CN114852093B - Method and device for estimating train weight of semi-trailer train and electronic equipment - Google Patents
Method and device for estimating train weight of semi-trailer train and electronic equipment Download PDFInfo
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Abstract
The application discloses a method and a device for estimating train weight of a semi-trailer train and electronic equipment. The method of the application comprises the following steps: acquiring the last state information of a semi-trailer train, and monitoring target state parameters of the semi-trailer train; determining current state information of the semi-trailer train according to the previous state information and the target state parameter; and determining a vehicle weight estimation model according to the current state information, and obtaining the whole vehicle weight estimation value of the semi-trailer train in the current state through the vehicle weight estimation model. The technical scheme of the application can improve the accuracy of the whole train weight estimated value of the semi-trailer train.
Description
Technical Field
The present application relates to the field of information processing technologies, and in particular, to a method and an apparatus for estimating train weight of a semi-trailer train, and an electronic device.
Background
At present, a semi-trailer train has the characteristic of large whole vehicle weight change range interval, and when the semi-trailer train operates, the connection state of the semi-trailer and the cargo carrying state of the semi-trailer have great influence on the power control and the safety control of the semi-trailer train. Therefore, when the whole weight of the semi-trailer train is estimated, the more accurate the whole weight estimation value is, the less the influence is on the power control and the safety control of the semi-trailer train.
In the related art, the method for estimating the mass of the whole vehicle is as follows: acquiring signals such as torque, vehicle speed, acceleration, gradient and the like of an engine or a driving motor, and acquiring parameters such as transmission ratio of a transmission system, efficiency of the transmission system, rolling radius of wheels, rolling resistance coefficient, air resistance coefficient, windward area, rotational inertia conversion coefficient and the like; substituting the acquired signals and parameters into an automobile running equation, and estimating the quality of the whole automobile by combining a least square method or Kalman filtering.
In the process of estimating the vehicle weight, the related art has at least the following defects:
first, since the specific power and hundred kilometers acceleration of the semi-trailer train are far lower than those of the passenger train, the absolute value of the acceleration of the semi-trailer train is usually not more than 1m/s 2 The existing vehicle weight estimation method is caused to use signals with larger noise occupation and low estimation accuracy.
Secondly, the existing vehicle weight estimation method generally adopts the whole vehicle preparation quality as an initial value, but for the semitrailer and the tractor whole vehicle in a connected state, the total mass of the whole vehicle is 5-6 times that of the semitrailer and the tractor whole vehicle in a single tractor state, and in the case, the convergence speed of the calculation result of the existing vehicle weight estimation method by adopting a least square method or Kalman filtering is too slow, or even not converged.
Third, the existing vehicle weight estimating method adopts transient values of signals such as torque, vehicle speed, acceleration, gradient and the like of an engine or a driving motor, and factors such as uneven pavement, acceleration hysteresis caused by elasticity of a transmission system and the like seriously influence the vehicle weight estimating precision.
Disclosure of Invention
The embodiment of the application provides a method and a device for estimating the train weight of a semi-trailer train and electronic equipment, so as to improve the accuracy of the estimated value of the whole train weight.
The embodiment of the application adopts the following technical scheme:
in a first aspect, an embodiment of the present application provides a method for estimating a train weight of a semi-trailer, including:
acquiring the last state information of a semi-trailer train, and monitoring target state parameters of the semi-trailer train;
determining current state information of the semi-trailer train according to the previous state information and the target state parameter;
and determining a vehicle weight estimation model according to the current state information, and obtaining the whole vehicle weight estimation value of the semi-trailer train in the current state through the vehicle weight estimation model.
In a second aspect, an embodiment of the present application further provides a device for estimating a train weight of a semi-trailer, including:
the system comprises a data acquisition unit, a data processing unit and a data processing unit, wherein the data acquisition unit is used for acquiring the last state information of a semi-trailer train and monitoring target state parameters of the semi-trailer train, and the semi-trailer train comprises a tractor and a semi-trailer;
The state determining unit is used for determining the current state information of the semi-trailer train according to the previous state information and the target state parameter;
and the vehicle weight estimation unit is used for determining a vehicle weight estimation model according to the current state information, and obtaining the whole vehicle weight estimation value of the semi-trailer train in the current state through the vehicle weight estimation model.
In a third aspect, an embodiment of the present application further provides an electronic device, including:
a processor; and
a memory arranged to store computer executable instructions that, when executed, cause the processor to perform any of the semi-trailer train weight estimation methods described previously.
In a fourth aspect, embodiments of the present application also provide a computer-readable storage medium storing one or more programs that, when executed by an electronic device comprising a plurality of application programs, cause the electronic device to perform any of the aforementioned half-on-car train weight estimation methods.
The above at least one technical scheme adopted by the embodiment of the application can achieve the following beneficial effects: the method, the device, the electronic equipment and the computer readable storage medium for estimating the train weight of the semi-trailer train acquire the last state information of the semi-trailer train and monitor the target state parameters of the semi-trailer train in real time.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:
FIG. 1 is a schematic flow chart of a method for estimating train weight of a semi-trailer in an embodiment of the application;
FIG. 2 is a schematic diagram of a semi-trailer train in an embodiment of the present application;
FIG. 3 is a schematic diagram of a vehicle state transition for a semi-trailer train in accordance with an embodiment of the present application;
FIG. 4 is a schematic diagram of the geometry of a semi-trailer train in accordance with an embodiment of the present application;
FIG. 5 is a schematic diagram of a train weight estimation device for a semi-trailer in an embodiment of the present application;
fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be clearly and completely described below with reference to specific embodiments of the present application and corresponding drawings. It will be apparent that the described embodiments are only some, but not all, embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The following describes in detail the technical solutions provided by the embodiments of the present application with reference to the accompanying drawings.
The embodiment of the application provides a method for estimating the train weight of a semi-trailer, as shown in fig. 1, and provides a flow diagram of the method for estimating the train weight of the semi-trailer, which at least comprises the following steps S110 to S130:
step S110, the last state information of the semi-trailer train is obtained, and target state parameters of the semi-trailer train are monitored.
The vehicle weight estimation method of the present embodiment is recommended to be integrated in an autopilot domain controller, a power domain controller or a chassis domain controller, i.e., the vehicle weight estimation method may be executed by the autopilot domain controller, the power domain controller or the chassis domain controller. The autopilot controller herein refers to a controller integrated with autopilot software of a vehicle, and for example, includes algorithms such as positioning, environment sensing, planning control, and the like, and may have built-in functions such as adaptive cruising, lane keeping, pilot assistance, automatic parking, remote parking, self-learning parking, automatic passenger parking, automatic emergency braking, and the like. The power domain controller is used for controlling a vehicle power system and a transmission system, and integrates functions such as power on/off control, whole vehicle energy management, whole vehicle fault management, whole vehicle torque control, power battery management, charging control, driving motor control, range extender control, transmission control and the like. The chassis domain controller is a chassis system for controlling a vehicle, and integrates functions such as service brake control, parking brake control, electronic stability control, electric power steering control, active suspension control, and the like.
As shown in fig. 2, the semitrailer train in the embodiment of the application comprises a tractor and a semitrailer, wherein the tractor and the semitrailer are connected through a traction seat arranged on the tractor, and the connection state of the semitrailer and the tractor can be determined through a chassis domain controller.
As described above, in the semi-trailer of the semi-trailer in different connection states or in the loading states of the semi-trailer such as no-load, half-load and full-load, the whole vehicle weight of the semi-trailer is greatly different, in the prior art, the vehicle weight estimation model designed by the different state information of the semi-trailer is not distinguished, usually includes more model parameters, the convergence speed of the least square method or the kalman filter calculation result of the vehicle weight estimation model is too slow, even is not converged, and the signals used by most of the model parameters have the conditions of large noise ratio and large signal value as transient values, so that the vehicle weight estimation accuracy is poor.
In view of this situation, the present embodiment designs corresponding weight estimation models according to different state information of the semi-trailer train, and because each weight estimation model is only specific to a specific scene, the model is simpler, and the integral value of the transient value in a period of time is used in the calculation process of model parameters, so as to eliminate the influence of adverse factors such as uneven road surface, acceleration lag caused by elasticity of a transmission system, and the like on the weight estimation accuracy.
In addition, the design target state parameter in the embodiment is a parameter related to the state information of the switching semi-trailer train, so that the current state information of the semi-trailer train can be determined according to the last state information of the semi-trailer train and the monitored target state parameter, and a weight estimation model which should be adopted under the current state information is determined.
Step S120, determining the current state information of the semi-trailer train according to the previous state information and the target state parameters.
And step S130, determining a weight estimation model according to the current state information, and obtaining the whole weight estimation value of the semi-trailer train in the current state through the weight estimation model.
Based on the weight estimation method shown in fig. 1, the embodiment obtains the last state information of the semi-trailer train, monitors the target state parameter of the semi-trailer train in real time, and because different state information corresponds to different weight estimation models, and the target state parameter is a parameter related to the state information of the switching semi-trailer train, the current state information of the semi-trailer train can be determined according to the last state information and the target state parameter, so as to select the corresponding weight estimation model to estimate the whole weight estimation value of the semi-trailer train in the current state, and improve the whole weight estimation precision of the semi-trailer train.
In one embodiment of the application, the state information of the semi-trailer train in a period of time can be stored in the local memory of the controller, and the state information in the period of time at least comprises one historical state information of the semi-trailer train, so that the last state information of the semi-trailer train can be obtained from the local memory of the controller. Of course, the historical state information of the semi-trailer train can also be written into a preset database, and the last state information can be obtained from the historical state information recorded in the database.
In one embodiment of the application, when the estimated whole weight value of the semi-trailer train in the current state is obtained through the weight estimation model, the estimated whole weight value corresponding to the last state information of the semi-trailer train is used before the estimated whole weight value is obtained;
before the semi-trailer train is in sleep mode, the current overall weight estimate of the semi-trailer train is saved to a preset storage area, which is optionally a live erasable programmable read-write memory (Electrically Erasable Programmable Read Only Memory, abbreviated as EEPROM).
In one embodiment of the present application, each state information of the semi-trailer train includes a state switching condition for switching to other state information, based on which, when determining the current state information of the semi-trailer train according to the previous state information and the target state parameter, the state switching condition corresponding to the previous state information may be acquired, whether the semi-trailer train meets the state switching condition is determined according to the target state parameter, and when the state switching condition is met, the state information of the semi-trailer train is switched to the current state information meeting the state switching condition.
According to the embodiment of the application, the state information of the semi-trailer train is set to at least comprise an initial state, a single-tractor state, a third-party train weight detection state and a train weight dynamic detection state according to the general working scene of the semi-trailer train in advance.
The initial state refers to that the semi-trailer train is determined to be in the initial state when the controller of the semi-trailer train is awakened, and the scene that the controller is awakened includes that the controller is awakened from a sleep mode or the controller is electrified to be awakened in a power-off mode. The single tractor state means that the semitrailer is not connected to the tractor by a fifth wheel. The third party weight detection state refers to that the weight of the vehicle is detected by the third party when the third party is located at a target geographic position, and the third party is related to a preset target address position. The dynamic detection state of the vehicle weight refers to that when the semitrailer is connected to the tractor through a traction seat and is not in a target geographic position, the vehicle weight is estimated through the self-train parameters of the semitrailer train, and the vehicle weight is estimated mainly through the output value of a shaft load sensor. In practical applications, the axle load sensor may not be configured in the semi-trailer train, or the axle load sensor may be unavailable due to failure, and at this time, the weight of the train may be estimated according to the law of conservation of energy. That is, the vehicle weight dynamic detection state includes a first sub-state that estimates the vehicle weight by the output value of the axle load sensor and a second sub-state that estimates the vehicle weight by the law of conservation of energy.
The target state parameters at least comprise a communication state parameter, a semitrailer train position information, a semitrailer connection state parameter, a semitrailer hatch cover state parameter, a gear switching parameter and a tractor driving wheel axle load validity parameter, wherein the communication state parameter, the semitrailer train position information, the semitrailer connection state parameter, the semitrailer hatch cover state parameter and the gear switching parameter are dynamic change parameters, and the tractor driving wheel axle load validity parameter is a static attribute parameter and generally cannot change in a primary initialization process of the vehicle.
In this embodiment, a communication establishment success signal corresponding to a communication state parameter may be obtained through bottom software of a controller, where the communication establishment success signal refers to a communication establishment success signal generated by responding to a test signal sent by another controller after the controller executing the method for estimating the train weight of a semi-trailer train in this embodiment establishes stable communication connection with the other controller, that is, only after the controller establishes stable communication connection with the other controller, the generated communication establishment success signal is a trusted signal, so that it can be ensured that state information determined based on the communication state parameter is reliable.
In this embodiment, the semitrailer connection state parameter may be acquired by the chassis domain controller, for example, setting the connection state of the fifth wheel on the tractor to include the semitrailer being unconnected and the semitrailer being connected, where a connection state signal "1" provided by the chassis domain controller indicates that the semitrailer is in the connection state, and a connection state signal "0" provided by the chassis domain controller indicates that the semitrailer is in the unconnected state.
In this embodiment, the position information of the semi-trailer train may be acquired based on a high-precision Map (High Definition Map, abbreviated as HD Map), which is machine-oriented Map data for automatically driving the car, and has sub-meter positioning capability, road-level and lane-level planning capability, lane-level guidance capability, and information including sub-meter (20 cm) positioning, gradient, curvature, heading, elevation, roll data, traffic sign, speed limit, and the like of each lane. The high-precision map can dynamically determine whether the semi-trailer train is at the target geographic position, where the target geographic position includes, for example, a high-speed toll gate window and a configurable geographic position, and for convenience of description, the following embodiment uses the target geographic position as the high-speed toll gate window, and those skilled in the art can understand that the geographic position where the weight of the semi-trailer train can be detected by a third party and the weight of the semi-trailer train can be obtained by the self-trailer train can be the target geographic position in the embodiment, and it should be noted that the reliability of the third party weight detection result provided at the target geographic position should be ensured.
In this embodiment, the semitrailer hatch state parameter value may be obtained through the semitrailer hatch state signal provided by the chassis domain controller, and in this embodiment, the semitrailer hatch is determined to be in a closed state or a non-closed state based on the semitrailer hatch state parameter value, when the semitrailer hatch is in the non-closed state, the cargo in the semitrailer of the semitrailer train in the driving state may fall, and under this state, the whole vehicle weight of the semitrailer train may be always changed, and at this time, the third party vehicle weight detection method is no longer applicable.
In this embodiment, the value of the axle load validity parameter of the traction vehicle driving wheel can be obtained through the axle load signal of the traction vehicle driving wheel provided by the chassis domain controller, and when the axle load sensor is not configured in the semi-trailer train or the axle load sensor fails, the axle load validity parameter of the traction vehicle driving wheel is invalid.
In this embodiment, the gear shift parameter value may be obtained by a gear shift signal provided by a power domain controller or an electronically controlled air suspension. Because the road surface is uneven and jolt exists in the running process of the semi-trailer train, the weighing value of the axle load sensor always fluctuates and loses the reference value; the estimated value of the whole vehicle weight is mainly used for controlling dynamics of the vehicle and controlling a safety system, so that the estimated value of the whole vehicle weight can meet application requirements before a semi-trailer train runs.
The non-power gear is a gear for cutting off the power output of the vehicle and comprises a P gear (also called a parking gear) and an N gear (also called a neutral gear); the power range refers to a range in which the vehicle can travel, and includes, but is not limited to, a D range (also referred to as a forward range), an S range (also referred to as a sporty range), an R range (also referred to as a reverse range), and the like.
The state switching conditions and the switching process between the respective state information in the embodiment of the present application will be described with reference to the state transition diagram shown in fig. 3, with respect to the state information and the target state parameter provided in the above embodiment.
And when the previous state information corresponds to the initial state, judging whether the target state parameter meets the following conditions a1 and b1, if so, determining that the semi-trailer train meets the state switching condition for switching the initial state to the single-trailer state, and determining that the current state information of the semi-trailer train is the single-trailer state.
a1, the communication state parameters are that the communication is successfully established;
b1, the semitrailer connection state parameter is that the semitrailer is not connected.
Otherwise, judging whether the target state parameters meet the following conditions a2, b2, c2 and d2, if so, determining that the semi-trailer train meets the state switching condition for switching the initial state into the third-party train weight detection state, and determining that the current state information of the semi-trailer train is the third-party train weight detection state.
a2, the communication state parameters are that the communication is successfully established;
b2, the semitrailer connection state parameter is semitrailer connection;
c2, the position information of the semi-trailer train is that the semi-trailer train is located at a target geographic position (namely a high-speed toll gate window in FIG. 3);
d2, closing the semitrailer hatch cover according to the semitrailer hatch cover state parameter.
Otherwise, judging whether the target state parameters meet the following conditions of a3, b3, c3, d3, e3 and f3, if so, determining that the semi-trailer train meets the state switching condition of switching the initial state into the first sub-state of the dynamic detection state of the weight of the vehicle, and determining that the current state information of the semi-trailer train is the first sub-state of the dynamic detection state of the weight of the vehicle.
a3, the communication state parameters are that the communication is established successfully;
b3, the semitrailer connection state parameter is semitrailer connection;
c3, the position information of the semi-trailer train is that the semi-trailer train is not located at the target geographic position, namely the semi-trailer train is not located at a high-speed toll gate window;
d3, closing the semitrailer hatch according to the semitrailer hatch state parameter;
e3, the axle load validity parameter of the traction vehicle driving wheel is valid;
f3, the gear switching parameter is to switch from the non-power gear to the power gear.
Otherwise, finally judging whether the target state parameters meet the following conditions of a4, b4, c4, d4 and e4, if so, determining that the semi-trailer train meets the state switching condition of switching the initial state into the second sub-state of the dynamic detection state of the weight of the vehicle, and determining that the current state information of the semi-trailer train is the second sub-state of the dynamic detection state of the weight of the vehicle.
a4, the communication state parameters are that the communication is established successfully;
b4, the semitrailer connection state parameter is semitrailer connection;
c4, the position information of the semi-trailer train is that the semi-trailer train is not located at the target geographic position, namely the semi-trailer train is not located at a high-speed toll gate window;
d4, closing the semitrailer hatch according to the semitrailer hatch state parameter;
and e4, invalidating the axle load validity parameter of the traction vehicle driving wheel.
And when the previous state information corresponds to the single tractor state, judging whether the target state parameter meets the following conditions a5, b5 and c5, if so, determining that the semi-trailer train meets the state switching condition for switching the single tractor state to the third party weight detection state, and determining that the current state information of the semi-trailer train is the third party weight detection state.
a5, semitrailer connection state parameters are semitrailer connection;
b5, the position information of the semi-trailer train is that the semi-trailer train is positioned at the target geographic position;
and c5, closing the semitrailer hatch cover according to the semitrailer hatch cover state parameter.
Otherwise, judging whether the target state parameters meet the following conditions of a6, b6, c6, d6 and e6, if so, determining that the semi-trailer train meets the state switching condition for switching the single-trailer state into the first sub-state, and determining that the current state information of the semi-trailer train is the first sub-state of the dynamic detection state of the vehicle weight.
a6, semitrailer connection state parameters are semitrailer connection;
b6, the position information of the semi-trailer train is that the semi-trailer train is not located at the target geographic position, namely the semi-trailer train is not located at a high-speed toll gate window;
c6, closing the semitrailer hatch according to the semitrailer hatch state parameter;
d6, the axle load validity parameter of the traction vehicle driving wheel is valid;
and e6, switching the gear switching parameter from the non-power gear to the power gear.
Otherwise, finally judging whether the target state parameters meet the following conditions a7, b7 and c7, if so, determining that the semi-trailer train meets the state switching condition for switching the single tractor state into the second sub-state, and determining that the current state information of the semi-trailer train is the second sub-state of the dynamic detection state of the vehicle weight.
a7, semitrailer connection state parameters are semitrailer connection;
b7, the position information of the semi-trailer train is that the semi-trailer train is not located at the target geographic position, namely the semi-trailer train is not located at a high-speed toll gate window;
and c7, invalidating the axle load validity parameter of the traction vehicle driving wheel.
When the previous state information corresponds to a third-party vehicle weight detection state, judging whether the semitrailer connection state parameter in the target state parameter is the semitrailer unconnected state or not, if the semitrailer connection state parameter is the semitrailer unconnected state, determining that the semitrailer train meets the state switching condition of switching the third-party vehicle weight detection state to the single-tractor state, and determining that the current state information of the semitrailer train is the single-tractor state.
Otherwise, judging whether the target state parameters meet the following conditions of a8, b8, c8 and d8, if so, determining that the semi-trailer train meets the state switching condition for switching the third-party train weight detection state into the first sub-state, and determining that the current state information of the semi-trailer train is the first sub-state of the train weight dynamic detection state.
a8, semitrailer connection state parameters are semitrailer connection;
b8, the position information of the semi-trailer train is that the semi-trailer train is not located at the target geographic position, namely the semi-trailer train is not located at a high-speed toll gate window;
c8, the state parameter of the semitrailer hatch is that the semitrailer hatch is not closed;
d8, the axle load validity parameter of the traction vehicle driving wheel is valid.
Otherwise, finally judging whether the target state parameters meet the following conditions of a9, b9, c9 and d9, if so, determining that the semi-trailer train meets the state switching condition for switching the third party train weight detection state into the second sub-state, and determining that the current state information of the semi-trailer train is the second sub-state of the train weight dynamic detection state.
a9, semitrailer connection state parameters are semitrailer connection;
b9, the position information of the semi-trailer train is that the semi-trailer train is not located at the target geographic position, namely the semi-trailer train is not located at a high-speed toll gate window;
c9, the semitrailer hatch state parameter is that the semitrailer hatch is not closed;
d9, the axle load validity parameter of the traction vehicle driving wheel is invalid.
When the previous state information corresponds to a first sub-state of the vehicle weight dynamic detection state, judging whether the semitrailer connection state parameter in the target state parameter is unconnected with the semitrailer or not, if the semitrailer connection state parameter is unconnected with the semitrailer, determining that the semitrailer train meets the state switching condition of switching the first sub-state to the single-tractor state, and determining that the current state information of the semitrailer train is the single-tractor state. And judging conditions a10, b10 and c10 in the target state parameters, and if the condition that the semi-trailer train meets the state switching condition for switching the first sub-state into the third-party train weight detection state is met, determining the current state information of the semi-trailer train as the third-party train weight detection state.
Similarly, when the previous state information corresponds to a second sub-state of the dynamic vehicle weight detection state, judging whether the semitrailer connection state parameter in the target state parameter is unconnected with the semitrailer, if the semitrailer connection state parameter is unconnected with the semitrailer, determining that the semitrailer train meets the state switching condition of switching the second sub-state to the single-tractor state, and determining that the current state information of the semitrailer train is the single-tractor state. And judging conditions a10, b10 and c10 in the target state parameters, and if the condition that the semi-trailer train meets the state switching condition for switching the second sub-state to the third-party train weight detection state is met, determining the current state information of the semi-trailer train to be the third-party train weight detection state.
a10, semitrailer connection state parameters are semitrailer connection;
b10, the position information of the semi-trailer train is that the semi-trailer train is positioned at a target geographic position;
and c10, closing the semitrailer hatch cover according to the semitrailer hatch cover state parameter.
The first estimation model in this embodiment is:
m＝m 1 ＝m traction and pull +m Human body +m Oil (oil) (1)
In the formula (1), m is an estimated value of the whole vehicle weight, and the unit is kg; m is m 1 The unit is kg of the total mass of the tractor; m is m Traction and pull The quality of the tractor is prepared in kg; m is m Human body The weight of the passenger is kg; m is m Oil (oil) Is the fuel oil mass unit of kg。
In practice, the mass of a single occupant may be set to 70kg (although the mass of a single occupant may be set to other values, and in the alternative, the mass of each occupant may be detected by a gravity sensor), the number of occupants n being provided by a seat occupancy sensor, the mass of each occupant m Human body ＝70×n kg。
For the fuel-powered semi-trailer train, the fuel quality needs to be considered, the residual fuel volume V is provided by a fuel quantity sensor, and the fuel quality m Oil (oil) ＝ρV kg。
As can be seen from formula (1), m Human body And m is equal to Oil (oil) As a variable, m should be obtained when estimating the estimated total vehicle weight using the first estimation model Human body And m is equal to Oil (oil) Parameter values.
The second estimation model is:
in the formula (2), m is an estimated value of the whole vehicle weight, and the unit is kg; m is m Driving device The unit is kg of a weighing value of the axle load of the driving axle of the tractor; as shown in fig. 4, a is the horizontal distance from the center of mass of the tractor to the front axle of the tractor, in m; b is the horizontal distance from the center of mass of the tractor to the rear support center of the tractor, and the unit is m; c is the horizontal distance from the center of mass of the semitrailer to the rear support center of the tractor, and the unit is m; d is the horizontal distance from the center of mass of the semitrailer to the rear support center of the semitrailer, and the unit is m.
As can be seen from formula (2), m Driving device As a variable, m should be obtained when estimating the estimated total vehicle weight using the second estimation model Driving device As described above, the weighing value of the axle load sensor will fluctuate due to the influence of uneven road surface, and thus m Driving device In the present embodiment, the weighing value of the axle load sensor at the time of switching the semi-trailer train from the non-power gear to the power gear is used as m when the second estimation model is used to estimate the estimated total weight Driving device Is ensured by the parameter value of (a)The parameter value is accurate and reliable.
The third estimation model is:
in the formula (3), m is an estimated value of the whole vehicle weight, and the unit is kg; s is the running distance of the semi-trailer train from the estimated starting time to the estimated ending time, and the unit is m; g is the gravitational acceleration, e.g. set to 9.8m/s 2 ；h 1 For the first elevation of the geographical position of the semi-trailer train at the estimated starting moment, h 2 For estimating a second elevation of the geographical position of the semi-trailer train at the end time, v 1 For the first instantaneous speed, v, of the semi-trailer train at the estimated start time 2 And F is the instantaneous value of the sum of external forces born by the semi-trailer train, and the unit is N.
Wherein when the semi-trailer train is in a non-braking state,when the semi-trailer train is in a braking state, the brake is applied to the semi-trailer train>
Here, T is the engine or motor torque of the semi-trailer train, i is the transmission ratio of the transmission system of the semi-trailer train, η is the transmission efficiency of the transmission system, R is the wheel rolling radius of the semi-trailer train, f is the wheel rolling resistance coefficient of the semi-trailer train, C D The air resistance coefficient of the tractor is A, v is the windward area of the tractor, v is the instantaneous speed of the semi-trailer train, mu is the brake friction coefficient of the semi-trailer train, r is the brake equivalent friction radius of the semi-trailer train, S is the brake air chamber equivalent area of the semi-trailer train, and P1, P2 and Px are the semi-trailer trainFirst brake chamber pressure, second brake chamber pressure, and Xth brake chamber pressure.
Wherein the parameters T, i, eta, R, f, C D The parameter values of P1, P2 … Px can be obtained by signals provided by the chassis domain controller.
In this embodiment, the first estimation model only relates to the tractor, the fuel quality and the passenger quality, the estimation model is simple, the relative error of the estimation value is less than 1%, and the estimation accuracy is high. The vehicle weight estimation model corresponding to the third-party vehicle weight detection state uses the weighing value provided by the high-speed toll station window, the relative error of the estimation value is less than 1%, and the estimation accuracy is high. The second estimation model uses the weighing value of the axle load sensor, the relative error of the estimation value is 5%, and the estimation accuracy is acceptable in engineering. The third estimation model uses the law of conservation of energy to estimate, the relative error of the estimated value is less than 10%, and the estimation accuracy is acceptable in engineering.
As can be seen from fig. 3, the estimation logic of the method for estimating the train weight of the semi-trailer train according to the present embodiment preferably uses the first estimation model corresponding to the single tractor state, then uses the weight estimation model corresponding to the third party train weight detection state, then uses the second estimation model corresponding to the first sub-state of the dynamic train weight detection state, and finally uses the third estimation model corresponding to the second sub-state of the dynamic train weight detection state, thereby improving the accuracy of the estimated value of the train weight of the whole train.
When the weight estimation model comprises a first estimation model, a second estimation model and a third estimation model, determining a weight estimation model according to the current state information, and obtaining the weight of the whole vehicle of the semi-trailer train in the current state through the weight estimation model, wherein the method comprises the following steps:
and when the current state information of the semi-trailer train is the initial state, acquiring the whole train weight estimated value of the semi-trailer train from a preset storage area of the semi-trailer train.
When the current state information of the semi-trailer train is a single-tractor state, the passenger quality and the fuel quality are acquired, for example, the passenger quantity is acquired through a seat occupancy sensor, and the passenger quantity is based on the presetCan calculate the occupant mass m Human body And the fuel mass may be calculated from the remaining fuel volume provided by the fuel quantity sensor. And inputting the calculated passenger mass and fuel mass into a first estimation model, and obtaining the estimated value of the whole train weight of the semi-trailer train in the current state through the first estimation model.
When the current state information of the semi-trailer train is the third party weight detection state, the weight information detected by the third party is collected, and the high-speed toll station window is taken as an example, the vehicle needs to be weighed before entering the high speed, and the weighing information can be displayed in an electronic display screen of the high-speed toll station window. Based on this, the embodiment may scan the electronic display screen by using a vehicle-mounted camera (generally a panoramic camera or an autopilot camera in the left front), collect the weight information detected at the high-speed toll station by using the target recognition technology, and use the collected weight information as the estimated value of the whole weight of the semi-trailer train in the current state.
It will be appreciated that the vehicle weight information provided by the third party detection platform may also be acquired by other means, for example, when the third party detection platform provides a wireless data transmission interface, the vehicle weight information may be acquired through the wireless data transmission interface.
When the current state information of the semi-trailer train is the first sub-state, the weighing value of the axle load of the tractor driving axle provided by the axle load sensor is obtained, the weighing value of the axle load of the tractor driving axle is input into a second estimation model, and the whole vehicle weight estimated value of the semi-trailer train in the current state is obtained through the second estimation model.
Referring to fig. 3, when the single tractor state is switched to the first sub-state of the dynamic detection state of the vehicle weight and the initial state is switched to the first sub-state of the dynamic detection state of the vehicle weight, the weighing value of the axle load sensor at the moment when the semi-trailer train is switched from the non-power gear to the power gear is taken as m Driving device Is used for the parameter values of (a).
When the third party vehicle weight detection state is switched to the first sub-state of the vehicle weight dynamic detection state, the semitrailer hatch state can be detectedThe parameter is the weighing value of the axle load sensor at the moment of non-closing of the semitrailer hatch as m Driving device Is used for the parameter values of (a). In some alternative embodiments, the weighing value of the axle load sensor can be acquired as m according to the set frequency in a state that the semitrailer hatch is not closed as the semitrailer hatch state parameter Driving device For example, the weighing value of the axle load sensor is collected every 1 minute or 5 minutes as m Driving device And calculating the estimated value of the whole vehicle weight corresponding to each sampling point based on the second estimated model.
When the current state information of the semi-trailer train is in the second sub-state, acquiring a first elevation and a first instantaneous speed of the semi-trailer train at the estimated starting time in the second sub-state, acquiring a second elevation and a second instantaneous speed at the estimated ending time, acquiring an instantaneous value of the sum of external forces born by the semi-trailer train, inputting the instantaneous value of the sum of the external forces born by the semi-trailer train, the first elevation, the first instantaneous speed, the second elevation and the second instantaneous speed into a third estimation model, and acquiring the estimated value of the whole vehicle weight of the semi-trailer train in the current state through the third estimation model.
Here, the estimation start time may be a time when it is detected that the semitrailer hatch status parameter is not closed, or may be a status switching time when it is switched to the second sub-status by other status information, or may be a time set based on a preset policy, where the next estimation start time is obtained at regular intervals, for example, when the semitrailer train is in the second sub-status, with the status switching time as an initial estimation start time. The estimation end time and the estimation start time have a set time interval, and for example, the time 60s later than the estimation start time is taken as the estimation end time.
The method comprises the steps of obtaining a first elevation through a high-precision map at an estimation starting moment, obtaining a first instantaneous vehicle speed through a speed sensor by using other existing speed estimation methods, obtaining a second elevation through the high-precision map at an estimation ending moment, obtaining a second instantaneous vehicle speed, and obtaining a distance from the estimation starting moment to the estimation ending moment.
In addition, an instantaneous value F at each sampling point from the estimation starting time to the estimation ending time is obtained, the instantaneous value F is integrated through the equation (3), a partial differential equation is obtained by inputting the parameter value into the equation (3), and the partial differential equation is solved to obtain the whole train weight estimated value of the semi-trailer train.
In summary, the embodiment of the application can be seen that the method for estimating the train weight of the semi-trailer train adopts the scheme of acquiring and weighing the existing parameters, thereby avoiding the problem that the noise in the signals used by the existing whole-vehicle train weight estimation algorithm is relatively large and improving the estimation precision; the four vehicle weight estimation models are designed, and the problems that the convergence speed of the least square method or the Kalman filtering calculation result is too slow or even not converged are avoided; in addition, the third estimation model adopts an integral value of an instantaneous value of the sum of external forces born by the semi-trailer train on a section of running distance, and calculates the total mass of the semi-trailer train by combining an energy conservation law, so that adverse factors such as uneven pavement, acceleration hysteresis caused by elasticity of a transmission system and the like are eliminated, and the estimation precision is ensured.
The method of estimating the train weight of the semi-trailer in the embodiment of the present application belongs to a technical concept, and the embodiment of the present application further provides a device 500 for estimating the train weight of the semi-trailer, as shown in fig. 5, and provides a schematic structural diagram of the device 500 for estimating the train weight of the semi-trailer in the embodiment of the present application, where the device 500 includes: a data acquisition unit 510, a state determination unit 520, and a vehicle weight estimation unit 530, wherein:
the data acquisition unit 510 is configured to acquire previous state information of a semi-trailer train, and monitor a target state parameter of the semi-trailer train, where the semi-trailer train includes a tractor and a semitrailer;
a state determining unit 520, configured to determine current state information of the semi-trailer train according to the previous state information and the target state parameter;
and the weight estimation unit 530 is configured to determine a weight estimation model according to the current state information, and obtain an estimated total weight value of the semi-trailer train in the current state through the weight estimation model.
In one embodiment of the present application, the state determining unit 520 is configured to obtain a state switching condition corresponding to the previous state information; determining whether the semi-trailer train meets the state switching condition according to the target state parameter; and when the state switching condition is met, switching the state information of the semi-trailer train into the current state information meeting the state switching condition.
In one embodiment of the present application, the state information of the semi-trailer train at least includes an initial state, a single-tractor state, a third party weight detection state, and a weight dynamic detection state, the weight dynamic detection state includes a first sub-state and a second sub-state, and the target state parameters include at least a communication state parameter, a semi-trailer train position information, a semi-trailer connection state parameter, a semi-trailer hatch state parameter, a gear switching parameter, and a tractor driving wheel axle load validity parameter;
the state determining unit 520 includes a first state switching condition determining module, a second state switching condition determining module, a third state switching condition determining module, and a fourth state switching condition determining module;
the first state switching condition judging module is used for determining that the semi-trailer train meets the state switching condition of switching the initial state into the single-tractor state if the communication state parameter is that the communication is established successfully and the semi-trailer connection state parameter is that the semi-trailer is not connected when the previous state information is the initial state;
if the communication state parameter is that the communication is successfully established, the semitrailer connection state parameter is semitrailer connection, the semitrailer train position information is that the semitrailer train is located at a target geographic position, the semitrailer hatch is closed, and it is determined that the semitrailer train meets a state switching condition for switching an initial state into a third party train weight detection state;
If the communication state parameter is that the communication is successfully established, the semitrailer connection state parameter is semitrailer connection, the semitrailer train position information is that the semitrailer train is not located at the target geographic position, the semitrailer hatch state parameter is that the semitrailer hatch is closed, the tractor driving wheel axle load validity parameter is valid, the gear switching parameter is that the non-power gear is switched to the power gear, and it is determined that the semitrailer train meets the state switching condition that the initial state is switched to the first sub-state;
if the communication state parameter is that the communication is successfully established, the semitrailer connection state parameter is semitrailer connection, the semitrailer train position information is that the semitrailer train is not located at the target geographic position, the semitrailer hatch state parameter is that the semitrailer hatch is closed, the tractor driving wheel axle load validity parameter is invalid, and it is determined that the semitrailer train meets the state switching condition of switching the initial state into the second sub-state.
The second state switching condition judging module is used for determining that the semitrailer train meets the state switching condition of switching the single tractor state into a third-party vehicle weight detection state when the previous state information corresponds to the single tractor state and the semitrailer connection state parameter is semitrailer connection, the semitrailer train position information is that the semitrailer train is located at a target geographic position and the semitrailer hatch is closed;
If the semitrailer connection state parameter is semitrailer connection, the semitrailer train position information is that the semitrailer train is not located at the target geographic position, the semitrailer hatch state parameter is that the semitrailer hatch is closed, the tractor driving wheel axle load validity parameter is valid, and the gear switching parameter is a state switching condition for determining that the semitrailer train meets the condition of switching the single tractor state into the first sub-state when the non-power gear is switched to the power gear;
if the semitrailer connection state parameter is semitrailer connection, the semitrailer train position information is that the semitrailer train is not located at the target geographic position, the semitrailer hatch state parameter is that the semitrailer hatch is closed, the tractor driving wheel axle load validity parameter is invalid, and it is determined that the semitrailer train meets the state switching condition that the single tractor state is switched to the second sub-state.
The third state switching condition judging module is used for determining that the semitrailer train meets the state switching condition of switching the third-party vehicle weight detection state into a single-tractor state if the semitrailer connection state parameter is that the semitrailer is not connected when the previous state information corresponds to the third-party vehicle weight detection state;
If the semitrailer connection state parameter is semitrailer connection, the semitrailer train position information is that the semitrailer train is not located at the target geographic position, the semitrailer hatch state parameter is that the semitrailer hatch is not closed, the tractor driving wheel axle load validity parameter is valid, and it is determined that the semitrailer train meets a state switching condition for switching a third party train weight detection state into a first sub-state;
if the semitrailer connection state parameter is semitrailer connection, the semitrailer train position information is that the semitrailer train is not located at the target geographic position, the semitrailer hatch state parameter is that the semitrailer hatch is not closed, the tractor driving wheel axle load validity parameter is invalid, and it is determined that the semitrailer train meets a state switching condition that a third party train weight detection state is switched to a second sub-state.
A fourth state switching condition judging module, configured to determine, when the previous state information corresponds to a vehicle weight dynamic detection state, that the semi-trailer train satisfies a state switching condition for switching the vehicle weight dynamic detection state to a single-tractor state if the semi-trailer connection state parameter is that the semi-trailer is not connected;
And if the semitrailer connection state parameter is semitrailer connection, the semitrailer train position information is that the semitrailer train is located at the target geographic position, and the semitrailer hatch cover state parameter is that the semitrailer hatch cover is closed, so that the semitrailer train is determined to meet the state switching condition of switching the dynamic vehicle weight detection state into the third-party vehicle weight detection state.
In one embodiment of the present application, the weight estimation unit 530 is further configured to, when obtaining the estimated total weight value of the semi-trailer train in the current state through the weight estimation model, follow the estimated total weight value corresponding to the previous state information of the semi-trailer train before obtaining the estimated total weight value;
the apparatus 500 further includes a data storage unit, configured to store, before the semi-trailer train is in the sleep mode, the current estimated total weight value of the semi-trailer train into a preset storage area.
In one embodiment of the present application, the weight estimation model includes a first estimation model, a second estimation model, and a third estimation model, and the weight estimation unit 530 is specifically configured to obtain, when the current state information of the semi-trailer train is an initial state, an estimated total weight value of the semi-trailer train from a preset storage area of the semi-trailer train;
When the current state information of the semi-trailer train is a single-tractor state, acquiring passenger mass and fuel mass, inputting the passenger mass and the fuel mass into a first estimation model, and acquiring an estimated value of the whole vehicle weight of the semi-trailer train in the current state through the first estimation model;
when the current state information of the semi-trailer train is a third party weight detection state, collecting weight information detected by a third party, and taking the collected weight information as an estimated value of the whole weight of the semi-trailer train in the current state;
when the current state information of the semi-trailer train is in a first sub-state, acquiring a weighing value of the axle load of the tractor driving axle provided by an axle load sensor, inputting the weighing value of the axle load of the tractor driving axle into a second estimation model, and acquiring an estimated value of the whole vehicle weight of the semi-trailer train in the current state through the second estimation model;
when the current state information of the semi-trailer train is in a second sub-state, acquiring a first elevation and a first instantaneous speed of the semi-trailer train at an estimation starting moment in the second sub-state, acquiring a second elevation and a second instantaneous speed of the semi-trailer train at an estimation ending moment, acquiring an instantaneous value of the sum of external forces born by the semi-trailer train, and inputting the instantaneous value of the sum of the external forces born by the semi-trailer train, the first elevation, the first instantaneous speed, the second elevation and the second instantaneous speed into a third estimation model, and acquiring an estimated value of the whole vehicle weight of the semi-trailer train in the current state through the third estimation model;
Wherein the first estimation model is: m=m 1 ＝m Traction and pull +m Human body +m Oil (oil) ；
The second estimation model is:
the third estimation model is:
m is the estimated value of the weight of the whole vehicle, M 1 For the total mass of the tractor, m Traction and pull For preparing the tractor for quality, m Human body For passenger mass, m Oil (oil) Is the fuel quality, m Driving device The weight value of the axle load of the tractor driving axle is a horizontal distance from the center of mass of the tractor to the front axle of the tractor, b is a horizontal distance from the center of mass of the tractor to the rear supporting center of the tractor, c is a horizontal distance from the center of mass of the semitrailer to the rear supporting center of the tractor, d is a horizontal distance from the center of mass of the semitrailer to the rear supporting center of the semitrailer, s is a driving distance from the estimated starting moment to the estimated ending moment of the semitrailer train, g is a gravity acceleration, h 1 For the first elevation of the geographical position of the semi-trailer train at the estimated starting moment, h 2 For estimating a second elevation of the geographical position of the semi-trailer train at the end time, v 1 For the first instantaneous speed, v, of the semi-trailer train at the estimated start time 2 In order to estimate the second instantaneous speed of the half-trailer train at the end time, F is the instantaneous value of the sum of the external forces exerted on the half-trailer train, when the half-trailer train is in a non-braking state, When half hanging steamWhen the train is in a braking state +.>T is the torque of an engine or a motor of the semi-trailer train, i is the transmission ratio of a transmission system of the semi-trailer train, eta is the transmission efficiency of the transmission system, R is the wheel rolling radius of the semi-trailer train, f is the wheel rolling resistance coefficient of the semi-trailer train, and C D The method comprises the steps of taking an air resistance coefficient of a tractor as a windward area of the tractor, v as an instantaneous speed of the semi-trailer train, mu as a brake friction coefficient of the semi-trailer train, r as a brake equivalent friction radius of the semi-trailer train, S as a brake chamber equivalent area of the semi-trailer train, and P1, P2 and Px as a first brake chamber pressure, a second brake chamber pressure and an X brake chamber pressure of the semi-trailer train.
It can be understood that the above-mentioned device for estimating the train weight of the semi-trailer train can implement each step of the method for estimating the train weight of the semi-trailer train provided in the foregoing embodiment, and the explanation about the method for estimating the train weight of the semi-trailer train is applicable to the device for estimating the train weight of the semi-trailer train, which is not repeated herein.
Fig. 6 is a schematic structural view of an electronic device according to an embodiment of the present application. Referring to fig. 6, at the hardware level, the electronic device includes a processor, and optionally an internal bus, a network interface, and a memory. The Memory may include a Memory, such as a Random-Access Memory (RAM), and may further include a non-volatile Memory (non-volatile Memory), such as at least 1 disk Memory. Of course, the electronic device may also include hardware required for other services.
The processor, network interface, and memory may be interconnected by an internal bus, which may be an ISA (Industry Standard Architecture ) bus, a PCI (Peripheral Component Interconnect, peripheral component interconnect standard) bus, or EISA (Extended Industry Standard Architecture ) bus, among others. The buses may be classified as address buses, data buses, control buses, etc. For ease of illustration, only one bi-directional arrow is shown in FIG. 6, but not only one bus or type of bus.
And the memory is used for storing programs. In particular, the program may include program code including computer-operating instructions. The memory may include memory and non-volatile storage and provide instructions and data to the processor.
The processor reads the corresponding computer program from the nonvolatile memory to the memory and then operates the computer program to form the semi-trailer train weight estimating device on a logic level. The processor is used for executing the programs stored in the memory and is specifically used for executing the following operations:
acquiring last state information of a semi-trailer train, and monitoring target state parameters of the semi-trailer train, wherein the semi-trailer train comprises a tractor and a semi-trailer;
Determining current state information of the semi-trailer train according to the previous state information and the target state parameter;
and determining a vehicle weight estimation model according to the current state information, and obtaining the whole vehicle weight estimation value of the semi-trailer train in the current state through the vehicle weight estimation model.
The method executed by the semitrailer train weight estimation device disclosed in the embodiment of fig. 1 of the present application can be applied to a processor or implemented by the processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or by instructions in the form of software. The processor may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), etc.; but also digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be embodied directly in the execution of a hardware decoding processor, or in the execution of a combination of hardware and software modules in a decoding processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in a memory, and the processor reads the information in the memory and, in combination with its hardware, performs the steps of the above method.
The electronic device may also execute the method executed by the semitrailer train weight estimation device in fig. 1, and implement the function of the semitrailer train weight estimation device in the embodiment shown in fig. 1, which is not described herein.
The embodiment of the application also proposes a computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by an electronic device comprising a plurality of application programs, enable the electronic device to perform the method performed by the semi-trailer train weight estimation device in the embodiment shown in fig. 1, and is specifically configured to perform:
acquiring last state information of a semi-trailer train, and monitoring target state parameters of the semi-trailer train, wherein the semi-trailer train comprises a tractor and a semi-trailer;
determining current state information of the semi-trailer train according to the previous state information and the target state parameter;
and determining a vehicle weight estimation model according to the current state information, and obtaining the whole vehicle weight estimation value of the semi-trailer train in the current state through the vehicle weight estimation model.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and variations of the present application will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the application are to be included in the scope of the claims of the present application.
Claims (10)
1. A method of estimating the weight of a semi-trailer train, the semi-trailer train comprising a tractor and a semi-trailer, the method comprising:
acquiring the last state information of a semi-trailer train, and monitoring target state parameters of the semi-trailer train; the state information of the semi-trailer train at least comprises an initial state, a single-tractor state, a third-party vehicle weight detection state and a vehicle weight dynamic detection state, wherein the vehicle weight dynamic detection state comprises a first sub-state and a second sub-state; the target state parameters are parameters related to state information of switching the semi-trailer trains and at least comprise communication state parameters, semi-trailer train position information, semi-trailer connection state parameters, semi-trailer hatch cover state parameters, gear switching parameters and tractor driving wheel axle load validity parameters;
determining current state information of the semi-trailer train according to the previous state information and the target state parameter;
determining a vehicle weight estimation model according to the current state information, and obtaining an estimated value of the whole vehicle weight of the semi-trailer train in the current state through the vehicle weight estimation model;
the vehicle weight estimation model comprises a first estimation model, a second estimation model and a third estimation model, the vehicle weight estimation model is determined according to the current state information, and the vehicle weight of the semi-trailer train in the current state is obtained through the vehicle weight estimation model, and the vehicle weight estimation model comprises the following steps:
When the current state information of the semi-trailer train is an initial state, acquiring an estimated value of the whole train weight of the semi-trailer train from a preset storage area of the semi-trailer train;
when the current state information of the semi-trailer train is a single-tractor state, acquiring passenger mass and fuel mass, inputting the passenger mass and the fuel mass into a first estimation model, and acquiring an estimated value of the whole vehicle weight of the semi-trailer train in the current state through the first estimation model;
when the current state information of the semi-trailer train is a third party weight detection state, collecting weight information detected by a third party, and taking the collected weight information as an estimated value of the whole weight of the semi-trailer train in the current state;
when the current state information of the semi-trailer train is in a first sub-state, acquiring a weighing value of the axle load of the tractor driving axle provided by an axle load sensor, inputting the weighing value of the axle load of the tractor driving axle into a second estimation model, and acquiring an estimated value of the whole vehicle weight of the semi-trailer train in the current state through the second estimation model;
when the current state information of the semi-trailer train is in a second sub-state, acquiring a first elevation and a first instantaneous speed of the semi-trailer train at the estimated starting moment in the second sub-state, acquiring a second elevation and a second instantaneous speed of the semi-trailer train at the estimated ending moment, acquiring an instantaneous value of the sum of external forces born by the semi-trailer train, and inputting the instantaneous value of the sum of the external forces born by the semi-trailer train, the first elevation, the first instantaneous speed, the second elevation and the second instantaneous speed into a third estimation model, and acquiring an estimated value of the whole vehicle weight of the semi-trailer train in the current state through the third estimation model.
2. The method of claim 1, wherein determining current status information for the semi-trailer train based on the last status information and the target status parameter comprises:
acquiring a state switching condition corresponding to the previous state information;
determining whether the semi-trailer train meets the state switching condition according to the target state parameter;
and when the state switching condition is met, switching the state information of the semi-trailer train into the current state information meeting the state switching condition.
3. The method of claim 2, wherein,
if the previous state information corresponds to an initial state, the determining whether the semi-trailer train meets the state switching condition according to the target state parameter includes:
if the communication state parameter is that the communication is successfully established, the semitrailer connection state parameter is that the semitrailer is not connected, and it is determined that the semitrailer train meets a state switching condition for switching an initial state into a single-tractor state;
if the communication state parameter is that the communication is successfully established, the semitrailer connection state parameter is semitrailer connection, the semitrailer train position information is that the semitrailer train is located at a target geographic position, the semitrailer hatch is closed, and it is determined that the semitrailer train meets a state switching condition for switching an initial state into a third party train weight detection state;
If the communication state parameter is that the communication is successfully established, the semitrailer connection state parameter is semitrailer connection, the semitrailer train position information is that the semitrailer train is not located at the target geographic position, the semitrailer hatch state parameter is that the semitrailer hatch is closed, the tractor driving wheel axle load validity parameter is valid, the gear switching parameter is that the non-power gear is switched to the power gear, and it is determined that the semitrailer train meets the state switching condition that the initial state is switched to the first sub-state;
if the communication state parameter is that the communication is successfully established, the semitrailer connection state parameter is semitrailer connection, the semitrailer train position information is that the semitrailer train is not located at the target geographic position, the semitrailer hatch state parameter is that the semitrailer hatch is closed, the tractor driving wheel axle load validity parameter is invalid, and it is determined that the semitrailer train meets the state switching condition of switching the initial state into the second sub-state.
4. The method of claim 3, wherein if the last state information corresponds to a single tractor state, the determining whether the semi-trailer train satisfies the state switch condition based on the target state parameter comprises:
If the semitrailer connection state parameter is semitrailer connection, the semitrailer train position information is that the semitrailer train is located at a target geographic position, the semitrailer hatch state parameter is that the semitrailer hatch is closed, and it is determined that the semitrailer train meets a state switching condition for switching a single tractor state to a third-party train weight detection state;
if the semitrailer connection state parameter is semitrailer connection, the semitrailer train position information is that the semitrailer train is not located at the target geographic position, the semitrailer hatch state parameter is that the semitrailer hatch is closed, the tractor driving wheel axle load validity parameter is valid, and the gear switching parameter is a state switching condition for determining that the semitrailer train meets the condition of switching the single tractor state into the first sub-state when the non-power gear is switched to the power gear;
if the semitrailer connection state parameter is semitrailer connection, the semitrailer train position information is that the semitrailer train is not located at the target geographic position, the semitrailer hatch state parameter is that the semitrailer hatch is closed, the tractor driving wheel axle load validity parameter is invalid, and it is determined that the semitrailer train meets the state switching condition that the single tractor state is switched to the second sub-state.
5. The method of claim 3, wherein if the last state information corresponds to a third party weight detection state, the determining whether the semi-trailer train meets the state switch condition according to the target state parameter comprises:
if the semitrailer connection state parameter is that the semitrailer is not connected, determining that the semitrailer train meets a state switching condition for switching a third-party train weight detection state to a single-tractor state;
if the semitrailer connection state parameter is semitrailer connection, the semitrailer train position information is that the semitrailer train is not located at the target geographic position, the semitrailer hatch state parameter is that the semitrailer hatch is not closed, the tractor driving wheel axle load validity parameter is valid, and it is determined that the semitrailer train meets a state switching condition for switching a third party train weight detection state into a first sub-state;
if the semitrailer connection state parameter is semitrailer connection, the semitrailer train position information is that the semitrailer train is not located at the target geographic position, the semitrailer hatch state parameter is that the semitrailer hatch is not closed, the tractor driving wheel axle load validity parameter is invalid, and it is determined that the semitrailer train meets a state switching condition that a third party train weight detection state is switched to a second sub-state.
6. The method of claim 3, wherein if the last state information corresponds to a weight dynamic detection state, the determining whether the semi-trailer train satisfies the state switch condition according to the target state parameter comprises:
if the semitrailer connection state parameter is that the semitrailer is not connected, determining that the semitrailer train meets a state switching condition for switching the dynamic detection state of the train weight into a single-tractor state;
and if the semitrailer connection state parameter is semitrailer connection, the semitrailer train position information is that the semitrailer train is located at the target geographic position, and the semitrailer hatch cover state parameter is that the semitrailer hatch cover is closed, so that the semitrailer train is determined to meet the state switching condition of switching the dynamic vehicle weight detection state into the third-party vehicle weight detection state.
7. A method as claimed in claim 3, wherein the method further comprises:
when the whole vehicle weight estimated value of the semi-trailer train in the current state is obtained through a vehicle weight estimated model, before the whole vehicle weight estimated value is obtained, the whole vehicle weight estimated value corresponding to the last state information of the semi-trailer train is used;
Before the semi-trailer train is in the sleep mode, the current whole train weight estimated value of the semi-trailer train is stored into a preset storage area.
8. The method of claim 7, wherein,
the first estimation model is: m=m 1 ＝m Traction and pull +m Human body +m Oil (oil) ；
The second estimation model is:
the third estimation model is:
m is the estimated value of the weight of the whole vehicle, M 1 For the total mass of the tractor, m Traction and pull For preparing the tractor for quality, m Human body For passenger mass, m Oil (oil) Is the fuel quality, m Driving device The weight value of the axle load of the tractor driving axle is a horizontal distance from the center of mass of the tractor to the front axle of the tractor, b is a horizontal distance from the center of mass of the tractor to the rear supporting center of the tractor, c is a horizontal distance from the center of mass of the semitrailer to the rear supporting center of the tractor, d is a horizontal distance from the center of mass of the semitrailer to the rear supporting center of the semitrailer, s is a driving distance from the estimated starting moment to the estimated ending moment of the semitrailer train, g is a gravity acceleration, h 1 For the first elevation of the geographical position of the semi-trailer train at the estimated starting moment, h 2 For estimating a second elevation of the geographical location of the semi-trailer train at the end time，v 1 For the first instantaneous speed, v, of the semi-trailer train at the estimated start time 2 In order to estimate the second instantaneous speed of the half-trailer train at the end time, F is the instantaneous value of the sum of the external forces exerted on the half-trailer train, when the half-trailer train is in a non-braking state,when the semi-trailer train is in a braking state, the brake is applied to the semi-trailer train>T is the torque of an engine or a motor of the semi-trailer train, i is the transmission ratio of a transmission system of the semi-trailer train, eta is the transmission efficiency of the transmission system, R is the wheel rolling radius of the semi-trailer train, f is the wheel rolling resistance coefficient of the semi-trailer train, and C D The method comprises the steps of taking an air resistance coefficient of a tractor as a windward area of the tractor, v as an instantaneous speed of the semi-trailer train, mu as a brake friction coefficient of the semi-trailer train, r as a brake equivalent friction radius of the semi-trailer train, S as a brake chamber equivalent area of the semi-trailer train, and P1, P2 and Px as a first brake chamber pressure, a second brake chamber pressure and an X brake chamber pressure of the semi-trailer train.
9. A semitrailer train weight estimation apparatus, the semitrailer train comprising a tractor and a semitrailer, comprising:
The data acquisition unit is used for acquiring the last state information of the semi-trailer train and monitoring the target state parameters of the semi-trailer train; the state information of the semi-trailer train at least comprises an initial state, a single-tractor state, a third-party vehicle weight detection state and a vehicle weight dynamic detection state, wherein the vehicle weight dynamic detection state comprises a first sub-state and a second sub-state; the target state parameters are parameters related to state information of switching the semi-trailer trains and at least comprise communication state parameters, semi-trailer train position information, semi-trailer connection state parameters, semi-trailer hatch cover state parameters, gear switching parameters and tractor driving wheel axle load validity parameters;
the state determining unit is used for determining the current state information of the semi-trailer train according to the previous state information and the target state parameter;
the vehicle weight estimation unit is used for determining a vehicle weight estimation model according to the current state information, and obtaining an estimated value of the whole vehicle weight of the semi-trailer train in the current state through the vehicle weight estimation model; the vehicle weight estimation model comprises a first estimation model, a second estimation model and a third estimation model, and the vehicle weight estimation model is determined according to the current state information;
The vehicle weight estimation unit is specifically configured to obtain an estimated value of the entire vehicle weight of the semi-trailer train from a preset storage area of the semi-trailer train when the current state information of the semi-trailer train is an initial state; when the current state information of the semi-trailer train is a single-tractor state, acquiring passenger mass and fuel mass, inputting the passenger mass and the fuel mass into a first estimation model, and acquiring an estimated value of the whole vehicle weight of the semi-trailer train in the current state through the first estimation model; when the current state information of the semi-trailer train is a third party weight detection state, collecting weight information detected by a third party, and taking the collected weight information as an estimated value of the whole weight of the semi-trailer train in the current state; when the current state information of the semi-trailer train is in a first sub-state, acquiring a weighing value of the axle load of the tractor driving axle provided by an axle load sensor, inputting the weighing value of the axle load of the tractor driving axle into a second estimation model, and acquiring an estimated value of the whole vehicle weight of the semi-trailer train in the current state through the second estimation model; when the current state information of the semi-trailer train is in a second sub-state, acquiring a first elevation and a first instantaneous speed of the semi-trailer train at the estimated starting moment in the second sub-state, acquiring a second elevation and a second instantaneous speed of the semi-trailer train at the estimated ending moment, acquiring an instantaneous value of the sum of external forces born by the semi-trailer train, and inputting the instantaneous value of the sum of the external forces born by the semi-trailer train, the first elevation, the first instantaneous speed, the second elevation and the second instantaneous speed into a third estimation model, and acquiring an estimated value of the whole vehicle weight of the semi-trailer train in the current state through the third estimation model.
10. An electronic device, comprising:
a processor; and
a memory arranged to store computer executable instructions which when executed cause the processor to perform the semi-trailer train weight estimation method of any one of claims 1 to 8.
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