Vehicle mass estimation method, device, electronic device and readable storage medium

Abstract

The present application relates to the field of new energy vehicles and provides a vehicle mass estimation method, device, electronic device and readable storage medium. The method includes: collecting the vehicle's curb weight, seat sensor information and remaining fuel information, and estimating the vehicle's physical mass based on the curb weight, seat sensor information and remaining fuel information; estimating the vehicle's kinematic mass based on the vehicle's drive torque, vehicle acceleration resistance, vehicle running resistance and vehicle slope resistance; based on the vehicle's current driving stability state, fusing the vehicle's physical mass and vehicle kinematic mass to obtain the vehicle's fused vehicle mass; based on the vehicle's current driving condition, updating the fused vehicle mass and outputting the vehicle's final estimated vehicle mass. The present application can improve the estimation accuracy of the vehicle's vehicle mass, significantly improve the vehicle's kinematic control accuracy, and thus improve the control effect of vehicle stability.

Description

Technical Field

[0001] The present application relates to the field of new energy vehicles, and in particular to a vehicle mass estimation method, device, electronic device and readable storage medium. Background Art

[0002] Vehicle mass (or car mass) is one of the most important fundamental parameters of an automobile and forms the foundation of vehicle kinematics research. The accuracy of vehicle mass estimation directly or indirectly impacts the effectiveness of vehicle stability control during motion. For example, when calculating a vehicle's maximum driving adhesion, the two primary parameters involved are vehicle mass and road adhesion coefficient. Inaccuracies in either vehicle mass or road adhesion coefficient directly impact the accuracy of maximum driving adhesion, and thus the effectiveness of vehicle stability control.

[0003] In related technologies, the curb weight of a vehicle is often used as a reference for estimating vehicle mass. However, in reality, vehicle mass is affected not only by factors such as the number of passengers and the amount of fuel in the tank, but also by the mass of certain components that cannot be directly measured by sensors.

[0004] It can be seen that the existing vehicle mass estimation scheme is easily affected by external interference and has low estimation accuracy, which will directly or indirectly affect the control effect of vehicle stability. Summary of the Invention

[0005] In view of this, the embodiments of the present application provide a vehicle mass estimation method, device, electronic device and readable storage medium to solve the problem that existing vehicle mass estimation solutions are easily affected by external interference and have low estimation accuracy, which directly or indirectly affects the control effect of vehicle stability.

[0006] A first aspect of an embodiment of the present application provides a vehicle mass estimation method, comprising:

[0007] Collecting the vehicle's curb weight, seat sensor information, and remaining fuel information, and estimating the vehicle's overall physical mass based on the curb weight, seat sensor information, and remaining fuel information;

[0008] Estimate the vehicle's kinematic mass based on the vehicle's driving torque, acceleration resistance, running resistance, and slope resistance.

[0009] Based on the current driving stability of the vehicle, the physical mass and kinematic mass of the vehicle are integrated to obtain the fused vehicle mass of the vehicle;

[0010] Based on the vehicle's current driving conditions and the integrated vehicle mass, the final estimated vehicle mass is calculated and output.

[0011] According to a second aspect of the present application, a vehicle mass estimation device is provided, comprising:

[0012] a collection module configured to collect the vehicle's curb weight, seat sensor information, and remaining fuel information, and estimate the vehicle's entire physical mass based on the curb weight, seat sensor information, and remaining fuel information;

[0013] an estimation module configured to estimate a vehicle kinematic mass based on a vehicle driving torque, a vehicle acceleration resistance, a vehicle running resistance, and a vehicle slope resistance;

[0014] a fusion module configured to fuse the physical mass and the kinematic mass of the vehicle based on the current driving stability state of the vehicle to obtain a fused vehicle mass;

[0015] The calculation module is configured to calculate and output the final estimated vehicle mass of the vehicle based on the current driving condition of the vehicle and the integrated vehicle mass.

[0016] According to a third aspect of an embodiment of the present application, an electronic device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.

[0017] According to a fourth aspect of an embodiment of the present application, a readable storage medium is provided, which stores a computer program. When the computer program is executed by a processor, the steps of the above method are implemented.

[0018] Compared with the prior art, the embodiments of the present application have at least the following advantages: on the one hand, based on the vehicle's curb mass, the vehicle's physical mass is estimated by combining the factors with the highest sensitivity to the estimation accuracy of the vehicle's physical mass, namely seat sensor information and remaining fuel information, thereby improving the estimation accuracy of the vehicle's physical mass; on the other hand, the vehicle's kinematic mass is estimated using a vehicle kinematic method, and then the above-mentioned vehicle physical mass and vehicle kinematic mass are integrated with the vehicle's current driving stability to obtain a fused vehicle mass, thereby further improving the estimation accuracy of the vehicle's mass; finally, the final vehicle mass estimate is calculated and output based on the vehicle's current driving condition and the integrated vehicle mass, thereby reducing the impact of external factors such as the vehicle's driving condition on the estimation accuracy of the vehicle mass. In this way, not only can the estimation accuracy of the vehicle's mass be improved, but it can also provide a more reliable and trustworthy source of vehicle mass parameters for other automotive dynamics research, significantly improving the vehicle's kinematic control accuracy, and thus improving the control effect of vehicle stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0020] Figure 1 This is a flow chart of a vehicle mass estimation method provided in an embodiment of the present application;

[0021] Figure 2 This is a schematic structural diagram of a vehicle mass estimation device provided in an embodiment of the present application;

[0022] Figure 3 This is a structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0023] In the following description, specific details such as specific system structures and techniques are provided for purposes of illustration rather than limitation to facilitate a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obscuring the description of the present application with unnecessary detail.

[0024] The automobiles in the embodiments of the present application may be new energy vehicles, which refer to automobiles that use new energy sources (non-traditional oil and diesel energy) and have advanced technology. These automobiles use new power systems that can effectively reduce automobile emissions, reduce environmental impact, and improve energy efficiency. The new energy vehicles in the embodiments of the present application include but are not limited to the following types of vehicles: electric vehicles (EVs), battery electric vehicles (BEVs), fuel cell electric vehicles (FCEVs), plug-in hybrid electric vehicles (PHEVs), and hybrid electric vehicles (HEVs).

[0025] A vehicle mass estimation method and device provided according to an embodiment of the present application will be described in detail below with reference to the accompanying drawings.

[0026] Figure 1 This is a flow chart of a vehicle mass estimation method provided in an embodiment of the present application. Figure 1 The vehicle mass estimation method can be executed by the vehicle controller of a vehicle (such as a new energy vehicle). Figure 1 As shown, the vehicle mass estimation method may specifically include the following steps:

[0027] Step S101 : collecting the vehicle's curb weight, seat sensor information, and remaining fuel information, and estimating the vehicle's overall physical mass based on the curb weight, seat sensor information, and remaining fuel information.

[0028] Curb mass refers to the weight of a car when it is fully equipped according to factory technical conditions (such as spare tire, tools, etc. installed) and filled with all kinds of oil and water. This is an important design indicator of a car.

[0029] Seat sensor information usually refers to the total number of drivers and passengers in the cabin collected by the vehicle's seat sensors.

[0030] The remaining fuel information refers to the percentage of the remaining fuel in the vehicle's fuel tank.

[0031] In some embodiments, an image of the interior of the vehicle cabin may be captured by a camera installed inside the vehicle cabin, and then the image may be analyzed to determine the total number of occupants in the vehicle cabin.

[0032] In some embodiments, images of the interior of the vehicle cabin can be captured by an on-board camera, and pressure signals of the seats in the cabin can be captured by seat sensors. Then, the total number of drivers and passengers in the cabin can be ultimately determined by parallel analysis of the captured images and pressure signals.

[0033] In the embodiment of the present application, the physical mass of the vehicle can be estimated according to the following formula (1).

[0034] m base =m0+65(n-2)-(100%-α)ρV o (1);

[0035] In formula (1), m base represents the vehicle's total physical mass; m0 represents the vehicle's curb weight, which usually includes 100% fuel and the mass of two passengers; n represents the total number of passengers collected by the seat sensors on the vehicle. For ease of calculation, the mass of one passenger is usually assumed to be 65 kg; α represents the percentage of remaining fuel; ρ represents the fuel density (usually 0.737 kg / L for 95-grade gasoline and 0.725 kg / L for 92-grade gasoline), which is used to calculate fuel mass; V o Indicates the fuel tank capacity. For fuel-driven new energy vehicles without fuel tanks, the fuel tank capacity V o The value is 0.

[0036] A vehicle consumes fuel while driving. When the remaining fuel level is lower than a preset fuel level threshold, the vehicle will usually refuel at a nearby gas station along the way. Therefore, the remaining fuel level in the fuel tank is a dynamically changing value.

[0037] The total number of drivers and passengers may also change. For example, the bus may be full, or some passengers may get off during the journey. In other words, the number of drivers and passengers is also a changing value.

[0038] Therefore, the vehicle's remaining fuel level and the total number of drivers and passengers have a significant impact on the vehicle's physical mass. This embodiment of the application improves the accuracy of the vehicle's estimated physical mass by combining the vehicle's curb weight with the two factors most sensitive to the vehicle's physical mass: the weight of the drivers and passengers and the remaining fuel level. This helps improve the accuracy of the final estimated vehicle mass.

[0039] Step S102 , estimating the vehicle kinematic mass based on the vehicle's driving torque, vehicle acceleration resistance, vehicle running resistance, and vehicle slope resistance.

[0040] The equation of motion for a vehicle, also known as the traction balance equation, relates the traction and various resistances to movement when a vehicle is traveling on a road. Traction refers to the force that propels the vehicle. To ensure that the vehicle can travel on the road, the traction must equal the sum of all resistances. These resistances primarily include acceleration resistance, driving resistance, and slope resistance.

[0041] Based on this, the mathematical expression of the vehicle kinematic equation can be obtained as shown in formula (2):

[0042] F d =F a +F f +F i (2);

[0043] In formula (2), F d 、F a 、F f 、F i They respectively represent the vehicle's driving torque, vehicle acceleration resistance, vehicle running resistance and vehicle slope resistance.

[0044] The vehicle driving torque can be calculated according to formula (3):

[0045]

[0046] In formula (3), T m It represents the actual driving torque of the motor; i represents the system transmission ratio, and η represents the system driving efficiency. i and η are generally determined when the vehicle is selected; r represents the wheel radius of the vehicle.

[0047] The vehicle acceleration resistance can be calculated according to formula (4):

[0048]

[0049] In formula (4), v is the actual vehicle speed, and m1 represents the vehicle kinematic mass.

[0050] The vehicle's running resistance represents the sum of the rolling friction resistance and air resistance when the vehicle is traveling on a regular road surface. Because traditional empirical formulas (theoretical values ​​calculated based on factors such as the drag coefficient) often have large errors, the present embodiment combines actual driving conditions with a vehicle's coasting resistance test to obtain relatively accurate fitting numerical data A, B, and C. The vehicle's running resistance is then calculated according to formula (5), which more accurately reflects the vehicle's actual running resistance.

[0051] F f =Cv 2 +Bv+A (5);

[0052] In formula (5), A, B, and C are constants related to the vehicle's running resistance.

[0053] The vehicle's ramp resistance represents the resistance generated by the vehicle overcoming gravity and climbing uphill. The vehicle's ramp resistance can be calculated according to formula (6):

[0054] F i =m1g sinθ (6);

[0055] In formula (6), θ is the estimated road slope and g is the acceleration due to gravity.

[0056] The road slope can be calculated by formula (7):

[0057]

[0058] In formula (7), a M is the longitudinal acceleration of the vehicle measured by the body sensor, g is the acceleration due to gravity, and v′ is the derivative of the actual vehicle speed, which represents the rate of change of the actual vehicle speed.

[0059] Combining the above equations (2) to (7), we can get the vehicle kinematic driving equation shown in the following equation (8):

[0060]

[0061] Furthermore, the kinematic mass m1 of the vehicle based on kinematics can be derived from equation (8), as shown in equation (9):

[0062]

[0063] Step S103 , based on the current driving stability state of the vehicle, the physical mass of the vehicle and the kinematic mass of the vehicle are integrated to obtain the integrated vehicle mass of the vehicle.

[0064] The current driving stability of the vehicle can be represented by the slip rate or slip ratio of each wheel.

[0065] Step S104 , based on the current driving condition of the vehicle and the integrated vehicle mass, calculate and output the final estimated vehicle mass of the vehicle.

[0066] The final estimated vehicle mass refers to the estimated vehicle mass at the current moment.

[0067] The technical solution provided in the embodiments of the present application can not only improve the estimation accuracy of the vehicle's overall mass, but also provide a more reliable and trustworthy source of overall mass parameters for other automotive dynamics research, which can greatly improve the vehicle's kinematic control accuracy, thereby improving the control effect of the vehicle's stability.

[0068] In some embodiments, based on the current driving stability state of the vehicle, the physical mass and the kinematic mass of the vehicle are fused to obtain the fusion and vehicle mass of the vehicle, including:

[0069] Calculating the slip or spin rate of each wheel of the vehicle;

[0070] Determining a current driving stability state of the vehicle based on a slip rate or a slip rate of each wheel of the vehicle, and determining a mass fusion coefficient based on the current driving stability state;

[0071] The physical mass and kinematic mass of the vehicle are fused based on the mass fusion coefficient to obtain the fused vehicle mass.

[0072] Specifically, the slip ratio or the slip rate of each wheel of the vehicle can be calculated according to formula (10).

[0073]

[0074] In formula (10), when S i When it is a positive value, it represents the slip rate of the wheel at position i. i When it is a negative value, it indicates the slip rate of the wheel at position i; Wi is the wheel speed collected by the sensor, i refers to the wheel position, that is, FL (left front wheel) / FR (right front wheel) / RL (left rear wheel) / RR (right rear wheel); v Wi_x It is the equivalent wheel speed of each wheel obtained based on the vehicle body posture and other information.

[0075] Wheel slip is when the distance covered by the vehicle's drive wheels is less than the distance they would have covered if they were rolling. Wheel slip is the ratio of the difference between the vehicle's theoretical speed and its actual speed to the theoretical speed.

[0076] The slip ratio refers to the proportion of sliding components in wheel movement.

[0077] In some embodiments, determining a current driving stability state of the vehicle based on the slip rate or the slip rate of each wheel of the vehicle, and determining a mass fusion coefficient based on the current driving stability state includes:

[0078] Determining a maximum slip ratio or an absolute value of a slip ratio based on the slip ratio or slip ratio of each wheel of the vehicle;

[0079] If the maximum slip ratio or the absolute value of the slip ratio is within a first preset range, the vehicle is currently in a first driving stable state, and the mass fusion coefficient is determined to be a first fusion coefficient, and the first fusion coefficient approaches 0 or is 0;

[0080] If the maximum slip ratio or the absolute value of the slip ratio is within a second preset range, the vehicle is currently in a second driving stable state, and the mass fusion coefficient is determined as a second fusion coefficient, wherein the second fusion coefficient is determined based on the maximum slip ratio or the absolute value of the slip ratio and the slip ratio or slip ratio threshold value;

[0081] If the maximum slip rate or the absolute value of the slip rate is within the third preset range, the vehicle is currently in a third driving stability state, the mass fusion coefficient is determined to be a third fusion coefficient, and the third fusion coefficient approaches 1 or is 1.

[0082] Specifically, the maximum slip ratio or the absolute value of the slip ratio can be determined according to formula (11).

[0083] S=max(|S i |) (11);

[0084] In formula (11), S represents the maximum slip rate or the absolute value of the slip rate, S i Indicates the slip rate or slip ratio of the wheel at the i-th position.

[0085] The mass fusion coefficient of the vehicle under different driving stability states is determined according to formula (12).

[0086]

[0087] In formula (12), Represents the mass fusion coefficient; Th Low Indicates the wheel slip rate or the lower limit of the slip rate, which is generally 5%; Th Hig It is the wheel slip rate or the upper limit of the slip rate, which is generally 10%.

[0088] In the embodiment of the present application, the first preset range is less than Th Low ; The second preset range is [Th Low ,Th Hig ], usually the second preset range is [5%, 10%]; the third preset range is greater than Th Hig .

[0089] When the maximum slip rate or the absolute value of the slip rate of the vehicle is within the first preset range, that is, S<Th Low When , it can be determined that each wheel of the vehicle is in the first stable driving state. In this case, the estimated mass of the whole vehicle is closer to the kinematic mass of the whole vehicle. The value of the mass fusion coefficient is the first fusion coefficient. The first fusion coefficient approaches 0 and can be 0.

[0090] When the maximum slip rate or the absolute value of the slip rate of the vehicle is within the second preset range, that is, S∈[Th Low ,Th Hig ], it can be determined that each wheel of the vehicle is in the second stable driving state. In this case, the value of the mass fusion coefficient is the second fusion coefficient, which can be determined according to the maximum slip rate or the absolute value of the slip rate, the slip rate or the slip rate threshold value, that is,

[0091] When the maximum slip rate or the absolute value of the slip rate of the vehicle is within the third preset range, that is, S>Th Hig When , it can be determined that each wheel of the vehicle is in the third stable driving state. In this case, the estimated mass of the whole vehicle is closer to the physical mass of the whole vehicle. The value of the mass fusion coefficient is the third fusion coefficient. The third fusion coefficient approaches 1 and can be 1.

[0092] The driving stability of a car refers to its ability to maintain normal driving state and direction under the influence of external factors during driving, without losing control and causing slippage, overturning, etc.

[0093] In some embodiments, the physical mass and the kinematic mass of the vehicle are fused based on the mass fusion coefficient to obtain the fused vehicle mass of the vehicle, including:

[0094] Determine a first weight coefficient of the physical mass of the vehicle and a second weight coefficient of the kinematic mass of the vehicle according to the mass fusion coefficient, wherein the sum of the first weight coefficient and the second weight coefficient is 1;

[0095] The fused vehicle mass of the vehicle is calculated according to the physical mass of the vehicle, the kinematic mass of the vehicle, the first weight coefficient and the second weight coefficient.

[0096] Specifically, the fused vehicle mass of the vehicle can be calculated according to formula (13).

[0097]

[0098] In formula (13), m Raw Represents the fused vehicle mass of the vehicle; m base Represents the physical mass of the vehicle; m1 represents the kinematic mass of the vehicle; Represents the mass fusion coefficient.

[0099] From formula (13), we can see that the value of the first weight coefficient in the embodiment of the present application is The value of the second weight coefficient is

[0100] By combining the current driving stability state of the vehicle and integrating the above-mentioned vehicle physical mass and vehicle kinematic mass, it is beneficial to further improve the estimation accuracy of the vehicle's vehicle mass.

[0101] In order to minimize the impact of external factors such as vehicle driving conditions on the vehicle's estimated vehicle mass, the embodiment of the present application further calculates and outputs the final estimated vehicle mass of the vehicle at the current moment based on the vehicle's current driving conditions and integrated vehicle mass.

[0102] In some embodiments, based on the vehicle's current driving condition and the integrated vehicle mass, the final estimated vehicle mass at the current moment is calculated and output, specifically including:

[0103] Obtain the vehicle's estimated mass output value at the previous moment;

[0104] Determine a forgetting factor for the vehicle's estimated mass output value at the previous moment based on the vehicle's current driving condition;

[0105] Based on the forgetting factor and the fused vehicle mass, the final estimated vehicle mass at the current moment is calculated and output.

[0106] The current driving conditions of the vehicle include but are not limited to: ① turning conditions; ② low-speed driving or parking conditions; ③ within a preset period (generally within 10 seconds), the deviation value of the estimated vehicle mass estimated a preset number of times (generally 10 times) is less than a preset threshold value (generally 10kg); for example, within 10 seconds, the deviation value of the estimated vehicle mass estimated 10 times is less than 10kg; ④ the vehicle's brake pedal is valid and is in the depressed state; ⑤ the vehicle's estimated vehicle mass exceeds a preset mass range (generally ±400kg of the curb weight); ⑥ other conditions (conditions other than the above ① to ⑤ conditions).

[0107] In some embodiments, whether the vehicle is in a turning state may be determined based on the vehicle's steering wheel angle and vehicle body yaw rate. Whether the vehicle is in a low-speed driving state may be determined based on the gear position and vehicle speed.

[0108] In some embodiments, determining a forgetting factor for the vehicle's estimated mass output value at a previous moment based on the vehicle's current driving condition specifically includes:

[0109] Determining an update rate for an output value of the vehicle's estimated mass at a previous moment based on the vehicle's current driving condition;

[0110] According to the update rate, a forgetting factor of the vehicle's estimated mass output value at the previous moment is determined.

[0111] Generally speaking, the greater the impact of the vehicle's current driving condition on the estimated vehicle mass, the smaller the update rate of the fused vehicle mass; conversely, the smaller the impact of the vehicle's current driving condition on the estimated vehicle mass, the greater the update rate of the fused vehicle mass.

[0112] As for the above-mentioned working conditions ① to ⑥, the ranking results are as follows: ⑤>④>②>①>⑥>③ according to the impact of each working condition on the estimated vehicle mass; their update rates are ranked from large to small as follows: ⑤<④<②<①<⑥<③.

[0113] As an example, when the vehicle's current driving condition belongs to the above-mentioned first condition, the update rate of the fused vehicle mass is the first slow update, and the forgetting factor is 0.1. When the vehicle's current driving condition belongs to the above-mentioned second condition, the update rate of the fused vehicle mass is the second slow update, and the corresponding forgetting factor is 0.2. When the vehicle's current driving condition belongs to the above-mentioned third condition, the update rate of the fused vehicle mass is the fastest update, and the forgetting factor is 0.01. When the vehicle's current driving condition belongs to the above-mentioned fourth condition, the update rate of the fused vehicle mass is the third slow update, and the forgetting factor is 0.5. When the vehicle's current driving condition belongs to the above-mentioned fifth condition, the update rate of the fused vehicle mass is the slowest update, and the forgetting factor is 1, that is, the estimated vehicle mass is not updated, and the estimated vehicle mass output value of the previous moment (or previous cycle) is directly used. When the vehicle's current driving condition belongs to the sixth condition mentioned above, the update rate of the integrated vehicle mass is medium-high speed, and the forgetting factor is 0.05.

[0114] The smaller the forgetting factor, the faster the update rate of the vehicle's estimated mass; the larger the forgetting factor, the slower the update rate of the vehicle's estimated mass.

[0115] In some embodiments, based on the forgetting factor and the fused vehicle mass, calculating and outputting the final estimated vehicle mass at the current moment includes:

[0116] Based on the forgetting factor, determine the update coefficient corresponding to the fused vehicle mass;

[0117] Based on the forgetting factor, update coefficient, fused vehicle mass and the vehicle's estimated vehicle mass output value at the previous moment, the final estimated vehicle mass of the vehicle at the current moment is calculated and output.

[0118] Specifically, the final estimated vehicle mass at the current moment can be calculated according to formula (14).

[0119] m=m Raw (1-σ fac )+m dly *σ fac (14);

[0120] In formula (14), m represents the final estimated vehicle mass at the current moment, m Raw represents the fused vehicle mass of the vehicle; σ fac represents the forgetting factor; m dly Indicates the estimated vehicle mass output value at the previous moment.

[0121] From formula (14), we can see that the update coefficient corresponding to the integrated vehicle mass is 1-σ fac When σ fac The smaller it is, the larger the update coefficient corresponding to the fusion vehicle mass is; when σ fac The larger it is, the smaller the update coefficient corresponding to the fusion vehicle mass is.

[0122] By combining the vehicle's current driving conditions, the update rate of the estimated vehicle mass and the corresponding forgetting factor are determined. Then, based on the forgetting factor and the fused vehicle mass, the estimated vehicle mass output value at the previous moment is updated in real time. This can reduce the impact of external factors such as the vehicle's driving conditions on the estimation accuracy of the vehicle mass, provide a more reliable and trustworthy source of vehicle mass parameters for other automotive dynamics research, and significantly improve the vehicle's kinematic control accuracy, thereby enhancing the control effect of vehicle stability.

[0123] All of the above optional technical solutions can be combined in any way to form optional embodiments of the present application, and will not be described in detail here.

[0124] The following are device embodiments of the present application, which can be used to implement the method embodiments of the present application. For details not disclosed in the device embodiments of the present application, please refer to the method embodiments of the present application.

[0125] Figure 2 Schematic diagram of a vehicle mass estimation device provided in an embodiment of the present application. Figure 2 As shown, the vehicle mass estimation device includes:

[0126] The acquisition module 201 is configured to acquire the vehicle's curb weight, seat sensor information, and remaining fuel information, and estimate the vehicle's physical mass based on the curb weight, seat sensor information, and remaining fuel information;

[0127] An estimation module 202 is configured to estimate the vehicle kinematic mass based on the vehicle's driving torque, vehicle acceleration resistance, vehicle running resistance, and vehicle slope resistance;

[0128] A fusion module 203 is configured to fuse the physical mass and the kinematic mass of the vehicle based on the current driving stability state of the vehicle to obtain a fused vehicle mass;

[0129] The calculation module 204 is configured to calculate and output the final estimated vehicle mass of the vehicle at the current moment based on the current driving condition of the vehicle and the integrated vehicle mass.

[0130] In some embodiments, the fusion module 203 includes:

[0131] a calculation unit configured to calculate a slip rate or a slip ratio of each wheel of the vehicle;

[0132] a determining unit configured to determine a current driving stability state of the vehicle based on a slip rate or a slip rate of each wheel of the vehicle, and determine a mass fusion coefficient based on the current driving stability state;

[0133] The fusion unit is configured to fuse the physical mass of the vehicle and the kinematic mass of the vehicle based on the mass fusion coefficient to obtain a fused vehicle mass of the vehicle.

[0134] In some embodiments, the determining unit includes:

[0135] a first determining component configured to determine a maximum slip ratio or an absolute value of the slip ratio based on the slip ratio or slip ratio of each wheel of the vehicle;

[0136] The second determining component is configured to determine the mass fusion coefficient as a first fusion coefficient if the maximum slip ratio or the absolute value of the slip ratio is within a first preset range, indicating that the vehicle is currently in a first driving stable state, and the first fusion coefficient is close to 0;

[0137] a third determining component configured to determine, if the maximum slip ratio or the absolute value of the slip ratio is within a second preset range, that the vehicle is currently in a second driving stable state, and to determine the mass fusion coefficient as a second fusion coefficient, wherein the second fusion coefficient is determined based on the maximum slip ratio or the absolute value of the slip ratio and the slip ratio or slip ratio threshold value;

[0138] The third determination component is configured to determine the mass fusion coefficient as a third fusion coefficient if the maximum slip rate or the absolute value of the slip rate is within a third preset range, then the vehicle is currently in a third driving stability state, and the third fusion coefficient is close to 1.

[0139] In some embodiments, the fusion unit comprises:

[0140] a weight determination component configured to determine a first weight coefficient of the physical mass of the entire vehicle and a second weight coefficient of the kinematic mass of the entire vehicle according to the mass fusion coefficient, wherein the sum of the first weight coefficient and the second weight coefficient is 1;

[0141] The mass calculation component is configured to calculate the fused vehicle mass of the vehicle based on the physical mass of the vehicle, the kinematic mass of the vehicle, the first weight coefficient and the second weight coefficient.

[0142] In some embodiments, the calculation module 204 includes:

[0143] an acquiring unit configured to acquire an estimated vehicle mass output value of the vehicle at a previous moment;

[0144] a determination unit configured to determine a forgetting factor for an estimated vehicle mass output value of the vehicle at a previous moment based on a current driving condition of the vehicle;

[0145] The computing unit is configured to calculate and output a final estimated vehicle mass of the vehicle at a current moment based on a forgetting factor and a fused vehicle mass.

[0146] In some embodiments, the determining unit includes:

[0147] A rate determination component configured to determine an update rate of an estimated vehicle mass output value of the vehicle at a previous moment based on a current driving condition of the vehicle;

[0148] The factor determination component is configured to determine a forgetting factor for the vehicle's estimated mass output value at a previous moment according to an update rate.

[0149] In some embodiments, the computing unit includes:

[0150] A coefficient determination component is configured to determine an update coefficient corresponding to the fused vehicle mass based on a forgetting factor;

[0151] The calculation component is configured to calculate and output the final vehicle estimated mass of the vehicle at the current moment based on the forgetting factor, the update coefficient, the fused vehicle mass and the vehicle estimated mass output value at the previous moment.

[0152] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0153] Figure 3 Schematic diagram of the electronic device 3 provided in the embodiment of the present application. Figure 3 As shown, the electronic device 3 of this embodiment includes: a processor 301, a memory 302, and a computer program 303 stored in the memory 302 and executable by the processor 301. When the processor 301 executes the computer program 303, the steps of the above-mentioned method embodiments are implemented. Alternatively, when the processor 301 executes the computer program 303, the functions of the modules / units in the above-mentioned device embodiments are implemented.

[0154] The electronic device 3 may be a desktop computer, a notebook, a PDA, a cloud server or other electronic device. The electronic device 3 may include but is not limited to a processor 301 and a memory 302. Those skilled in the art will understand that Figure 3 This is merely an example of the electronic device 3 and does not limit the electronic device 3 . The electronic device 3 may include more or fewer components than shown in the figure, or different components.

[0155] The processor 301 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0156] The memory 302 can be an internal storage unit of the electronic device 3, such as a hard disk or memory of the electronic device 3. The memory 302 can also be an external storage device of the electronic device 3, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash memory card, etc. equipped on the electronic device 3. The memory 302 can also include both an internal storage unit of the electronic device 3 and an external storage device. The memory 302 is used to store computer programs and other programs and data required by the electronic device.

[0157] Those skilled in the art will clearly understand that for the sake of convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0158] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium (such as a computer-readable storage medium). Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. The computer program may include computer program code, which may be in source code form, object code form, executable file or some intermediate form, etc. Computer-readable storage media may include: any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0159] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A vehicle mass estimation method, characterized in that: include: estimating the vehicle's overall physical mass based on the vehicle's curb mass, seat sensor information, and remaining fuel information; estimating the vehicle kinematic mass based on the vehicle's driving torque, acceleration resistance, running resistance, and slope resistance; determining a maximum slip rate or an absolute value of the slip rate based on the slip rate or the slip rate of each wheel of the vehicle; if the maximum slip rate or the absolute value of the slip rate is less than a lower limit of the slip rate or the slip rate of the wheel, the vehicle is currently in a first driving stable state, and the mass fusion coefficient is determined to be a first fusion coefficient, and the first fusion coefficient is close to 0; The physical mass and kinematic mass of the vehicle are fused based on the mass fusion coefficient to obtain the fused vehicle mass of the vehicle. The calculation formula of the fused vehicle mass of the vehicle is as follows: m Raw Represents the fused vehicle mass of the vehicle; m base Represents the physical mass of the vehicle; m1 represents the kinematic mass of the vehicle; represents the mass fusion coefficient; Based on the current driving condition of the vehicle and the fused vehicle mass, the final estimated vehicle mass of the vehicle at the current moment is calculated and output.

2. The method according to claim 1, characterized in that After determining the maximum slip rate or the absolute value of the slip rate according to the slip rate or the slip rate of each wheel of the vehicle, the method further includes: If the maximum slip ratio or the absolute value of the slip ratio is within a second preset range, the vehicle is currently in a second driving stable state, and the mass fusion coefficient is determined as a second fusion coefficient, wherein the second fusion coefficient is determined according to the maximum slip ratio or the absolute value of the slip ratio and the slip ratio or slip ratio threshold value; If the maximum slip ratio or the absolute value of the slip ratio is within a third preset range, the vehicle is currently in a third driving stability state, the mass fusion coefficient is determined to be a third fusion coefficient, and the third fusion coefficient is close to 1.

3. The method according to claim 1, characterized in that The physical mass of the entire vehicle and the kinematic mass of the entire vehicle are fused based on the mass fusion coefficient to obtain a fused vehicle mass of the vehicle, including: Determining, according to the mass fusion coefficient, a first weight coefficient of the physical mass of the entire vehicle and a second weight coefficient of the kinematic mass of the entire vehicle, wherein the sum of the first weight coefficient and the second weight coefficient is 1; The fused vehicle mass of the vehicle is calculated according to the vehicle physical mass, the vehicle kinematic mass, the first weight coefficient and the second weight coefficient.

4. The method according to claim 1, wherein Calculating and outputting a final estimated vehicle mass of the vehicle at the current moment based on the current driving condition of the vehicle and the fused vehicle mass, including: Obtaining the estimated vehicle mass output value of the vehicle at the previous moment; Determining, based on the current driving condition of the vehicle, a forgetting factor for an estimated vehicle mass output value of the vehicle at a previous moment; Based on the forgetting factor and the fused vehicle mass, a final estimated vehicle mass of the vehicle at the current moment is calculated and output.

5. The method according to claim 4, characterized in that Determining, based on the current driving condition of the vehicle, a forgetting factor for the vehicle's estimated mass output value at a previous moment, including: Determining an update rate for an output value of the vehicle's estimated mass at a previous moment based on a current driving condition of the vehicle; A forgetting factor for the vehicle estimated mass output value at a previous moment is determined according to the update rate.

6. The method according to claim 4, characterized in that Calculating and outputting a final estimated vehicle mass of the vehicle at the current moment based on the forgetting factor and the fused vehicle mass, including: Determining an update coefficient corresponding to the fused vehicle mass based on the forgetting factor; The final estimated vehicle mass of the vehicle at the current moment is calculated and output based on the forgetting factor, the update coefficient, the fused vehicle mass and the estimated vehicle mass output value of the vehicle at the previous moment.

7. A vehicle mass estimation device, characterized in that: include: a collection module configured to estimate the vehicle's physical mass based on the vehicle's curb mass, seat sensor information, and remaining fuel information; an estimating module configured to estimate the vehicle kinematic mass based on the vehicle's driving torque, vehicle acceleration resistance, vehicle running resistance, and vehicle slope resistance; A fusion module is configured to determine a maximum slip rate or an absolute value of a slip rate based on the slip rate or slip rate of each wheel of the vehicle; if the maximum slip rate or the absolute value of the slip rate is less than a lower limit of the slip rate or slip rate of the wheel, the vehicle is currently in a first driving stability state, and the mass fusion coefficient is determined to be a first fusion coefficient, where the first fusion coefficient approaches 0; based on the mass fusion coefficient, the physical mass and the kinematic mass of the vehicle are fused to obtain a fused vehicle mass of the vehicle; wherein the calculation formula of the fused vehicle mass of the vehicle is as follows: m Raw Represents the fused vehicle mass of the vehicle; m base Represents the physical mass of the vehicle; m1 represents the kinematic mass of the vehicle; represents the mass fusion coefficient; The calculation module is configured to calculate and output a final estimated vehicle mass of the vehicle based on the current driving condition of the vehicle and the fused vehicle mass.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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