CN111717214A - Vehicle mass estimation method and device, electronic equipment and storage medium - Google Patents

Vehicle mass estimation method and device, electronic equipment and storage medium Download PDF

Info

Publication number
CN111717214A
CN111717214A CN201910223240.0A CN201910223240A CN111717214A CN 111717214 A CN111717214 A CN 111717214A CN 201910223240 A CN201910223240 A CN 201910223240A CN 111717214 A CN111717214 A CN 111717214A
Authority
CN
China
Prior art keywords
current
vehicle
determining
mass estimation
mass
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201910223240.0A
Other languages
Chinese (zh)
Other versions
CN111717214B (en
Inventor
陶晓
谭志红
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Changsha Intelligent Driving Research Institute Co Ltd
Original Assignee
Changsha Intelligent Driving Research Institute Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Changsha Intelligent Driving Research Institute Co Ltd filed Critical Changsha Intelligent Driving Research Institute Co Ltd
Priority to CN201910223240.0A priority Critical patent/CN111717214B/en
Publication of CN111717214A publication Critical patent/CN111717214A/en
Application granted granted Critical
Publication of CN111717214B publication Critical patent/CN111717214B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/12—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to parameters of the vehicle itself, e.g. tyre models
    • B60W40/13—Load or weight
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2510/00—Input parameters relating to a particular sub-units
    • B60W2510/06—Combustion engines, Gas turbines
    • B60W2510/0657—Engine torque
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2510/00—Input parameters relating to a particular sub-units
    • B60W2510/10—Change speed gearings
    • B60W2510/1005—Transmission ratio engaged
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/10—Longitudinal speed
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2540/00—Input parameters relating to occupants
    • B60W2540/10—Accelerator pedal position
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2540/00—Input parameters relating to occupants
    • B60W2540/12—Brake pedal position

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Mathematical Physics (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Control Of Transmission Device (AREA)
  • Control Of Driving Devices And Active Controlling Of Vehicle (AREA)

Abstract

The application relates to a vehicle mass estimation method, a vehicle mass estimation device, electronic equipment and a storage medium. The method comprises the following steps: acquiring current running state information of a vehicle, wherein the current running state information of the vehicle comprises: current vehicle speed, current accelerator pedal opening, current brake pedal opening and current gradient; when the condition that the vehicle mass estimation preset triggering condition is met is determined based on the current running state information of the vehicle, obtaining current running parameters of the vehicle; and determining the current finished vehicle mass estimation value according to the current running parameters of the vehicle. By adopting the method, the error of the estimation of the mass of the whole vehicle can be reduced.

Description

Vehicle mass estimation method and device, electronic equipment and storage medium
Technical Field
The present application relates to the field of vehicle technologies, and in particular, to a method and an apparatus for estimating a vehicle mass, an electronic device, and a storage medium.
Background
The mass of the whole vehicle is an important parameter for vehicle operation, and if the mass of the whole vehicle cannot be determined in the running process of the vehicle, the control accuracy of the driving force or the braking force of the whole vehicle is poor, and the safety problem of the vehicle is easily caused. However, the error of the existing vehicle mass estimation method is larger.
Disclosure of Invention
In view of the above, it is necessary to provide a vehicle mass estimation method, apparatus, electronic device and storage medium for solving the above technical problems.
A vehicle mass estimation method comprises the following steps:
acquiring current running state information of a vehicle, wherein the current running state information of the vehicle comprises: current vehicle speed, current accelerator pedal opening, current brake pedal opening and current gradient;
when the condition that the vehicle mass estimation preset triggering condition is met is determined based on the current vehicle running state information, obtaining current vehicle running parameters;
and determining the current finished vehicle mass estimation value according to the current driving parameters of the vehicle.
In one embodiment, when the current vehicle speed is not 0, the current accelerator pedal opening and the current brake pedal opening are both 0, and the variation of the current gradient in a preset time period is within a preset variation range, it is determined that a preset trigger condition for estimating the whole vehicle mass is met.
In one embodiment, after determining the current estimated vehicle quality according to the current driving parameters of the vehicle, the method further comprises the following steps: and determining the validity of the current finished automobile mass estimation value based on the relative error between the current finished automobile mass estimation value and the current finished automobile mass effective value.
In one embodiment, if the relative error between the current vehicle mass estimation value and the current vehicle mass effective value is smaller than a first preset relative error, it is determined that the current vehicle mass estimation value is invalid.
In one embodiment, if the relative error between the current vehicle mass estimation value and the current vehicle mass effective value is greater than or equal to the first preset relative error, it is determined that the current vehicle mass estimation value is effective.
In one embodiment, after determining that the current vehicle mass estimation value is valid, the method further includes:
if the continuously determined finished automobile mass estimation values of the preset times are all effective, calculating the relative error between the finished automobile mass estimation values of the preset times;
and if the relative error between the vehicle mass estimation values of the preset times is smaller than a second preset relative error, replacing the current vehicle mass effective value with the average value of the vehicle mass estimation values of the preset times.
In one embodiment, the relative error between the vehicle mass estimation values of the preset times includes: and in the vehicle mass estimation values of the preset times, the relative error between any two adjacent vehicle mass estimation values.
In one embodiment, determining the current estimated vehicle quality according to the current driving parameters of the vehicle comprises: and determining the current finished vehicle mass estimation value according to the current driving parameters of the vehicle on the basis that the finished vehicle output force is equal to 0.
In one embodiment, the current vehicle driving parameters include a current engine torque, a current vehicle speed, a current grade, and a current gear of the vehicle.
In one embodiment, the determining a current finished vehicle mass estimation value according to the current driving parameter of the vehicle based on the fact that the finished vehicle output force is equal to 0 includes:
determining air resistance based on the current vehicle speed and the windward area;
determining a current gear ratio of the gearbox based on the current gear, and determining engine resistance based on the current gear ratio of the gearbox, the current torque of the engine and a reduction gear ratio of a speed reducer;
determining a rolling resistance coefficient based on the current vehicle speed and a rolling resistance factor based on the rolling resistance coefficient and the current grade;
determining a ramp resistance factor based on the current grade;
determining a current acceleration based on the variation of the current vehicle speed divided by the corresponding time variation, and determining an acceleration resistance factor based on the current acceleration and a rotating mass conversion coefficient;
determining the current gross vehicle mass estimate based on the air resistance, the engine resistance, the rolling resistance factor, the ramp resistance factor, and the acceleration resistance factor.
In one embodiment, the air resistance is a quotient obtained by dividing a first product by a predetermined constant, and the first product is a product of an air resistance coefficient, the frontal area, and a square value of the current vehicle speed.
In one embodiment, the engine resistance is a quotient of a second product divided by a wheel radius, the second product being a product of the current engine torque, the current transmission gear ratio of the transmission, and the reduction gear ratio of the retarder.
In one embodiment, the rolling resistance factor is a product of the gravitational acceleration, the rolling resistance coefficient, and a cosine of the slope angle corresponding to the current slope.
In one embodiment, the ramp resistance factor is a product of gravitational acceleration and a sine of the current slope corresponding to the slope angle.
In one embodiment, the acceleration resistance factor is a product of the current acceleration and the rotating mass scaling factor.
In one embodiment, the current estimated vehicle mass is a quotient obtained by dividing a first calculated value by a second calculated value, the first calculated value is a sum of the air resistance and the engine resistance, and the second calculated value is a difference obtained by subtracting the rolling resistance factor from the sum of the ramp resistance factor and the acceleration resistance factor.
An entire vehicle mass estimation device, the device comprising:
the driving state information acquiring module is used for acquiring current driving state information of the vehicle, wherein the current driving state information of the vehicle comprises: current vehicle speed, current accelerator pedal opening, current brake pedal opening and current gradient;
the driving parameter acquisition module is used for acquiring the current driving parameters of the vehicle when the condition that the vehicle mass estimation preset triggering condition is met is determined based on the current driving state information of the vehicle;
and the quality estimation module is used for determining the current finished vehicle quality estimation value according to the current running parameters of the vehicle.
In one embodiment, the driving parameter obtaining module includes: and the judging unit is used for judging that the preset trigger condition of the whole vehicle mass estimation is met when the current vehicle speed is not 0, the current accelerator pedal opening and the current brake pedal opening are both 0, and the variation of the current gradient in a preset time period is within a preset variation range.
In one embodiment, the apparatus further comprises: and the effectiveness determining module is used for determining the effectiveness of the current finished automobile mass estimation value based on the relative error between the current finished automobile mass estimation value and the current finished automobile mass effective value after determining the current finished automobile mass estimation value according to the current running parameters of the automobile.
In one embodiment, the validity determination module includes a first determination unit, configured to determine that the current vehicle mass estimated value is invalid if a relative error between the current vehicle mass estimated value and the current vehicle mass valid value is smaller than a first preset relative error.
In one embodiment, the validity determining module includes a second determining unit, configured to determine that the current vehicle mass estimated value is valid if a relative error between the current vehicle mass estimated value and the current vehicle mass valid value is greater than or equal to the first preset relative error.
In one embodiment, the validity determination module further includes:
the third determining unit is used for calculating the relative error between the vehicle mass estimation values of the preset times if the vehicle mass estimation values of the preset times are all effective after the current vehicle mass estimation value is determined to be effective;
and the replacing unit is used for replacing the current effective value of the mass of the whole vehicle by the average value of the estimated mass of the whole vehicle of the preset times if the relative error between the estimated mass values of the whole vehicle of the preset times is smaller than a second preset relative error.
In one embodiment, the relative error between the vehicle mass estimation values of the preset times includes: and in the vehicle mass estimation values of the preset times, the relative error between any two adjacent vehicle mass estimation values.
In one embodiment, the mass estimation module is used for determining the current finished vehicle mass estimation value according to the current driving parameter of the vehicle on the basis that the finished vehicle output force is equal to 0.
In one embodiment, the current vehicle driving parameters include a current engine torque, a current vehicle speed, a current grade, and a current gear of the vehicle.
In one embodiment, the quality estimation module comprises:
the first calculation unit is used for determining air resistance based on the current vehicle speed and the windward area;
the second calculation unit is used for determining the current gear ratio of the gearbox based on the current gear, and determining the engine resistance based on the current gear ratio of the gearbox, the current torque of the engine and the reduction gear ratio of the speed reducer;
a third calculation unit for determining a rolling resistance coefficient based on the current vehicle speed and a rolling resistance factor based on the rolling resistance coefficient and the current gradient;
a fourth calculation unit for determining a ramp resistance factor based on the current gradient;
a fifth calculation unit configured to determine a current acceleration based on a variation of the current vehicle speed divided by a corresponding time variation, and determine an acceleration resistance factor based on the current acceleration and a rotating mass conversion coefficient;
a sixth calculating unit, configured to determine the current vehicle mass estimation value based on the air resistance, the engine resistance, the rolling resistance factor, the ramp resistance factor, and the acceleration resistance factor.
An electronic device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
acquiring current running state information of a vehicle, wherein the current running state information of the vehicle comprises: current vehicle speed, current accelerator pedal opening, current brake pedal opening and current gradient;
when the condition that the vehicle mass estimation preset triggering condition is met is determined based on the current vehicle running state information, obtaining current vehicle running parameters;
and determining the current finished vehicle mass estimation value according to the current driving parameters of the vehicle.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
acquiring current running state information of a vehicle, wherein the current running state information of the vehicle comprises: current vehicle speed, current accelerator pedal opening, current brake pedal opening and current gradient;
when the condition that the vehicle mass estimation preset triggering condition is met is determined based on the current vehicle running state information, obtaining current vehicle running parameters;
and determining the current finished vehicle mass estimation value according to the current driving parameters of the vehicle.
According to the vehicle mass estimation method, the vehicle mass estimation device, the electronic equipment and the storage medium, the vehicle mass estimation is started only when the current vehicle running state information based on the current vehicle speed, the current accelerator pedal opening, the current brake pedal opening and the current gradient meets the preset trigger condition, so that fluctuation interference in the estimation process is reduced, and the vehicle mass estimation precision is improved.
Drawings
FIG. 1 is an environmental diagram of an embodiment of a vehicle mass estimation method;
FIG. 2 is a schematic flow chart of a vehicle mass estimation method according to an embodiment;
FIG. 3 is a schematic flow chart of a vehicle mass estimation method in another embodiment;
FIG. 4 is a logic diagram of a vehicle mass estimation method in one embodiment;
FIG. 5 is a block diagram showing the structure of a vehicle mass estimating apparatus according to an embodiment;
FIG. 6 is a block diagram showing the structure of a vehicle mass estimating apparatus according to another embodiment;
FIG. 7 is a diagram illustrating an internal structure of an electronic device in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The vehicle mass estimation method can be applied to the application environment shown in fig. 1. The application environment relates to a vehicle control unit of a vehicle. The current running parameters of the vehicle such as engine torque, gradient, vehicle speed, gear and the like are input to the vehicle control unit through a CAN bus or a hard wire. And the vehicle control unit determines the current vehicle quality estimation value through the current vehicle running parameters.
In one embodiment, as shown in fig. 2, a vehicle mass estimation method is provided, which is described by taking the vehicle controller in fig. 1 as an example, and includes the following steps S202 to S206.
S202, obtaining the current running state information of the vehicle, wherein the current running state information of the vehicle comprises: current vehicle speed, current accelerator pedal opening, current brake pedal opening, and current grade.
Specifically, the vehicle speed at which the vehicle runs may be acquired by an ABS (antilock brake system) or an engine ECU (electronic control unit). The accelerator pedal or brake pedal opening may be obtained by outputting a PWM signal from the pedal. The gradient of the vehicle can be obtained by installing a gradient sensor on the chassis of the vehicle head.
And S204, acquiring the current running parameters of the vehicle when the vehicle current running state information is determined to meet the preset trigger condition of the whole vehicle mass estimation.
In one embodiment, the preset trigger conditions for the whole vehicle mass estimation are as follows: the vehicle is in a running state and in a coasting state with neither acceleration nor braking, and the current gradient is stable.
In one embodiment, when the current vehicle speed is not 0, the current accelerator pedal opening and the current brake pedal opening are both 0, and the variation of the current gradient in the preset time period is within the preset variation range, the fact that the preset trigger condition of the whole vehicle mass estimation is met is judged.
Specifically, whether the vehicle is running is determined by the current vehicle speed. And if the current vehicle speed is 0, the vehicle is in a static state. And if the current vehicle speed is not 0, the vehicle is in a running state.
And determining whether the vehicle slides or not according to the current accelerator pedal opening and the current brake pedal opening. And if the current opening degree of the accelerator pedal and the current opening degree of the brake pedal are both 0, the vehicle is in a sliding state without acceleration or braking.
And determining whether the current gradient is stable according to whether the relative error of the current gradient in a preset time period is within a set standard range. In one embodiment, specifically, multiple gradient data may be acquired within a preset time period (e.g., 0.5 second), for example, one gradient data may be acquired every 0.05 second, 10 gradient data may be acquired within 0.5 second, each gradient data may be compared with the current gradient, and if the relative error is within a set standard range (e.g., 1%), the current gradient may be considered to be stable. And if one or more than one of the slope data and the current slope have relative errors exceeding the set standard range, the current slope is considered unstable.
And S206, determining the current finished vehicle mass estimation value according to the current running parameters of the vehicle.
The current driving parameters of the vehicle include a current torque of an engine of the vehicle, a current vehicle speed, a current gradient, and a current gear. The torque of the output shaft of the engine can be obtained by additionally arranging a torque sensor between the engine and the gearbox. The vehicle speed at which the vehicle runs may be acquired by an ABS (antilock brake system) or an engine ECU (electronic control unit). The gradient of the vehicle can be obtained by installing a gradient sensor on the chassis of the vehicle head. The vehicle gear may be obtained by a transmission controller.
In one embodiment, the current finished vehicle mass estimation value is determined according to the current running parameters of the vehicle on the basis that the finished vehicle output force is equal to 0.
In one embodiment, the vehicle overall output force (driving force or braking force) includes rolling resistance, ramp resistance, acceleration resistance, air resistance, and engine resistance.
In one embodiment, a method of calculating rolling resistance includes: determining a rolling resistance coefficient based on a current vehicle speed; and multiplying the mass of the whole vehicle to be estimated, the gravity acceleration and the rolling resistance coefficient by the cosine value of the slope angle corresponding to the current gradient to obtain the rolling resistance. Specifically, the rolling resistance can be calculated by the following formula:
Ff＝m*g*f*cosθ (1)
wherein, FfThe method comprises the steps of representing rolling resistance, representing the mass of the whole vehicle to be estimated, representing g gravity acceleration, representing a rolling resistance coefficient, representing theta by a slope angle corresponding to a current slope, and obtaining theta by calculating an arctangent value of the current slope. f can be obtained by looking up a table of the current vehicle speed, and specifically, the rolling resistance coefficient f can be obtained by the following functional relation:
f＝0.0076+0.000056v (2)
where v represents the current vehicle speed (in km/h).
In one embodiment, a method of calculating a ramp resistance includes: and multiplying the mass of the whole vehicle to be estimated, the gravity acceleration and the sine value of the slope angle corresponding to the current slope to obtain the slope resistance. Specifically, the ramp resistance may be calculated by the following formula:
Fi＝m*g*sinθ (3)
wherein, FiThe slope resistance is represented, m represents the mass of the whole vehicle to be estimated, g represents the gravity acceleration, theta represents the slope angle corresponding to the current slope, and theta can be obtained by calculating the arc tangent value of the current slope.
In one embodiment, a method of calculating acceleration resistance includes: acquiring the last-time vehicle speed of a vehicle; dividing the variation of the current vehicle speed and the vehicle speed at the previous moment by the corresponding time variation to obtain the current acceleration; and multiplying the mass of the whole vehicle to be estimated, the conversion coefficient of the rotating mass and the current acceleration to obtain the acceleration resistance. The rotating mass conversion coefficient is a vehicle intrinsic parameter. Specifically, the acceleration resistance can be calculated by the following formula:
Fj＝m**a (4)
wherein, FjRepresenting the acceleration resistance, m representing the mass of the entire vehicle to be estimated, representing a rotating mass conversion coefficient (typically 1.01), a representing the current acceleration, a being obtained by dividing the variation of the current vehicle speed and the vehicle speed at the previous moment by the corresponding time variation. Specifically, the current acceleration a may be calculated by the following formula:
Figure BDA0002004296530000101
wherein v isiIndicates the current vehicle speed (in km/h), also corresponding to tiVehicle speed at time (unit s). v. ofi-1Indicates the vehicle speed (unit km/h) at the previous moment and also corresponds to ti-1Vehicle speed at time (unit s).
In one embodiment, a method of calculating air resistance includes: and dividing the product of the air resistance coefficient, the windward area and the square value of the current vehicle speed by a preset constant to obtain the air resistance. The air resistance coefficient and the windward area are both intrinsic parameters of the vehicle, and the predetermined constant is 21.15. Specifically, the air resistance can be calculated by the following formula:
Figure BDA0002004296530000102
wherein, FwRepresents air resistance, represents an air resistance coefficient (usually 0.8), and A represents a frontal area (usually 8.7325 m)2) And v represents the current vehicle speed (in km/h).
In one embodiment, a method of calculating engine resistance comprises: determining a current gear ratio of the gearbox based on the current gear; and dividing the product of the current torque of the engine, the current speed change ratio of the gearbox and the reduction ratio of the speed reducer by the radius of the wheel to obtain the resistance of the engine. The current gear ratio of the gearbox can be obtained through a gear look-up table of the current gearbox, and when the gearbox is in a neutral gear, the gear ratio is 0. The retarder reduction ratio is a vehicle-inherent parameter. Specifically, the engine resistance may be calculated by the following equation:
Figure BDA0002004296530000111
wherein, FeRepresenting engine resistance, TeRepresenting the current torque of the engine, I1Indicating the current gear ratio of the gearbox, I2Indicating the reduction ratio of the reducer, RwRepresenting the radius of the wheel. The engine resistance of the vehicle under different vehicle speeds and different gears can be calculated through the formula.
In one embodiment, as the vehicle is free-wheeling, a vehicle travel equation may be established based on rolling resistance, ramp resistance, acceleration resistance, air resistance, and engine resistance for a total force of 0 for the vehicle; and solving the vehicle mass to be estimated in the vehicle running equation to obtain the current vehicle mass estimation value.
In one embodiment, the rolling resistance F is positive in the direction of the vehicle's forward directionfAir resistance FwAnd engine resistance FeIs always in the positive direction, and the ramp resistance FiIs determined according to the vehicle ramp condition, acceleration resistance FjIs determined based on the vehicle speed change. Specifically, the ramp resistance F on an uphill slopeiPositive direction, ramp resistance F on downhill slopeiIn the negative direction, the resistance F of the ramp when driving horizontallyiIs zero. Acceleration resistance F at accelerationjIn the positive direction, acceleration resistance F during decelerationjIn the negative direction, and the acceleration resistance F is in constant speed runningjIs zero
In one embodiment, the overall vehicle output force FzThe following equation is satisfied:
Fz＝Ff+Fw+Fe-Fi-Fj＝0 (8)
substituting the formulas (1) to (7) into the formula (8), and solving the mass of the whole vehicle to be estimated in the formula, namely:
Figure BDA0002004296530000112
and m obtained by the formula calculation is the current finished automobile mass estimation value. With respect to equation (9) above, in one embodiment, the slope angle θ is calculated using a positive value if the vehicle is in a downhill condition. In one embodiment, the slope angle θ is calculated using a negative value if the vehicle is in an uphill condition. In one embodiment, the acceleration a is calculated as a positive value if the vehicle is decelerating. In one embodiment, if the vehicle is in an acceleration state, the acceleration a is calculated using a negative value.
In one embodiment, as shown in fig. 3, after determining the current estimated vehicle quality according to the current driving parameters of the vehicle, the method further includes step S208: and determining the validity of the current finished automobile mass estimation value based on the relative error between the current finished automobile mass estimation value and the current finished automobile mass effective value.
The vehicle mass estimation method can be used for estimating the current vehicle mass at each estimation moment, and each estimation moment can be set according to a preset time interval. The current vehicle mass effective value may be a vehicle mass estimated value obtained by the vehicle mass estimation method at a previous estimation time. The current finished automobile mass estimation value estimated each time is compared with the current finished automobile mass effective value, and whether the finished automobile mass estimation result is effective or not is determined through the relative error between the current finished automobile mass estimation value estimated each time and the current finished automobile mass effective value, so that frequent fluctuation of the finished automobile mass estimation value caused by the estimation error can be effectively eliminated, and the stability and the safety of the finished automobile are guaranteed.
In one embodiment, if the relative error between the current vehicle mass estimation value and the current vehicle mass effective value is smaller than a first preset relative error, the current vehicle mass estimation value is determined to be invalid.
In one embodiment, if the relative error between the current vehicle mass estimation value and the current vehicle mass effective value is greater than or equal to a first preset relative error, the current vehicle mass estimation value is determined to be effective.
Specifically, if the relative error between the current vehicle mass estimation value and the current vehicle mass effective value is smaller than a first preset relative error (e.g., 10%), the current vehicle mass estimation value is considered to be similar to the current vehicle mass effective value, and the estimation result can be ignored and determined to be invalid. And if the relative error between the current finished automobile mass estimation value and the current finished automobile mass effective value is larger than or equal to a first preset relative error (such as 10%), considering that the difference between the current finished automobile mass estimation value and the current finished automobile mass is larger, and determining that the current finished automobile mass estimation value and the current finished automobile mass are effective.
In one embodiment, after determining that the current vehicle mass estimation value is valid, the method further includes:
if the continuously determined finished automobile mass estimation values of the preset times are all effective, calculating the relative error between the finished automobile mass estimation values of the preset times; and if the relative error between the vehicle mass estimation values of the preset times is smaller than a second preset relative error, replacing the current vehicle mass effective value with the average value of the vehicle mass estimation values of the preset times. Wherein, the relative error between the vehicle mass estimation values of the preset times comprises: and in the preset times of vehicle mass estimation values, the relative error between any two adjacent vehicle mass estimation values.
In one embodiment, the preset times are set to be two times, after the two effective finished vehicle mass estimation values are obtained, the relative error between the second finished vehicle mass estimation value and the first finished vehicle mass estimation value is calculated, and if the relative error is smaller than a second preset relative error (such as 10%), the current mass effective value is replaced by the average value of the two effective finished vehicle mass estimation values, so that the influence on vehicle stability due to frequent vehicle mass updating is avoided. The vehicle control system adjusts the current driving force or braking force according to the updated total vehicle mass, so that the running state of the vehicle can be effectively controlled, and the safety of the vehicle is guaranteed.
In one embodiment, as shown in fig. 4, a method for estimating a mass of a finished vehicle is provided, which includes the following steps:
s401, acquiring current running state information of a vehicle; the current running state information of the vehicle includes: the method comprises the following steps of (1) obtaining a current vehicle speed, a current pedal opening and a current gradient, wherein the current pedal opening comprises a current accelerator pedal opening and a current brake pedal opening;
s402, judging whether the current vehicle speed is 0, if not, entering the step S403;
s403, judging whether the current pedal opening is 0, if so, entering the step S404;
s404, judging whether the current gradient is stable, if so, entering the step S405;
s405, obtaining the current driving parameters of the vehicle;
s406, determining the current finished vehicle mass estimation value according to the current driving parameters of the vehicle;
s407, calculating the relative error between the current finished automobile mass estimation value and the effective value;
s408, judging whether the relative error between the current finished automobile mass estimation value and the effective value is larger than or equal to a first preset relative error or not, and if so, entering the step S409;
s409, calculating the relative error between the vehicle mass estimation values of preset times;
s410, judging whether the relative error between the vehicle mass estimation values of the preset times is smaller than a second preset relative error or not, if so, entering a step S411;
s411, calculating the average value of the vehicle mass estimation values of the preset times, and replacing the current vehicle mass effective value.
For specific limitations of steps S401 to S411, refer to the above embodiments, and are not described herein again.
According to the vehicle mass estimation method, the vehicle mass estimation is started only when the current running state information of the vehicle is determined to meet the preset trigger condition based on the current running state information of the vehicle, so that fluctuation interference in the estimation process is reduced, and the vehicle mass estimation precision is improved; then, estimating the current whole vehicle mass from the angle of vehicle stress, and considering the influence of specific engine torque, vehicle speed, gradient and gear on mass estimation, so that the whole vehicle mass estimation is more accurate; and the effectiveness of the estimation result is evaluated, and the stability of the whole vehicle quality estimation is improved.
It should be understood that although the various steps in the flow charts of fig. 2-4 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2-4 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternating with other steps or at least some of the sub-steps or stages of other steps.
In one embodiment, as shown in fig. 5, there is provided a vehicle mass estimation device including: a driving state information obtaining module 510, a driving parameter obtaining module 520, and a quality estimating module 530. Wherein:
a driving state information obtaining module 510, configured to obtain current driving state information of a vehicle, where the current driving state information of the vehicle includes: current vehicle speed, current accelerator pedal opening, current brake pedal opening, and current grade.
And a driving parameter obtaining module 520, configured to obtain a current driving parameter of the vehicle when it is determined that the preset trigger condition for estimating the mass of the entire vehicle is satisfied based on the current driving state information of the vehicle.
And the mass estimation module 530 is used for determining the current finished vehicle mass estimation value according to the current running parameters of the vehicle.
In one embodiment, the driving parameter acquisition module 520 includes: and the judging unit is used for judging that the preset trigger condition of the whole vehicle quality estimation is met when the current vehicle speed is not 0, the current accelerator pedal opening and the current brake pedal opening are both 0, and the variation of the current gradient in the preset time period is in the preset variation range.
In one embodiment, as shown in fig. 6, the apparatus further comprises: and the validity determining module 540 is configured to determine, after determining the current vehicle mass estimation value according to the current vehicle running parameter, validity of the current vehicle mass estimation value based on a relative error between the current vehicle mass estimation value and the current vehicle mass valid value.
In one embodiment, the validity determination module 540 includes: and the first determining unit is used for determining that the current finished automobile mass estimation value is invalid if the relative error between the current finished automobile mass estimation value and the current finished automobile mass effective value is smaller than a first preset relative error.
In one embodiment, the validity determination module 540 includes: and the second determining unit is used for determining that the current finished automobile mass estimation value is effective if the relative error between the current finished automobile mass estimation value and the current finished automobile mass effective value is greater than or equal to a first preset relative error.
In one embodiment, the validity determination module 540 further comprises: and the third determining unit is used for calculating the relative error between the vehicle mass estimation values of the preset times if the vehicle mass estimation values of the preset times are continuously determined to be effective after the current vehicle mass estimation value is determined to be effective.
In one embodiment, the validity determination module 540 further comprises: and the replacing unit is used for replacing the current effective value of the mass of the whole vehicle by the average value of the estimated mass of the whole vehicle of the preset times if the relative error between the estimated mass of the whole vehicle of the preset times is smaller than a second preset relative error.
In one embodiment, the relative error between the vehicle mass estimation values of the preset times comprises: and in the preset times of vehicle mass estimation values, the relative error between any two adjacent vehicle mass estimation values.
In one embodiment, the mass estimation module 530 is configured to determine a current finished vehicle mass estimation value based on the current vehicle driving parameter based on the vehicle finished vehicle output force being equal to 0.
In one embodiment, the current vehicle driving parameters include a current engine torque, a current vehicle speed, a current grade, and a current gear of the vehicle.
In one embodiment, the quality estimation module 530 includes a first calculation unit, a second calculation unit, a third calculation unit, a fourth calculation unit, a fifth calculation unit, and a sixth calculation unit.
And the first calculation unit is used for determining the air resistance based on the current vehicle speed and the windward area. In one embodiment, the air resistance is a quotient obtained by dividing a first product by a predetermined constant, the first product being a product of an air resistance coefficient, a windward area, and a square value of a current vehicle speed.
And the second calculation unit is used for determining the current speed change ratio of the gearbox based on the current gear and determining the engine resistance based on the current speed change ratio of the gearbox, the current torque of the engine and the reduction gear ratio of the speed reducer. In one embodiment, the engine resistance is a quotient of a second product divided by the wheel radius, the second product being a product of the current engine torque, the current transmission gear ratio of the transmission, and the reduction gear ratio of the retarder.
A third calculation unit for determining a rolling resistance coefficient based on the current vehicle speed and a rolling resistance factor based on the rolling resistance coefficient and the current gradient. In one embodiment, the rolling resistance factor is the product of the gravitational acceleration, the rolling resistance coefficient, and the cosine of the slope angle to which the current slope corresponds.
A fourth calculation unit for determining a ramp resistance factor based on the current grade. In one embodiment, the ramp resistance factor is the product of the acceleration of gravity and the sine of the current slope with respect to the ramp angle.
And a fifth calculation unit for determining the current acceleration based on the variation of the current vehicle speed divided by the corresponding time variation, and determining the acceleration resistance factor based on the current acceleration and the rotating mass conversion coefficient. In one embodiment, the acceleration resistance factor is the product of the current acceleration and the rotating mass scaling factor.
And the sixth calculating unit is used for determining the current finished automobile mass estimation value based on the air resistance, the engine resistance, the rolling resistance factor, the ramp resistance factor and the acceleration resistance factor. In one embodiment, the current vehicle mass estimate is a quotient of a first calculated value divided by a second calculated value, the first calculated value being a sum of air resistance and engine resistance, and the second calculated value being a difference of a sum of a ramp resistance factor and an acceleration resistance factor minus a rolling resistance factor.
For specific limitations of the vehicle mass estimation device, reference may be made to the above limitations of the vehicle mass estimation method, which are not described herein again. The above-mentioned modules in the vehicle mass estimation device may be implemented wholly or partially by software, hardware, or a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, an electronic device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 7. The electronic device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the electronic device is configured to provide computing and control capabilities. The memory of the electronic equipment comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the electronic device is used for connecting and communicating with an external terminal through a network. The computer program is executed by a processor to implement a vehicle mass estimation method.
Those skilled in the art will appreciate that the architecture shown in fig. 7 is a block diagram of only a portion of the architecture associated with the subject application, and does not constitute a limitation on the electronic devices to which the subject application may be applied, and that a particular electronic device may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, an electronic device is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor implementing the following steps when executing the computer program:
acquiring current running state information of a vehicle, wherein the current running state information of the vehicle comprises: current vehicle speed, current accelerator pedal opening, current brake pedal opening and current gradient;
when the condition that the vehicle mass estimation preset triggering condition is met is determined based on the current running state information of the vehicle, obtaining current running parameters of the vehicle;
and determining the current finished vehicle mass estimation value according to the current running parameters of the vehicle.
In one embodiment, the processor, when executing the computer program, further performs the steps of: and when the current vehicle speed is not 0, the current accelerator pedal opening and the current brake pedal opening are both 0, and the variation of the current gradient in a preset time period is within a preset variation range, judging that the preset trigger condition of the whole vehicle quality estimation is met.
In one embodiment, the processor, when executing the computer program, further performs the steps of: after the current finished automobile mass estimation value is determined according to the current running parameters of the automobile, the effectiveness of the current finished automobile mass estimation value is determined based on the relative error between the current finished automobile mass estimation value and the current finished automobile mass effective value.
In one embodiment, the processor, when executing the computer program, further performs the steps of: and if the relative error between the current finished automobile mass estimation value and the current finished automobile mass effective value is smaller than a first preset relative error, determining that the current finished automobile mass estimation value is invalid.
In one embodiment, the processor, when executing the computer program, further performs the steps of: and if the relative error between the current finished automobile mass estimation value and the current finished automobile mass effective value is larger than or equal to a first preset relative error, determining that the current finished automobile mass estimation value is effective.
In one embodiment, the processor, when executing the computer program, further performs the steps of: after the current finished automobile mass estimation value is determined to be effective, if the continuously determined finished automobile mass estimation values of preset times are all effective, calculating the relative error between the finished automobile mass estimation values of the preset times; and if the relative error between the vehicle mass estimation values of the preset times is smaller than a second preset relative error, replacing the current vehicle mass effective value with the average value of the vehicle mass estimation values of the preset times.
In one embodiment, the processor, when executing the computer program, further performs the steps of: and determining the current finished vehicle mass estimation value according to the current driving parameters of the vehicle on the basis that the finished vehicle output force is equal to 0.
In one embodiment, the processor, when executing the computer program, further performs the steps of: based on the current vehicle speed and the frontal area, the air resistance is determined. In one embodiment, the air resistance is a quotient obtained by dividing a first product by a predetermined constant, the first product being a product of an air resistance coefficient, a windward area, and a square value of a current vehicle speed.
In one embodiment, the processor, when executing the computer program, further performs the steps of: a current transmission ratio of the transmission is determined based on the current gear, and an engine resistance is determined based on the current transmission ratio, the current torque of the engine, and the reduction gear ratio of the retarder. In one embodiment, the engine resistance is a quotient of a second product divided by the wheel radius, the second product being a product of the current engine torque, the current transmission gear ratio of the transmission, and the reduction gear ratio of the retarder.
In one embodiment, the processor, when executing the computer program, further performs the steps of: a rolling resistance coefficient is determined based on a current vehicle speed, and a rolling resistance factor is determined based on the rolling resistance coefficient and a current grade. In one embodiment, the rolling resistance factor is the product of the gravitational acceleration, the rolling resistance coefficient, and the cosine of the slope angle to which the current slope corresponds.
In one embodiment, the processor, when executing the computer program, further performs the steps of: a ramp resistance factor is determined based on the current grade. In one embodiment, the ramp resistance factor is the product of the acceleration of gravity and the sine of the current slope with respect to the ramp angle.
In one embodiment, the processor, when executing the computer program, further performs the steps of: a current acceleration is determined based on a variation of the current vehicle speed divided by a corresponding time variation, and an acceleration resistance factor is determined based on the current acceleration and a rotating mass conversion coefficient. In one embodiment, the acceleration resistance factor is the product of the current acceleration and the rotating mass scaling factor.
In one embodiment, the processor, when executing the computer program, further performs the steps of: an overall mass estimate is determined based on the air resistance, the engine resistance, the rolling resistance factor, the ramp resistance factor, and the acceleration resistance factor. In one embodiment, the current vehicle mass estimate is a quotient of a first calculated value divided by a second calculated value, the first calculated value being a sum of air resistance and engine resistance, and the second calculated value being a difference of a sum of a ramp resistance factor and an acceleration resistance factor minus a rolling resistance factor.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring current running state information of a vehicle, wherein the current running state information of the vehicle comprises: current vehicle speed, current accelerator pedal opening, current brake pedal opening and current gradient;
when the condition that the vehicle mass estimation preset triggering condition is met is determined based on the current running state information of the vehicle, obtaining current running parameters of the vehicle;
and determining the current finished vehicle mass estimation value according to the current running parameters of the vehicle.
In one embodiment, the computer program when executed by the processor further performs the steps of: and when the current vehicle speed is not 0, the current accelerator pedal opening and the current brake pedal opening are both 0, and the variation of the current gradient in a preset time period is within a preset variation range, judging that the preset trigger condition of the whole vehicle quality estimation is met.
In one embodiment, the computer program when executed by the processor further performs the steps of: after the current finished automobile mass estimation value is determined according to the current running parameters of the automobile, the effectiveness of the current finished automobile mass estimation value is determined based on the relative error between the current finished automobile mass estimation value and the current finished automobile mass effective value.
In one embodiment, the computer program when executed by the processor further performs the steps of: and if the relative error between the current finished automobile mass estimation value and the current finished automobile mass effective value is smaller than a first preset relative error, determining that the current finished automobile mass estimation value is invalid.
In one embodiment, the computer program when executed by the processor further performs the steps of: and if the relative error between the current finished automobile mass estimation value and the current finished automobile mass effective value is larger than or equal to a first preset relative error, determining that the current finished automobile mass estimation value is effective.
In one embodiment, the computer program when executed by the processor further performs the steps of: after the current finished automobile mass estimation value is determined to be effective, if the continuously determined finished automobile mass estimation values of preset times are all effective, calculating the relative error between the finished automobile mass estimation values of the preset times; and if the relative error of the vehicle mass estimation values of the preset times is smaller than a second preset relative error, replacing the current vehicle mass effective value with the average value of the vehicle mass estimation values of the preset times.
In one embodiment, the computer program when executed by the processor further performs the steps of: and determining the current finished vehicle mass estimation value according to the current driving parameters of the vehicle on the basis that the finished vehicle output force is equal to 0.
In one embodiment, the computer program when executed by the processor further performs the steps of: based on the current vehicle speed and the frontal area, the air resistance is determined. In one embodiment, the air resistance is a quotient obtained by dividing a first product by a predetermined constant, the first product being a product of an air resistance coefficient, a windward area, and a square value of a current vehicle speed.
In one embodiment, the computer program when executed by the processor further performs the steps of: a current transmission ratio of the transmission is determined based on the current gear, and an engine resistance is determined based on the current transmission ratio, the current torque of the engine, and the reduction gear ratio of the retarder. In one embodiment, the engine resistance is a quotient of a second product divided by the wheel radius, the second product being a product of the current engine torque, the current transmission gear ratio of the transmission, and the reduction gear ratio of the retarder.
In one embodiment, the computer program when executed by the processor further performs the steps of: a rolling resistance coefficient is determined based on a current vehicle speed, and a rolling resistance factor is determined based on the rolling resistance coefficient and a current grade. In one embodiment, the rolling resistance factor is the product of the gravitational acceleration, the rolling resistance coefficient, and the cosine of the slope angle to which the current slope corresponds.
In one embodiment, the computer program when executed by the processor further performs the steps of: a ramp resistance factor is determined based on the current grade. In one embodiment, the ramp resistance factor is the product of the acceleration of gravity and the sine of the current slope with respect to the ramp angle.
In one embodiment, the computer program when executed by the processor further performs the steps of: a current acceleration is determined based on a variation of the current vehicle speed divided by a corresponding time variation, and an acceleration resistance factor is determined based on the current acceleration and a rotating mass conversion coefficient. In one embodiment, the acceleration resistance factor is the product of the current acceleration and the rotating mass scaling factor.
In one embodiment, the computer program when executed by the processor further performs the steps of: an overall mass estimate is determined based on the air resistance, the engine resistance, the rolling resistance factor, the ramp resistance factor, and the acceleration resistance factor. In one embodiment, the current vehicle mass estimate is a quotient of a first calculated value divided by a second calculated value, the first calculated value being a sum of air resistance and engine resistance, and the second calculated value being a difference of a sum of a ramp resistance factor and an acceleration resistance factor minus a rolling resistance factor.
It should be understood that the terms "first", "second", "third", "fourth", "fifth", "sixth" in the above-described embodiments are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims (13)

1. A vehicle mass estimation method, the method comprising:
acquiring current running state information of a vehicle, wherein the current running state information of the vehicle comprises: current vehicle speed, current accelerator pedal opening, current brake pedal opening and current gradient;
when the condition that the vehicle mass estimation preset triggering condition is met is determined based on the current vehicle running state information, obtaining current vehicle running parameters;
and determining the current finished vehicle mass estimation value according to the current driving parameters of the vehicle.
2. The method according to claim 1, characterized by determining that a whole vehicle mass estimation preset trigger condition is satisfied when the current vehicle speed is not 0, the current accelerator pedal opening and the current brake pedal opening are both 0, and a variation amount of the current gradient in a preset time period is within a preset variation range.
3. The method of claim 1, wherein after determining a current finished vehicle mass estimate based on current vehicle operating parameters, further comprising:
and determining the validity of the current finished automobile mass estimation value based on the relative error between the current finished automobile mass estimation value and the current finished automobile mass effective value.
4. The method of claim 3, comprising at least one of:
if the relative error between the current finished automobile mass estimation value and the current finished automobile mass effective value is smaller than a first preset relative error, determining that the current finished automobile mass estimation value is invalid;
and if the relative error between the current finished automobile mass estimation value and the current finished automobile mass effective value is larger than or equal to the first preset relative error, determining that the current finished automobile mass estimation value is effective.
5. The method of claim 4, further comprising, after determining that the current vehicle mass estimate is valid:
if the continuously determined finished automobile mass estimation values of the preset times are all effective, calculating the relative error between the finished automobile mass estimation values of the preset times;
and if the relative error between the vehicle mass estimation values of the preset times is smaller than a second preset relative error, replacing the current vehicle mass effective value with the average value of the vehicle mass estimation values of the preset times.
6. The method of claim 5, wherein the relative error between the vehicle mass estimates for the predetermined number of times comprises: and in the vehicle mass estimation values of the preset times, the relative error between any two adjacent vehicle mass estimation values.
7. The method of any of claims 1-6, wherein determining a current finished vehicle mass estimate based on current vehicle operating parameters comprises:
and determining the current finished vehicle mass estimation value according to the current driving parameters of the vehicle on the basis that the finished vehicle output force is equal to 0.
8. The method of claim 7, wherein the vehicle current driving parameters include a current engine torque, a current vehicle speed, a current grade, and a current gear of the vehicle.
9. The method of claim 8, wherein determining a current finished vehicle mass estimate based on the current vehicle travel parameter based on a vehicle finished vehicle output force equal to 0 comprises:
determining air resistance based on the current vehicle speed and the windward area;
determining a current gear ratio of the gearbox based on the current gear, and determining engine resistance based on the current gear ratio of the gearbox, the current torque of the engine and a reduction gear ratio of a speed reducer;
determining a rolling resistance coefficient based on the current vehicle speed and a rolling resistance factor based on the rolling resistance coefficient and the current grade;
determining a ramp resistance factor based on the current grade;
determining a current acceleration based on the variation of the current vehicle speed divided by the corresponding time variation, and determining an acceleration resistance factor based on the current acceleration and a rotating mass conversion coefficient;
determining the current gross vehicle mass estimate based on the air resistance, the engine resistance, the rolling resistance factor, the ramp resistance factor, and the acceleration resistance factor.
10. The method of claim 9, comprising at least one of:
the air resistance is a quotient obtained by dividing a first product by a preset constant, and the first product is a product of an air resistance coefficient, the windward area and a square value of the current vehicle speed;
the engine resistance is a quotient obtained by dividing a second product by the radius of the wheel, and the second product is a product of the current torque of the engine, the current speed change ratio of the gearbox and the reduction ratio of the speed reducer;
the rolling resistance factor is the product of the gravity acceleration, the rolling resistance coefficient and the cosine value of the slope angle corresponding to the current slope;
the ramp resistance factor is the product of the gravity acceleration and the sine value of the slope angle corresponding to the current slope;
the acceleration resistance factor is the product of the current acceleration and the rotating mass conversion coefficient;
the current finished automobile mass estimation value is a quotient obtained by dividing a first calculation value by a second calculation value, the first calculation value is the sum of the air resistance and the engine resistance, and the second calculation value is a difference value obtained by subtracting the rolling resistance factor from the sum of the ramp resistance factor and the acceleration resistance factor.
11. An entire vehicle mass estimation device, characterized by comprising:
the driving state information acquiring module is used for acquiring current driving state information of the vehicle, wherein the current driving state information of the vehicle comprises: current vehicle speed, current accelerator pedal opening, current brake pedal opening and current gradient;
the driving parameter acquisition module is used for acquiring the current driving parameters of the vehicle when the condition that the vehicle mass estimation preset triggering condition is met is determined based on the current driving state information of the vehicle;
and the quality estimation module is used for determining the current finished vehicle quality estimation value according to the current running parameters of the vehicle.
12. An electronic device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor realizes the steps of the method of any one of claims 1 to 10 when executing the computer program.
13. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 10.
CN201910223240.0A 2019-03-22 2019-03-22 Vehicle mass estimation method and device, electronic equipment and storage medium Active CN111717214B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201910223240.0A CN111717214B (en) 2019-03-22 2019-03-22 Vehicle mass estimation method and device, electronic equipment and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910223240.0A CN111717214B (en) 2019-03-22 2019-03-22 Vehicle mass estimation method and device, electronic equipment and storage medium

Publications (2)

Publication Number Publication Date
CN111717214A true CN111717214A (en) 2020-09-29
CN111717214B CN111717214B (en) 2021-11-30

Family

ID=72563523

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910223240.0A Active CN111717214B (en) 2019-03-22 2019-03-22 Vehicle mass estimation method and device, electronic equipment and storage medium

Country Status (1)

Country Link
CN (1) CN111717214B (en)

Cited By (24)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112356837A (en) * 2020-11-18 2021-02-12 潍柴动力股份有限公司 Vehicle load monitoring method, server and control system
CN112373484A (en) * 2020-11-26 2021-02-19 同济大学 Method for acquiring vehicle mass dynamics based on feedforward neural network
CN112406888A (en) * 2020-10-29 2021-02-26 广西玉柴机器股份有限公司 Automobile weight calculation method and related device
CN112498357A (en) * 2020-11-20 2021-03-16 奇瑞新能源汽车股份有限公司 Vehicle total mass calculation device and method
CN112590804A (en) * 2020-12-23 2021-04-02 苏州挚途科技有限公司 Load trajectory tracking method and device for unmanned vehicle
CN112896178A (en) * 2021-03-17 2021-06-04 中国重汽集团济南动力有限公司 Method and system for calculating total mass of vehicle
CN112977459A (en) * 2021-04-20 2021-06-18 一汽解放汽车有限公司 Method, apparatus, computer device and storage medium for determining vehicle control parameters
CN113022319A (en) * 2021-04-27 2021-06-25 山东汽车制造有限公司 Electric vehicle self-adaptive energy recovery control method and electric vehicle
CN113085876A (en) * 2021-03-23 2021-07-09 浙江吉利控股集团有限公司 Vehicle mass estimation method and device based on recursive gradient correction method
CN113264056A (en) * 2021-05-25 2021-08-17 三一汽车制造有限公司 Vehicle weight estimation method, device, vehicle and readable storage medium
CN113335290A (en) * 2021-07-22 2021-09-03 中国第一汽车股份有限公司 Vehicle rolling resistance acquisition method, acquisition module and storage medium
CN113859253A (en) * 2021-11-24 2021-12-31 吉林大学 Real-time estimation method for quality in vehicle driving process
CN113954851A (en) * 2021-12-17 2022-01-21 天津大学 Vehicle mass estimation method based on high-precision positioning
CN114132324A (en) * 2021-12-03 2022-03-04 浙江吉利控股集团有限公司 Vehicle mass estimation method, device, equipment and storage medium
CN114312805A (en) * 2022-01-04 2022-04-12 一汽解放汽车有限公司 Fuel consumption rate acquisition method and device, computer equipment and storage medium
CN114407906A (en) * 2022-01-25 2022-04-29 东风柳州汽车有限公司 Vehicle load measuring method and device, storage medium and equipment
TWI768884B (en) * 2021-05-10 2022-06-21 威剛科技股份有限公司 Weight estimation system and method for an electric vehicle
CN114684159A (en) * 2022-03-21 2022-07-01 潍柴动力股份有限公司 Vehicle mass estimation method and device, electronic equipment and storage medium
CN114954495A (en) * 2022-07-29 2022-08-30 所托(杭州)汽车智能设备有限公司 Commercial vehicle mass estimation method, electronic device and storage medium
CN114987510A (en) * 2022-06-17 2022-09-02 东风悦享科技有限公司 Method and device for on-line estimation of quality parameters of automatic driving vehicle
CN115009288A (en) * 2022-07-19 2022-09-06 潍柴动力股份有限公司 Method and device for determining vehicle weight
CN115027486A (en) * 2022-06-22 2022-09-09 东风柳州汽车有限公司 Vehicle weight measuring method, device and equipment based on big data and storage medium
WO2022236529A1 (en) * 2021-05-10 2022-11-17 威刚科技股份有限公司 System and method for estimating weight of electric vehicle
CN116729399A (en) * 2023-07-11 2023-09-12 长春一东离合器股份有限公司苏州研发中心 Vehicle ramp, vehicle weight dynamic identification method, device, equipment and medium

Citations (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102910172A (en) * 2011-08-02 2013-02-06 通用汽车环球科技运作有限责任公司 Use of on-vehicle accelerometer to estimate vehicle grade and mass while vehicle is in motion
US20130190945A1 (en) * 2012-01-25 2013-07-25 Advics Co., Ltd. Vehicle mass estimating apparatus
US20140172253A1 (en) * 2012-12-19 2014-06-19 Caterpillar Inc. System and method for controlling a transmission
DE102013008839A1 (en) * 2013-05-24 2014-11-27 Wabco Gmbh Method and device for determining the mass of a motor vehicle and motor vehicle with such a device
CN104457937A (en) * 2014-10-11 2015-03-25 中国第一汽车股份有限公司 Method for calculating gross vehicle weight and fuel-saving control method
CN106529111A (en) * 2015-09-14 2017-03-22 北汽福田汽车股份有限公司 Method and system for detecting total vehicle weight and vehicle
CN106891896A (en) * 2017-03-27 2017-06-27 中国第汽车股份有限公司 A kind of commercial car automatic mechanical transmission load recognizes computational methods
CN108068824A (en) * 2016-11-07 2018-05-25 现代自动车株式会社 Estimate the device and its application method of vehicle weight
CN108128301A (en) * 2017-12-21 2018-06-08 潍柴动力股份有限公司 A kind of engine power adjusting method, device and electronic equipment
CN207594866U (en) * 2017-08-25 2018-07-10 安徽江淮汽车集团股份有限公司 A kind of vehicle load measurement system of vehicle load
US20180194357A1 (en) * 2017-01-09 2018-07-12 Michael Hall Determining Weight of Electric and Hybrid Vehicles
US10173689B1 (en) * 2018-01-19 2019-01-08 Thor Tech, Inc. Recreational vehicle and integrated body control and weight sensing system
CN109597346A (en) * 2019-01-30 2019-04-09 南京越博动力系统股份有限公司 A kind of novel commercial vehicle remained capacity and ramp estimation method

Patent Citations (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102910172A (en) * 2011-08-02 2013-02-06 通用汽车环球科技运作有限责任公司 Use of on-vehicle accelerometer to estimate vehicle grade and mass while vehicle is in motion
US20130190945A1 (en) * 2012-01-25 2013-07-25 Advics Co., Ltd. Vehicle mass estimating apparatus
US20140172253A1 (en) * 2012-12-19 2014-06-19 Caterpillar Inc. System and method for controlling a transmission
DE102013008839A1 (en) * 2013-05-24 2014-11-27 Wabco Gmbh Method and device for determining the mass of a motor vehicle and motor vehicle with such a device
CN104457937A (en) * 2014-10-11 2015-03-25 中国第一汽车股份有限公司 Method for calculating gross vehicle weight and fuel-saving control method
CN106529111A (en) * 2015-09-14 2017-03-22 北汽福田汽车股份有限公司 Method and system for detecting total vehicle weight and vehicle
CN108068824A (en) * 2016-11-07 2018-05-25 现代自动车株式会社 Estimate the device and its application method of vehicle weight
US20180194357A1 (en) * 2017-01-09 2018-07-12 Michael Hall Determining Weight of Electric and Hybrid Vehicles
CN106891896A (en) * 2017-03-27 2017-06-27 中国第汽车股份有限公司 A kind of commercial car automatic mechanical transmission load recognizes computational methods
CN207594866U (en) * 2017-08-25 2018-07-10 安徽江淮汽车集团股份有限公司 A kind of vehicle load measurement system of vehicle load
CN108128301A (en) * 2017-12-21 2018-06-08 潍柴动力股份有限公司 A kind of engine power adjusting method, device and electronic equipment
US10173689B1 (en) * 2018-01-19 2019-01-08 Thor Tech, Inc. Recreational vehicle and integrated body control and weight sensing system
CN109597346A (en) * 2019-01-30 2019-04-09 南京越博动力系统股份有限公司 A kind of novel commercial vehicle remained capacity and ramp estimation method

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
林楠: "基于误差自适应的整车质量辨识与基于曲率的道路坡度估计方法研究", 《中国优秀博硕士学位论文全文数据库(博士)工程科技Ⅱ辑》 *

Cited By (33)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112406888B (en) * 2020-10-29 2022-07-15 广西玉柴机器股份有限公司 Automobile weight calculation method and related device
CN112406888A (en) * 2020-10-29 2021-02-26 广西玉柴机器股份有限公司 Automobile weight calculation method and related device
CN112356837A (en) * 2020-11-18 2021-02-12 潍柴动力股份有限公司 Vehicle load monitoring method, server and control system
CN112498357A (en) * 2020-11-20 2021-03-16 奇瑞新能源汽车股份有限公司 Vehicle total mass calculation device and method
CN112373484A (en) * 2020-11-26 2021-02-19 同济大学 Method for acquiring vehicle mass dynamics based on feedforward neural network
CN112373484B (en) * 2020-11-26 2021-12-31 同济大学 Method for acquiring vehicle mass dynamics based on feedforward neural network
CN112590804A (en) * 2020-12-23 2021-04-02 苏州挚途科技有限公司 Load trajectory tracking method and device for unmanned vehicle
CN112896178A (en) * 2021-03-17 2021-06-04 中国重汽集团济南动力有限公司 Method and system for calculating total mass of vehicle
CN113085876A (en) * 2021-03-23 2021-07-09 浙江吉利控股集团有限公司 Vehicle mass estimation method and device based on recursive gradient correction method
CN112977459A (en) * 2021-04-20 2021-06-18 一汽解放汽车有限公司 Method, apparatus, computer device and storage medium for determining vehicle control parameters
CN113022319A (en) * 2021-04-27 2021-06-25 山东汽车制造有限公司 Electric vehicle self-adaptive energy recovery control method and electric vehicle
WO2022236529A1 (en) * 2021-05-10 2022-11-17 威刚科技股份有限公司 System and method for estimating weight of electric vehicle
TWI768884B (en) * 2021-05-10 2022-06-21 威剛科技股份有限公司 Weight estimation system and method for an electric vehicle
CN113264056A (en) * 2021-05-25 2021-08-17 三一汽车制造有限公司 Vehicle weight estimation method, device, vehicle and readable storage medium
CN113335290A (en) * 2021-07-22 2021-09-03 中国第一汽车股份有限公司 Vehicle rolling resistance acquisition method, acquisition module and storage medium
CN113859253B (en) * 2021-11-24 2023-03-07 吉林大学 Real-time estimation method for mass in vehicle driving process
CN113859253A (en) * 2021-11-24 2021-12-31 吉林大学 Real-time estimation method for quality in vehicle driving process
CN114132324A (en) * 2021-12-03 2022-03-04 浙江吉利控股集团有限公司 Vehicle mass estimation method, device, equipment and storage medium
CN114132324B (en) * 2021-12-03 2024-02-02 浙江吉利控股集团有限公司 Whole vehicle quality estimation method, device, equipment and storage medium
CN113954851B (en) * 2021-12-17 2022-03-11 天津大学 Vehicle mass estimation method based on high-precision positioning
CN113954851A (en) * 2021-12-17 2022-01-21 天津大学 Vehicle mass estimation method based on high-precision positioning
CN114312805A (en) * 2022-01-04 2022-04-12 一汽解放汽车有限公司 Fuel consumption rate acquisition method and device, computer equipment and storage medium
CN114407906B (en) * 2022-01-25 2023-07-07 东风柳州汽车有限公司 Vehicle load measuring method, device, storage medium and equipment
CN114407906A (en) * 2022-01-25 2022-04-29 东风柳州汽车有限公司 Vehicle load measuring method and device, storage medium and equipment
CN114684159A (en) * 2022-03-21 2022-07-01 潍柴动力股份有限公司 Vehicle mass estimation method and device, electronic equipment and storage medium
CN114987510A (en) * 2022-06-17 2022-09-02 东风悦享科技有限公司 Method and device for on-line estimation of quality parameters of automatic driving vehicle
CN115027486A (en) * 2022-06-22 2022-09-09 东风柳州汽车有限公司 Vehicle weight measuring method, device and equipment based on big data and storage medium
CN115027486B (en) * 2022-06-22 2024-05-28 东风柳州汽车有限公司 Vehicle weight measuring method, device, equipment and storage medium based on big data
CN115009288A (en) * 2022-07-19 2022-09-06 潍柴动力股份有限公司 Method and device for determining vehicle weight
CN114954495B (en) * 2022-07-29 2022-11-15 所托(杭州)汽车智能设备有限公司 Commercial vehicle mass estimation method, electronic device and storage medium
CN114954495A (en) * 2022-07-29 2022-08-30 所托(杭州)汽车智能设备有限公司 Commercial vehicle mass estimation method, electronic device and storage medium
CN116729399A (en) * 2023-07-11 2023-09-12 长春一东离合器股份有限公司苏州研发中心 Vehicle ramp, vehicle weight dynamic identification method, device, equipment and medium
CN116729399B (en) * 2023-07-11 2024-02-13 长春一东离合器股份有限公司苏州研发中心 Vehicle ramp, vehicle weight dynamic identification method, device, equipment and medium

Also Published As

Publication number Publication date
CN111717214B (en) 2021-11-30

Similar Documents

Publication Publication Date Title
CN111717214B (en) Vehicle mass estimation method and device, electronic equipment and storage medium
US9616898B2 (en) System and method for determining effective road grade characteristic
US8768536B2 (en) Method for determining the driving resistance of a vehicle
EP4206045A1 (en) Auto hold control method and system
CN112622872B (en) Energy recovery control method and device
CN111824165B (en) Gradient calculation method and device
CN113650615B (en) Gear shifting control method and device and storage medium
CN112829756A (en) Vehicle and energy recovery method and device thereof and storage medium
CN109383469A (en) Calculation method, device and the automobile of optimal slip ratio
CN115782616B (en) Control method, device, computer equipment and medium for vehicle creep
CN112752694B (en) Method for estimating load of vehicle
CN109835345B (en) Required torque calculation method, required torque calculation device and automobile
CN113492868A (en) Automobile acceleration intention identification method and device, automobile and computer readable storage medium
CN113119986A (en) Vehicle mass estimation method and device, electronic equipment and storage medium
CN115817481B (en) Control method, system, equipment and medium for vehicle creep
US8620555B2 (en) Wheel slip determination for vehicles
CN115655431A (en) Method, system, computer and storage medium for estimating automobile load
CN114852094A (en) Vehicle mass estimation method and device
CN114701508A (en) Vehicle mass estimation method, apparatus, device, storage medium, and program product
CN115649168A (en) Vehicle stabilization control method, device, equipment and storage medium
CN117418940B (en) Engine torque control method, device, equipment and automobile
EP4310454A1 (en) Rotation rate offset compensation
CN110901414B (en) Vehicle torque control method, device and equipment
CN117261919A (en) Commercial vehicle weight calculation method, device and storage medium
CN116587872A (en) Energy recovery control method and device and vehicle

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant