CN111311782A - Load estimation method and device - Google Patents
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Abstract
The invention provides a load estimation method and a load estimation device, which are used for acquiring load mass under the condition of not arranging a load sensor. The method comprises the following steps: acquiring vehicle driving data; sequencing the driving data according to a time sequence; determining a parameter value of a vehicle static parameter; the vehicle static parameters include: the idle running radius, the full-load running radius and the engine base load power of the vehicle wheels; determining corresponding parameter values of the dynamic resistance parameters at different moments by using the static vehicle parameters and the sequenced vehicle running data; establishing an equation representing the relationship between the vehicle weight and the vehicle driving force and resistance according to the dynamic equation, the static parameters and the parameter values of the dynamic resistance parameters; wherein, in the equation, the vehicle weight is an unknown quantity to be solved; solving and calculating the equation by using the parameter values of the vehicle static parameters and the parameter values of the resistance dynamic parameters at different moments to obtain a solution value of the vehicle weight; and calculating the difference value of the weight of the vehicle and the weight of the unloaded vehicle to obtain the load weight.
Description
Technical Field
The invention relates to the technical field of automobile electronics, in particular to a load estimation method and device.
Background
With the development of economy, the demand of cargo vehicles tends to increase year by year. If the loading capacity of the cargo vehicle can be accurately obtained, the logistics company can improve the single-vehicle utilization rate of the cargo vehicle, and traffic policemen can more conveniently track overloaded vehicles.
Cargo vehicles generally comprise a towing tractor and a trailer, and at present, few cargo vehicles are provided with load sensors on the trailer. This is because the load sensors on the trailers need to be wired to the towing host vehicle, and many trailers and the towing host vehicle are connected by hooks, which makes wiring difficult. In addition, the load sensor is also expensive. These make the acquisition of the load mass of the cargo vehicle difficult.
Disclosure of Invention
In view of this, embodiments of the present invention provide a load estimation method and apparatus to obtain a load mass without arranging a load sensor.
In order to achieve the above purpose, the embodiments of the present invention provide the following technical solutions:
a load estimation method, comprising:
acquiring vehicle driving data;
sequencing the driving data according to a time sequence;
determining a parameter value of a vehicle static parameter; the vehicle static parameters include: the idle running radius, the full-load running radius and the engine base load power of the vehicle wheels;
determining parameter values corresponding to the resistance dynamic parameters at different moments by using the vehicle static parameters and the sequenced vehicle running data;
establishing an equation representing the relationship between the vehicle weight and the vehicle driving force and resistance according to the dynamic equation, the static parameters and the parameter values of the dynamic resistance parameters; wherein in the equation representing the relationship between the vehicle weight and the vehicle driving force and resistance, the vehicle weight is an unknown quantity to be solved;
solving and calculating the equation representing the relationship between the vehicle weight and the vehicle driving force and the resistance by using the parameter values of the vehicle static parameters and the parameter values of the resistance dynamic parameters at different moments to obtain a solution value of the vehicle weight;
and calculating the difference value of the vehicle weight and the unloaded vehicle weight to obtain the loaded weight.
Optionally, the vehicle driving data at least comprises a vehicle speed and a transmission gear, and the dynamic resistance parameters comprise a vehicle rolling resistance coefficient f, a road slope value α, a rotating mass conversion coefficient delta, an acceleration and a transmission ratio i corresponding to the transmission under the geargMain transmission ratio ioEngine output torque TtqThe running radius r of the wheel; the resistance includes: air resistance, vehicle acceleration resistance, road grade resistance, and rolling resistance; wherein the driving force is the torque T output by the enginetqTransmission ratio i of the transmissiongMain reducer transmission ratio ioAnd a known variable determined by a wheel running radius r, wherein r is calculated according to the empty running radius and the full running radius, the air resistance is a known variable determined by a vehicle speed, the vehicle acceleration resistance is determined by the vehicle weight, the acceleration and a rotating mass conversion factor delta, the road slope resistance is determined by the vehicle weight and a road slope value α, and the rolling resistance is determined by the vehicle weight and a vehicle rolling resistance factor f.
Optionally, the equation representing the relationship between the vehicle weight and the driving force and the resistance of the vehicle is expressed as: y ═ BK; wherein: y is the product of the driving force and the wheel running radius r; b ═ θ1,θ2,θ3,θ4]，θ1＝gfcosα，θ2＝du/dt，θ3＝1，θ4＝CDA ua 2/21.15；K＝[k1,k2,k3,k4]T，k1＝mr，k2＝δmr，k3＝mgrsinα，k4＝r；θ1And k is1Equal to the product of said rolling resistance and the running radius r of the wheel, theta2And k is2Equal to the product of said acceleration resistance and the wheel running radius r, theta3And k is3Equal to the product of said road gradient resistance and the wheel running radius r, theta4And k is4The product of (a) is equal to the product of the air resistance and the wheel running radius r.
Optionally, the solving and calculating the equation representing the relationship between the vehicle weight and the vehicle driving force and the vehicle resistance to obtain the solution value of the vehicle weight includes: solving to obtain K in K based on the parameter values of the vehicle static parameters and the parameter values of the resistance dynamic parameters at different moments by using a least square method1、k2、k3And k4The optimal solution value of (a); will k1And k is4And taking the quotient of the corresponding optimal solution value as the solution value of the vehicle weight.
Optionally, the vehicle driving data further includes: engine speed EngSpd and engine torque ToutLatitude and longitude, and elevation.
Optionally, any time is denoted as time t; the parameter value of the vehicle rolling resistance coefficient f at the time t is determined by the following method: determining the road type of the road where the vehicle is located according to the longitude and latitude corresponding to the time t; wherein, different road types correspond to different rolling resistance coefficients; the corresponding road type at the time t is a target road type; and determining the rolling resistance coefficient corresponding to the target road type as a parameter value of the vehicle rolling resistance coefficient f at the time t.
Optionally, any time is represented as time t, the parameter value of the road slope value α at the time t is determined by calculating an average vehicle speed between time t-1 and time t by using the vehicle speeds corresponding to time t-1 and time t, calculating a driving distance Dist between the time t-1 and time t according to the average vehicle speed, calculating an elevation difference Δ Alti between the time t-1 and time t by using elevations corresponding to time t-1 and time t, and calculating the parameter value of the road slope value α at the time t according to α ═ arctan (Δ Alti/Dist) or α ═ arcsin (Δ Alti/Dist).
A load estimating apparatus comprising:
an acquisition unit configured to:
acquiring vehicle driving data;
sequencing the driving data according to a time sequence;
a parameter value determination unit for:
determining a parameter value of a vehicle static parameter; the vehicle static parameters include: the idle running radius, the full-load running radius and the engine base load power of the vehicle wheels;
determining parameter values corresponding to the resistance dynamic parameters at different moments by using the vehicle static parameters and the sequenced vehicle running data;
an estimation unit for:
establishing an equation representing the relationship between the vehicle weight and the vehicle driving force and resistance according to the dynamic equation, the static parameters and the parameter values of the dynamic resistance parameters; wherein in the equation representing the relationship between the vehicle weight and the vehicle driving force and resistance, the vehicle weight is an unknown quantity to be solved;
solving and calculating the equation representing the relationship between the vehicle weight and the vehicle driving force and the resistance by using the parameter values of the vehicle static parameters and the parameter values of the resistance dynamic parameters at different moments to obtain a solution value of the vehicle weight;
and calculating the difference value of the vehicle weight and the unloaded vehicle weight to obtain the loaded weight.
Optionally, the vehicle driving data at least comprises a vehicle speed and a transmission gear, and the dynamic resistance parameters comprise a vehicle rolling resistance coefficient f, a road slope value α, a rotating mass conversion coefficient delta, an acceleration and a transmission gear ratio i corresponding to the transmission under the geargMain reducer transmission ratio ioEngine output torque TtqThe running radius r of the wheel; the resistance includes: air resistance, vehicle acceleration resistance, road grade resistance, and rolling resistance; wherein the driving force is the torque T output by the enginetqTransmission ratio i of the transmissiongMain reducer transmission ratio ioAnd a known variable determined by the wheel running radius r; the r is calculated according to the no-load running radius and the full-load running radius; the air resistance is a known variable determined by the vehicle speed; the vehicle acceleration resistance is determined by the vehicle weight, the acceleration and a rotating mass conversion coefficient delta; the road grade resistance is determined by the vehicle weight and the roadThe grade value α, and the rolling resistance is determined by the vehicle weight and the vehicle rolling resistance coefficient f.
Optionally, the equation representing the relationship between the vehicle weight and the driving force and the resistance of the vehicle is expressed as: y ═ BK; wherein: y is the product of the driving force and the wheel running radius r; b ═ θ1,θ2,θ3,θ4]，θ1＝gfcosα，θ2＝du/dt，θ3＝1，θ4＝CDA ua 2/21.15；K＝[k1,k2,k3,k4]T，k1＝mr，k2＝δmr，k3＝mgrsinα，k4＝r；θ1And k is1Equal to the product of said rolling resistance and the running radius r of the wheel, theta2And k is2Equal to the product of said acceleration resistance and the wheel running radius r, theta3And k is3Equal to the product of said road gradient resistance and the wheel running radius r, theta4And k is4The product of (a) is equal to the product of the air resistance and the wheel running radius r.
It can be seen that, in the embodiment of the present invention, vehicle driving data and vehicle static parameters are obtained, then, dynamic parameters at different times are determined by using the driving data and the vehicle static parameters, an equation representing the relationship between the vehicle weight (independent variable) and the driving force and the resistance is established according to the vehicle static parameters and the dynamic parameters, the equation is solved to obtain an estimated value of the vehicle weight, and then, a difference value between the vehicle weight and the unloaded vehicle weight is calculated to obtain the load weight. In the estimation process, the data based on the existing vehicle running data and the vehicle factory information does not need to be measured by using a load sensor, and the load mass can be acquired under the condition that the load sensor is not arranged.
Drawings
Fig. 1 is an exemplary structure of a load estimating apparatus according to an embodiment of the present invention;
fig. 2 is an exemplary interactive flow of a load estimation method according to an embodiment of the present invention;
FIG. 3 is another exemplary interactive flow of a load estimation method according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a relationship between the height difference, Dist, and the road gradient value α according to an embodiment of the present invention.
Detailed Description
The invention provides a load estimation method and a load estimation device, which are used for acquiring load mass under the condition of not arranging a load sensor.
The load estimation device can be deployed in a vehicle-mounted intelligent terminal (namely, in a vehicle), and can be used for calculating the load mass in real time in the running process of the vehicle, and also can be deployed in a background of the internet of vehicles and calculating the load mass off line.
The vehicle-mounted intelligent terminal can be specifically an ECU (electronic control unit), a T-BOX (telematics BOX), and the like.
Referring to fig. 1, the load estimation device may include an obtaining unit 1, a parameter value determination unit 2, and an estimation unit 3.
The function of each unit will be described in detail later in this document in conjunction with a load estimation method.
Fig. 2 shows an exemplary interactive flow of a load estimation method performed by the load estimation device, which may include:
s0: vehicle travel data is acquired.
Various sensors arranged in the cargo vehicle CAN send collected data to the CAN bus, namely, data signals of the sensors are collected on the CAN bus, and vehicle driving data are partial signals selected from a plurality of data signals.
If the load estimation device is deployed in the vehicle-mounted intelligent terminal, vehicle running data CAN be acquired from the CAN bus.
And if the load estimation device is deployed in the background, the vehicle running data can be acquired by transmitting the vehicle running data to the background of the Internet of vehicles through the vehicle-mounted communication terminal.
The vehicle travel data may specifically include vehicle speed, transmission gear (Gears), and the like. In addition, the method can also comprise the following steps: engine speed (EngSpd), engine torque (T)out) Longitude and latitude, elevation.
In addition, depending on the vehicle type, some vehicle types can obtain the travel (Acc) of an accelerator pedal and the transmission ratio (i) of a main speed reducer0) And the like.
The accelerator pedal travel may be used to determine acceleration, although speed may also be used to calculate acceleration.
The acquired vehicle travel data is provided by sensors already equipped in the vehicle.
S1: and sequencing the vehicle running data according to a time sequence.
Specifically, a time signal (signal is accurate to the second level) of data can be extracted, and the travel data are sorted according to the sequence of the time signal to obtain T ═ S1,S2,...,Si,...,SN],i＝1,2,...N,SiAll the traveling data signals of the vehicle at the ith moment.
For example, assuming that the vehicle driving data is collected once at a data interval of 1s, and the vehicle driving data has 10 signals, there are 10 signal data in the 1 st second and 10 signal data in the 2 nd second.
Of course, the periods of data sent by the sensors to the CAN may be different, a common signal period is millisecond, the least common multiple of each period is taken as a data interval, and then the running data at the same time is classified into a set.
In one example, the pre-processing may include washing and converting. Wherein:
the conversion may include: the unit conversion, for example, converts the unit of the vehicle speed signal from km/h to m/s.
The cleaning may include: abnormal values of signals such as vehicle speed, engine torque, acceleration and the like are removed.
Outliers include values outside of the normal range and missing values where the signal is empty. For example, assuming that the highest speed of the cargo vehicle is 120k/h, data of the speed exceeding 120km/h is deleted; for another example, if the maximum engine speed is 6500rad/min, the data with the speed greater than 6500rad/min is deleted. The other data is processed in the same manner as above.
The data signals after being cleaned and converted have high reliability and good quality, and provide guarantee for the accuracy of the following algorithm.
Steps S0 and S1 may be performed by the aforementioned acquisition unit 1.
S2: parameter values of the vehicle static parameters are determined.
Wherein the vehicle static parameters may include: empty running radius, full running radius, engine base load power P of vehicle wheelload。
The static parameters of the vehicle do not change with the change of the driving environment.
Specifically, the static parameters of the vehicle may be determined according to factory information of the vehicle. The factory information includes: the idle running radius, the full-load running radius, the engine base load power, the vehicle idle mass and the full-load mass of the vehicle wheels. There are also maximum driving speed, maximum climbing slope, maximum acceleration, etc.
S3: and determining the corresponding parameter values of the dynamic resistance parameters at different moments by using the static parameters of the vehicle and the sequenced vehicle running data.
The dynamic resistance parameter is easy to change along with the change of the driving environment. The type and calculation of the dynamic resistance parameter will be described later.
Steps S2 and S3 may be performed by the aforementioned parameter value determination unit 2.
S4: according to the dynamic mechanical equation, the static parameters and the dynamic resistance parameters, the characteristic vehicle weight m and the vehicle driving force F are establishedtResistance.
Where m denotes the empty vehicle weight + the cargo weight.
Where in the equation, the vehicle weight is the unknown to be solved for.
Specifically, the resistance may include: rolling resistance FfAir resistance FwSlope resistance FiAnd acceleration resistance Fj。
The dynamic mechanical equation of the running process of the automobile comprises Ft＝Ff+Fw+Fi+FjAnd also rolling resistance FfAir resistance FwSlope resistance FiAnd acceleration resistance FjCalculating an equation in which rolling resistance FfSlope resistance FiAnd acceleration resistance FjIn relation to the weight of the vehicle.
According to the kinetic equation, the characteristic vehicle weight m and the vehicle driving force F can be establishedtResistance.
S5: and solving and calculating the equation by using the parameter values of the static parameters of the vehicle and the parameter values of the dynamic resistance parameters at different moments to obtain a solution value of the vehicle weight.
S6: and calculating the difference value of the weight of the vehicle and the weight of the unloaded vehicle to obtain the load weight.
The weight of the unloaded vehicle is a fixed value and can be stored in advance.
Steps S4 to S6 may be performed by the aforementioned estimation unit 3.
There are various methods for solving, such as least squares, and the specific method for solving will be described later herein.
Additionally, the payload weight may also be estimated using a neural network. For example, vehicle driving data may be input into a trained neural network, and the neural network may output a corresponding estimated weight.
It can be seen that, in the embodiment of the present invention, vehicle driving data and vehicle static parameters are obtained, then, dynamic parameters at different times are determined by using the driving data and the vehicle static parameters, an equation representing the relationship between the vehicle weight (independent variable) and the driving force and the resistance is established according to the vehicle static parameters and the dynamic parameters, the equation is solved to obtain an estimated value of the vehicle weight, and then, a difference value between the vehicle weight and the unloaded vehicle weight is calculated to obtain the load weight. In the estimation process, the data based on the existing vehicle running data and the vehicle factory information does not need to be measured by using a load sensor, and the load mass can be acquired under the condition that the load sensor is not arranged.
The calculation of the dynamic parameters of the resistance, the establishment of the equation and the least square solution process will be described in detail below. Please refer to fig. 3, which may include the following steps:
s300: vehicle travel data is acquired.
Vehicle driving dataSpecifically, the vehicle speed, the transmission gear (Gears), the engine speed (EngSpd), and the engine torque (T)out) Longitude and latitude, elevation.
In addition, some vehicle types can obtain the travel (Acc) of an accelerator pedal, the transmission ratio of a main speed reducer and the like according to different vehicle types.
The acquired vehicle travel data is provided by sensors already equipped in the vehicle.
Step S300 is similar to step S0, and will not be described herein.
S301: and preprocessing the vehicle running data.
For an introduction to the preprocessing, refer to the aforementioned step S1, which is not described herein.
S302: and sequencing the vehicle running data according to a time sequence.
Step S302 is similar to step S1, and will not be described herein.
Steps S300 to S302 may be performed by the aforementioned acquisition unit 1.
S303: parameter values of the vehicle static parameters are determined.
Wherein the vehicle static parameters may include: empty running radius, full running radius, engine base load power P of vehicle wheelload。
The static parameters of the vehicle do not change with the change of the driving environment.
S304: and determining the corresponding parameter values of the dynamic resistance parameters at different moments by using the static parameters of the vehicle and the sequenced vehicle running data.
Specifically, the dynamic resistance parameters can comprise a vehicle rolling resistance coefficient f, a road slope value α, a rotating mass conversion coefficient delta, acceleration and a transmission gear ratio i corresponding to the transmission under the geargMain reducer transmission ratio ioEngine output torque TtqAnd a wheel running radius r.
The calculation method of each resistance dynamic parameter at the time t is described below.
1) Coefficient of rolling resistance f of vehicle
In one example, a fixed parameter value may be set for f.
Considering that the operation condition of the cargo vehicle is complex, the cargo vehicle may shuttle between urban roads, mountain roads or high speed, the rolling resistance coefficients of different roads have certain difference, and if a single value is used, the result deviation is caused, therefore, in another example, assuming that any time is represented as time t, the parameter value of f at time t (f) can be dynamically calculatedt)。
Specifically, the road type of the road where the vehicle is located at the time t can be obtained through the longitude and latitude corresponding to the time t.
The road types can be divided into: urban area, mountain road, high speed.
The correspondence of the road type to f is expressed as follows:
mountain roads: 0.20;
urban areas: 0.15;
high speed: 0.10.
the corresponding road type at time t may be referred to as a target road type, for example, if the target road type is a mountain road, ft＝0.20。
2) Road grade value α
Specifically, the average vehicle speed v between the time t-1 and the time t can be calculated by using the vehicle speeds corresponding to the time t-1 and the time tavg；
Calculating the driving distance Dist between the t-1 moment and the t moment according to the average vehicle speed; assuming that the time t-1 is 30 seconds different from the time t, Dist is equal to vavg*30。
And then calculating the elevation difference delta Alti between the t-1 moment and the t moment by using the elevations corresponding to the t-1 moment and the t moment.
The relationship between the height difference, Dist and the road grade value α can be seen in fig. 4, and the parameter value of α at time t can be calculated according to α ═ arctan (Δ Alti/Dist).
Further, when α is small enough, sin and tan are almost equal and approximate, so the parameter value of α at time t can also be calculated using equation α arcsin (Δ Alti/Dist).
3) Speed variator drive ratio i corresponding to speed variator under gearg
The speed variator being in each gearThe transmission ratio of the transmission is different, and the dynamic ratio i of the transmission under the gear at the moment t can be determined according to the speed ratios of the transmissions of different vehicle typesg。
igF (gears). Wherein F (#) represents a corresponding relation, igThe correspondence to Gears can be obtained by looking up a table.
4) Main reducer transmission ratio io
ioThe value of the change is small, and the change can be calculated according to the gear at the time t.
5) Coefficient of conversion of rotating mass delta
δ can be obtained by empirical formula: δ ═ 1.04+1.05 × ig 2。
6) Acceleration of
According to different vehicle types, the acceleration can be acquired, or calculated according to the vehicle speed, or calculated according to the travel of an accelerator pedal.
7) Engine output torque Ttq
Engine output torque Ttq＝Tout-TloadWherein, ToutIs the aforementioned acquired engine torque; t isloadIs the engine base load torque, TloadBased on static parameter-basic engine load power PloadAnd (4) calculating.
8) Running radius of wheel r
The wheel running radius r can be calculated according to the no-load running radius and the full-load running radius of the vehicle wheel.
S305: a least squares model equation representing the relationship between the vehicle weight m and the vehicle driving force, resistance (air resistance, vehicle acceleration resistance, road slope resistance, and rolling resistance) is established.
The least squares model equation can be expressed as: y ═ BK;
wherein:
y is the product of the driving force F and the wheel running radius r; the driving force can be represented by the formula F ═ TtqigioηTCalculated as/r, is a known variable. That is, FtTorque T output from the enginetqTransmission ratio i of the transmissiongMain reducer transmission ratio ioAnd the wheel running radius r.
B＝[θ1,θ2,θ3,θ4]，θ1＝gfcosα，θ2＝du/dt，θ3＝1，θ4＝CDA ua 2/21.15；
K＝[k1,k2,k3,k4]T，k1＝mr，k2＝δmr，k3＝mgrsinα，k4＝r；
θ1And k is1Is equal to the rolling resistance FfProduct of the radius r of travel of the wheel, theta2And k is2Is equal to the acceleration resistance FjProduct of the radius r of travel of the wheel, theta3And k is3Is equal to road slope resistance FiProduct of the radius r of travel of the wheel, theta4And k is4Is equal to the air resistance FwThe product of the wheel running radius r.
The derivation of the equation is described below:
the dynamic mechanical equation of the automobile in the running process is F ═ Ff+Fj+Fi+Fw。
F＝TtqigioηT/r；
FfGfcos α, G mg, where G is the acceleration of gravity of the earth, 9.8fDetermined by the vehicle weight and the vehicle rolling resistance coefficient F, since m is unknownfIs unknown.
Fw＝CDA ua 2/21.15，CDIs the air resistance coefficient of the vehicle, A is the windward area of the vehicle in the running process, CDAnd A is a vehicle fixed parameter, uaIs the vehicle speed and, therefore, the air resistance is a known variable determined by the vehicle speed.
FiGsin α, see road grade resistance FiDetermined by the vehicle weight m and the road grade value α, F, since m is unknowniIs unknown.
Fjδ m du/dt. du/dt represents the acceleration, visible as the vehicle acceleration resistance FjDetermined by vehicle weight m, acceleration and delta, since m is unknown, FjIs unknown.
Substituting the calculation formulas of the resistances into a kinetic equation to obtain:
TtqigioηT/r＝Gfcosα+δm*du/dt+Gsinα+CDA ua 2/21.15＝mgfcosα+δm*du/dt+mgsinα+CDA ua 2/21.15。
both sides are multiplied by r to yield:
TtqigioηT＝mgfrcosα+δmr*du/dt+mgrsinα+CDA ua 2r/21.15。
can be Y ═ TtqigioηT，k1＝mr，θ1＝gfcosα，k2＝δmr，θ2＝du/dt，k3＝mgrsinα，θ3＝1，k4＝r，θ4＝CDA ua 2/21.15。
Let matrix B ═ θ1,θ2,θ3,θ4]The matrix K ═ K1,k2,k3,k4]TThen, Y is obtained as BK.
Let YpreIs a least squares estimate, then Ypre＝BK。
S306: solving to obtain K in K based on the parameter values of the static parameters of the vehicle and the parameter values of the dynamic resistance parameters at different moments by using a least square method1、k2、k3And k4The optimal solution value of (a);
can be iterated continuously by using least squares method to make YpreInfinitely close to Y, i.e. Y and YpreThe difference of (a) is minimal.
Instead of the least square method, the relationship between Y and B, K representing different time points can be established based on the parameter values of the static parameters of the vehicle and the parameter values of the dynamic parameters of the resistance at different time pointsSolving the equation of the system, and carrying out violent solution on the equation to obtain k1、k2、k3And k4The solution value of (a).
S307: will k1And k is4The quotient of the corresponding optimal solution value is used as the solution value of the vehicle weight.
Due to k1＝mr，k4R, mixing k1Divided by k4A solution for the vehicle weight is obtained.
S308: and calculating the difference value of the weight of the vehicle and the weight of the unloaded vehicle to obtain the load weight.
The weight of the unloaded vehicle is a fixed value and can be stored in advance.
The following describes how to obtain the best solution using the least squares method.
At first (0 th, t)0Time), an initial value of K (denoted as K) is set first0) Due to k4Known, so is for k1、k2And k3The initial value is set randomly.
B at 0 th is represented as B0。
According to the initial value of K, the 0 th Y can be calculatedpre(shown as Y)pre 0)，Ypre 0＝B0K0。
Y (denoted as Y) at time 00) Are known. Let the error function L ═ Ypre-Y‖2 2Then the error (residual) at time 0 can be calculated.
In order to minimize the error function, the derivation of the error function is required.
Since L ═ Ypre-Y‖2 2＝‖BK-Y‖2 2Then, taking the derivative of K, we can obtain:
K-represents a value that makes the derivative equation equal to 0.
B is to be0And Y0Substituting to obtain the value of the next time K (denoted as K)1)：
K1＝K0-μ((B0)TB0)-1(B0)TY0And μ represents the learning rate. μ may be a fixed value or a varying value.
Next, t is calculated1Y corresponding to time (1 st iteration)pre(shown as Y)pre 1) B of the 1 st iteration is represented as B1And Y is Y1。
Ypre 1＝B1K1。
And calculating the value of K at the next moment based on the error function (expressed as K)2)：
K2＝K1-μ((B1)TB1)-1(B1)TY1。
And repeating the iteration for a plurality of times by analogy.
I.e. K used in the P-th iterationP＝KP-1-μ((BP-1)TBP-1)-1(BP-1)TYP-1。
Wherein, KP-1Is K, B at iteration P-1P-1Is B, Y at P-1 iterationP-1The driving force for the P-1 th iteration.
Referring now to the load estimating apparatus, fig. 1 is a view illustrating an exemplary structure of the load estimating apparatus, including:
an acquisition unit 1 for:
acquiring vehicle driving data;
sequencing the driving data according to a time sequence;
a parameter value determination unit 2 for:
determining the parameter value of the vehicle static parameter according to the delivery information of the vehicle; the vehicle static parameters include: the idle running radius, the full-load running radius and the engine base load power of the vehicle wheels;
determining corresponding parameter values of the dynamic resistance parameters at different moments by using the static vehicle parameters and the sequenced vehicle running data;
an estimation unit 3 for:
establishing an equation representing the relationship between the vehicle weight and the vehicle driving force and resistance according to the dynamic equation, the static parameters and the parameter values of the dynamic resistance parameters; wherein, in the equation, the vehicle weight is an unknown quantity to be solved;
solving and calculating the equation by using the parameter values of the vehicle static parameters and the parameter values of the resistance dynamic parameters at different moments to obtain a solution value of the vehicle weight;
and calculating the difference value of the weight of the vehicle and the weight of the unloaded vehicle to obtain the load weight.
For details, please refer to the above description, which is not repeated herein.
In other embodiments, the vehicle travel data in all the above embodiments includes at least: vehicle speed and transmission gear.
In other embodiments, the vehicle travel data in all the above embodiments further includes: engine speed EngSpd and engine torque ToutLatitude and longitude, and elevation.
The dynamic resistance parameters comprise a vehicle rolling resistance coefficient f, a road grade value α, a rotating mass conversion coefficient delta, acceleration and a transmission gear ratio i corresponding to the transmission under a geargMain reducer transmission ratio ioEngine output torque TtqThe running radius r of the wheel;
the resistance comprises: air resistance, vehicle acceleration resistance, road grade resistance, and rolling resistance;
wherein the driving force is torque T output by the enginetqTransmission ratio i of the transmissiongMain reducer transmission ratio ioAnd a known variable determined by the wheel running radius r; r is calculated according to the no-load running radius and the full-load running radius;
air resistance is a known variable determined by vehicle speed;
the acceleration resistance of the vehicle is determined by the conversion coefficient delta of the weight, the acceleration and the rotating mass of the vehicle;
road slope resistance is determined by vehicle weight and road slope value α;
the rolling resistance is determined by the vehicle weight and the vehicle rolling resistance coefficient f.
For details, please refer to the above description, which is not repeated herein.
In other embodiments, the equations in all of the above embodiments are expressed as: y ═ BK;
wherein:
y is the product of the driving force and the wheel running radius r;
B＝[θ1,θ2,θ3,θ4]，θ1＝gfcosα，θ2＝du/dt，θ3＝1，θ4＝CDA ua 2/21.15；
K＝[k1,k2,k3,k4]T，k1＝mr，k2＝δmr，k3＝mgrsinα，k4＝r；
θ1and k is1Equal to the product of the rolling resistance and the running radius r of the wheel, theta2And k is2Equal to the product of the acceleration resistance and the wheel running radius r, theta3And k is3Equal to the product of the road slope resistance and the wheel running radius r, theta4And k is4The product of (a) is equal to the product of the air resistance and the wheel running radius r.
For details, please refer to the above description, which is not repeated herein.
In other embodiments, K is a coefficient to be solved;
in terms of solving and calculating the equation to obtain a solution value of the vehicle weight, the estimation unit 3 may be specifically configured to:
solving to obtain K in K based on the parameter values of the static parameters of the vehicle and the parameter values of the dynamic resistance parameters at different moments by using a least square method1、k2、k3And k4The optimal solution value of (a);
will k1And k is4Of the corresponding optimum solution valueThe quotient is used as a solution value for the vehicle weight.
For details, please refer to the above description, which is not repeated herein.
Any time may be denoted as time t. In other embodiments, the parameter value of the vehicle rolling resistance coefficient f at the time t may be determined as follows:
determining the road type of the road where the vehicle is located according to the longitude and latitude corresponding to the time t; wherein, different road types correspond to different rolling resistance coefficients; the corresponding road type at the time t is a target road type;
and determining the rolling resistance coefficient corresponding to the target road type as a parameter value of the vehicle rolling resistance coefficient f at the time t.
The parameter value of the road grade value α at time t is determined as follows:
calculating the average speed between the t-1 moment and the t moment by using the speeds corresponding to the t-1 moment and the t moment;
calculating the driving distance Dist between the t-1 moment and the t moment according to the average vehicle speed;
calculating the elevation difference delta Alti between the t-1 moment and the t moment by using the elevations corresponding to the t-1 moment and the t moment;
the parameter value of the road grade value α at time t is calculated according to α ═ arctan (Δ Alti/Dist) or α ═ arcsin (Δ Alti/Dist).
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is simple, and the description can be referred to the method part.
Those of skill would further appreciate that the various illustrative components and model steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or model described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, WD-ROM, or any other form of storage medium known in the art.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A method of estimating a load, comprising:
acquiring vehicle driving data;
sequencing the driving data according to a time sequence;
determining a parameter value of a vehicle static parameter; the vehicle static parameters include: the idle running radius, the full-load running radius and the engine base load power of the vehicle wheels;
determining parameter values corresponding to the resistance dynamic parameters at different moments by using the vehicle static parameters and the sequenced vehicle running data;
establishing an equation representing the relationship between the vehicle weight and the vehicle driving force and resistance according to the dynamic equation, the static parameters and the parameter values of the dynamic resistance parameters; wherein in the equation representing the relationship between the vehicle weight and the vehicle driving force and resistance, the vehicle weight is an unknown quantity to be solved;
solving and calculating the equation representing the relationship between the vehicle weight and the vehicle driving force and the resistance by using the parameter values of the vehicle static parameters and the parameter values of the resistance dynamic parameters at different moments to obtain a solution value of the vehicle weight;
and calculating the difference value of the vehicle weight and the unloaded vehicle weight to obtain the loaded weight.
2. The method of claim 1,
the vehicle travel data includes at least: vehicle speed and transmission gear;
the dynamic resistance parameters comprise a vehicle rolling resistance coefficient f, a road slope value α, a rotating mass conversion coefficient delta, acceleration and a transmission ratio i corresponding to the transmission under a geargMain transmission ratio ioEngine output torque TtqThe running radius r of the wheel;
the resistance includes: air resistance, vehicle acceleration resistance, road grade resistance, and rolling resistance;
wherein the driving force is the torque T output by the enginetqTransmission ratio i of the transmissiongMain reducer transmission ratio ioAnd a known variable determined by the wheel running radius r; the r is calculated according to the no-load running radius and the full-load running radius;
the air resistance is a known variable determined by the vehicle speed;
the vehicle acceleration resistance is determined by the vehicle weight, the acceleration and a rotating mass conversion coefficient delta;
the road slope resistance is determined by the vehicle weight and a road slope value α;
the rolling resistance is determined by the vehicle weight and a vehicle rolling resistance coefficient f.
3. The method of claim 2,
the equation representing the relationship between the vehicle weight and the vehicle driving force and resistance is expressed as: y ═ BK;
wherein:
y is the product of the driving force and the wheel running radius r;
B＝[θ1,θ2,θ3,θ4]，θ1＝gfcosα，θ2＝du/dt，θ3＝1，θ4＝CDA ua 2/21.15；
K＝[k1,k2,k3,k4]T，k1＝mr，k2＝δmr，k3＝mgrsinα，k4＝r；
θ1and k is1Equal to the product of said rolling resistance and the running radius r of the wheel, theta2And k is2Equal to the product of said acceleration resistance and the wheel running radius r, theta3And k is3Equal to the product of said road gradient resistance and the wheel running radius r, theta4And k is4The product of (a) is equal to the product of the air resistance and the wheel running radius r.
4. The method of claim 3,
solving and calculating the equation representing the relationship between the vehicle weight and the vehicle driving force and resistance to obtain a solution value of the vehicle weight comprises:
solving to obtain K in K based on the parameter values of the vehicle static parameters and the parameter values of the resistance dynamic parameters at different moments by using a least square method1、k2、k3And k4The optimal solution value of (a);
will k1And k is4And taking the quotient of the corresponding optimal solution value as the solution value of the vehicle weight.
5. The method of claim 3, wherein the vehicle travel data further comprises: engine speed EngSpd, startingMechanical torque ToutLatitude and longitude, and elevation.
6. The method of claim 5,
any time is denoted as time t;
the parameter value of the vehicle rolling resistance coefficient f at the time t is determined by the following method:
determining the road type of the road where the vehicle is located according to the longitude and latitude corresponding to the time t; wherein, different road types correspond to different rolling resistance coefficients; the corresponding road type at the time t is a target road type;
and determining the rolling resistance coefficient corresponding to the target road type as a parameter value of the vehicle rolling resistance coefficient f at the time t.
7. The method of claim 5,
any time is denoted as time t;
the parameter value of the road grade value α at the time t is determined as follows:
calculating the average speed between the t-1 moment and the t moment by using the speeds corresponding to the t-1 moment and the t moment;
calculating the driving distance Dist between the t-1 moment and the t moment according to the average vehicle speed;
calculating the elevation difference delta Alti between the t-1 moment and the t moment by using the elevations corresponding to the t-1 moment and the t moment;
the parameter value of the road grade value α at the time t is calculated according to α ═ arctan (Δ Alti/Dist) or α ═ arcsin (Δ Alti/Dist).
8. A load estimating apparatus, characterized by comprising:
an acquisition unit configured to:
acquiring vehicle driving data;
sequencing the driving data according to a time sequence;
a parameter value determination unit for:
determining a parameter value of a vehicle static parameter; the vehicle static parameters include: the idle running radius, the full-load running radius and the engine base load power of the vehicle wheels;
determining parameter values corresponding to the resistance dynamic parameters at different moments by using the vehicle static parameters and the sequenced vehicle running data;
an estimation unit for:
establishing an equation representing the relationship between the vehicle weight and the vehicle driving force and resistance according to the dynamic equation, the static parameters and the parameter values of the dynamic resistance parameters; wherein in the equation representing the relationship between the vehicle weight and the vehicle driving force and resistance, the vehicle weight is an unknown quantity to be solved;
solving and calculating the equation representing the relationship between the vehicle weight and the vehicle driving force and the resistance by using the parameter values of the vehicle static parameters and the parameter values of the resistance dynamic parameters at different moments to obtain a solution value of the vehicle weight;
and calculating the difference value of the vehicle weight and the unloaded vehicle weight to obtain the loaded weight.
9. The load estimation device according to claim 8,
the vehicle travel data includes at least: vehicle speed and transmission gear;
the dynamic resistance parameters comprise a vehicle rolling resistance coefficient f, a road slope value α, a rotating mass conversion coefficient delta, acceleration and a transmission gear ratio i corresponding to the transmission under a geargMain reducer transmission ratio ioEngine output torque TtqThe running radius r of the wheel;
the resistance includes: air resistance, vehicle acceleration resistance, road grade resistance, and rolling resistance;
wherein the driving force is the torque T output by the enginetqTransmission ratio i of the transmissiongMain reducer transmission ratio ioAnd a known variable determined by the wheel running radius r; r is based on the empty running radius and the full running radiusCalculating;
the air resistance is a known variable determined by the vehicle speed;
the vehicle acceleration resistance is determined by the vehicle weight, the acceleration and a rotating mass conversion coefficient delta;
the road slope resistance is determined by the vehicle weight and a road slope value α;
the rolling resistance is determined by the vehicle weight and a vehicle rolling resistance coefficient f.
10. The load estimation device according to claim 9,
the equation representing the relationship between the vehicle weight and the vehicle driving force and resistance is expressed as: y ═ BK;
wherein:
y is the product of the driving force and the wheel running radius r;
B＝[θ1,θ2,θ3,θ4]，θ1＝gfcosα，θ2＝du/dt，θ3＝1，θ4＝CDA ua 2/21.15；
K＝[k1,k2,k3,k4]T，k1＝mr，k2＝δmr，k3＝mgrsinα，k4＝r；
θ1and k is1Equal to the product of said rolling resistance and the running radius r of the wheel, theta2And k is2Equal to the product of said acceleration resistance and the wheel running radius r, theta3And k is3Equal to the product of said road gradient resistance and the wheel running radius r, theta4And k is4The product of (a) is equal to the product of the air resistance and the wheel running radius r.
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