Vehicle longitudinal control method and device, vehicle controller and vehicle

Abstract

The application provides a vehicle longitudinal control method and device, a vehicle controller and a vehicle, and relates to the technical field of vehicle auxiliary driving. The method comprises the following steps: acquiring a gear shifting demand of the vehicle and vehicle running state information, wherein the vehicle running state information at least comprises speed information; if the gear shifting demand of the vehicle is an acceleration demand, calculating a target feedforward torque according to the vehicle running state information; determining a cruise control mode according to whether there is another moving object in a preset range of the driving direction of the vehicle; calculating a closed-loop feedback torque corresponding to the cruise control mode according to the speed information; calculating a target control torque according to the target feedforward torque and the closed-loop feedback torque; and performing longitudinal control on the vehicle according to the target control torque. The application can realize accurate control of the vehicle in different working conditions and ensure stable and smooth operation of the vehicle.

Description

Technical Field

[0001] This application relates to the field of vehicle driver assistance technology, and more specifically, to a vehicle longitudinal control method, device, vehicle controller, and vehicle. Background Technology

[0002] In recent years, with the large-scale use of driver assistance systems in the commercial vehicle sector, drive-by-wire is the foundation of driver assistance.

[0003] In vehicle motion control, steer-by-wire is divided into lateral steer-by-wire and longitudinal steer-by-wire. Longitudinal control mainly involves acceleration control and braking control. Acceleration control involves the conversion of acceleration and torque. Traditional acceleration-to-torque conversion schemes mainly use dynamics or calibration tables for torque conversion.

[0004] Existing methods are difficult to perform targeted torque calculations for different operating conditions, resulting in poor vehicle control. Summary of the Invention

[0005] The purpose of this application is to address the shortcomings of the prior art by providing a vehicle longitudinal control method, device, vehicle controller, and vehicle, so as to achieve precise control of the vehicle under different operating conditions and ensure stable and smooth vehicle operation.

[0006] To achieve the above objectives, the technical solutions adopted in the embodiments of this application are as follows:

[0007] In a first aspect, embodiments of this application provide a vehicle longitudinal control method, the method comprising:

[0008] Obtain the vehicle's gear shifting requirements and vehicle operating status information, wherein the vehicle operating status information includes at least: speed information;

[0009] If the vehicle's gear shifting requirement is an acceleration requirement, calculate the target feedforward torque based on the vehicle's operating status information;

[0010] The cruise control mode is determined based on whether there are other moving objects within a preset range of the vehicle's direction of travel;

[0011] Based on the speed information, calculate the closed-loop feedback torque corresponding to the cruise control mode;

[0012] The target control torque is calculated based on the target feedforward torque and the closed-loop feedback torque;

[0013] The vehicle is longitudinally controlled according to the target control torque.

[0014] Optionally, calculating the target feedforward torque based on the vehicle operating status information includes:

[0015] If the real-time speed of the vehicle is greater than or equal to the preset speed value, the target feedforward torque is calculated based on the vehicle's operating status information using the motor power formula and the vehicle dynamics formula.

[0016] If the real-time speed of the vehicle is less than the preset speed value, the target feedforward torque is calculated by linear interpolation based on multi-dimensional vehicle operating status information and a multi-dimensional lookup table of multi-dimensional information and torque.

[0017] Optionally, the speed information includes at least: the vehicle's target speed and real-time speed, and determining the cruise control mode based on whether there are other moving objects within a preset range of the vehicle's direction of travel includes:

[0018] If no other moving object is present, the cruise control mode is determined to be constant speed cruise control mode;

[0019] The step of calculating the closed-loop feedback torque corresponding to the cruise control mode based on the speed information includes:

[0020] The closed-loop feedback torque is calculated using a fixed PID control algorithm based on the speed deviation between the target speed and the real-time speed.

[0021] Optionally, the speed information includes at least: the target acceleration and real-time acceleration of the vehicle, and the step of determining the cruise control mode based on whether there are other moving objects within a preset range of the vehicle's direction of travel includes:

[0022] If other moving objects exist, the cruise control mode is determined to be the following cruise control mode;

[0023] The step of calculating the closed-loop feedback torque corresponding to the cruise control mode based on the speed information includes:

[0024] The closed-loop feedback torque is calculated based on the acceleration deviation between the target acceleration and the real-time acceleration.

[0025] Optionally, calculating the closed-loop feedback torque based on the acceleration deviation between the target acceleration and the real-time acceleration of the vehicle includes:

[0026] If the acceleration deviation is greater than or equal to a preset deviation threshold, the closed-loop feedback torque is calculated using a fuzzy PID control algorithm.

[0027] If the acceleration deviation is less than the preset deviation threshold, the closed-loop feedback torque is calculated using a fixed PID control algorithm.

[0028] Optionally, calculating the target control torque based on the target feedforward torque and the closed-loop feedback torque includes:

[0029] Calculate the initial control torque based on the target feedforward torque and the closed-loop feedback torque;

[0030] Based on the vehicle's real-time acceleration, the maximum torque change rate is determined using a mapping table between acceleration and torque change rate.

[0031] Based on the maximum torque change rate, the initial control torque is limited and smoothed to obtain the target control torque.

[0032] Optionally, the speed information includes at least: the target deceleration and real-time deceleration of the vehicle, and the method further includes:

[0033] If the vehicle's speed change requirement is a deceleration requirement, the initial closed-loop feedback torque is calculated using a fixed PID control algorithm based on the target deceleration and the real-time deceleration.

[0034] Based on the vehicle's operating status information and the target deceleration, the maximum rate of change of deceleration is determined using a pre-established deceleration gradient limit table.

[0035] The target control torque is generated by limiting the initial closed-loop feedback torque based on the maximum rate of change of deceleration.

[0036] Secondly, embodiments of this application also provide a vehicle longitudinal control device, the device comprising:

[0037] The information acquisition module is used to acquire the vehicle's gear shifting requirements and vehicle operating status information, wherein the vehicle operating status information includes at least: speed information;

[0038] The feedforward torque calculation module is used to calculate the target feedforward torque based on the vehicle's operating status information if the vehicle's gear shifting requirement is an acceleration requirement.

[0039] The control mode determination module is used to determine the cruise control mode based on whether there are other moving objects within a preset range of the vehicle's driving direction;

[0040] The feedback torque calculation module is used to calculate the closed-loop feedback torque corresponding to the cruise control mode based on the speed information.

[0041] The control torque calculation module is used to calculate the target control torque based on the target feedforward torque and the closed-loop feedback torque;

[0042] The vehicle control module is used to perform longitudinal control of the vehicle based on the target control speed generated by the target control torque.

[0043] Optionally, the feedforward torque calculation module is specifically used to calculate the target feedforward torque based on the vehicle's operating status information, using the motor power formula and vehicle dynamics formula, if the vehicle's real-time speed is greater than or equal to a preset speed value; and to calculate the target feedforward torque by linear interpolation based on multi-dimensional vehicle operating status information and a multi-dimensional lookup table of multi-dimensional information and torque, if the vehicle's real-time speed is less than the preset speed value.

[0044] Optionally, the speed information includes at least: the target speed and real-time speed of the vehicle, and the control mode determination module is specifically used to determine the cruise control mode as constant speed cruise control mode if there are no other moving objects.

[0045] The feedback torque calculation module is specifically used to calculate the closed-loop feedback torque based on the speed deviation between the target speed and the real-time speed using a fixed PID control algorithm.

[0046] Optionally, the speed information includes at least: the target acceleration and real-time acceleration of the vehicle; the control mode determination module is specifically used to determine the cruise control mode as a following cruise control mode if the other moving object exists.

[0047] The feedback torque calculation module is specifically used to calculate the closed-loop feedback torque based on the acceleration deviation between the target acceleration and the real-time acceleration.

[0048] Optionally, the feedback torque calculation module is specifically used to calculate the closed-loop feedback torque using a fuzzy PID control algorithm if the acceleration deviation is greater than or equal to a preset deviation threshold; and to calculate the closed-loop feedback torque using a fixed PID control algorithm if the acceleration deviation is less than the preset deviation threshold.

[0049] Optionally, the control torque calculation module is specifically used to calculate the initial control torque based on the target feedforward torque and the closed-loop feedback torque; determine the maximum torque change rate based on the real-time acceleration of the vehicle through a mapping table of acceleration and torque change rate; and limit and smooth the initial control torque based on the maximum torque change rate to obtain the target control torque.

[0050] Optionally, the speed information includes at least: the target deceleration and real-time deceleration of the vehicle. The feedback torque calculation module is further configured to calculate the initial closed-loop feedback torque based on the target deceleration and the real-time deceleration if the vehicle's gear shifting requirement is a deceleration requirement.

[0051] The control torque calculation module is further configured to determine the maximum deceleration change rate based on the vehicle's operating status information and the target deceleration using a pre-established deceleration gradient limit table; and to limit the initial closed-loop feedback torque based on the maximum deceleration change rate to generate the target control torque.

[0052] Thirdly, embodiments of this application also provide a vehicle controller, including: a processor, a storage medium, and a bus, wherein the storage medium stores program instructions executable by the processor, and when the vehicle controller is running, the processor communicates with the storage medium via the bus, and the processor executes the program instructions to perform the steps of the vehicle longitudinal control method as described in any of the first aspects.

[0053] Fourthly, embodiments of this application also provide a vehicle, the vehicle including a vehicle body and a vehicle controller as described in the third aspect, the vehicle controller employing a vehicle longitudinal control method as described in any of the first aspects for longitudinal control.

[0054] Fifthly, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, performs longitudinal control of the vehicle as described in any of the first aspects.

[0055] The beneficial effects of this application are:

[0056] The vehicle longitudinal control method, device, vehicle controller, and vehicle provided in this application, in acceleration scenarios, calculate the closed-loop feedback torque corresponding to the cruise control mode based on whether there are other moving objects within a preset range of the vehicle's travel direction. The target feedforward torque in the acceleration scenario is compensated based on the closed-loop feedback torque to obtain the target control torque. The vehicle is then longitudinally controlled based on the target control torque, enabling separate control for situations where there are other moving objects within the preset range of the vehicle's travel direction and situations where there are no other moving objects, thereby improving the control accuracy of longitudinal vehicle control under different operating conditions. Attached Figure Description

[0057] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0058] Figure 1 A flowchart illustrating the vehicle longitudinal control method provided in this application embodiment. Figure 1 ;

[0059] Figure 2 This is a block diagram of torque control in cruise control mode provided in an embodiment of this application;

[0060] Figure 3 A fuzzy PID flowchart provided for embodiments of this application;

[0061] Figure 4 This is a block diagram of torque control in the following cruise mode provided in an embodiment of this application;

[0062] Figure 5 A flowchart illustrating the vehicle longitudinal control method provided in this application embodiment. Figure 2 ;

[0063] Figure 6 A flowchart illustrating the vehicle longitudinal control method provided in this application embodiment. Figure 3 ;

[0064] Figure 7 This is a block diagram of torque control for braking deceleration provided in an embodiment of this application;

[0065] Figure 8 This is a schematic diagram of the structure of the vehicle longitudinal control device provided in the embodiments of this application;

[0066] Figure 9 This is a schematic diagram of a vehicle controller provided in an embodiment of this application. Detailed Implementation

[0067] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some embodiments of this application, but not all embodiments.

[0068] Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0069] Furthermore, the terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Additionally, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0070] It should be noted that, where there is no conflict, the features in the embodiments of this application can be combined with each other.

[0071] Figure 1 A flowchart illustrating the vehicle longitudinal control method provided in this application embodiment. Figure 1 ,like Figure 1 As shown, the method may include:

[0072] S101. Obtain the vehicle's gear shifting requirements and vehicle operating status information, including at least speed information.

[0073] In this embodiment, the vehicle's gear shifting requirement can be either an acceleration requirement or a deceleration requirement. The vehicle's gear shifting requirement and vehicle operating status information can be obtained through vehicle sensors such as wheel speed sensors and acceleration sensors. The vehicle operating status information obtained under acceleration and deceleration requirements may be different. For example, the speed information in the vehicle operating status information corresponding to acceleration requirements can be acceleration information, while the speed information in the vehicle operating status information corresponding to deceleration requirements can be deceleration information.

[0074] S102. If the vehicle's gear shifting requirement is an acceleration requirement, calculate the target feedforward torque based on the vehicle's operating status information.

[0075] In this embodiment, the acceleration requirement indicates that the vehicle needs to accelerate, for example, the vehicle needs to gradually accelerate to the target speed, or needs to operate with the target acceleration. Based on the vehicle's operating status information and the target speed / target acceleration, the theoretical torque required to maintain the target speed / target acceleration, i.e., the target feedforward torque, is calculated based on the vehicle's operating status information.

[0076] The target speed / target acceleration can be determined based on the driver's driving operation, or calculated by the vehicle's adaptive cruise control (ACC) system using a preset driving strategy.

[0077] S103. Determine the cruise control mode based on whether there are other moving objects within a preset range of the vehicle's driving direction.

[0078] In this embodiment, the vehicle's adaptive cruise control is divided into cruise control and following cruise control, and the cruise control mode can be determined based on whether there are other moving objects in front of the vehicle.

[0079] Among them, cruise control instructs the vehicle to operate at a target speed, while following cruise control instructs the vehicle to adjust its own speed to maintain a safe distance from other moving objects, or to have a relative speed of zero with other moving objects.

[0080] In some embodiments, the presence of other moving objects within a preset range in the vehicle's direction of travel can be determined using the vehicle's forward-facing radar or camera.

[0081] S104. Based on the speed information, calculate the closed-loop feedback torque corresponding to the cruise control mode.

[0082] In this embodiment, in order to prevent the error of the feedforward torque from increasing during the long-term driving of the vehicle, it is necessary to compensate for the error of the feedforward torque. This solution calculates the closed-loop feedback torque corresponding to the cruise control mode based on the error between the real-time speed information and the target speed information corresponding to the cruise control mode, using the calculation method corresponding to the cruise control mode.

[0083] S105. Calculate the target control torque based on the target feedforward torque and the closed-loop feedback torque.

[0084] In this embodiment, the target control torque is determined based on the sum or weighted sum of the target feedforward torque and the closed-loop feedback torque.

[0085] S106. Perform longitudinal control of the vehicle based on the target control torque.

[0086] In this embodiment, during acceleration, the target control torque is converted into a torque command for the motor. The motor controller receives the command and precisely controls the current to enable the motor to output the corresponding drive torque. The drive torque is transmitted to the wheels through the transmission system to generate driving force for longitudinal control of the vehicle.

[0087] The vehicle longitudinal control method provided in the above embodiments calculates the closed-loop feedback torque corresponding to the cruise control mode based on whether there are other moving objects within a preset range of the vehicle's driving direction in acceleration scenarios. The target feedforward torque in acceleration scenarios is compensated based on the closed-loop feedback torque to obtain the target control torque. The vehicle is then longitudinally controlled based on the target control torque, enabling separate control for situations where there are other moving objects within the preset range of the vehicle's driving direction and situations where there are no other moving objects. This improves the control accuracy of longitudinal vehicle control under different operating conditions.

[0088] In one possible implementation, the process of calculating the target feedforward torque based on the vehicle operating status information in step S102 may include:

[0089] If the vehicle's real-time speed is greater than or equal to the preset speed value, the target feedforward torque is calculated based on the vehicle's operating status information using the motor power formula and the vehicle dynamics formula.

[0090] In this embodiment, the vehicle's real-time speed is used to determine whether the vehicle is in a creeping state. Specifically, if the vehicle's real-time speed is greater than or equal to a preset speed value, such as 3 km / h, the vehicle is determined to be in a non-creeping state. In the non-creeping state, the vehicle's operating status information may include: vehicle mass m, vehicle speed, etc. v The system obtains the vehicle mass via CAN bus, the vehicle speed via wheel speed sensor, the road slope α, the motor speed ω, and the frontal area A. It also estimates the road slope using integrated GPS data and longitudinal acceleration signal from an inertial measurement unit, and obtains the motor speed via a motor resolver.

[0091] According to the motor power formula and vehicle dynamics formula Determine the feedforward torque model η is the transmission efficiency of the vehicle's transmission system.

[0092] Based on the vehicle's target acceleration The total driving force required to obtain the target acceleration is obtained using Newton's second law. Decompose and calculate all forces that impede the vehicle's movement, including air resistance. Rolling resistance Slope resistance and acceleration resistance .

[0093] Among them, air resistance The calculation formula can be expressed as: , C d Here, ρ is the drag coefficient, and ρ is the air density; rolling resistance. The calculation formula can be expressed as: , f Rolling resistance coefficient; slope resistance The calculation formula can be expressed as: Acceleration resistance The calculation formula can be expressed as: δ is the rotational mass conversion factor.

[0094] When the real-time speed is greater than or equal to the preset speed value, the operating status information of each of the above vehicles is obtained, and the total driving force is calculated. air resistance Rolling resistance Slope resistance and acceleration resistance Based on the above feedforward torque model, the target feedforward torque under non-creeping conditions is calculated.

[0095] In another possible implementation, the process of calculating the target feedforward torque based on the vehicle operating status information in step S102 above may include:

[0096] If the vehicle's real-time speed is less than the preset speed value, the target feedforward torque is calculated by linear interpolation based on multi-dimensional vehicle operating status information and a multi-dimensional lookup table of multi-dimensional information and torque.

[0097] In this embodiment, if the real-time speed of the vehicle is less than the preset speed value, it is determined that the vehicle is in a creeping state. Since the motor speed is very low, the torque change is large, and the rolling resistance and transmission efficiency change nonlinearly at this time. The error of the feedforward torque model increases significantly, and the smoothness of the system acceleration is severely reduced. In response to this situation, this application uses a multi-dimensional lookup table of multi-dimensional information and torque to determine the target feedforward torque.

[0098] Specifically, a database covering all common crawling states is established, with dimensions including multiple slopes, multiple loads, multiple vehicle speeds, and multiple accelerations. For example, Table 1 is a multi-dimensional lookup table provided in an embodiment of this application. As shown in Table 1, multiple slopes include, for example, -10°, -5°, 0°, 5°, 10°, etc.; multiple loads include, for example, unloaded, half-loaded, fully loaded, etc.; multiple vehicle speeds less than a preset speed value include, for example, 0.5km / h, 1km / h, 1.5km / h, 2km / h, 2.5km / h, etc.; and multiple accelerations include, for example, -0.5m / s². 2 (Slight deceleration), 0m / s 2 (Constant speed), 0.5 m / s 2 (Micro-acceleration), etc. Collect the most accurate and smoothest motor output torque to maintain the state under different combinations of slope, load, vehicle speed and acceleration, and establish a multi-dimensional lookup table of multi-dimensional information and torque.

[0099] Table 1 Multidimensional Lookup Table

[0100]

[0101] In the creeping state, the vehicle load rate, real-time speed, and real-time acceleration are collected in real time. Combined with the rolling resistance model and attitude sensor, the real-time slope is identified online. The torque corresponding to each dimension is determined by looking up a multi-dimensional lookup table of multi-dimensional information and torque. Linear interpolation or bilinear interpolation is performed on the torque corresponding to each dimension to calculate the target feedforward torque.

[0102] By using a multidimensional lookup table to match different combinations of slope / load / acceleration / speed, the torque output error is less than 5%, which is much lower than the 15% of the traditional solution. Experiments show that within the slope range of ±5°, when the load changes by 20%, this method reduces the creep speed fluctuation rate from 12.3% of the traditional solution to 3.8%, which significantly improves the torque control accuracy and dynamic response capability under low-speed conditions.

[0103] The vehicle longitudinal control method provided in the above embodiments calculates the target feedforward torque using motor power formulas and vehicle dynamics formulas when the vehicle is not crawling, accurately providing the torque required for acceleration and avoiding insufficient or over-adjusted torque during acceleration, thus achieving smooth acceleration. When the vehicle is crawling, a multi-dimensional lookup table is used to calculate the target feedforward torque through linear interpolation, ensuring the stability and controllability of the vehicle during low-speed driving. This solution can ensure that a relatively accurate target feedforward torque can be calculated in both crawling and non-crawl states, achieving stable and smooth control of the vehicle.

[0104] In one possible implementation, the speed information may include at least: the vehicle's target acceleration and real-time acceleration. The process of determining the cruise control mode in step S103 based on whether there are other moving objects within a preset range of the vehicle's direction of travel may include:

[0105] If there are no other moving objects, the cruise control mode is set to constant speed cruise control mode.

[0106] The process of S104 above, which calculates the closed-loop feedback torque corresponding to the cruise control mode based on the speed information, may include:

[0107] Based on the speed deviation between the target speed and the real-time speed, a fixed PID control algorithm is used to calculate the closed-loop feedback torque.

[0108] In this embodiment, radar or camera is used to determine whether there are other moving objects in front of the vehicle. If there are no other moving objects in front, the vehicle is controlled to enter cruise control mode. The control objective of cruise control mode is to maintain the vehicle speed at a constant target speed set by the driver.

[0109] Specifically, the vehicle's real-time speed is collected by a speed sensor. Based on the speed deviation between the target speed and the real-time speed, a proportional-integral-derivative (PID) controller outputs the closed-loop feedback torque required to eliminate the speed deviation.

[0110] For example, the calculation formula for a PID controller is shown below:

[0111]

[0112] in, For the controller at the sampling time t The output closed-loop feedback torque, Sampling time t The error signal, here representing the speed deviation. , For the target value, These are real-time values, representing the target speed and the real-time speed, respectively. The proportional gain determines the strength of the proportional effect. The integral gain determines the strength of the integral action. The differential gain determines the strength of the differential action. For error From 0 to the current sampling time t The integral of , i.e., the sum of errors accumulated over time, For error The derivative of the error, i.e. the instantaneous rate of change of the error, represents the trend of error change.

[0113] Example, Figure 2 The torque control block diagram in cruise control mode provided in the embodiments of this application is as follows: Figure 2 As shown, vehicle operating status information is acquired, and a target feedforward torque is output through a crawl / non-crawl torque controller. Based on the speed deviation between the target speed and the real-time speed, a speed closed-loop torque controller, i.e., a fixed PID controller, is used to output closed-loop feedback torque. The target control torque is determined based on the sum of the target feedforward torque and the closed-loop feedback torque. The vehicle is controlled through the target control torque to change the vehicle's real-time speed.

[0114] The vehicle longitudinal control method provided in the above embodiments uses the speed signal as the input of the PID controller. For cruise control scenarios, it can achieve high-precision and high-stability speed control, quickly respond to speed change requirements, and effectively suppress speed fluctuations caused by system disturbances, ensuring that the system always works in the best state.

[0115] In another possible implementation, the speed information may include at least: the vehicle's target acceleration and real-time acceleration. The process of determining the cruise control mode in step S103 based on whether there are other moving objects within a preset range of the vehicle's direction of travel may include:

[0116] If other moving objects are present, the cruise control mode is set to follow cruise control mode.

[0117] The process of S104 above, which calculates the closed-loop feedback torque corresponding to the cruise control mode based on the speed information, may include:

[0118] The closed-loop feedback torque is calculated based on the acceleration deviation between the target acceleration and the real-time acceleration.

[0119] In this embodiment, radar or a camera is used to determine whether there are other moving objects in front of the vehicle. If there are other moving objects in front, the vehicle is controlled to enter the following cruise control mode. The control objective of the following cruise control mode is to adjust the vehicle speed to maintain a safe distance from other moving objects, or to make the relative speed with other moving objects zero.

[0120] Specifically, the vehicle's real-time acceleration is collected by an accelerometer. Based on the distance and relative speed between the vehicle and other moving objects in front, the target acceleration is determined. The acceleration deviation between the target acceleration and the real-time acceleration is input to the acceleration PID controller, which outputs a closed-loop feedback torque to eliminate the acceleration deviation.

[0121] The vehicle longitudinal control method provided in the above embodiments calculates the closed-loop feedback torque based on the acceleration deviation between the target acceleration and the real-time acceleration when there are other moving objects within a preset range of the vehicle's driving direction, so as to achieve safe following.

[0122] In one possible implementation, the process of calculating the closed-loop feedback torque based on the acceleration deviation between the target acceleration and the real-time acceleration may include:

[0123] If the acceleration deviation is greater than or equal to the preset deviation threshold, the fuzzy PID control algorithm is used to calculate the closed-loop feedback torque; if the acceleration deviation is less than the preset deviation threshold, the fixed PID control algorithm is used to calculate the closed-loop feedback torque.

[0124] In this embodiment, based on a preset deviation threshold As a basis for switching control strategies, if the acceleration deviation is ≥ A fuzzy PID controller is used to calculate the closed-loop feedback torque, achieving a fast response under large deviations. If the acceleration deviation is < A fixed PID controller is used to calculate the closed-loop feedback torque, achieving precise stability under small deviations.

[0125] In some embodiments, Figure 3 The fuzzy PID flowchart provided in the embodiments of this application is as follows: Figure 3 As shown, fuzzification processing is performed on the acceleration deviation and the rate of change of acceleration deviation, and a fuzzy rule base is established. Fuzzy inference is used to determine the fuzzification. , , Change , , According to the amount of change , , right , , Update.

[0126] Example, Figure 4 This is a block diagram of torque control in the following cruise mode provided in an embodiment of this application, such as... Figure 4 As shown, vehicle operating status information is acquired, and a target feedforward torque is output through a creep / non-creep torque controller. The acceleration deviation is determined based on the speed deviation between the target acceleration and the real-time acceleration. It is then determined whether the acceleration deviation is greater than or equal to the deviation threshold. If so, a fuzzy PID controller is used to output closed-loop feedback torque; otherwise, a fixed PID controller is used to output closed-loop feedback torque. The target control torque is determined based on the sum of the target feedforward torque and the closed-loop feedback torque. The vehicle is then controlled using the target control torque to change the vehicle's real-time acceleration.

[0127] The vehicle longitudinal control method provided in the above embodiments combines fuzzy PID control and fixed PID control. When the acceleration deviation is large, fuzzy PID control is used to achieve fast response and stability. When the acceleration deviation enters a smaller range, it switches to fixed PID control to ensure static accuracy. Thus, while ensuring a safe distance, it significantly improves the riding comfort and driving safety performance during following.

[0128] In one possible implementation, Figure 5 A flowchart illustrating the vehicle longitudinal control method provided in this application embodiment. Figure 2 ,like Figure 5 As shown, the process of calculating the target control torque based on the target feedforward torque and the closed-loop feedback torque in S105 above may include:

[0129] S201. Calculate the initial control torque based on the target feedforward torque and the closed-loop feedback torque.

[0130] S202. Based on the vehicle's real-time acceleration, determine the maximum torque change rate using the mapping table between acceleration and torque change rate.

[0131] S203. Based on the maximum torque change rate, the initial control torque is limited and smoothed to obtain the target control torque.

[0132] In this embodiment, a large amount of real driving data from the driver is acquired. For example, real driving data exceeding 1000 kW can be recorded, including data such as vehicle mass, torque, acceleration, speed, and road gradient. The torque change rate and acceleration at each sampling moment are calculated. The maximum torque change rate commonly used by the driver under different acceleration requirements is analyzed with acceleration as the horizontal axis. A mapping relationship between acceleration and maximum allowable torque change rate is generated. This mapping relationship is used to indicate the maximum allowable change gradient of torque under different acceleration requirements.

[0133] The maximum permissible torque change rate under the current operating condition can be obtained by querying the mapping relationship between real-time acceleration and maximum permissible torque change rate.

[0134] Compare the difference between the initial control torque at the current sampling time and the target control torque at the previous sampling time, and determine whether the difference is within the range of the maximum allowable torque change rate. If the difference is within the range of the maximum allowable torque change rate, then the initial control torque is determined to be the target control torque. If the difference exceeds the maximum allowable torque change rate, then the target control torque at the current sampling time is generated based on the sum of the target control torque at the previous sampling time and the maximum allowable torque change rate.

[0135] A smoothing filter is used to smooth the target control torque from the previous sampling time to the target control torque at the current sampling time, and the control torque at each control time is determined according to the control cycle.

[0136] For example, if the target control torque at the previous sampling time is 100 N·m, the initial control torque at the current sampling time is 1000 N·m, and the sampling interval is 1 s, then the torque change rate is 900 N·m / s. If the maximum allowable torque change rate is 500 N·m, then the target control torque is 600 N·m. If the control period is 0.01 s (10 ms), then 500 N·m is incremented by 5 N·m every 10 ms in 100 10 ms intervals. Assuming the sliding window N is 5, in the initial stage, the window content is [100, 100, 100, 100, 100]. In the first control cycle (i=1), the control torque is 100 + i × 5 = 105 N·m, so the window content is updated to [100, 100, 100, 100, 105]. The average window value is (100 + 100 + 100 + 100 + 105) / 5 = 101 N·m. The vehicle is then controlled based on 101 N·m. In the second control cycle (i=2), the control torque is 110 N·m, so the window content is updated to [100, 100, 100, 105, 110]. The average window value is (100 + 100 + 100 + 105 + 110) / 5 = 103 N·m. The vehicle is then controlled based on 103 N·m. Subsequent control cycles follow the same principle and will not be elaborated further here.

[0137] like Figure 2 and Figure 4 As shown, the initial control torque is passed through the gradient limit controller to output the target control torque, which is then smoothed to control the vehicle.

[0138] In some embodiments, in addition to gradient limiting the initial control torque, after the feedforward torque is calculated, the feedforward torque can also be gradient limited before being used together with the closed-loop feedback torque to calculate the target control torque.

[0139] The vehicle longitudinal control method provided in the above embodiments, in order to effectively prevent large gradient changes in torque output and avoid operating conditions that do not conform to the driver's operating habits, generates a mapping relationship table between acceleration and torque change rate by analyzing the driver's operating habits. The control torque is gradient-limited and smoothed by the mapping relationship table between acceleration and torque change rate, ensuring that the control of the vehicle's power output according to the target control torque can maintain a smooth transition, significantly improving driving comfort and natural handling.

[0140] In one possible implementation, the speed information may include at least: the vehicle's target deceleration and real-time deceleration. Figure 6 A flowchart illustrating the vehicle longitudinal control method provided in this application embodiment. Figure 3 ,like Figure 6 As shown, the method may further include:

[0141] S301. If the vehicle's speed change requirement is a deceleration requirement, the initial closed-loop feedback torque is calculated using a fixed PID control algorithm based on the target deceleration and the real-time deceleration.

[0142] S302. Based on the vehicle's operating status information and the target deceleration, determine the maximum rate of change of deceleration using a pre-established deceleration gradient limit table.

[0143] S303. Limit the initial closed-loop feedback torque based on the maximum rate of change of deceleration to generate the target control torque.

[0144] In this embodiment, the deceleration requirement indicates that the vehicle needs to decelerate, such as when the vehicle needs to brake or stop. The target deceleration can be calculated by ACC according to a preset driving strategy. Based on the difference between the target deceleration and the real-time deceleration, the fixed PID controller outputs the initial closed-loop feedback torque required to eliminate the deceleration deviation.

[0145] The system collects vehicle operating status information under different road conditions and at various speeds. Road conditions may include dry roads, wet roads, different loads, and different gradients. Vehicle speeds may range from 0 to 80 km / h. Vehicle operating status information may include brake pedal travel, brake pressure, and real-time speed. Data from each braking event is analyzed to determine braking characteristic parameters, such as initial braking speed, maximum deceleration value, deceleration rise time (e.g., time from 10% to 90% of maximum deceleration), total braking time, and braking distance. By analyzing the operating conditions and braking characteristic parameters, a braking characteristic model is established. This model includes a deceleration gradient limit table for the target deceleration and the maximum permissible rate of deceleration change. Based on real-time vehicle speed, vehicle load, road gradient, and braking distance, the target deceleration value is calculated using the braking characteristic model. The maximum rate of deceleration change is then determined using the deceleration gradient limit table based on the target deceleration value.

[0146] Based on the maximum deceleration rate of change, the maximum permissible torque rate of change is calculated. Based on the initial closed-loop feedback torque at the current sampling time and the target control torque at the previous sampling time, the desired torque rate of change is calculated. If the desired torque rate of change is less than or equal to the maximum permissible torque rate of change, the initial closed-loop feedback torque is determined to be the target control torque. If the desired torque rate of change is greater than the maximum permissible torque rate of change, the target control torque at the current sampling time is calculated based on the maximum permissible torque rate of change and the target control torque at the previous sampling time. The target control torque is then smoothed to control the vehicle.

[0147] Example, Figure 7 The torque control block diagram for braking deceleration provided in the embodiments of this application is as follows: Figure 7As shown, based on the deceleration deviation between the target deceleration and the real-time deceleration, a deceleration closed-loop torque controller, i.e., a fixed PID controller, is used to output the initial closed-loop feedback torque. Based on the target deceleration and the initial closed-loop feedback torque, the deceleration gradient limit controller outputs the target control torque. The vehicle is controlled by the target control torque to change the real-time deceleration of the vehicle.

[0148] The vehicle longitudinal control method provided in the above embodiments, in order to effectively prevent excessive gradient changes in braking deceleration and avoid operating conditions that do not conform to the driver's operating habits, generates a deceleration gradient limit table by analyzing the driver's operating habits, and performs gradient limitation and smoothing processing on the control torque through the deceleration gradient limit table, so as to ensure that the braking control of the vehicle can maintain a smooth transition according to the target control torque, and ensure smooth and reliable deceleration.

[0149] The longitudinal vehicle control method adopted in this solution controls the vehicle separately for acceleration, deceleration, following cruise, and constant speed cruise, which overcomes the limitations of a single control strategy and achieves stable and smooth vehicle control.

[0150] Based on the above method embodiments, this application also provides a vehicle longitudinal control device. Figure 8 This is a schematic diagram of the vehicle longitudinal control device provided in the embodiments of this application, as shown below. Figure 8 As shown, the device may include:

[0151] The information acquisition module 401 is used to acquire the vehicle's gear shifting requirements and vehicle operating status information, which includes at least speed information.

[0152] The feedforward torque calculation module 402 is used to calculate the target feedforward torque based on the vehicle's operating status information if the vehicle's gear shifting requirement is an acceleration requirement.

[0153] The control mode determination module 403 is used to determine the cruise control mode based on whether there are other moving objects within a preset range of the vehicle's driving direction.

[0154] The feedback torque calculation module 404 is used to calculate the closed-loop feedback torque corresponding to the cruise control mode based on the speed information.

[0155] The control torque calculation module 405 is used to calculate the target control torque based on the target feedforward torque and the closed-loop feedback torque.

[0156] The vehicle control module 406 is used to perform longitudinal control of the vehicle based on the target control speed generated by the target control torque.

[0157] Optionally, the feedforward torque calculation module 402 is specifically used to calculate the target feedforward torque based on the vehicle's operating status information, using the motor power formula and the vehicle dynamics formula, if the vehicle's real-time speed is greater than or equal to a preset speed value; and to calculate the target feedforward torque by linear interpolation based on multi-dimensional vehicle operating status information and a multi-dimensional lookup table of multi-dimensional information and torque, if the vehicle's real-time speed is less than the preset speed value.

[0158] Optionally, the speed information includes at least: the vehicle's target speed and real-time speed. The control mode determination module 403 is specifically used to determine the cruise control mode as constant speed cruise control mode if there are no other moving objects.

[0159] The feedback torque calculation module 404 is specifically used to calculate the closed-loop feedback torque based on the speed deviation between the target speed and the real-time speed using a fixed PID control algorithm.

[0160] Optionally, the speed information includes at least: the vehicle's target acceleration and real-time acceleration. The control mode determination module 403 is specifically used to determine the cruise control mode as the following cruise control mode if there are other moving objects.

[0161] The feedback torque calculation module 404 is specifically used to calculate the closed-loop feedback torque based on the acceleration deviation between the target acceleration and the real-time acceleration.

[0162] Optionally, the feedback torque calculation module 404 is specifically used to calculate the closed-loop feedback torque using a fuzzy PID control algorithm if the acceleration deviation is greater than or equal to a preset deviation threshold; and to calculate the closed-loop feedback torque using a fixed PID control algorithm if the acceleration deviation is less than the preset deviation threshold.

[0163] Optionally, the control torque calculation module 403 is specifically used to calculate the initial control torque based on the target feedforward torque and the closed-loop feedback torque; determine the maximum torque change rate based on the real-time acceleration of the vehicle through a mapping table of acceleration and torque change rate; and limit and smooth the initial control torque based on the maximum torque change rate to obtain the target control torque.

[0164] Optionally, the speed information includes at least: the vehicle's target deceleration and real-time deceleration. The feedback torque calculation module 404 is also used to calculate the initial closed-loop feedback torque based on the target deceleration and real-time deceleration if the vehicle's gear shifting requirement is a deceleration requirement.

[0165] The control torque calculation module 403 is also used to determine the maximum deceleration change rate based on the vehicle's operating status information and the target deceleration using a pre-established deceleration gradient limit table; and to limit the initial closed-loop feedback torque based on the maximum deceleration change rate to generate the target control torque.

[0166] The above-described device is used to execute the method provided in the foregoing embodiments, and its implementation principle and technical effect are similar, so they will not be described again here.

[0167] These modules can be one or more integrated circuits configured to implement the above methods, such as one or more Application Specific Integrated Circuits (ASICs), one or more microprocessors, or one or more Field Programmable Gate Arrays (FPGAs). Alternatively, when a module is implemented using processing element scheduler code, the processing element can be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor capable of calling program code. Furthermore, these modules can be integrated together as a system-on-a-chip (SOC).

[0168] Figure 9 A schematic diagram of the vehicle controller provided in the embodiments of this application, as shown below. Figure 9 As shown, the vehicle controller 500 may include a processor 501, a storage medium 502, and a bus. The storage medium 502 stores program instructions executable by the processor 501. When the vehicle controller 500 is running, the processor 501 communicates with the storage medium 502 via the bus, and the processor 501 executes the program instructions to perform the above-described method embodiment. The specific implementation and technical effects are similar and will not be described in detail here.

[0169] Optionally, this application also provides a computer-readable storage medium storing a computer program, which is executed by a processor to perform the above-described method embodiments.

[0170] Optionally, this application embodiment also provides a vehicle, which includes a vehicle body and a vehicle controller, and the vehicle uses the above-described vehicle longitudinal control method for longitudinal control.

[0171] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0172] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0173] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in a combination of hardware and software functional units.

[0174] The integrated units implemented as software functional units described above can be stored in a computer-readable storage medium. These software functional units, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0175] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A vehicle longitudinal control method, characterized in that, The method includes: Obtain the vehicle's gear shifting requirements and vehicle operating status information, wherein the vehicle operating status information includes at least: speed information; If the vehicle's gear shifting requirement is an acceleration requirement, calculate the target feedforward torque based on the vehicle's operating status information; The cruise control mode is determined based on whether there are other moving objects within a preset range of the vehicle's direction of travel; Based on the speed information, calculate the closed-loop feedback torque corresponding to the cruise control mode; The target control torque is calculated based on the target feedforward torque and the closed-loop feedback torque; The vehicle is longitudinally controlled according to the target control torque; The speed information includes at least: the vehicle's target acceleration and real-time acceleration. Determining the cruise control mode based on whether there are other moving objects within a preset range of the vehicle's direction of travel includes: If other moving objects exist, the cruise control mode is determined to be the following cruise control mode; The step of calculating the closed-loop feedback torque corresponding to the cruise control mode based on the speed information includes: Calculate the acceleration deviation between the target acceleration and the real-time acceleration; If the acceleration deviation is greater than or equal to a preset deviation threshold, the closed-loop feedback torque is calculated using a fuzzy PID control algorithm. If the acceleration deviation is less than the preset deviation threshold, the closed-loop feedback torque is calculated using a fixed PID control algorithm.

2. The method as described in claim 1, characterized in that, The step of calculating the target feedforward torque based on the vehicle operating status information includes: If the real-time speed of the vehicle is greater than or equal to the preset speed value, the target feedforward torque is calculated based on the vehicle's operating status information using the motor power formula and the vehicle dynamics formula. If the real-time speed of the vehicle is less than the preset speed value, the target feedforward torque is calculated by linear interpolation based on multi-dimensional vehicle operating status information and a multi-dimensional lookup table of multi-dimensional information and torque.

3. The method as described in claim 1, characterized in that, The speed information includes at least: the vehicle's target speed and real-time speed. Determining the cruise control mode based on whether there are other moving objects within a preset range of the vehicle's direction of travel includes: If no other moving object is present, the cruise control mode is determined to be constant speed cruise control mode; The step of calculating the closed-loop feedback torque corresponding to the cruise control mode based on the speed information includes: The closed-loop feedback torque is calculated using a fixed PID control algorithm based on the speed deviation between the target speed and the real-time speed.

4. The method as described in claim 1, characterized in that, The step of calculating the target control torque based on the target feedforward torque and the closed-loop feedback torque includes: Calculate the initial control torque based on the target feedforward torque and the closed-loop feedback torque; Based on the vehicle's real-time acceleration, the maximum torque change rate is determined using a mapping table between acceleration and torque change rate. Based on the maximum torque change rate, the initial control torque is limited and smoothed to obtain the target control torque.

5. The method as described in claim 1, characterized in that, The speed information includes at least: the target deceleration and real-time deceleration of the vehicle, and the method further includes: If the vehicle's speed change requirement is a deceleration requirement, the initial closed-loop feedback torque is calculated using a fixed PID control algorithm based on the target deceleration and the real-time deceleration. Based on the vehicle's operating status information and the target deceleration, the maximum rate of change of deceleration is determined using a pre-established deceleration gradient limit table. The target control torque is generated by limiting the initial closed-loop feedback torque based on the maximum rate of change of deceleration.

6. A vehicle longitudinal control device, characterized in that, The device includes: The information acquisition module is used to acquire the vehicle's gear shifting requirements and vehicle operating status information, wherein the vehicle operating status information includes at least: speed information; The feedforward torque calculation module is used to calculate the target feedforward torque based on the vehicle's operating status information if the vehicle's gear shifting requirement is an acceleration requirement. The control mode determination module is used to determine the cruise control mode based on whether there are other moving objects within a preset range of the vehicle's driving direction; The feedback torque calculation module is used to calculate the closed-loop feedback torque corresponding to the cruise control mode based on the speed information. The control torque calculation module is used to calculate the target control torque based on the target feedforward torque and the closed-loop feedback torque; The vehicle control module is used to perform longitudinal control of the vehicle based on the target control speed generated by the target control torque; The speed information includes at least: the target acceleration and real-time acceleration of the vehicle; the control mode determination module is specifically used to determine the cruise control mode as a following cruise control mode if there are other moving objects. The feedback torque calculation module is specifically used to calculate the acceleration deviation between the target acceleration and the real-time acceleration. If the acceleration deviation is greater than or equal to a preset deviation threshold, the closed-loop feedback torque is calculated using a fuzzy PID control algorithm; if the acceleration deviation is less than the preset deviation threshold, the closed-loop feedback torque is calculated using a fixed PID control algorithm.

7. A vehicle controller, characterized in that, include: The system includes a processor, a storage medium, and a bus, wherein the storage medium stores program instructions executable by the processor, and when the vehicle controller is running, the processor communicates with the storage medium via the bus, and the processor executes the program instructions to perform the steps of the vehicle longitudinal control method as described in any one of claims 1 to 5.

8. A vehicle, characterized in that, The vehicle includes a vehicle body and a vehicle controller as described in claim 7, wherein the vehicle controller performs longitudinal control using the vehicle longitudinal control method as described in any one of claims 1 to 5.

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