned vehicle speed into the corresponding torque or acceleration, and finally realizing the control of the vehicle speed. The specific control scheme depends on the vehicle's software architecture. Since the acceleration interface needs to pass through IBC (Integration Cruise Assist, integrated cruise system), IBC needs to be debugged and matched by the supplier, and IBC cannot effectively use the intelligent driving information. There will be a lot of lags in the control process. For example, when the vehicle goes uphill, IBC cannot predict the slope in advance and can only detect the slope after going uphill, which will inevitably cause the vehicle speed to drop. When IBC detects that the vehicle speed has dropped, in order to maintain the required vehicle speed, the upper controller must send an increased acceleration. At the same time, IBC itself will increase the current control torque to track the target to achieve the purpose of tracking the target acceleration. However, the upper controller (intelligent driving controller) can get the road information ahead in advance based on the camera and map, and can make corrections in the feedforward for this working condition. The control effect will be better, and controlling the vehicle through the acceleration interface is also a future trend.

[0070] However, when the vehicle is running on a curve, the direction of the driving force is not consistent with the direction of vehicle movement. Since the tire is a plastic element with a certain elasticity, the angle between the driving force and the direction of movement is not completely equal to the front wheel turning angle. If the front wheel turning angle is calculated by the steering wheel angle, the process itself will introduce certain deviations.

[0071] Since the existing technology mainly estimates the driving force through the front wheel angle, there is a certain deviation between the estimated driving force and the actual value. Although this deviation can be further eliminated through closed-loop control, there is a certain hysteresis in PID control, which will cause speed fluctuations and is not a perfect control. When the vehicle exits the curve, due to the continuity of control, it will also cause certain speed fluctuations, that is, there is a high probability of a certain speed overshoot. The direct manifestation of the appearance of this control deviation is the deterioration of the control effect of the entire vehicle.

[0072] The present application provides a solution, which determines the influencing factors of the vehicle driving on a curve to construct the efficiency coefficient of the driving force on the curve, and corrects the efficiency coefficient based on self-learning to achieve smooth vehicle speed control on the curve and improve control accuracy.

[0073] It should be noted that the execution subject of this embodiment may be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a vehicle curve driving control device, etc. The following takes the vehicle curve driving control device as an example to illustrate this embodiment and the following embodiments.

[0074] Based on this, the embodiment of the present application provides a vehicle curve driving control method, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the vehicle curve driving control method of the present application.

[0075] In this embodiment, the vehicle curve driving control method includes steps S10 to S60:

[0076] Step S10: When the vehicle is on a curve, the current steering wheel angle, current vehicle speed and vehicle mass of the vehicle are obtained.

[0077] It should be noted that if Figure 2 As shown, Figure 2 This is a schematic diagram of the relationship between driving force and speed. When the vehicle is in a curve, only the component of the driving force in the direction of the vehicle speed can accelerate the vehicle, thereby achieving longitudinal speed control of the vehicle, as shown in the figure below. t ' is the projection of the tire driving force in the direction of speed, F t ′=F tcosα, this component is used for the longitudinal acceleration of the vehicle. As the front wheel turning angle increases, the component of the same driving force in the speed direction becomes smaller and smaller, and the generated acceleration becomes smaller and smaller; similarly, after obtaining the required acceleration, if the angle between the actual front wheel trajectory and the speed direction cannot be accurately obtained during the conversion into driving force, the calculation of the process will have a certain deviation, which can only be eliminated through closed-loop adjustment. Assuming that the torque calculation of other modules is accurate, the actual speed performance is as follows Figure 3 As shown in the figure, the vehicle is traveling at a constant speed. After entering the curve, the calculation deviation of the driving force of the curve causes a deviation in the vehicle speed control. Then, the speed deviation is eliminated through the PID closed loop. When the vehicle exits the curve, due to the continuity of the control, it will also cause a certain speed fluctuation, that is, there is a high probability that a certain speed overshoot will occur. The direct manifestation of the control deviation is that the control effect of the whole vehicle is deteriorated, so it is necessary to eliminate the deviation as much as possible. Since the tire is a plastic element, the real α angle is difficult to solve and can only be solved by calibration. It mainly depends on the stiffness of the tire, and the stiffness of the tire will be affected by the wear and pressure of the tire. Therefore, solving this problem through calibration will cause the effect to deteriorate when the tire characteristics change. At the same time, there is usually no real tire angle sensor on the vehicle. It is generally obtained by dividing the steering wheel angle by the steering ratio. However, in actual use, the steering wheel angle will also have a certain deviation (such as 0-position deviation), which will further amplify the control error in the process. During the actual operation of the vehicle, wind resistance is related to the wind speed in addition to the vehicle's drag coefficient / windward area. In order to accurately solve the driving force of the entire vehicle, the vehicle usually performs self-learning of rolling resistance and wind resistance on a straight road to eliminate changes in wind resistance, rolling resistance and other environmental factors.

[0078] Therefore, this embodiment takes into account all control deviations on the curve, thereby setting the control deviation to construct the dynamics formula and constructing the relationship between the driving data and the control deviation. Therefore, when it is detected that the vehicle enters a curve, the current steering wheel angle, current vehicle speed and vehicle mass of the vehicle can be directly obtained.

[0079] Step S20: querying an efficiency coefficient calibration table according to the current steering wheel angle, the current vehicle speed and the vehicle mass to obtain a calibrated efficiency coefficient.

[0080] It should be noted that the efficiency coefficient calibration table represents the mapping relationship between the steering wheel angle, vehicle speed, vehicle mass and the efficiency coefficient. Therefore, the efficiency coefficient calibration table can be queried according to the current steering wheel angle, current vehicle speed and vehicle mass to obtain the corresponding calibrated efficiency coefficient.

[0081] The efficiency coefficient is the efficiency coefficient η of the vehicle's driving force on a curve. The efficiency coefficient calibration table can be constructed in advance, and the step of constructing the efficiency coefficient calibration table can include steps A11 to A15:

[0082] Step A11: Define the relationship between the efficiency coefficient and the longitudinal dynamics of the vehicle.

[0083] It should be noted that, in fact, the slip angle of a vehicle when driving on a curve is not only related to tire characteristics, tire pressure, etc., but also to the lateral force. The actual slip angle is relatively complex. At the same time, in order to include all control deviations on the curve into the longitudinal dynamics formula, this embodiment proposes to define an efficiency coefficient η of the driving force on the curve, so the longitudinal dynamics formula is rewritten as: F t *η=F w +F r +F a +F s The longitudinal dynamics formula is the relationship between the efficiency coefficient and the longitudinal dynamics of the vehicle.

[0084] Among them, F w , F r , F a , F s and F t Both are longitudinal dynamics of the vehicle.

[0085] F t is the driving force of the vehicle, F w is wind resistance, F r is the rolling resistance, F s is the slope resistance, F a For acceleration resistance.

[0086] Step A12: Collect historical driving data of the vehicle when driving on different curves.

[0087] It should be noted that historical driving data of the vehicle when driving on different curves can be collected. The data needs to include information such as slope (which can be from a sensor or from a controller with a higher reliability of calculation results), engine / motor torque, steering wheel angle, vehicle speed, rolling resistance, wind resistance, acceleration, and vehicle mass.

[0088] Step A13: Obtain historical efficiency coefficient data of the vehicle when traveling on different curves according to the historical driving data and the relationship.

[0089] In a specific implementation, the efficiency coefficients in all collected data can be solved by using the longitudinal dynamics formula according to the driving force, wind resistance, rolling resistance, ramp resistance and acceleration resistance in the historical driving data to obtain historical efficiency coefficient data.

[0090] Step A14: fitting the historical efficiency coefficient data, and obtaining influencing factors affecting the efficiency coefficient according to the fitting results, wherein the influencing factors include steering wheel angle, vehicle speed and vehicle mass.

[0091] It should be noted that a neural network can be used to fit η, and flat road data is preferably used for fitting. After the fitting is completed, the ramp data is used for further verification. The main influencing factors affecting the efficiency coefficient are selected according to the fitting results. The fitting results show that this value is mainly affected by the steering wheel angle, and the vehicle mass and speed also have a great influence on the result. The most important influencing factors are selected according to the control accuracy requirements. This proposal selects three influencing factors a1 (steering wheel angle), a2 (vehicle speed), and a3 (vehicle mass).

[0092] Step A15: Establish a mapping relationship between the efficiency coefficient and the steering wheel angle, vehicle speed and vehicle mass according to the historical steering wheel angle, historical vehicle speed, vehicle mass and the historical efficiency coefficient data in the historical driving data to obtain an efficiency coefficient calibration table.

[0093] It is understandable that an efficiency coefficient calibration table can be constructed based on historical steering wheel angles, historical vehicle speeds, vehicle instructions, and historical efficiency coefficient data.

[0094] Specifically, the value ranges of the three factors can be determined respectively, and the coordinate axes can be formulated according to the value ranges. The points on the coordinate axes can be input into the fitting results to obtain η under the values, such as Figure 4 As shown, Figure 4 To construct a schematic diagram for calibrating MAP for the efficiency coefficient, the data table lookup result of MAP1 corresponds to the first data y value of the a3 coordinate axis, and the data table lookup result of MAP2 corresponds to the second y value data of the a3 coordinate axis, and so on. After completing the first table lookup, a new array is formed, which is the function value of MP5, thereby simplifying the three-parameter table lookup problem.

[0095] As shown in Table 1 below, Table 1 is an efficiency coefficient calibration table. After obtaining the efficiency coefficient calibration table, the corresponding map can be determined according to the current steering wheel angle and the current vehicle speed, and the corresponding value can be found in MAP5 according to the vehicle mass to obtain the calibrated efficiency coefficient.

[0096] Table 1

[0097]

[0098] Step S30: controlling the vehicle to drive on a curve based on the calibrated efficiency coefficient, and detecting whether a self-learning condition of the efficiency coefficient of the driving force on the curve is triggered during the vehicle's driving on the curve.

[0099] It can be understood that after obtaining the calibrated efficiency coefficient, the vehicle can be controlled to travel on a curve by first using the calibrated efficiency coefficient. Specifically, a specific control driving force can be calculated based on the calibrated efficiency coefficient to control the vehicle.

[0100] When controlling the vehicle to drive on a curve, it is also necessary to detect in real time whether the vehicle triggers the self-learning condition of the efficiency coefficient of the driving force on the curve during the curve driving process. For example, if the current calibrated efficiency coefficient does not meet the user's needs when controlling the vehicle, the self-learning condition of the efficiency coefficient of the driving force on the curve will be triggered. If the current calibrated efficiency coefficient meets the user's needs when controlling the vehicle, the self-learning condition of the efficiency coefficient of the driving force on the curve may not be triggered. Alternatively, it is determined whether the changes in the turning angle and speed of the vehicle meet the needs. If the changes in the turning angle and speed of the vehicle meet the needs and the amount of data is greater than a certain threshold, the self-learning condition of the efficiency coefficient of the driving force on the curve can be automatically triggered.

[0101] In a feasible implementation, step S30 may include steps S31 to S36:

[0102] Step S31: Obtain the relationship between the calibrated efficiency coefficient and the longitudinal power of the vehicle.

[0103] It should be noted that the relationship between the calibrated efficiency coefficient and the longitudinal dynamics of the vehicle is the above-mentioned longitudinal dynamics formula: F t *η=F w +F r +F a +F s .

[0104] Step S32: Obtain the current wind resistance, current rolling resistance, current ramp resistance and current acceleration resistance.

[0105] In a specific implementation, the current wind resistance, the current rolling resistance, the current ramp resistance and the current acceleration resistance can be calculated based on the collected vehicle parameters and driving parameters.

[0106] Wind resistance Among them, C d is the drag coefficient, A is the frontal area, and u is the relative vehicle speed. w =μmg, μ is the coefficient of kinetic friction, m is the mass of the vehicle, g is the acceleration of gravity, and the slope resistance F s =mgsinα, α is the slope angle, acceleration resistance F a =ma, a is the acceleration of the vehicle. The current wind resistance, current rolling resistance, current slope resistance and current acceleration resistance can be calculated through the above formula and specific parameters.

[0107] Step S33: Calculate the control driving force of the vehicle according to the calibrated efficiency coefficient, the relationship, the current wind resistance, the current rolling resistance, the current ramp resistance and the current acceleration resistance.

[0108] It should be understood that the vehicle's control driving force may be calculated based on the relationship between the calibrated efficiency coefficient and the vehicle's longitudinal power, the calibrated efficiency coefficient, and the current wind resistance, current rolling resistance, current ramp resistance, and current acceleration resistance.

[0109] The controlled driving force is the driving force currently used to control the vehicle when traveling on a curve according to the calibrated efficiency coefficient.

[0110] Step S34: controlling the vehicle to travel on a curve according to the controlled driving force.

[0111] In a specific implementation, after the control driving force is obtained, the required motor torque or engine torque can be calculated according to the control driving force, so as to control the vehicle to travel on the curve according to the required torque.

[0112] Step S35: When the vehicle is traveling on a curve, the steering wheel angle change rate is obtained.

[0113] In specific implementations, since the calibrated efficiency coefficient is not necessarily an accurate efficiency coefficient, the control driving force calculated based on the calibrated efficiency coefficient may not be able to accurately control the vehicle's cornering. Therefore, while the vehicle is cornering, the steering wheel angle change rate of the vehicle can also be obtained in real time.

[0114] Step S36: When the current steering wheel angle is greater than a preset angle threshold and the steering wheel angle change rate is less than a preset change rate threshold, determining a self-learning condition for triggering the efficiency coefficient of the cornering driving force.

[0115] It can be understood that the current steering wheel angle can be compared with the preset angle threshold set in advance by calibration, so as to determine whether there is a significant change in the steering wheel of the vehicle. At the same time, the steering wheel angle change rate can be compared with the preset change rate threshold set in advance by calibration. When the current steering wheel angle is greater than the preset angle threshold and the steering wheel angle change rate is less than the preset change rate threshold, the efficiency coefficient self-learning of the cornering driving force can be triggered. If not, the efficiency self-learning of the cornering driving force will not be triggered, and the control driving force calculated according to the calibrated efficiency coefficient will continue to be used to control the vehicle to drive on the curve.

[0116] Step S40: when the efficiency coefficient self-learning condition of the curve driving force is triggered, the current efficiency coefficient is determined according to the current driving data of the vehicle when traveling on the curve.

[0117] It should be understood that when the efficiency coefficient self-learning condition of the cornering driving force is triggered, the current efficiency coefficient can be determined based on the current driving data of the vehicle when traveling on the curve, and can be specifically calculated based on the relationship between the above-mentioned efficiency coefficient and the longitudinal power of the vehicle.

[0118] In a feasible implementation, step S40 may include steps S41 to S43:

[0119] Step S41: When the self-learning condition of the efficiency coefficient of the curve driving force is triggered, the driving force, the driving wind resistance, the driving rolling resistance, the driving slope resistance and the driving acceleration resistance are obtained according to the current driving data of the vehicle when driving on the curve.

[0120] It should be noted that when the self-learning condition of the efficiency coefficient of the cornering driving force is triggered, the driving force, driving wind resistance, driving rolling resistance, driving slope resistance and driving acceleration resistance can be obtained according to the current driving data of the vehicle when it is driving on the corner.

[0121] Driving force, driving wind resistance, driving rolling resistance, driving slope resistance and driving acceleration resistance can also be calculated based on the real-time collected environmental coefficients and the real-time driving data of the vehicle.

[0122] Step S42: Obtain the relationship between the calibrated efficiency coefficient and the vehicle longitudinal power.

[0123] Step S43: Calculate the current efficiency coefficient according to the relationship, the driving force, the driving wind resistance, the driving rolling resistance, the driving slope resistance and the driving acceleration resistance.

[0124] It should be noted that the current efficiency coefficient can be obtained based on the relationship between the calibrated efficiency coefficient and the longitudinal dynamics of the vehicle, that is, the dynamics formula and the driving driving force, the driving wind resistance, the driving rolling resistance, the driving slope resistance and the driving acceleration resistance. The current efficiency coefficient is the real-time efficiency coefficient of the vehicle during cornering. The current efficiency coefficient may be the same as or different from the calibrated efficiency coefficient. If the current efficiency coefficient is the same as the calibrated efficiency coefficient, there is no need to update the calibrated efficiency coefficient. If the current efficiency coefficient is different from the calibrated efficiency coefficient, the calibrated efficiency coefficient needs to be updated.

[0125] Step S50: updating the calibrated efficiency coefficient in the efficiency coefficient calibration table by using the current efficiency coefficient.

[0126] It should be noted that the corresponding calibrated efficiency coefficient in the efficiency coefficient calibration table may be updated according to the calculated current efficiency coefficient, so as to obtain an updated efficiency coefficient calibration table.

[0127] Step S60: Controlling the vehicle on a curve using the updated calibrated efficiency coefficient.

[0128] In a specific implementation, after updating the calibrated efficiency coefficient, it can be determined whether to exit the efficiency coefficient self-learning. If not, the efficiency coefficient will continue to be updated. If the self-learning is exited, the updated calibrated efficiency coefficient table can be stored. The next time the cornering control is performed, the updated calibrated efficiency coefficient table can be directly queried based on the acquired data to obtain the calibrated efficiency coefficient. The vehicle can be controlled on the cornering according to the calibrated efficiency coefficient to improve the stability of the cornering control.

[0129] The present embodiment provides a method for controlling vehicle driving on a curve. When the vehicle is on a curve, the current steering wheel angle, current vehicle speed and vehicle mass of the vehicle are obtained; an efficiency coefficient calibration table is queried according to the current steering wheel angle, current vehicle speed and vehicle mass to obtain a calibrated efficiency coefficient; the vehicle is controlled to drive on the curve based on the calibrated efficiency coefficient, and it is detected whether a self-learning condition of the efficiency coefficient of the driving force on the curve is triggered during the vehicle driving on the curve; when the self-learning condition of the efficiency coefficient of the driving force on the curve is triggered, the current efficiency coefficient is determined according to the current driving data of the vehicle when driving on the curve; the calibrated efficiency coefficient in the efficiency coefficient calibration table is updated according to the current efficiency coefficient; and the vehicle is controlled to drive on the curve according to the updated calibrated efficiency coefficient. By querying the efficiency coefficient calibration table based on the acquired driving data to obtain the best driving force, the stability of the vehicle when driving on curves can be ensured, thereby significantly improving driving safety. The efficiency coefficient self-learning condition for the driving force on curves is introduced. When specific conditions are met, the data in the efficiency coefficient calibration table is automatically updated to better adapt to different road conditions and changes in personal driving habits, providing a more personalized and efficient driving experience, thereby achieving smooth vehicle speed control on curves and improving control accuracy.

[0130] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 5 , step S50 includes steps S501 to S504:

[0131] Step S501: Calculate a current efficiency coefficient deviation according to the current efficiency coefficient and the calibrated efficiency coefficient.

[0132] It should be noted that during the actual driving of the vehicle, due to some factors, the current efficiency coefficient may be inconsistent with the calibrated efficiency coefficient in the calibration table. Therefore, the current efficiency coefficient deviation η_error can be calculated based on the current efficiency coefficient and the calibrated efficiency coefficient, η_error = current efficiency coefficient - calibrated efficiency coefficient.

[0133] Step S502: determining the angle interval of the current steering wheel angle according to the current steering wheel angle, and determining the speed interval of the current vehicle speed according to the current vehicle speed.

[0134] In the specific implementation, when performing self-learning of the efficiency coefficient, it is first necessary to determine the coordinate axis interval of the current vehicle speed and the current steering wheel angle, and start counting from counter count = 0. If the vehicle speed of this cycle is in the same coordinate axis interval as the vehicle speed of the previous cycle, and the steering angle of this cycle is in the same coordinate axis interval as the steering angle of the previous cycle, then the counter is incremented by 1, otherwise the counter is set to 0.

[0135] Step S503: Acquire multiple steering wheel angles and multiple vehicle speeds within a cycle.

[0136] The period countn can be set arbitrarily, for example, to 4, 6, etc., and this embodiment does not limit this.

[0137] Step S504: When the plurality of steering wheel angles are within the angle interval and the plurality of vehicle speeds are within the vehicle speed interval, the calibrated efficiency coefficient in the efficiency coefficient calibration table is updated according to the cycle number, the angle interval, the vehicle speed interval and the current efficiency coefficient deviation.

[0138] The average steering wheel angle of multiple steering wheel angles in a cycle can be calculated to determine whether the average steering wheel angle is in the angle interval. If so, the multiple steering wheel angles are all in the angle interval. The average vehicle speed of multiple vehicle speeds in the cycle can be calculated to determine whether the average vehicle speed is in the vehicle speed interval. If so, the multiple vehicle speeds are all in the vehicle speed interval.

[0139] When a plurality of steering wheel angles are within the angle range and a plurality of vehicle speeds are within the vehicle speed range, the efficiency coefficient of self-learning may be updated according to corresponding parameters.

[0140] Specifically, the efficiency coefficient deviation in the corresponding turning angle interval and the corresponding vehicle speed interval can be calculated by using the cycle number, the turning angle interval, the vehicle speed interval and the current efficiency coefficient deviation, so as to update the calibrated efficiency coefficient.

[0141] In a feasible implementation, step S504 may include steps B11 to B14:

[0142] Step B11: When the plurality of steering wheel angles are within the angle interval and the plurality of vehicle speeds are within the vehicle speed interval, the average steering wheel angle within the angle interval is calculated based on the plurality of steering wheel angles and cycle numbers, and the average vehicle speed within the vehicle speed interval is calculated based on the plurality of vehicle speeds and cycle numbers.

[0143] It should be noted that the average vehicle speed is calculated as follows:

[0144] V_avg=[V_avg*(count-1)+v] / count

[0145] Wherein, v is the current vehicle speed, Count is a counter that increases by 1 in each cycle during self-learning, i.e., the number of cycles, and V_avg is the average vehicle speed during self-learning.

[0146] The average steering wheel angle is calculated as follows:

[0147] angle_avg=[angle_avg*(count-1)+angle] / count

[0148] angle_avg is the average steering wheel angle during the self-learning period, angle is the current steering wheel angle, and the average vehicle speed and average steering wheel angle are calculated repeatedly. If the steering wheel angle or the angle change rate does not meet the conditions, the self-learning will be exited. Once the number of calculations reaches a certain calibration value LearnTimer, that is, count>LearnTimer, the self-learning data update will be activated.

[0149] Step B12: Obtain a first angle and a second angle according to the angle interval, wherein the first angle is smaller than the second angle.

[0150] During the self-learning process, we obtained the average vehicle speed and the average turning angle in the process, and the speed value and the turning angle value always belong to a certain speed and turning angle range in the efficiency calibration table. Therefore, the first turning angle and the second turning angle can be obtained according to the turning angle range. For example, if the turning angle range is [m, n], the first turning angle is m and the second turning angle is n.

[0151] Step B13: Calculating a corner efficiency coefficient deviation using the first corner, the average steering wheel angle, the second corner, and the current efficiency coefficient deviation.

[0152] In a specific implementation, the corner efficiency coefficient deviation is as follows:

[0153] η_error_m=[1-(angle_avg-m) / (nm)]*η_error

[0154] η_error_n=[(angle_avg-n) / (nm)]*η_error

[0155] η_error is the current efficiency coefficient deviation, m is the first corner, n is the second corner, η_error_m is the efficiency deviation at point m of the first corner of the coordinate axis, and η_error_n is the efficiency deviation at point n of the second corner of the coordinate axis, thereby obtaining the corner efficiency coefficient deviation.

[0156] It should be noted that the corner efficiency coefficient deviation is a deviation in the efficiency coefficient caused when the steering wheel angle is distributed.

[0157] Step B14: updating the calibrated efficiency coefficient in the efficiency coefficient calibration table based on the corner efficiency coefficient deviation, the vehicle speed range and the current efficiency coefficient deviation.

[0158] In a specific implementation, after obtaining the corner efficiency coefficient deviation, the corner efficiency coefficient deviation can be mapped to the efficiency coefficient calibration table. Because the calibration table is a two-dimensional parameter map, after allocating the corner, it is necessary to further allocate it on the vehicle speed. Therefore, the calibrated efficiency coefficient in the efficiency coefficient calibration table can be updated according to the corner efficiency coefficient deviation, the vehicle speed range and the current efficiency coefficient deviation. Specifically, Figure 4 As shown, the deviation of MAP5 is initially obtained. Based on the actual vehicle mass and the mass coordinate axis, the corner efficiency coefficient deviation can be allocated to two MAPs of MAP1-MAP4, such as map1 and map2, and then allocated again on map1 and map2.

[0159] In a feasible implementation, step B14 may include:

[0160] Based on the corner efficiency coefficient deviation, the calibrated efficiency coefficient of the corresponding corner in the efficiency coefficient calibration table is updated using an inversely proportional distribution deviation method to obtain a reference efficiency coefficient calibration table; a first vehicle speed and a second vehicle speed are obtained according to the vehicle speed range, and the first vehicle speed is less than the second vehicle speed; a vehicle speed efficiency coefficient deviation is calculated using the first vehicle speed, the second vehicle speed, the average vehicle speed, the first turning angle, the second turning angle and the current efficiency coefficient deviation; the calibrated efficiency coefficient of the corresponding vehicle speed in the reference efficiency coefficient calibration table is updated using the vehicle speed efficiency coefficient deviation to complete the update of the efficiency coefficient calibration table.

[0161] It should be noted that the inverse proportional distribution deviation method can be used for the efficiency coefficient deviation distribution of the turning angle, so the initial update of the calibrated efficiency coefficient can be performed through the obtained η_error_m and η_error_n, thereby obtaining the reference efficiency coefficient calibration table. Assuming that the average vehicle speed V_avg is in the interval [j, k], there are a total of 4 data points that need to be updated, namely jm, jn, km, and kn. The impact of vehicle speed on the deviation is much smaller than that of the turning angle, so for the vehicle speed, we can use the inverse proportional update method or the average distribution.

[0162] The vehicle speed efficiency coefficient deviation is a deviation in the efficiency coefficient caused when the vehicle speed distribution is performed.

[0163] Specifically, the first vehicle speed and the second vehicle speed can be obtained according to the vehicle speed range, the first vehicle speed is j, and the second vehicle speed is k. Specifically, if the inverse proportional update method is adopted, the vehicle speed efficiency coefficient deviation is calculated as follows:

[0164] η_error_jm=[1-(angle_avg-m) / (nm)]*η_error*[1-(v_avg-j) / (kj)]

[0165] η_error_km=[1-(angle_avg-m) / (nm)]*η_error*[(v_avg-j) / (kj)]

[0166] η_error_jn=[(angle_avg-m) / (nm)]*η_error*[1-(v_avg-j) / (kj)]

[0167] η_error_kn=[(angle_avg-m) / (nm)]*η_error*[(v_avg-j) / (kj)]

[0168] m is the first turning angle, n is the second turning angle, j is the first vehicle speed, k is the second vehicle speed, η_error is the current efficiency coefficient deviation, and the vehicle speed efficiency coefficient deviations at the four positions are calculated.

[0169] In a feasible implementation manner, the vehicle speed efficiency coefficient deviation can also be calculated according to the average steering wheel angle, the first turning angle, the second turning angle and the current efficiency coefficient deviation, so as to update the calibrated efficiency coefficient of the corresponding vehicle speed in the reference efficiency coefficient calibration table through the vehicle speed efficiency coefficient deviation, that is, the deviation caused by the vehicle speed is updated by the average distribution method, then:

[0170] η_error_jm=[1-(angle_avg-m) / (nm)]*η_error

[0171] η_error_km=[1-(angle_avg-m) / (nm)]*η_error

[0172] η_error_jn=[(angle_avg-m) / (nm)]*η_error

[0173] η_error_kn=[(angle_avg-m) / (nm)]*η_error

[0174] It should be noted that in order to avoid too large fluctuations in calibration data caused by too fast self-learning deviation updates, and to eliminate efficiency deviations caused by occasional factors, the calculated vehicle speed efficiency coefficient deviation can be multiplied by a coefficient and then added to the previous cornering driving force efficiency deviation. Specifically, the weight coefficient f can be set. f can be calibrated and set in advance. For example, it can be set to 0.01. The vehicle speed efficiency coefficient deviation is multiplied by the weight coefficient f, and the calculation is as follows:

[0175] η_jm'=η_error_jm*f+η_jm

[0176] η_km'=η_error_km*f+η_km

[0177] η_jn'=η_error_jn*f+η_jn

[0178] η_kn'=η_error_kn*f+η_kn

[0179] η_jm', η_km', η_jn' and η_kn' are the updated calibration efficiency coefficients, η_jm represents the calibration efficiency coefficient at vehicle speed j and steering wheel angle m, η_km represents the calibration efficiency coefficient at vehicle speed k and steering wheel angle m, η_jn represents the calibration efficiency coefficient at vehicle speed j and steering wheel angle n, and η_kn represents the calibration efficiency coefficient at vehicle speed k and steering wheel angle n. After the calculated speed efficiency coefficient deviation is multiplied by the weight f, the result is updated to the corresponding calibration efficiency coefficient, thereby further eliminating the problem of frequent changes in cornering efficiency caused by frequent data changes, improving data stability, and enhancing driving experience.

[0180] It should be noted that when updating the efficiency data, the range of the changed variable needs to be limited to ensure that the efficiency after deviation compensation is between adjacent coordinates. If the data exceeds the limit, the endpoint data on both sides - set value q, q can be set to a very small value to ensure that the data does not exceed the range of the interval.

[0181] It should be noted that the updating of the entire deviation table is completed by updating the calibrated efficiency coefficient of the corresponding vehicle speed in the reference efficiency coefficient calibration table.

[0182] This embodiment calculates the current efficiency coefficient deviation based on the current efficiency coefficient and the calibrated efficiency coefficient; determines the angle interval of the current steering wheel angle based on the current steering wheel angle, and determines the speed interval of the current vehicle speed based on the current vehicle speed; obtains multiple steering wheel angles and multiple vehicle speeds within a cycle; when multiple steering wheel angles are all in the angle interval and multiple vehicle speeds are all in the speed interval, updates the calibrated efficiency coefficient in the efficiency coefficient calibration table based on the number of cycles, the angle interval, the vehicle speed interval, and the current efficiency coefficient deviation. By calculating the current efficiency coefficient deviation in real time and dynamically adjusting the calibrated efficiency coefficient based on the interval of the current steering wheel angle and vehicle speed, the vehicle response characteristics under actual driving conditions can be more accurately reflected, thereby improving the accuracy of the vehicle control system.

[0183] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the vehicle curve driving control method of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0184] This application also provides a vehicle curve driving control device, please refer to Figure 6 , the vehicle curve driving control device comprises:

[0185] The acquisition module 10 is used to acquire the current steering wheel angle, current vehicle speed and vehicle mass of the vehicle when the vehicle is in a curve.

[0186] The query module 20 is used to query the efficiency coefficient calibration table according to the current steering wheel angle, the current vehicle speed and the vehicle mass to obtain a calibrated efficiency coefficient.

[0187] The control module 30 is used to control the vehicle to drive on a curve based on the calibrated efficiency coefficient, and detect whether the efficiency coefficient self-learning condition of the driving force on the curve is triggered during the vehicle's driving on the curve.

[0188] The determination module 40 is used to determine the current efficiency coefficient according to the current driving data of the vehicle when the vehicle is traveling on the curve when the self-learning condition of the efficiency coefficient of the driving force on the curve is triggered.

[0189] The updating module 50 is used to update the calibrated efficiency coefficient in the efficiency coefficient calibration table according to the current efficiency coefficient.

[0190] The control module 30 is also used to control the vehicle's cornering by using the updated calibrated efficiency coefficient.

[0191] The vehicle curve driving control device provided by the present application adopts the vehicle curve driving control method in the above embodiment, which can solve the technical problem that the driving force of the vehicle control has deviation when the vehicle is driving on a curve, affecting the stability of the vehicle speed. Compared with the prior art, the beneficial effects of the vehicle curve driving control device provided by the present application are the same as the beneficial effects of the vehicle curve driving control method provided by the above embodiment, and the other technical features of the vehicle curve driving control device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0192] In one embodiment, the update module 50 is further used to calculate a current efficiency coefficient deviation based on the current efficiency coefficient and the calibrated efficiency coefficient; determine the angle range in which the current steering wheel angle is located based on the current steering wheel angle, and determine the speed range in which the current vehicle speed is located based on the current vehicle speed; obtain multiple steering wheel angles and multiple vehicle speeds within a cycle; and when multiple steering wheel angles are all in the angle range and multiple vehicle speeds are all in the speed range, update the calibrated efficiency coefficient in the efficiency coefficient calibration table based on the number of cycles, the angle range, the vehicle speed range and the current efficiency coefficient deviation.

[0193] In one embodiment, the update module 50 is further used to calculate the average steering wheel angle within the angle interval according to the multiple steering wheel angles and the number of cycles, and calculate the average vehicle speed within the speed interval according to the multiple vehicle speeds and the number of cycles when the multiple steering wheel angles are all within the angle interval and the multiple vehicle speeds are all within the vehicle speed interval; obtain a first angle and a second angle according to the angle interval, the first angle being smaller than the second angle; calculate a corner efficiency coefficient deviation through the first angle, the average steering wheel angle, the second angle and the current efficiency coefficient deviation; and update the calibrated efficiency coefficient in the efficiency coefficient calibration table based on the corner efficiency coefficient deviation, the vehicle speed interval and the current efficiency coefficient deviation.

[0194] In one embodiment, the update module 50 is also used to update the calibrated efficiency coefficient of the corresponding corner in the efficiency coefficient calibration table by using an inverse proportional distribution deviation method based on the corner efficiency coefficient deviation to obtain a reference efficiency coefficient calibration table; obtain a first vehicle speed and a second vehicle speed according to the vehicle speed range, the first vehicle speed being less than the second vehicle speed; calculate the vehicle speed efficiency coefficient deviation through the first vehicle speed, the second vehicle speed, the average vehicle speed, the first turning angle, the second turning angle and the current efficiency coefficient deviation; update the calibrated efficiency coefficient of the corresponding vehicle speed in the reference efficiency coefficient calibration table through the vehicle speed efficiency coefficient deviation to complete the update of the efficiency coefficient calibration table.

[0195] In one embodiment, the determination module 40 is also used to obtain the driving force, driving wind resistance, driving rolling resistance, driving slope resistance and driving acceleration resistance according to the current driving data of the vehicle when it is driving on the curve when the self-learning condition of the efficiency coefficient of the cornering driving force is triggered; obtain the relationship between the calibrated efficiency coefficient and the longitudinal power of the vehicle; and calculate the current efficiency coefficient according to the relationship, the driving force, the driving wind resistance, the driving rolling resistance, the driving slope resistance and the driving acceleration resistance.

[0196] In one embodiment, the device also includes a construction module, which is used to define the relationship between the efficiency coefficient and the longitudinal power of the vehicle; collect historical driving data of the vehicle when driving on different curves; obtain historical efficiency coefficient data of the vehicle when driving on different curves based on the historical driving data and the relationship; fit the historical efficiency coefficient data, and obtain influencing factors that affect the efficiency coefficient based on the fitting results, and the influencing factors include steering wheel angle, vehicle speed and vehicle mass; establish a mapping relationship between the efficiency coefficient and the steering wheel angle, vehicle speed and vehicle mass based on the historical steering wheel angle, historical vehicle speed, vehicle mass in the historical driving data and the historical efficiency coefficient data, and obtain an efficiency coefficient calibration table.

[0197] In one embodiment, the control module 30 is also used to obtain the relationship between the calibrated efficiency coefficient and the longitudinal power of the vehicle; obtain the current wind resistance, the current rolling resistance, the current ramp resistance and the current acceleration resistance; calculate the control driving force of the vehicle according to the calibrated efficiency coefficient, the relationship, the current wind resistance, the current rolling resistance, the current ramp resistance and the current acceleration resistance; and control the vehicle to travel on a curve according to the control driving force.

[0198] In one embodiment, the control module 30 is also used to obtain the steering wheel angle change rate when the vehicle is traveling on a curve; when the current steering wheel angle is greater than a preset angle threshold and the steering wheel angle change rate is less than a preset change rate threshold, determine the self-learning condition for triggering the efficiency coefficient of the curve driving force.

[0199] The present application provides a vehicle curve driving control device, which includes: at least one processor; and a memory that is communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the vehicle curve driving control method in the above-mentioned embodiment one.

[0200] Reference below Figure 7, which shows a schematic diagram of the structure of a vehicle curve driving control device suitable for implementing the embodiment of the present application. The vehicle curve driving control device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 7 The vehicle curve driving control device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0201] like Figure 7 As shown, the vehicle curve driving control device may include a processing device 1001 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to the program stored in ROM (Read Only Memory) 1002 or the program loaded from the storage device 1003 to RAM (Random Access Memory) 1004. In RAM 1004, various programs and data required for the operation of the vehicle curve driving control device are also stored. The processing device 1001, ROM 1002 and RAM 1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems may be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, an LCD (Liquid Crystal Display), a speaker, a vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication device 1009 may allow the vehicle curve driving control device to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows a vehicle curve driving control device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have alternatively.

[0202] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0203] The vehicle curve driving control device provided by the present application adopts the vehicle curve driving control method in the above embodiment, which can solve the technical problem that the driving force of the vehicle control has deviation when the vehicle is driving on a curve, affecting the stability of the vehicle speed. Compared with the prior art, the beneficial effects of the vehicle curve driving control device provided by the present application are the same as the beneficial effects of the vehicle curve driving control method provided by the above embodiment, and the other technical features of the vehicle curve driving control device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0204] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0205] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0206] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the vehicle curve driving control method in the above-mentioned embodiment.

[0207] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, RAM (Random Access Memory), ROM (Read Only Memory), EPROM (Erasable Programmable Read Only Memory, Erasable Programmable Read Only Memory or Flash Memory), optical fiber, CD-ROM (CD-Read Only Memory, portable compact disk read-only memory), optical storage device, magnetic storage device, or any suitable combination of the above. In the present embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0208] The computer-readable storage medium may be included in the vehicle curve driving control device; or may exist independently without being assembled into the vehicle curve driving control device.

[0209] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the vehicle curve driving control device, the vehicle curve driving control device: when the vehicle is in a curve, obtains the vehicle's current steering wheel angle, current vehicle speed and vehicle mass; queries the efficiency coefficient calibration table according to the current steering wheel angle, the current vehicle speed and the vehicle mass to obtain a calibrated efficiency coefficient; controls the vehicle to drive on the curve based on the calibrated efficiency coefficient, and detects whether the vehicle triggers a self-learning condition for the efficiency coefficient of the curve driving force during the curve driving process; when the self-learning condition for the efficiency coefficient of the curve driving force is triggered, determines the current efficiency coefficient according to the current driving data of the vehicle when driving on the curve; updates the calibrated efficiency coefficient in the efficiency coefficient calibration table according to the current efficiency coefficient; and controls the vehicle to drive on the curve according to the updated calibrated efficiency coefficient.

[0210] The computer program code for performing the operation of the present application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on the remote computer, or completely on the remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a LAN (Local Area Network) or a WAN (Wide Area Network), or it can be connected to an external computer (e.g., using an Internet service provider to connect through the Internet).

[0211] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0212] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0213] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned vehicle curve driving control method, and can solve the technical problem that the driving force of the vehicle control has deviations when the vehicle is driving on a curve, which affects the stability of the vehicle speed. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the vehicle curve driving control method provided by the above-mentioned embodiment, and will not be repeated here.

[0214] The present application also provides a computer program product, including a computer program, which implements the steps of the vehicle curve driving control method as described above when the computer program is executed by a processor.

[0215] The computer program product provided by the present application can solve the technical problem that the driving force of the vehicle control has deviations when the vehicle is traveling on a curve, which affects the stability of the vehicle speed. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as the beneficial effects of the vehicle curve driving control method provided by the above embodiment, and will not be elaborated here.

[0216] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A vehicle curve driving control method, characterized in that: The vehicle curve driving control method comprises: When the vehicle is on a curve, obtain the vehicle's current steering wheel angle, current speed, and vehicle mass; According to the current steering wheel angle, the current vehicle speed and the vehicle mass, an efficiency coefficient calibration table is searched to obtain a calibration efficiency coefficient; Controlling the vehicle to drive on a curve based on the calibrated efficiency coefficient, and detecting whether a self-learning condition of the efficiency coefficient of the driving force of the curve is triggered during the vehicle's driving on the curve; When the efficiency coefficient self-learning condition of the driving force on a curve is triggered, the current efficiency coefficient is determined according to the current driving data of the vehicle when driving on the curve; Updating the calibrated efficiency coefficient in the efficiency coefficient calibration table by using the current efficiency coefficient; The vehicle is controlled on curves using the updated calibrated efficiency coefficient.

2. The method according to claim 1, characterized in that The step of updating the calibrated efficiency coefficient in the efficiency coefficient calibration table by using the current efficiency coefficient comprises: Calculating a current efficiency coefficient deviation according to the current efficiency coefficient and the calibrated efficiency coefficient; Determining the angle interval of the current steering wheel angle according to the current steering wheel angle, and determining the speed interval of the current vehicle speed according to the current vehicle speed; Get multiple steering wheel angles and multiple vehicle speeds within a cycle; When the plurality of steering wheel angles are within the angle interval and the plurality of vehicle speeds are within the vehicle speed interval, the calibrated efficiency coefficient in the efficiency coefficient calibration table is updated according to the cycle number, the angle interval, the vehicle speed interval and the current efficiency coefficient deviation.

3. The method according to claim 2, characterized in that The step of updating the calibrated efficiency coefficient in the efficiency coefficient calibration table according to the number of cycles, the angle interval, the vehicle speed interval and the current efficiency coefficient deviation when the plurality of steering wheel angles are all within the angle interval and the plurality of vehicle speeds are all within the vehicle speed interval comprises: When the plurality of steering wheel angles are within the angle interval and the plurality of vehicle speeds are within the vehicle speed interval, calculating an average steering wheel angle within the angle interval according to the plurality of steering wheel angles and cycle numbers, and calculating an average vehicle speed within the vehicle speed interval according to the plurality of vehicle speeds and cycle numbers; Obtaining a first angle and a second angle according to the angle interval, wherein the first angle is smaller than the second angle; calculating a corner efficiency coefficient deviation by using the first corner angle, the average steering wheel angle, the second corner angle, and the current efficiency coefficient deviation; The calibrated efficiency coefficient in the efficiency coefficient calibration table is updated based on the corner efficiency coefficient deviation, the vehicle speed range, and the current efficiency coefficient deviation.

4. The method according to claim 3, characterized in that The step of updating the calibrated efficiency coefficient in the efficiency coefficient calibration table based on the corner efficiency coefficient deviation, the vehicle speed range and the current efficiency coefficient deviation comprises: Based on the corner efficiency coefficient deviation, the calibrated efficiency coefficient of the corresponding corner in the efficiency coefficient calibration table is updated by using an inverse proportional distribution deviation method to obtain a reference efficiency coefficient calibration table; Obtaining a first vehicle speed and a second vehicle speed according to the vehicle speed interval, wherein the first vehicle speed is less than the second vehicle speed; Calculating a vehicle speed efficiency coefficient deviation by using the first vehicle speed, the second vehicle speed, the average vehicle speed, the first turning angle, the second turning angle, and the current efficiency coefficient deviation; The calibrated efficiency coefficient of the corresponding vehicle speed in the reference efficiency coefficient calibration table is updated by using the vehicle speed efficiency coefficient deviation to complete the updating of the efficiency coefficient calibration table.

5. The method according to claim 1, characterized in that When the self-learning condition of the efficiency coefficient of the driving force on a curve is triggered, the step of determining the current efficiency coefficient according to the current driving data of the vehicle when driving on the curve comprises: When the self-learning condition of the efficiency coefficient of the curve driving force is triggered, the driving driving force, the driving wind resistance, the driving rolling resistance, the driving slope resistance and the driving acceleration resistance are obtained according to the current driving data of the vehicle when driving on the curve; Obtain the relationship between the calibrated efficiency coefficient and the longitudinal dynamics of the vehicle; A current efficiency coefficient is calculated based on the relationship, the running drive force, the running wind resistance, the running rolling resistance, the running slope resistance, and the running acceleration resistance.

6. The method according to claim 1, characterized in that The steps to construct the efficiency coefficient calibration table include: Define the relationship between the efficiency coefficient and the longitudinal dynamics of the vehicle; Collect historical driving data of vehicles when driving on different curves; Obtaining historical efficiency coefficient data of the vehicle when traveling on different curves according to the historical driving data and the relationship; Fitting the historical efficiency coefficient data, and obtaining influencing factors affecting the efficiency coefficient according to the fitting results, wherein the influencing factors include steering wheel angle, vehicle speed and vehicle mass; A mapping relationship between the efficiency coefficient and the steering wheel angle, the vehicle speed and the vehicle mass is established based on the historical steering wheel angle, the historical vehicle speed, the vehicle mass and the historical efficiency coefficient data in the historical driving data to obtain an efficiency coefficient calibration table.

7. The method according to claim 1, characterized in that The step of controlling the vehicle to drive on a curve based on the calibrated efficiency coefficient comprises: Obtain the relationship between the calibrated efficiency coefficient and the longitudinal dynamics of the vehicle; Get the current wind resistance, current rolling resistance, current ramp resistance and current acceleration resistance; calculating a control driving force of the vehicle according to the calibrated efficiency coefficient, the relationship, the current wind resistance, the current rolling resistance, the current ramp resistance, and the current acceleration resistance; The vehicle is controlled to travel on a curve according to the controlled driving force.

8. The method according to any one of claims 1 to 6, characterized in that The steps of detecting whether the efficiency coefficient self-learning condition of the curve driving force is triggered during the curve driving process of the vehicle include: When the vehicle is driving on a curve, the steering wheel angle change rate is obtained; When the current steering wheel angle is greater than a preset angle threshold and the steering wheel angle change rate is less than a preset change rate threshold, a self-learning condition for triggering the efficiency coefficient of the curve driving force is determined.

9. A vehicle curve driving control device, characterized in that: The device comprises: An acquisition module is used to acquire the current steering wheel angle, current vehicle speed and vehicle mass of the vehicle when the vehicle is in a curve; A query module, configured to query an efficiency coefficient calibration table according to the current steering wheel angle, the current vehicle speed and the vehicle mass to obtain a calibrated efficiency coefficient; a control module, configured to control the vehicle to drive on a curve based on the calibrated efficiency coefficient, and detect whether a self-learning condition of the efficiency coefficient of the driving force of the curve is triggered during the vehicle's driving on the curve; A determination module, for determining a current efficiency coefficient according to current driving data of the vehicle when driving on the curve when a self-learning condition for the efficiency coefficient of the driving force on the curve is triggered; An updating module, configured to update the calibrated efficiency coefficient in the efficiency coefficient calibration table by using the current efficiency coefficient; The control module is also used to control the vehicle's cornering driving through the updated calibrated efficiency coefficient.

10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the vehicle curve driving control method as described in any one of claims 1 to 8 are implemented.

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