An Adaptive Coasting Feedback Intensity Control System and Control Method for Electric Vehicles

Abstract

The present invention discloses an electric vehicle adaptive coasting feedback intensity control system, which includes: a judgment module for detecting whether the current vehicle state is in a coasting feedback stable state; a trigger module for generating a trigger instruction for dynamically adjusting the coasting feedback intensity when the current vehicle state is in a coasting feedback stable state and meets the dynamic adjustment condition of the coasting feedback intensity; a collection module for collecting coasting parameter information within a preset sampling period according to the trigger instruction; a processing module for calculating a target coasting feedback intensity b according to the coasting parameter information; and a feedback correction module for correcting the target feedback torque according to the vehicle driving equation and the target coasting feedback intensity b. The present invention collects information such as the driver's throttle pedal, brake pedal, steering wheel angle, road gradient, and vehicle speed, so as to analyze the driver's demand to obtain the coasting feedback intensity, realize the real-time adjustment of the coasting feedback intensity, and achieve the coasting deceleration feeling required by the driver.

Description

Technical Field

[0001] The present invention relates to the field of vehicle control technology, and particularly to an electric vehicle adaptive coasting feedback intensity control system and its control method. Background Art

[0002] At present, the coasting feedback intensity of a vehicle is determined by calibration and matching by the vehicle manufacturer. When the vehicle decelerates and coasts, the motor executes the pre-calibrated and matched motor torque to reflect a certain deceleration intensity. Many vehicles provide two or more different levels of energy feedback for the driver to choose. After the driver selects a certain level of feedback, the vehicle will decelerate according to the pre-matched motor torque in the program. There is also a way to adjust the deceleration intensity by adding an additional feedback torque on the basis of the basic feedback torque. This additional feedback torque needs to be manually set by the driver through a joystick. At the same time, the existing technology for adjusting the coasting feedback intensity requires manual operation by the driver to select, and the selectable intensities are not continuous, and the number of selectable options is limited. Too few settings cannot meet the diverse needs of different drivers, and too many settings are cumbersome. It is difficult for the driver to find a suitable feedback intensity, which is not intelligent enough. Summary of the Invention

[0003] The present invention aims at one or more of the above existing problems, and provides an electric vehicle adaptive coasting feedback intensity control system and its control method.

[0004] According to one aspect of the present invention, there is provided an electric vehicle adaptive coasting feedback intensity control system, comprising:

[0005] A judgment module, configured to detect whether the current vehicle state is in a stable coasting feedback state;

[0006] A trigger module, configured to generate a trigger instruction for dynamically adjusting the coasting feedback intensity when the current vehicle state is in a stable coasting feedback state and meets the conditions for dynamic adjustment of the coasting feedback intensity;

[0007] An acquisition module, configured to acquire coasting parameter information within a plurality of preset sampling periods according to the trigger instruction;

[0008] A processing module, configured to calculate a target coasting feedback intensity b according to a plurality of coasting parameter information;

[0009] A feedback correction module, configured to correct the target feedback torque according to the vehicle driving equation and the target coasting feedback intensity b.

[0010] In some implementable ways, the processing module includes:

[0011] A first calculation unit, configured to calculate a real-time dynamic adjustment coefficient λ for each preset sampling period according to a plurality of coasting parameter information;

[0012] A second calculation unit for calculating the average acceleration a of the vehicle within each sampling period 平均 and the average value λ of the dynamic adjustment coefficient 平均 ;

[0013] A comparison unit for comparing the obtained average acceleration a of each sampling period 平均 with a preset target coasting feedback acceleration to obtain a plurality of differences δa;

[0014] A generation unit for, when the signs of the acceleration differences δa obtained through multiple calculations are the same, taking the arithmetic mean of the products of the acceleration differences δa obtained through multiple calculations and the corresponding average values λ of the dynamic adjustment coefficient 平均 as the target intensity adjustment requirement value;

[0015] A processing unit for adding the obtained target intensity adjustment requirement value to the currently collected feedback intensity to generate a target coasting feedback intensity b.

[0016] In some realizable ways, the calculation formula for the real-time dynamic adjustment coefficient λ is: λ = (1 - Min(Ap, 0.1) * 10) * (1 - Min(Bp, 0.1) * 10) * (1 - Min(I, 0.1) * 10) * (1 - Min(|θ|, 90) / 90), where λ is the dynamic adjustment coefficient; Ap is the collected accelerator pedal opening, Bp is the brake pedal opening, I is the road gradient, and θ is the steering wheel angle.

[0017] In some realizable ways, the processing module further includes a judgment unit for detecting whether the target coasting feedback intensity b satisfies the range of a preset standard coasting feedback intensity.

[0018] In some realizable ways, the feedback correction module includes:

[0019] A collection unit for collecting the road gradients passed by the vehicle within a plurality of sampling periods and obtaining their arithmetic mean i;

[0020] An operation unit for calculating the driving force F of the vehicle by using the obtained average road gradient i, where F = mb + Gsin(tan －1 i) + Gcos(tan －1 i) + C D AV 2 / 21.15, m is the vehicle mass, G is the vehicle gravity, C D is the air resistance coefficient, A is the vehicle frontal area, and V is the vehicle speed;

[0021] A correction unit that corrects the feedback torque T according to the vehicle driving equation and the driving force correction target, where the vehicle driving equation is T = Fr / i g i0n T , r is the wheel rolling radius, i g is the transmission ratio, i0 is the final drive ratio, n T is the transmission efficiency.

[0022] In a second aspect, the present invention provides an electric vehicle adaptive coasting feedback intensity control method, including the following steps:

[0023] Detect whether the current vehicle state is in a coasting feedback stable state;

[0024] When the current vehicle state is in a coasting feedback stable state and meets the coasting feedback intensity dynamic adjustment condition, generate a trigger command for dynamic adjustment of the coasting feedback intensity;

[0025] Collect coasting parameter information within multiple preset sampling periods according to the trigger command;

[0026] Calculate the target coasting feedback intensity b using the obtained multiple coasting parameter information;

[0027] Correct the target feedback torque according to the vehicle driving equation and the target coasting feedback intensity b.

[0028] In some implementable ways, the calculating the target coasting feedback intensity b using the obtained coasting parameter information includes the following steps:

[0029] Calculate the real-time dynamic adjustment coefficient λ for each sampling period according to the coasting parameter information;

[0030] Calculate the average acceleration a of the vehicle within each sampling period 平均 and the average value of the dynamic adjustment coefficient λ 平均 ;

[0031] Compare the average acceleration a obtained for each sampling period 平均 with the preset target coasting feedback acceleration to obtain the difference δa;

[0032] When the signs of the acceleration differences δa obtained from multiple calculations are the same, take the arithmetic mean of the products of the acceleration differences δa obtained from multiple calculations and the corresponding average values of the dynamic adjustment coefficient λ 平均 as the target intensity adjustment demand value;

[0033] Add the obtained target intensity adjustment demand value to the currently collected feedback intensity to generate the target coasting feedback intensity b.

[0034] In some realizable ways, the calculation formula for the real-time dynamic adjustment coefficient λ is: λ = (1 - Min(Ap, 0.1) * 10) * (1 - Min(Bp, 0.1) * 10) * (1 - Min(I, 0.1) * 10) * (1 - Min(|θ|, 90) / 90), where λ is the dynamic adjustment coefficient; Ap is the collected accelerator pedal opening, Bp is the brake pedal opening, I is the road gradient, and θ is the steering wheel angle.

[0035] In some realizable ways, correcting the target feedback torque according to the vehicle driving equation and the target coasting feedback strength b includes the following steps:

[0036] Collect the road gradients passed by the vehicle within multiple sampling periods and obtain their arithmetic mean i;

[0037] Calculate the driving force F of the vehicle using the obtained average road gradient i, where F = mb + Gsin(tan －1 i) + Gcos(tan －1 i) + C D AV 2 / 21.15, where m is the vehicle mass, G is the vehicle gravity, C D is the air resistance coefficient, A is the vehicle frontal area, and V is the vehicle speed;

[0038] Correct the target feedback torque T according to the vehicle driving equation and the driving force, where the vehicle driving equation is T = Fr / i g i0n T , r is the wheel rolling radius, i g is the transmission ratio, i0 is the final drive ratio, and n T is the transmission efficiency.

[0039] In a third aspect, the present invention also provides a terminal, including: at least one processor; and a memory storing program instructions, where the program instructions are configured to be executed by the at least one processor, and the program instructions include instructions for executing the above-mentioned method for controlling the coasting feedback strength of an electric vehicle adaptively.

[0040] The beneficial effects of the present invention are:

[0041] The control system provided by the present invention calculates the real-time dynamic adjustment coefficient λ of the preset sampling period according to the coasting parameter information through the first calculation unit, and the second calculation unit calculates the average acceleration a of the vehicle within the sampling period 平均 and the average value λ of the dynamic adjustment coefficient 平均 , and the comparison unit compares the obtained average acceleration a 平均Compare with the preset target coasting feedback acceleration to obtain the difference δa. When the signs of the acceleration differences δa obtained by the generating unit in multiple calculations are the same, the arithmetic mean of the product of the acceleration differences δa obtained in multiple calculations and the average value of the dynamic adjustment coefficient is used as the target intensity adjustment requirement value. The processing unit adds the obtained target intensity adjustment requirement value to the currently collected feedback intensity to generate the target coasting feedback intensity b. Thus, in this embodiment, the real-time adjustment of the coasting feedback intensity can be realized to achieve the coasting deceleration feeling required by the driver; by collecting information such as the driver's throttle pedal, brake pedal, steering wheel angle, road gradient, and vehicle speed, the driver's demand is analyzed to obtain the coasting feedback intensity. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 FIG. is a schematic diagram of the principle structure of an adaptive coasting feedback intensity control system for an electric vehicle according to the present invention;

[0043] Figure 2 FIG. is a schematic diagram of the structure of an embodiment of a processing module of an adaptive coasting feedback intensity control system for an electric vehicle according to the present invention;

[0044] Figure 3 FIG. is a schematic diagram of the structure of another embodiment of a processing module of an adaptive coasting feedback intensity control system for an electric vehicle according to the present invention;

[0045] Figure 4 FIG. is a schematic diagram of the structure of an embodiment of a feedback correction module of an adaptive coasting feedback intensity control system for an electric vehicle according to the present invention;

[0046] Figure 5 FIG. is a schematic diagram of the flow of an embodiment of an adaptive coasting feedback intensity control method for an electric vehicle according to the present invention;

[0047] Figure 6 FIG. is a schematic diagram of the flow of another embodiment of an adaptive coasting feedback intensity control method for an electric vehicle according to the present invention;

[0048] Figure 7 FIG. is a schematic diagram of the flow of another embodiment of an adaptive coasting feedback intensity control method for an electric vehicle according to the present invention.

[0049] Through the above-mentioned drawings, the clear embodiments of the present disclosure have been shown, and there will be more detailed descriptions hereinafter. These drawings and the textual descriptions are not intended to limit the scope of the concept of the present disclosure in any way, but to illustrate the concept of the present disclosure to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0050] The technical solutions of the application will be further described in detail below with reference to the drawings.

[0051] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0052] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which this invention belongs. The terms used in the description of the present invention herein are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the associated listed items.

[0053] The following will describe in detail some embodiments of the present invention with reference to the accompanying drawings. Without conflict, the following embodiments and the features in the embodiments may be combined with each other. For the same or similar concepts or processes, they may not be repeated in some embodiments.

[0054] Embodiment 1

[0055] Figure 1 It is a schematic structural diagram of an electric vehicle adaptive coasting feedback intensity control system provided by an embodiment of the present invention; this embodiment provides an electric vehicle adaptive coasting feedback intensity control system, including:

[0056] A judgment module 1, configured to detect whether the current vehicle state is in a stable coasting feedback state;

[0057] A trigger module 2, configured to generate a trigger instruction for dynamically adjusting the coasting feedback intensity when the current vehicle state is in a stable coasting feedback state and meets the conditions for dynamically adjusting the coasting feedback intensity;

[0058] An acquisition module 3, configured to acquire coasting parameter information within a plurality of preset sampling periods according to the trigger instruction; specifically, after entering the dynamic adjustment of the coasting feedback intensity, the actual torque of the motor and signals such as the accelerator pedal are detected in real time. When the accelerator pedal is depressed and the actual torque of the motor is greater than a preset reference value for a continuous period of time, it is a sampling period. At the same time, it is also possible to wait until the conditions for dynamically adjusting the coasting feedback are met again and then sample again.

[0059] A processing module 4, configured to calculate the target coasting feedback intensity b according to a plurality of coasting parameter information;

[0060] A feedback correction module 5, configured to correct the target feedback torque according to the vehicle driving equation and the target coasting feedback intensity b.

[0061] The electric vehicle adaptive coasting feedback intensity control system provided in this embodiment uses a judgment module to detect whether the current vehicle state is in a stable coasting feedback state. When the current vehicle state is in a stable coasting feedback state and meets the conditions for dynamic adjustment of the coasting feedback intensity, a trigger module generates a trigger command for dynamically adjusting the coasting feedback intensity. Then, a collection module collects coasting parameter information within a preset sampling period according to the trigger command, a processing module calculates the target coasting feedback intensity b based on the coasting parameter information, and a feedback correction module corrects the target feedback torque according to the vehicle driving equation and the target coasting feedback intensity b. Thus, in this embodiment, when the current vehicle state is in a stable coasting feedback state and meets the conditions for dynamic adjustment of the coasting feedback intensity, a trigger command for dynamically adjusting the coasting feedback intensity is generated, and the target feedback torque is corrected in real time according to the vehicle driving equation and the calculated target coasting feedback intensity b, so as to realize the real-time adjustment of the coasting feedback intensity and achieve the coasting deceleration feeling required by the driver.

[0062] Preferably, the judgment module 1 is used to detect whether the current vehicle state is in a stable coasting feedback state. The judgment module includes a first detection unit and a second detection unit. The first detection unit is used to detect whether both the brake pedal and the accelerator pedal are not depressed in the current driving gear, and the second detection unit is used to detect the percentage of the actual feedback torque of the motor reaching the preset current target feedback torque when both the brake pedal and the accelerator pedal are not depressed in the current driving gear. Normally, at the same time, during the driving process of the vehicle, the signals of the current accelerator pedal, brake pedal, gear, vehicle speed, and steering wheel angle are detected. When both the brake pedal and the accelerator pedal are not depressed in the current driving gear and the actual feedback torque of the motor reaches more than 95% of the current target feedback torque, it is considered that the whole vehicle enters the stable coasting feedback state.

[0063] Preferably, meeting the conditions for dynamic adjustment of the coasting feedback intensity means that during the driving process of the vehicle, the collected steering wheel angle is less than a preset value, the vehicle speed is within a preset range, and the road slope is less than a preset value. For example: the steering wheel angle is within the range of ±90°, the vehicle speed is within the range of 10 - 160 km / h, and the road slope is less than 10%. When all the above conditions are met, it is considered to meet the conditions for dynamic adjustment of the coasting feedback intensity. Thus, the correction process is safer and more reliable, avoiding damage to vehicle components and causing some unsafe situations during the correction process in other cases.

[0064] Embodiment 2

[0065] As a feasible way, based on the above embodiment and referring to Appendix Figure 2 -4, it can be seen that in order to further improve the reliability of the electric vehicle adaptive coasting feedback intensity control system, the processing module 4 includes:

[0066] The first calculation unit 41 is configured to calculate a real-time dynamic adjustment coefficient λ for each preset sampling period according to a plurality of coasting parameter information;

[0067] The second calculation unit 42 is configured to calculate an average acceleration a of the vehicle within each preset sampling period 平均 and an average value λ of the dynamic adjustment coefficient 平均 ;

[0068] The comparison unit 43 is configured to compare the obtained average acceleration a of each preset sampling period 平均 with a preset target coasting feedback acceleration to obtain a plurality of differences δa;

[0069] The generation unit 44 is configured to, when the signs of the acceleration differences δa obtained by multiple calculations are the same, take the arithmetic mean of the product of each calculated acceleration difference δa and the corresponding average value λ of the dynamic adjustment coefficient 平均 as the target intensity adjustment requirement value; for example, δa1 is collected in the first time sampling period, δa2 is collected in the second time sampling period, and δa3 is collected in the third time sampling period. If the signs of these three values are the same, then take the arithmetic mean of the product of the acceleration differences δa obtained by multiple calculations and the corresponding average value λ of the dynamic adjustment coefficient 平均 as the target intensity adjustment requirement value

[0070] The processing unit 45 is configured to add the obtained target intensity adjustment requirement value to the currently collected feedback intensity to generate a target coasting feedback intensity b.

[0071] The calculation formula for calculating the real-time dynamic adjustment coefficient λ is: λ = (1 - Min(Ap, 0.1) * 10) * (1 - Min(Bp, 0.1) * 10) * (1 - Min(I, 0.1) * 10) * (1 - Min(|θ|, 90) / 90), where λ is the dynamic adjustment coefficient; Ap is the collected accelerator pedal opening, Bp is the brake pedal opening, I is the road gradient, and θ is the steering wheel angle.

[0072] As Figure 3 shown, the processing module 4 further includes a judgment unit 46, and the judgment unit is configured to detect whether the target coasting feedback intensity b satisfies the range of the preset standard coasting feedback intensity.

[0073] As Figure 4 shown, the feedback correction module includes: a collection unit configured to collect the road gradient passed by the vehicle within a plurality of sampling periods and obtain its arithmetic mean value i;

[0074] An operation unit configured to calculate the driving force F of the vehicle by using the obtained road gradient average value i, where F = mb + Gsin(tan －1 i) + Gcos(tan－1 i)+C D AV 2 / 21.15, where m is the vehicle mass, G is the vehicle gravity, C D is the air resistance coefficient, A is the vehicle frontal area, and V is the vehicle speed;

[0075] A correction unit that, based on the vehicle driving equation and the driving force correction target, feeds back the torque T. Among them, the vehicle driving equation is T = Fr / i g i0n T , r is the wheel rolling radius, i g is the transmission ratio, i0 is the final drive ratio, n T is the transmission efficiency.

[0076] In the electric vehicle adaptive coasting feedback intensity control system provided in this embodiment, the first calculation unit calculates the real-time dynamic adjustment coefficient λ of the preset sampling period according to the coasting parameter information, and the second calculation unit calculates the average acceleration a of the vehicle within the sampling period 平均 and the average value λ of the dynamic adjustment coefficient 平均 . The comparison unit compares the obtained average acceleration a 平均 with the preset target coasting feedback acceleration to obtain the difference δa. When the signs of the acceleration differences δa obtained from multiple calculations are the same, the generating unit takes the arithmetic mean of the product of the acceleration differences δa obtained from multiple calculations and the average value of the dynamic adjustment coefficient as the target intensity adjustment demand value. The processing unit adds the obtained target intensity adjustment demand value to the currently collected feedback intensity to generate the target coasting feedback intensity b. Thus, in this embodiment, the real-time adjustment of the coasting feedback intensity can be realized to achieve the coasting deceleration feeling required by the driver; by collecting information such as the driver's throttle pedal, brake pedal, steering wheel angle, road gradient, and vehicle speed, the driver's demand is analyzed to obtain the coasting feedback intensity.

[0077] Embodiment III

[0078] Figure 5 is a schematic flowchart of a method for controlling the adaptive coasting feedback intensity of an electric vehicle provided in an embodiment of the present invention; this embodiment provides a method for controlling the adaptive coasting feedback intensity of an electric vehicle. The execution subject of this method for controlling the adaptive coasting feedback intensity of an electric vehicle can be the control of the adaptive coasting feedback intensity of an electric vehicle. Specifically, it includes the following steps:

[0079] S100. Detect whether the current vehicle state is in the coasting feedback stable state;

[0080] S200. When the current vehicle state is in the coasting feedback stable state and meets the dynamic adjustment condition of the coasting feedback intensity, generate a trigger command for dynamically adjusting the coasting feedback intensity;

[0081] S300. Collect the coasting parameter information within multiple preset sampling periods according to the trigger instruction;

[0082] S400. Calculate the target coasting feedback intensity b by using the obtained coasting parameter information;

[0083] S500. Correct the target feedback torque T according to the vehicle driving equation and the target coasting feedback intensity b.

[0084] The control method provided in this embodiment detects whether the current vehicle state is in the coasting feedback stable state. When it is detected that the coasting feedback intensity dynamic adjustment condition is met under the condition that the current vehicle state is in the coasting feedback stable state, a trigger instruction for dynamically adjusting the coasting feedback intensity is generated. The coasting parameter information within each preset sampling period is collected according to the trigger instruction, and the target coasting feedback intensity b is calculated by using the obtained coasting parameter information; the target feedback torque is corrected according to the vehicle driving equation and the target coasting feedback intensity b. Thus, this method can realize the real-time adjustment of the coasting feedback intensity, achieve the coasting deceleration feeling required by the driver, obtain the coasting feedback intensity by analyzing the driver's demand, and gradually correct the target feedback torque T through the obtained coasting feedback intensity and the vehicle driving equation, better meeting the control requirements of the driver for the coasting vehicle speed, and improving the control safety and controllability of the electric vehicle's adaptive coasting feedback intensity.

[0085] Embodiment Four

[0086] As an implementable manner, based on the above embodiment and referring to Figure 6 -7, it can be seen that in step S400, calculating the target coasting feedback intensity b by using the obtained coasting parameter information includes the following steps:

[0087] S401. Calculate the real-time dynamic adjustment coefficient λ for each sampling period according to the coasting parameter information; the calculation formula for calculating the real-time dynamic adjustment coefficient λ is: λ = (1 - Min(Ap, 0.1) * 10) * (1 - Min(Bp, 0.1) * 10) * (1 - Min(I, 0.1) * 10) * (1 - Min(|θ|, 90) / 90), where λ is the dynamic adjustment coefficient; Ap is the collected accelerator pedal opening, Bp is the brake pedal opening, I is the road gradient, and θ is the steering wheel angle.

[0088] S402. Calculate the average acceleration a of the vehicle within each preset sampling period 平均 and the average value of the dynamic adjustment coefficient λ 平均 ; specifically, it includes calculating the average acceleration according to the acceleration a of the vehicle within the collected sampling period, and calculating the average value of the dynamic adjustment coefficient λ according to the collected real-time dynamic adjustment coefficient λ 平均 ;

[0089] S403. Compare the average acceleration a obtained in each sampling period with a preset target coasting feedback acceleration to obtain a plurality of differences δa; 平均

[0090] S404. When the signs of the calculated plurality of acceleration differences δa are the same, take the arithmetic mean of the product of the calculated acceleration differences δa and the average value λ of the dynamic adjustment coefficient as the target intensity adjustment demand value; 平均

[0091] S405. Add the obtained target intensity adjustment demand value to the currently collected feedback intensity to generate the target coasting feedback intensity b.

[0092] As shown in the figure, in step S405, according to the vehicle driving equation and the target coasting feedback intensity b, the target feedback torque is corrected, including the following steps: Figure 7

[0093] S4051. Collect the road slope passed by the vehicle in a plurality of sampling periods and obtain its arithmetic mean value i;

[0094] S4052. Calculate the driving force F of the vehicle by using the obtained average road slope value i, where F = mb + Gsin(tan －1 i) + Gcos(tan －1 i) + C D AV 2 / 21.15, m is the vehicle mass, G is the vehicle gravity, C D is the air resistance coefficient, A is the vehicle frontal area, and V is the vehicle speed;

[0095] S4053. Correct the target feedback torque T according to the vehicle driving equation and the driving force, where the vehicle driving equation is T = Fr / i g i0n T g , r is the wheel rolling radius, i T is the transmission ratio, i0 is the final drive ratio, and n 平均 is the transmission efficiency. 平均

[0096] The control method provided in this embodiment obtains the real-time dynamic adjustment coefficient λ by collecting the accelerator pedal opening Ap, the brake pedal opening Bp, the road slope I, and the steering wheel angle θ, calculates the average value λ of the dynamic adjustment coefficient through the real-time dynamic adjustment coefficient λ, and when the signs of the calculated plurality of acceleration differences δa are the same, takes the arithmetic mean of the product of the calculated acceleration differences δa and the average value λ of the dynamic adjustment coefficient as the target intensity adjustment demand value, thereby calculating and generating the target coasting feedback intensity b, through T = Fr / i g ​​​​​i0n T and F = mb + Gsin(tan －1 i) + Gcos(tan －1 i) + C D AV 2 / 21.15 to correct the target feedback torque T.

[0097] Embodiment Five

[0098] The present invention further provides a terminal, including: at least one processor; and a memory storing program instructions, wherein the program instructions are configured to be executed by at least one processor, and the program instructions include instructions for executing the above-mentioned coasting feedback intensity control method.

[0099] The electric vehicle adaptive coasting feedback intensity control method shown in this embodiment can be executed in the Figure 1 or Figure 2 control system in the shown embodiments, and its implementation principle and technical effects are the same, so details are not described herein again.

[0100] An embodiment of the present invention further provides a storage medium, including: a readable storage medium and a computer program, the computer program is stored on the readable storage medium, and the computer program is used to implement the electric vehicle adaptive coasting feedback intensity control method in the above-mentioned embodiments.

[0101] An embodiment of the present invention further provides a program product, which includes: a computer program (i.e., execution instructions), and the computer program is stored in a readable storage medium. At least one processor of the encoding device can read the computer program from the readable storage medium, and at least one processor executes the computer program so that the encoding device implements the creep vehicle speed control method provided by the foregoing various implementation manners.

[0102] Those of ordinary skill in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The foregoing program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps including the above-mentioned method embodiments; and the foregoing storage medium includes: various media such as ROM, RAM, magnetic disk or optical disk that can store program codes.

[0103] Finally, it should be noted that: the above-mentioned embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention.

[0104] The above are only some embodiments of the present invention. For those of ordinary skill in the art, without departing from the creative concept of the present invention, several modifications and improvements can still be made, and these all fall within the protection scope of the present invention.

Claims

1. An adaptive coasting feedback intensity control system for an electric vehicle, characterized in that, Including: A judgment module (1) for detecting whether the current vehicle state is in a stable coasting feedback state; A trigger module (2) for generating a trigger instruction for dynamically adjusting the coasting feedback intensity when the current vehicle state is in a stable coasting feedback state and meets the conditions for dynamically adjusting the coasting feedback intensity; An acquisition module (3) for acquiring coasting parameter information within multiple preset sampling periods according to the trigger instruction; A processing module (4) for calculating a target coasting feedback intensity b based on the multiple coasting parameter information; A feedback correction module (5) for correcting the target feedback torque T according to the vehicle driving equation and the target coasting feedback intensity b; The processing module (4) includes: A first calculation unit (41) for calculating a real-time dynamic adjustment coefficient λ for each preset sampling period according to the multiple coasting parameter information; A second calculation unit (42) for calculating the average acceleration a of the vehicle in each sampling period 平均 and the average value λ of the dynamic adjustment coefficient 平均 ; A comparison unit (43) for comparing the average acceleration a obtained for each preset sampling period 平均 with a preset target coasting feedback acceleration to obtain a plurality of differences δa; A generating unit (44) is configured to, when the signs of the acceleration differences δa obtained through multiple calculations are the same, use the arithmetic mean of the products of the multiple calculated acceleration differences δa and the corresponding average value λ of the dynamically adjusted coefficients 平均 as the target intensity adjustment requirement value; A processing unit (45) for adding the obtained target intensity adjustment demand value to the currently acquired feedback intensity to generate the target coasting feedback intensity b; The formula for calculating the real-time dynamic adjustment coefficient λ is: λ = (1 - Min(Ap, 0.1) * 10) * (1 - Min(Bp, 0.1) * 10) * (1 - Min(I, 0.1) * 10) * (1 - Min(|θ|, 90) / 90), where λ is the dynamic adjustment coefficient; Ap is the acquired accelerator pedal opening, Bp is the brake pedal opening, I is the road gradient, and θ is the steering wheel angle.

2. The adaptive coasting feedback intensity control system for an electric vehicle according to claim 1, wherein The processing module further includes a judgment unit (46), and the judgment unit is used to detect whether the target coasting feedback intensity b meets the range of the preset standard coasting feedback intensity.

3. An electric vehicle adaptive coasting feedback intensity control system according to claim 1, characterized in that, The feedback correction module (5) includes: An acquisition unit (51) for acquiring the road gradient passed by the vehicle within multiple preset sampling periods and obtaining its arithmetic mean value i; An operation unit (52) is configured to calculate the driving force F of the vehicle by using the obtained average road slope i, where F = mb + Gsin(tan -1 i) + Gcos(tan -1 i) + C D AV 2 / 21.15, m is the vehicle mass, G is the vehicle gravity, C D is the air resistance coefficient, A is the vehicle frontal area, and V is the vehicle speed; A correction unit (53) corrects the feedback torque T according to the vehicle driving equation and the driving force correction target. Among them, the vehicle driving equation is T = Fr / i g i0n T , where r is the wheel rolling radius, and i g is the transmission ratio, i0 is the final drive ratio, and n T is the transmission efficiency.

4. An adaptive coasting feedback intensity control method for an electric vehicle, characterized in that, Including the following steps: Detecting whether the current vehicle state is in a stable coasting feedback state; When the current vehicle state is in a stable coasting feedback state and meets the conditions for dynamically adjusting the coasting feedback intensity, generating a trigger instruction for dynamically adjusting the coasting feedback intensity; Acquiring coasting parameter information within each preset sampling period according to the trigger instruction; Calculating the target coasting feedback intensity b by using the acquired coasting parameter information; Correcting the target feedback torque according to the vehicle driving equation and the target coasting feedback intensity b; The calculating the target coasting feedback intensity b by using the acquired coasting parameter information includes the following steps: Calculating a real-time dynamic adjustment coefficient λ for each preset sampling period according to the coasting parameter information; Calculate the average acceleration a of the vehicle within each sampling period 平均 and the average value λ_avg of the dynamic adjustment coefficient; The average acceleration a obtained for each preset sampling period 平均 is compared with a preset target coasting feedback acceleration to obtain a difference δa; When the signs of the acceleration differences δa obtained from multiple calculations are the same, the arithmetic mean of the product of the acceleration differences δa obtained from multiple calculations and the corresponding average value λ of the dynamic adjustment coefficient 平均 is used as the target intensity adjustment requirement value; Adding the obtained target intensity adjustment demand value to the currently acquired feedback intensity to generate the target coasting feedback intensity b; The formula for calculating the real-time dynamic adjustment coefficient λ is: λ = (1 - Min(Ap, 0.1) * 10) * (1 - Min(Bp, 0.1) * 10) * (1 - Min(I, 0.1) * 10) * (1 - Min(|θ|, 90) / 90), where λ is the dynamic adjustment coefficient; Ap is the acquired accelerator pedal opening, Bp is the brake pedal opening, I is the road gradient, and θ is the steering wheel angle.

5. The adaptive coasting feedback intensity control method for an electric vehicle according to claim 4, wherein The correction of the target feedback torque according to the vehicle driving equation and the target coasting feedback strength b includes the following steps: Collect the road slopes passed by the vehicle within multiple preset sampling periods and obtain their arithmetic mean value i; Calculate the driving force F of the vehicle using the obtained average road slope i, where F = mb + Gsin(tan -1 i) + Gcos(tan -1 i) + C D AV 2 / 21.15, m is the vehicle mass, G is the vehicle gravity, C D is the air resistance coefficient, A is the vehicle frontal area, and V is the vehicle speed; According to the vehicle driving equation and the target of driving force correction, the feedback torque T is obtained. Among them, the vehicle driving equation is T = Fr / i g i0n T , r is the wheel rolling radius, i g is the transmission ratio, i0 is the final drive ratio, n T is the transmission efficiency.

6. A terminal, characterized in that, Including: At least one processor; And a memory storing program instructions, wherein the program instructions are configured to be executed by the at least one processor, and the program instructions include instructions for executing any one of the above-mentioned electric vehicle adaptive coasting feedback strength control methods in claims 4-5.

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