Vehicle regional self-organizing energy-saving control system and method for networked electric vehicles under high-speed working conditions

Abstract

The application discloses a kind of network connection electric vehicle vehicle area self-organizing energy-saving control system and method under high-speed working condition, vehicle i current driving mode is single vehicle driving mode, when the total number of vehicles in road area is greater than or equal to the set value and vehicle type is same, next driving mode is platoon driving mode, otherwise is single vehicle driving mode, in single vehicle driving mode, the driving efficiency of vehicle i current driving mode is compared with the driving efficiency of next driving mode, the maximum driving efficiency and corresponding driving mode are determined, and as next driving mode;Vehicle i current driving mode is platoon driving mode, when the total number of vehicles in road area is greater than or equal to the set value, vehicle i keeps existing platoon driving mode, otherwise becomes single vehicle driving mode, in single vehicle driving mode, next driving mode is determined.The application realizes the integration of single vehicle energy-saving driving mode and multi-vehicle platoon driving mode under high-speed working condition, and improves the economy of vehicle driving.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of automobile auxiliary driving technology, and particularly relates to a vehicle regional self-organizing energy-saving control system and method for high-speed working conditions of a networked electric vehicle using V2I to realize information sharing. BACKGROUND

[0002] At present, the automobile industry in China is facing energy crisis, air pollution and other problems, and industrial transformation is imminent. In terms of traffic management, traffic congestion has a great impact on road traffic capacity, such as low traffic efficiency and serious energy waste. Therefore, the research on vehicle energy saving and driving control is vigorously promoted.

[0003] Existing research shows that there are two angles to achieve energy-saving driving of networked electric vehicles: single-vehicle energy-saving driving control and multi-vehicle formation energy-saving driving control. Single-vehicle energy-saving driving control adjusts the vehicle driving state (cruise, following and lane changing) to achieve vehicle control at the optimal energy-saving speed, and multi-vehicle formation energy-saving driving controls the vehicle formation to reduce the wind resistance of the vehicle, thereby achieving the purpose of energy saving. Research around these single aspects is common, but how to realize the switching of vehicle energy-saving driving from single-vehicle energy-saving driving to multi-vehicle formation energy-saving driving in a specific scenario has not been studied, but this research is the key point of integrating and centralized control of vehicle energy-saving driving state. SUMMARY

[0004] In view of the deficiencies in the prior art, the present application provides a networked electric vehicle regional self-organizing energy-saving control system and method under high-speed working conditions, which realizes the integration of single-vehicle energy-saving driving mode and multi-vehicle formation driving mode of vehicles under high-speed working conditions, and further improves the energy-saving effect of vehicle driving.

[0005] The present application achieves the above technical purpose by the following technical means.

[0006] The networked electric vehicle regional self-organizing energy-saving control method under high-speed working conditions comprises the following steps:

[0007] At the start time of the current time period T, when the vehicle i is in the road area and satisfies N≥N0 and L1=L2=L3=…=L, the current driving mode of the vehicle i is the formation driving mode, otherwise it is the single-vehicle driving mode, wherein N is the total number of vehicles in the road area at the start time of the current time period T, N0 is a set value, L i is a vehicle type parameter, i=1, 2, 3……N;

[0008] When the current driving mode of the vehicle i is the single-vehicle driving mode, the next driving mode is determined with the time period T as the update interval.

[0009] At the start time of the next time period T, when N'≥N0and L1=L2=L3=…=L N′ , the next driving mode is the platoon driving mode, otherwise the next driving mode is the single vehicle driving mode, in the single vehicle driving mode, the driving efficiency of the current driving mode of the vehicle i is compared with the driving efficiency of the next driving mode, the maximum driving efficiency is determined, and the driving mode corresponding to the maximum driving efficiency is taken as the next driving mode; wherein N' is the total number of vehicles in the road area at the start time of the next time period T;

[0010] When the current driving mode of the vehicle i is the platoon driving mode, the next driving mode is determined with time T as the update interval:

[0011] At the start time of the next time period T, when N'≥N0, the vehicle i keeps the existing platoon driving mode; when N'<N0, the vehicle i becomes the single vehicle driving mode, the driving efficiency of the current driving mode is compared with the driving efficiency of the next driving mode, the maximum driving efficiency is determined, and the next driving mode is determined.

[0012] Further, the driving efficiency of the current driving mode is compared with the driving efficiency of the next driving mode to determine the maximum driving efficiency, specifically:

[0013] η mode_i(t+1) =max(η i(t) ,η cruising_i(t+1) ,η following_i(t+1) ,η changing_1_i(t+1) ,η changing_2_i(t+1) )

[0014] Wherein: η i(t) is the driving efficiency of the vehicle i, η cruising_i(t+1) is the cruise efficiency of the next driving mode of the vehicle i, η following_i(t+1) is the following efficiency of the next driving mode of the vehicle i, η changing_1_i(t+1) is the first lane changing efficiency of the next driving mode of the vehicle i, η changing_2_i(t+1) is the second lane changing efficiency of the next driving mode of the vehicle i, mode is the optimal driving mode of the next driving mode of the vehicle i, and η mode_i(t+1) is the driving efficiency corresponding to the optimal driving mode of the next driving mode of the vehicle i.

[0015] Further, when η mode_i(t+1) = η i(t) , the vehicle i keeps the existing driving mode; when η mode_i(t+1) = η cruising_i(t+1) , the vehicle i performs cruise driving; when η mode_i(t+1) = η following_i(t+1) , the vehicle i performs following driving; and when η mode_i(t+1) = η changing_1_i(t+1)When η mode_i(t+1) = η changing_2_i(t+1) , vehicle i performs the second lane-changing driving.

[0016] Further, the first lane-changing driving is that there is a vehicle in the target lane, and the second lane-changing driving is that there is no vehicle in the target lane.

[0017] Further, when vehicle i is in the single-vehicle driving mode and the next driving mode is the single-vehicle driving mode or the platoon driving mode, the vehicle speed compensation value Δv v_i_(t) of vehicle i at the next moment is calculated by the current vehicle speed error e s_i_(t) and the current position error e i_(t+1) :

[0018]

[0019]

[0020] e v_i_(t) = v i_c_(t) - v i_r_(t)

[0021] wherein v i_r_(t) is the current driving vehicle speed, and v i_c_(t) is the reference driving vehicle speed.

[0022] Further, when vehicle i is in the platoon driving mode and the next driving mode is the platoon driving mode, the vehicle speed compensation value Δv′ v_i_(t) and the distance compensation value Δd′ i_(t+1) of vehicle i at the next moment are calculated by the current vehicle speed error e′ s_i_(t) and the current position error e′ i_(t+1) :

[0023]

[0024]

[0025] e′ v_i_(t) = v i_r_(t) - v f_(t)

[0026] e′ s_i_(t) = d f_i(t) - d formating_i(t)

[0027] wherein v′ f_(t) is the platoon driving vehicle speed, d′ formating_i(t) is the current vehicle distance constraint, and d′ f_i(t) is the distance between vehicle i+1 and the front vehicle.

[0028] Further, the vehicle distance constraint is satisfied:

[0029] d formating_i(t+1) = v formating_1(t+1) τ + D

[0030] where d formating_i(t+1) is the distance between vehicle i and vehicle i+1, v formating_1(t+1) is the driving speed of the head vehicle of the platoon, τ is a time factor, and D is a static distance.

[0031] Further, the driving efficiency of vehicle i and the driving efficiency of the next driving mode are calculated using a vehicle efficiency calculation model η = F(η m , η d ) = ω1*η m + ω2*η d , where the weight parameters ω1 + ω2 = 1, and η m is the motor efficiency, η d is the transmission efficiency, and η m = F(n m , T m ), η d = F(v), n m is the motor speed, T m is the motor torque, and v is the vehicle speed.

[0032] Further, the single-vehicle dynamics model satisfied by η d and n m is:

[0033]

[0034] F f = mgf cos α

[0035]

[0036] F i = mg sin α

[0037] where F f is the rolling resistance, F air is the air resistance, F i is the slope resistance, m is the vehicle mass, i is the product of the reduction device and the main reducer transmission ratio, r is the wheel radius, g is the gravitational acceleration, f is the rolling resistance coefficient, α is the road slope, C W is the wind resistance coefficient, ρ is the air density, and A is the windward area.

[0038] A vehicle regional self-organizing energy-saving control system for a networked electric vehicle in a high-speed working condition, comprising:

[0039] The central processor receives vehicle state parameters of the vehicle on the road segment, determines a current driving mode of the vehicle i, determines a next driving mode with time T as an update interval, and transmits to the vehicle i;

[0040] The vehicle state parameters include: a type parameter L of the vehicle i i , L i =1 is a small vehicle, L i =2 is a medium vehicle, and L i =3 is a large vehicle; a position coordinate (x i , y i ) of the vehicle i; a longitudinal driving speed v i of the vehicle i; and a driving efficiency η i of the vehicle i.

[0041] The present application has the following beneficial effects:

[0042] (1) The present application determines a more efficient driving mode of the vehicle by calculating the driving efficiency of the next driving mode of the network-connected electric vehicle in the local road segment and comparing the driving efficiency with that of the current driving mode, thereby improving the economy of the vehicle driving;

[0043] (2) The present application realizes orderly driving of the vehicle by switching control of the driving mode of the network-connected electric vehicle in the local road segment, including: the current driving mode is single-vehicle driving mode, the next driving mode is single-vehicle driving mode or platoon driving mode, and the current driving mode is platoon driving mode, the next driving mode is platoon driving mode, thereby improving the overall driving safety, economy and traffic efficiency in the microscopic traffic environment. BRIEF DESCRIPTION OF DRAWINGS

[0044] Figure 1 It is a flowchart of the vehicle regional self-organizing energy-saving control of the network-connected electric vehicle under high-speed working conditions;

[0045] Figure 2 It is a characteristic data diagram of a certain brushless DC motor;

[0046] Figure 3 It is a diagram of the relationship between the speed and the driving resistance of a certain small car;

[0047] Figure 4 It is a real-time sharing diagram of the vehicle state parameters and control quantity parameters;

[0048] Figure 5 It is a flowchart of the vehicle regional self-organizing energy-saving control. DETAILED DESCRIPTION

[0049] The present application will be further described below in combination with the drawings and specific embodiments, but the protection scope of the present application is not limited thereto.

[0050] AsFigure 1 As shown, the present invention provides a self-organizing energy-saving control method for connected electric vehicles under high-speed operating conditions, specifically including the following:

[0051] I. Establish a single-vehicle dynamics model based on vehicle motor efficiency evaluation to calculate the vehicle's current driving efficiency and the predicted driving efficiency in the next driving mode.

[0052] The single-vehicle dynamics model based on vehicle motor efficiency evaluation is established based on motor experiments and driving resistance experiments. The specific modeling process is as follows:

[0053] 1) The motor efficiency evaluation function was experimentally fitted to obtain the functional relationship between motor speed, torque and motor efficiency, as shown in the following expression:

[0054] η m =F(n) m T m )

[0055] Where, n m T is the motor speed. m η is the motor torque. m For motor efficiency;

[0056] This embodiment uses a certain type of brushless DC motor as an example for analysis. The characteristic data of the brushless DC motor are as follows: Figure 2 As shown, the fitted relationship between motor speed, torque, and motor efficiency is as follows:

[0057]

[0058] Among them, a 11 a 12 a 13 a 14 a 15 a 16 a 21 a 22 a 23 a 24 a 25 and a 26 The fitting coefficients for motor efficiency are denoted as .

[0059] 2) The transmission efficiency evaluation function was fitted experimentally to obtain the functional relationship between vehicle speed and transmission efficiency, as shown in the following expression:

[0060] η d =F(v)

[0061] Where v is the vehicle speed, η d For transmission efficiency;

[0062] The embodiment takes a small car as an example for analysis, and the relationship between the vehicle speed and the travel resistance of the car is shown in Figure 3 The relationship between the vehicle speed and the transmission efficiency obtained by fitting is as follows:

[0063] η d = b1 + b2v + b3v 2

[0064] wherein b1, b2 and b3 are fitting coefficients of the transmission efficiency.

[0065] 3) A single vehicle dynamics model is established, and the expression is as follows:

[0066]

[0067] F f = mgf cos a

[0068]

[0069] F i = mgsin a

[0070] wherein F f is the rolling resistance, F air is the air resistance, F i is the slope resistance, m is the vehicle mass, i is the transmission ratio product of the deceleration device and the main reducer, r is the wheel radius, g is the gravitational acceleration, f is the rolling resistance coefficient, a is the road slope, C W is the wind resistance coefficient, p is the air density, and A is the windward area.

[0071] 4) The embodiment uses the vehicle efficiency calculation model η = F(η m , η d ) = ω1*η m + ω2*η d to calculate the current travel efficiency of the vehicle, and the weight parameters ω1 + ω2 = 1, wherein the current transmission efficiency of the vehicle is calculated by the vehicle speed (according to the relationship in 2), and then the current transmission efficiency of the vehicle is substituted into the single vehicle dynamics model to calculate the motor torque of the current vehicle, and then the motor torque and the motor speed (obtained from the vehicle speed) of the current vehicle are used to obtain the motor efficiency (according to the relationship in 1); in the art, the travel efficiency of the vehicle is selected according to the specific vehicle or actual demand.

[0072] The method for calculating the predicted travel efficiency in the next travel mode is the same as the method for calculating the current travel efficiency of the vehicle; and it is specifically divided into two cases:

[0073] When the vehicle travels alone, the next travel mode may appear in the cruise, following and lane changing states:

[0074] When the vehicle is in cruise control, the transmission efficiency is calculated using the maximum permitted speed in the current lane as the vehicle speed, and then the vehicle's driving efficiency is calculated. At this time, η′=η cruising ;

[0075] When the vehicle is in a car-following state, the vehicle's driving efficiency is calculated using the target vehicle's speed as the vehicle's speed. In this case, η′=η following ;

[0076] When a vehicle is changing lanes, there are two possibilities: ① There is a vehicle in the target lane, and the driving efficiency is calculated using the speed of the vehicle in the target lane as the vehicle speed. In this case, η′=η changing_1 ② When there are no vehicles in the target lane, the maximum permitted speed in the target lane is used as the vehicle speed to calculate the vehicle driving efficiency. In this case, η′=η changing_2 .

[0077] When multiple vehicles are traveling in a convoy, the current driving efficiency η′=η is calculated using the current speed of the vehicles in the convoy as the vehicle speed. formating .

[0078] Where: η cruising For cruise efficiency, η following To achieve car-keeping efficiency, η changing_1 For the first type of lane-changing efficiency, η changing_2 For the second type of lane-changing efficiency, η formating For formation efficiency.

[0079] In the above process, the acquisition of the maximum speed allowed in the current lane, the speed of the target vehicle, the speed of the vehicle in the target lane, the maximum speed allowed in the target lane, and the speed of the current queue are all existing technologies and will not be described in detail here.

[0080] 2. Transfer vehicle status parameters for participating vehicles to achieve vehicle status sharing among all vehicles within a local road segment.

[0081] The transfer of vehicle state parameters participating in the evaluation is based on V2I technology to achieve real-time sharing of vehicle state parameters. The sharing method is as follows: Figure 4 As shown, the central processing unit a of road segment j and the central processing unit b of road segment j+1 communicate through V2I technology. When a vehicle switches from road segment j to road segment j+1, central processing unit a transmits the status parameters and self-organizing control strategy of all vehicles on road segment j to central processing unit b. On road segment j, through V2I technology, all vehicles transmit their vehicle status parameters to central processing unit a, and central processing unit a transmits the self-organizing control strategy to each vehicle.

[0082] The vehicle state parameters include: the type parameter L of vehicle i. i L i =1 represents a small vehicle, L i= 2 is a medium-sized vehicle, L i = 3 is a large vehicle; position coordinates (x i , y i ) of vehicle i; longitudinal driving speed v i of vehicle i (including current driving speed v i_r_(t) and reference driving speed v i_c_(t) ); driving efficiency η i of vehicle i.

[0083] III. As shown in Figure 5 , the self-organizing control strategy of the connected electric vehicle is:

[0084] 1) Select the road area and vehicle participating in organization

[0085] The vehicle at the front of the target area (self-defined area) is numbered i = 1, and the maximum distance from the vehicle numbered 1 is selected as S max , and the area within the range of S max is the road area participating in organization. The distance S i from the vehicle numbered 1 is calculated, and the vehicle satisfying S i ≤ S max is the vehicle participating in organization, and is numbered 2 ~ N from small to large distance; the distance S i is calculated as follows:

[0086]

[0087] Wherein: (x1, y1) is the position of the vehicle numbered 1 in the global coordinate system.

[0088] 2) At the beginning of the current time period T, when the vehicle i is in the road area satisfying N ≥ N0 (a set value) and L1 = L2 = L3 = … = L N , the current driving mode is platoon driving mode, otherwise it is single vehicle driving mode:

[0089] ① When the current driving mode of vehicle i is single vehicle driving mode, the mode is updated with time T as the update interval to determine the next driving mode:

[0090] At the beginning of the next time period T, when N ≥ N0 and L1 = L2 = L3 = … = L N , vehicle i prefers to drive in platoon driving mode, and the platoon driving speed is v formating_1(t+1) , the head vehicle driving speed, and the distance constraint within the queue is:

[0091] d formating_i(t+1) = v formating_1(t+1) τ+ D

[0092] Where, d formating_i(t+1)is the current distance between vehicles with numbers i and i+1, τ is a time factor, and D is a static distance;

[0093] Otherwise (i.e., N≥N0, L1=L2=L3=…=L N ), vehicle i continues the single-vehicle driving mode and compares the driving efficiency of the current driving mode of the vehicle with the driving efficiency of the next driving mode (single-vehicle driving mode) to determine the maximum driving efficiency, and the driving mode corresponding to the maximum driving efficiency is taken as the next driving mode of the vehicle. The comparison method is as follows:

[0094] η mode_i(t+1) = max(η i(t) , η cruising_i(t+1) , η following_i(t+1) , η changing_1_i(t+1) , η changing_2_i(t+1) )

[0095] η i(t) is the driving efficiency of vehicle i, η cruising_i(t+1) is the cruising efficiency of the next driving mode of vehicle i, η following_i(t+1) is the following efficiency of the next driving mode of vehicle i, η changing_1_i(t+1) is the first lane-changing efficiency of the next driving mode of vehicle i, η changing_2_i(t+1) is the second lane-changing efficiency of the next driving mode of vehicle i, mode is the optimal driving mode in the next driving mode of vehicle i, and η mode_i(t+1) is the driving efficiency corresponding to the optimal driving mode in the next driving mode of vehicle i.

[0096] When η mode_i(t+1) = η i(t) , vehicle i keeps the existing driving mode; when η mode_i(t+1) = η cruising_i(t+1) , vehicle i performs cruising driving; when η mode_i(t+1) = η following_i(t+1) , vehicle i performs following driving; when η mode_i(t+1) = η changing_1_i(t+1) , vehicle i performs first lane-changing driving; and when η mode_i(t+1) = η changing_2_i(t+1) , vehicle i performs second lane-changing driving.

[0097] 2) When the current driving mode of vehicle i is the platoon driving mode, the mode is updated in the update interval T to determine the next driving mode: at the start time of the next time period T, when the number of participating organization vehicles N≥N0, vehicle i keeps the existing platoon driving mode; and when the number of participating organization vehicles N

[0098] Four, the self-organizing coordination control process of the connected electric vehicle, the control error of the participating vehicles in the current road segment is calculated, the error coordination control in the region is realized, and the stable driving of the vehicles in the region is ensured

[0099] The error coordination control in the region is realized by sharing the speed error and position error of a single vehicle, and the specific content is as follows:

[0100] When the vehicle i is in the single vehicle driving mode, and the next driving mode is the single vehicle driving mode or the platoon driving mode: the current driving speed v i_r_(t) is compared with the reference driving speed v i_c_(t) , the current speed error e v_i_(t) is determined; the integral of the current reference speed in the interval T and the integral of the current driving speed in the interval T are determined to determine the current position error e s_i_(t) ; the speed compensation value Δv i_(t+1) of the vehicle i at the next moment is calculated by the current speed error and the current position error, and the specific compensation method is as follows:

[0101] e v_i_(t) =v i_c_(t) -v i_r_(t)

[0102]

[0103]

[0104] When the vehicle i is in the platoon driving mode, and the next driving mode is the platoon driving mode: the current driving speed v i_r_(t) is compared with the reference platoon driving speed v f_(t) , the current speed error e′ v_i_(t) is determined; the distance d f_i_(t) between the current vehicle with the vehicle i+1 and the front vehicle, and the distance constraint d formating_i(t) of the current vehicle are determined to determine the current position error e′ s_i_(t) ; the speed compensation value Δv′ i_(t+1) and the distance compensation value Δd i_(t+1) of the vehicle i at the next moment are calculated by the current speed error and the current position error, and the specific compensation method is as follows:

[0105] e′ v_i_(t) =v i_r_(t) -v f_(t)

[0106] e′ s_i_(t) =d f_i(t) -d formating_i(t)

[0107]

[0108]

[0109] The above embodiments are preferred embodiments of the present application, but the present application is not limited to the above embodiments, and any obvious improvements, replacements or modifications made by those skilled in the art without departing from the spirit of the present application shall fall within the scope of protection of the present application.

Claims

1. A vehicle regional self-organizing energy-saving control method for a connected electric vehicle in a high-speed working condition, characterized in that: when the current driving mode of the vehicle i is a single-vehicle driving mode, the next driving mode is determined with a time period T as an update interval; when the current driving mode of the vehicle i is a platoon driving mode, the next driving mode is determined with a time T as an update interval; at the start time of the next time period T, when N' is greater than or equal to N0, the vehicle i maintains the existing platoon driving mode; when N' is less than N0, the vehicle i becomes a single-vehicle driving mode, the driving efficiency of the current driving mode is compared with the driving efficiency of the next driving mode, the maximum driving efficiency is determined, and then the next driving mode is determined. At the start of the current time period T, when vehicle i is located in a road region that satisfies N≥N0 and L1=L2=L3=…=L N When vehicle i is in platoon mode, it is otherwise in single-vehicle mode. Here, N is the total number of vehicles in the road area at the start of the current time period T, N0 is a set value, and L... i For vehicle type parameters, i = 1, 2, 3...N; The driving efficiency of the current driving mode is compared with the driving efficiency of the next driving mode, the maximum driving efficiency is determined, and the specific process is as follows: the first lane-changing driving is that there is a vehicle in the target lane, and the second lane-changing driving is that there is no vehicle in the target lane. At the start time of the next time period T, when N'≥N0and L1=L2=L3=...=L N′ , the next driving mode is the platoon driving mode, otherwise the next driving mode is the single vehicle driving mode. In the single vehicle driving mode, the driving efficiency of the current driving mode of the vehicle i is compared with the driving efficiency of the next driving mode, and the maximum driving efficiency is determined. The driving mode corresponding to the maximum driving efficiency is the next driving mode; wherein N' is the total number of vehicles in the road area at the start time of the next time period T. The vehicle distance constraint is satisfied, and the specific process is as follows: the vehicle distance constraint is satisfied, and the specific process is as follows: the vehicle distance constraint is satisfied, and the specific process is as follows: the vehicle distance constraint is satisfied, and the specific process is as follows: the vehicle distance constraint is satisfied, and the specific process is as follows: the vehicle distance constraint is satisfied, and the specific process is as follows: the vehicle distance constraint is satisfied, and the specific process is as follows: the vehicle distance constraint is satisfied, and the specific process is as follows: the vehicle distance constraint is satisfied, and the specific process is as follows: the vehicle distance constraint is satisfied, and the specific process is as follows: the vehicle distance constraint is satisfied, and the specific process is as follows: the vehicle distance constraint is satisfied, and the specific process is as follows: the vehicle distance constraint is satisfied, and the specific process is as follows: the vehicle distance constraint is satisfied, and the specific process is as follows: the vehicle distance constraint is satisfied, and the specific process is as follows: the vehicle distance constraint is satisfied, and the specific process is as follows: the vehicle distance constraint is satisfied, and the specific process is as follows: the vehicle distance constraint is satisfied, and the specific process is as follows: the vehicle distance constraint is satisfied, and the specific process is as follows: the vehicle distance constraint is satisfied, and the specific process is as follows: the vehicle distance constraint is satisfied, and the specific process is as follows: the vehicle distance constraint is satisfied, and the specific process is as follows: the vehicle distance constraint is satisfied, and the specific ​ 2. The cybernetic electric vehicle vehicular zone self-organizing energy saving control method of claim 1, wherein, ​ η mode_i (t+1) = max(η i(t) , η cruising_i(t+1) , η following_i(t+1) , η changing_1_i(t+1) , η changing_2_i(t+1) ) wherein: η i(t) is the driving efficiency of vehicle i, η cruising_i(t+1) is the cruising efficiency of the next driving mode of vehicle i, η following_i(t+1) is the following efficiency of the next driving mode of vehicle i, η changing_1_i(t+1) is the first lane-changing efficiency of the next driving mode of vehicle i, η changing_2_i(t+1) is the second lane-changing efficiency of the next driving mode of vehicle i, mode is the optimal driving mode under the next driving mode of vehicle i, η mode_i(t+1) is the driving efficiency corresponding to the optimal driving mode under the next driving mode of vehicle i.

3. The cybernetic electric vehicle vehicular zone self-organizing energy saving control method of claim 2, wherein, When η mode_i(t+1) = η i(t) , vehicle i keeps driving in the existing driving mode; when η mode_i(t+1) = η cruising_i(t+1) , vehicle i drives in a cruise mode; when η mode_i(t+1) = η following_i(t+1) , vehicle i drives in a car following mode; when η mode_i(t+1) = η changing_1_i(t+1) , vehicle i drives in a first lane-changing mode; and when η mode_i(t+1) = η changing_2_i(t+1) , vehicle i drives in a second lane-changing mode.

4. The cybernetic electric vehicle vehicular zone self-organizing energy saving control method of claim 3, wherein, ​ 5. The cybernetic electric vehicle vehicular zone self-organizing energy saving control method of claim 1, wherein, When the vehicle i is in the single-vehicle driving mode, and the next driving mode is the single-vehicle driving mode or the platoon driving mode, the vehicle speed error e v_i_(t) and the current position error e s_i_(t) is calculated, and the vehicle speed compensation value Δv i_(t+1) of the vehicle i at the next time is calculated. e v_i_(t) = v i_c_(t) - v i_r_(t) wherein: v i_r_(t) is the current driving speed, v i_c_(t) is the reference driving speed.

6. The cybernetic electric vehicle vehicular zone self-organizing energy saving control method of claim 5, wherein, When the vehicle i is in the platoon driving mode, and the next driving mode is the platoon driving mode, the vehicle speed error e' of the current vehicle speed is calculated by the following formula v_i_(t) and the current position error e' of the current position is calculated by the following formula s_i_(t) The vehicle speed compensation value Δv' of the vehicle i at the next time is calculated by the following formula i_(t+1) and the distance compensation value Δd is calculated by the following formula i_(t+1) : e′ vi_r_(t) = v i_r_(t) -v f_(t) e′ s_i_(t) = d f-i(t) - d formating_i(t) where: v f_(t) is the platoon driving speed, d formating_i(t) is the current vehicle distance constraint, d f_i(t) is the distance of vehicle i+1 from the preceding vehicle.

7. The cybernetic electric vehicle vehicular zone self-organizing energy saving control method of claim 6, wherein, ​ d formating_i(t+1) = v formating_1(t+1) τ + D where d formating_i(t+1) is the distance between vehicle i and vehicle i+1, v formatinh-1(t+1) is the vehicle speed of the head vehicle of the platoon, τ is the time factor, and D is the static distance.

8. The cybernetic electric vehicle vehicular zone self-organizing energy saving control method of claim 1, wherein, The driving efficiency of vehicle i and the driving efficiency of the next driving mode are calculated using the vehicle efficiency model η = F(η). m η d )=ω1*η m +ω2*η d The calculated weight parameters are ω1 + ω2 = 1, where η m For motor efficiency, η d For transmission efficiency, and η m =F(n) m T m ), η d =F(v), n m T is the motor speed. m v is the motor torque, and v is the vehicle speed.

9. The cybernetic electric vehicle vehicular zone self-organizing energy saving control method of claim 8, wherein, η d and n m The single-cycle dynamics model that is satisfied is: F f = mgfcos a F i = mgsin a where F f is the rolling resistance, F air is the air resistance, F i is the ramp resistance, m is the total vehicle mass, i is the product of the transmission ratio of the deceleration device and the main decelerator, r is the wheel radius, g is the gravitational acceleration, f is the rolling resistance coefficient, a is the road slope, C W is the wind resistance coefficient, p is the air density, and A is the windward area.

10. A system for implementing the method for self-organizing energy saving control of a vehicle area of a connected electric vehicle according to any one of claims 1 to 9, characterized in that, ​ ​ The vehicle state parameters include: a type parameter L of the vehicle i i , L i =1 is a small vehicle, L i =2 is a medium vehicle, L i =3 is a large vehicle; a position coordinate (x i , y i ) of the vehicle i; a longitudinal driving speed v i of the vehicle i, and a driving efficiency η i of the vehicle i.

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