Electric vehicle self-adaptive cruise hierarchical control method and system and storage medium

Abstract

The invention provides an electric vehicle self-adaptive cruise hierarchical control method and system and a storage medium. The method comprises the following steps that the front vehicle running speed of a vehicle in front of a target vehicle is obtained through a vehicle-mounted radar of the target vehicle; the target driving speed of the target vehicle is obtained in real time, and the given variable time interval of the target vehicle is obtained through calculation; calculating the planned speed of the target vehicle according to a safe distance control strategy in combination with the driving speed of the front vehicle and the given variable time interval; speed compensation of the target vehicle is obtained through calculation based on the position PID control strategy; acceleration compensation of the target vehicle is obtained through calculation based on the speed PID control strategy; calculating an acceleration deviation based on acceleration compensation according to an acceleration PID control strategy; and the control torque of the target vehicle is calculated according to the acceleration deviation, and the target driving speed of the target vehicle is adjusted through the control torque. The method has the effect of keeping the vehicle speed stable for a long time in the self-adaptive cruise control process.

Description

Technical Field

[0001] The present invention belongs to the technical field of automobile control, and in particular relates to a hierarchical control method, system and storage medium for adaptive cruise control of an electric vehicle. Background Art

[0002] In recent years, with the continuous development of cruise control technology in electric vehicles, cruise control technology has evolved from traditional cruise control (CC) to adaptive cruise control (ACC). Traditional cruise control can control the vehicle to travel at a constant speed according to the speed set in advance by the driver when there is no car in front. Adaptive cruise control is actually derived from the traditional cruise control system. The main function of adaptive cruise control is to detect the relative speed and relative distance of the vehicle in front based on sensors such as on-board radar and cameras. The vehicle cruise control system automatically adjusts the speed to maintain a safe distance and relative speed with the vehicle in front, which can fully improve driving comfort and active safety of the vehicle.

[0003] At present, the ACC systems of most vehicles on the market use speed PID control to perform adaptive cruise control, that is, the planned speed of the vehicle is set in real time according to the real-time speed of the vehicle in front and the real-time distance between the two vehicles. However, in the actual driving process, if the speed of the vehicle does not reach the planned speed, it will continue to accelerate until it reaches the planned speed. However, due to the delay effect of speed PID control, the real-time speed will continue to accelerate for a short time after reaching the planned speed, so that the final real-time speed will exceed the planned speed. Because the real-time speed exceeds the planned speed, the ACC system will control the vehicle to brake and decelerate to reduce the real-time speed to the planned speed. Similarly, due to the delay effect of speed PID control, the real-time speed will continue to decelerate for a short time after it drops to the planned speed. Ultimately, the ACC system will frequently switch the drive and brake of the vehicle, causing the vehicle to switch between acceleration and deceleration states for a long time, and it is impossible to stabilize the vehicle speed for a long time, making the driver or passengers in the car uncomfortable when riding. Summary of the invention

[0004] The present invention provides an electric vehicle adaptive cruise hierarchical control method, system and storage medium to solve the problem that the vehicle speed cannot be stabilized for a long time during the vehicle adaptive cruise control process, resulting in low riding comfort for the driver or passengers in the vehicle.

[0005] In a first aspect, the present invention provides a hierarchical control method for adaptive cruise control of an electric vehicle, the method comprising the following steps:

[0006] Acquiring the driving speed of the vehicle ahead of the target vehicle through the on-board radar of the target vehicle;

[0007] Acquire the target driving speed of the target vehicle in real time and calculate the given variable time headway of the target vehicle;

[0008] Combining the speed of the preceding vehicle and the given variable headway, and calculating the planned speed of the target vehicle according to a safety distance control strategy;

[0009] Combining the given variable time head and the planned speed, and calculating the speed compensation of the target vehicle based on the position PID control strategy;

[0010] Combining the target driving speed, the planned speed and the speed compensation, and calculating the acceleration compensation of the target vehicle based on a speed PID control strategy;

[0011] Based on the acceleration compensation and according to the acceleration PID control strategy, an acceleration deviation is calculated;

[0012] The control torque of the target vehicle is calculated according to the acceleration deviation, and the target driving speed of the target vehicle is adjusted by the control torque.

[0013] Optionally, the step of combining the preceding vehicle's speed and the given variable headway and calculating the planned speed of the target vehicle according to a safety distance control strategy comprises the following steps:

[0014] Building a variable safe vehicle distance model based on the given variable time headway and in accordance with a safe distance control strategy;

[0015] Substituting the preceding vehicle's speed into the variable safe vehicle distance model, and calculating the planned speed of the target vehicle;

[0016] The model formula of the variable safety vehicle distance model is as follows:

[0017]

[0018] Where: d s represents the given variable time interval, υ set represents the planned speed, T h represents the reaction time of the target vehicle driver, υ p represents the speed of the preceding vehicle, a min represents the minimum braking deceleration of the target vehicle, and Δx represents the safe distance between the target vehicle and the vehicle ahead when the target vehicle stops.

[0019] Optionally, the combining the given variable time interval and the planned speed and calculating the speed compensation of the target vehicle based on the position PID control strategy comprises the following steps:

[0020] Combining the planned speed and the cycle duration of the current time cycle, calculating the planned driving distance of the target vehicle within the current time cycle;

[0021] Acquire the periodic driving distance of the target vehicle in the current time period based on the given variable time interval;

[0022] Calculating the difference between the planned driving distance and the periodic driving distance to obtain the position deviation of the target vehicle;

[0023] Based on the position deviation and according to the position PID control strategy, a speed compensation transfer function of the target vehicle is constructed;

[0024] The speed compensation transfer function is discretized to obtain a discrete speed compensation function, and the speed compensation of the target vehicle in the current time period is calculated according to the discrete speed compensation function.

[0025] Optionally, the calculation formula of the position deviation is as follows:

[0026] e s (t) = v set *T k -S(k),e s (t)≥d s

[0027] Where: e s (t) represents the position deviation, υ set represents the planning speed, k represents the current time period, T k represents the cycle duration of the current time period, S(k) represents the cycle driving distance within the current time period, and d s represents the given variable time interval;

[0028] The speed compensation transfer function is expressed as follows:

[0029] V B (t) = K pa (e s (t)+(∫e s (t)dt) / K Ia )

[0030] Where: V B (t) represents the speed compensation of the target vehicle, K pa Represents the proportionality coefficient, K Ia represents the integral coefficient;

[0031] The expression formula of the discrete speed compensation function is as follows:

[0032]

[0033] Where: T s Indicates the time period, nT s represents the nth time period, V B (nT s ) represents the speed compensation in the nth time period, e s (nT s ) represents the position deviation within the nth time period.

[0034] Optionally, the step of combining the target driving speed, the planned speed and the speed compensation and calculating the acceleration compensation of the target vehicle based on a speed PID control strategy comprises the following steps:

[0035] Calculating the speed deviation of the target vehicle by combining the target driving speed, the planned speed and the speed compensation;

[0036] Constructing an acceleration compensation transfer function based on the speed deviation and in accordance with a speed PID control strategy;

[0037] Discretizing the acceleration compensation transfer function to obtain a discrete acceleration compensation function, and calculating the acceleration compensation of the target vehicle according to the discrete acceleration compensation function;

[0038] The speed deviation is calculated as follows:

[0039] e υ (t) = v set +V B (t)+V act

[0040] Where: e υ (t) represents the speed deviation, υ set represents the planned speed, V B (t) represents the speed compensation, V act represents the target driving speed;

[0041] The expression formula of the discrete acceleration compensation function is as follows:

[0042]

[0043] Where: T s Indicates the time period, nT s represents the nth time period, U a (nT s ) represents the acceleration compensation in the nth time period, K pa Represents the proportionality coefficient, K Ia Indicates the integral coefficient, eυ (nT s ) represents the speed deviation within the nth time period.

[0044] Optionally, before calculating the acceleration deviation based on the acceleration compensation and according to the acceleration PID control strategy, the following steps are also included:

[0045] Constructing a planned acceleration adaptive model of the target vehicle in combination with a preset maximum acceleration of the target vehicle and a preset adjustment coefficient;

[0046] generating a speed adjustment factor by combining the planned speed and the target driving speed, and adjusting the adjustment coefficient in the planned acceleration adaptive model by the speed adjustment factor;

[0047] The planned acceleration of the target vehicle is calculated by using the planned acceleration adaptive model after adjusting the adjustment coefficient;

[0048] The speed adjustment factor is expressed as follows:

[0049] C(s)=[(υ set -V act )T s / υ set ]

[0050] Wherein: C(s) represents the speed adjustment factor;

[0051] The expression formula of the planned acceleration adaptive model is as follows:

[0052]

[0053] Where: a set represents the planned acceleration, β, γ, λ, μ all represent the adjustment coefficients, a max1 and a max2 Both represent the maximum acceleration, and a1 and a2 both represent preset speed adjustment values.

[0054] Optionally, the step of calculating the acceleration deviation based on the acceleration compensation and according to the acceleration PID control strategy comprises the following steps:

[0055] Continuously sampling the real-time speed at a plurality of moments from the target driving speed based on the time period;

[0056] Combining the real-time speed and the speed deviation and using a weighted fitting method to calculate the actual acceleration of the target vehicle;

[0057] Combining the planned acceleration, the acceleration compensation and the real-time acceleration, and calculating the acceleration deviation of the target vehicle according to the acceleration PID control strategy;

[0058] The calculation formula of the acceleration deviation is as follows:

[0059] e a (t) = U a (nT s )+a set -a act

[0060] Where: e a (t) represents the acceleration deviation, a act represents the actual acceleration.

[0061] Optionally, the calculating the control torque of the target vehicle according to the acceleration deviation, and adjusting the target driving speed of the target vehicle by the control torque comprises the following steps:

[0062] Constructing a torque compensation transfer function of the target vehicle based on the acceleration deviation and according to a torque PID control strategy;

[0063] Discretizing the torque compensation transfer function to obtain a discrete torque compensation function, and calculating the torque compensation of the target vehicle according to the discrete torque compensation function;

[0064] Calculating the planned torque of the target vehicle using a vehicle dynamics equation;

[0065] Adding the planned torque to the torque compensation to obtain the control torque of the target vehicle, and adjusting the target driving speed of the target vehicle by the control torque;

[0066] The expression formula of the discrete torque compensation function is as follows:

[0067]

[0068] Where: U T (nT s ) represents the torque compensation in the nth time period, K PT Represents the proportionality coefficient, K IT Indicates the integral coefficient, K DT represents the differential coefficient, e a (nT s ) represents the acceleration deviation in the nth time period.

[0069] In a second aspect, the present invention further provides an electric vehicle adaptive cruise control system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in the first aspect when executing the computer program.

[0070] In a third aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method described in the first aspect.

[0071] The beneficial effects of the present invention are:

[0072] The electric vehicle adaptive cruise layered control method adopted by the present invention comprises the following steps: obtaining the driving speed of a vehicle ahead of the target vehicle through an on-board radar of the target vehicle; obtaining the target driving speed, a given variable time headway and a given variable time headway of the target vehicle in real time; combining the driving speed of the preceding vehicle and the given variable time headway, and calculating the planned speed of the target vehicle according to a safety distance control strategy; combining the given variable time headway and the planned speed, and calculating the speed compensation of the target vehicle based on a position PID control strategy; combining the target driving speed, the planned speed and the speed compensation, and calculating the acceleration compensation of the target vehicle based on a speed PID control strategy; calculating the acceleration deviation based on the acceleration compensation and according to the acceleration PID control strategy; calculating the control torque of the target vehicle according to the acceleration deviation, and adjusting the target driving speed of the target vehicle by the control torque.

[0073] Compared with the prior art that only uses the speed PID control strategy to adjust the driving speed of the vehicle, the present invention adopts the position PID control strategy, the speed PID control strategy and the acceleration PID control strategy to jointly control the speed. In particular, the acceleration PID control strategy can be adjusted according to the current acceleration of the target vehicle, so that the vehicle can more accurately control the stability of the vehicle speed after reaching the set cruising speed. Through joint control, the speed difference fluctuation problem between the actual vehicle speed and the set cruising speed can be better solved. Through the setting of the acceleration PID control strategy, the driving force or braking force can be adjusted more quickly according to the current acceleration demand of the vehicle, so that the vehicle can reach the set cruising speed more quickly. And through the acceleration PID control strategy, the acceleration and braking force of the vehicle can be better balanced to avoid excessive acceleration or braking during long-term cruising, thereby providing higher riding comfort. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] Figure 1 It is a flow chart of the hierarchical control method for adaptive cruise control of an electric vehicle in the present invention.

[0075] Figure 2This is a system architecture diagram of an electric vehicle adaptive cruise control system in one embodiment of the present invention.

[0076] Figure 3 It is a flow chart of a longitudinal controller executing a hierarchical control method for adaptive cruise control of an electric vehicle in one embodiment of the present invention. DETAILED DESCRIPTION

[0077] The invention discloses a hierarchical control method for adaptive cruise control of an electric vehicle.

[0078] Reference Figure 1 , the electric vehicle adaptive cruise control method comprises the following steps:

[0079] S101. Obtain the driving speed of the vehicle in front of the target vehicle through the on-board radar of the target vehicle.

[0080] The vehicle-mounted radar transmits a radar beam to the vehicle in front of the target vehicle. The radar beam interacts with the vehicle in front, and the reflected beam is received by the receiver of the vehicle-mounted radar. The receiver converts the received beam into an electrical signal. By processing the electrical signal, the speed of the vehicle in front can be calculated.

[0081] S102. Obtain the target driving speed of the target vehicle in real time and calculate the given variable time headway of the target vehicle.

[0082] Among them, the target driving speed of the target vehicle is obtained through the sensor of the target vehicle, and the expected distance, that is, the expected distance interval between the target vehicle and the preceding vehicle, can also be obtained from the system settings of the vehicle. The expected distance is pre-input by the personnel on the target vehicle through the vehicle-mounted system. The given variable time interval of the target vehicle can be calculated by combining the target driving speed and the expected distance.

[0083] S103. Combining the speed of the preceding vehicle and the given variable headway, and calculating the planned speed of the target vehicle according to the safety distance control strategy.

[0084] The speed of the preceding vehicle is combined with the given variable headway, and the planned speed of the target vehicle is calculated according to the safety distance control strategy. The safety distance control strategy usually considers factors such as the minimum safety distance between vehicles and the braking capacity of the vehicles.

[0085] S104. Combine the given variable time interval and the planned speed, and calculate the speed compensation of the target vehicle based on the position PID control strategy.

[0086] The given variable time headway of the target vehicle is combined with the planned speed, and the speed compensation of the target vehicle is calculated based on the position PID control strategy. The position PID control strategy generally adjusts the speed compensation by calculating the error between the target vehicle's travel distance and the given variable time headway.

[0087] S105. Combine the target driving speed, the planned speed and the speed compensation, and calculate the acceleration compensation of the target vehicle based on the speed PID control strategy.

[0088] The target driving speed, planned speed and speed compensation of the target vehicle are combined, and the acceleration compensation of the target vehicle is calculated based on the speed PID control strategy. The speed PID control strategy generally adjusts the magnitude of the acceleration compensation by calculating the speed error and speed change rate of the target vehicle.

[0089] S106. Calculate the acceleration deviation based on the acceleration compensation and the acceleration PID control strategy.

[0090] The acceleration of the target vehicle is calculated based on the acceleration compensation, and the acceleration deviation is calculated based on the acceleration PID control strategy. The acceleration PID control strategy generally adjusts the magnitude of the acceleration deviation by calculating the acceleration error and the acceleration change rate.

[0091] S107. Calculate the control torque of the target vehicle according to the acceleration deviation, and adjust the target driving speed of the target vehicle by the control torque.

[0092] The control torque of the target vehicle can be calculated based on the acceleration deviation. The acceleration of the target vehicle can be changed by adjusting the control torque. And the target driving speed of the target vehicle can be adjusted and controlled by adjusting the control torque.

[0093] The implementation principle of this embodiment is:

[0094] Compared with the prior art that only uses the speed PID control strategy to adjust the driving speed of the vehicle, the present invention adopts the position PID control strategy, the speed PID control strategy and the acceleration PID control strategy to jointly control the speed. In particular, the acceleration PID control strategy can be adjusted according to the current acceleration of the target vehicle, so that the vehicle can more accurately control the stability of the vehicle speed after reaching the set cruising speed. Through joint control, the speed difference fluctuation problem between the actual vehicle speed and the set cruising speed can be better solved. Through the setting of the acceleration PID control strategy, the driving force or braking force can be adjusted more quickly according to the current acceleration demand of the vehicle, so that the vehicle can reach the set cruising speed more quickly. And through the acceleration PID control strategy, the acceleration and braking force of the vehicle can be better balanced to avoid excessive acceleration or braking during long-term cruising, thereby providing higher riding comfort.

[0095] In one embodiment, step S103, i.e., combining the speed of the preceding vehicle and the given variable headway and calculating the planned speed of the target vehicle according to the safety distance control strategy, specifically comprises the following steps:

[0096] Constructing a variable safety distance model based on a given variable time headway and a safety distance control strategy;

[0097] Substitute the speed of the preceding vehicle into the variable safety distance model to calculate the planned speed of the target vehicle;

[0098] The model formula of the variable safety distance model is as follows:

[0099]

[0100] Where: d s Denotes a given variable time interval, υ set represents the planning speed, T h represents the target vehicle driver's reaction time, υ p Indicates the speed of the preceding vehicle, a min represents the minimum braking deceleration of the target vehicle, and Δx represents the safe distance between the target vehicle and the vehicle in front when stopping.

[0101] In this implementation, the safe distance determines the safe following distance of the target vehicle. If the safe distance is too large, the lane traffic efficiency will be too low, and vehicles in the side lanes will change lanes or vehicles behind will overtake. If the safe distance is too small, there will be no time to react when the front vehicle brakes suddenly, resulting in dangerous conditions. The traditional expected safe distance calculation adopts a fixed headway time (VTH) strategy. The safe distance between vehicles is fixed during driving, and the surrounding traffic environment is not considered. This strategy has a simple structure, but it cannot meet the complex and changeable deceleration behavior of the front vehicle in actual driving.

[0102] In this embodiment, a variable safe vehicle distance model can be constructed according to the safe distance control strategy. Since the reaction time of the driver of the target vehicle, the minimum braking deceleration of the target vehicle, the safe vehicle distance between the target vehicle and the vehicle in front when stopping, and the given variable time headway are all pre-acquired quantitative quantities, it is only necessary to substitute the driving speed of the vehicle in front into the variable safe vehicle distance model to calculate the planned speed of the target vehicle.

[0103] In one embodiment, step S104, namely, combining the given variable time headway and the planned speed and calculating the speed compensation of the target vehicle based on the position PID control strategy, specifically comprises the following steps:

[0104] Combining the planned speed and the cycle duration of the current time cycle, the planned driving distance of the target vehicle in the current time cycle is calculated;

[0105] Obtaining a periodic driving distance of a target vehicle in a current time period based on a given variable time interval;

[0106] Calculate the difference between the planned driving distance and the periodic driving distance to obtain the position deviation of the target vehicle;

[0107] Based on the position deviation and according to the position PID control strategy, a speed compensation transfer function of the target vehicle is constructed;

[0108] The speed compensation transfer function is discretized to obtain a discrete speed compensation function, and the speed compensation of the target vehicle in the current time period is calculated according to the discrete speed compensation function.

[0109] In this embodiment, the calculation formula of the position deviation is as follows:

[0110] e s (t) = v set *T k -S(k),e s (t)≥d s

[0111] Where: e s (t) represents the position deviation, υ set represents the planning speed, k represents the current time period, T k represents the cycle duration of the current time period, S(k) represents the cycle driving distance within the current time period, and d s Represents a given variable time interval, e s The t in (t) indicates that the data attribute is continuous data rather than discrete data;

[0112] The speed compensation transfer function is expressed as follows:

[0113] V B(t) = K pa (e s (t)+(∫e s (t)dt) / K Ia )

[0114] Where: V B (t) represents the speed compensation of the target vehicle, K pa Represents the proportionality coefficient, K Ia Indicates the integral coefficient, V B The t in (t) indicates that the data attribute is continuous data rather than discrete data;

[0115] The expression formula of discrete speed compensation function is as follows:

[0116]

[0117] Where: T s Indicates the time period, nT s Indicates the nth time period, V B (nT s ) represents the speed compensation in the nth time period, e s (nT s ) represents the position deviation in the nth time period.

[0118] In one embodiment, step S105, i.e. combining the target driving speed, the planned speed and the speed compensation, and calculating the acceleration compensation of the target vehicle based on the speed PID control strategy, specifically includes the following steps:

[0119] The speed deviation of the target vehicle is calculated by combining the target driving speed, the planned speed and the speed compensation;

[0120] Based on the speed deviation and according to the speed PID control strategy, the acceleration compensation transfer function is constructed;

[0121] The acceleration compensation transfer function is discretized to obtain a discrete acceleration compensation function, and the acceleration compensation of the target vehicle is calculated according to the discrete acceleration compensation function;

[0122] The speed deviation is calculated as follows:

[0123] e υ (t) = v set +V B (t)+V act

[0124] Where: e υ (t) represents the speed deviation, υ set represents the planning speed, V B (t) represents speed compensation, V actrepresents the target driving speed, e υ The t in (t) indicates that the data attribute is continuous data rather than discrete data;

[0125] The expression formula of discrete acceleration compensation function is as follows:

[0126]

[0127] Where: T s Indicates the time period, nT s represents the nth time period, U a (nT s ) represents the acceleration compensation in the nth time period, K pa Represents the proportionality coefficient, K Ia Indicates the integral coefficient, e υ (nT s ) represents the speed deviation in the nth time period.

[0128] In one embodiment, before step S106, i.e., calculating the acceleration deviation based on the acceleration compensation and according to the acceleration PID control strategy, the following steps are also included:

[0129] A planned acceleration adaptive model of the target vehicle is constructed by combining a preset maximum acceleration of the target vehicle and a preset adjustment coefficient;

[0130] A speed adjustment factor is generated by combining the planned speed and the target driving speed, and the adjustment coefficient in the planned acceleration adaptive model is adjusted by the speed adjustment factor;

[0131] The planned acceleration of the target vehicle is calculated by using the planned acceleration adaptive model after adjusting the adjustment coefficient;

[0132] The speed adjustment factor is expressed as follows:

[0133] C(s)=[(υ set -V act )T s / υ set ]

[0134] Where: C(s) represents the speed adjustment factor;

[0135] The expression formula of the planning acceleration adaptive model is as follows:

[0136]

[0137] Where: a set represents the planned acceleration, β, γ, λ, μ all represent adjustment coefficients, a max1 and a max2Both represent the maximum acceleration, and a1 and a2 both represent the preset speed adjustment value.

[0138] In this embodiment, the planned acceleration is a fusion value of the driving and braking conditions, that is, when the target vehicle has a driving acceleration requirement, the planned acceleration sign is positive; when the target vehicle has a braking deceleration requirement, the planned acceleration sign is negative, also known as the planned deceleration. In order to obtain a more accurate planned acceleration, a speed adjustment factor is set to characterize the target vehicle's satisfaction with the acceleration requirement. For example, according to the speed adjustment factor C(s), the larger the C(s), the greater the deceleration capacity required by the target vehicle, and the greater the planned deceleration required at this time, so it is necessary to increase a accordingly. max2 The adjustment coefficient λ of the speed adjustment value a2 is appropriately reduced, thereby obtaining a larger planned deceleration value. act Reach planned speed set After that, the speed adjustment factor C(s) is cleared accordingly.

[0139] In one embodiment, step S106, i.e., calculating the acceleration deviation based on the acceleration compensation and according to the acceleration PID control strategy, specifically includes the following steps:

[0140] The real-time speed at multiple moments is continuously sampled from the target driving speed based on a time period;

[0141] The actual acceleration of the target vehicle is calculated by combining the real-time speed and speed deviation and using a weighted fitting method;

[0142] Combining the planned acceleration, acceleration compensation and real-time acceleration, and calculating the acceleration deviation of the target vehicle according to the acceleration PID control strategy;

[0143] The acceleration deviation is calculated as follows:

[0144] e a (t) = U a (nT s )+a set -a act

[0145] Where: e a (t) represents the acceleration deviation, a act Indicates the actual acceleration, e a The t in (t) indicates that the data attribute is continuous data rather than discrete data.

[0146] In this embodiment, continuously sampling the real-time speed at four moments, combining the real-time speed and the speed deviation and using a weighted fitting method to calculate the actual acceleration of the target vehicle specifically includes the following steps:

[0147] If the speed deviation is greater than or equal to 0 and less than the first deviation threshold, the calculation formula for calculating the actual acceleration of the target vehicle using the weighted fitting method is as follows:

[0148]

[0149] Where: a act represents the actual acceleration, λ1, λ2, and λ3 are weighting coefficients, and λ3=λ1+λ2, λ2=2λ1, V0, V1, V2, and V3 are the real-time speeds of four consecutive sampling moments, respectively, T s For the time period.

[0150] If the speed deviation is greater than or equal to the first deviation threshold and less than the second deviation threshold, and the second deviation threshold is greater than the first deviation threshold, the calculation formula for calculating the actual acceleration of the target vehicle using the weighted fitting method is as follows:

[0151]

[0152] In the formula: λ2=2λ1.

[0153] If the speed deviation is greater than or equal to the second deviation threshold, the calculation formula for calculating the actual acceleration of the target vehicle using the weighted fitting method is as follows:

[0154]

[0155] In this implementation, the first deviation threshold may be 1.5, and the second deviation threshold may be 3.5.

[0156] In one embodiment, step S107, i.e., calculating the control torque of the target vehicle according to the acceleration deviation, and adjusting the target driving speed of the target vehicle by the control torque, specifically includes the following steps:

[0157] Constructing a torque compensation transfer function of the target vehicle based on the acceleration deviation and according to the torque PID control strategy;

[0158] The torque compensation transfer function is discretized to obtain a discrete torque compensation function, and the torque compensation of the target vehicle is calculated according to the discrete torque compensation function;

[0159] The planned torque of the target vehicle is calculated using the vehicle dynamics equation;

[0160] The planned torque is added to the torque compensation to obtain the control torque of the target vehicle, and the target driving speed of the target vehicle is adjusted by the control torque;

[0161] The expression formula of discrete torque compensation function is as follows:

[0162]

[0163] Where: U T (nT s ) represents the torque compensation in the nth time period, K PT Represents the proportionality coefficient, K IT Indicates the integral coefficient, K DT represents the differential coefficient, e a (nT s ) represents the acceleration deviation in the nth time period.

[0164] In this embodiment, the torque compensation transfer function of the target vehicle is constructed based on the acceleration deviation and according to the torque PID control strategy. The expression formula is as follows:

[0165]

[0166] Where: U T (t) represents torque compensation, U T The t in (t) indicates that the data attribute is continuous data rather than discrete data.

[0167] The calculation formula of the planned torque of the target vehicle is calculated using the vehicle dynamics equation as follows:

[0168] T tag ·i g ·i o ·η T / r=mg·f+C w ·A·(V act ) 2 / 21.15+δ·m·a set

[0169] Where: T tag represents the planned torque of the target vehicle, i g represents the gearbox ratio of the target vehicle, i o represents the drive axle ratio of the target vehicle, η T represents the transmission efficiency, r represents the tire radius of the target vehicle, mg represents the mass of the target vehicle, f represents the friction coefficient, C w represents the drag coefficient, A represents the windward area of ​​the target vehicle during driving, V act represents the target driving speed, δ represents the rotational mass coefficient, a set represents the planned acceleration.

[0170] The planned torque is added to the torque compensation to obtain the control torque of the target vehicle, and the target driving speed of the target vehicle is adjusted by the control torque. When the calculated control torque is greater than 0, the target vehicle will be in an acceleration state; when the control torque is equal to 0, the target vehicle will be in a cruise control state; when the control torque is less than 0, the target vehicle will be in a deceleration state.

[0171] The present invention also discloses an electric vehicle adaptive cruise control system, comprising a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the electric vehicle adaptive cruise control method in any of the above-mentioned embodiments is implemented.

[0172] In one embodiment, referring to Figure 2 , Figure 2 The system architecture diagram of the electric vehicle adaptive cruise control system in this embodiment. The ACC upper controller calculates the desired speed based on the environmental information data transmitted by various vehicle-mounted sensors, and the ACC lower controller obtains the vehicle controlled torque through a double closed-loop control strategy, thereby achieving acceleration, constant speed, and deceleration of the target vehicle. The longitudinal controller is mainly used to execute the electric vehicle adaptive cruise control method. In this embodiment, the process of the longitudinal controller executing the electric vehicle adaptive cruise control method is specifically referred to Figure 3 .

[0173] The implementation principle of this embodiment is:

[0174] The following steps are executed by calling the program: the speed of the vehicle in front of the target vehicle is obtained through the on-board radar of the target vehicle; the target speed, given variable headway and given variable headway of the target vehicle are obtained in real time; the planned speed of the target vehicle is calculated based on the safety distance control strategy in combination with the speed of the vehicle in front and the given variable headway; the speed compensation of the target vehicle is calculated based on the position PID control strategy in combination with the given variable headway and the planned speed; the acceleration compensation of the target vehicle is calculated based on the speed PID control strategy in combination with the target speed, the planned speed and the speed compensation; the acceleration deviation is calculated based on the acceleration compensation and according to the acceleration PID control strategy; the control torque of the target vehicle is calculated based on the acceleration deviation, and the target speed of the target vehicle is adjusted by the control torque.

[0175] Through the execution of the above steps, compared with the prior art that only uses the speed PID control strategy to adjust the driving speed of the vehicle, the present invention adopts the position PID control strategy, the speed PID control strategy and the acceleration PID control strategy to jointly control the speed. In particular, the acceleration PID control strategy can be adjusted according to the current acceleration of the target vehicle, so that the vehicle can more accurately control the stability of the vehicle speed after reaching the set cruising speed. Through the joint control, the speed difference fluctuation problem between the actual vehicle speed and the set cruising speed can be better solved. Through the setting of the acceleration PID control strategy, the driving force or braking force can be adjusted more quickly according to the current acceleration demand of the vehicle, so that the vehicle can reach the set cruising speed more quickly. And through the acceleration PID control strategy, the acceleration and braking force of the vehicle can be better balanced, avoiding excessive acceleration or braking during long-term cruising, thereby providing higher riding comfort.

[0176] The present invention also discloses a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the electric vehicle adaptive cruise layered control method in any of the above-mentioned embodiments are implemented.

[0177] The implementation principle of this embodiment is:

[0178] The following steps are executed by calling the program: the speed of the vehicle in front of the target vehicle is obtained through the on-board radar of the target vehicle; the target speed, given variable headway and given variable headway of the target vehicle are obtained in real time; the planned speed of the target vehicle is calculated based on the safety distance control strategy in combination with the speed of the vehicle in front and the given variable headway; the speed compensation of the target vehicle is calculated based on the position PID control strategy in combination with the given variable headway and the planned speed; the acceleration compensation of the target vehicle is calculated based on the speed PID control strategy in combination with the target speed, the planned speed and the speed compensation; the acceleration deviation is calculated based on the acceleration compensation and according to the acceleration PID control strategy; the control torque of the target vehicle is calculated based on the acceleration deviation, and the target speed of the target vehicle is adjusted by the control torque.

[0179] Through the execution of the above steps, compared with the prior art that only uses the speed PID control strategy to adjust the driving speed of the vehicle, the present invention adopts the position PID control strategy, the speed PID control strategy and the acceleration PID control strategy to jointly control the speed. In particular, the acceleration PID control strategy can be adjusted according to the current acceleration of the target vehicle, so that the vehicle can more accurately control the stability of the vehicle speed after reaching the set cruising speed. Through the joint control, the speed difference fluctuation problem between the actual vehicle speed and the set cruising speed can be better solved. Through the setting of the acceleration PID control strategy, the driving force or braking force can be adjusted more quickly according to the current acceleration demand of the vehicle, so that the vehicle can reach the set cruising speed more quickly. And through the acceleration PID control strategy, the acceleration and braking force of the vehicle can be better balanced, avoiding excessive acceleration or braking during long-term cruising, thereby providing higher riding comfort.

[0180] A person skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of protection of the present application is limited to these examples. In line with the concept of the present application, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of different aspects of one or more embodiments of the present application as above, which are not provided in detail for the sake of simplicity.

[0181] One or more embodiments of the present application are intended to cover all such substitutions, modifications and variations that fall within the broad scope of the present application. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of one or more embodiments of the present application should be included in the protection scope of the present application.

Claims

1. A hierarchical control method for adaptive cruise control of an electric vehicle, characterized in that: The steps include: Acquiring the driving speed of the vehicle ahead of the target vehicle through the on-board radar of the target vehicle; Acquire the target driving speed of the target vehicle in real time and calculate the given variable time headway of the target vehicle; Combining the speed of the preceding vehicle and the given variable headway, and calculating the planned speed of the target vehicle according to a safety distance control strategy; Combining the given variable time headway and the planned speed, and calculating the speed compensation of the target vehicle based on the position PID control strategy; Combining the target driving speed, the planned speed and the speed compensation, and calculating the acceleration compensation of the target vehicle based on a speed PID control strategy; Based on the acceleration compensation and according to the acceleration PID control strategy, an acceleration deviation is calculated; The control torque of the target vehicle is calculated according to the acceleration deviation, and the target driving speed of the target vehicle is adjusted by the control torque.

2. The electric vehicle adaptive cruise control method according to claim 1, characterized in that: The step of combining the preceding vehicle's speed and the given variable headway and calculating the planned speed of the target vehicle according to the safety distance control strategy comprises the following steps: Building a variable safe vehicle distance model based on the given variable time headway and in accordance with a safe distance control strategy; Substituting the preceding vehicle's speed into the variable safe vehicle distance model, and calculating the planned speed of the target vehicle; The model formula of the variable safety vehicle distance model is as follows: Where: d s Denotes the given variable time interval, v set represents the planned speed, T h represents the reaction time of the target vehicle driver, v p represents the speed of the preceding vehicle, a min represents the minimum braking deceleration of the target vehicle, and Δx represents the safe distance between the target vehicle and the vehicle ahead when the target vehicle stops.

3. The electric vehicle adaptive cruise control method according to claim 1, characterized in that: The method of combining the given variable time interval and the planned speed and calculating the speed compensation of the target vehicle based on the position PID control strategy comprises the following steps: Combining the planned speed and the cycle duration of the current time cycle, calculating the planned driving distance of the target vehicle within the current time cycle; Acquire the periodic driving distance of the target vehicle in the current time period based on the given variable time interval; Calculating the difference between the planned driving distance and the periodic driving distance to obtain the position deviation of the target vehicle; Based on the position deviation and according to the position PID control strategy, a speed compensation transfer function of the target vehicle is constructed; The speed compensation transfer function is discretized to obtain a discrete speed compensation function, and the speed compensation of the target vehicle in the current time period is calculated according to the discrete speed compensation function.

4. The electric vehicle adaptive cruise control method according to claim 3, characterized in that: The calculation formula of the position deviation is as follows: e s (t)=v set *T k -S(k),e s (t)≥d s Where: e s (t) represents the position deviation, υ set represents the planning speed, k represents the current time period, T k represents the cycle duration of the current time period, S(k) represents the cycle driving distance within the current time period, and d s represents the given variable time interval; The speed compensation transfer function is expressed as follows: V B (t)=K pa (e s (t)+(∫e s (t)dt) / K Ia ) Where: V B (t) represents the speed compensation of the target vehicle, K pa Represents the proportionality coefficient, K Ia represents the integral coefficient; The expression formula of the discrete speed compensation function is as follows: Where: T s Indicates the time period, nT s represents the nth time period, V B (nT s ) represents the speed compensation in the nth time period, e s (nT s ) represents the position deviation within the nth time period.

5. The electric vehicle adaptive cruise control method according to claim 1, characterized in that: The step of combining the target driving speed, the planned speed and the speed compensation and calculating the acceleration compensation of the target vehicle based on the speed PID control strategy comprises the following steps: Calculating the speed deviation of the target vehicle by combining the target driving speed, the planned speed and the speed compensation; Constructing an acceleration compensation transfer function based on the speed deviation and in accordance with a speed PID control strategy; Discretizing the acceleration compensation transfer function to obtain a discrete acceleration compensation function, and calculating the acceleration compensation of the target vehicle according to the discrete acceleration compensation function; The speed deviation is calculated as follows: e v (t)=υ set +V B (t)+V act Where: e v (t) represents the speed deviation, v set represents the planned speed, V B (t) represents the speed compensation, V act represents the target driving speed; The expression formula of the discrete acceleration compensation function is as follows: Where: T s Indicates the time period, nT s represents the nth time period, U a (nT s ) represents the acceleration compensation in the nth time period, K pa Represents the proportionality coefficient, K Ia Indicates the integral coefficient, e v (nT s ) represents the speed deviation within the nth time period.

6. The electric vehicle adaptive cruise control hierarchical method according to claim 5, characterized in that: Before the acceleration deviation is calculated based on the acceleration compensation and according to the acceleration PID control strategy, the following steps are also included: Constructing a planned acceleration adaptive model of the target vehicle in combination with a preset maximum acceleration of the target vehicle and a preset adjustment coefficient; generating a speed adjustment factor by combining the planned speed and the target driving speed, and adjusting the adjustment coefficient in the planned acceleration adaptive model by the speed adjustment factor; The planned acceleration of the target vehicle is calculated by using the planned acceleration adaptive model after adjusting the adjustment coefficient; The speed adjustment factor is expressed as follows: C(s)=[(υ set -V act )T s / v set ] Wherein: C(s) represents the speed adjustment factor; The expression formula of the planned acceleration adaptive model is as follows: Where: a set represents the planned acceleration, β, γ, λ, μ all represent the adjustment coefficients, a max1 and a max2 Both represent the maximum acceleration, and a1 and a2 both represent preset speed adjustment values.

7. The electric vehicle adaptive cruise control hierarchical method according to claim 6, characterized in that: The acceleration deviation is calculated based on the acceleration compensation and according to the acceleration PID control strategy, comprising the following steps: Continuously sampling the real-time speed at a plurality of moments from the target driving speed based on the time period; Combining the real-time speed and the speed deviation and using a weighted fitting method to calculate the actual acceleration of the target vehicle; Combining the planned acceleration, the acceleration compensation and the real-time acceleration, and calculating the acceleration deviation of the target vehicle according to the acceleration PID control strategy; The calculation formula of the acceleration deviation is as follows: e a (t)=U a (nT s )+a set -a act Where: e a (t) represents the acceleration deviation, a act represents the actual acceleration.

8. The electric vehicle adaptive cruise control method according to claim 7, characterized in that: The step of calculating the control torque of the target vehicle according to the acceleration deviation and adjusting the target driving speed of the target vehicle by the control torque comprises the following steps: Constructing a torque compensation transfer function of the target vehicle based on the acceleration deviation and according to a torque PID control strategy; Discretizing the torque compensation transfer function to obtain a discrete torque compensation function, and calculating the torque compensation of the target vehicle according to the discrete torque compensation function; Calculating the planned torque of the target vehicle using a vehicle dynamics equation; Adding the planned torque to the torque compensation to obtain the control torque of the target vehicle, and adjusting the target driving speed of the target vehicle by the control torque; The expression formula of the discrete torque compensation function is as follows: Where: U T (nT s ) represents the torque compensation in the nth time period, K PT Represents the proportionality coefficient, K IT Indicates the integral coefficient, K DT represents the differential coefficient, e a (nT s ) represents the acceleration deviation in the nth time period.

9. An electric vehicle adaptive cruise control system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 8 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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