Expressway truck fleet dynamic insertion combined control method and system based on energy consumption optimization

Abstract

The invention relates to the technical field of motorcade insertion control, and discloses a highway freight car motorcade dynamic insertion combined control method and system based on energy consumption optimization, and the method comprises the steps: obtaining motorcade driving data and motorcade state data; if detecting that a new truck applies for joining at the intersection, evaluating whether the new truck has a joining condition or not; constructing a first vehicle fuel consumption model and a second vehicle fuel consumption model, and calculating and analyzing the fuel benefit difference between the independent driving of the vehicle and the joining of the vehicle team; by adding fuel energy consumption benefits and vehicle distribution conditions of different positions of a vehicle team, vehicle team insertion positions of new vehicles are optimized, and an optimal insertion scheme is selected. By intelligently evaluating the insertion position of the new vehicle, optimizing the overall energy efficiency of the vehicle team, collecting and analyzing the historical data and real-time state information of the vehicle, and combining cloud benefit calculation, the fuel consumption and carbon emission of the truck team can be effectively reduced, and the transportation efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of truck platoon insertion control, and particularly to a method and system for dynamic insertion joint control of highway truck platoons based on energy consumption optimization. Background Art

[0002] With the increasing demand for highway truck transportation, energy efficiency optimization during the driving process of trucks in the same type or with the same function has become an important means to improve transportation efficiency and reduce operating costs. Existing methods for dynamic insertion joint control of truck platoons mostly focus on the management of vehicle speed and spacing, but have not fully considered the impact of newly added vehicles on the energy efficiency of the platoon, especially the potential impact on the overall fuel consumption and air resistance of the platoon after the new vehicle is inserted.

[0003] Currently, traditional methods for joint control insertion of truck platoons usually ignore factors such as vehicle characteristics, air resistance, and the current driving state of the platoon, resulting in the failure to maximize the overall energy efficiency of the platoon. Therefore, how to optimize the joining position and method of new vehicles, and thus reduce the fuel consumption of the entire platoon, has become a technical problem to be solved urgently. Summary of the Invention

[0004] In view of the above existing problems, the present invention is proposed. Therefore, the present invention provides a method and system for dynamic insertion joint control of highway truck platoons based on energy consumption optimization, aiming to solve the defect in the prior art that vehicle characteristics and the overall benefits of the platoon are not fully considered. By evaluating the driving data of the new vehicle and its potential impact on energy efficiency, the best joint control insertion plan is selected, so as to minimize the overall fuel consumption of the platoon.

[0005] To solve the above technical problems, the present invention provides the following technical solutions: In a first aspect, the present invention provides a method for dynamic insertion joint control of highway truck platoons based on energy consumption optimization, including: Obtain platoon driving data and platoon status data; Based on the platoon status data and driving data, if it is detected that a new truck applies to join at an intersection, evaluate whether the new vehicle meets the joining conditions; If the new vehicle meets the joining conditions, construct a first vehicle fuel consumption model and a second vehicle fuel consumption model, calculate and analyze the difference in fuel benefits between the vehicle driving alone and after joining the platoon. If the energy consumption of the vehicle driving alone is greater than the energy consumption of driving after joining the platoon, agree to the new vehicle to join; Optimize the platoon insertion position of the new vehicle through the fuel energy consumption benefits and vehicle distribution at different positions of joining the platoon, and select the optimal insertion plan.

[0006] As a preferred solution of the dynamic insertion joint control method for highway truck fleets based on energy consumption optimization according to the present invention, wherein: obtaining the fleet driving data and the fleet status data includes: The fleet driving data includes fuel consumption parameters and hardware status data. The fuel consumption parameters include engine speed, torque, load rate, fuel injection volume, and instantaneous fuel consumption. The hardware status information includes the health of the braking system, the status of sensors, and the status of the power system; The fleet status data includes the number of vehicles and the total length of the current fleet, the real-time speed and acceleration of the vehicles, the real-time fuel consumption of each vehicle, and the air resistance coefficient.

[0007] As a preferred solution of the dynamic insertion joint control method for highway truck fleets based on energy consumption optimization according to the present invention, wherein: evaluating whether a new vehicle meets the joining conditions includes: Condition 1: Determine whether the total length of the fleet is less than the maximum length specified by traffic safety after the new vehicle joins the fleet. If the total length of the fleet is less than the maximum length specified by traffic safety, then Condition 1 is met; Condition 2: Perform real-time vehicle fault detection based on the engine status, fuel sensor data, and brake system health data of the vehicle. If there is no fault, then Condition 2 is met; If both Condition 1 and Condition 2 are met, the new vehicle meets the conditions for joining the fleet.

[0008] As a preferred solution of the dynamic insertion joint control method for highway truck fleets based on energy consumption optimization according to the present invention, wherein: constructing the first vehicle fuel consumption model includes: According to the data of the new vehicle and the current status of the fleet, calculate the fuel consumption of the new vehicle during single-vehicle driving through the fuel consumption model and the air resistance reduction coefficient; The first vehicle fuel consumption model is expressed as:

[0009] Wherein, is the fuel consumption of vehicle i, represents the driving speed, and the parameters , and represent the energy consumption coefficients of the vehicle.

[0010] As a preferred solution of the dynamic insertion joint control method for highway truck fleets based on energy consumption optimization according to the present invention, wherein: constructing the second vehicle fuel consumption model includes: Based on the vehicle fuel consumption calculation results and the current driving status of the fleet, analyze the fuel consumption benefits of inserting the new vehicle into the fleet; The second vehicle fuel consumption benefit model is expressed as: ; where r is the air resistance reduction coefficient, and the value of the air resistance reduction coefficient depends on the fleet size and the insertion position, and the energy-saving benefits under different insertion methods are calculated.

[0011] As a preferred solution of the highway truck fleet dynamic insertion joint control method based on energy consumption optimization according to the present invention, wherein: optimizing the fleet insertion position of the new vehicle by adding the fuel energy consumption benefits at different positions in the fleet includes: Calculating the total fuel consumption of the vehicle under different insertion methods according to the vehicle parameters and the air resistance reduction coefficient, and optimizing the insertion position by using the following formula, which is expressed as: ; where, represents the fuel benefit of the whole fleet, is the fuel consumption of vehicle i when driving alone, is the fuel consumption after joining the fleet, represents the adjustment cost generated during insertion; Optimizing the insertion position by comparing the energy efficiency differences before and after the new vehicle joins the fleet.

[0012] As a preferred solution of the highway truck fleet dynamic insertion joint control method based on energy consumption optimization according to the present invention, wherein: optimizing the fleet insertion position of the new vehicle by the vehicle distribution includes: Optimizing the insertion order according to the weight and volume distribution of the existing vehicles in the fleet. By comparing the weight and volume of the vehicles, inserting the vehicle with a large weight or volume to the front of the fleet, calculating the air resistance reduction amount and the acceleration adjustment cost of the rear vehicles, and selecting the optimal insertion position; Constructing a sorting weight by weight and volume, establishing an optimization objective function and constraint conditions, and maximizing the energy efficiency benefit.

[0013] In a second aspect, the present invention provides a highway truck fleet dynamic insertion joint control system based on energy consumption optimization, including: An acquisition module, configured to acquire the fleet driving data and the fleet status data; A first evaluation module, configured to evaluate whether the new vehicle meets the joining conditions based on the fleet status data and the driving data when it is detected that a new truck applies to join at an intersection; A second evaluation module, configured to, if the new vehicle meets the joining conditions, construct a first vehicle fuel consumption model and a second vehicle fuel consumption model, calculate and analyze the fuel benefit differences between the vehicle driving alone and after joining the fleet, and if the energy consumption of the vehicle driving alone is greater than the energy consumption of driving after joining the fleet, agree to the new vehicle to join; An optimization module for optimizing the fleet insertion position of new vehicles by incorporating the fuel consumption benefits and vehicle distribution at different positions in the fleet and selecting the optimal insertion plan.

[0014] In a third aspect, the present invention provides an electronic device, including: A memory and a processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the joint control method for dynamic insertion of highway truck fleets based on energy consumption optimization are implemented.

[0015] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, and when the computer-executable instructions are executed by a processor, the steps of the joint control method for dynamic insertion of highway truck fleets based on energy consumption optimization are implemented.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: By intelligently evaluating the insertion position of new vehicles, the present invention optimizes the overall energy efficiency of the fleet. By collecting and analyzing the historical data and real-time status information of vehicles and combining cloud benefit calculation, it can effectively reduce the fuel consumption and carbon emissions of truck fleets, improve transportation efficiency, and has the advantages of remarkable energy-saving effect, low cost, and repeatable application, providing an efficient and environmentally friendly fleet management solution for highway truck transportation. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings based on these drawings without creative efforts.

[0018] Figure 1 It is a schematic diagram of the overall process of the joint control method for dynamic insertion of highway truck fleets based on energy consumption optimization according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] In order to make the above objects, features, and advantages of the present invention more obvious and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings of the specification. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments of the present invention shall fall within the protection scope of the present invention.

[0020] Refer to Figure 1As well as Tables 1 - 3, an embodiment of the present invention provides a dynamic insertion joint control method for highway freight vehicle fleets based on energy consumption optimization, including: S100, obtaining fleet driving data and fleet status data; S200, based on the fleet status data and driving data, if it is detected that a new truck applies to join at an intersection, evaluating whether the new vehicle meets the joining conditions; S300, if the new vehicle meets the joining conditions, constructing a first vehicle fuel consumption model and a second vehicle fuel consumption model, calculating and analyzing the difference in fuel efficiency between the vehicle driving alone and after joining the fleet. If the energy consumption of the vehicle driving alone is greater than the energy consumption of driving in the fleet, the new vehicle is allowed to join; S400, optimizing the fleet insertion position of the new vehicle through the fuel energy consumption benefits and vehicle distribution at different positions in the fleet, and selecting the optimal insertion plan.

[0021] It should be noted that the present invention is used for fleets of the same type or same function of vehicles. When a new vehicle applies to join at a highway intersection, by evaluating the driving data and potential energy efficiency impact of the new vehicle, the best insertion plan is selected to maximize the overall benefit of the fleet.

[0022] In a preferred embodiment, obtaining the fleet driving data and fleet status data includes: The fleet driving data includes fuel consumption parameters and hardware status data. The fuel consumption parameters include engine speed, torque, load rate, fuel injection volume, and instantaneous fuel consumption. The hardware status information includes the health of the braking system, sensor status, and power system status; The fleet status data includes the number of vehicles and total length in the current fleet (which needs to comply with traffic regulations), the real - time speed and acceleration of the vehicles, the real - time fuel consumption of each vehicle, and the air resistance coefficient.

[0023] Specifically, the fuel consumption parameters are used to construct an accurate fuel energy consumption model. The hardware status information is used to ensure that the vehicle can safely, accurately, and timely respond to the speed adjustment instructions of the formation. The real - time speed and acceleration of the vehicle dynamic parameters affect the change in fuel consumption. The energy efficiency - related parameters, that is, the real - time fuel consumption of each vehicle, are used to compare the energy - saving benefits after insertion. The air resistance coefficient, that is, the wind resistance coefficient and front surface area of each vehicle, are used to calculate the reduction in formation air resistance.

[0024] In a preferred embodiment, evaluating whether the new vehicle meets the joining conditions includes: Condition 1, judging whether the total length of the fleet is less than the maximum length stipulated by traffic safety after the new vehicle joins the fleet. If the total length of the fleet is less than the maximum length stipulated by traffic safety, then Condition 1 is met; Condition 2: Based on the engine status of the vehicle, fuel sensor data, and brake system health data, perform real-time vehicle fault detection. If no faults are present, then Condition 2 is satisfied. If both Condition 1 and Condition 2 are satisfied simultaneously, then the new vehicle meets the conditions for joining the convoy.

[0025] Specifically, when the convoy is traveling on the highway and a new truck applies to join at an intersection, the joint control system first evaluates whether the new vehicle meets the joining conditions, including whether the current length of the convoy complies with traffic safety regulations (which is determined based on the real-time traffic regulation values in each location). According to traffic safety standards, the maximum length of the convoy is limited to ensure that new vehicle joining requests can be received without exceeding the safety limit; and hardware status detection, performing real-time fault detection based on hardware data such as the engine status of the vehicle, fuel sensor data, and brake system health, to ensure that the vehicle will not affect the stability of the convoy after joining.

[0026] In an alternative implementation, the hardware data for real-time fault detection and the fault detection judgment can refer to Tables 1 - 3.

[0027] Table 1: Engine Status Parameters Parameter Acquisition method Normal range Fault threshold Crankshaft speed Crankshaft position sensor (CKP) 600 - 3000 RPM (no load) Continuous > 3500 RPM Coolant temperature Temperature sensor (ECT) 85-105℃ >110 °C or <70 °C Oil pressure Piezo-resistive sensor 200 - 600 kPa <150 kPa (low load) Turbocharger pressure MAP sensor 100 - 250 kPa (depending on vehicle model) Fluctuation > 30% of reference value Vibration amplitude In-cylinder knock sensor <5 m / s² > 8 m / s² (continuous for 10 s) Table 2: Fuel System Parameters Parameter Acquisition method Normal range Fault characteristic Fuel pressure Rail pressure sensor (common rail system) 200 - 2000 bar Fluctuation > ±10% of set value Fuel flow Mass air flow meter (MAF) Match current engine load Continuous deviation from theoretical value by 15% Fuel filter status Differential pressure sensor ΔP < 50 kPa ΔP > 80 kPa Injector pulse width ECU control signal 1 - 20 ms Beyond ECU calibration range Table 3: Brake System Parameters Parameter Acquisition method Normal range Failure criterion Brake pad thickness Wear sensor (contact type) > 5 mm (new pad 12 mm) ≤ 2 mm Brake fluid level Float type sensor Liquid level between MAX - MIN <MIN tag ABS wheel speed difference Hall wheel speed sensor Four-wheel speed difference < 10% > 20% (possible wheel lock) Brake chamber pressure Air pressure sensor (commercial vehicle) 6 - 8 bar (service brake) <4.5 bar (Emergency braking failure) In a preferred implementation, constructing the first vehicle fuel consumption model includes: Based on the data of the new vehicle and the current state of the convoy, calculate the fuel consumption of the new vehicle during single-vehicle driving through the fuel consumption model and the air resistance reduction coefficient. The first vehicle fuel consumption model is expressed as: ; Where, is the fuel consumption of vehicle i, represents the driving speed, and the parameters , and represent the energy consumption coefficients of the vehicle.

[0028] In a preferred implementation, constructing the second vehicle fuel consumption model includes: Based on the vehicle fuel consumption calculation results and the current driving state of the convoy, analyze the fuel consumption benefit of inserting the new vehicle into the convoy. The second vehicle fuel consumption benefit model is expressed as: ; Among them, r is the air resistance reduction coefficient, and the value of the air resistance reduction coefficient depends on the fleet size and the insertion position, and the energy-saving benefits under different insertion methods are calculated.

[0029] Specifically, when a new vehicle applies to join the fleet, information such as the driving destination, hardware operating status, and fuel model is automatically obtained and transmitted to the cloud for comprehensive benefit analysis. The benefit difference is calculated, and the fuel consumption difference between the vehicle driving alone and joining the fleet is compared. The dynamically set threshold is determined according to factors such as vehicle type and road traffic conditions. In this embodiment, when the fuel consumption benefit after joining the fleet is greater than the dynamically set threshold, it meets , then the insertion condition is satisfied, and the join request is approved.

[0030] In a preferred implementation manner, optimizing the fleet insertion position of a new vehicle through the fuel energy consumption benefits at different positions in the fleet includes: According to the vehicle parameters and the air resistance reduction coefficient, calculate the total fuel consumption of different insertion methods of the vehicle, and optimize the insertion position using the following formula, expressed as: ; Among them, represents the fuel benefit of the entire fleet, is the fuel consumption of vehicle i driving alone, is the fuel consumption after joining the fleet, represents the adjustment cost generated during insertion; Optimize the insertion position by comparing the energy efficiency differences before and after the new vehicle joins the fleet.

[0031] In a preferred implementation manner, optimizing the fleet insertion position of a new vehicle through the vehicle distribution includes: Optimize the insertion order according to the weight and volume distribution of the existing vehicles in the fleet. By comparing the weight and volume of the vehicles, insert the vehicles with larger weight or volume to the front of the fleet, calculate the air resistance reduction amount and acceleration adjustment cost of the rear vehicles, and select the optimal insertion position; Construct sorting weights through weight and volume, establish an optimization objective function and constraint conditions to maximize the energy efficiency benefit.

[0032] In an alternative implementation manner, optimizing the fleet insertion position of a new vehicle through the vehicle distribution includes: Calculate the air resistance reduction amount after joining the fleet through parameters such as the vehicle air resistance coefficient and the front surface area, aiming to optimize the air flow cooperation between vehicles and further reduce energy consumption.

[0033] Based on the fuel consumption model of the vehicle, apply mixed integer nonlinear programming to optimize the insertion position and solve the permutation scheme that minimizes the fuel consumption of the fleet.

[0034] 1. Weight and Volume Optimization Function of front heavy vehicles. When a heavy vehicle (weight , volume ) is placed at the front of the vehicle fleet, the reduction in air resistance ΔD of the rear vehicles is proportional to the cross-sectional area A front of the leading vehicle and the square of the speed v 2 , expressed as: ΔD ≈A front ×v 2 × rho, where rho is the air density; Inertial traction effect, reduction in acceleration adjustment cost: If the mass of the leading vehicle is large, the acceleration adjustment cost of the rear vehicles can be reduced, expressed as: ; where is the change in speed.

[0035] 2. Mathematical Model of Sequential Optimization Calculation of weight factors. Sorting weights are constructed based on weight and volume , expressed as: ; where represents the adjustment coefficient, taking a value of 0.6 places more emphasis on weight, represents the maximum weight in the vehicle fleet, represents the maximum volume in the vehicle fleet, represents the weight of the th vehicle in the vehicle fleet, represents the th vehicle in the vehicle fleet; Establish an optimization objective function to maximize the energy efficiency benefit, which is the sum of the individual fuel consumption of each vehicle to be inserted minus the fuel consumption after forming a team, and then subtract the total adjustment cost. The constraint conditions include safety distance and vehicle fleet length limit.

[0036] Determination of insertion position. The optimized vehicle order changes the air resistance coefficient, directly affecting the fuel model; Reduction in adjustment cost. Placing heavy vehicles in the front reduces the acceleration cost of the rear vehicles.

[0037] Arrange heavier vehicles at the front to enhance the overall energy-saving effect of the vehicle fleet.

[0038] In an alternative implementation, calculate the adjustment cost generated when a new vehicle is inserted into the vehicle fleet , and this adjustment cost generally includes the following factors: Acceleration or deceleration cost: When a new vehicle is inserted into the fleet, it may need to accelerate or decelerate, which consumes additional fuel. This part of the cost is determined based on the powertrain of the new vehicle and the relative speed changes of other vehicles in the fleet.

[0039] Safety distance adjustment cost: After a new vehicle joins, it may be necessary to adjust the safety distances between the vehicles in the fleet, which affects the overall driving efficiency of the fleet and may lead to additional fuel consumption. This part of the cost is calculated based on the current vehicle speed and inter-vehicle distance in the fleet.

[0040] Traffic flow and road condition adaptation cost: After a new vehicle joins the fleet, it may be necessary to adjust the fleet driving strategy according to the current road conditions and traffic flow, which may lead to a decrease in the overall efficiency of the fleet and thus increase additional fuel consumption. This part of the cost takes into account factors such as congested roads and road gradient changes during calculation.

[0041] Adjustment costs generated when a new vehicle is inserted into the fleet Expressed as: ; Where represents the time increment caused by the inserted vehicle (such as adjusting vehicle speed, parking, etc.); is the average fuel consumption of each vehicle in the fleet; is the speed change amount when the vehicle is inserted; is the fuel consumption increment caused by the speed change; is the change amount of the inter-vehicle distance adjusted due to the addition of the new vehicle; is the additional cost increased due to traffic flow and road condition changes.

[0042] Finally, the optimal insertion position and speed command are fed back to jointly regulate the addition of the new vehicle in real time, optimizing the energy consumption benefit of the fleet.

[0043] It should be noted that the present invention can effectively reduce the fuel consumption and carbon emissions of the truck fleet, improve the transportation efficiency, and has the advantages of remarkable energy-saving effect, low cost, and repeatable application by intelligently evaluating the insertion position of the new vehicle, optimizing the overall energy efficiency of the fleet, collecting and analyzing the historical data and real-time status information of the vehicle, and combining the cloud benefit calculation, providing an efficient and environmentally friendly fleet management solution for highway truck transportation.

[0044] The above is a schematic solution of a joint control method for dynamic insertion of highway truck fleets based on energy consumption optimization in this embodiment. It should be noted that the technical solution of the joint control system for dynamic insertion of highway truck fleets based on energy consumption optimization belongs to the same concept as the technical solution of the above-mentioned joint control method for dynamic insertion of highway truck fleets based on energy consumption optimization. For the details not described in detail in the technical solution of the joint control system for dynamic insertion of highway truck fleets based on energy consumption optimization in this embodiment, reference can be made to the description of the technical solution of the above-mentioned joint control method for dynamic insertion of highway truck fleets based on energy consumption optimization.

[0045] A joint control system for dynamic insertion of highway truck fleets based on energy consumption optimization in this embodiment includes: An acquisition module for obtaining fleet driving data and fleet status data; A first evaluation module for evaluating whether a new vehicle meets the joining conditions based on the fleet status data and driving data when it is detected that a new truck applies to join at an intersection; A second evaluation module for, if the new vehicle meets the joining conditions, constructing a first vehicle fuel consumption model and a second vehicle fuel consumption model, calculating and analyzing the difference in fuel efficiency between the vehicle driving alone and after joining the fleet, and if the energy consumption of the vehicle driving alone is greater than the energy consumption of driving after joining the fleet, agreeing to the new vehicle to join; An optimization module for optimizing the fleet insertion position of the new vehicle through the fuel energy consumption benefits and vehicle distribution at different positions in the fleet, and selecting the optimal insertion plan.

[0046] The system of the present invention also includes a receiving module, a feedback module and a data processing module. The receiving module is used to receive the driving data and real-time status information of the new vehicle and transmit them to the first evaluation module and the second evaluation module, which perform energy efficiency calculations based on the historical data of the vehicle, the fuel consumption model and the current fleet status, and evaluate the best plan for inserting the new vehicle into the fleet; the feedback module then performs joint control of the fleet according to the evaluation results, and issues insertion position and speed control instructions to the leading vehicle to ensure the optimal overall energy efficiency of the fleet; the data processing module is used for data storage, real-time calculation and scheduling management. The receiving module and the feedback module are installed in on-vehicle devices, and the first evaluation module, the second evaluation module, the optimization module and the data processing center are established in the cloud server to ensure the smooth and efficient dynamic insertion joint control process of the entire fleet.

[0047] This embodiment also provides an electronic device applicable to the situation of joint control of dynamic insertion of highway truck fleets based on energy consumption optimization, including: A memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the dynamic insertion joint control method for highway truck fleets based on energy consumption optimization as proposed in the above embodiments.

[0048] This embodiment also provides a storage medium, on which a computer program is stored. When the program is executed by a processor, it implements the dynamic insertion joint control method for highway truck fleets based on energy consumption optimization as proposed in the above embodiments.

[0049] The storage medium proposed in this embodiment and the dynamic insertion joint control method for highway truck fleets based on energy consumption optimization proposed in the above embodiments belong to the same inventive concept. The technical details not described in detail in this embodiment can be referred to the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0050] Through the above description of the embodiments, those skilled in the art can clearly understand that the present invention can be implemented by means of software and necessary general hardware. Of course, it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a floppy disk, a read-only memory (ROM), a random access memory (RAM), a flash memory (FLASH), a hard disk, or an optical disc of a computer, etc., including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods of the various embodiments of the present invention.

[0051] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered by the scope of the claims of the present invention.

Claims

1. A joint control method for dynamic insertion of a highway truck fleet based on energy consumption optimization, characterized in that: include: Obtain fleet driving data and fleet status data; Based on the fleet status data and driving data, if a new truck is detected to apply for joining at the intersection, assess whether the new truck meets the conditions for joining; If the new vehicle meets the conditions for joining, the first vehicle fuel consumption model and the second vehicle fuel consumption model are constructed to calculate and analyze the difference in fuel efficiency between the vehicle driving alone and joining the team. If the energy consumption of the vehicle driving alone is greater than the energy consumption of joining the team, the new vehicle is allowed to join; By taking into account the fuel efficiency and vehicle distribution at different positions in the fleet, the insertion position of new vehicles into the fleet is optimized and the best insertion plan is selected.

2. A highway truck fleet dynamic insertion joint control method based on energy consumption optimization as claimed in claim 1, characterized in that: Obtaining fleet driving data and fleet status data includes: The fleet driving data includes fuel consumption parameters and hardware status data, wherein the fuel consumption parameters include engine speed, torque, load rate, fuel injection amount, and instantaneous fuel consumption, and the hardware status information includes brake system health, sensor status, and power system status; The fleet status data includes the number and total length of the vehicles in the current fleet, the real-time speed and acceleration of the vehicles, the real-time fuel consumption of each vehicle, and the air resistance coefficient.

3. The method for dynamic insertion joint control of a highway truck fleet based on energy consumption optimization as claimed in claim 1, characterized in that: The assessment of whether a new vehicle is eligible for inclusion includes: Condition 1: After a new vehicle joins the team, determine whether the total length of the team is less than the maximum length stipulated by traffic safety regulations. If the total length of the team is less than the maximum length stipulated by traffic safety regulations, condition 1 is met. Condition 2: Perform real-time vehicle fault detection based on the vehicle's engine status, fuel sensor data, and brake system health data. If there is no fault, condition 2 is met; If both condition one and condition two are met, the new vehicle is eligible to join the fleet.

4. A highway truck fleet dynamic insertion joint control method based on energy consumption optimization as claimed in claim 2, characterized in that: Constructing the first vehicle fuel consumption model includes: According to the data of the new vehicle and the current status of the fleet, the fuel consumption of the new vehicle during the driving process of a single vehicle is calculated through the fuel consumption model and the air resistance reduction coefficient; The first vehicle fuel consumption model is expressed as: ； in, is the fuel consumption of vehicle i, Indicates the driving speed, parameter , and Indicates the energy consumption coefficient of the vehicle.

5. The method for dynamic insertion joint control of a highway truck fleet based on energy consumption optimization as claimed in claim 4, characterized in that: Constructing the second vehicle fuel consumption model includes: Analyze the fuel consumption benefits of adding new vehicles to the fleet based on the vehicle fuel consumption calculation results and the current driving status of the fleet; The fuel consumption benefit model of the second vehicle is expressed as: ； Among them, r is the air resistance reduction coefficient. The air resistance reduction coefficient is determined by the fleet size and insertion position. The energy saving benefits under different insertion methods are calculated.

6. A highway truck fleet dynamic insertion joint control method based on energy consumption optimization as claimed in claim 5, characterized in that: Optimizing the position of new vehicles for fleet insertion by taking into account the fuel efficiency benefits of different positions in the fleet, including: According to the vehicle parameters and the air resistance reduction coefficient, the total fuel consumption of the vehicle in different insertion modes is calculated, and the insertion position is optimized using the following formula, which is expressed as: ； in, Represents the overall fuel efficiency of the fleet, is the fuel consumption of vehicle i driving alone, is the fuel consumption after joining the fleet, represents the adjustment cost incurred during insertion; By comparing the energy efficiency difference of new vehicles before and after they join the fleet, the insertion position can be optimized.

7. A highway truck fleet dynamic insertion joint control method based on energy consumption optimization as claimed in claim 6, characterized in that: Optimizing the position of new vehicles for fleet insertion based on vehicle distribution includes: Optimize the insertion order according to the weight and volume distribution of the existing vehicles in the fleet. By comparing the weight and volume of the vehicles, the vehicles with larger weight or volume are inserted at the front of the fleet. The air resistance reduction and acceleration adjustment cost of the rear vehicles are calculated to select the optimal insertion position. The sorting weights are constructed by weight and volume, and the optimization objective function and constraints are established to maximize the energy efficiency benefits.

8. A highway truck fleet dynamic insertion joint control system based on energy consumption optimization, using a highway truck fleet dynamic insertion joint control method based on energy consumption optimization as described in any one of claims 1 to 7, characterized in that: include, The acquisition module is used to obtain the fleet driving data and fleet status data; A first evaluation module is used to evaluate whether a new truck meets the conditions for joining the road if a new truck is detected to apply for joining the road based on the fleet status data and driving data; The second evaluation module is used to construct a first vehicle fuel consumption model and a second vehicle fuel consumption model if the new vehicle meets the conditions for joining, calculate and analyze the difference in fuel efficiency between the vehicle driving alone and joining the team, and if the energy consumption of the vehicle driving alone is greater than the energy consumption of joining the team, the new vehicle is allowed to join; The optimization module is used to optimize the insertion position of new vehicles into the fleet by adding the fuel consumption efficiency and vehicle distribution at different positions of the fleet, and select the best insertion plan.

9. An electronic device, characterized in that: include: Memory and processor; The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of a method for dynamic insertion joint control of a highway truck fleet based on energy consumption optimization as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: It stores computer executable instructions, which, when executed by a processor, implement the steps of a method for dynamic insertion joint control of a highway truck fleet based on energy consumption optimization as described in any one of claims 1 to 7.

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