Vehicle weight estimation method and device and storage medium

Abstract

The invention provides a vehicle weight estimation method and device and a storage medium. The method comprises the steps of obtaining vehicle structure parameters; acquiring vehicle operation data at the effective stage that the vehicle speed is greater than zero and the driving torque is greater than zero; obtaining an ideal wind resistance coefficient and an ideal rolling resistance coefficient of the vehicle in the running process; and estimating the estimated weight of the vehicle according to the vehicle structure parameters, the vehicle operation data, the ideal wind resistance coefficient and the ideal rolling resistance coefficient. According to the method, the whole vehicle weight estimation can be realized under the condition of not increasing the hardware cost.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and in particular to a vehicle weight estimation method, device and storage medium. Background Art

[0002] Vehicle overloading and speeding are the main causes of traffic accidents. Compared with speeding, vehicle overloading is more dangerous and more hidden. Overweight vehicles cause collapse and damage to restricted sections of roads, which not only seriously damages highway pavement and bridge facilities, but also easily causes road traffic accidents, endangering the lives and safety of people.

[0003] For the measurement of vehicle weight, existing solutions usually require the addition of suspension travel sensors or road slope sensors, which increases vehicle costs. Summary of the invention

[0004] The purpose of the embodiments of the present application is to provide a vehicle weight estimation method, device and storage medium, which can realize vehicle weight estimation without increasing hardware costs.

[0005] One aspect of an embodiment of the present application provides a vehicle weight estimation method. The method includes: obtaining vehicle structural parameters; obtaining vehicle operation data in an effective stage when the vehicle speed is greater than zero and the driving torque is greater than zero; obtaining an ideal wind resistance coefficient and an ideal rolling resistance coefficient of the vehicle during operation; estimating the vehicle estimated weight based on the vehicle structural parameters, the vehicle operation data, the ideal wind resistance coefficient, and the ideal rolling resistance coefficient.

[0006] Furthermore, the method also includes: obtaining a vehicle energy balance equation in an effective stage based on a dynamic equation of vehicle driving, wherein the vehicle estimated weight is estimated through the vehicle energy balance equation based on the vehicle structural parameters, the vehicle operating data, the ideal wind resistance coefficient and the ideal rolling resistance coefficient.

[0007] Furthermore, the vehicle energy balance equation is:

[0008] A1-A2×C D -A3=m×(A4+A5×f+A6)

[0009] Among them, A1, A2, A3, A4, A5, A6 represent the characteristic parameters of the vehicle energy balance equation, C D represents the drag coefficient, f represents the rolling resistance coefficient, and m represents the vehicle weight.

[0010]

[0011] In the above formula, n represents the number of sampling cycles; Δt represents the sampling period, in seconds; g represents the acceleration of gravity;

[0012] The vehicle structural parameters include μ d , A, I f ,I r ,I m 、i g , i0 and r, μ d represents the efficiency of the transmission system; A represents the frontal area, in square meters; I f Represents the moment of inertia of the front wheel, in kilograms per square meter; I r Represents the moment of inertia of the rear wheel, in kilograms per square meter; I m Represents the motor rotor moment of inertia, in kilograms per square meter; i g represents the transmission ratio of the reducer; i0 represents the main reduction ratio; r represents the wheel radius, in meters;

[0013] The vehicle operation data includes T m,i 、n m,i 、V i , and h i , T m,i Represents the motor drive torque of the i-th sampling period, in Nm; n m,i Represents the speed of the drive motor in the i-th sampling period, in revolutions per minute; V i represents the vehicle speed in the i-th sampling period, in meters per second; represents the acceleration of the ith sampling period, in meters per square meter; h i Represents the vehicle altitude increment in the i-th sampling period, in meters.

[0014] Furthermore, the obtaining of the ideal drag coefficient and the ideal rolling resistance coefficient of the vehicle during operation includes: identifying the ideal drag coefficient and the ideal rolling resistance coefficient of the vehicle during operation based on vehicle test operation data of multiple effective test stages under different loads, the effective test stage being a stage where the vehicle speed is greater than zero and the driving torque is greater than zero.

[0015] Furthermore, the method of identifying the ideal drag coefficient and the ideal rolling resistance coefficient of the vehicle during operation based on the vehicle test operation data of multiple valid test stages of the vehicle at different loads includes: establishing a constraint relationship between the drag coefficient and the rolling resistance coefficient based on the vehicle test operation data of multiple valid test stages of the vehicle at different loads, and establishing an optimization model of the drag coefficient and the rolling resistance coefficient to calculate the ideal drag coefficient and the ideal rolling resistance coefficient.

[0016] Furthermore, the optimization model takes minimizing the sum of the differences between the actual weight of the vehicle and the estimated weight of the vehicle in multiple valid test stages as the optimization goal, and finally identifies the ideal drag coefficient and the ideal rolling resistance coefficient. The optimization goal is:

[0017]

[0018] Wherein, Δm represents the sum of the differences between the actual vehicle weight and the estimated vehicle weight in multiple valid stages; i represents the i-th valid test stage; k represents the number of data in the valid test stage; m sj,i Represents the actual weight of the vehicle in the i-th valid test stage; m gj,i Represents the estimated vehicle weight estimated in the i-th valid test stage.

[0019] Further, the acquiring of vehicle operation data in the effective stage where the vehicle speed is greater than zero and the driving torque is greater than zero includes: acquiring the vehicle operation data in multiple effective stages, wherein the estimating the vehicle estimated weight through the vehicle energy balance equation based on the vehicle structural parameters, the vehicle operation data, the ideal drag coefficient and the ideal rolling resistance coefficient includes: obtaining the vehicle estimated weight in each effective stage through the vehicle energy balance equation based on the vehicle structural parameters, the vehicle operation data in each effective stage, the ideal drag coefficient and the ideal rolling resistance coefficient; obtaining the final vehicle estimated weight based on the vehicle estimated weight in each effective stage.

[0020] Furthermore, obtaining the final vehicle estimated weight based on the vehicle weight at each valid stage includes obtaining the final vehicle estimated weight by one of the following methods: assigning weights to the vehicle estimated weights at each valid stage according to the corresponding mileage to obtain the final vehicle estimated weight; taking the middle value of the vehicle estimated weights at each valid stage as the final vehicle estimated weight; taking the average value of the vehicle estimated weights at each valid stage as the final vehicle estimated weight.

[0021] Another aspect of an embodiment of the present application provides a computer-readable storage medium having a computer program / instruction stored thereon, which implements the steps of the vehicle weight estimation method as described above when the computer program / instruction is executed by a processor.

[0022] Another aspect of the embodiments of the present application provides a vehicle weight estimation device, which includes a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the vehicle weight estimation method described above.

[0023] The vehicle weight estimation method, device, and storage medium of one or more embodiments of the present application use big data to estimate the weight of the entire vehicle without increasing hardware costs, and are low-cost.

[0024] In addition, the vehicle weight estimation method, device and storage medium of one or more embodiments of the present application only use the energy balance of the driving stage to estimate the weight of the whole vehicle, thereby eliminating the influence of friction braking and achieving high weight estimation accuracy.

[0025] In addition, the vehicle weight estimation method, device and storage medium of one or more embodiments of the present application can reduce the impact of altitude accuracy on weight estimation by fusing data from multiple valid stages of the vehicle, thereby further improving the weight estimation accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 The present invention is a flowchart of a vehicle weight estimation method according to an embodiment of the present invention.

[0027] Figure 2 This is a flow chart for identifying the wind resistance coefficient and rolling resistance coefficient according to one embodiment of the present application.

[0028] Figure 3 A schematic block diagram of a vehicle weight estimation device according to an embodiment of the present application. DETAILED DESCRIPTION

[0029] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Instead, they are merely examples of devices consistent with some aspects of the present application as detailed in the appended claims.

[0030] The following is a detailed description of the vehicle weight estimation method, device and storage medium of each embodiment of the present application in conjunction with the accompanying drawings. In the absence of conflict, the features of the following embodiments and implementations can be combined with each other.

[0031] Figure 1 A flow chart of a vehicle control method according to an embodiment of the present application is disclosed. Figure 1 As shown, a vehicle control method according to an embodiment of the present application may include steps S1 to S4.

[0032] In step S1, vehicle structural parameters are obtained.

[0033] In step S2 , vehicle operation data in an effective phase in which the vehicle speed is greater than zero and the driving torque is greater than zero is acquired.

[0034] Table 1 shows the classification of vehicle driving conditions. When the vehicle speed is > 0, the longitudinal force of the vehicle is divided into three conditions: driving, feedback, and braking. Driving: vehicle speed > 0 and driving torque > 0; feedback: vehicle speed > 0 and driving torque < 0, feedback braking is implemented; braking: vehicle speed > 0 and friction braking torque > 0, driving torque < 0 or = 0, feedback braking is implemented.

[0035] Table 1

[0036] drive Giving Back brake Effective stage Invalid phase Invalid phase

[0037] Among them, vehicle speed > 0 and driving torque > 0 (driving stage) means that the vehicle is subjected to forward driving force, which is the valid stage of the vehicle weight identification data of this application, that is, the data in the valid stage can be used for the vehicle weight analysis and calculation of this application; and other stages are invalid stages of the vehicle weight identification data of this application, that is, they are not used for vehicle weight analysis and calculation.

[0038] In step S3, the ideal wind resistance coefficient and the ideal rolling resistance coefficient of the vehicle during operation are obtained.

[0039] In step S4, the estimated vehicle weight may be estimated based on vehicle structural parameters, vehicle operating data, an ideal wind resistance coefficient, and an ideal rolling resistance coefficient.

[0040] In some embodiments, the vehicle weight estimation method of the present application may further include step S5.

[0041] In step S5, the vehicle energy balance equation in the effective stage can be obtained according to the dynamic equation of vehicle driving.

[0042] Among them, in step S4, the estimated vehicle weight can be estimated by the vehicle energy balance equation obtained in step S5 based on the vehicle structural parameters obtained in step S1, the vehicle operation data in the effective stage obtained in step S2, and the ideal drag coefficient and ideal rolling resistance coefficient obtained in step S3.

[0043] The following will introduce in detail how to obtain the vehicle energy balance equation in the effective stage based on the vehicle's dynamic equation.

[0044] According to the vehicle dynamics equation F t =F f +F w +F i +F j , where F t Represents wheel traction, F f Represents rolling resistance, F w Represents air resistance, F i Represents the slope resistance, F jrepresents the acceleration resistance, which can be obtained as follows:

[0045]

[0046] Among them, F t1 Represents the wheel traction after deducting wind resistance, in N (Newton); T m Represents the motor drive torque, in Nm (Newton meter); μ d represents the transmission system efficiency; i0 represents the main reduction transmission ratio; i g represents the transmission ratio of the reducer; r represents the wheel radius, in m (meter); C D represents the drag coefficient; f represents the rolling resistance coefficient; A represents the frontal area, the unit is m 2 (square meters); V represents the vehicle speed, in km / h (kilometers per hour); m represents the vehicle weight, in kg (kilograms); g represents the acceleration of gravity; α represents the slope angle of the vehicle; δ represents the mass increase coefficient; Represents acceleration in m / s 2 (meters / second squared).

[0047] Among them, the mass increase coefficient δ is expressed as:

[0048]

[0049] Mass increment of rotating parts m δ It is expressed as:

[0050]

[0051] Among them, I f Represents the front wheel moment of inertia, in kgm 2 (kg / m2); I r Represents the moment of inertia of the rear wheel, in kgm 2 ;I m Represents the motor rotor inertia, unit is kgm 2 .

[0052] Substituting formula (2) and (3) into formula (1), we can obtain:

[0053]

[0054] Among them, the vehicle structure parameters can include μ d ,i0,i g , r, A, I f ,I r ,I m Table 2 shows the vehicle structural parameters used in formula (4).

[0055] Table 2 Vehicle structural parameters

[0056] parameter <![CDATA[μ d ]]> <![CDATA[i0]]> <![CDATA[i g ]]> r A <![CDATA[I f ]]> <![CDATA[I r ]]> <![CDATA[I m ]]> Numeric 0.95 4.235 2.3 0.314 3.16 0.45 0.9 0.05

[0057] Multiply both sides of formula (4) by V×Δt to obtain the vehicle energy balance equation for the i-th sampling period in the effective stage, as shown below:

[0058]

[0059] Among them, T m,i Represents the motor drive torque of the i-th sampling period, in Nm; n m,i Represents the speed of the drive motor in the i-th sampling period, in rpm (revolutions per minute); V i Represents the vehicle speed in the i-th sampling period, in m / s; Represents the acceleration of the i-th sampling period, in m / s 2 ; Δt represents the sampling period, the unit is s (seconds); h i Represents the vehicle altitude increment in the i-th sampling period, in m (meters).

[0060] Table 3 shows the vehicle operation data in the effective stage. The vehicle operation data may include T m,i 、n m,i ,V, and h i Of course, in order to ensure mutual verification between data, the vehicle operation data may also include other data, etc., and this application does not limit this.

[0061] Table 3 Vehicle operation data

[0062]

[0063]

[0064] For formula (5), the acceleration of the i-th sampling period is The mass increment m of the rotating part can be obtained by dividing the front and rear speed difference shown in Table 3 by the time interval Δt; δ It can be easily obtained by formula (3); the vehicle altitude increment h in the i-th sampling period i It can be obtained by using the altitude difference.

[0065] The energy balance equation of the vehicle in the effective stage can be further obtained from formula (5), as shown below:

[0066] A1-A2×C D -A3=m×(A4+A5×f+A6) (6)

[0067] Among them, A1, A2, A3, A4, A5, and A6 represent the characteristic parameters of the vehicle energy balance equation, which can be expressed as follows:

[0068]

[0069] Where n represents the number of sampling cycles.

[0070] Therefore, after obtaining the vehicle structural parameters and the vehicle operation data in the effective stage, the characteristic parameters A1, A2, A3, A4, A5, and A6 in the vehicle energy balance equation in the effective stage can be calculated according to the formulas of the above characteristic parameters.

[0071] Furthermore, after calculating the characteristic parameters A1, A2, A3, A4, A5, A6 in the vehicle energy balance equation in the effective stage, and obtaining the ideal drag coefficient and the ideal rolling resistance coefficient, the vehicle weight can be estimated according to the vehicle energy balance equation in the effective stage shown in formula (6), which is called the estimated vehicle weight.

[0072] The following will introduce in detail how to obtain the ideal drag coefficient and ideal rolling resistance coefficient of the vehicle during operation.

[0073] Since the vehicle's drag coefficient C during operation D The rolling resistance coefficient f has a great influence on energy consumption. Therefore, it is necessary to obtain the drag coefficient C of the vehicle during operation. D The ideal values ​​of the rolling resistance coefficient f are called the ideal drag coefficient and the ideal rolling resistance coefficient.

[0074] From formula (6), we can get the estimated vehicle weight m in the effective stage: gj The expression is as follows:

[0075]

[0076] The vehicle is loaded with different loads and the drag coefficient C of the vehicle is measured on typical roads. D And identification test of rolling resistance coefficient f. Figure 2 The following is a flow chart for identifying an ideal wind resistance coefficient and an ideal rolling resistance coefficient according to an embodiment of the present application. Figure 2 As shown, in step S31, it is determined whether the vehicle is in the effective test stage during the test, and the effective test stage refers to the stage where the vehicle speed is greater than zero and the driving torque is greater than zero. That is, it is determined whether the vehicle speed>0 and the driving torque>0. When the result of the determination is "yes", it proceeds to step S32. Otherwise, it returns to continue the determination.

[0077] In step S32, vehicle test operation data of the vehicle in multiple valid test stages is collected.

[0078] In each effective test stage, the mileage can be long or short, the speed can be fast or slow, and the test time can be long or short. Before each test, the vehicle load is measured to obtain the actual weight of the vehicle.

[0079] The ideal wind resistance coefficient and the ideal rolling resistance coefficient of the vehicle during operation can be identified based on vehicle test operation data of multiple effective test stages under different loads.

[0080] Specifically, in step S33, the vehicle test operation data of multiple effective test stages under different loads can be used to construct k effective test stages, and the actual vehicle weight obtained is substituted into the vehicle weight expression shown in formula (7), and the drag coefficient C of the k effective test stages can be established. D and the constraint relationship between the rolling resistance coefficient f and the drag coefficient C D and optimization model of rolling resistance coefficient f.

[0081] In step S34, the optimization target of the optimization model is set, so that the ideal wind resistance coefficient and the ideal rolling resistance coefficient of the vehicle can be finally identified.

[0082] Optionally, the optimization model takes minimizing the sum of the differences between the actual weight of the vehicle and the estimated weight of the vehicle in multiple valid test stages as the optimization objective. The optimization objective can be expressed as:

[0083]

[0084] Wherein, Δm represents the sum of the differences between the actual vehicle weight and the estimated vehicle weight in multiple valid stages; i represents the i-th valid test stage; k represents the number of data in the valid test stage; m sj,i Represents the actual weight of the vehicle in the i-th valid test stage; m gj,i Represents the estimated vehicle weight estimated in the i-th valid test stage.

[0085] The estimated vehicle weight m estimated in the i-th effective test phase gj,i It can be obtained by the above formula (7).

[0086] In some embodiments, the step S2 of acquiring the vehicle operation data in the effective stage when the vehicle speed is greater than zero and the driving torque is greater than zero may include: acquiring the vehicle operation data in multiple effective stages.

[0087] Then, in this case, step S4 of estimating the vehicle weight according to the vehicle structural parameters, vehicle operating data, ideal wind resistance coefficient and ideal rolling resistance coefficient through the vehicle energy balance equation may include step S41 and step S42.

[0088] In step S41, the vehicle weight at each effective stage can be estimated through the vehicle energy balance equation according to the vehicle structural parameters, the vehicle operation data at each effective stage, the ideal wind resistance coefficient and the ideal rolling resistance coefficient.

[0089] In step S42, the final estimated vehicle weight is obtained based on the estimated vehicle weights at each effective stage estimated in step S41.

[0090] In some embodiments, the estimated vehicle weights at each effective stage may be weighted according to the corresponding mileage to obtain the final estimated vehicle weight, as shown in the following formula:

[0091]

[0092] in,

[0093]

[0094] m gj,final represents the final estimated vehicle weight; N represents the total number of valid test phases for this vehicle weight estimation; L i represents the mileage of the i-th valid test phase; L represents the total mileage of N valid test phases, m gj,i Represents the estimated weight of the vehicle in the i-th valid test stage.

[0095] Of course, the final estimated vehicle weight obtained based on the estimated vehicle weight at each effective stage in the present application is not limited to being obtained by assigning weights to the estimated vehicle weight at each effective stage according to the corresponding mileage. In other embodiments, the middle value of the estimated vehicle weight at each effective stage can be taken as the final estimated vehicle weight; or, the average value of the estimated vehicle weight at each effective stage can be taken as the final estimated vehicle weight. The present application does not impose any restrictions on this.

[0096] The vehicle weight estimation method of the present application can use the effective phase vehicle energy balance equation to identify the drag coefficient C when the vehicle weight is known. D and the ideal value of the rolling resistance coefficient f, that is, the ideal drag coefficient and the ideal rolling resistance coefficient, and further estimate the vehicle weight when the ideal drag coefficient and the ideal rolling resistance coefficient are determined, eliminating the intervention of friction braking and regenerative braking.

[0097] The vehicle weight estimation method of the present application uses big data to estimate the weight of the entire vehicle without increasing hardware costs, and the cost is low.

[0098] In addition, the vehicle weight estimation method of the present application estimates the weight of the entire vehicle using only the energy balance of the driving phase, thereby eliminating the influence of friction braking and achieving high weight estimation accuracy.

[0099] In addition, the vehicle weight estimation method of the present application can reduce the impact of altitude accuracy on weight estimation by fusing data from multiple valid stages of the vehicle, thereby further improving the weight estimation accuracy.

[0100] The present application also provides a computer-readable storage medium on which a computer program / instruction is stored. When the computer program / instruction is executed by a processor, the steps of the above-mentioned vehicle weight estimation method are implemented.

[0101] The present application also provides a vehicle weight estimation device. Figure 3 A schematic block diagram of a vehicle weight estimation device 100 according to an embodiment of the present application is disclosed. Figure 3 As shown, a vehicle weight estimation device 100 of an embodiment of the present application includes a processor 101, an internal bus 102, a network interface 103, a memory 104 and a non-volatile memory 105, and may also include hardware required for other services. The processor 101 can read the corresponding computer program from the non-volatile memory 105 into the memory 104 and then run it to implement the steps of the vehicle weight estimation method as described above. Of course, in addition to the software implementation, the present application does not exclude other implementation methods, such as logic devices or a combination of software and hardware, etc., that is to say, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic components.

[0102] The vehicle weight estimation device 100 of the present application may have similar beneficial technical effects as the vehicle weight estimation method described above, and therefore, will not be described in detail herein.

[0103] The above is a detailed introduction to the vehicle weight estimation method, device and storage medium provided in the embodiments of the present application. Specific examples are used herein to illustrate the vehicle weight estimation method, device and storage medium of the embodiments of the present application. The description of the above embodiments is only used to help understand the core idea of ​​the present application and is not intended to limit the present application. It should be pointed out that for ordinary technicians in this technical field, without departing from the spirit and principles of the present application, several improvements and modifications can be made to the present application, and these improvements and modifications should also fall within the scope of protection of the claims attached to the present application.

Claims

1. A vehicle weight estimation method, characterized in that: include: Obtain vehicle structural parameters; Acquiring vehicle operation data in a valid stage when the vehicle speed is greater than zero and the driving torque is greater than zero; Obtain the ideal wind resistance coefficient and ideal rolling resistance coefficient of the vehicle during operation; The estimated vehicle weight is estimated according to the vehicle structural parameters, the vehicle operating data, the ideal wind resistance coefficient and the ideal rolling resistance coefficient.

2. The method according to claim 1, characterized in that: Also includes: According to the dynamic equation of vehicle driving, the vehicle energy balance equation in the effective stage is obtained: The estimated vehicle weight is estimated by using the vehicle energy balance equation according to the vehicle structural parameters, the vehicle operating data, the ideal drag coefficient and the ideal rolling resistance coefficient.

3. The method according to claim 2, characterized in that: The vehicle energy balance equation is: A1-A2×C D -A3=m×(A4+A5×f+A6) Wherein, a1, a2, A3, A4, A5, a6 represent the characteristic parameters of the vehicle energy balance equation, C D represents the drag coefficient, f represents the rolling resistance coefficient, and m represents the vehicle weight. In the above formula, n represents the number of sampling cycles; Δt represents the sampling period, in seconds; g represents the acceleration of gravity; The vehicle structural parameters include μ d , A, I f ,I r ,I m 、i g , i0 and r, μ d represents the efficiency of the transmission system; A represents the frontal area, in square meters; I f Represents the moment of inertia of the front wheel, in kilograms per square meter; I r Represents the moment of inertia of the rear wheel, in kilograms per square meter; I m Represents the motor rotor moment of inertia, in kilograms per square meter; i g represents the transmission ratio of the reducer; i0 represents the main reduction ratio; r represents the wheel radius, in meters; The vehicle operation data includes T m,i 、n m,i 、V i , and h i , T m,i Represents the motor drive torque of the i-th sampling period, in Nm; n m,i Represents the speed of the drive motor in the i-th sampling period, in revolutions per minute; V i represents the vehicle speed in the i-th sampling period, in meters per second; represents the acceleration of the ith sampling period, in meters per square meter; h i Represents the vehicle altitude increment in the i-th sampling period, in meters.

4. The method according to any one of claims 1 to 3, characterized in that: The step of obtaining the ideal wind resistance coefficient and the ideal rolling resistance coefficient of the vehicle during operation includes: The ideal wind resistance coefficient and the ideal rolling resistance coefficient of the vehicle during operation are identified based on vehicle test operation data of multiple effective test stages under different loads, and the effective test stage is a stage where the vehicle speed is greater than zero and the driving torque is greater than zero.

5. The method according to claim 4, characterized in that: The step of identifying the ideal wind resistance coefficient and the ideal rolling resistance coefficient of the vehicle during operation according to the vehicle test operation data of multiple effective test stages under different loads includes: A constraint relationship between the drag coefficient and the rolling resistance coefficient is established based on vehicle test operation data of multiple effective test stages under different loads, and an optimization model of the drag coefficient and the rolling resistance coefficient is established to obtain the ideal drag coefficient and the ideal rolling resistance coefficient.

6. The method according to claim 5, characterized in that: The optimization model takes minimizing the sum of the differences between the actual weight of the vehicle and the estimated weight of the vehicle in multiple effective test stages as the optimization goal, and finally identifies the ideal drag coefficient and the ideal rolling resistance coefficient. The optimization goal is: Wherein, Δm represents the sum of the differences between the actual vehicle weight and the estimated vehicle weight in multiple valid stages; i represents the i-th valid test stage; k represents the number of data in the valid test stage; m sj,i Represents the actual weight of the vehicle in the i-th valid test stage; m gj,i Represents the estimated vehicle weight estimated in the i-th valid test stage.

7. The method according to claim 2, characterized in that: The obtaining of vehicle operation data in the effective stage when the vehicle speed is greater than zero and the driving torque is greater than zero comprises: Obtain vehicle operation data under multiple valid stages, Wherein, estimating the vehicle estimated weight by using the vehicle energy balance equation according to the vehicle structural parameters, the vehicle operating data, the ideal wind resistance coefficient and the ideal rolling resistance coefficient includes: Obtaining the estimated vehicle weight at each effective stage through the vehicle energy balance equation according to the vehicle structural parameters, the vehicle operation data at each effective stage, the ideal wind resistance coefficient and the ideal rolling resistance coefficient; The final estimated vehicle weight is obtained based on the estimated vehicle weights at each valid stage.

8. The method according to claim 7, characterized in that: The obtaining of the final estimated vehicle weight based on the vehicle weights at each valid stage includes obtaining the final estimated vehicle weight by one of the following methods: The estimated vehicle weight at each effective stage is weighted according to the corresponding mileage to obtain the final estimated vehicle weight; Taking the middle value of the estimated vehicle weights in each valid stage as the final estimated vehicle weight; The average value of the estimated vehicle weights in each effective stage is taken as the final estimated vehicle weight.

9. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instructions are executed by a processor, the steps of the vehicle weight estimation method according to any one of claims 1 to 8 are implemented.

10. A vehicle weight estimation device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the vehicle weight estimation method according to any one of claims 1 to 8.

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