CN113264056A

CN113264056A - Vehicle weight estimation method, device, vehicle and readable storage medium

Info

Publication number: CN113264056A
Application number: CN202110572477.7A
Authority: CN
Inventors: 罗锐; 吴帅刚; 龙成冰
Original assignee: Sany Automobile Manufacturing Co Ltd
Current assignee: Sany Automobile Manufacturing Co Ltd
Priority date: 2021-05-25
Filing date: 2021-05-25
Publication date: 2021-08-17

Abstract

The invention provides a vehicle weight estimation method, a vehicle weight estimation device, a vehicle and a readable storage medium, wherein the vehicle weight estimation method comprises the following steps: acquiring current state information of a vehicle; recording an acceleration detection value of the vehicle and a ramp angle value of a current driving road of the vehicle under a zero-torque output state of the vehicle based on the current state information; the acceleration detection value and the slope angle value of the current running road of the vehicle are detected information when the vehicle is in a zero-torque output state, so that the influence of a motor torque error on a vehicle weight estimated value is reduced, the accuracy of the estimated vehicle weight information is improved, and the influence of the vehicle weight information estimation precision on the power output and safety system of the vehicle is finally reduced.

Description

Vehicle weight estimation method, device, vehicle and readable storage medium

Technical Field

The invention relates to the technical field of information processing, in particular to a vehicle weight estimation method, a vehicle weight estimation device, a vehicle and a readable storage medium.

Background

The conventional dump truck has a characteristic that a range of variation in the cargo mass is large, and in this characteristic, the cargo mass has a large influence on the power output of the vehicle and the safety system of the vehicle when the dump truck is operating, so that the more accurate the vehicle weight estimation is, the less influence is on the power output and the safety system of the vehicle when the dump truck is running.

The existing vehicle weight estimation has low precision and cannot meet the use requirement at the present stage.

Disclosure of Invention

The present invention is directed to solving at least one of the problems of the prior art or the related art.

To this end, a first aspect of the present invention provides a vehicle weight estimation method.

In a second aspect of the present invention, a vehicle weight estimating apparatus is provided.

A third aspect of the invention provides a vehicle.

A fourth aspect of the present invention is to provide a readable storage medium.

In view of the above, according to a first aspect of the present invention, there is provided a vehicle weight estimation method, including: acquiring current state information of a vehicle; recording an acceleration detection value of the vehicle and a ramp angle value of a current driving road of the vehicle under a zero-torque output state of the vehicle based on the current state information; and inputting the acceleration detection value and the slope angle value into a target dynamic whole vehicle weight estimation algorithm model to obtain vehicle weight information.

The technical scheme of the application provides a vehicle weight estimation method, and the method can be operated to realize the estimation of vehicle weight information, in the process, because the acceleration detection value of the vehicle and the ramp angle value of the current running road of the vehicle are the detection information when the vehicle is in a zero torque output state, the influence of the motor torque error on the vehicle weight estimated value is reduced, the accuracy of the estimated vehicle weight information is improved, and the influence of the vehicle weight information estimation precision on the power output and safety system of the vehicle is finally reduced.

Specifically, the technical scheme of the application is realized by the following steps of specifically obtaining current state information of a vehicle, judging whether the current state information of the vehicle meets a zero-torque output state or not, recording an acceleration detection value of the vehicle and a slope angle value of a current driving road of the vehicle when the vehicle meets the zero-torque output state, and inputting the acceleration detection value and the slope angle value into a target dynamic whole vehicle weight estimation algorithm model so as to obtain vehicle weight information according to the target dynamic whole vehicle weight estimation algorithm model.

The target dynamic whole vehicle weight estimation algorithm model is based on a longitudinal dynamic equation of the vehicle, and is established in the VCU by acquiring acceleration and utilizing a least square method.

Specifically, the formula quoted by the dynamic whole vehicle weight estimation algorithm model is as follows:

on the basis of the formula, when the vehicle is in a zero torque output state, the left value of the equal sign is equal to zero, the formula is deformed to obtain the following formula, namely a target dynamic whole vehicle weight estimation algorithm model:

wherein, T_tqAs motor torque, i_gIs the current gear ratio of the variator, i₀Is the transmission ratio of the reduction mechanism, eta_TFor the mechanical efficiency of the vehicle's driveline, r is the vehicle tire rolling radius, C_DIs an air resistance coefficient, ρ is an air density, v is a running speed of the vehicle, A is a windward area of the vehicle, f₀And f₁Is a speed fitting constant item and a primary item coefficient of a rolling resistance coefficient F, M is vehicle weight information, g is a gravity constant, alpha is a ramp angle value of a current driving road of the vehicle, delta is a rotating mass conversion coefficient,

is the current acceleration of the vehicle.

In the formula, only the ramp angle value and the current acceleration are variables when the same vehicle is in the same speed state, so that one piece of vehicle weight information can be estimated by measuring the parameters.

In addition, the vehicle weight estimation method provided by the technical scheme of the invention also has the following additional technical characteristics:

in the above technical solution, the recording vehicle is in the zero torque output state, and the acceleration detection value of the vehicle further includes: acquiring the running attitude of the vehicle in a zero-torque output state; and recording the acceleration detection value of the vehicle based on the fact that the running posture of the vehicle is in a stable state.

In the technical scheme, the time for recording the acceleration detection value of the vehicle is limited again, specifically, the running posture of the vehicle is obtained so as to judge whether the vehicle is in a stable state or not according to the running posture of the vehicle, and the acceleration detection value of the vehicle is recorded only when the vehicle is in the stable state, so that the influence of the posture change of the vehicle on the obtained acceleration detection value is avoided, and the accuracy of the vehicle weight information estimation is improved.

In any of the above technical solutions, the state where the vehicle is in a moving state, the vehicle is in a non-braking state, and the current gear of the transmission mechanism of the vehicle is neutral under the shift gap, and the output torque is zero is a zero torque output state.

In the technical scheme, the condition that the vehicle is in a zero-torque output state is specifically limited, specifically, the zero-torque output state is a state that the vehicle is in a moving state, the current vehicle is not braked, and the output torque is zero when a speed change mechanism of the vehicle is in a neutral position under a gear shift gap.

In any technical scheme, no jump exists in the components of the acceleration detection value in the height direction and the width direction of the vehicle, and the vehicle is in a stable running attitude state; wherein, the width direction, the height direction and the advancing direction of the vehicle are vertical in pairs.

In the technical scheme, the judgment standard that the vehicle is in the stable running attitude state is specifically limited, so that whether the running attitude of the vehicle is in the stable state or not is judged by acquiring the current state information of the vehicle in an actual use scene, the influence of the attitude change of the vehicle on the acquired acceleration detection value is avoided, and the accuracy of estimating the vehicle weight information is improved.

Specifically, in the technical scheme, whether the vehicle is in the running attitude steady state or not is determined by acquiring the variation condition of the acceleration detection value in the height direction and the width direction of the vehicle, and if the acceleration detection value does not jump in the height direction and the width direction of the vehicle, the vehicle is determined to be in the running attitude steady state.

It is understood that, in the unit time, the increase or decrease of the acceleration detection value corresponding to the component in the height direction of the vehicle exceeds a preset value and/or the increase or decrease of the component in the width direction exceeds a preset value, and it is considered that the jump exists.

In one of the aspects, a fluctuation value between a plurality of detected values of the detected acceleration detected value in a component in the height direction of the vehicle exceeds a preset value and/or a fluctuation value between a plurality of detected values of the detected acceleration detected value in a component in the width direction of the vehicle exceeds a preset value, and a jump is considered to exist.

In any of the above technical solutions, the vehicle weight estimation method further includes: acquiring loading information of a vehicle; and indicating that the vehicle is in an idle load state based on the loading information, and performing parameter correction on the target dynamic whole vehicle weight estimation algorithm model according to the vehicle weight information in the idle load state.

According to the technical scheme, the loading information of the vehicle is obtained, the vehicle weight information in an unloaded state is determined, and the vehicle weight is used for carrying out parameter correction on the target dynamic whole vehicle weight estimation algorithm model, so that the vehicle weight information obtained by estimating the target dynamic whole vehicle weight estimation algorithm model after parameter correction is more accurate.

Specifically, the modified target dynamic vehicle weight estimation algorithm model is expressed as follows:

and F (k) is the current acceleration of the vehicle, wherein F (k) is a vehicle weight correction coefficient, the vehicle weight information in the no-load state corresponds to a k value, and the k value is input to F (k) to obtain the vehicle weight correction coefficient.

In one embodiment, f (k) may be a linear function or a piecewise function.

In the technical scheme, the vehicle weight information in the no-load state is used for correcting the target dynamic whole vehicle weight estimation algorithm model, so that the deviation of factors such as vehicle abrasion and the like to the estimation model is reduced, and the estimation precision of the vehicle weight information is improved.

In any technical scheme, the vehicle is determined to finish one-time unloading treatment according to the loading information, and the vehicle is determined to be in an unloaded state; determining that the vehicle completes one-time loading processing according to the loading information, and determining that the vehicle is in a loading state; the loading information comprises one or more of lifting state of a box body of the vehicle, historical work information of a power take-off switch of the vehicle, historical gear switching information of a speed change mechanism of the vehicle and vehicle speed information of the vehicle.

In the technical scheme, the current state of the vehicle is determined by adopting the method of completing one unloading process or completing one loading process by the vehicle, so that the obtained vehicle weight information in the no-load state is matched with the vehicle weight information in the actual application scene, and the probability of the situation that the vehicle weight information in the no-load state is not matched with the vehicle weight information in the actual application scene is reduced.

In any of the above technical solutions, the method includes the steps of inputting a plurality of acceleration detection values and a plurality of slope angle values to a target dynamic vehicle weight estimation algorithm model to obtain vehicle weight information, and includes: obtaining a plurality of estimated values of vehicle weight information according to the plurality of detected acceleration values and the plurality of slope angle values; and carrying out convergence judgment on the plurality of estimated values of the vehicle weight information to obtain the vehicle weight information.

In the technical scheme, a determination process of the vehicle weight information is specifically limited, a plurality of acceleration detection values and a plurality of slope angle values are obtained and input into a target dynamic vehicle weight estimation algorithm model so as to obtain a plurality of estimated values of the vehicle weight information, and convergence calculation is performed on the plurality of estimated values of the vehicle weight information so as to obtain the vehicle weight information.

In any of the above technical solutions, performing convergence judgment on the plurality of estimated vehicle weight information values to obtain the vehicle weight information specifically includes: carrying out convergence judgment on the plurality of estimated vehicle weight information values to obtain a first converged vehicle weight; and judging the convergence of the first convergence vehicle weights with the preset values based on the fact that the number of the convergence vehicle weights obtained through statistics is larger than or equal to the preset value, so as to obtain vehicle weight information.

In the technical scheme, the vehicle weight information is specifically limited to be obtained based on secondary convergence judgment, and the obtained vehicle weight information can represent the distribution situation of a plurality of first convergence vehicle weights, so that the vehicle weight information obtained by the convergence judgment can reflect the actual vehicle weight information of the vehicle more accurately, and the estimation precision of the vehicle weight information is improved.

In any of the above technical solutions, performing convergence judgment on the plurality of estimated vehicle weight information values to obtain the vehicle weight information specifically includes: carrying out convergence judgment on the estimated value of the vehicle weight information obtained in each first preset time interval to obtain a second convergence vehicle weight; and carrying out convergence judgment on the second convergence vehicle weight in each second preset time interval to obtain vehicle weight information.

In the technical scheme, another scheme of vehicle weight information obtained based on secondary convergence judgment is provided, specifically, the first preset time interval is smaller than the second preset time interval, and the obtained vehicle weight information can represent the distribution situation of a plurality of first converged vehicle weights, so that the vehicle weight information obtained by convergence judgment can reflect the actual vehicle weight information of the vehicle more accurately, and the estimation accuracy of the vehicle weight information is improved.

In any of the above-described aspects, the output vehicle weight information is stored as the latest vehicle weight information based on the deviation of the output vehicle weight information from the vehicle weight information output last time being greater than or equal to 5%, and the vehicle weight information output last time is stored as the latest vehicle weight information when the deviation of the output vehicle weight information from the vehicle weight information output last time being less than 5%.

In any of the above technical solutions, the converged vehicle weight is an average value of the vehicle weight information estimated values within the corresponding convergence time, or is a vehicle weight information estimated value with the highest frequency of occurrence within the corresponding convergence time.

According to a second aspect of the present invention, there is provided a vehicle weight estimation device, comprising: the acquisition module is used for acquiring the current state information of the vehicle; the recording module is used for recording the acceleration detection value of the vehicle when the vehicle is in a zero-torque output state based on the current state information; and the calculation module is used for inputting the acceleration detection value and the slope angle value of the current driving road of the vehicle into the target dynamic whole vehicle weight estimation algorithm model to obtain vehicle weight information.

The technical scheme of the application provides a vehicle weight estimation device, a vehicle provided with the vehicle weight estimation device can realize the estimation of vehicle weight information, and in the process, because the acceleration detection value of the vehicle and the ramp angle value of the current running road of the vehicle are the detection information when the vehicle is in a zero torque output state, the influence of motor torque error on the vehicle weight estimated value is reduced, the accuracy of the estimated vehicle weight information is improved, and the influence of the vehicle weight information estimation precision on the power output and safety system of the vehicle is finally reduced.

on the basis of the formula, when the vehicle is in a zero torque output state, the left value of the equal sign is equal to zero, and the formula is transformed to obtain the following formula:

is the current acceleration of the vehicle.

In any of the above technical solutions, the recording module is further configured to: acquiring the running attitude of the vehicle in a zero-torque output state; and recording the acceleration detection value of the vehicle based on the fact that the running posture of the vehicle is in a stable state.

In any of the above technical solutions, the calculation module is further configured to: acquiring loading information of a vehicle; and indicating that the vehicle is in an idle load state based on the loading information, and performing parameter correction on the target dynamic whole vehicle weight estimation algorithm model according to the vehicle weight information in the idle load state.

is the current acceleration of the vehicle, wherein F (k) is the vehicle weight correction factorAnd (5) the vehicle weight information in the no-load state corresponds to a k value, and the k value is input to F (k) to obtain a vehicle weight correction coefficient.

In one embodiment, f (k) may be a linear function or a piecewise function.

In any of the above technical solutions, the acceleration detection value and the ramp angle value are multiple, and the calculation module is specifically configured to: obtaining a plurality of estimated values of vehicle weight information according to the plurality of detected acceleration values and the plurality of slope angle values; and carrying out convergence judgment on the plurality of estimated values of the vehicle weight information to obtain the vehicle weight information.

In the technical scheme, another scheme of vehicle weight information obtained based on secondary convergence judgment is provided, specifically, the first preset time interval is smaller than the second preset time interval, and the obtained vehicle weight information can represent the distribution situation of a plurality of first converged vehicle weights, so that the vehicle weight information obtained by convergence judgment can reflect the actual vehicle weight information of the vehicle more accurately, and the estimation accuracy of the vehicle weight information is improved. In any of the above-described aspects, the output vehicle weight information is stored as the latest vehicle weight information based on the deviation of the output vehicle weight information from the vehicle weight information output last time being greater than or equal to 5%, and the vehicle weight information output last time is stored as the latest vehicle weight information when the deviation of the output vehicle weight information from the vehicle weight information output last time being less than 5%.

According to a third aspect of the present invention, there is provided a vehicle comprising: a processor; a memory having stored thereon a program or instructions executable on the processor, the program or instructions when executed by the processor implementing the steps of the vehicle weight estimation method according to any one of the first aspect.

According to a fourth aspect of the present invention, there is provided a readable storage medium having stored thereon a program or instructions which, when executed by a processor, performs the steps of the vehicle weight estimation method according to any one of the first aspect

Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.

Drawings

The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:

FIG. 1 illustrates one of the flow diagrams of a vehicle weight estimation method in an embodiment of the invention;

FIG. 2 is a second schematic flow chart of the vehicle weight estimation method according to the embodiment of the invention;

fig. 3 shows a schematic view of the height direction and the width direction of the vehicle in the embodiment of the invention;

FIG. 4 is a third schematic flow chart of a vehicle weight estimation method according to an embodiment of the present invention;

FIG. 5 is a schematic diagram showing connection of respective components of the vehicle at the time of vehicle attitude acquisition in the embodiment of the invention;

FIG. 6 is a schematic flow chart illustrating the process of inputting the detected acceleration value and the slope angle value of the current driving road of the vehicle into the target dynamic vehicle weight estimation algorithm model to obtain the vehicle weight information according to the embodiment of the present invention;

FIG. 7 is a fourth flowchart of a vehicle weight estimation method according to an embodiment of the present invention;

FIG. 8 is a schematic block diagram showing a vehicle weight estimating apparatus in the embodiment of the invention;

fig. 9 shows a schematic block diagram of a vehicle in the embodiment of the invention.

Wherein, the correspondence between the reference numbers and the part names in fig. 8 and 9 is:

800 vehicle weight estimation device, 802 acquisition module, 804 recording module, 806 calculation module, 900 vehicles, 902 processor, 904 memory.

Detailed Description

So that the manner in which the above recited aspects, features and advantages of the present invention can be understood in detail, a more particular description of the invention, briefly summarized above, may be had by reference to the embodiments thereof which are illustrated in the appended drawings. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.

Example one

As shown in fig. 1, according to an embodiment of the present invention, there is provided a vehicle weight estimation method including:

102, acquiring current state information of a vehicle;

104, recording an acceleration detection value of the vehicle and a ramp angle value of a current driving road of the vehicle under a zero-torque output state of the vehicle based on the current state information;

and 106, inputting the acceleration detection value and the slope angle value into a target dynamic whole vehicle weight estimation algorithm model to obtain vehicle weight information.

In the process, because the acceleration detection value of the vehicle and the ramp angle value of the current running road of the vehicle are detection information under the condition that the vehicle is in a zero torque output state, the influence of the motor torque error on the vehicle weight estimated value is reduced, the accuracy of the estimated vehicle weight information is improved, and the influence of the vehicle weight information estimation precision on the power output and the safety system of the vehicle is finally reduced.

Specifically, the embodiment of the application is realized by specifically obtaining current state information of a vehicle, judging whether the current state information of the vehicle meets a zero-torque output state, recording an acceleration detection value of the vehicle and a slope angle value of a current driving road of the vehicle when the vehicle meets the zero-torque output state, and inputting the acceleration detection value and the slope angle value to a target dynamic vehicle weight estimation algorithm model so as to obtain vehicle weight information according to the target dynamic vehicle weight estimation algorithm model.

wherein, T_tqAs motor torque, i_gIs the current gear ratio of the variator, i₀Is the transmission ratio of the reduction mechanism, eta_TFor driving vehiclesMechanical efficiency of the system, r is the rolling radius of the vehicle tyre, C_DIs an air resistance coefficient, ρ is an air density, v is a running speed of the vehicle, A is a windward area of the vehicle, f₀And f₁Is a speed fitting constant item and a primary item coefficient of a rolling resistance coefficient F, M is vehicle weight information, g is a gravity constant, alpha is a ramp angle value of a current driving road of the vehicle, delta is a rotating mass conversion coefficient,

is the current acceleration of the vehicle.

In one embodiment, the ramp angle value may be obtained by mounting an angle sensor.

Example two

In the above embodiment, recording the detected acceleration value of the vehicle in the zero-torque output state of the vehicle, as shown in fig. 2, further includes:

step 202, acquiring the running attitude of the vehicle in a zero-torque output state;

and 204, recording the acceleration detection value of the vehicle based on the fact that the running posture of the vehicle is in a stable state.

In the embodiment, the timing for recording the acceleration detection value of the vehicle is defined again, specifically, the operation posture of the vehicle is obtained so as to judge whether the vehicle is in a steady state or not according to the operation posture of the vehicle, and the acceleration detection value of the vehicle is recorded only when the vehicle is in the steady state, so that the influence of the posture change of the vehicle on the obtained acceleration detection value is avoided, and the accuracy of estimating the vehicle weight information is improved.

EXAMPLE III

In this embodiment, a determination manner of a zero-torque output state is defined, specifically, a state where the output torque is zero when the vehicle is in a moving state, the vehicle is in a non-braking state, and the current gear position of the transmission mechanism of the vehicle is neutral under the shift gap is a zero-torque output state.

In the embodiment, a condition that the vehicle is in a zero-torque output state is specifically defined, specifically, the zero-torque output state is a state that the vehicle is in a moving state, the current vehicle is not braked, and the transmission mechanism of the vehicle is in a neutral position under a shift gap, and the output torque is zero.

Example four

In this embodiment, a determination manner that the vehicle is in the running posture stationary state is defined, and specifically, the vehicle is in the running posture stationary state based on the absence of a jump in the components of the detected acceleration value in the height direction and the width direction of the vehicle; wherein, the width direction, the height direction and the advancing direction of the vehicle are vertical in pairs.

In the embodiment, the determination standard that the vehicle is in the running attitude stationary state is specifically defined, so that in an actual use scene, whether the running attitude of the vehicle is stationary or not is determined by acquiring the current state information of the vehicle, and the influence of the attitude change of the vehicle on the acquired acceleration detection value is avoided, so that the accuracy of estimating the vehicle weight information is improved.

Specifically, as shown in fig. 3, in this embodiment, it is determined whether the vehicle is in the running attitude stationary state by acquiring the variation of the components of the detected acceleration value in the height direction and the width direction of the vehicle, and if there is no jump in the components of the detected acceleration value in the height direction and the width direction of the vehicle, it is determined that the vehicle is in the running attitude stationary state.

In one of the embodiments, a fluctuation value between a plurality of detected values of the detected acceleration detected value in the component in the height direction of the vehicle exceeds a preset value and/or a fluctuation value between a plurality of detected values of the detected acceleration detected value in the component in the width direction of the vehicle exceeds a preset value, and a jump is considered to exist.

EXAMPLE five

In any of the above embodiments, as shown in fig. 4, the vehicle weight estimation method further includes:

step 402, acquiring loading information of a vehicle;

and step 404, indicating that the vehicle is in an unloaded state based on the loading information, and performing parameter correction on the target dynamic whole vehicle weight estimation algorithm model according to the vehicle weight information in the unloaded state.

In the embodiment, the loading information of the vehicle is obtained, the vehicle weight information in the no-load state is determined, and the vehicle weight is used for carrying out parameter correction on the target dynamic whole vehicle weight estimation algorithm model, so that the vehicle weight information obtained by estimating the target dynamic whole vehicle weight estimation algorithm model after parameter correction is more accurate.

wherein, T_tqAs motor torque, i_gIs the current gear ratio of the variator, i₀Is the transmission ratio of the reduction mechanism, eta_TFor the mechanical efficiency of the vehicle's driveline, r is the vehicle tire rolling radius, C_DIs an air resistance coefficient, ρ is an air density, v is a running speed of the vehicle, A is a windward area of the vehicle, f₀And f₁Is a velocity fitting constant term and a first order term coefficient of a rolling resistance coefficient F, M is vehicle weight information,g is a gravity constant, alpha is a ramp angle value of a current driving road of the vehicle, delta is a rotating mass conversion coefficient,

In one embodiment, f (k) may be a linear function or a piecewise function.

In the embodiment, the vehicle weight information in the no-load state is used for correcting the target dynamic whole vehicle weight estimation algorithm model, so that the deviation of factors such as vehicle abrasion and the like to the estimation model is reduced, and the estimation precision of the vehicle weight information is improved.

In any of the above embodiments, it is determined that the vehicle completes one unloading process according to the loading information, and the vehicle is determined to be in an unloaded state; determining that the vehicle completes one-time loading processing according to the loading information, and determining that the vehicle is in a loading state; the loading information comprises one or more of lifting state of a box body of the vehicle, historical work information of a power take-off switch of the vehicle, historical gear switching information of a speed change mechanism of the vehicle and vehicle speed information of the vehicle.

In this embodiment, the current state of the vehicle is determined by completing one unloading process or completing one loading process by the vehicle, so as to ensure that the obtained vehicle weight information in the no-load state matches with the vehicle weight information in the actual application scene, and reduce the probability that the vehicle weight information in the no-load state does not match with the vehicle weight information in the actual application scene.

As shown in fig. 5, the vehicle meter, the acceleration sensor and the shift handle are connected to the VCU through the CAN, and the power take-off switch, the lifting state and the brake signal are transmitted to the VCU through the electrical connection, wherein the VCU is an electric control system of the pure electric vehicle.

EXAMPLE six

In any of the above embodiments, the acceleration detection value and the slope angle value are multiple, and the acceleration detection value and the slope angle value of the current driving road of the vehicle are input to the target dynamic vehicle weight estimation algorithm model to obtain the vehicle weight information, as shown in fig. 6, specifically including:

step 602, obtaining a plurality of estimated values of vehicle weight information according to a plurality of detected acceleration values and a plurality of slope angle values;

step 604, performing convergence judgment on the plurality of estimated vehicle weight information values to obtain the vehicle weight information.

In the embodiment, a determination process of the vehicle weight information is specifically defined, in the embodiment of the application, a plurality of acceleration detection values and a plurality of slope angle values are obtained and input to a target dynamic vehicle weight estimation algorithm model so as to obtain a plurality of vehicle weight information estimation values, and convergence calculation is performed on the plurality of vehicle weight information estimation values so as to obtain the vehicle weight information.

In any of the above embodiments, performing convergence determination on the plurality of estimated vehicle weight information values to obtain the vehicle weight information specifically includes: carrying out convergence judgment on the plurality of estimated vehicle weight information values to obtain a first converged vehicle weight; and judging the convergence of the first convergence vehicle weights with the preset values based on the fact that the number of the convergence vehicle weights obtained through statistics is larger than or equal to the preset value, so as to obtain vehicle weight information.

In this embodiment, it is specifically limited that the vehicle weight information is obtained based on the secondary convergence determination, and the obtained vehicle weight information can represent the distribution of a plurality of first converged vehicle weights, so that the vehicle weight information obtained by the convergence determination can reflect the actual vehicle weight information of the vehicle more accurately, and the estimation accuracy of the vehicle weight information is improved.

In any of the above embodiments, performing convergence determination on the plurality of estimated vehicle weight information values to obtain the vehicle weight information specifically includes: carrying out convergence judgment on the estimated value of the vehicle weight information obtained in each first preset time interval to obtain a second convergence vehicle weight; and carrying out convergence judgment on the second convergence vehicle weight in each second preset time interval to obtain vehicle weight information.

In this embodiment, another scheme of obtaining the vehicle weight information based on the secondary convergence judgment is provided, specifically, the first preset time interval is smaller than the second preset time interval, and the obtained vehicle weight information can represent the distribution situation of a plurality of first converged vehicle weights, so that the vehicle weight information obtained by the convergence judgment can reflect the actual vehicle weight information of the vehicle more accurately, and the estimation accuracy of the vehicle weight information is improved.

In any of the embodiments described above, the output vehicle weight information is stored as the latest vehicle weight information based on the deviation of the output vehicle weight information from the vehicle weight information output last time being greater than or equal to 5%, and the vehicle weight information output last time is stored as the latest vehicle weight information when the deviation of the output vehicle weight information from the vehicle weight information output last time being less than 5%.

In one embodiment, the converged vehicle weight is an average value of the vehicle weight information estimated values within the corresponding convergence time or an estimated value of the vehicle weight information with the highest frequency of occurrence within the corresponding convergence time.

DETAILED DESCRIPTION OF EMBODIMENT (S) OF INVENTION

As shown in fig. 7, the vehicle weight estimation method includes:

step 702, controlling the vehicle to move at the speed of more than 5 km/h;

step 704, outputting zero torque at the gear shifting clearance and the speed change mechanism;

step 706, identifying the stable state of the vehicle running posture;

step 708, judging whether the vehicle running posture is stable, if so, executing step 710, and if not, executing step 708;

step 710, inputting the target dynamic vehicle weight estimation algorithm model;

step 712, performing parameter correction on the target dynamic whole vehicle weight estimation algorithm model;

and step 714, outputting the vehicle weight information.

The vehicle weight estimation method further comprises the following steps: and (3) recognizing the loading state of the whole vehicle: the vehicle control unit establishes an algorithm model in the vehicle control unit by acquiring vehicle speed information of an instrument, opening and closing state information of a top cover of the upper-mounted controller, D/R gear switching information of a gear shifting handle, a power take-off switch and lifting state information, considers that the vehicle is in an idle-load state when the vehicle finishes a primary unloading working condition, and considers that the vehicle is in a loading state when the vehicle finishes a primary loading working condition.

Zero torque output state identification: when the vehicle speed is more than 5km/h (can be set according to actual use scenes), the whole vehicle is not mechanically braked, the speed change mechanism is in a gear shifting process, the driving motor needs to quit the current gear, is switched to a neutral gear to regulate the speed, then enters a target gear, and is in a zero-torque output state when the motor controls no torque to output to the whole vehicle in the neutral gear switching process.

And (3) identifying the running posture of the whole vehicle: the vehicle control unit establishes a vehicle running attitude model based on information such as vehicle vertical and width direction acceleration and vehicle speed by collecting acceleration sensor messages, and considers that the vehicle running attitude is stable when the vehicle does not jump vertically and width direction during running.

Estimating the vehicle weight of the whole vehicle: the vehicle weight estimation model is built in the vehicle controller based on a vehicle longitudinal dynamics formula, and different vehicle weight estimation data need to be collected in the model building process to correct the vehicle weight estimation model. After the vehicle runs, after the VCU recognizes that the vehicle speed is greater than 5km/h and the vehicle enters a zero-torque state, the VCU starts to calculate the vehicle weight, the gear shifting gap is about 1.5s, the VCU performs convergence processing on all calculated vehicle weights (M1, M2 and M3 … … Mn) once in each gear shifting process to obtain the vehicle weight Mn, the VCU performs convergence processing on the converged vehicle weights (M1, M2 and M3 … … Mn) obtained by the gear shifting gap again to obtain the final estimated vehicle weight M, if the calculated vehicle weight deviation is less than 5%, the output estimated vehicle weight is not modified, and if not, the latest estimated vehicle weight is output. When a Vehicle Controller Unit (VCU) identifies that the vehicle is in an idle load state, the vehicle weight estimation model needs to be corrected by using the 'idle load' vehicle weight, and the accuracy of vehicle weight estimation is ensured.

In the embodiment, the VCU establishes the vehicle load state model based on the CAN bus information of the whole vehicle, does not need to increase extra cost, realizes the estimation of the vehicle weight based on the control of the whole vehicle and software, and identifies the load state.

EXAMPLE seven

As shown in fig. 8, the present invention provides a vehicle weight estimation device 800 including: an obtaining module 802, configured to obtain current state information of a vehicle; the recording module 804 is used for recording the acceleration detection value of the vehicle when the vehicle is in a zero-torque output state based on the current state information; and the calculating module 806 is configured to input the acceleration detection value and the slope angle value of the current driving road of the vehicle into the target dynamic vehicle weight estimation algorithm model to obtain vehicle weight information.

The embodiment of the application provides a vehicle weight estimation device 800, and a vehicle provided with the vehicle weight estimation device 800 can realize estimation of vehicle weight information, in the process, because an acceleration detection value of the vehicle and a ramp angle value of a current driving road of the vehicle are detection information under a zero torque output state of the vehicle, the influence of a motor torque error on a vehicle weight estimated value is reduced, the accuracy of the estimated vehicle weight information is improved, and the influence of the vehicle weight information estimation precision on the power output and safety system of the vehicle is finally reduced.

In one embodiment, the recording module 804 is further configured to obtain an operation posture of the vehicle when the vehicle is in a zero-torque output state; and recording the acceleration detection value of the vehicle based on the fact that the running posture of the vehicle is in a stable state.

In one embodiment, the vehicle is in a zero torque output state based on the vehicle being in motion, the vehicle being in a no-brake state, and the current gear of the vehicle's transmission being neutral with a shift gap.

In one embodiment, the vehicle is in a running attitude stationary state based on the absence of a jump in the components of the detected acceleration value in the height direction and the width direction of the vehicle; the width direction is a direction perpendicular to both the height direction and the traveling direction of the vehicle.

In one embodiment, the calculation module 806 is further configured to obtain loading information of the vehicle; and indicating that the vehicle is in an idle load state based on the loading information, and performing parameter correction on the target dynamic whole vehicle weight estimation algorithm model according to the vehicle weight information in the idle load state.

In one embodiment, the vehicle is determined to finish a discharging process according to the loading information, and the vehicle is determined to be in an unloaded state; determining that the vehicle completes one-time loading processing according to the loading information, and determining that the vehicle is in a loading state; the loading information comprises one or more of lifting state of a box body of the vehicle, historical work information of a power take-off switch of the vehicle, historical gear switching information of a speed change mechanism of the vehicle and vehicle speed information of the vehicle.

In one embodiment, the acceleration detection value and the slope angle value are multiple, and the calculating module 806 is configured to obtain multiple estimated values of the vehicle weight information according to the multiple acceleration detection values and the multiple slope angle values; carrying out convergence judgment on the estimated values of the vehicle weight information to obtain a converged vehicle weight; and based on the fact that the number of the converged vehicle weights obtained through statistics is larger than or equal to a preset value, convergence judgment is conducted on the converged vehicle weights of the preset value, and vehicle weight information is obtained.

In any of the above embodiments, the recording module 804 is further configured to: acquiring the running attitude of the vehicle in a zero-torque output state; and recording the acceleration detection value of the vehicle based on the fact that the running posture of the vehicle is in a stable state.

In any of the embodiments described above, the state where the output torque is zero when the vehicle is in a moving state, the vehicle is in a non-braking state, and the current gear position of the transmission mechanism of the vehicle is neutral under the shift gap is a zero-torque output state.

In any of the above embodiments, the vehicle is in the running attitude stationary state based on the absence of a jump in the components of the detected acceleration value in the height direction and the width direction of the vehicle; wherein, the width direction, the height direction and the advancing direction of the vehicle are vertical in pairs.

Specifically, in this embodiment, it is determined whether the vehicle is in the running attitude stationary state by acquiring the variation of the acceleration detection value in the height direction and width direction components of the vehicle, and if there is no jump in the acceleration detection value in the height direction and width direction components of the vehicle, it is determined that the vehicle is in the running attitude stationary state.

In any of the above embodiments, the calculation module 806 is further configured to: acquiring loading information of a vehicle; and indicating that the vehicle is in an idle load state based on the loading information, and performing parameter correction on the target dynamic whole vehicle weight estimation algorithm model according to the vehicle weight information in the idle load state.

wherein, T_tqAs motor torque, i_gIs the current gear ratio of the variator, i₀Is the transmission ratio of the reduction mechanism, eta_TFor the mechanical efficiency of the vehicle's driveline, r is the vehicle tire rolling radius, C_DIs the coefficient of air resistance, and ρ is the air densityV is the running speed of the vehicle, A is the frontal area of the vehicle, f₀And f₁Is a speed fitting constant item and a primary item coefficient of a rolling resistance coefficient F, M is vehicle weight information, g is a gravity constant, alpha is a ramp angle value of a current driving road of the vehicle, delta is a rotating mass conversion coefficient,

In one embodiment, f (k) may be a linear function or a piecewise function.

In any of the above embodiments, the acceleration detection value and the ramp angle value are multiple, and the calculating module 806 is specifically configured to: obtaining a plurality of estimated values of vehicle weight information according to the plurality of detected acceleration values and the plurality of slope angle values; and carrying out convergence judgment on the plurality of estimated values of the vehicle weight information to obtain the vehicle weight information.

In any of the above embodiments, the converged vehicle weight is an average value of the vehicle weight information estimated values within the corresponding convergence time, or is a vehicle weight information estimated value with the highest frequency of occurrence within the corresponding convergence time.

Example eight

In one embodiment, as shown in fig. 9, a vehicle 900 is proposed, comprising: a processor 902; a memory 904, the memory 904 having stored thereon programs or instructions executable on the processor 902, the programs or instructions when executed by the processor 902 implementing the steps of the vehicle weight estimation method as in any one of the above.

In this embodiment, a vehicle 900 is proposed, where the vehicle 900 includes, for example, a processor 902 and a memory 904, where the processor 902 executes a program or an instruction stored in the memory 904 to implement the vehicle weight estimation method according to any one of the foregoing descriptions, and therefore, the vehicle 900 has all the beneficial technical effects of the vehicle weight estimation method according to any one of the foregoing descriptions, and details are not repeated herein.

Example nine

In one embodiment, a readable storage medium is provided, on which a program or instructions are stored, which when executed by a processor implement the steps of the vehicle weight estimation method as in any one of the above.

When the program or the instructions stored on the readable storage medium provided by the present invention is executed, the steps of the vehicle weight estimation method according to any one of the above embodiments can be implemented, and therefore, the readable storage medium has all the beneficial technical effects of the vehicle weight estimation method according to any one of the above embodiments, and the detailed description thereof is omitted here.

In the description of the present invention, the terms "plurality" or "a plurality" refer to two or more, and unless otherwise specifically limited, the terms "upper", "lower", and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are merely for convenience in describing the present invention and simplifying the description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus should not be construed as limiting the present invention; the terms "connected," "mounted," "secured," and the like are to be construed broadly and include, for example, fixed connections, removable connections, or integral connections; may be directly connected or indirectly connected through an intermediate. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.

In the description of the present invention, the description of the terms "one embodiment," "some embodiments," "specific embodiments," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In the present invention, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes will occur to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A vehicle weight estimation method, comprising:

acquiring current state information of a vehicle;

recording an acceleration detection value of the vehicle and a ramp angle value of a current driving road of the vehicle when the vehicle is in a zero-torque output state based on the current state information;

and inputting the acceleration detection value and the slope angle value into a target dynamic whole vehicle weight estimation algorithm model to obtain vehicle weight information.

2. The vehicle weight estimation method according to claim 1, wherein the recording of the detected value of the acceleration of the vehicle in a zero-torque output state of the vehicle further comprises:

acquiring the running attitude of the vehicle when the vehicle is in a zero-torque output state;

and recording an acceleration detection value of the vehicle based on the fact that the running posture of the vehicle is in a stable state.

3. The vehicle weight estimation method according to claim 1,

the vehicle is in a motion state, the vehicle is in a non-braking state, and the state that the output torque is zero is the zero-torque output state when the current gear of the speed change mechanism of the vehicle is neutral under the shift gap.

4. The vehicle weight estimation method according to claim 2,

based on the fact that the components of the acceleration detection value in the height direction and the width direction of the vehicle do not jump, the vehicle is in a running attitude stable state;

wherein the width direction, the height direction and the traveling direction of the vehicle are perpendicular to each other.

5. The vehicle weight estimation method according to any one of claims 1 to 4, characterized by further comprising:

acquiring loading information of the vehicle;

and indicating that the vehicle is in an idle load state based on the loading information, and performing parameter correction on the target dynamic whole vehicle weight estimation algorithm model according to the vehicle weight information in the idle load state.

6. The vehicle weight estimation method according to claim 5, wherein the modified target dynamic vehicle weight estimation algorithm model is expressed as follows:

7. The vehicle weight estimation method according to claim 5,

determining that the vehicle completes one unloading process according to the loading information, and determining that the vehicle is in an unloaded state;

determining that the vehicle completes one-time loading processing according to the loading information, and determining that the vehicle is in a loading state;

wherein the loading information includes one or more of a lifting state of a box body of the vehicle, historical operating information of a power take-off switch of the vehicle, historical gear shift switching information of a transmission mechanism of the vehicle, and vehicle speed information of the vehicle.

8. The vehicle weight estimation method according to any one of claims 1 to 4, wherein the detected acceleration value and the slope angle value are plural, and the inputting of the detected acceleration value and the slope angle value of the current driving road of the vehicle into the target dynamic vehicle weight estimation algorithm model to obtain the vehicle weight information specifically comprises:

obtaining a plurality of estimated values of vehicle weight information according to the plurality of detected acceleration values and the plurality of ramp angle values;

and carrying out convergence judgment on the plurality of estimated values of the vehicle weight information to obtain the vehicle weight information.

9. The vehicle weight estimation method according to claim 8, wherein the performing convergence determination on the plurality of estimated vehicle weight information values to obtain the vehicle weight information specifically includes:

carrying out convergence judgment on the plurality of estimated vehicle weight information values to obtain a first converged vehicle weight;

and judging the convergence of the first convergence vehicle weights with preset values based on the fact that the number of the convergence vehicle weights obtained through statistics is larger than or equal to the preset values, so as to obtain the vehicle weight information.

10. The vehicle weight estimation method according to claim 8, wherein the performing convergence determination on the plurality of estimated vehicle weight information values to obtain the vehicle weight information specifically includes:

carrying out convergence judgment on the estimated value of the vehicle weight information obtained in each first preset time interval to obtain a second convergence vehicle weight;

and carrying out convergence judgment on the second convergence vehicle weight in each second preset time interval to obtain the vehicle weight information.

11. The vehicle weight estimation method according to claim 8, wherein the converged vehicle weight is an average value of the vehicle weight information estimates within a corresponding convergence time thereof, or is the vehicle weight information estimate having a highest frequency of occurrence within the corresponding convergence time thereof.

12. A vehicle weight estimation device, characterized by comprising:

the acquisition module is used for acquiring the current state information of the vehicle;

the recording module is used for recording an acceleration detection value of the vehicle when the vehicle is in a zero-torque output state based on the current state information;

and the calculation module is used for inputting the acceleration detection value and the slope angle value of the current running road of the vehicle into a target dynamic whole vehicle weight estimation algorithm model to obtain vehicle weight information.

13. The vehicle weight estimation device according to claim 12, wherein the recording module is further configured to:

14. The vehicle weight estimation device according to claim 12, wherein a state in which the output torque is zero when the vehicle is in a moving state, the vehicle is in a non-braking state, and a current gear position of a transmission mechanism of the vehicle is neutral under a shift gap is the zero-torque output state.

15. The vehicle weight estimation device according to claim 13, wherein the vehicle is in a running attitude stationary state based on absence of a jump in components of the acceleration detection value in a height direction and a width direction of the vehicle;

16. The vehicle weight estimation device according to any one of claims 12 to 15, wherein the calculation module is further configured to:

acquiring loading information of the vehicle;

17. The vehicle weight estimation device according to claim 16, wherein the modified model of the target dynamic vehicle weight estimation algorithm is expressed as follows:

wherein, T_tqAs motor torque, i_gIs the current gear ratio of the variator, i₀Is the transmission ratio of the reduction mechanism, eta_TFor the mechanical efficiency of the vehicle's driveline, r is the vehicle tire rolling radius, C_DIs an air resistance coefficient, ρ is an air density, v is a running speed of the vehicle, A is a windward area of the vehicle, f₀And f₁Is a speed fitting constant term and a primary term coefficient of a rolling resistance coefficient F, M is vehicle weight information, g is a gravity constant, alpha is a ramp angle value of a current driving road of the vehicle, and delta is a rotating mass conversion coefficient

18. The vehicle weight estimation device according to claim 16,

19. The vehicle weight estimation device according to any one of claims 12 to 15, wherein the detected acceleration value and the ramp angle value are plural, and the calculation module is specifically configured to:

20. The vehicle weight estimation device according to claim 19, wherein the calculation module is specifically configured to:

21. The vehicle weight estimation device according to claim 19, wherein the calculation module is specifically configured to:

22. The vehicle weight estimation device according to claim 19, wherein the converged vehicle weight is an average value of the vehicle weight information estimates within its corresponding convergence time or is the vehicle weight information estimate having a highest frequency of occurrence within its corresponding convergence time.

23. A vehicle, characterized by comprising:

a processor;

a memory having stored thereon a program or instructions executable on the processor, the program or instructions when executed by the processor implementing the steps of the vehicle weight estimation method according to any one of claims 1 to 11.

24. A readable storage medium on which a program or instructions are stored, the program or instructions, when executed by a processor, implementing the steps of the vehicle weight estimation method according to any one of claims 1 to 11.