阅读说明：本技术 一种纯电动客车自适应巡航纵向控制方法、装置及电子设备 (Self-adaptive cruise longitudinal control method and device for pure electric bus and electronic equipment ) 是由 赵苗苗 黄萍 李桉楠 芮苏黔 刘瑶秋 于 2021-09-27 设计创作，主要内容包括：本发明属于纯电动客车控制技术领域,提供一种纯电动客车自适应巡航纵向控制方法、装置及电子设备。该控制方法包括以下步骤：S1：计算安全车间距和紧急制动临界距离；S2：判定本车处于定速巡航模式或跟车巡航模式；S3:基于PID控制计算定速巡航模式下的期望纵向加速度或基于模型预测控制计算跟车巡航模式下的期望纵向加速度；S4：确定本车切换驱动或制动状态；S5：将期望纵向加速度转变为对应的电机驱动力矩或对应的车辆制动力,完成对车辆的控制。该控制方法无需对每辆车控制器增益系数进行参数标定,可实时输出期望纵向加速度,时效性强,在保证舒适性的前提下使车速尽快达到设定车速。(The invention belongs to the technical field of pure electric bus control, and provides a method and a device for self-adaptive cruise longitudinal control of a pure electric bus and electronic equipment. The control method comprises the following steps: s1: calculating a safe inter-vehicle distance and an emergency braking critical distance; s2: judging that the vehicle is in a constant-speed cruise mode or a following cruise mode; s3, calculating the expected longitudinal acceleration under the constant-speed cruise mode based on PID control or calculating the expected longitudinal acceleration under the following cruise mode based on model prediction control; s4: determining the driving or braking state of the vehicle switching; s5: and converting the expected longitudinal acceleration into corresponding motor driving torque or corresponding vehicle braking force to finish the control of the vehicle. The control method does not need to calibrate the gain coefficient of each vehicle controller, can output expected longitudinal acceleration in real time, has strong timeliness, and enables the vehicle speed to reach the set vehicle speed as soon as possible on the premise of ensuring comfort.)

1. A self-adaptive cruise longitudinal control method of a pure electric bus is characterized by comprising the following steps:

s1: obtaining the speed of the vehicle and the speed of the front vehicle and calculating the safe inter-vehicle distance and the emergency braking critical distance;

s2: obtaining the distance between the vehicle and the front vehicle and judging that the vehicle is in a constant-speed cruise mode or a following cruise mode according to the safe inter-vehicle distance and the critical emergency braking distance;

s3, if the vehicle is in the constant speed cruise mode, calculating the expected longitudinal acceleration in the constant speed cruise mode based on PID control; if the vehicle is in the following vehicle cruise mode, calculating expected longitudinal acceleration in the following vehicle cruise mode based on model prediction control;

s4: determining the vehicle switching driving or braking state according to the expected longitudinal acceleration;

s5: if the vehicle is in a driving state, converting the expected longitudinal acceleration into a corresponding motor driving torque to complete the control of the vehicle; if the vehicle is in a braking state, converting the expected longitudinal acceleration into corresponding vehicle braking force; the control of the vehicle is completed.

2. The control method according to claim 1, wherein the step S1 is specifically:

calculating the safe inter-vehicle distance:

d_safe＝τv_h+d₀

in the formula: d_safeFor safe inter-vehicle distance, τ is inter-vehicle time distance, v_hFor the speed of the vehicle, d₀The minimum distance between the two vehicles in a static state;

calculating an emergency braking critical distance:

in the formula: d_emergencyCritical distance for emergency braking, t_sFor brake system response time, v_hIs the speed of the vehicle, v_relRelative speed of front and rear vehicles, a_maxMaximum acceleration in emergency braking conditions, d₀The minimum distance between the two vehicles in a static state.

3. The control method according to claim 2, wherein the step S2 is specifically:

when no vehicle exists in front, or the distance between the vehicle and the front vehicle is larger than the safe inter-vehicle distance, or the speed of the front vehicle is larger than the speed of the vehicle, the vehicle is judged to be in a constant-speed cruise mode; and when the distance between the vehicle and the front vehicle is smaller than the safe distance and larger than the emergency braking critical distance or the speed of the front vehicle is smaller than the speed of the vehicle, judging that the vehicle is in a following cruise mode.

4. The control method according to claim 3, wherein the step S2 further includes: and when the distance between the vehicle and the front vehicle is smaller than the emergency braking critical distance, judging that the vehicle enters an emergency braking mode.

5. The control method according to claim 3, wherein in step S3, when the host vehicle is in the constant-speed-cruise mode, the desired longitudinal acceleration is calculated as follows:

e(t)＝v_set-v_h

wherein e (t) is a velocity error, v_setIs a target vehicle speed, v_hU (t) is the desired acceleration, K_pIs a proportionality coefficient, K_iIs the integral coefficient, K_dIs a differential coefficient.

6. The control method according to claim 5, wherein in step S3, when the host vehicle is in the following cruise mode, the desired longitudinal acceleration is calculated as follows:

establishing a stable car following mode state space model as follows:

wherein x (k) ═ Δ d (k), v_rel(k)，v_h(k)，a_h(k)，j(k)]，Δd(k)＝d-d_safeIs a vehicle-to-vehicle distance error, a_h(k) Is the acceleration of the vehicle, j (k) is the rate of change of the acceleration of the vehicle, u (k) is the desired acceleration,w (k) is the front vehicle acceleration, y (k) ═ Δ d (k), v_rel(k)，a_h(k)，j(k)]A, B, G, C, Z is a coefficient matrix of the system, which is:

wherein, T_sFor the system sampling time, T_jIs a time constant, τ denotes the time interval between cars, d₀Representing a minimum inter-vehicle distance in a static state;

setting system constraints:

setting a constraint range for the distance between two vehicles, the deviation value of the actual distance between the vehicle and the front vehicle and the safe distance between the vehicle and the front vehicle, and the speed deviation value of the vehicle and the front vehicle; setting constraint ranges for the speed, the acceleration change rate and the control variable of the vehicle:

the comprehensive performance index function J is established as follows:

wherein Δ d (k) d-d_safeIs the vehicle spacing error, [ delta ] v [ (k)＝v_rel＝v_f-v_hIs the relative velocity, a_h(k) For the acceleration of the vehicle, Δ u (k) is the desired acceleration increment, ω_ΔdWeight coefficient, ω, for inter-vehicle distance error_ΔvIs a weight coefficient of relative velocity, ω_ahIs the weight coefficient, omega, of the acceleration of the vehicle_ΔuA weight coefficient for the desired acceleration increment, t being the integration time;

4) and acquiring the optimal expected car following acceleration corresponding to the optimization index at the moment k according to the stable car following mode state space model, the comprehensive performance index function and the system constraint.

7. The control method according to claim 6, wherein the step S4 is specifically:

pre-calibrating a driving brake switching curve corresponding to the vehicle speed, and adding buffer areas above and below the switching curve;

under the corresponding vehicle speed, if the acquired expected longitudinal acceleration is above the switching curve and the buffer area, the ACC system enters a driving state; if the acquired desired longitudinal acceleration is below the switching curve and the buffer zone, the ACC system enters a braking state.

8. The control method according to claim 1, wherein in step S5, when the host vehicle is in a driving state, the motor drive torque is calculated as follows:

in the formula, T_motorFor motor drive torque, i₀Is the transmission ratio of the transmission system eta_tFor transmission efficiency, r is the wheel rolling radius, C_DIs an air resistance coefficient, A is a windward area, theta is a road slope angle, m is the mass of the whole vehicle, a is an expected longitudinal acceleration output by the system, V is a longitudinal vehicle speed, f is a rolling resistance coefficient,is the running resistance;

when the vehicle is in a braking state, the vehicle braking force is calculated in the following way:

in the formula, F_bTo expect the vehicle braking force, C_DThe coefficient is an air resistance coefficient, A is a windward area, theta is a road slope angle, m is the mass of the whole vehicle, a is an expected longitudinal acceleration output by the system, V is a longitudinal vehicle speed, and f is a rolling resistance coefficient.

9. The utility model provides a pure [ electric ] motor coach self-adaptation longitudinal control device that cruises which characterized in that includes:

the calculation module is used for acquiring the speed of the vehicle and the speed of the front vehicle and calculating the safe inter-vehicle distance and the emergency braking critical distance;

the mode judging module is used for acquiring the distance between the vehicle and the front vehicle and judging that the vehicle is in a constant-speed cruise mode or a following cruise mode according to the safe inter-vehicle distance and the emergency braking critical distance;

an expected longitudinal acceleration calculation module, which is used for calculating the expected longitudinal acceleration in the constant-speed cruise mode based on PID control if the vehicle is in the constant-speed cruise mode; if the vehicle is in the following vehicle cruise mode, calculating expected longitudinal acceleration in the following vehicle cruise mode based on model prediction control;

the state switching module is used for determining the switching driving or braking state of the vehicle according to the expected longitudinal acceleration;

the conversion module is used for converting the expected longitudinal acceleration into corresponding motor driving torque to finish the control of the vehicle if the vehicle is in a driving state; and if the vehicle is in a braking state, converting the expected longitudinal acceleration into corresponding vehicle braking force to finish the control of the vehicle.

10. An electronic device, characterized in that the electronic device comprises:

at least one processor; and the number of the first and second groups,

a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the control method of any one of claims 1-8.

Technical Field

The invention relates to the technical field of pure electric bus control, in particular to a method and a device for self-adaptive cruise longitudinal control of a pure electric bus and electronic equipment.

Background

The self-adaptive cruise is a safety auxiliary driving system for automobile, which combines with constant-speed cruise control and vehicle forward collision early warning to realize the speed keeping or the proper distance keeping with the front automobile in the following process, thereby realizing the self-adaptive cruise function. The current self-adaptive cruise environment sensing system can accurately sense the relative position relation between peripheral objects and a vehicle in front and a main vehicle through various sensors such as a millimeter wave radar, a laser radar and a high-definition camera. The self-adaptive cruise system can control the vehicle to carry out speed control or distance control according to the information obtained by the sensing system, relieves the fatigue of a driver and improves the running safety of the vehicle.

At present, many adaptive cruise researches still aim at the traditional fuel oil vehicle, but the response speed of a motor in a power system of an electric vehicle is high, and the characteristics of the motor are greatly different from those of the traditional fuel oil vehicle, so that the traditional adaptive cruise control method is not suitable for a pure electric bus.

Disclosure of Invention

In view of the above, embodiments of the present invention provide a method, an apparatus, and an electronic device for adaptive cruise longitudinal control of a pure electric bus, so as to solve or partially solve the above problems.

In a first aspect, an embodiment of the invention provides a self-adaptive cruise longitudinal control method for a pure electric bus, which comprises the following steps:

s1: obtaining the speed of the vehicle and the speed of the front vehicle and calculating the safe inter-vehicle distance and the emergency braking critical distance;

s2: obtaining the distance between the vehicle and the front vehicle and judging that the vehicle is in a constant-speed cruise mode or a following cruise mode according to the safe inter-vehicle distance and the critical emergency braking distance;

s3, if the vehicle is in the constant speed cruise mode, calculating the expected longitudinal acceleration in the constant speed cruise mode based on PID control; if the vehicle is in the following vehicle cruise mode, calculating expected longitudinal acceleration in the following vehicle cruise mode based on model prediction control;

s4: determining the vehicle switching driving or braking state according to the expected longitudinal acceleration;

s5: if the vehicle is in a driving state, converting the expected longitudinal acceleration into a corresponding motor driving torque to complete the control of the vehicle; if the vehicle is in a braking state, converting the expected longitudinal acceleration into corresponding vehicle braking force; the control of the vehicle is completed.

According to the control method, parameter calibration is not needed to be carried out on gain coefficients of each vehicle controller, the expected longitudinal acceleration can be output in real time through an algorithm, timeliness is high, meanwhile, the driving or braking state of the vehicle is switched according to the expected longitudinal acceleration, the expected longitudinal acceleration is converted into the expected motor driving torque or the expected braking force, and accurate control of the vehicle is completed.

According to a specific implementation manner of the embodiment of the present invention, the step S1 specifically includes:

calculating the safe inter-vehicle distance:

d_safe＝τv_h+d₀

in the formula: d_safeFor safe inter-vehicle distance, τ is inter-vehicle time distance, v_hFor the speed of the vehicle, d₀The minimum distance between the two vehicles in a static state.

Calculating an emergency braking critical distance:

in the formula: d_emergencyCritical distance for emergency braking, t_sFor brake system response time, v_hIs the speed of the vehicle, v_relRelative speed of front and rear vehicles, a_maxMaximum acceleration in emergency braking conditions, d₀The minimum distance between the two vehicles in a static state.

According to a specific implementation manner of the embodiment of the present invention, the step S2 specifically includes:

when no vehicle exists in front, or the distance between the vehicle and the front vehicle is larger than the safe inter-vehicle distance, or the speed of the front vehicle is larger than the speed of the vehicle, the vehicle is judged to be in a constant-speed cruise mode; and when the distance between the vehicle and the front vehicle is smaller than the safe distance and larger than the emergency braking critical distance or the speed of the front vehicle is smaller than the speed of the vehicle, judging that the vehicle is in a following cruise mode.

According to a specific implementation manner of the embodiment of the present invention, the step S2 further includes: and when the distance between the vehicle and the front vehicle is smaller than the emergency braking critical distance, judging that the vehicle enters an emergency braking mode. When the vehicle enters the emergency braking mode, the maximum braking force is directly output.

According to a specific implementation manner of the embodiment of the present invention, in the step S3, when the host vehicle is in the constant-speed cruise mode, the expected longitudinal acceleration is calculated as follows:

e(t)＝v_set-v_h

wherein e (t) is a velocity error, v_setIs a target vehicle speed, v_hU (t) is the desired acceleration, K_pIs a proportionality coefficient, K_iIs the integral coefficient, K_dIs a differential coefficient. And in the constant-speed cruise mode, the PID control is added, so that the comfort of the vehicle can be ensured, and the speed of the vehicle can reach the set speed as soon as possible.

According to a specific implementation manner of the embodiment of the present invention, in step S3, when the host vehicle is in the following cruise mode, the expected longitudinal acceleration is calculated as follows:

1) establishing a stable car following mode state space model as follows:

wherein x (k) ═ Δ d (k), v_rel(k)，v_h(k)，a_h(k)，j(k)]，Δd(k)＝d-d_safeIs a vehicle-to-vehicle distance error, a_h(k) U (k) is a desired acceleration, w (k) is a preceding acceleration, y (k) [ Δ d (k) ], v_rel(k)，a_h(k)，j(k)]A, B, G, C, Z is a coefficient matrix of the system, respectively

Wherein, T_sFor the system sampling time, T_jIs a time constant, τ denotes the time interval between cars, d₀Representing a minimum inter-vehicle distance in a static state;

2) setting system constraints:

setting a constraint range for the distance between two vehicles, the deviation value of the actual distance between the vehicle and the front vehicle and the safe distance between the vehicle and the front vehicle, and the speed deviation value of the vehicle and the front vehicle; setting constraint ranges for the speed, the acceleration change rate and the control variable of the vehicle:

3) the comprehensive performance index function J is established as follows:

wherein Δ d (k) d-d_safeFor the vehicle spacing error,. DELTA.v (k) ═ v_rel＝v_f-v_hIs the relative velocity, a_h(k) For acceleration of the vehicle, Δ u (k) is the desired acceleration increment, ω_ΔdWeight coefficient, ω, for inter-vehicle distance error_ΔvIs a weight coefficient of relative velocity, ω_ahIs the weight coefficient, omega, of the acceleration of the vehicle_ΔuA weight coefficient for the desired acceleration increment, t being the integration time;

4) and acquiring the optimal expected car following acceleration corresponding to the optimization index at the moment k according to the stable car following mode state space model, the comprehensive performance index function and the system constraint.

According to a specific implementation manner of the embodiment of the present invention, the step S4 specifically includes:

pre-calibrating a driving brake switching curve corresponding to the vehicle speed, and adding buffer areas above and below the switching curve;

under the corresponding vehicle speed, if the acquired expected longitudinal acceleration is above the switching curve and the buffer area, the ACC system enters a driving state; if the acquired desired longitudinal acceleration is below the switching curve and the buffer zone, the ACC system enters a braking state.

According to a specific implementation manner of the embodiment of the present invention, in the step S5, when the vehicle is in a driving state, the motor driving torque is calculated as follows:

in the formula, T_motorFor motor drive torque, i₀Is the transmission ratio of the transmission system eta_tFor transmission efficiency, r is the rolling radius of the wheel,C_Dis an air resistance coefficient, A is a windward area, theta is a road slope angle, m is the mass of the whole vehicle, a is an expected longitudinal acceleration output by the system, V is a longitudinal vehicle speed, f is a rolling resistance coefficient,is the running resistance.

According to a specific implementation manner of the embodiment of the present invention, in the step S5, when the vehicle is in the braking state, the vehicle braking force is calculated as follows:

in the formula, F_bTo expect the vehicle braking force, C_DThe coefficient is an air resistance coefficient, A is a windward area, theta is a road slope angle, m is the mass of the whole vehicle, a is an expected longitudinal acceleration output by the system, V is a longitudinal vehicle speed, and f is a rolling resistance coefficient.

In a second aspect, an embodiment of the present invention provides a self-adaptive cruise longitudinal control device for a pure electric bus, including:

the calculation module is used for acquiring the speed of the vehicle and the speed of the front vehicle and calculating the safe inter-vehicle distance and the emergency braking critical distance;

the mode judging module is used for acquiring the distance between the vehicle and the front vehicle and judging that the vehicle is in a constant-speed cruise mode or a following cruise mode according to the safe inter-vehicle distance and the emergency braking critical distance;

an expected longitudinal acceleration calculation module, which is used for calculating the expected longitudinal acceleration in the constant-speed cruise mode based on PID control if the vehicle is in the constant-speed cruise mode; if the vehicle is in the following vehicle cruise mode, calculating expected longitudinal acceleration in the following vehicle cruise mode based on model prediction control;

the state switching module is used for determining the switching driving or braking state of the vehicle according to the expected longitudinal acceleration;

the conversion module is used for converting the expected longitudinal acceleration into corresponding motor driving torque to finish the control of the vehicle if the vehicle is in a driving state; and if the vehicle is in a braking state, converting the expected longitudinal acceleration into corresponding vehicle braking force to finish the control of the vehicle.

In a third aspect, an embodiment of the present invention further provides an electronic device, where the electronic device includes:

at least one processor; and the number of the first and second groups,

a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,

the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method for self-adaptive cruise longitudinal control of the electric-only passenger vehicle in any one of the foregoing first aspects or any one of the foregoing implementation manners of the first aspect.

The embodiment of the invention at least has the following technical effects:

firstly, the control method does not need to calibrate parameters of gain coefficients of each vehicle controller, can output expected longitudinal acceleration in real time through an algorithm, has strong timeliness, and enables the vehicle speed to reach the set vehicle speed as soon as possible on the premise of ensuring comfort.

And secondly, under the following cruise mode, establishing a stable following mode state space model, comprehensively considering the safety, the following performance, the comfort and the economy by a comprehensive performance index function, optimally adjusting the weight of each performance index, and realizing the expected longitudinal acceleration of the optimal performance of the vehicle.

Thirdly, comparing the output expected longitudinal acceleration with a driving brake switching curve, determining the braking and driving states, and converting the expected longitudinal acceleration into expected motor driving torque or expected braking force to finish the accurate control of the vehicle.

Drawings

In order to more clearly illustrate the detailed description of the invention or the technical solutions in the prior art, the drawings that are needed in the detailed description of the invention or the prior art will be briefly described below. Throughout the drawings, like elements or portions are generally identified by like reference numerals. In the drawings, elements or portions are not necessarily drawn to scale.

FIG. 1 shows a flow chart of a self-adaptive cruise longitudinal control method for a pure electric bus according to an embodiment of the invention;

FIG. 2 shows a schematic diagram of a driving brake switching curve in an embodiment of the invention;

FIG. 3 shows a structural block diagram of an adaptive cruise longitudinal control device of a pure electric bus according to an embodiment of the invention;

fig. 4 shows a schematic structural diagram of an electronic device for adaptive cruise longitudinal control of a pure electric bus according to an embodiment of the present invention.

Detailed Description

Embodiments of the present invention will be described in detail below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and therefore are only examples, and the protection scope of the present invention is not limited thereby.

It is to be noted that, unless otherwise specified, technical or scientific terms used herein shall have the ordinary meaning as understood by those skilled in the art to which the invention pertains.

Fig. 1 is a flowchart of steps of a method for controlling a pure electric bus in a self-adaptive cruise longitudinal direction, provided by an embodiment of the present invention, and referring to fig. 1, the method includes the following steps:

s1: and obtaining the speed of the vehicle and the speed of the front vehicle and calculating the safe inter-vehicle distance and the emergency braking critical distance.

1) And calculating the safe inter-vehicle distance by adopting a variable inter-vehicle distance algorithm with fixed time distance:

d_safe＝τv_h+d₀ (1)

in formula (1): d_safeFor safe inter-vehicle distance, τ is inter-vehicle time distance, v_hFor the speed of the vehicle, d₀The minimum distance between the two vehicles in a static state.

2) Calculating an emergency braking critical distance:

in formula (2): d_emergencyCritical distance for emergency braking, t_sFor brake system response time, v_hIs the speed of the vehicle, v_relRelative speed of front and rear vehicles, a_maxMaximum acceleration in emergency braking conditions, d₀The minimum distance between the two vehicles in a static state.

S2: and acquiring the distance between the vehicle and the front vehicle and judging that the vehicle is in a constant-speed cruise mode or a following cruise mode according to the safe inter-vehicle distance and the emergency braking critical distance.

When no vehicle exists in front, or the distance between the vehicle and the front vehicle is larger than the safe inter-vehicle distance, or the speed of the front vehicle is larger than the speed of the vehicle, the vehicle is judged to be in a constant-speed cruise mode; when the distance between the vehicle and the front vehicle is smaller than the safe distance and larger than the critical distance of emergency braking, or the speed of the front vehicle is smaller than the speed of the vehicle, judging that the vehicle is in a following cruise mode; when the distance between the vehicle and the front vehicle is smaller than the emergency braking critical distance, the vehicle is judged to enter an emergency braking mode, and the maximum braking force is directly output without subsequent steps when the vehicle enters the emergency braking mode.

S3: if the vehicle is in the constant-speed cruise mode, calculating expected longitudinal acceleration in the constant-speed cruise mode based on PID control; and if the vehicle is in the following vehicle cruise mode, calculating the expected longitudinal acceleration in the following vehicle cruise mode based on model prediction control.

When the vehicle is in the constant-speed cruise mode, the expected longitudinal acceleration is calculated in the following mode:

calculating expected longitudinal acceleration under a constant-speed cruise mode based on PID control, and setting an upper limit and a lower limit of the acceleration at the same time, so that the vehicle speed reaches a set vehicle speed as soon as possible on the premise of ensuring comfort;

e(t)＝v_set-v_h

in the formula (3), e (t) is a velocity error, v_setIs a target vehicle speed, v_hU (t) is the desired acceleration, K_pIs a proportionality coefficient, K_iIs the integral coefficient, K_dIs a differential coefficient.

When the vehicle is in the following cruise mode, the expected longitudinal acceleration is calculated in the following mode:

1) establishing a stable car following mode state space model:

according to the relative motion states of the two vehicles, a state relation model of the vehicle and a front target vehicle is established:

d＝x_f-x_h

Δd＝d-d_safe

v_rel＝v_f-v_h (4)

in the formula (4), d represents the distance between the preceding vehicle and the host vehicle, and x_hIndicating the position of the host car, x_fIndicating the position of the leading vehicle,. DELTA.d indicating the inter-vehicle distance error, d_safeIndicating a safe separation between two vehicles, v_relIndicating the relative speed of the two vehicles, v_fIndicating the speed, v, of the preceding vehicle_hIndicates the vehicle speed of the host vehicle.

Because the vehicle transmission system has time lag, the acceleration response characteristic of the vehicle can be described by a first-order inertia link:

in the formula (5), a_hIs the actual acceleration of the vehicle, a_desTo desired acceleration, K_lFor system gain, T_jIs the time constant, S is the Laplace operator.

According to the longitudinal acceleration response model and the longitudinal kinematics relationship between the main vehicle and the front vehicle, a longitudinal vehicle following model of the vehicle can be established:

v_rel(k+1)＝v_rel(k)+a_f(k)T_s-a_h(k)T_s

v_h(k+1)＝v_h(k)+a_h(k)T_s

in the formula (6), v_h(k) Represents the longitudinal speed of the vehicle at time k, a_f(k)、a_h(k) Acceleration at the moment k of the front and rear vehicles, v_rel(k) Showing the relative speed of two vehicles at the time k, u (k) showing the expected acceleration signal sent by the system, j (k) showing the change rate of the acceleration of the vehicle at the time k, and T_sThe system sample time.

Defining a state vector as x_h＝[Δd(k)，v_rel(k)，v_h(k)，a_h(k) J (k) an observed value a of the acceleration of the preceding vehicle_fAnd establishing an adaptive cruise longitudinal dynamics discrete state space equation as the disturbance quantity of the equation.

x(k+1)＝Ax(k)+Bu(k)+Gw(k) (7)

In equation (7), A, B, G is the coefficient matrix of the system:

selecting the error delta d between the vehicles,relative velocity v between the leading vehicle and the own vehicle_relAcceleration a of the vehicle_hAnd the acceleration change rate j of the vehicle is used as an optimization performance index, and the output equation of the self-adaptive cruise control system is as follows:

y(k)＝Cx(k)-Z

in the formula (9), τ represents the time interval between cars, d₀Indicating the minimum vehicle separation distance at rest.

The final formed steady car following mode state space model is as follows:

2) setting system constraints:

for the safety index, the actual distance between two vehicles is always ensured to be larger than a safe following distance, so that the rear-end collision is avoided, and corresponding hard constraint needs to be applied to the real distance between two vehicles:

d＝x_f-x_h≥d_c (11)

in the formula (11), d_cIndicating a minimum safe vehicle distance.

Setting hard constraints on the deviation value of the actual distance between the vehicle and the front vehicle, the safety distance between the vehicle and the front vehicle and the speed deviation value of the vehicle and the front vehicle:

Δd_min≤Δd≤Δd_max

Δv_min≤Δv≤Δv_max (12)

in formula (12), Δ d_min，Δd_maxThe minimum value and the maximum value of the deviation between the actual distance between the vehicle and the front vehicle and the safe distance between the vehicles are obtained; Δ v_min，Δv_maxThe speed deviation between the vehicle and the front vehicle is minimizedA value and a maximum value.

In addition, in consideration of the capability limitation and the comfort requirement of the vehicle itself, the speed, acceleration rate of change, and control variable of the host vehicle are constrained as follows:

v_min≤v(k)≤v_max

a_min≤a(k)≤a_max

j_min≤j(k)≤j_max

u_min≤u(k)≤u_max (13)

in the formula (13), v_min、v_max、a_min、a_max、j_min、j_max、u_min、u_maxThe vehicle minimum speed, the vehicle maximum speed, the vehicle minimum acceleration, the vehicle maximum acceleration, the vehicle minimum acceleration change rate, the vehicle maximum acceleration change rate, the vehicle expected following acceleration minimum value and the vehicle expected following acceleration maximum value are respectively.

3) Establishing an objective function:

for the following performance index, the sum of the two norms of the matrix of the vehicle spacing error and the relative speed is taken as the following performance index, which can be expressed as:

J_T＝ω_ΔdΔd(k)²+ψ_ΔvΔv(k)² (14)

in formula (14), J_TTo follow the performance index, omega_ΔdWeight coefficient, ω, for inter-vehicle distance error_ΔvIs a weighting factor for the relative velocity.

For comfort and economy indices, this can be expressed as:

J_C＝ω_aha_h(k)²+ω_ΔuΔu(k)² (15)

in formula (15), J_CFor comfort and economic performance index, omega_ah，ω_ΔuThe weighting coefficients of the vehicle acceleration and the expected acceleration increment are respectively.

Weighting and summing the tracking performance, the safety performance and the comfort performance indexes to obtain a comprehensive performance index function J:

in the formula (16), t is an integration time.

4) According to the stable following mode state space model formula (10), the comprehensive performance index function formula (16) and system constraints, the multi-objective optimization of the ACC system can be realized by adjusting the weight of each performance index based on the linear quadratic optimal control theory. And at the moment k, seeking the optimal expected longitudinal acceleration corresponding to the optimization index. At the next moment, because the MPC controller has the roll optimization feature, the above process can be repeated, resulting in the optimal desired longitudinal acceleration for each moment.

S4: and determining the driving or braking state of the vehicle switching according to the expected longitudinal acceleration.

1) Pre-calibrating a driving brake switching curve:

calibrating sliding acceleration corresponding to different speeds according to sliding of the vehicle at different speeds under a non-driving and non-braking state under standard load and road conditions, and taking the curve as a switching curve, in order to avoid frequent switching of driving and braking, adding buffer areas with the width delta h above and below the switching curve, wherein the switching curve is shown in FIG. 2;

2) determining a driving braking state:

if the expected acceleration is above the switching curve and the buffer area, the ACC system enters a driving state;

if the expected acceleration is below the switching curve and the buffer area, the ACC system enters a braking state;

if the desired acceleration is within the buffer zone, the ACC system remains in the original state.

S5: if the vehicle is in a driving state, converting the expected longitudinal acceleration into a corresponding motor driving torque to complete the control of the vehicle; if the vehicle is in a braking state, converting the expected longitudinal acceleration into corresponding vehicle braking force; the control of the vehicle is completed.

When the vehicle is in a driving state, the driving torque of the motor is calculated in the following way:

according to the vehicle inverse longitudinal dynamics model, the following relation between the expected acceleration and the driving torque of the motor can be obtained:

in formula (17), T_motorFor motor drive torque, i₀Is the transmission ratio of the transmission system eta_tFor transmission efficiency, r is the wheel rolling radius, C_DIs an air resistance coefficient, A is a windward area, theta is a road slope angle, m is the mass of the whole vehicle, a is an expected longitudinal acceleration output by the system, V is a longitudinal vehicle speed, f is a rolling resistance coefficient,is the running resistance.

When the vehicle is in a braking state, the vehicle braking force is calculated in the following way:

according to the vehicle inverse longitudinal dynamic model, the following relation between the expected acceleration and the vehicle braking force can be obtained:

in the formula (18), F_bIs the desired vehicle braking force. C_DThe coefficient is an air resistance coefficient, A is a windward area, theta is a road slope angle, m is the mass of the whole vehicle, a is an expected longitudinal acceleration output by the system, V is a longitudinal vehicle speed, and f is a rolling resistance coefficient.

After the expected braking force is obtained, the braking controller can convert the expected braking force into braking pressure and motor braking torque according to a braking force distribution strategy, and therefore the deceleration control of the braking working condition is achieved.

It should be noted that, the modules are arranged according to a streaming layout, which is only one embodiment of the present invention, and may also be arranged in other manners, and the present invention is not limited to this.

The beneficial effects of the above embodiment are as follows:

firstly, the control method does not need to calibrate parameters of gain coefficients of each vehicle controller, can output expected longitudinal acceleration in real time through an algorithm, has strong timeliness, and enables the vehicle speed to reach the set vehicle speed as soon as possible on the premise of ensuring comfort.

And secondly, under the following cruise mode, establishing a stable following mode state space model, comprehensively considering the safety, the following performance, the comfort and the economy by a comprehensive performance index function, optimally adjusting the weight of each performance index, and realizing the expected longitudinal acceleration of the optimal performance of the vehicle.

Thirdly, comparing the output expected longitudinal acceleration with a driving brake switching curve, determining the braking and driving states, and converting the expected longitudinal acceleration into expected motor driving torque or expected braking force to finish the accurate control of the vehicle.

Fig. 3 is a structural block diagram of a self-adaptive cruise longitudinal control device of a pure electric bus according to an embodiment of the present invention, where the device includes:

the calculation module is used for acquiring the speed of the vehicle and the speed of the front vehicle and calculating the safe inter-vehicle distance and the emergency braking critical distance;

the mode judging module is used for acquiring the distance between the vehicle and the front vehicle and judging that the vehicle is in a constant-speed cruise mode or a following cruise mode according to the safe inter-vehicle distance and the emergency braking critical distance;

an expected longitudinal acceleration calculation module, which is used for calculating the expected longitudinal acceleration in the constant-speed cruise mode based on PID control if the vehicle is in the constant-speed cruise mode; if the vehicle is in the following vehicle cruise mode, calculating expected longitudinal acceleration in the following vehicle cruise mode based on model prediction control;

the state switching module is used for determining the switching driving or braking state of the vehicle according to the expected longitudinal acceleration;

the conversion module is used for converting the expected longitudinal acceleration into corresponding motor driving torque to finish the control of the vehicle if the vehicle is in a driving state; and if the vehicle is in a braking state, converting the expected longitudinal acceleration into corresponding vehicle braking force to finish the control of the vehicle.

The functions of the modules in the embodiment of fig. 3 correspond to the contents in the corresponding method embodiment, and are not described again here.

Fig. 4 shows a schematic structural diagram of an electronic device 40 provided in an embodiment of the present invention, where the electronic device 40 includes at least one processor 401 (e.g., a CPU), at least one input/output interface 404, a memory 402, and at least one communication bus 403, which are used to implement connection communication between these components. The at least one processor 401 is configured to execute computer instructions stored in the memory 402 to enable the at least one processor 401 to execute the embodiments of the aforementioned electric-only passenger vehicle adaptive cruise longitudinal control method. The Memory 402 is a non-transitory Memory (non-transitory Memory), which may include a volatile Memory such as a high-speed Random Access Memory (RAM) or a non-volatile Memory such as at least one disk Memory. A communication connection with at least one other device or unit is made through at least one input-output interface 404, which may be a wired or wireless communication interface.

In some embodiments, memory 402 stores program 4021 and processor 401 executes program 4021 for performing the contents of any of the foregoing sub-table method examples.

The electronic device may exist in a variety of forms, including but not limited to:

(1) a mobile communication device: such devices are characterized by mobile communications capabilities and are primarily targeted at providing voice, data communications. Such terminals include: smart phones (e.g., iphones), multimedia phones, functional phones, and low-end phones, among others.

(2) Ultra mobile personal computer device: the equipment belongs to the category of personal computers, has calculation and processing functions and generally has the characteristic of mobile internet access. Such terminals include: PDA, MID, and UMPC devices, etc., such as ipads.

(3) A portable entertainment device: such devices can display and play multimedia content. This type of device comprises: audio, video players (e.g., ipods), handheld game consoles, electronic books, and smart toys and portable car navigation devices.

(4) The specific server: the device for providing the computing service comprises a processor, a hard disk, a memory, a system bus and the like, and the server is similar to a general computer architecture, but has higher requirements on processing capacity, stability, reliability, safety, expandability, manageability and the like because of the need of providing high-reliability service.

(5) And other electronic equipment with data interaction function.

All the embodiments in the present specification are described in a related manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments.

In particular, as for the apparatus embodiment, since it is substantially similar to the method embodiment, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiment.

The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.